Bowdoin Science Journal

Chemistry and Biochemistry

LiNx: A Dual-Pronged Approach to Cancer Immunotherapy

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mRNA vaccines have emerged from the COVID-19 pandemic as a promising approach to fighting infectious diseases (Kutikuppala et al. 2024). Different from traditional vaccines, which use a weakened version of a virus, mRNA vaccines deliver an mRNA corresponding to a protein on the surface of the virus. This mRNA allows our immune system to recognize and make small parts of the virus so that it can create antibodies to combat it (Cleveland Clinic 2024). However, mRNA is an unstable and negatively charged molecule, so it must be encased with some type of transport protection to prevent its degradation during delivery (Kutikuppala et al. 2024).

Lipid nanoparticles, or LNPs, have gained popularity in recent years as an effective delivery platform for mRNA vaccines due to their highly tunable composition and their ability to prevent nucleic acid degradation (Xu et al., 2025). One popular example is the utilization of LNPs in the Moderna mRNA-1273 COVID vaccine, where mRNA encoding the protein on the outside of the virus that is recognized by the immune system was encapsulated in an LNP. Vaccination with this LNP-encapsulated mRNA resulted in 90% lower risk of contracting COVID within 21 days for those over the age of 16, demonstrating the power and possibility of this technology (Noor, 2021).

LNPs are extremely small particles composed of: 1) ionizable lipids, which act as a case for the nucleic acid being delivered; 2) phospholipids regulating cell membrane fusion; 3) PEG-lipids and 4) cholesterol which both affect its size and stability (Figure 1) (Xu et al., 2025). An LNP’s formulation can have substantial effects on its ability to avoid cellular barriers for vaccine mRNA entry to a targeted area. For example, degradation of LNPs by enzymes and/or other immune cells after entering the body can affect a vaccine’s ability to reach the targeted tissue (Hou et al., 2021). This is especially critical for scientists working on immunotherapies, as a variation in lipid composition can determine whether the LNP will be taken up by immune cells like dendritic cells or other antigen-presenting cells, which present the LNP to other immune cells and start the immune response (Hou et al., 2021). 

 

Figure showing the composition of LNPs. Phospholipid bilayer with cholesterol surrounds the LNP, which contains nucleic acid encapsulated within ionizable lipids
Figure 1. Composition of lipid nanoparticles. Adapted from 2025 Xu et al.

Hydrogels have also been utilized by scientists as vaccine carriers that can also augment immune responses. Hydrogels are natural or synthetic materials containing a 3D network of cross-linked polymer chains that allow them to absorb large amounts of a target substance (Ho et al. 2022). Depending on the composition of the hydrogel, scientists have found evidence of greatly increased immune cell recruitment and prolonged immune memory in mouse models of melanoma after a hydrogel-based vaccine was delivered (Kerr et al., 2023; Pal et al., 2024). In other words, the immune response was stronger and also more effective upon encountering a pathogen a second time. Therefore, if a hydrogel were to be used to deliver an LNP, finding the right composition is extremely important, as it can greatly impact its efficacy.

In their paper, Zhu et al. report the effectiveness of LiNx, a nanofiber-hydrogel composite (NHC) mRNA LNP matrix, in tumor and melanoma mouse models. Essentially, they embedded their LNPs within the 3D network of extremely small and cross-linked fibers in a hydrogel to significantly boost the immune response to cancer. 

LiNx works as a subcutaneous injection combining the potent immune activation capability of LNPs with the immunostimulatory microenvironment provided by the NHC. While the NHC recruits immune cells to the injection site and promotes immune cell signaling, the LNPs introduce nearby cells to the encapsulated mRNA, resulting in a coordinated adaptive immune response (Figure 2).

Diagram showing LiNx mechanism. It's delivered into the body, transfects non-APCs, enters an APC and is processed and presented through MHC1 or MHC2 pathways
Figure 2. Diagram of LiNx mechanism. (1) LiNx is delivered into the body and (2) transfects non-antigen-presenting cells. (3) The LNP enters an antigen-presenting cell, and the mRNA within is processed and presented through (4) two different pathways. Adapted from 2025 Zhu et al.

The lipid composition of LNPs can affect not only their size and stability, but also their transfection and delivery efficacy, or their ability to deliver the vaccine mRNA into host cells like dendritic cells (which start the immune response). To identify the top-performing LNP formulations, the researchers screened over one thousand different lipid compositions. Three top-performing LNP formulations were identified based on their transfection efficiency in bone marrow-derived dendritic cells: C10, D6, and F5. All of these formulations also separately activated powerful Th1 responses, a type of immune response meant to eliminate bacteria, viruses, and cancer cells, after three doses of subcutaneous injections.  

To simply quantify the host cell recruitment and transfection profile of the three different formulations, the researchers injected LiNx containing C10, D6, or F5 LNP into mice and measured the present immune cells 3 and 7 days post-injection. At both 3 and 7 days post-injection, a considerable amount of host cells were found in the NHC scaffold for all three formulations. The D6 formulation showed the greatest host cell recruitment, having a 12.6-fold increase compared to the control.

The researchers then performed a similar experiment, injecting mice with LiNx loaded with a test mRNA to get a better idea of the performance of each formulation compared to each other. They found that 10 days after injection, the D6 formulation contained over one-hundred-fold more transfected cells than C10 and F5-mRNA LiNx. Fourteen days post-injection, the D6-mRNA LiNx was also found to have recruited a more diverse range of immune cells associated with robust and specific immune responses like T cells and B cells. On the other hand, the C10 and F5-mRNA LiNx recruited more immune cells associated with general immune responses, like neutrophils. This shows that the D6-mRNA LiNx induces a stronger and more customized immune response. Additionally, three months post-vaccination, there were 10x more central memory T cells present in the spleens of D6-mRNA mice compared to the control and other formulations, indicating a stronger long-term memory response. These results suggest that the D6 LiNx is the most efficient LiNx formulation. 

Having characterized the immune activation induced by D6-mRNA LiNx, the researchers then tested its effectiveness in cancer mouse models. Mice were inoculated with colorectal cancer cells and received vaccinations of one of the LiNx formulations four days later. These mice were administered the vaccines in a single dose, while a separate control group received three doses of only D6 LNPs. The negative control group received only the NHC and protein without the LNP. The median survival time of the single-dose D6 LiNx mice was 75 days compared to 31 days for the negative control group and 37.5 days for the three-dose group, underscoring a heightened tumor suppression response. Fifty percent of these mice remained tumor-free after 100 days. This experiment demonstrated LiNx’s anti-cancer potential in vivo. 

In their paper, Zhu et al. demonstrated the effectiveness of a dual-modal approach to cancer immunotherapy. Through the combination of lipid nanoparticle mRNA delivery and a hydrogel microenvironment, they were able to induce a substantially stronger immune response characterized by tumor suppression and long-term immune memory in mouse models. The superior performance of a singular dose of D6 LiNx compared to three LNP doses illustrates the promise found in combining delivery methods with immune-boosting materials for the future development of stronger and longer-lasting cancer immunotherapies.

 

References:

Ho T-C et al. 2022. Hydrogels: Properties and Applications in Biomedicine. Molecules. 27(9):2902. 

Hou X, Zaks T, Langer R, Dong Y. 2021. Lipid nanoparticles for mRNA delivery. Nat Rev Mater. 6(12):1078–1094. 

Kerr MD et al. 2023. Biodegradable scaffolds for enhancing vaccine delivery. Bioeng Transl Med. 8(6):e10591. 

Kutikuppala LVS et al. 2024. Prospects and Challenges in Developing mRNA Vaccines for Infectious Diseases and Oncogenic Viruses. Med Sci (Basel). 12(2):28. 

mRNA Vaccines: What They Are & How They Work. 2024. Cleveland Clinic; [accessed 2026 May 2]. https://my.clevelandclinic.org/health/treatments/21898-mrna-vaccines

Noor R. 2021. Developmental Status of the Potential Vaccines for the Mitigation of the COVID-19 Pandemic and a Focus on the Effectiveness of the Pfizer-BioNTech and Moderna mRNA Vaccines. Curr Clin Microbiol Rep. 8(3):178–185. 

Pal S et al. 2024. Extracellular Matrix Scaffold-Assisted Tumor Vaccines Induce Tumor Regression and Long-Term Immune Memory. Adv Mater. 36(15):e2309843. 

Xu S et al. 2025. Lipid nanoparticles: Composition, formulation, and application. Mol Ther Methods Clin Dev. 33(2):101463. 

