Browse Articles

Synergistic induction of apoptosis by the epigenetic modulator decitabine and metformin in gastric cancer cells highlights the potential for combination therapy

Catalytic Asymmetric Total Synthesis of Grisemycin, a Thioangucycline Polyketide

SLIT3 fragments orchestrate neurovascular expansion and thermogenesis in brown adipose tissue

Abstract Brown adipose tissue is an evolutionary innovation in placental mammals that regulates body temperature through adaptive thermogenesis. Cold exposure activates brown adipose tissue thermogenesis through coordinated induction of brown adipogenesis, angiogenesis, and sympathetic innervation; however, how these processes are coordinated remains unclear. Here, we show that fragments of Slit guidance ligand 3 (SLIT3) drive crosstalk among adipocyte progenitors, endothelial cells, and sympathetic nerves. Adipocyte progenitors secrete SLIT3, which is cleaved into functionally distinct SLIT3-N and SLIT3-C fragments that independently promote angiogenesis and sympathetic innervation. We identify PLXNA1 as a receptor for SLIT3-C and demonstrate its essential role in sympathetic innervation of brown adipose tissue. Moreover, we identify BMP1 as the first SLIT protease described in vertebrates. Coordinated neurovascular expansion mediated by distinct SLIT3 fragments provides a bifurcated yet integrated mechanism that ensures a synchronized brown adipose tissue response to environmental challenges. Finally, this study reveals a previously unrecognized role for adipocyte progenitors in regulating tissue innervation.

Mini-batch size sensitivity in deep residual networks for short-term load forecasting: an empirical study

Correction to “Shaping the Glycan Landscape: Hidden Relationships between Linkage and Ring Distortions Induced by Carbohydrate-Active Enzymes”

LSD1 inhibitor, TAS1440, disrupts INSM1-LSD1 complex activating tumor-suppressive pathways via transcriptional reprogramming in neuroendocrine SCLC

Multifaceted biological and computational assessment of aromatic and N-heteroaromatic non-substituted thiosemicarbazones

Successive Magnetic Transitions Enable an Ultrawide Temperature Window of Zero Thermal Expansion in (Hf,Ti)Fe _2+x

Therapeutic potential of dihydronicotinamide riboside (NRH) on obesity and glucose intolerance in mice

An explainable AI-driven hybrid feature selection approach for coronary artery disease diagnosis

Abstract Coronary artery disease (CAD), where the heart does not get enough oxygen-rich blood due to a buildup of fatty matter, is a leading cause of death worldwide. Since its symptoms may not be recognized until a cardiac attack occurs, its early diagnosis is crucial. In this paper, we introduce the SHAP Optimized Wrapper (SHOW) feature selection algorithm, which works in two steps. First, a SHapley Additive exPlanations (SHAP) method is developed using XGBoost, Random Forest (RF), and Support Vector Machine (SVM) classifiers, to rank the features based on their diagnostic significance. Second, an optimized sequential forward selection wrapper technique is employed, whereby the ranked features are evaluated to select the optimal subset. To validate the algorithm, it is used in seven classifiers to classify three public domain CAD data sets. The classifiers are XGBoost, RF, SVM, Decision Tree (DT), Logistic Regression (LR), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP). The data sets are the Z-Alizadeh Sani, Cleveland, and Statlog. Leveraging stratified 10-fold cross-validation and delicate hyperparameter tuning, the results reveal that the SHOW algorithm significantly outperforms 14 state-of-the-art competitive algorithms in terms of accuracy and the number of selected features, while also demonstrating favorable performance in clinically relevant metrics such as sensitivity, specificity, AUC, and F1-score. For example, using the XGBoost classifier, the algorithm selects 14 features (out of 55) from the Z-Alizadeh Sani data set, achieving 93.79% accuracy, 93.98% sensitivity, 89.81% specificity, 0.97 AUC, and 93.98% F1-score; 5 features (out of 13) from the Cleveland data set, achieving 86.52% accuracy, 88.55% sensitivity, 85% specificity, 0.89 AUC, and 84.84% F1-score; and 5 features (out of 13) from the Statlog data set, achieving 87.78% accuracy, 80% sensitivity, 92.67% specificity, 0.90 AUC, and 85.18% F1-score. These figures are not matched by any of the 14 competitive algorithms.

Automated Discovery of Algorithms for Molecular Electronic Structure Calculations Using Physics-Informed Program Synthesis

A highly energy-efficient multi-core neuromorphic architecture for training deep spiking neural networks

Abstract There is a growing necessity for edge training to adapt to dynamically changing environments. Neuromorphic computing represents a significant pathway for highly efficient intelligent computation in energy-constrained edges, but existing neuromorphic architectures lack the ability of directly training spiking neural networks based on backpropagation. We developed a multi-core neuromorphic architecture with Feedforward-Propagation, Back-Propagation, and Weight-Gradient engines in each core, supporting highly efficient parallel computing at both the engine and core levels, achieving 190% ~ 330% performance of Jetson Orin. It combines various data flows and sparse computation optimization by fully leveraging the sparsity in spiking neural network training, obtaining a high energy efficiency of 1.05TFLOPS/W@ FP16 @ 28 nm, 55 ~ 85% reduction of memory access compared to A100 GPU in the training. Additionally, we deployed the architecture on Field Programmable Gate Arrays, successfully demonstrating 20-core deep spiking network training and 5-worker federated learning. Our study develops the first multi-core neuromorphic architecture supporting direct training of spiking neural network, facilitating neuromorphic computing in edge-learnable applications.

