Classification-based pathway analysis using GPNet with novel P-value computation.

Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.

Clearing the path for whole-mount labeling and quantification of neuron- and vessel-density in adipose tissue.

White adipose tissue (WAT) comprises a plethora of cell types beyond adipocytes forming a regulatory network that ensures systemic energy homeostasis. Intertissue communication is facilitated by metabolites and signaling molecules that are spread by vasculature and nerves. Previous works indicated that WAT responds to environmental cues by adapting the abundance of these "communication routes", however, high intra-tissue heterogeneity questions the informative value of bulk or single cell analyses and underscores the necessity of whole-mount imaging.

Structural basis for human NKCC1 inhibition by loop diuretic drugs.

Na-K-Cl cotransporters functions as an anion importers, regulating trans-epithelial chloride secretion, cell volume, and renal salt reabsorption. Loop diuretics, including furosemide, bumetanide, and torsemide, antagonize both NKCC1 and NKCC2, and are first-line medicines for the treatment of edema and hypertension. NKCC1 activation by the molecular crowding sensing WNK kinases is critical if cells are to combat shrinkage during hypertonic stress; however, how phosphorylation accelerates NKCC1 ion transport remains unclear.

Dual modality feature fused neural network integrating binding site information for drug target affinity prediction.

Accurately predicting binding affinities between drugs and targets is crucial for drug discovery but remains challenging due to the complexity of modeling interactions between small drug and large targets. This study proposes DMFF-DTA, a dual-modality neural network model integrates sequence and graph structure information from drugs and proteins for drug-target affinity prediction. The model introduces a binding site-focused graph construction approach to extract binding information, enabling more balanced and efficient modeling of drug-target interactions.

SARS-CoV-2 S-protein expression drives syncytia formation in endothelial cells.

SARS-CoV-2 is a viral infection, best studied in the context of epithelial cell infection. Epithelial cells, when infected with SARS-CoV-2 express the viral S-protein, which causes host cells to fuse together into large multi-nucleated cells known as syncytia. Because SARS-CoV-2 infections also frequently present with cardiovascular phenotypes, we sought to understand if S-protein expression would also result in syncytia formation in endothelial cells.

Merging metabolic modeling and imaging for screening therapeutic targets in colorectal cancer.

Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved a novel machine learning-based method to computationally screen, in a high-throughput manner, the effects of enzyme perturbations predicted by a computational model of CRC metabolism.

Platelet-white cell ratio is more strongly associated with mortality than other common risk ratios derived from complete blood counts.

Complete blood count indices and their ratios are associated with adverse clinical outcomes for many acute illnesses, but the mechanisms generating these associations are not fully understood. Recent identification of a consistent pattern of white blood cell and platelet count co-regulation during acute inflammatory recovery provides a potentially unifying explanation. Here we show that the platelet-to-white-cell ratio, which was selected based on this conserved recovery pattern, is more strongly associated with mortality than other blood count markers and ratios in four important illnesses involving acute inflammation: COVID-19, acute heart failure, myocardial infarction, and stroke.

Health networking on cancer in the European Union: a 'green paper' by the EU Joint Action on Networks of Expertise (JANE).

Health networking is in principle a formidable instrument to address many challenges posed by cancer, one of the two most common and most lethal non-communicable chronic diseases. The European Union (EU)'s Beating Cancer Plan foresaw the addition of new health networks to the four already existing European Reference Networks on rare cancers: the Network of Comprehensive Cancer Centres and several networks of expertise (NoEs), which will be shortly deployed on items as complex and poor-prognosis cancers, palliative care, survivorship, personalised primary and secondary prevention, omic technologies, hi-tech medical resources, and cancers in adolescents and young adults. The community of experts of the EU Joint Action, due to build such NoEs, has drafted this 'green paper', incorporating 13 open questions, in an effort to foster discussion on some open questions about health networking on cancer in the EU.