Zhu Y et al. 2025. An mRNA lipid nanoparticle-incorporated nanofiber-hydrogel composite for cancer immunotherapy. Nat Commun. 16(1):5707. 






Infant Development and The Social Sharing of Microbes

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The human digestive tract, which includes the mouth, esophagus, stomach, intestines, anus, and rectum, contains a highly diverse and complex community of microorganisms, known collectively as the gut microbiome. The gut microbiome forms during birth and rapidly evolves throughout infancy. This phase of development is absolutely crucial for the health of the immune system, metabolism, and long-term health outcomes, as it plays a large role in reducing the risk of allergies, diabetes, and many bowel and cardiovascular diseases (Borrego-Ruiz and Borrego, 2025). While it may be tempting to think that the sharing of microbes among infants is a bad thing, this is largely not the case. The microbes that are transmitted in a nursery and other similar environments are mainly non-pathogenic, meaning that they do not cause disease. Many of these microbes are actually beneficial for health, aiding in digestion, immune system development, and more. Typically, the development of the gut microbiome has been thought to be through vertical transmission, where microbes are passed from the mother or other close, immediate family contact, to infants. However, a recent study from Ricci et al. (2026) published in Nature suggests that gut microbiome development through simple vertical transmission serves as an incomplete model. Instead, they suggest that another key process is at play: horizontal transmission. This kind of transmission is the sharing of microbes between unrelated people. In infants, this often occurs in communal environments like nurseries.

Researchers Ricci and colleagues sought to investigate if infants obtained microbes just from their families, or if they acquired them from their peers, especially in a daycare setting. In the study, Ricci et al. analyzed how social interactions influence the human gut microbiome in infants by studying 43 infants in the UK between the ages of four and fifteen months, as well as their parents, siblings, caregivers, and even household pets. These authors analyzed DNA sequences obtained from samples of the stool of these infants over time to gather data about which microbes were present in their gut microbiomes. They analyzed several timepoints, including before and after nursery attendance began. This study design allowed the researchers to effectively track the transmission of microbes between individuals. The DNA sequencing approach taken by this group offered the advantages of more accurate, strain-level identification of microbes and allowed tracking of where certain microbes originated, because they analyzed entire DNA sequences. The alternative to this approach is culturing stool samples, which offers opportunity for additional testing but a severe limitation in that most microbes can not be cultured in a lab (Ricci et al., 2026).

Looking specifically in a daycare setting, the researchers discovered that infants experienced a significant increase in sharing of microbes, indicating that a nursery setting can play an important role in shaping the gut microbiome. This increase in transmission was seen at a much higher rate compared to settings within family-only units, where sharing was relatively stable. These findings indicate that horizontal transmission can be just as important as vertical transmission when it comes to developing and increasing biodiversity of the infant gut microbiome.

But how are microbes transmitted between infants in a nursery environment? It all comes down to proximity and activities. Researchers found increased microbial transmission between infants who spent more time together or had frequent physical contact compared to those that didn’t. Additionally, activities such as playing with the same toys and touching the same surfaces further facilitated microbe exchange. These findings show that exchange of microbes between infants in a nursery is not random, but rather a process that follows a pattern of behavior exhibited by the infants.

On top of understanding that microbial transmission occurs, the study highlighted the individual differences between infants and how they were affected by the conditions in the nursery. The researchers found that infants with siblings had more diverse microbiomes from the start of the study compared to those without, likely due to more microbe exposure at home from siblings. In turn, these infants acquired less new microbe strains, suggesting that previous microbe exposure can influence later development of the microbiome. This highlights the importance of being exposed to a diverse range of microbes as an infant, tying into the hygiene hypothesis, which states that without an early, diverse exposure to microbes, children are more likely to develop allergies and autoimmune diseases (Sironi and Clerici, 2010). Infants who had previously taken antibiotics, and therefore had a lack of diversity in their gut microbiome, experienced a recovery from being in a nursery environment. While the infants did recover fully, they recovered with a different composition of microbes. Through exposure to new strains around them, infants regained microbial diversity, highlighting the adaptability of the infant gut microbiome in the face of disruption. The findings of the study illustrate how the social environments of infants can be crucial in developing a gut microbiome that supports a healthy body.

This study also has its limitations. The number of nurseries was quite small, three to be exact, and researchers did not address the long-term presence of these microbes and their impact on health in the future. As such, because the infants were from a similar region, these findings may not be applicable to other populations who have different environmental and socioeconomic differences. Additionally, possible confounding variables such as diet and broader environmental conditions were not studied. Future research is needed to account for these limitations and progress the body of knowledge on infant horizontal transmission, as well as the microbial composition of infants who do not get placed in daycare or other social settings.

Overall, Ricci et al. (2026) challenge our current understanding of how the human gut microbiome develops. By looking beyond the process of vertical transmission, we learn that the microbiome is also influenced by social interaction, behaviors, and shared environments. Specifically, nursery settings are centers of important microbial exchanges, where infants are constantly exposed to new microbes. The results of this study emphasize that infant social interactions can biologically shape long-term health through development of the gut microbiome.

 

Works Cited

Borrego-Ruiz A, Borrego JJ. 2025. Early-life gut microbiome development and its potential long-term impact on health outcomes. Microbiome Res Rep. 4(2). doi:10.20517/mrr.2024.78. [accessed 2026 May 3]. https://www.oaepublish.com/articles/mrr.2024.78.

Ricci L, Heidrich V, Punčochář M, Armanini F, Ciciani M, Nabinejad A, Fazaeli F, Piperni E, Servais C, Pinto F, et al. 2026. Baby-to-baby strain transmission shapes the developing gut microbiome. Nature. 651(8104):191–200. doi:10.1038/s41586-025-09983-z. [accessed 2026 May 3]. https://www.nature.com/articles/s41586-025-09983-z.

Sironi M, Clerici M. 2010. The hygiene hypothesis: an evolutionary perspective. Microbes and Infection. 12(6):421–427. doi:10.1016/j.micinf.2010.02.002. [accessed 2026 May 3]. https://linkinghub.elsevier.com/retrieve/pii/S128645791000050X.



Venom As Medicine: Novel Pathways for Dravet Syndrome Treatment Using Modulatory Peptides from Scorpion Venom

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Dravet Syndrome (DS) is a form of pediatric epilepsy that produces prolonged seizures that cannot be prevented or stopped by available medications (Dravet Syndrome Foundation 2025). These seizures cause a wide range of severe health effects, ranging from cognitive impairment to infection and premature death (Dravet Syndrome Foundation 2025). Dravet syndrome is a disease that typically begins between 2 and 15 months of age and it affects 1:15,700 infants born (Dravet Syndrome Foundation 2025). While rare, this disease has a high mortality rate, with 15-20% of patients passing due to Sudden Unexpected Death in Epilepsy (SUDEP) (Dravet Syndrome Foundation 2025).

On the molecular level, DS is caused by a mutation in the SCN1A gene, which encodes a voltage gated sodium channel (Chow et al. 2019). This channel plays an important role in generating action potentials, which are the observable changes in cell voltage that conduct signals between nerves (Fig. 1). These electrical signals are transmitted by the movement of ions into and out of nerve cells, a transition that changes the charge of the cells. Typically, nerve cells have a resting potential of -70mV. When nerve cells reach the threshold potential, typically by allowing a small number of cations into the cell, the voltage gated sodium channels open, and a large number Na+ ions move into the cell, raising the voltage near +40mV. Once this new threshold is reached, the voltage gated sodium channels close and other channels open, allowing potassium ions to leave the cell. This removal of potassium from the cells drives the voltage back to a negative value. This process is vital to the correct transmission of electrical signals throughout the body to drive movement.

The mutation in the SCN1A gene alters the specific voltage-gated sodium channel 1.1 (Chow et al. 2019). Voltage-gated sodium channels are built from specifically folded proteins. In a normally functioning channel, there are two types of subunits: 1-2 β subunits and an ɑ subunit consisting of 4 distinct domains, or regions of the subunit (Chow et al. 2019). Each domain includes a voltage-sensing region, which detects alterations in cell voltage in order to signal for channel opening (Chow et al. 2019). A pore region is also present, which helps control the channel’s permeability (Chow et al. 2019). When SCN1A is mutated, several alterations to function can occur, including increased channel opening or channel mutations that prevent the influx of ions (Escayg and Goldin 2010). Unfortunately, even if only one copy of this gene is mutated, the functional copy is unable to overcome the deficit caused by the mutated gene, a principle known as haploinsufficiency.

