Browse Articles

Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging

IDH status dictates oHSV mediated metabolic reprogramming affecting anti-tumor immunity

Abstract Identification of isocitrate dehydrogenase (IDH) mutations has uncovered the crucial role of metabolism in gliomagenesis. Oncolytic herpes virus (oHSV) initiates direct tumor debulking by tumor lysis and activates anti-tumor immunity, however, little is known about the role of glioma metabolism in determining oHSV efficacy. Here we identify that oHSV rewires central carbon metabolism increasing glucose utilization towards oxidative phosphorylation and shuttling glutamine towards reductive carboxylation in IDH wildtype glioma. The switch in metabolism results in increased lipid synthesis and cellular ROS. PKC induces ACSL4 in oHSV treated cells leading to lipid peroxidation and ferroptosis. Ferroptosis is critical to launch an anti-tumor immune response which is important for viral efficacy. Mutant IDH (IDHR132H) gliomas are incapable of reductive carboxylation and hence ferroptosis. Pharmacological blockade of IDHR132H induces ferroptosis and anti-tumor immunity. This study provides a rationale to use an IDHR132H inhibitor to treat high grade IDH-mutant glioma patients undergoing oHSV treatment.

Competitive enzyme linked aptamer based assay for salivary melatonin detection

Author Correction: Cortical representations of affective pain shape empathic fear in male mice

ZFP36 regulates the osteogenic differentiation of adipose-derived mesenchymal stem cells in osteoporosis by mediating KLF3 mRNA degradation

Shapeshifting origami material shrinks when twisted

Conformational changes in the motor ATPase CpaF facilitate a rotary mechanism of Tad pilus assembly

Abstract The type IV pilus family uses PilT/VirB11-like ATPases to rapidly assemble and disassemble pilin subunits. Among these, the tight adherence (Tad) pilus performs both functions using a single bifunctional ATPase, CpaF. Here, we determine three conformationally distinct structures of CpaF hexamers with varying nucleotide occupancies by cryo-electron microscopy. Analysis of these structures suggest ATP binding and hydrolysis expand and rotate the hexamer pore clockwise while subsequent ADP release contracts the ATPase. Truncation of the intrinsically disordered region of CpaF in Caulobacter crescentus equally reduces pilus extension and retraction events observed using fluorescence microscopy, but does not reduce ATPase activity. AlphaFold3 modeling suggests that CpaF and other motors of the type IV filament superfamily employ conserved secondary structural features to engage their respective platform proteins. From these data, we propose that CpaF uses a clockwise, rotary mechanism of catalysis to assemble a right-handed, helical Tad pilus, a process broadly applicable to other single motor systems.

Enhanced detection of glioblastoma vasculature with superparamagnetic iron oxide nanoparticles and MRI

Abstract Detecting glioblastoma infiltration in the brain is challenging due to limited MRI contrast beyond the enhancing tumour core. This study aims to investigate the potential of superparamagnetic iron oxide nanoparticles (SPIONs) as contrast agents for improved detection of diffuse brain cancer. We examine the distribution and pharmacokinetics of SPIONs in glioblastoma models with intact and disrupted blood-brain barriers. Using MRI, we imaged RN1-luc and U87MG mice injected with Gadovist and SPIONs, observing differences in blood-brain barrier permeability. Peripheral imaging showed strong uptake of nanoparticles in the liver and spleen, while vascular and renal signals were transient. Susceptibility gradient mapping enabled positive nanoparticle contrast within tumours and provided additional information on tumour angiogenesis. This approach offers a novel method for detecting diffuse brain cancer. Our findings demonstrate that SPIONs enhance glioblastoma detection beyond conventional MRI, providing insights into tumour angiogenesis and opening new avenues for early diagnosis and targeted treatment strategies.

Cancer vaccine momentum builds, but US funding cuts raise concerns

DHODH modulates immune evasion of cancer cells via CDP-Choline dependent regulation of phospholipid metabolism and ferroptosis

Musical note recognition based on the upper adjacent harmonics without the presence of the fundamental frequency

Functional impact of splicing variants in the elaboration of complex traits in cattle

Abstract GWAS conducted directly on imputed whole genome sequence have led to the identification of numerous genetic variants associated with agronomic traits in cattle. However, such variants are often simply markers in linkage disequilibrium with the actual causal variants, which is a limiting factor for the development of accurate genomic predictions. It is possible to identify causal variants by integrating information on how variants impact gene expression into GWAS output. RNA splicing plays a major role in regulating gene expression. Thus, assessing the effect of variants on RNA splicing may explain their function. Here, we use a high-throughput strategy to functionally analyse putative splice-disrupting variants in the bovine genome. Using GWAS, massively parallel reporter assay and deep learning algorithms designed to predict splice-disrupting variants, we identify 38 splice-disrupting variants associated with complex traits in cattle, three of which could be classified as causal. Our results indicate that splice-disrupting variants are widely found in the quantitative trait loci related to these phenotypes. Using our combined approach, we also assess the validity of splicing predictors originally developed to analyse human variants in the context of the bovine genome.

