Hasil untuk "Biochemistry"

T. Chou

J. Ramus, J. Kirk

R. Milo, S. Shen-Orr, S. Itzkovitz et al.

F. J. Stevenson

A. Saeed, V. Sharov, J. White et al.

White1, J. Li1, W. Liang1, N. Bhagabati1, J. Braisted1, M. Klapa1, T. Currier1, M. Thiagarajan1, A. Sturn1, M. Snuffin2, A. Rezantsev2, D. Popov2, A. Ryltsov2, E. Kostukovich2, I. Borisovsky2, Z. Liu3, A. Vinsavich3, V. Trush3, and J. Quackenbush1,4 1The Institute for Genomic Research, Rockville, MD, 2DataNaut, Bethesda, MD, 3Syntek Systems, Bethesda, MD, and 4Department of Biochemistry, George Washington University, Washington, D.C., USA

G. Farquhar, S. Caemmerer, J. Berry

W. Boerjan, J. Ralph, M. Baucher

R. Mall, W. Franke, D. Schiller et al.

W. Saenger

Rishik Aggarwal, Krisha Joshi, Pappu Kumar Yadav et al.

Hyperspectral imaging (HSI) allows researchers to study plant traits non-destructively. By capturing hundreds of narrow spectral bands per pixel, it reveals details about plant biochemistry and stress that standard cameras miss. However, processing this data is often challenging. Many labs still rely on loosely organized collections of lab-specific MATLAB or Python scripts, which makes workflows difficult to share and results difficult to reproduce. MVOS_HSI is an open-source Python library that provides an end-to-end workflow for processing leaf-level HSI data. The software handles everything from calibrating raw ENVI files to detecting and clipping individual leaves based on multiple vegetation indices (NDVI, CIRedEdge and GCI). It also includes tools for data augmentation to create training-time variations for machine learning and utilities to visualize spectral profiles. MVOS_HSI can be used as an importable Python library or run directly from the command line. The code and documentation are available on GitHub. By consolidating these common tasks into a single package, MVOS_HSI helps researchers produce consistent and reproducible results in plant phenotyping

S. Edition, C. Brett, K. Waldron

Balázs Boros, Gheorghe Craciun, Oskar Henriksson et al.

Dynamical systems with polynomial right-hand sides are very important in various applications, e.g., in biochemistry and population dynamics. The mathematical study of these dynamical systems is challenging due to the possibility of multistability, oscillations, and chaotic dynamics. One important tool for this study is the concept of reaction systems, which are dynamical systems generated by reaction networks for some choices of parameter values. Among these, disguised toric systems are remarkably stable: they have a unique attracting fixed point, and cannot give rise to oscillations or chaotic dynamics. The computation of the set of parameter values for which a network gives rise to disguised toric systems (i.e., the disguised toric locus of the network) is an important but difficult task. We introduce new ideas based on network fluxes for studying the disguised toric locus. We prove that the disguised toric locus of any network $G$ is a contractible manifold with boundary, and introduce an associated graph $G^{\max}$ that characterizes its interior. These theoretical tools allow us, for the first time, to compute the full disguised toric locus for many networks of interest.

Zhongmin Li, Runze Ma, Jiahao Tan et al.

Nucleotide sequence variation can induce significant shifts in functional fitness. Recent nucleotide foundation models promise to predict such fitness effects directly from sequence, yet heterogeneous datasets and inconsistent preprocessing make it difficult to compare methods fairly across DNA and RNA families. Here we introduce NABench, a large-scale, systematic benchmark for nucleic acid fitness prediction. NABench aggregates 162 high-throughput assays and curates 2.6 million mutated sequences spanning diverse DNA and RNA families, with standardized splits and rich metadata. We show that NABench surpasses prior nucleotide fitness benchmarks in scale, diversity, and data quality. Under a unified evaluation suite, we rigorously assess 29 representative foundation models across zero-shot, few-shot prediction, transfer learning, and supervised settings. The results quantify performance heterogeneity across tasks and nucleic-acid types, demonstrating clear strengths and failure modes for different modeling choices and establishing strong, reproducible baselines. We release NABench to advance nucleic acid modeling, supporting downstream applications in RNA/DNA design, synthetic biology, and biochemistry. Our code is available at https://github.com/mrzzmrzz/NABench.

Tingli Hu, Sami Haddadin

Achieving optimality in controlling physical systems is a profound challenge across diverse scientific and engineering fields, spanning neuromechanics, biochemistry, autonomous systems, economics, and beyond. Traditional solutions, relying on time-consuming offline iterative algorithms, often yield limited insights into fundamental natural processes. In this work, we introduce a novel, causally deterministic approach, presenting the closed-form optimal tracking controller (OTC) that inherently solves pseudoconvex optimization problems in various fields. Through rigorous analysis and comprehensive numerical examples, we demonstrate OTC's capability of achieving both high accuracy and rapid response, even when facing high-dimensional and high-dynamical real-world problems. Notably, our OTC outperforms state-of-the-art methods by, e.g., solving a 1304-dimensional neuromechanics problem 1311 times faster or with 113 times higher accuracy. Most importantly, OTC embodies a causally deterministic system interpretation of optimality principles, providing a new and fundamental perspective of optimization in natural and artificial processes. We anticipate our work to be an important step towards establishing a general causally deterministic optimization theory for a broader spectrum of system and problem classes, promising advances in understanding optimality principles in complex systems.