Thus, new approaches are needed to control when this dysfunctional channel opens and closes. Venom peptides are a rich source of what are known as channel modulators (Chow et al. 2019). These short molecules, formed from the same molecular building blocks as larger proteins, can assume unique shapes. These folded conformations are stabilized by the presence of numerous cysteine residues, which can form strong disulfide bridges to “lock” a peptide in place. The CSɑβ fold describes one such disulfide bridge which forms between the beta sheets and alpha helix in the protein structure (Fig. 2). Venom peptides containing these folds can act as both alpha and beta toxins, with alpha toxins causing inhibition of channel inactivation and beta toxins causing direct activation. Chow et al. (2019) investigated two of these dual modulatory venom peptides, Hj1a and Hj2a, both found in scorpion venom.

The researchers studied the activation and inactivation of both of the venom peptides (Fig. 3). For Hj1a, the activation threshold increases, making activation harder, and the inactivation threshold decreases, also making inactivation easier (Chow et al. 2019). This change limits the range of functioning for the channels and thus increases its resistance to changes to voltage. This same pattern is seen for Hj2a, but to a lesser extent, as emphasized by the more limited distance between the blue and gray lines (Chow et al. 2019). The researchers then decided to explore the specificity of activation/inactivation using a technique known as patch/clamp electrophysiology. In this method, the researchers attach a small glass pipette to the membrane of a nerve cell and use this connection to pass signals through the nerve cell (Molecular Devices 2025). The researchers found that the inactivation was subtype specific, with Hj1a primarily impacting channels 1.4 and 1.5, and to a lesser extent, 1.1 and 1.6. Hj2a also showed favorability for channels 1.4 and 1.6, and to a lesser extent, channel 1.1 (Chow et al. 2019). Thus, while both have some impact on channel 1.1, the target channel for DS, they also impact other sodium channels, which could have adverse impacts.

These venom peptides are attractive drug candidates due to their stability and potency, but they lack what is known as subtype specificity (Chow et al. 2019). Essentially, they cannot reliably interact with the specific channel involved in DS without impacting the function of other biologically critical channels. This subtype specificity is one of the biggest features of antiepileptic drugs (AEDs). This, evidently, imposes a key problem in the use of Hj1a and Hj2a as AEDs. However, impacts on other channels may be ameliorated. Both Hj1a and Hj2a show agonistic activity on channels 1.4 and 1.5, which impact the smooth and skeletal muscle and the cardiac system respectively – these application sites are restricted to the peripheral nervous system, and impacts can be avoided by targeting the AED to the central nervous system (Chow et al. 2019). Channel 1.2 poses more problems as it is part of neuronal cells, thus pharmacological activation of this could cause similar symptoms to a gain-of-function mutation, including the early onset of severe epileptic encephalopathies (a disease that impacts the brain) (Chow et al. 2019). Since Hj2a does not affect channel 1.2, researchers are evaluating this peptide further and will need to conduct additional structural analyses.

Ultimately, while neither are truly effective AEDs for DS in their present form, venom peptides provide a basis for the investigation of dual modulatory scorpion peptides. Based on the study by Chow et al. (2019), there is a possibility that, with further modification and future study, venom peptides may be able to help ameliorate the symptoms of DS, which have resisted current treatment methods.

A graph showing the action potential curve and the molecular mechanisms which occur at different stages.
Figure 1. Action Potential Generation. The cell spends most of its time negatively charged, until the voltage gated sodium channels open.

 

An image showing the three dimensional protein structure of the peptide including showing two dimensional representation of the disulfide bridges.
Figure Two. The structure of the CSɑβ fold as it appears in the Hj1a and Hj2a scorpion peptides. The pink and blue lines represent key disulfide bridges, critical for maintaining structure.
(Adapted from Chow et al. 2019)

 

An image with two graphs showing the activation and inactivation effects of the two scorpion venom peptides.
Figure Three. Results of the subtype specificity experiments by Chow et al. (2020) showing increased voltage of channel activation and decreased voltage of channel inactivation. (Adapted from Chow et al. 2019)

References:

Dravet Syndrome Foundation: “What is Dravet Syndrome?”; no date [accessed December 15, 2025]. https://dravetfoundation.org/what-is-dravet-syndrome/.

Molecular Devices: “Patch Clamp Electrophysiology”; no date [accessed December 15, 2025]. https://www.moleculardevices.com/applications/patch-clamp-electrophysiology.

Chow, C. Y., et al. (2019). “Venom Peptides with Dual Modulatory Activity on the Voltage-Gated Sodium Channel NaV1.1 Provide Novel Leads for Development of Antiepileptic Drugs.” ACS Pharmacology & Translational Science 3(1): 119-134.

Escayg, Andrew, and Alan L Goldin. “Sodium channel SCN1A and epilepsy: mutations and mechanisms.” Epilepsia vol. 51,9 (2010): 1650-8.

The Science of When You Exercise

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People often think the most important aspect of how exercise affects your overall health is how hard you work, how much weight you can lift, or how far you can run. However, two recent studies have uncovered another factor that might be just as important for maximizing health benefits – when you exercise. Multiple studies have looked at the impact of how when you exercise affects your body. For example, one study looked at the impact of exercise timing in mice, focusing on the growth of muscle tissue, while another study looked at a large population of people and how their exercise habits affected sleep quality. Together, these studies show that when exercise takes place matters more than most people believe.

The first study, done by Liu et al. and published in Nature Communications, looked at how timing of exercise in mice affected long-term health (Liu et al., 2025). Mice, like people, have a circadian rhythm, which is a 24-hour internal clock in the body that regulates and affects energy, metabolism, and sleep. Muscles in the body also have internal clocks, which decide when to burn fat or sugar.

In the study, Liu et al. had two groups of mice run at a low intensity and low volume on treadmills at different times of day: one group exercised before sleep and the other exercised right after waking up. Training lasted for several months, and researchers measured the mice’s body weight throughout the study and measured the mice’s strength, endurance, and blood sugar before and after the study was conducted, all of which are indicators of long-term exercise results. The results of the study were quite clear. Mice who exercised before sleep showed increased physical and metabolic improvements after the period of consistent exercise, meaning they gained less fat, had more endurance, and showed better blood sugar control. The group of mice that exercised after waking saw less improvement in these areas (Liu et al., 2025).

The second study, done by Leota et al. and also published in Nature Communications, tracked the health data of over 14,000 human participants using fitness wearables over four million nights of sleep (Leota et al., 2025). The researchers wanted to see whether exercising in the evening, before bedtime, affected sleep quality.

The researchers found that the later and harder people worked out, the more their sleep was affected. When people exercised four or more hours before going to bed, their sleep was normal, regardless of the intensity of the workout. When people exercised two to four hours before going to bed, they took a longer time to fall asleep and slept less. When people exercised two hours or less before going to bed, especially at a high intensity, sleep noticeably got worse. Some took up to over an hour longer to fall asleep, slept about 40 minutes less overall, and had a higher heart rate throughout the night (Leota et al., 2025).

Although the mice study found that exercise before bed improved overall health, the human study found that the closer exercise got to bedtime, the worse sleep became, which is also known to negatively impact recovery and overall health. While these studies may seem contradictory, they actually align upon consideration of the factor of exercise intensity. High-intensity training in the evening negatively affects sleep, while low/moderate-intensity exercise in the evening is beneficial for muscle growth and recovery without impacting sleep.

Although both studies were different, they arrived at the same key conclusion: that the body works best when its internal cycles, like its circadian rhythm, are not disrupted. Exercise, such as heavy lifting or sprinting, activates the body’s sympathetic nervous system, which is the part of the nervous system responsible for the “fight or flight” response. Sleep, along with recovery, lowered heart rate, and relaxation, is activated by the parasympathetic nervous system, otherwise known as the “rest and digest” state. While the activation of the sympathetic nervous system is good for exercise and performance, it is not good when the body needs to sleep. Instead of letting the body settle down, activation of the sympathetic nervous system keeps your body revved up, lessening sleep time and quality, and therefore overall recovery and future performance.

Because of the busyness of daily life, it’s not always possible to perfectly time every workout. Evening workouts are often unavoidable due to the realities of many people’s daily schedules. However, the combination of results from these studies shows that evening workouts aren’t automatically bad for overall health. In fact, they can even improve the benefits of exercise as long as their intensities are adjusted according to their relation to bedtime. If working out in the evening more than four hours before bedtime, high-intensity exercise can take place without risk of impacting sleep quality and physical health. If working out four hours or less before bedtime, it is better to opt for lower-intensity exercise, which will allow you to sleep better and recover more quickly. In the end, both studies show that being slightly more intentional about when and how hard you train can make a real difference in your sleep, recovery, and overall performance.

