Biology subjects

Angel, M.

Publications and source records attributed to Angel, M..

7 recordsLinked to original sources

bioRxiv2026

Pex9 regulates TORC2 during the cellular response to oxidative stress

Peroxisomes are known for their detoxification role in cellular reactive oxygen species (ROS) homeostasis, yet their regulatory roles in cellular recovery from oxidative stress remain unclear. Here, using yeast, we systematically screened a panel of fluorescently tagged peroxisome-related proteins and identified widespread stress-induced changes in their localization. Notably, we discovered that the peroxisomal import receptor, Pex9, rapidly enters the nucleus upon H2O2 exposure, independently of the canonical oxidative stress regulators-Yap1 and Skn7, suggesting a non-canonical signaling function. We further show that Pex9 nuclear entry is modulated by Avo1, an essential Tor complex 2 (TORC2) subunit. In turn, Pex9 downregulates the essential TOR complexes kinase, Tor2, at both the transcriptional and protein levels. Finally, we show that this Pex9-TORC2 regulatory loop during oxidative stress is facilitated by the cellular envelope stress response. Our findings uncover an unexpected peroxisome-TORC2 signaling axis and highlight the importance of organelles in shaping global cellular responses to stress.

cell biology↗

bioRxiv2023

Performance of Large Language Models on Pharmacy Exam: A Comparative Assessment Using the NAPLEX

BackgroundThere has been considerable recent effort in integrating Large Language Models (LLMs) across different fields, including healthcare. However, the possibility of applying LLMs in pharmacy-related sciences is under-explored. ObjectivesThis study aims to evaluate the capabilities and limitations of six LLMs-GPT-3.5, GPT-4, Llama-2-7B, Llama-2-13B, Llama-2-70B, and Mistral-7B, in the field of pharmacy by assessing their reasoning abilities on a sample of the North American Pharmacist Licensure Examination (NAPLEX). Additionally, we explore the potential impacts of LLMs on pharmacy education and practice. MethodsTo evaluate the LLMs, we utilized the sample of the NAPLEX exam comprising 225 multiple-choice questions sourced from the APhA Complete Review for Pharmacy, 13th Edition | Pharmacy Library. These questions were presented to the Large Language Models through either local deployment or the Application programming interface (API), and the answers generated by the LLMs were subsequently compared with the answer key. ResultsThere is a notable disparity in the performance of the LLMs. GPT-4 emerged as the top performer, accurately answering 87.1% of the questions. Among the six LLMs evaluated, GPT-4 was the only model capable of passing the NAPLEX exam. ConclusionWe examined the performance of Large Language Models based on their model size, training methods, and fine-tuning algorithms. Given the continuous evolution of LLMs, it is reasonable to anticipate that future models will effortlessly excel in exams such as the NAPLEX. This highlights the significant potential of LLMs to influence the field of pharmacy. Hence, we must evaluate both the positive and negative implications associated with the integration of LLMs in pharmacy education and practice.

bioinformatics↗

bioRxiv2023

C1q Enables Influenza HA Stem Binding Antibodies to Block Viral Attachment and Broadens the Antibody Escape Repertoire

Broadly neutralizing, anti-hemagglutinin stem antibodies (Abs) are a promising universal influenza vaccine target. While anti-stem Abs are not believed to block viral attachment, we show that C1q confers attachment inhibition and boosts fusion and neuraminidase inhibition, greatly enhancing virus neutralization activity in vitro and in mice challenged with influenza virus via the respiratory route. These effects reflect increased steric interference and not increased Ab avidity. Remarkably, C1q greatly expands the anti-stem Ab viral escape repertoire to include residues throughout the hemagglutinin. Some substitutions cause antigenic alterations in the globular region or modulate HA receptor avidity. We also show that C1q enhances the neutralization activity of non-RBD anti-SARS-CoV-2 Spike Abs, an effect dependent on Spike density on the virion surface. Together, our findings show that first, Ab function must be considered in a physiological context and second, inferring the exact selection pressure for Ab-driven viral evolution is risky business, at best.

microbiology↗

bioRxiv2023

Clinical Knowledge and Reasoning Abilities of AI Large Language Models in Pharmacy: A Comparative Study on the NAPLEX Exam

