Hasil untuk "Biochemistry"

Adam Roberts, C. Trapnell, Julie Donaghey et al.

The biochemistry of RNA-Seq library preparation results in cDNA fragments that are not uniformly distributed within the transcripts they represent. This non-uniformity must be accounted for when estimating expression levels, and we show how to perform the needed corrections using a likelihood based approach. We find improvements in expression estimates as measured by correlation with independently performed qRT-PCR and show that correction of bias leads to improved replicability of results across libraries and sequencing technologies.

Rosalind Kornfeld, R. Jeanloz

K. Barnham, C. Masters, A. Bush

C. Nathan

J. C. Mcdonald, D. Duffy, Janelle R. Anderson et al.

S. Moncada, E. Higgs, H. Hodson et al.

G. Ourisson, P. Albrecht, M. Rohmer

P. Lengyel

D. Metzler

Lucas Fornari Laurindo, Victória Dogani Rodrigues, Enzo Pereira de Lima et al.

Cardiovascular diseases are the primary cause of mortality worldwide. In this scenario, atherosclerotic cardiovascular outcomes dominate since their incidence increases as populations grow and age. Atherosclerosis is a chronic inflammatory disease that affects arteries. Although its pathophysiology is heterogeneous, some genes are indissociably associated with its occurrence, and understanding their effects on the disease’s occurrence could undoubtedly define effective screening and treatment strategies. One such gene is NEDD4L. The NEDD4L gene is related to ubiquitin ligase enzyme activities. It is essential to regulate vascular inflammation, atherosclerosis plaque stability, endothelial and vascular smooth cell function, and lipid metabolism, particularly in controlling cholesterol levels. However, the evidence is dubious, and no review has yet synthesized the effects of targeting NEDD4L on atherosclerosis. Therefore, our review aims to fill this gap by analyzing the literature on NEDD4L concerning atherosclerosis occurrence. To achieve this goal, we performed a systematic literature search of reputable databases, including PubMed, Google Scholar, Web of Science, Scopus, and Embase. The inclusion criteria comprised peer-reviewed original studies using in vitro and animal models due to the unavailability of relevant clinical studies. Systematic reviews, meta-analyses, and articles that did not focus on the relationship between NEDD4L and atherosclerosis and those unrelated to this health condition were excluded. Studies not written in the English language were also excluded. The search strategy included studies from January 2000 to January 2025 in the final analysis to capture recent advancements. Following screening, five studies were included. Most of the included studies underscored NEDD4L’s role in increasing atherosclerosis plaque formation, but other studies indicated that stimulating NEDD4L may positively counter atherosclerosis plaque formation. Therefore, future research endeavors must address several limitations, which have been tentatively highlighted throughout the manuscript, for more informative research based on preclinical studies and to successfully translate the findings into clinical trials.

Sunil K. Joshi, Ariane Huang, Janét Pittsenbarger et al.

Not available.

Gözde Bozdal, Şeyma Arıcı Tüfekçi, Büşra Şahin et al.

Volatile organic compounds (VOCs) of essential oils (EOs) and solid phase microextract (SPME) obtained from the flower, leaf, and stem of Epilobium angustifolium L. were analyzed by GC-FID/MS. The EOs and SPMEs consist mainly of monoterpenes and aldehydes, which are major classes of compounds. Limonene was found to be a major compound in flower (HD: 42.9% vs. SPME: 95.5%), in leaf (HD: 60.3% vs. SPME: 4.7%), and in stem (HD: 49.06% vs. SPME: 93.6%). The antimicrobial activity of EOs and the solvent extracts (n-hexane, acetonitrile, and methanol) of E. angustifolium were screened in vitro against nine microorganisms. The EO of the leaf showed the best activity (10.2 µg/mL MIC) against Mycobacterium smegmatis. All the EOs and the solvent extracts gave moderate activity against the Staphylococcus aureus, Bacillus cereus, and M. smegmatis within the range of 10.2-1300.0 µg/mL MIC values. The best antibacterial activity was observed against S. aureus and B. cereus in the n-hexane extract of stem and methanol extract of flower samples.

Ryung Lee, Rahul Kumar, Jainam Shah et al.