 

Works Cited

Liu, J., Xiao, F., Choubey, A., Kumar S, U., Wang, Y., Hong, S., Yang, T., Otlu, H. G., Oturmaz, E. S., Loro, E., Sun, Y., Saha, P., Khurana, T. S., Chen, L., Hou, X., & Sun, Z. (2025). Muscle Rev-erb controls time-dependent adaptations to chronic exercise in mice. Nature Communications, 16(1), 5708. https://doi.org/10.1038/s41467-025-60520-y

Leota, J., Presby, D. M., Le, F., Czeisler, M. É., Mascaro, L., Capodilupo, E. R., Wiley, J. F., Drummond, S. P. A., Rajaratnam, S. M. W., & Facer-Childs, E. R. (2025). Dose-response relationship between evening exercise and sleep. Nature Communications, 16(1), 3297. https://doi.org/10.1038/s41467-025-58271-x

Co-pyrolysis of Biomass and RDF for Waste to Energy Conversion

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One of the primary concerns regarding fossil fuels today is not only their massive environmental impact but their persistent dominance in the energy field. Growing waste, pollution and energy consumption and demand all prompt the search for alternative, renewable energy sources, for example, biomass. Biomass waste includes agricultural residues, such as crops, crop residues, animal waste, and food scraps. All of these can be thermochemically converted into fuel, chemicals, and other biobased materials for various applications, simultaneously reducing the amount of waste going into landfills. Biomasses are also widely available, have high moisture and volatile matter content, presence of alkali metals in ash, and display a wide range of different physical and chemical properties.  

Refuse Derived Fuel (RDF) is another example of waste with high energy potential. RDF is mainly composed of plastic waste, paper, textiles, and wood, containing high organic matter content, giving it a high calorific value. RDF is a fuel produced from municipal solid waste that has been processed to remove non-combustible materials, like metals, glass, and other inorganic materials, leading to relatively stable chemical properties and low moisture content. In return, this gives it a high energy potential. RDF also has a higher energy content than raw municipal solid waste, making it a more efficient fuel source. It can be easily transported and stored, making it a convenient fuel source for energy generation in the cement industry or in energy plants. However, the direct combustion of RDF can be potentially unsafe, causing the emission of hazardous substances.  

 Magdziarz et al., 2024 examines the co-conversion of biomass and RDF, specifically through a process called pyrolysis. Pyrolysis is a thermochemical conversion process carried out in an oxygen-free atmosphere (typically in nitrogen or argon) at a temperature above 300–400 ◦C. This leads to the production of three main products: syngas, pyro-oil (liquid or “bio-oil”), and pyro-char (solid or “bio-char”). The distribution of product yields depends directly on the conditions of the process (operational parameters) including the temperature, heating rate, residence time of the volatiles, the particle size of the feedstock, type of feedstock or biomass, etc. The syngas may be useful in generating heat and electricity, while the solid bio-char may be useful as a soil applicant, aiding in carbon sequestration, water retention, and nutrient availability. However, the main focus of this study was to improve the quality and quantity of produced bio-oil, which can be used as a renewable alternative to fossil fuels.  

Co-pyrolysis of biomass and RDF was considered a “good solution”, as it helps reduce deposited waste and improves the quality of bio-oil produced by overcoming some of the challenges associated with the pyrolysis of biomass alone, such as poor bio-oil quality due to the presence of impurities. Additionally, the process supports the development of circular economy principles by reducing the dependence of fossil fuel resources. Previous studies focused on co-pyrolysis of biomass and plastics as opposed to RDF and found that minimizing the concentration of complex liquid compounds and heavy hydrocarbons improved the quality of syngas and liquid products. The addition of catalysts further improved bio-oil quality by increasing the content of hydrocarbons and reducing the content of oxygenated compounds in bio-oil. Pyrolysis of pure RDF can be problematic due to the formation of tar, wax, and other volatile organic compounds, causing equipment damage, reducing product quality, and increasing emissions.  

Additionally, Magdziarz et al., 2024 investigated two agricultural biomass feedstocks, rye straw (RS) and agriculture grass (AG), along with RDF, mainly composed of plastics. The pyrolysis process was conducted at 600 ◦C under a nitrogen atmosphere with a mass sample of 1 gram and residence time of 3 minutes. First, the pyrolysis of raw feedstocks was conducted to collect and analyze the properties of solid, liquid, and gas products. Then, co-pyrolysis experiments were conducted to investigate the impact of RDF addition on the properties of products with mixtures of 75:25 and 50:50 weight-percentage ratios (biomass to RDF mass ratio). Respectively, the samples were named: 75RS-25RDF, 75AG-25RDF, 50RS-50RDF, and 50AG-50RDF. RS and AG have similar physical and chemical properties, but AG contains a higher ash content and, consequently, lower volatile matter. Ash content and volatile matter both can influence the yield of products, as ash can catalyze undesirable secondary reactions (char oxidation or tar formation), reducing bio-oil yield, and higher volatile matter content generally correlates with the higher yield of gaseous products. The study analyzed the composition of volatile matter released during the pyrolysis process for both feedstocks and for the mixtures of biomass and RDF.  

In the case of the RDF sample, there were over 300 chemical compounds, while the biomass samples released about half as many chemical compounds. Therefore, the released analytes, especially forRDF, may be considered highly complex mixtures composed of compounds with different volatility.

Atomic Share for Biomass Samples by Percentage

For RS and AG as seen in the table above, the main group of compounds were oxygen compounds. Meanwhile, for RDF, hydrocarbons were the dominant volatile products, and the very low oxygen content for RDF (<2.85 weight%) resulted in a negligible CO2 content, unlike the biomass samples. For the four mixtures of biomass and RDF (75RS-25RDF, 75AG-25RDF, 50RS-50RDF, and 50AG-50RDF), the percentages of the groups of volatile compounds released were compared to the values estimated based on the linear model.


Atomic Share for Varying Mixtures of Biomass Samples by Percentage

In all four samples, the hydrocarbons and their oxygen derivatives were the dominant group of compounds released during co-pyrolysis. The release of hydrocarbons is arguably beneficial for increasing the application potential of volatile pyrolysis products that can be a type of alternative fuel. Hydrocarbons can enhance the energy value of the fuel and after additional treatment, can be used as by-products to value-added materials. The study also noted that the observed share of hydrocarbons released during pyrolysis was significantly higher than calculated from the linear model, which correlated with the addition of RDF to the biomass samples. The increased percentage of hydrocarbons also correlated with a simultaneous decrease in the relative share of other groups of compounds, especially oxygen compounds, as well as significantly lower CO2 content than expected from the linear model’s calculation.  

Yields of Bio-char and Bio-oil for Varying Mixtures of Biomass Samples

The yields of the bio-char and bio-oil phases are presented in Figure 5 above. The char yield for AG was higher (27.3%) than for RS (21.2%). The addition of 50% RDF to biomass decreased the char yields to 16.2% and 13.2%, respectively. Bio-oil yield was higher for RS (35.9%) than for AG (29.9%). Results from previous studies also show higher bio-oil yields and lower bio-char yields as RDF percentage increased. As predicted, co-pyrolysis of RDF with biomass gave a better synergetic effect for RS than for AG with the RS samples producing a higher ratio of bio-oil than the AG samples.The gas yield was calculated by the formula, 100% – char yield – liquid yield, and the pure RS and AG samples had similar gas yields at around 40%. The presence of RDF did not significantly influence gas yield for AG, but for RS (50RS-50RDF) decreased the yield by 13%. Gas yields consisted mainly of CO, CO2, H2, and CH4. The calorific value of gas from RS pyrolysis was higher than for AG. The addition of RDF for both biomasses (50RS-50RDF and 50AG-50RDF) decreased the content of CO and H2 and simultaneously increased the amount of CO2 and CH4 product. However, the study mentions that the gas yields from co-pyrolysis were not a concern, as the main goal was to obtain bio-oil. 

The main conclusions for the study were that for mixtures of biomass and RDF the content of oxygen in volatiles was significantly reduced, while the content of hydrocarbons was increased, and co-pyrolysis of biomass and RDF confirmed the benefits of RDF addition, which positively influenced product yields and quality. The co-pyrolysis of the AG and RS (waste materials) with RDF offers another method to contribute to circular economics and sustainable waste management. Co-pyrolysis of biomass and RDF may potentially be effective ways to convert waste into energy and produce useful bio-char, bio-oil, and even various gaseous products. Future studies should focus on the type of feedstock used and various parameters of the pyrolysis process to ensure that the process is as efficient, sustainable, and environmentally friendly as possible.  