High glycosylated serum protein to high density lipoprotein cholesterol ratios are predictive of worse acute on chronic liver failure prognoses

Author Correction: Recapitulation of premature ageing with iPSCs from Hutchinson–Gilford progeria syndrome

Targeted plasma proteomics reveals organ damage signatures of AIDS- and noncommunicable disease-related deaths in people with HIV

Smoking status and voting behaviour and intentions in countries of the former Soviet Union

Abstract Smokers experience multiple disadvantages throughout their lives, yet there is another disadvantage, political, that is less widely recognised. Smokers are less likely to vote but only so far in studies conducted in Western democratic regimes. This cross-sectional study aimed to examine the association between current smoking and voting behaviour and intentions in nine countries of the former Soviet Union (FSU). Data were analysed from 18,000 individuals aged ≥ 18 in Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine, collected in the Health in Times of Transition (HITT) survey in 2010/11. Information was obtained on smoking status and voting behaviour and intentions. In a fully adjusted logistic regression analysis, current smoking was associated with significantly higher odds of ‘never voting’ (not having voted in the past or intending to vote in future) in the pooled sample (OR: 1.29, 95% CI 1.13–1.47). In stratified analyses, smoking was associated with never voting in women but not men and in young but not middle-aged or older adults. The smoking-never voting association was observed in flawed democracies (OR: 1.57, 95% CI 1.07–2.32) and hybrid regimes (OR: 1.31, 95% CI 1.08–1.59) but not in authoritarian regimes (OR: 1.02, 95% CI 0.81–1.29). Smoking is associated with never voting in these FSU countries although not in all population subgroups or types of political regime. A necessary task for future research will be determining the factors associated with not voting among smokers in these countries.

Internal lattice oxygen sites invert product selectivity in electrocatalytic alkyne hydrogenation over copper catalysts

Pan-cancer analysis reveals immunological and prognostic significance of CCT5 in human tumors

Abstract The chaperonin containing TCP1 subunit 5 (CCT5) is believed to function as a tumor driver. However, a systematic pan-cancer analysis of CCT5 is still lacking. Therefore, this study aimed to identify the potential role of CCT5 in different types of tumors. This study comprehensively investigated the gene expression, proteomic expression, immune infiltration, DNA methylation, genetic alterations, correlation with TMB and MSI, drug sensitivity, enrichment analysis, and prognostic significance of CCT5 in 33 different tumors based on the TIMER2.0, GEPIA2, UALCAN, SMART, cBioPortal, GSCA databases, and TCGAplot R package. The results revealed significant CCT5 overexpression in most tumors and was significantly associated with poor OS and DFS in different tumor types. Reduced promoter and N-shore methylation of CCT5, indicating its potential oncogenic and epigenetic roles. Amplification was the most common type of CCT5 alterations. Immune infiltration analysis revealed a strong correlation between CCT5 and different immune cells. CCT5 exhibited a significant correlation with TMB and MSI in KIRC and STAD. Furthermore, enrichment analysis revealed associations between CCT5 and cell cycle pathway and various cellular functions. These findings suggested that CCT5 might serve as a potential prognostic biomarker and target for immunotherapy in various cancers.

In-sensor compressing via programmable optoelectronic sensors based on van der Waals heterostructures for intelligent machine vision

A novel temporal classification prototype network for few-shot bearing fault detection

Abstract In the process of industrial production, bearing fault detection has always been a hot issudza20000528@163.comsolved. At present, the problem of less fault data samples in the field of fault detection has caused great trouble to the research of deep learning. In the application of industrial fault detection, which is difficult to obtain massive data, it is easy to lead to the lack of fitting of neural network training and many generalization problems. To solve the above problems, this paper proposes an improved and more efficient method of few-shot supervised learning, which is called the Temporal Classification Prototype Network (TCPN). This model is designed to maintain both training efficacy and generalization capabilities under conditions of data scarcity. Initially, Fourier transform is employed to accentuate the frequency domain characteristics of the fault section in the bearing signal before it is input into the model, thereby enabling the subsequent model to concentrate on distinguishing between normal and fault signals. Subsequently, discrete data sample points are transformed into points within the feature space via our Enhanced Temporal Convolutional Network(ETCN). In our investigation, we utilize the features of the support set as anchors within the feature space and employ similarity measures as the basis for classification, thus developing a more effective comparative learning classifier known as the ContractSim Classifier (CSC). Within the CSC, the model learns the data features of the query set, which are then back-propagated to refine our model. The proposed TCPN model has been evaluated across four standard bearing datasets, corroborating its few-shot learning proficiency through k-shot experiments. In comparative model experiments, our TCPN outperforms baseline models, while the ablation study confirms the rationality and robustness of our module integration.