Proteomic Characterization of NEDD4 Unveils Its Potential Novel Downstream Effectors in Gastric Cancer.

The E3 ubiquitin ligase neural precursor cell-expressed developmentally down-regulated 4 (NEDD4) is involved in various cancer signaling pathways, including PTEN/AKT. However, its role in promoting gastric cancer (GC) progression is unclear. This study was conducted to elucidate the role of NEDD4 in GC progression.

The Developmental Origin of Novel Complex Morphological Traits in Lepidoptera.

Novel traits in the order Lepidoptera include prolegs in the abdomen of larvae, scales, and eyespot and band color patterns in the wings of adults. We review recent work that investigates the developmental origin and diversification of these four traits from a gene-regulatory network (GRN) perspective. While prolegs and eyespots appear to derive from distinct ancestral GRNs co-opted to novel body regions, scales derive from in situ modifications of a sensory bristle GRN.

Evaluation of tumor-colonizing strains using the chick chorioallantoic membrane model.

The chick embryo chorioallantoic membrane (CAM) tumor model is a valuable preclinical model for studying the tumor-colonizing process of serovar Typhimurium. It offers advantages such as cost-effectiveness, rapid turnaround, reduced engraftment issues, and ease of observation. In this study, we explored and validated the applicability of the partially immune-deficient CAM tumor model.

Temporal Genomic Analysis of Homogeneous Tumor Models Reveals Key Regulators of Immune Evasion in Melanoma.

In this study, we find that Mif expression is associated with tumor growth and aggressiveness, specifically in tumors with low heterogeneity. These findings could facilitate the development of new strategies to treat patients with homogeneous, high MIF-expressing tumors that are unresponsive to immune checkpoint therapy.

An Optimized Protocol for Simultaneous Propagation of Patient-derived Organoids and Matching CAFs.

Recurrent hormone receptor-positive (HR+) breast cancer is a leading cause of cancer mortality in women. Recurrence and resistance to targeted therapies have been difficult to study due to the long clinical course of the disease, the complex nature of resistance, and the lack of clinically relevant model systems. Existing models are limited to a few HR+ cell lines, organoid models, and patient-derived xenograft models, all lacking components of the human tumor microenvironment.

Multiomics characterization of breast angiosarcoma from an Asian cohort reveals enrichment for angiogenesis signaling pathway and tumor-infiltrating macrophages.

Introduction: Recent epidemiological data suggests a rising incidence of breast angiosarcoma (AS-B) in the Western population, with over two-thirds related to irradiation or chronic lymphedema. However, unlike head and neck angiosarcoma (AS-HN), AS-B disease characteristics in Asia remain unclear.

Methods: We examined clinical patterns of angiosarcoma patients (n = 176) seen in an Asiantertiary cancer center from 1999 to 2021, and specifically investigated the molecular and immune features of AS-B in comparison to AS-HN.

A gut instinct for childhood leukemia prevention: microbiome-targeting recommendations aimed at parents and caregivers.

Childhood leukemia accounts for 30% of all pediatric cancer cases with acute lymphoblastic leukemia (ALL) being the most common subtype. Involvement of the gut microbiome in ALL development has recently garnered interest due to an increasing recognition of the key contribution the microbiome plays in maintaining the immune system's homeostatic balance. Commensal gut microbiota provide a first line of defense against different pathogens and gut microbiome immaturity has been implicated in ALL pathogenesis.

The multi-omics signatures of telomere length in childhood.

Background: Telomere length is an important indicator of biological age and a complex multi-factor trait. To date, the telomere interactome for comprehending the high-dimensional biological aspects linked to telomere regulation during childhood remains unexplored. Here we describe the multi-omics signatures associated with childhood telomere length.

GenVarLoader: An accelerated dataloader for applying deep learning to personalized genomics.

Deep learning sequence models trained on personalized genomics can improve variant effect prediction, however, applications of these models are limited by computational requirements for storing and reading large datasets. We address this with GenVarLoader, which stores personalized genomic data in new memory-mapped formats with optimal data locality to achieve ~1,000x faster throughput and ~2,000x better compression compared to existing alternatives.