Spaceflight-associated dry eye syndrome (SADES) has been reported among astronauts during both International Space Station (ISS) and Space Transportation System (STS) missions. As future missions extend beyond low Earth orbit, the physiological challenges of spaceflight include microgravity, radiation, and environmental stressors, which may further exacerbate the development of ocular surface disease. A deeper understanding of the underlying pathophysiology, along with the exploration of innovative countermeasures, is critical. In this review, we examine nanomedicine as a promising countermeasure for managing ophthalmic conditions in space, with the goal of enhancing visual health and mission readiness for long-duration exploration-class missions.

Yuan Zhang, Yali Jing

Background: Previous studies have suggested that type 2 diabetes mellitus (T2DM) is associated with poor bone health, including osteoporosis (OP) and osteopenia. The ZJU index, a novel calculation that integrates fasting plasma glucose (FPG), body mass index (BMI), triglyceride (TG), and alanine aminotransferase (ALT) to aspartate aminotransferase (AST) ratio, is strongly associated with glucolipid metabolism and insulin resistance (IR). In this study, we explored the association of ZJU with bone mineral density (BMD) and OP/osteopenia, and investigated the predictive effect of ZJU on OP/osteopenia in patients with T2DM. Methods: This cross-sectional study included 496 patients with T2DM aged>50 years. The clinical data were collected and the BMD of femoral neck (FN), left hip (LH), and lumbar spine (LS) were measured. The association between BMDs and ZJU levels was investigated by adjusting for covariates utilizing multiple linear regression analyses. Multivariable logistic regression was constructed to identify independent factors of OP and osteopenia, and receiver operating characteristic (ROC) curves were used to display the diagnostic performance according to the area under the ROC curve (AUC). Results: OP and osteopenia patients showed significantly higher ZJU levels than those with normal BMD in T2DM (39.387 ± 3.558, 38.112 ± 2.552 vs 35.192 ± 2.600, p < 0.001). Spearman's correlation analysis showed that ZJU was significantly negatively correlated with the BMD of FN (r = −0.39, p < 0.001), LH (r = −0.35, p < 0.001), and LS (r = -0.32, p < 0.001). The multiple linear regression indicated a negative association between ZJU and BMD of FN (β = −0.006, p = 0.009), LS (β = -0.155, p = 0.011) after adjusted for covariates. Meanwhile, the results of logistic regression revealed that the ZJU was a contributing factor to osteopenia and OP risk in T2DM individuals aged>50 years (OR 1.446, 95 % CI: 1.087–1.923, p = 0.011; OR 1.878, 95 % CI: 1.218–3.715, p = 0.039, respectively). ZJU provided the AUC value of 0.695 and 0.716 on osteopenia and OP in T2DM, respectively. Conclusions: A high ZJU index was significantly associated with an increasing risk of osteopenia and OP. The ZJU is expected to be a potential index for detecting decreased BMDs in middle-aged and elderly T2DM patients. Early intervention in T2DM patients with increased ZJU may further reduce the incidence of osteopenia and OP, in addition to focusing on independent biomarker in clinical practice.

Nafees Ahmed, Vishwas Gaur, Madhu Kamle et al.

Marco Conz, Francesca Scognamiglio, Ivan Donati et al.

Long-term solutions for cartilage repair after injury are currently being investigated, with most research aiming to exploit the regenerative and chondrogenic differentiation potential of stem-cell-based spheroids. The incorporation of the bioactive polymer CTL, a lactose-modified chitosan, into spheroids is a strategy to improve cell viability and accelerate type II collagen gene expression. In this work, the role of CTL in influencing the dynamics of spheroid formation and its interplay with cell membrane adhesion molecules (integrins and cadherins) and cytoskeletal components is elucidated. The results indicate that CTL is actively involved in the reorganization of cells into spheroids. An analysis of the effects of physical form of CTL (rehydrated polymer coating or polymer solution) in stimulating peculiar biological responses indicates that CTL matrix in spheroids facilitates an early phase of chondrogenic differentiation. Once the CTL matrix is included in spheroids, there is an increase in COL2A1 gene expression and matrix deposition, regardless of the initial physical form of CTL. Overall, these results contribute to a better understanding of the dynamics of spheroid formation in the presence of the polymer and on its bioactive role in mesenchymal stem cell spheroids.

