G-cleave LC3B biosensor: monitoring autophagy and assessing resveratrol's synergistic impact on doxorubicin-induced apoptosis in breast cancer cells.

Autophagy, a crucial process in cancer, is closely intertwined with both tumor progression and drug resistance development. However, existing methods used to assess autophagy activity often pose invasiveness and time-related constraints, limiting their applicability in preclinical drug investigations. In this study, we developed a non-invasive autophagy detection system (NIADS-autophagy, also called G-cleave LC3B biosensor) by integrating a split-luciferase-based biosensor with an LC3B cleavage sequence, which swiftly identified classic autophagic triggers, such as Earle's Balanced Salt Solution and serum deprivation, through protease-mediated degradation pathways.

Fluvastatin, an HMG-CoA reductase inhibitor, exerts protective effect against NMDA-induced seizure by increasing the seizure threshold and modulating membrane excitability in embryonic rat cortical neuron.

Background: Epilepsy affects nearly 50 million people worldwide. Previous studies have indicated the neuroprotective effects of statin on several neuropathological conditions. However, it is very much unknown whether fluvastatin was able to alter the seizure types related to neuronal excitability and progression mediated by NMDA receptor activation, and the mechanisms involved in these actions are not completely understood so far.

DeepKlapred: A deep learning framework for identifying protein lysine lactylation sites via multi-view feature fusion.

Lysine lactylation (Kla) is a post-translational modification (PTM) that holds significant importance in the regulation of various biological processes. While traditional experimental methods are highly accurate for identifying Kla sites, they are both time-consuming and labor-intensive. Recent machine learning advances have enabled computational models for Kla site prediction.

dbAMP 3.0: updated resource of antimicrobial activity and structural annotation of peptides in the post-pandemic era.

Antimicrobial resistance is one of the most urgent global health threats, especially in the post-pandemic era. Antimicrobial peptides (AMPs) offer a promising alternative to traditional antibiotics, driving growing interest in recent years. dbAMP is a comprehensive database offering extensive annotations on AMPs, including sequence information, functional activity data, physicochemical properties and structural annotations.

dbPTM 2025 update: comprehensive integration of PTMs and proteomic data for advanced insights into cancer research.

Post-translational modifications (PTMs) are essential for modulating protein function and influencing stability, activity and signaling processes. The dbPTM 2025 update significantly expands the database to include over 2.79 million PTM sites, of which 2.

Human DCP1 is crucial for mRNA decapping and possesses paralog-specific gene regulating functions.

The mRNA 5'-cap structure removal by the decapping enzyme DCP2 is a critical step in gene regulation. While DCP2 is the catalytic subunit in the decapping complex, its activity is strongly enhanced by multiple factors, particularly DCP1, which is the major activator in yeast. However, the precise role of DCP1 in metazoans has yet to be fully elucidated.

Robust and Sustained STING Pathway Activation via Hydrogel-Based In Situ Vaccination for Cancer Immunotherapy.

The stimulator of interferon genes (STING) pathway is crucial for tumor immunity, leading to the exploration of STING agonists as potential immunotherapy adjuvants. However, their clinical application faces obstacles including poor pharmacokinetics, transient activation, and an immunosuppressive tumor microenvironment (TME). Addressing these limitations, our study aims to develop an injectable silk fibroin hydrogel-based in situ vaccine.

Exploring prognostic implications of miRNA signatures and telomere maintenance genes in kidney cancer.

Kidney cancer, particularly clear cell renal cell carcinoma (KIRC), presents significant challenges in disease-specific survival. This study investigates the prognostic potential of microRNAs (miRNAs) in kidney cancers, including KIRC and kidney papillary cell carcinoma (KIRP), focusing on their interplay with telomere maintenance genes. Utilizing data from The Cancer Genome Atlas, miRNA expression profiles of 166 KIRC and 168 KIRP patients were analyzed.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published.

ACP-CapsPred: an explainable computational framework for identification and functional prediction of anticancer peptides based on capsule network.

Cancer is a severe illness that significantly threatens human life and health. Anticancer peptides (ACPs) represent a promising therapeutic strategy for combating cancer. In silico methods enable rapid and accurate identification of ACPs without extensive human and material resources.

An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria.

The rise of antibiotic resistance necessitates effective alternative therapies. Antimicrobial peptides (AMPs) are promising due to their broad inhibitory effects. This study focuses on predicting the minimum inhibitory concentration (MIC) of AMPs against whom-priority pathogens: ATCC 25923, ATCC 25922, and ATCC 27853.

