Computational Biology

The Mutational Alteration of the Primary Structure of Yeast Iso-1-cytochrome c (Sherman, F., Stewart, J. W., Parker, J. H., Inhaber, E., Shipman, N. A., Putterman, G. J., Gardisky, R. L., and Margoliash, E. (1968) J. Biol. Chem. 243, 5446–5456) Identification of Missense Mutants by Amino Acid Replacements in Iso-l-cytochrome c from Yeast (Putterman, G. J., Margoliash, E., and Sherman, F. (1974) J. Biol. Chem. 249, 4006–4015)

Cells respond to environmental stress and proinflammatory cytokines by stimulating the Jun N-terminal kinase/stress-activated protein kinase (JNK/SAPK) and the p38 mitogen-activated protein kinase cascades. Infection of eukaryotic cells with herpes simplex virus type 1 (HSV-1) resulted in stimulation of both JNK/SAPK and p38 mitogen-activated protein kinase after 3 h of infection, and activation reached a maximum of 4-fold by 9 h post-infection. By using a series of mutant viruses, we showed that the virion transactivator protein VP16 stimulates p38/JNK, whereas no immediate-early, early, or late viral expressed gene is involved. We identified the stress-activated protein kinase kinase 1 as an upstream activator of p38/JNK, and we demonstrated that activation of AP-1 binding proceeded p38/JNK stimulation. During infection, the activated AP-1 consisted mainly of JunB and JunD with a simultaneous decrease in the cellular levels of Jun protein. We suggest that activation of the stress pathways by HSV-1 infection either represents a cascade triggered by the virus to facilitate the lytic cycle or a defense mechanism of the host cell against virus invasion.

The landscape of clinical microbiome research has dramatically evolved over the past decade. By leveraging in vivo and in vitro experimentation, multiomic approaches and computational biology, we have uncovered mechanisms of action and microbial metrics of association and identified effective ways to modify the microbiome in many diseases and treatment modalities. This Review explores recent advances in the clinical application of microbiome research over the past 5 years, while acknowledging existing barriers and highlighting opportunities. We focus on the translation of microbiome research into clinical practice, spearheaded by Food and Drug Administration (FDA)-approved microbiome therapies for recurrent Clostridioides difficile infections and the emerging fields of microbiome-based diagnostics and therapeutics. We highlight key examples of studies demonstrating how microbiome mechanisms, metrics and modifiers can advance clinical practice. We also discuss forward-looking perspectives on key challenges and opportunities toward integrating microbiome data into routine clinical practice, precision medicine and personalized healthcare and nutrition.

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Contributors

The Center for Drug Evaluation and Research (CDER) and the Center for Biologics Evaluation and Research (CBER) of the U.S. Food and Drug Administration (FDA) have been leaders in protecting and promoting the U.S. public health by helping to ensure that safe and effective drugs and biological products are available in the United States for those who need them. The null hypothesis significance testing approach, along with other considerations, is typically used to demonstrate the effectiveness of a drug or biological product. The Bayesian framework presents an alternative approach to demonstrate the effectiveness of a treatment. This article discusses the Bayesian framework for drug and biological product development, highlights key settings in which Bayesian approaches may be appropriate, and provides recent examples of the use of Bayesian approaches within CDER and CBER.

Following the identification of a late mortality signal, the Food and Drug Administration (FDA) convened an advisory panel that concluded that additional clinical study data are needed to comprehensively evaluate the late mortality signal observed with the use of drug-coated balloons (DCB) and drug-eluting stent (DES). The objective of this review is to (1) identify and summarize the existing clinical and cohort studies assessing paclitaxel-coated DCBs and DESs, (2) describe and determine the quality of the available data sources for the evaluation of these devices, and (3) present methodologies that can be leveraged for proper signal discernment within available data sources. Studies and data sources were identified through comprehensive searches. original research studies, clinical trials, comparative studies, multicenter studies, and observational cohort studies written in the English language and published from January 2007 to November 2021, with a follow-up longer than 36 months, were included in the review. Data quality of available data sources identified was assessed in three groupings. Moreover, accepted data-driven methodologies that may help circumvent the limitations of the extracted studies and data sources were extracted and described. There were 39 studies and data sources identified. This included 19 randomized clinical trials, nine single-arm studies, eight registries, three administrative claims, and electronic health records. Methodologies focusing on the use of existing premarket clinical data, the incorporation of all contributed patient time, the use of aggregated data, approaches for individual-level data, machine learning and artificial intelligence approaches, Bayesian approaches, and the combination of various datasets were summarized. Despite the multitude of available studies over the course of eleven years following the first clinical trial, the FDA-convened advisory panel found them insufficient for comprehensively assessing the late-mortality signal. High-quality data sources with the capabilities of employing advanced statistical methodologies are needed to detect potential safety signals in a timely manner and allow regulatory bodies to act quickly when a safety signal is detected.