Zihao Deng, Lixia Liu, Guantai Xie et al.

Excessive lipid accumulation promotes the occurrence and progression of hepatocellular carcinoma (HCC), accompanied by high levels of fatty acid synthetase (FASN) and more active lipogenesis. Heat shock protein 90 (Hsp90) acts as a chaperone to maintain the stability and activity of the client proteins. Studies have revealed that Hsp90 regulates the lipid metabolism of HCC, but the effect of Hsp90 on FASN still remains unknown. This study aims to discover the mechanism of Hsp90 inhibition on lipid accumulation and investigate the different effects of Hsp90 N-terminal domain inhibitor STA9090 and C-terminal domain inhibitor novobiocin on FASN protein stability and transcription pathway in HCC. We found that HCC cells tended to store lipids, which could be disrupted by Hsp90 inhibitors in vivo and in vitro. High levels of Hsp90α and FASN in tumor tissue had correlation with poor prognosis of HCC patients, and Hsp90α interacted with FASN to maintain its protein stability. Furthermore, N-terminal domain of Hsp90α was essential for process of sterol regulatory element binding protein 1 to activate FASN transcription and Hsp90α prevented proteasomal degradation of liver X receptor α to upregulate FASN transcription via liver X receptor α/sterol regulatory element binding protein 1 axis. Our data reveal that Hsp90α promotes lipid accumulation by increasing the protein stability and FASN mRNA transcription, and can be alleviated by Hsp90 inhibitors, which provides a theoretical basis for Hsp90-targeted therapy on lipid metabolism in HCC.

Mehvish Aqil, Malik Istikhar Ali Sajjad , Mehr Muhammad Imran et al.

Background: Nontuberculous mycobacteria (NTM), a diverse group of environmental organisms rapidly proliferating in water, soil, and dust, are becoming a common cause of clinical disease. This study analyzed patient data from two major hospitals in Faisalabad, Pakistan, to improve early detection of NTM lung disease and to guide clinical practice in seeking earlier and quicker intervention.   Methods: A retrospective cross-sectional study was conducted from January 2020 to December 2021, using the records of 294 tuberculosis patients at Allied Hospital and DHQ Hospital, Faisalabad. Non-probability convenience sampling was used for sample collection and sample size was collected using OpenEpi 3.0.0.  Data from patients with NTM lung disease were checked. The diagnosis was based on criteria defined by the ATS/IDSA (a clinical, radiological and microbiological evidence). Testing of specimens (sputum, BAL fluid, puncture fluid) was conducted using AFB smear, culture (MGIT 960) and species identification by molecular techniques. Chi-square, Wilcoxon tests and logistic regression were performed using SPSS version 26.0.p<0.05 was considered as significant. Results: There were 294 patients (147 males; 147 females); median age 61 years, 77.2% had bronchiectasis. The most frequently identified species was the Mycobacterium avium-intracellulare complex (MAC 56.1%) followed by M. kansasii (19%) and M. abscessus (15.3%).   Sputum cultures had the highest positivity rate (87.4%), outperforming BAL fluid (80.3%) and puncture fluid (61.5%). Conclusion: The M. avium-intracellulare complex is the most common NTM species found in patients in these hospitals. The signs of expectoration, gender and bronchiectasis increased likelihood of BAL culture positivity, which aids in diagnosis.

Zahed Khatooni, Gordon Broderick, Sanjeev K Anand et al.

Lawsonia intracellularis (LI) are obligate intracellular bacteria and the causative agent of proliferative hemorrhagic enteropathy that significantly impacts the health of piglets and the profitability of the swine industry. In this study, we used immunoinformatic and computational methodologies such as homology modelling, molecular docking, molecular dynamic (MD) simulation, and free energy calculations in a novel three stage approach to identify strong T and B cell epitopes in the LI proteome. From ∼ 1342 LI proteins, we narrowed our focus to 256 proteins that were either not well-identified (unknown role) or were expressed at a higher frequency in pathogenic strains relative to non-pathogenic strains. At stage 1, these proteins were analyzed for predicted virulence, antigenicity, solubility, and probability of residing within a membrane. At stage 2, we used NetMHCPan4-1 to identify over ten thousand cytotoxic T lymphocyte epitopes (CTLEs) and 286 CTLEs were ranked as having high predicted binding affinity for the SLA-1 and SLA-2 complexes. At stage 3, we used homology modeling to predict the structures of the top ranked CTLEs and we subjected each of them to molecular docking analysis with SLA-1*0401 and SLA-2*0402. The top ranked 25 SLA-CTLE complexes were selected to be an input for subsequent MD simulations to fully investigate the atomic-level dynamics of proteins under the natural thermal fluctuation of water and thus potentially provide deep insight into the CTLE-SLA interaction. We also performed free energy evaluation by Molecular Mechanics/Poisson-Boltzmann Surface Area to predict epitope interactions and binding affinities to the SLA-1 and SLA-2. We identified the top five CTLEs having the strongest binding energy to the indicated SLAs (-305.6 kJ/mol, -219.5 kJ/mol, -214.8 kJ/mol, -139.5 kJ/mol and -92.6 kJ/mol, respectively.) W also performed B-cell epitope prediction and the top-ranked 5 CTLEs and 3 B-cell epitopes were organized into a multi-epitope subunit antigen vaccine construct joined using EAAAK, AAY, KK, and GGGGG linkers with 40 residues of the LI DnaK protein attached to the N-terminus to further enhance the antigenicity of the vaccine construct. Blind docking studies showed strong interactions between our vaccine construct with swine Toll-like receptor 5. Collectively, these molecular modeling and immunoinformatic analyses present a useful in silico protocol for the discovery of candidate antigen in many viral and bacterial pathogens.