 

References

Magdziarz, A., Jerzak, W., Wądrzyk, M., & Sieradzka, M. (2024). Benefits from co-pyrolysis of biomass and refuse derived fuel for biofuels production: Experimental investigations. Renewable Energy, 230, 120808. https://doi.org/10.1016/j.renene.2024.120808

MMOF Hydrogels: A New Tool in Aquatic Dye Removal

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Every year, over 280,000 tons of synthetic dyes are introduced into aquatic environments as wastage from textile mills. This significant amount of runoff accounts for the augmentation of environmental contamination in several countries, including China, and can have detrimental effects on aquatic life. For example, decreased red blood cell count has been observed in mosquitofish, and liver degeneration in Mozambique tilapia (Dutta et al. 2024).

Previous studies have attempted to use polyacrylamide hydrogels to selectively remove contaminants from an environment. However, the process of creating these hydrogels was found to be too complex and therefore impractical for real-world applications (He et al. 2021). Cheng et al. describe a sodium alginate hydrogel with increased selectivity to a pollutant, malachite green (MG) dye, and heightened adsorptive properties through enhancement with magnetic and MOF materials. 

Metal-organic frameworks, or MOFs, are a class of crystalline materials that are made up of a metal ion or cluster and organic linkers. They are extremely porous (~90% free volume) and have extremely high internal surface areas (beyond 6000m^2/g) (Zhou, Long, Yaghi. 2012). These properties, along with the adjustability of their composition, have made MOFs of interest for applications as high-capacity adsorbents for pollutants.

To create their MOF, the researchers dissolved two metal solids, FeCl3·6H2O & FeCl2·4H2O, in water and ethanol, centrifuged, and collected Fe3O4 nanoparticles. They then added another hydrated metal, ZrOCl2·8H2O, and TCPP (the organic linker) to the solution, washed with DMF solvent to dissolve the metals and linkers, and obtained their MOF: Fe3O4@MOF-545 with an average particle size of 1100nm.

Structure of a Zr-based MOF-545
Figure 1. Zr-based MOF-545. Adapted from 2024 Chen et al.

 

Next, they created a solution of their MOF, 4.2% sodium alginate, TEMED, and acrylamide to form the polyacrylamide hydrogel. The resulting solution was added drop-by-drop to a CaCl2 solution to form microspheres and stirred magnetically for an hour to obtain the MMOF hydrogel (magnetic MOF hydrogel). The researchers used scanning electron microscopy to characterize the MMOF hydrogel and found that the MMOF hydrogel had a microporous structure and clear surface grooves, enhancing its surface area and adsorptive capacity. (Figure 2)

Scanning electron microscopy of the MMOF hydrogel. The surface grooves and external and internal porous structure are visible.
Figure 2. (A) SEM image of MMOF hydrogel. (B-C) Notable grooves are seen on the surface of the MMOF hydrogel. Adapted from 2025 Cheng et al.

To confirm the heightened performance of the MMOF hydrogel, the researchers compared its dye adsorption and selectivity for MG dye compared to a magnetic hydrogel and a pure hydrogel.  The resulting MMOF hydrogel was found to be a significantly more effective adsorptive agent for MG dye than the other types of hydrogels (Figure 3), further showing the effectiveness of MOFs in increasing adsorption. The MMOF hydrogel also displayed enhanced selectivity to MG dye when applied to the surface of aquatic tissues in situ (Figure 4). 

 

Picture of hydrogel, MOF hydrogel, and MMOF hydrogel placed in solution containing MG dye. The container with MMOF hydrogel is the only one that became clear with no blue color left over, showing the higher adsorption rate of the MMOF hydrogel. The graph to the right of the image further supports this as MMOF hydrogel adsorption rate is over 90%.
Figure 3. Adsorption rate of MMOF hydrogel compared to magnetic hydrogel and hydrogel. MMOF hydrogel displayed greater MG dye adsorption than the magnetic hydrogel and hydrogel. Adapted from 2025 Cheng et al.

 

MMOF hydrogels placed on fish tissue with MG and other dyes on the surface. The hydrogels fully remove the MG dye.
Figure 4. MMOF hydrogel selectivity tested through application of fish tissue containing MG, acridine yellow, methylene blue, carmine, and crystal violet dyes. MMOF hydrogel shown to selectively remove MG dye from environment when in proximity to other dyes. Adapted from 2025 Cheng et al.

Cheng et al. then tested MMOF hydrogels with different characteristics to find material and environmental conditions for optimal adsorption. They found that sodium alginate concentration and MOF:hydrogel weight ratio were associated with the adsorptive capacity of the MMOF hydrogels. The optimal sodium alginate concentration was found to be 4.2%, and the optimal MOF:hydrogel weight ratio was found to be 12.

The researchers also tested the MMOF hydrogel in different environmental conditions to determine its limitations and where it performed best. They observed that the MMOF hydrogels showed the greatest adsorption at an MG dye concentration of 100mg/L (Figure 5A). This is due to the increased competition of MG molecules for adsorption sites on the surface of the MMOF hydrogel at higher concentrations. They also found that adsorption plateaued at MMOF hydrogel weight concentrations higher than 20mg/mL (Figure 5B) due to the adsorption sites on the hydrogel reaching equilibrium. Additionally, adsorption was highest at an MG solution pH of 6 (Figure 5C). At lower pH, H+ ions would compete with MG by due to the negatively charged functional group on the MMOF hydrogel. At higher pH, the carboxyl group on the MMOF hydrogel is ionized, decreasing the adsorption rate of MG dye. The adsorption rate of MG dye by the MMOF hydrogel was also found to show little decrease after 25 days of storage at 60ºC, indicating the strong stability of the material. 

Image containing Graphs A, B, C.A: Conc. vs adsorption rate. Adsorption rate peaks at conc of 100mg/L B: MMOF hydrogel weight concentration vs adsorption rate. adsorption rate peaks at 20mg/ml C: pH vs adsorption rate. Adsorption rate peaks at pH 6.
Figure 5. (A) MMOF hydrogel MG dye adsorption rate peaked at MG concentration of 100 mg/L. (B) Adsorption remains almost the same at MMOF hydrogel weight concentrations of 20mg/L and higher. (C) When the concentration of the MG solution is 100 mg/mL, the pH of the MG solution alters the adsorptive capacity of the MMOF hydrogel with the highest adsorption being observed at pH 6. Adapted from 2025 Cheng et al.

In their work, Cheng et al. have successfully created stable and easy-to-replicate MMOF hydrogels showing high adsorptive capacity and selectivity to MG dye for aquatic tissue in situ. The easily modifiable structure of MOFS also opens the door to the production of MMOF hydrogels selective to other dyes as well. This research has great potential applications for the pretreatment of aquatic products like fish before they reach the market. If automated and integrated into the screening processes of aquatic products, these MMOF hydrogels could strengthen quality control and increase the safety of products that are entering the market.

 

References

Chen, H., Brubach, J.-B., Tran, N.-H., Robinson, A. L., Ferdaous Ben Romdhane, Mathieu Frégnaux, Francesc Penas-Hidalgo, Solé-Daura, A., Mialane, P., Fontecave, M., Dolbecq, A., & Mellot-Draznieks, C. (2024). Zr-Based MOF-545 Metal–Organic Framework Loaded with Highly Dispersed Small Size Ni Nanoparticles for CO2 Methanation. ACS Applied Materials & Interfaces, 16(10), 12509–12520. https://doi.org/10.1021/acsami.3c18154

Cheng, L., Lu, Y., Li, P., Sun, B., & Wu, L. (2025). Metal–Organic Framework (MOF)-Embedded Magnetic Polysaccharide Hydrogel Beads as Efficient Adsorbents for Malachite Green Removal. Molecules, 30(7), 1560–1560. https://doi.org/10.3390/molecules30071560‌

Dutta, S., Adhikary, S., Bhattacharya, S., Roy, D., Chatterjee, S., Chakraborty, A., Banerjee, D., Ganguly, A., Nanda, S., & Rajak, P. (2024). Contamination of textile dyes in aquatic environment: Adverse impacts on aquatic ecosystem and human health, and its management using bioremediation. Journal of Environmental Management, 353(120103), 120103. https://doi.org/10.1016/j.jenvman.2024.120103‌

Zhou, H.-C., Long, J. R., & Yaghi, O. M. (2012). Introduction to Metal–Organic Frameworks. Chemical Reviews, 112(2), 673–674. https://doi.org/10.1021/cr300014x










Floating Systems: Jellyfish and Evolving Nervous Systems

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Jellyfish are just one species within the phylum cnidaria. A phylum is a broad level of taxonomic classification that includes many different species, with cnidaria additionally including coral and anemones. Cnidaria provides comparative neuroscience information due to the simple behaviors that the species within the phylum exhibit. Despite their shared phylum that creates nerve cells with similar properties, the species have dramatically different nervous systems, allowing for unique perspectives on the diversity, origins, and evolution of neural systems within species (Cunningham et al., 2024). Comparative neuroscience information is the study of nervous systems across a variety of animal species. Through this research, the evolutionary changes in the brain’s structure can be examined, allowing scientists to see how differences in nervous systems shape certain behaviors (Miller et al., 2019). Neuroscience researchers can use an all-optical interrogation, in which they study and manipulate neural systems using light, upon these species, allowing them to image and photograph the neuronal networks in the creature for further examination. 