Inference of single-cell network using mutual information for scRNA-seq data analysis.

Background: With the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression profiles at a single-cell resolution has become possible. It has been known that network modeling by estimating the associations between genes could better reveal dynamic changes in biological systems. However, accurately constructing a single-cell network (SCN) to capture the network architecture of each cell and further explore cell-to-cell heterogeneity remains challenging.

Multi-epitope vaccine design of African swine fever virus considering T cell and B cell immunogenicity.

T and B cell activation are equally important in triggering and orchestrating adaptive host responses to design multi-epitope African swine fever virus (ASFV) vaccines. However, few design methods have considered the trade-off between T and B cell immunogenicity when identifying promising ASFV epitopes. This work proposed a novel Pareto front-based ASFV screening method PFAS to identify promising epitopes for designing multi-epitope vaccines utilizing five ASFV Georgia 2007/1 sequences.

One-month daily and three-month weekly rifapentine plus isoniazid are comparable in completion rate and safety for latent tuberculosis infection in non-HIV Population: a randomized controlled trial.

Objectives: The weekly rifapentine plus isoniazid for 3 months (3HP) improves completion rate of latent tuberculosis infection treatment, but flu-like symptoms are common. The novel 1HP regimen, involving daily rifapentine plus isoniazid for 28 days, has demonstrated low toxicity in HIV-infected populations. We aimed to investigate whether 1HP has a lower incidence rate of systemic drug reaction (SDR) compared with 3HP during treatment in non-HIV populations.

The non-mitotic role of HMMR in regulating the localization of TPX2 and the dynamics of microtubules in neurons.

A functional nervous system is built upon the proper morphogenesis of neurons to establish the intricate connection between them. The microtubule cytoskeleton is known to play various essential roles in this morphogenetic process. While many microtubule-associated proteins (MAPs) have been demonstrated to participate in neuronal morphogenesis, the function of many more remains to be determined.

Discovery of Novel Spike Inhibitors against SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the current coronavirus disease pandemic. With the rapid evolution of variant strains, finding effective spike protein inhibitors is a logical and critical priority. Angiotensin-converting enzyme 2 (ACE2) has been identified as the functional receptor for SARS-CoV-2 viral entry, and thus related therapeutic approaches associated with the spike protein-ACE2 interaction show a high degree of feasibility for inhibiting viral infection.

Glycyrrhizic acid conjugates with amino acid methyl esters target the main protease, exhibiting antiviral activity against wild-type and nirmatrelvir-resistant SARS-CoV-2 variants.

COVID-19 pandemic is predominantly caused by SARS-CoV-2, with its main protease, Mpro, playing a pivotal role in viral replication and serving as a potential target for inhibiting different variants. In this study, potent Mpro inhibitors were identified from glycyrrhizic acid (GL) derivatives with amino acid methyl/ethyl esters. Out of the 17 derivatives semisynthesized, Compounds 2, 6, 9, and 15, with methionine methyl esters, D-tyrosine methyl esters, glutamic acid methyl esters, and methionines in the carbohydrate moiety, respectively, significantly inhibited wild-type SARS-CoV-2 Mpro-mediated proteolysis, with IC50 values ranging from 0.

Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease.

Objectives: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing.

Methods: We analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M.

A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

Antiviral peptides (AVPs) have shown potential in inhibiting viral attachment, preventing viral fusion with host cells and disrupting viral replication due to their unique action mechanisms. They have now become a broad-spectrum, promising antiviral therapy. However, identifying effective AVPs is traditionally slow and costly.

Guided diffusion for molecular generation with interaction prompt.

Molecular generative models have exhibited promising capabilities in designing molecules from scratch with high binding affinities in a predetermined protein pocket, offering potential synergies with traditional structural-based drug design strategy. However, the generative processes of such models are random and the atomic interaction information between ligand and protein are ignored. On the other hand, the ligand has high propensity to bind with residues called hotspots.

The impact of Lacticaseibacillus paracasei GMNL-143 toothpaste on gingivitis and oral microbiota in adults: a randomized, double-blind, crossover, placebo-controlled trial.

Background: This study examines the oral health benefits of heat-killed Lacticaseibacillus paracasei GMNL-143, particularly its potential in oral microbiota alterations and gingivitis improvement.

Methods: We assessed GMNL-143's in vitro interactions with oral pathogens and its ability to prevent pathogen adherence to gingival cells. A randomized, double-blind, crossover clinical trial was performed on gingivitis patients using GMNL-143 toothpaste or placebo for four weeks, followed by a crossover after a washout.