Pooria Pakdaman, Nadereh Naderi, Narges Farshidi et al.

Abstract Background The Slit guidance Ligand 2 (SLIT2) glycoprotein is of particular interest because of its role in modulating inflammation and the progression of diseases such as atherosclerosis. This study aimed to determine whether SLIT2 polymorphisms can serve as predictive markers for coronary artery disease (CAD) development by investigating its single-nucleotide polymorphisms (SNPs). Methods In this case-control study, a total of 321 participants including 217 patients with diagnosed CAD and 104 healthy controls were recruited. Patients were divided into acute coronary syndrome (ACS) (n = 153) and stable angina pectoris (SAP) (n = 64). Allele and genotype frequency of SLIT2 SNP variants rs666088 C > T and rs16869521 A > T were determined using Polymerase Chain Reaction with Sequence-Specific Primers (PCR-SSP). Odds ratios (ORs) were reported along with their 95% confidence intervals (CIs) and P-values. Crude estimates were initially presented, followed by adjusted ORs computed using logistic regression, controlling for potential confounders including age, gender, high-density lipoprotein (HDL) levels, fasting blood sugar (FBS), and smoking status. Results The frequencies of the T allele of rs666088 were significantly higher in ACS patients compared to healthy controls, and were associated with an increased risk of ACS both before (OR = 1.5, 95% CI = 1.1–2.2, P = 0.01) and after adjustment for confounding factors (OR = 1.3, 95% CI = 1.1–1.9, P = 0.02). Moreover, analysis of ACS subgroups—myocardial infarction (MI) and unstable angina pectoris (UAP), revealed consistent results. However, the allele and genotype frequencies of rs16869521 were not significantly different between patients and controls in any disease categories. Conclusions Our study revealed that genetic polymorphism of SLIT2 (rs666088) TT genotype and T allele is the potential host genetic risk factor for ACS. Therefore, SLIT2 (rs666088) genetic variation may be considered as a biomarker for early screening and diagnosis of the disease.

Deqiang An, Xianyao Jiang, Yucheng Yang

Background: Sesamin can suppress many cancers, but its effect on nasopharyngeal carcinoma (NPC) is unclear. Herein, we set out to pinpoint the possible changes in NPC due to Sesamin. Methods: The biological function of NPC cells exposed to Sesamin/N-acetyl-L-cysteine (NAC)/3-Methyladenine (3-MA) was detected, followed by evaluation of reactive oxygen species (ROS) production (dichlorodihydrofluorescein diacetate staining) and mitochondrial membrane potential (MMP) (flow cytometry). Proteins pertinent to apoptosis (cleaved caspase-3, cleaved poly (ADP-ribose) polymerase 1 (PARP1)), cell cycle (Cyclin B1), and autophagy (microtubule-associated protein light chain 3 (LC3)-I, LC3-II, Beclin-1, P62) were quantified by Western blot. After the xenografted tumor model in mice was established, the tumor volume and weight were recorded, and Ki-67 and cleaved caspase-3 levels were determined by immunohistochemical analysis. Results: Sesamin inhibited viability, proliferation, cell cycle progression and migration, induced apoptosis, increased ROS production, and decreased MMP in NPC cells. Sesamin elevated cleaved caspase-3/caspase-3, cleaved PARP1/PARP1, and Beclin-1 expressions as well as LC3-II/LC3-I ratio, while diminishing Cyclin B1 and P62 levels. NAC and 3-MA abrogated Sesamin-induced changes as above in NPC cells. Sesamin inhibited the increase of the xenografted tumor volume and weight, down-regulated Ki-67, and up-regulated cleaved caspase-3 in xenografted tumors. Conclusion: Sesamin exerts anti-tumor activity in NPC, as demonstrated by attenuated tumor proliferation and xenografted tumor volume and weight, as well as induced apoptosis in tumor tissues, consequent upon the promotion of autophagy and reactive oxygen species production.

G. Sen, P. Lengyel