Fig 1. Photo of Clytia hemisphaerica (Clytia Hemisphaerica Medusa – 13673149 ❘ Science Photo Library, n.d.)

Jellyfish are major contributors to ocean ecosystems. Their reproductive, foraging, and defensive behaviors all uniquely impact the ecosystem at large. What is notable about jellyfish, however, is that these behaviors are shaped out of decentralized, regenerative nervous systems. Rather than the creature being controlled by the neurons in its brain, the jellyfish’s neurons are spread throughout the body (“Thinking without a Centralized Brain,” n.d.). This allows the various parts of its body to have a role in controlling and processing information. Additionally, the nervous system itself has the ability to repair and restore itself, allowing damaged nerves to be replaced by new ones (Gaskill, 2018). 

Jellyfish are the most complicated species of Cnidaria, due to various behaviors that demonstrate their higher level functioning compared to other species in the phylum. They have the ability to move in 3-dimensions, capture and consume other creatures, and the ability to escape from predators and other potential threats. Notably, jellyfish also exhibit courtship behaviors and sleep states, despite lacking a central brain. These behaviors are  due to their sensory structures, made up by two nervous systems: one which controls their swimming and another that controls all other behaviors. The jellyfish’s nervous systems can respond to each other, despite the lack of a central controller (Cunningham et al., 2024). 

A recent scientific investigation conducted at Caltech by Anderson et al. sought to explore how the jellyfish can be used to conduct neuroscience research. Clytia hemisphaerica is a species of jellyfish that has recently been adopted into a genetic neuroscience model. It has previously been used as a model to study evolution, embryology, regeneration, and other fields. This species of jellyfish is a particularly useful model for neuroscience research because its genome is already sequenced and assembled from the birth of the creature, with whole-animal single-celled Ribonucleic Acid (RNA) sequences formed within the species. Rather than using multiple animals to sequence the RNA, Clytia hemisphaerica has the capability to provide the necessary amounts of cells needed to be examined. Using multiplexed single-cell RNA sequencing, in which individual animals were indexed and pooled from control and perturbation conditions into a single sequencing run (Chari et al., 2021). Clytia hemisphaerica is the only jellyfish whose RNA sequences are being used to rapidly develop genomic tools. These tools can be tested and utilized by researchers, allowing them to explore brain function and neurological disorders through this model (Cunningham et al., 2024).

The last common ancestor of Clytia hemisphaerica was a hydrozoan jellyfish, which are able to perform specific behaviors even if certain body parts are detached from the body. Hydrozoan jellyfish, notably, have the ability to cycle back and forth between various stages of their life–allowing them to live for large expanses of time. When the body parts exist in an intact organism, they also have the ability to perform more complex behaviors. These include different feeding behaviors and mechanisms. The swimming behavior of the Clytia hemisphaerica also reveals key information about the neuromechanics behind different behaviors of jellyfish. As an example, although jellyfish spend a majority of their lives swimming, there are periods where they may start and stop. These periods are only exhibited when there is food passing or defensive behaviors are exhibited. When these behaviors are examined, neuroscientists can ponder and develop further conclusions about multi-sensory integration, motor control, and the mechanisms that underlie behavioral states (Cunningham et al., 2024). Figure 1

Fig 2. The Evolution, Life Cycle, and Genetic Tools of Clytia hemisphaerica (Cunningham et al., 2024)

Through using neural population imaging, in which researchers have the ability to monitor large groups of neurons through calcium and voltage imaging, on the whole-organism scale through the Clytia hemisphaerica, emergent properties of function networks can be uncovered (Zhu et al., 2022). Without this model, scientists would have to use traditional single-cell unit recordings, requiring using fine tools just to see the individual activity of a single neutron, or anatomical studies, which would not provide the same amount of potential discoveries that new techniques with Clytia hemisphaerica provide. Through using this species as a model, researchers can uncover more knowledge and data about nervous system evolution and function, particularly for neural regeneration.

Neural regeneration is particularly important in the treatment of injury and disease in the nervous system. It aids in cognitive recovery following neurodegeneration, helping rebuild neurons and nervous tissue (Steward et al., 2013). Through neural regeneration, the nervous system may regain its functions, allowing for betterment of quality of life. By continuing to examine species capable of neural regeneration, we may learn to apply this to the human nervous system, allowing us to move forward in curing traumatic brain injuries and degeneration of the brain and its abilities (Neuroregeneration – an Overview | Sciencedirect Topics, n.d.).

 

 

 

 

 

References:

Chari, T., Weissbourd, B., Gehring, J., Ferraioli, A., Leclère, L., Herl, M., Gao, F., Chevalier, S., Copley, R. R., Houliston, E., Anderson, D. J., & Pachter, L. (2021). Whole animal multiplexed single-cell rna-seq reveals plasticity of clytia medusa cell types. bioRxiv. https://doi.org/10.1101/2021.01.22.427844

Cunningham, K., Anderson, D. J., & Weissbourd, B. (2024). Jellyfish for the study of nervous system evolution and function. Current Opinion in Neurobiology, 88, 102903. https://doi.org/10.1016/j.conb.2024.102903

Gaskill, M. (2018, November 20). No brain? For jellyfish, no problem | blog | nature | pbs. Nature. https://www.pbs.org/wnet/nature/blog/no-brain-for-jellyfish-no-problem/

Miller, C. T., Hale, M. E., Okano, H., Okabe, S., & Mitra, P. (2019). Comparative principles for next-generation neuroscience. Frontiers in Behavioral Neuroscience, 13. https://doi.org/10.3389/fnbeh.2019.00012

Neuroregeneration—An overview | sciencedirect topics. (n.d.). Retrieved April 27, 2025, from https://www.sciencedirect.com/topics/neuroscience/neuroregeneration

Steward, M. M., Sridhar, A., & Meyer, J. S. (2013). Neural regeneration. Current Topics in Microbiology and Immunology, 367, 163–191. https://doi.org/10.1007/82_2012_302

Thinking without a centralized brain: The intelligence of the octopus. (n.d.). WHYY. Retrieved April 27, 2025, from https://whyy.org/segments/thinking-without-a-centralized-brain-the-intelligence-of-the-octopus/

Zhu, F., Grier, H. A., Tandon, R., Cai, C., Agarwal, A., Giovannucci, A., Kaufman, M. T., & Pandarinath, C. (2022). A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with sub-frame temporal resolution. Nature Neuroscience, 25(12), 1724–1734. https://doi.org/10.1038/s41593-022-01189-0

Identification of Underlying Apoptotic Pathways in MCF-7 Breast Cancer Cells via CRISPRa Upregulation of HtrA2/Omi

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This experiment investigated a possible candidate for cancer treatment utilizing a cell’s own function for programmed cell death. The purpose of this study was to determine if upregulation of the apoptotic gene HtrA2/Omi in breast cancer cells would lead to increased apoptosis in the cells. Previous literature had described upregulation of apoptotic pathways as a possible viable mechanism for cancer treatment. However, this study did not find significant results to support these claims. 

Breast cancer, one of the most prevalent forms of cancer in the world, disproportionately affects women in the United States. On average, 13 percent of women in the United States will be diagnosed with breast cancer at some point during their lifetime (Breast Cancer Facts and Statistics 2023). Every year, 42,000 women die from breast cancer in the United States, with 240,000 more diagnosed with breast cancer (Basic Information About Breast Cancer 2023). 

Cells undergo a highly regulated process of programmed cell death called apoptosis that allows for natural development and growth of the organism. Through apoptosis, organisms are able to destroy surplus, infected, and damaged cells. Cancerous tumors develop when the apoptosis function of a cell is not working properly, resulting in a malignant cell that can grow and divide uncontrollably into a tumor. As apoptosis pathways can be induced non-surgically, it is a highly effective method used to control or terminate malignant cancer cells. By utilizing the cell’s own mechanism for death, research for cancer treatment has identified apoptosis as a way to target malignant tumors (Pfeffer et al., 2018). 