Cognitive offloading reduces internal memory processing in children

Helicity-Biased Light-Driven Rolling of Twisted Crystals

Suppression of pathological oscillations with transcranial focused ultrasound in Parkinson’s disease

Abstract Transcranial ultrasound stimulation (TUS) is an emerging method for non-invasive neuromodulation of deep brain structures. However, to date, there is no evidence that TUS can directly modulate disease-related pathological oscillations in the same direction as known therapies. Inspired by clinical deep brain stimulation, in this randomised controlled cross-over study we probed the effects of pallidal TUS pulsed at 130 Hz on subthalamic beta-band activity, a biomarker in Parkinson’s Disease (PD) in four male participants with PD. Beta-band power reduced in the ipsilateral subthalamic nucleus (STN) by 10.34% (95% CI:3.81% to 16.87%, p < 0.05, false discovery rate (FDR) adjusted). Beta power reduction was correlated between the ipsilateral ( R 2  = 0.980, p < 0.05, FDR adjusted), but not contralateral, STN and primary motor cortex. Bradykinesia, as measured by change in reaction time, was also reduced by 17.70% (95% CI:8.95% to 26.41%, p < 0.05, FDR adjusted). In this proof of concept study, we demonstrate that TUS can suppress pathological oscillations, potentially opening the door for therapeutic TUS (NCT06932185).

PrimerAST: A predictive machine learning tool for primer design and quality assessment

Formally Triplet Aluminyl Anions within the [Al ₂ Pd ₂ ] ^2– Cluster Stabilized by All-Metal Double Aromaticity

First-line Nivolumab plus FOLFOXIRI/Bevacizumab in advanced RAS/BRAF-mutated colorectal cancer: efficacy, safety and biomarker discovery from the phase II NIVACOR trial

Abstract Immunotherapy achieved remarkable results in patients with deficient mismatch repair (dMMR)/microsatellite instable (MSI) metastatic colorectal carcinoma (mCRC). However, its efficacy in proficient MMR (pMMR)/microsatellite stable (MSS) mCRC remains limited. In the phase II NIVACOR trial, we evaluated the activity and safety of FOLFOXIRI/bevacizumab plus nivolumab as first-line therapy in patients with RAS/BRAF-mutated mCRC (NCT04072198). The primary endpoint of the trial was the Objective Response Rate (ORR) whereas secondary endpoints were safety profile, overall survival (OS), progression free survival (PFS), duration of response (DoR) and quality of life. The primary endpoint was met. Among the 73 enrolled patients, 76.7% achieved an objective response (95% CI, 65.4 to 85.8%), while the disease control rate was 97.3% (95% CI, 90.5 to 99.7%). The median progression-free survival (mPFS) was 10.1 months (95% CI, 9.0 to 14.3 months), and the median overall survival (mOS) was not reached. Treatment-related adverse events of grade 3 or higher occurred in 48 patients out 73 enrolled patients (65.8%). Comprehensive genomic profiling and RNA sequencing analysis revealed genomic and transcriptomic profiles associated with treatment response in pMMR/MSS patients. Alterations in pathways such as PI3K/AKT, chemokine signaling and DNA repair showed correlation with treatment activity. These findings highlight the potential synergy between immune checkpoint inhibitors and cytotoxic chemotherapy in selected patients with pMMR/MSS mCRC.

Effects of whole-body vibration training on sarcopenia in older adults: a systematic review and meta-analysis of randomized controlled trials

Polymersomes preventing brain infiltration of CD177+ neutrophils to mitigate hemorrhagic transformation post-tPA thrombolysis

Abstract As an intravenous thrombolytic agent, tissue plasminogen activator (tPA) is limited by hemorrhagic transformation (HT) and a narrow therapeutic time window. Here we develop ROS-triggered polymersomes conjugated with fibrin-targeting CREKA peptide (CP) for tPA encapsulation. CP@tPA achieves efficient thrombosis targeting and enhanced thrombolytic efficacy, however, it has not been able to avert the occurrence of hemorrhage subsequent to thrombolysis. Building from our clinical discovery that stroke patients suffer from tPA-induced HT featured strong expression of CD177 , recombinant CD177 protein (rCD177) was loaded into CP polymersomes (CP@rCD177) as nanomedicine and administrated prior to CP@tPA thrombolysis. rCD177 can be released in response to elevated ROS within the obstructed vessels, which binds to endothelial cells through interacting with CD31 and efficiently prevents the migration of CD177 + neutrophils into the brain parenchyma. The reduced CD177 + neutrophils suppress the generation of neutrophil extracellular traps (NETs), thereby dampening the inflammatory activation of microglia and ultimately improving the prognosis of HT. This innovative strategy presents a promising avenue for attenuating hemorrhagic complications post-thrombolysis.