Liu Hong, Hong Qian

The general theory of a complex system of nonlinear chemical reactions is a primary language of chemistry that includes chemical engineering and cellular biochemistry. Its significance as an analytical framework, however, has not been fully appreciated outside the community of physical chemists. In this review, we discuss the latest advances in the kinetics and Gibbsian thermodynamics of chemical reactions in a spatially homogeneous aqueous solution with a multiscale perspective on complex systems. From the microscopic level of single reaction events which are purely stochastic in continuous time, one at a time among a set of molecules, to the macroscopic chemical reaction systems in bulk in terms of deterministic rate equations, the mathematical descriptions of kinetic models for chemical reactions at different levels are presented in detail, with rigorous mathematical justifications presented. In parallel with the kinetics of chemical reactions, the irreversible thermodynamics of open systems and the stochastic thermodynamics along reactions trajectories are reviewed thoroughly. As a novel feature, the mathematical theory of large deviations is shown to play a pivotal role in the thermodynamics of chemical reactions in equilibrium and in irreversible processes. This review is expected to stimulate interests in and help defining multiscale phenomena and nonequilibrium thermodynamics in many research fields on population dynamics of interacting species using chemical reactions as an analytic paradigm.

Kiet Bennema ten Brinke, Koen Minartz, Vlado Menkovski

Simulating trajectories of dynamical systems is a fundamental problem in a wide range of fields such as molecular dynamics, biochemistry, and pedestrian dynamics. Machine learning has become an invaluable tool for scaling physics-based simulators and developing models directly from experimental data. In particular, recent advances in deep generative modeling and geometric deep learning enable probabilistic simulation by learning complex trajectory distributions while respecting intrinsic permutation and time-shift symmetries. However, trajectories of N-body systems are commonly characterized by high sensitivity to perturbations leading to bifurcations, as well as multi-scale temporal and spatial correlations. To address these challenges, we introduce STFlow (Spatio-Temporal Flow), a generative model based on graph neural networks and hierarchical convolutions. By incorporating data-dependent couplings within the Flow Matching framework, STFlow denoises starting from conditioned random-walks instead of Gaussian noise. This novel informed prior simplifies the learning task by reducing transport cost, increasing training and inference efficiency. We validate our approach on N-body systems, molecular dynamics, and human trajectory forecasting. Across these benchmarks, STFlow achieves the lowest prediction errors with fewer simulation steps and improved scalability.

Saransh Kumar Gupta, Lipika Dey, Partha Pratim Das et al.

This paper presents an ontology design along with knowledge engineering, and multilingual semantic reasoning techniques to build an automated system for assimilating culinary information for Indian food in the form of a knowledge graph. The main focus is on designing intelligent methods to derive ontology designs and capture all-encompassing knowledge about food, recipes, ingredients, cooking characteristics, and most importantly, nutrition, at scale. We present our ongoing work in this workshop paper, describe in some detail the relevant challenges in curating knowledge of Indian food, and propose our high-level ontology design. We also present a novel workflow that uses AI, LLM, and language technology to curate information from recipe blog sites in the public domain to build knowledge graphs for Indian food. The methods for knowledge curation proposed in this paper are generic and can be replicated for any domain. The design is application-agnostic and can be used for AI-driven smart analysis, building recommendation systems for Personalized Digital Health, and complementing the knowledge graph for Indian food with contextual information such as user information, food biochemistry, geographic information, agricultural information, etc.

S. H. Mejias, A. L. Cortajarena, R. Mincigrucci et al.

Understanding complex biological macromolecules, especially proteins, is vital for grasping their diverse chemical functions with direct impact in biology and pharmacology. While techniques like X-ray crystallography and cryo-electron microscopy have been valuable, they face limitations such as radiation damage and difficulties in crystallizing certain proteins. X-ray free-electron lasers (XFELs) offer promising solutions with their ultrafast, high-intensity pulses, potentially enabling structural determination before radiation damage occurs. However, challenges like low signal-to-noise ratio persist, particularly for single protein molecules. To address this, we propose a new method involving engineered protein scaffolds to create ordered arrays of proteins with controlled orientations, aiming at enhancing the signal at the detector. This innovative strategy has the potential to address signal limitations and protein crystallization issues, opening avenues for determining protein structures under physiological conditions. Moreover, it holds promise for studying conformational changes resulting from photo-induced changes, protein-drug and/or protein-protein interactions. Indeed, the prediction of protein-protein interactions, fundamental to numerous biochemical and cellular processes, and the time-dependent conformational changes they undergo, continue to pose a considerable challenge in biology and biochemistry.