BioScience Laboratories (United States)

Abstract Cross-protein mutational susceptibility is not well understood, despite the fact that neurodegenerative diseases are caused by the misfolding, aggregation, and functional disruption of several proteins. Integrative analyses that combine mutational susceptibility patterns across several proteins implicated in neurodegenerative illness are lacking, despite the fact that prior research has concentrated on specific disease-associated proteins. Here, we offer a computational atlas of mutational vulnerability that includes 22 proteins associated with important neurodegenerative diseases, such as spinocerebellar ataxias, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.We conducted a cross-protein comparative analysis to find regions that are disproportionately sensitive to amino acid substitutions using curated human variant data from UniProt, prion-like domain predictions, sequence-derived mutational sensitivity profiling, and aggregation-prone region mapping. Several structurally and functionally diverse proteins, many of which are still underrepresented in naturally occurring human variation, share susceptibility regions, as our results demonstrate. Specifically, proteins like ATXN2, OPTN, and MATR3 show strong mutational sensitivity and little overlap with known human variants, indicating unknown loci with potentially harmful effects. Furthermore, mechanistic connections between intrinsic sequence instability and pathological misfolding are strengthened by the selective enrichment of susceptible residues in prion-like and aggregation-prone areas. A resource for prioritizing proteins and regions for mutational screening, structural biophysics, and therapeutic targeting is provided by this study, which unifies mutational, structural, and aggregation-prone characteristics into a unified framework. In addition to confirming established risk loci, the cross-protein mutational vulnerability atlas identifies obscure locations that require more investigation. More generally, our method creates a scalable framework for mapping sequence-derived susceptibility across protein families, providing a link between mechanistic understanding of the causes of neurodegeneration and computational predictions. This study offers a strategic roadmap for upcoming experimental and translational research in neurodegenerative illnesses and emphasizes the value of integrative, multi-protein investigations in comprehending disease causation. All findings are derived from computational analyses and are intended to guide, rather than replace, experimental validation.

Abstract In mammalian reproduction, the ability of sperm cells to move across diverse physiological conditions and reach the oocyte is crucial to the success of fertilization. In this work, we create a thorough stochastic computer model that simulates the dynamics of sperm chemotaxis in a limited two-dimensional microenvironment. This model takes into account important biological factors such as temperature, pH fluctuations, ambient flow, and chemotactic strength. Through comprehensive parameter sweeps and duplicate simulations, we measure fertilization success rates and timing distributions under various situations in order to systematically investigate the impact of these parameters on fertilization efficiency. Our model incorporates stochastic sperm mortality to represent chemical and immunological challenges, and environmental barriers to replicate physical and metabolic heterogeneities found in the female reproductive system. Using survival analytic frameworks such as log-rank tests and Kaplan-Meier curves, fertilization time distributions were examined. The results showed statistically significant variations in fertilization kinetics among chemotactic regimes and environmental variables. Furthermore, sperm density heatmaps emphasize the crucial role that directed motility plays in fertilization outcomes by highlighting spatial clustering dynamics that are influenced by external fluxes and the intensity of chemotaxis. The robustness of the observed effects is confirmed by statistical comparisons using the ANOVA and Kolmogorov-Smirnov tests. Our results give a prediction framework for comprehending sperm behavior in vivo and quantitative insights into the relative contributions of biophysical and biochemical elements influencing fertilization success. By clarifying the mechanics behind sperm navigation and egg encounter efficiency, this integrative modeling method paves the way for future experimental validation and could influence assisted reproductive technologies and fertility therapies.

Vanadium is used in alloys, batteries as well as catalyst and is a known impurity in medical devices and pharmaceuticals. The present work describes the calculation of a parenteral tolerable intake (TI) for vanadium by chronic exposure in implantable medical devices per ISO 10993-17:2023, the applicable standard. The 2023 update of ISO 10993-17 [1] introduces new uncertainty factors (UFs) for calculating a TI. Therefore, we noted differences between the ISO guidance and the ICH Q3D guidance on Permissible Daily Exposure (PDE) for parental elemental pharmaceutical impurities. We derived a TI of 0.20μgV/kg/day based on the updated ISO guidance, and a PDE of 0.24μgV/kg/day based on ICH guidance. The latter is considered a more realistic estimate.