Research has shown that apoptosis is induced by overexpressing certain genes. HtrA2/Omi is a gene that induces apoptosis when overexpressed in the cell. When released from the mitochondria, HtrA2 inhibits the function of an apoptosis inhibitor, effectively inducing cell death (Suzuki et al., 2001). These data suggest that modulating and upregulating HtrA2 expression shows promising findings in enhancing apoptosis in breast cancer. 

CRISPR-Cas9 is a type of cellular biotechnology which can be used to study the manipulation of genomes by either adding, deleting, or altering genetic material in specific locations. This tool can be used to overexpress the HtrA2 gene in order to induce cell death. The process of CRISPR-Cas9 involves using sgRNA (a single guide RNA) with an enzyme to act as a gene-editing tool and introduce mutations into a desired target sequence in the genome. In order to modulate the HtrA2 gene, this experiment will require CRISPRa, a variant of CRISPR that uses a protein (dCas9) and transcriptional effector. The sgRNA navigates to the genome locus, guiding the dCas9. The dCas9 is unable to make a cut, so the effector instead activates the desired downstream gene expression (“Chapter 2: CRISPRa,” n.d.). This experiment will use CRISPRa technology to upregulate the HtrA2/Omi gene, which will inhibit the X chromosome-linked inhibitor of apoptosis, inducing either caspase-dependent cell death or Caspase-3 independent cell death in MCF-7 cells.

The pilot study for this experiment was conducted to determine the optimal level of Lipofectamine – which is a reagent that can be used for an efficient transfection without causing the cells to undergo apoptosis. The Lipofectamine concentration was varied to identify the fold change it would create in the expression of the target gene, HtrA2/Omi. After statistical analyses, researchers found no statistically significant correlation between the HtrA2/Omi gene expression and the Lipofectamine concentration in this experiment.

Fig. 1. After the transfection, qPCR was conducted on the control, 100% Lipofectamine, 75% Lipofectamine with sgRNA, and 75% Lipofectamine without sgRNA. The average Ct values were calculated and graphed.

Overall, the results from conducting quantitative PCR (qPCR), which shows how much of the HtrA2 was transfected, demonstrated extreme variance, indicating that there may have been errors that significantly affected these results. One possible error was that qPCR was conducted as cells were undergoing apoptosis, which would skew the results as mRNA is destroyed in cells as they die, leaving fragments behind. Another error observed throughout this experiment was high cell confluence (number of cells covering the adherent surface). Much of this experiment was conducted with cells at 100% or almost 100% confluence, which means it is possible that the concentrations of Lipofectamine that were predicted to cause efficient transfection did not work because the reagent could not enter the cells. Ultimately, it was found that a cell seeding concentration of 1*104 cells/mL worked best with regard to transformation, but the experiment still did not yield statistically significant results.

Fig. 2. For the pilot experiment, mCherry plasmid was transfected in MCF-7 cells. The following ZOE images showed the images of MCF-7 before transfection under different fluorescence as well as the merged image of both green and red fluorescence.

 

References

ATCC. (n.d.). MCF-7. ATCC. Retrieved November 17, 2021, from https://www.atcc.org/products/htb-22

Breast cancer facts and statistics, 2023. (n.d.). https://www.breastcancer.org/facts-statistics

Siegel, R. L., Miller, K. D., Fuchs, H., & Jemal, A. (2021). Cancer Statistics, 2021. CA: A Cancer Journal for Clinicians, 71(1), 7–33. https://doi.org/10.3322/caac.21654

Basic Information About Breast Cancer, 2023. https://www.cdc.gov/cancer/breast/basic_info

Pfeffer, C. M., & Singh, A. T. K. (2018). Apoptosis: A Target for Anticancer Therapy. International Journal of Molecular Sciences, 19(2), 448. https://doi.org/10.3390/ijms19020448

Suzuki Y, Imai Y, Nakayama H, Takahashi K, Takio K, Takahashi R. A serine protease, HtrA2, is released from the mitochondria and interacts with XIAP, inducing cell death. Mol Cell. 2001 Sep;8(3):613-21. doi: 10.1016/s1097-2765(01)00341-0. PMID: 11583623.

Hu, Q., Myers, M., Fang, W., Yao, M., Brummer, G., Hawj, J., Smart, C., Berkland, C., & Cheng, N. (2019). Role of ALDH1A1 and HTRA2 expression in CCL2/CCR2-mediated breast cancer cell growth and invasion. Biology open, 8(7), bio040873. https://doi.org/10.1242/bio.040873

Camarillo, Ignacio G., et al. “4 – Low and High Voltage Electrochemotherapy for Breast Cancer:

An in Vitro Model Study.” ScienceDirect, Woodhead Publishing, 1 Jan. 2014. www.sciencedirect.com/science/article/abs/pii/B9781907568152500042.

Rouhimoghadam M, Safarian S, Carroll JS, Sheibani N, Bidkhori G. Tamoxifen-Induced Apoptosis of MCF-7 Cells via GPR30/PI3K/MAPKs Interactions: Verification by ODE Modeling and RNA Sequencing. Front Physiol. 2018 Jul 11;9:907. doi: 10.3389/fphys.2018.00907. PMID: 30050469; PMCID: PMC6050429.

Mooney, L. M., Al-Sakkaf, K. A., Brown, B. L., & Dobson, P. R. (2002). Apoptotic mechanisms in T47D and MCF-7 human breast cancer cells. British journal of cancer, 87(8), 909–917. https://doi.org/10.1038/sj.bjc.6600541

Suzuki, Y., Takahashi-Niki, K., Akagi, T. et al. Mitochondrial protease Omi/HtrA2 enhances caspase activation through multiple pathways. Cell Death Differ 11, 208–216 (2004). https://doi.org/10.1038/sj.cdd.440134

Chapter 2: CRISPRa and CRISPRi. (n.d.). In A Comprehensive Guide on CRISPR Methods. https://www.synthego.com/guide/crispr-methods/crispri-

Better Bonds and New Molecules

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Keywords – chemical bonds, covalent bonds, ionic bonds, ions, free radicals, dissociation, synthesis, stimuli, heterolysis

Free radicals are typically atoms that are most commonly found in diatomic molecules (for example, Oxygen) that are not bonded, so they tend to bond to the first available molecule and are therefore very unpredictable. Free radicals are atoms with unpaired electrons attached. They are commonly found in the body or in the environment. Having unpaired electrons means that they are volatile and can randomly bond to other molecules, creating toxic compounds if they become too abundant. 

By contrast, ions are atoms with charges that create much more predictable bonds in nature. Like free radicals, ions have a different number of electrons (negatively charged parts) than protons (positively charged parts). However, ions have paired electrons and occur more naturally in the body. Ions are essential for communication between cells.

The synthetic breakdown – or dissociation – of molecules in solutions or bodily environments often releases free radicals instead of ions. This new study explores the possibility of using energy differently to reduce the release of free radicals in synthetic dissociation. The replacement of free radicals with ions will reduce harm to the body, as well as the environment. This opens up new possibilities for the creation of new medicines and more efficient biofuels.

Heterolysis results in the release of ions rather than free radicals. The Nuerberger and Breder lab conducted experiments that center around the understanding that many molecules can not be dissociated into their respective atomic contents via heterolysis, a process that involves breaking molecular bonds by using two different energetic stimuli rather than one (for example, light and heat rather than one or the other). The challenge here is to balance the use of heat and light to efficiently break down molecules without harmful byproducts like free radicals.

This procedure begins with determining the lambda-max value, which is the optimal wavelength of light that will maximize the absorbance in a certain molecule, for the molecules PhSe, PhSe+, and PhSe- (Breder, 2024). These are charged compounds consisting of a Selenium atom attached to a phenyl group, or a six-Carbon ring with five attached Hydrogen atoms. These molecules were selected to mimic the complexity and size of many biological molecules found in the body.

Next, the researchers determined the amount of energy that could be absorbed from a light source with the calculated lambda-max wavelength. This data was obtained through the use of absorbance sensors, which shine a broad spectrum of light with various wavelengths and can detect which wavelengths are blocked the most by dissolved particles. All substances have a lambda-max value, which is why we are able to see in color. Even samples that appear to be colorless have a slight color to them. The lambda-max value of a sample will typically correspond to its complementary color in the red-blue-green system (for example, the lambda-max value for a green substance will correspond to a shade of purple light).