ObjectiveThis study aims to evaluate the capabilities and limitations of three large language models (LLMs) - GPT-3, GPT-4, and Bard, in the field of pharmaceutical sciences by assessing their pharmaceutical reasoning abilities on a sample North American Pharmacist Licensure Examination (NAPLEX). We also analyze the potential impacts of LLMs on pharmaceutical education and practice. MethodsA sample NAPLEX exam consisting of 137 multiple-choice questions was obtained from an online source. GPT-3, GPT-4, and Bard were used to answer the questions by inputting them into the LLMs user interface. The answers provided by the LLMs were then compared with the answer key. ResultsGPT-4 exhibited superior performance compared to GPT-3 and Bard, answering 78.8% of the questions correctly. This score was 11% higher than Bard and 27.7% higher than GPT-3. However, when considering questions that required multiple selections, the performance of each LLM decreased significantly. GPT-4, GPT-3, and Bard only correctly answered 53.6%, 13.9%, and 21.4% of these questions, respectively. ConclusionAmong the three LLMs evaluated, GPT-4 was the only model capable of passing the NAPLEX exam. Nevertheless, given the continuous evolution of LLMs, it is reasonable to anticipate that future models will effortlessly pass the exam. This highlights the significant potential of LLMs to impact the pharmaceutical field. Hence, we must evaluate both the positive and negative implications associated with the integration of LLMs in pharmaceutical education and practice.

scientific communication and education↗

bioRxiv2019

Discovery Of UFO Proteins: Human-Virus Chimeric Proteins Generated During Influenza Virus Infection

Influenza A virus (IAV) is a threat to mankind because it generates yearly epidemics and poorly predictable sporadic pandemics with catastrophic potential. IAV has a small RNA genome composed of 8 mini-chromosomes (segments) that constitute a 5UTR followed by a coding region and a 3UTR. Transcription of IAV RNA into mRNA depends on host mRNA, as the viral polymerase cleaves 5m7G-capped nascent transcripts to use as primers to initiate viral mRNA synthesis. We hypothesized that captured host transcripts bearing AUG could drive the expression of upstream ORFs in the viral segments, a phenomenon that would depend on the translatability of the viral 5UTRs. Here we report the existence of this mechanism, which generates host-virus chimeric proteins. We label these proteins as Upstream Flu ORFs (UFO). Depending on the frame, two types of host-virus UFO proteins are made: canonical viral proteins with human-derived N term extensions or novel uncharacterized proteins. Here we show that both types are made during IAV infection. Sequences that enable chimeric protein synthesis are conserved across IAV strains, indicating that selection allowed the expansion of the proteome diversity of IAV in infected cells to include multiple human-virus proteins.

microbiology↗

bioRxiv2018

Neuraminidase Inhibition Contributes to Influenza A Virus Neutralization by Anti-Hemagglutinin Stem Antibodies

Broadly neutralizing antibodies (Abs) that bind the influenza virus hemagglutinin (HA) stem may enable universal influenza vaccination. Here, we show that anti-stem Abs sterically inhibit viral neuraminidase activity against large substrates, with activity inversely proportional to the length of the fibrous NA stalk that supports the enzymatic domain. By modulating NA stalk length in recombinant IAVs, we show that anti-stem Abs inhibit virus release from infected cells by blocking NA, accounting for their in vitro neutralization activity. NA inhibition contributes to anti-stem Ab protection in influenza infected mice, likely due at least in part to NA-mediated inhibition of Fc{gamma}R dependent activation of innate immune cells by antibody bound to virions. FDA approved NA inhibitors enhance anti-stem based Fc{gamma} dependent immune cell activation, raising the possibility of therapeutic synergy between NA inhibitors and anti-stem mAb treatment in humans.

microbiology↗

bioRxiv2017

Hemagglutinin Glycan Clock Guides Human Influenza A Virus Evolution

Adaptive immunity to influenza A virus is limited by frequent mutations in the immunodominant head of hemagglutinin (HA). Over the last century, the upward trend in HA-head glycosylation indicates glycan addition can increase fitness, but its role in viral evolution remains unclear. Here, we report glycan evolution follows a clock-like rhythm, pacing the timeline, trajectory, and replacement of HA. Following pandemic introduction, glycans are added to HA at 4- to 6-year intervals, until a functional glycan limit is reached, after which, at 9- to 12-year intervals, glycans are either swapped between different sites, or the HA is replaced by a novel pandemic virus. Using this, we predicted the appearance of the newest glycan on pH1N1 HA. Phylogeographic reconstruction suggests these highly fit strains originated in the Middle East, before rapidly replacing all strains globally. Going forward, we can use this simple algorithm to forecast future glycan evolution and identify seasons with higher pandemic potential.

microbiology↗