Hepatocellular cancer (HCC) progression is facilitated by gene-silencing chromatin histone hypoacetylation due to histone deacetylases (HDACs) activation. However, inhibiting HDACs, an effective treatment for lymphomas, has shown limited success in solid tumors. We report the discovery of a class of HDAC inhibitors (HDACi) that demonstrates exquisite selective cytotoxicity against human HCC cells. The lead compound STR-V-53 (3) showed favorable safety profile in mice and robustly suppressed tumor growth in orthotopic xenograft models of HCC. When combined with the anti-HCC drug sorafenib, STR-V-53 showed greater in vivo efficacy. Moreover, STR-V-53 combined with anti-PD1 therapy increased the CD8+ to regulatory T-cell (Treg) ratio and survival in an orthotopic HCC model in immunocompetent mice. This combination therapy resulted in durable responses in 40% of the mice. Collectively, our data demonstrate that the novel HDACi STR-V-53 is an effective anti-HCC agent that can induce profound responses when combined with standard immunotherapy.

レクチンで高分子多糖類をサンドイッチするEnzyme-Linked Lectin Assay（ELLA）により，高分子多糖類の新規定量技術を開発した．本法は，96ウェルマイクロプレートに固相化したレクチンと高分子多糖類を反応させたのち，酵素標識レクチンを反応させ，酵素反応により比色する特異性の高い方法である．本法により，グアーガムが0.1〜3 μg mL−1の範囲で，Lactobacillus delbrueckii ssp. bulgaricus OLL1073R-1（R-1）株由来菌体外多糖（EPS）が0.2～1 μg mL−1の範囲で検出可能であった．除タンパク質処理したR-1株培養液のEPSの定量においては，添加回収率は97〜99％ であり，分析精度は併行精度6.2％，室内再現精度6.8％ であった．以上の結果から，本法によるEPS定量法は良好な分析能を示すことが確認され，さらに優れた操作性を持つことから，種々の高分子多糖類の定量への応用が期待される．

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Early detection and long‐term monitoring are important for urothelial carcinoma of the bladder (UCB). Urine cytology and existing markers have insufficient diagnostic performance. Here, we examined medium‐sized extracellular vesicles (EVs) in urine to identify specific markers for UCB and evaluated their usefulness as diagnostic material. To identify specific markers in urinary EVs derived from UCB, we undertook shotgun proteomics using urine from four UCB patients and four healthy subjects. Next, 29 healthy specimens, 18 noncancer specimens, and 33 UCB specimens, all from men, were analyzed for urinary EVs by flow cytometry to evaluate the diagnostic performance of UCB‐specific EVs. Nanoparticle‐tracking analysis indicated that the size of EVs extracted from urine was mostly <400 nm. By shotgun proteomics, we detected several proteins characteristic of UCB and found that carcinoembryonic antigen‐related adhesion molecule (CEACAM) proteins were increased in patients. Flow cytometric analysis revealed that the degree of expression of CEACAM1, CEACAM5, and CEACAM6 proteins on the surface of EVs varied among patients. Extracellular vesicles expressing CEACAM proteins also expressed mucin 1, suggesting that they were derived from tumorigenic uroepithelial cells. The number of EVs expressing CEACAM1, 5, and 6 proteins was significantly increased in UCB (mean ± SD, 8.6 ± 13%) compared to non‐UCB (0.69 ± 0.46) and healthy (0.46 ± 0.34) by flow cytometry. The results of receiver operating characteristic (ROC) analysis showed a good score of area under the ROC curve of 0.907. We identified EVs that specifically express CEACAM proteins in urine and have potential for diagnostic applications. These EVs are potential targets in a new liquid biopsy test for UCB patients.