Once the lambda-max values were determined for each substance, the researchers calculated how much energy was contained in the absorbed light. This value was subtracted from the known amount of energy required to break the Se-C (Selenium-Carbon) bonds. The remaining energy was supplemented in the form of heat, and the molecules in turn dissociated with a much higher frequency of ions and atoms with paired electrons than free radicals (Breder, 2024). Researchers were able to quantify the difference in ion dissociation from free radicals by determining experimental lambda-max values after exposure to the light and heat stimuli and comparing those of the ion products and of the free radical products. (see Figure 1 for comparison)

Figure 1. Comparison of average energy levels required to separate atoms via homolysis vs. heterolysis (Breder, 2024). 

 

This experiment demonstrates that the combined use of heat and light stimuli to dissociate molecules results in safer byproducts for the human body and the environment. This means that more diverse molecules can be created without extensive energy usage. This leap in chemistry expands into the biological and environmental fields of research, allowing for more complex and efficient medicines, implants, biofuels, plastic replacements, and more to be created.

This research has broad implications in the research world. In environmental sciences, the creation of biofuels can require several steps of synthesizing and dissociating molecules to achieve specific formulas and structures. The knowledge of how to minimize the release of volatile materials during this process is vital to ensuring that living organisms in nearby ecosystems are not harmed by the creation of more renewable fuels.

In medicine, a similar dilemma occurs with the creation of new drugs. While medicinal compounds are synthesized in controlled lab environments, their individual chemical formulas may be counterproductive in that they favor the release of free radicals in the body once administered into such an uncontrolled environment. In addition to reducing the abundance of free radicals in the synthesis of new materials, the knowledge of how to more efficiently construct and break apart molecules opens up new possibilities for entirely unique drug compounds. Ideally, many of these will serve the same functions but will be less structurally in favor of releasing free radicals into the body.

Works Cited

Sayre, Hannah J., and Harsh Bhatia. “Innovative Way to Break Chemical Bonds Broadens Horizons for Making Molecules.” Nature, vol. 632, no. 8025, Nature Portfolio, Aug. 2024, pp. 508–9, https://doi.org/10.1038/d41586-024-02437-y. Accessed 10 Oct. 2024.

Tiefel, Anna F., et al. “Unimolecular Net Heterolysis of Symmetric and Homopolar σ-Bonds.” Nature, vol. 632, no. 8025, Aug. 2024, pp. 550–56, https://doi.org/10.1038/s41586-024-07622-7.

From Milk to Malignancy – Breast Cancer and its Metabolic Implications 

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The annual rise of cancer cases has created a high demand for new innovative treatments and has made cancer a prominent topic in the scientific community. According to the American Cancer Society (ACS), approximately 20 million new cancer cases were diagnosed worldwide in 2022, leading to 9.7 million deaths [1]. It is expected that by 2050, cancer cases will reach 35 million, largely due to population growth [1]. While significant advancements have been made in cancer research, the complexity of different cancer types presents challenges. 

One of the most prevalent forms is breast cancer, which, in 2022, was the second most common cancer in the U.S., with 2.3 million new cases, predominantly affecting women [2]. Unlike many cancers, breast cancer is not a single disease but a collection of subtypes characterized by distinct clinical, morphological, and molecular features. This heterogeneity makes it challenging to study and treat effectively. A recent study published in Nature Metabolism explores the metabolic differences between normal mammary cells and breast cancer cells [4]. Understanding these metabolic processes could pave the way for new, targeted therapies. Researchers have identified specific metabolic vulnerabilities in mammary epithelial cells, which line the breast tissue.

 

Figure 1. Non-tumorigenic Mammary Gland Components. A diagram of a non-tumorigenic mammary gland showing a cluster of alveoli containing luminal and basal cells. Luminal cells line the milk ducts and alveoli and are responsible for milk secretion during lactation. Basal cells are believed to play a role in transporting milk to the nipple during lactation. Source: Created in BioRender, [4], [10], [11].

In the normal mammary gland, various types of cells carry out specific functions, one of which is the progenitor cells. These progenitor cells generate distinct alveolar structures that continuously form in the adult breast, and their activity is crucial for maintaining normal mammary homeostasis [5]. Progenitor cells are located in the luminal compartment [6], which is also home to the luminal cells. The luminal cells play a key role in lactation by lining the milk ducts and alveoli, where they secrete milk (Figure 1)[7]. In contrast, basal cells are located around the luminal cells and are believed to function during lactation by helping to transport milk to the nipple (Figure 1)[7]. Although these mammalian epithelial cells (luminal and basal cells) are important to the function of normal mammary glands, these also serve as a tumour cell of origin [4].

In their study, Mahendralingam et al. used mass spectrometry to analyze the metabolic profiles of normal human mammary cells [8]. They discovered that luminal progenitor cells primarily rely on oxidative phosphorylation for energy, whereas basal cells depend more on glycolysis [4]. This distinction is crucial because oxidative phosphorylation is an efficient, oxygen-dependent process that generates substantial energy, while glycolysis, though faster, is less efficient and does not require oxygen — a pathway often favored by cancer cells to support rapid growth [9]. Targeting these distinct energy pathways could lead to more effective treatments for different breast cancer subtypes.

However, a new discovery was that breast cancer cells appear to adopt the metabolic programs of their cells of origin [4,9]. This complicates treatment since the cancer cells may still be vulnerable to metabolic pathways that are important for normal cell function. As a result, treatments designed to target specific metabolic pathways might not work as expected, since the cancer cells might behave similarly to the healthy cells from which they originated. 

The results from Mahendralingam et al. can form a basis for future metabolic studies that may lead to specific anti-tumoral drug therapies designed to treat specific breast cancer subtypes. This type of research lays a foundation for targeted approaches but further studies are needed to assess how findings, such as this one, can translate into clinical practice. As breast cancer continues to rise, understanding the complexity is more important than ever. 

 

Work Cited: 

  1. Global Cancer Facts & Figures. (n.d.). Retrieved October 27, 2024, from https://www.cancer.org/research/cancer-facts-statistics/global-cancer-facts-and-figures.html
  2. Global cancer burden growing, amidst mounting need for services. (n.d.). Retrieved October 27, 2024, from https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing–amidst-mounting-need-for-services
  3. Sánchez López de Nava, A., & Raja, A. (2024). Physiology, Metabolism. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK546690/
  4. Alfonso-Pérez, T., Baonza, G., & Martin-Belmonte, F. (2021). Breast cancer has a new metabolic Achilles’ heel. Nature Metabolism, 3(5), 590–592. https://doi.org/10.1038/s42255-021-00394-8
  5. Tharmapalan, P., Mahendralingam, M., Berman, H. K., & Khokha, R. (2019). Mammary stem cells and progenitors: Targeting the roots of breast cancer for prevention. The EMBO Journal, 38(14), e100852. https://doi.org/10.15252/embj.2018100852
  6. Tornillo, G., & Smalley, M. J. (2015). ERrrr…Where are the Progenitors? Hormone Receptors and Mammary Cell Heterogeneity. Journal of Mammary Gland Biology and Neoplasia, 20(1–2), 63–73. https://doi.org/10.1007/s10911-015-9336-1
  7. New Paradigm for Mammary Glands. (n.d.). Massachusetts General Hospital. Retrieved December 8, 2024, from https://www.massgeneral.org/cancer-center/clinician-resources/advances/new-paradigm-for-mammary-glands
  8. Mahendralingam, M. J., Kim, H., McCloskey, C. W., Aliar, K., Casey, A. E., Tharmapalan, P., Pellacani, D., Ignatchenko, V., Garcia-Valero, M., Palomero, L., Sinha, A., Cruickshank, J., Shetty, R., Vellanki, R. N., Koritzinsky, M., Stambolic, V., Alam, M., Schimmer, A. D., Berman, H. K., … Khokha, R. (2021). Mammary epithelial cells have lineage-rooted metabolic identities. Nature Metabolism, 3(5), 665–681. https://doi.org/10.1038/s42255-021-00388-6
  9. ZHENG, J. (2012). Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review). Oncology Letters, 4(6), 1151–1157. https://doi.org/10.3892/ol.2012.928
  10. Fig. 3 Stem cell in glandular and stratified epithelia. A A schematic… (n.d.). ResearchGate. Retrieved December 7, 2024, from https://www.researchgate.net/figure/Stem-cell-in-glandular-and-stratified-epithelia-A-A-schematic-model-depicting-the_fig3_374804603
  11. Model of normal mammary gland structure. This tissue is composed of… (n.d.). ResearchGate. Retrieved December 8, 2024, from https://www.researchgate.net/figure/Model-of-normal-mammary-gland-structure-This-tissue-is-composed-of-ducts-which-are_fig1_357239665