Chapter 7 - Immunogenomics: steps toward personalized medicines

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Although dermatitis from common English ivy, Hedera helix, is known to botanists, 1 it is not familiar to dermatologists. This common ornamental plant can cause dermatitis, not only from its leaves and stems but also from its roots. It is important to emphasize that the dermatitis clinically may resemble that from poison ivy. There is no botanical relationship between English ivy, which belongs to the ginseng family, Araliaceae, and poison ivy, of the famed cashew family, Anacardiaceae. Sensitivity to English ivy is commoner than one supposes, since it is generally assumed that all plant dermatitis acquired out of doors is due usually to poison ivy. One of us (H.R.M.), in his lectures to garden clubs, has heard of instances of dermatitis from English ivy and even disbelief of physicians in this. It is apparent that proof could be established easily by testing to this type of ivy. An engineer, age

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics. In a broader sense, statistics in regulatory science can be defined as valid statistics that are employed in the review and approval process of regulatory submissions of pharmaceutical products. In addition, statistics in regulatory science are involved with the development of regulatory policy, guidance, and regulatory critical clinical initiatives related research. This book is devoted to the discussion of statistics in regulatory science for pharmaceutical development. It covers practical issues that are commonly encountered in regulatory science of pharmaceutical research and development including topics related to research activities, review of regulatory submissions, recent critical clinical initiatives, and policy/guidance development in regulatory science. Devoted entirely to discussing statistics in regulatory science for pharmaceutical development. Reviews critical issues (e.g., endpoint/margin selection and complex innovative design such as adaptive trial design) in the pharmaceutical development and regulatory approval process. Clarifies controversial statistical issues (e.g., hypothesis testing versus confidence interval approach, missing data/estimands, multiplicity, and Bayesian design and approach) in review/approval of regulatory submissions. Proposes innovative thinking regarding study designs and statistical methods (e.g., n-of-1 trial design, adaptive trial design, and probability monitoring procedure for sample size) for rare disease drug development. Provides insight regarding current regulatory clinical initiatives (e.g., precision/personalized medicine, biomarker-driven target clinical trials, model informed drug development, big data analytics, and real world data/evidence). This book provides key statistical concepts, innovative designs, and analysis methods that are useful in regulatory science. Also included are some practical, challenging, and controversial issues that are commonly seen in the review and approval process of regulatory submissions. About the author Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.

Understanding the molecular interactions that drive peptide folding is crucial to chemistry and biology. In this study, we analyzed the role of CO···CO tetrel bonding (TtB) interactions in the folding mechanism of three different peptides (ATSP, pDIQ, and p53), which exhibit a different propensity to fold in an α helix motif. To achieve this goal, we used both a recently developed Bayesian inference approach (MELDxMD) and Quantum Mechanics (QM) calculations at the RI-MP2/def2-TZVP level of theory. These techniques allowed us to study the folding process and to evaluate the strength of the CO···CO TtBs as well as the synergies between TtBs and hydrogen-bonding (HB) interactions. We believe that the results derived from our study will be helpful for those scientists working in computational biology, peptide chemistry, and structural biology.

Use of UV methods for measurement of protein and nucleic acid concentrations.

Poison-ivy and poison-oak dermatitis

The recent convergence of high-dimensional molecular datasets with small-molecule inhibitor pipelines allows for selective targeting of aberrantly regulated pathways in many cancer types. But intra-tumor heterogeneity, paradoxical activation, intrinsic or acquired therapeutic resistance, and non-linear pathway interactions confound most simple targeting strategies(Widmer et al., 2015). For instance, MAPK signaling is activated by hot-spot mutations in BRAF, which are found in about 40-50% of melanoma cases. This article is protected by copyright. All rights reserved.