Combinatorial phenotypic landscape enables bacterial resistance to phage infection.

Success of phage therapies is limited by bacterial defenses against phages. While a large variety of anti-phage defense mechanisms has been characterized, how expression of these systems is distributed across individual cells and how their combined activities translate into protection from phages has not been studied. Using bacterial single-cell RNA sequencing, we profiled the transcriptomes of ~50,000 cells from cultures of a human pathobiont, , infected with a lytic bacteriophage.

From Pioneering Discoveries to Innovative Therapies: A Journey Through the History and Advancements of Nanoparticles in Breast Cancer Treatment.

Nanoparticle technology has revolutionized breast cancer treatment by offering innovative solutions addressing the gaps in traditional treatment methods. This paper aimed to comprehensively explore the historical journey and advancements of nanoparticles in breast cancer treatment, highlighting their transformative impact on modern medicine. The discussion traces the evolution of nanoparticle-based therapies from their early conceptualization to their current applications and future potential.

Detection of alteration in carotid artery volumetry using standard-of-care computed tomography surveillance scans following unilateral radiation therapy for early-stage tonsillar squamous cell carcinoma survivors: a cross-sectional internally-matched carotid isodose analysis.

Aim: This study leveraged standard-of-care CT scans of patients receiving unilateral radiotherapy (RT) for early tonsillar cancer to detect volumetric changes in the carotid arteries, and determine whether there is a dose-response relationship.

Methods: Disease-free cancer survivors (>3 months since therapy and age > 18 years) treated with intensity modulated RT for early (T1-2, N0-2b) tonsillar cancer with pre- and post-therapy contrast-enhanced CT scans available were included. Patients treated with definitive surgery, bilateral RT, or additional RT before the post-RT CT scan were excluded.

Molecular docking and molecular dynamics simulation studies of inhibitor candidates against 3-hydroxykynurenine transaminase and implications on vector control.

Isoxazole and oxadiazole derivatives inhibiting 3-hydroxykynurenine transaminase (3HKT) are potential larvicidal candidates. This study aims to identify more suited potential inhibitors of 3HKT (3HKT) through molecular docking and molecular dynamics simulation. A total of 958 compounds were docked against 3HKT (PDB ID: 2CH2) using Autodock vina and Autodock4.

Intratumor heterogeneity of HPV integration in HPV-associated head and neck cancer.

Integration of human papillomavirus (HPV) into the host genome drives HPV-positive head and neck squamous cell carcinoma (HPV HNSCC). Whole-genome sequencing of 51 tumors revealed intratumor heterogeneity of HPV integration, with 44% of breakpoints subclonal, and a biased distribution of integration breakpoints across the HPV genome. Four HPV physical states were identified, with at least 49% of tumors progressing without integration.

The First Multiomics Association Study of Trace Element and Mineral Concentration and RNA Sequencing Profiles in Human Cancers.

Integration of various types of omics data is an important trend in contemporary molecular oncology. In this regard, high-throughput analysis of trace and essential elements in cancer biosamples is an emerging field that has not yet been sufficiently addressed. For the first time, we simultaneously obtained gene expression profiles (RNA sequencing) and essential and trace element profiles (inductively coupled plasma mass spectrometry) for a set of human cancer samples.

PSMA-targeted delivery of docetaxel in prostate cancer using small-sized PDA-based micellar nanovectors.

In this study, we present the first comparative analysis of active and passive drug delivery systems for docetaxel (DTX) in prostate cancer using supramolecular self-assembled micellar nanovectors. Specifically, we developed two novel micelles based on polydiacetylenic amphiphiles (PDA) for passive and active targeting. The active targeting micelles were designed with a prostate-specific membrane antigen (PSMA) ligand, ACUPA, to facilitate recognition by PSMA-positive cancer cells.