Asymmetrical estimator for training encapsulated deep photonic neural networks.

Photonic neural networks (PNNs) are fast in-propagation and high bandwidth paradigms that aim to popularize reproducible NN acceleration with higher efficiency and lower cost. However, the training of PNN is known to be challenging, where the device-to-device and system-to-system variations create imperfect knowledge of the PNN. Despite backpropagation (BP)-based training algorithms being the industry standard for their robustness, generality, and fast gradient convergence for digital training, existing PNN-BP methods rely heavily on accurate intermediate state extraction or extensive computational resources for deep PNNs (DPNNs).

IL-8-NF-κB-ALDH1A1 loop promotes the progression of intrahepatic cholangiocarcinoma.

Background: Intrahepatic cholangiocarcinoma (ICC) is a poor prognosis of malignant cancer with high lymph node metastasis and resistance to systemic therapies. Recent studies suggested that the involvement of IL-8 could promote ICC metastasis through epithelial-mesenchymal transition while the ICC-ALDH1A1high subtype is clarified by multi-omics study. The correlation between ALDH1A1 and IL-8 in ICC remains elusive.

Prediction of Gene Regulatory Connections with Joint Single-Cell Foundation Models and Graph-Based Learning.

Motivation: Single-cell RNA sequencing (scRNA-seq) data offers unprecedented opportunities to infer gene regulatory networks (GRNs) at a fine-grained resolution, shedding light on cellular phenotypes at the molecular level. However, the high sparsity, noise, and dropout events inherent in scRNA-seq data pose significant challenges for accurate and reliable GRN inference. The rapid growth in experimentally validated transcription factor-DNA binding data (e.

A feature extraction method for hydrofoil attached cavitation based on deep learning image semantic segmentation algorithm.

Cavitation is a technical challenge for high-speed underwater vehicles, such as nuclear submarines and underwater robots, et al. The cavitation phenomena of hydrofoils are typically studied through water tunnel experiments or numerical simulations, which yield extensive cavitation images. To conveniently extract cavitation features from the massive images, a feature extraction method for hydrofoil cavitation was proposed in this work based on deep learning image semantic segmentation techniques.

Keratinocyte-derived extracellular vesicles in painful diabetic neuropathy.

Painful diabetic neuropathy (PDN) is a challenging complication of diabetes with patients experiencing a painful and burning sensation in their extremities. Existing treatments provide limited relief without addressing the underlying mechanisms of the disease. PDN involves the gradual degeneration of nerve fibers in the skin.

TLS and immune cell profiling: immunomodulatory effects of immunochemotherapy on tumor microenvironment in resectable stage III NSCLC.

Background: The use of programmed death-1 (PD-1) inhibitors in the neoadjuvant setting for patients with resectable stage III NSCLC has revolutionized this field in recent years. However, there is still 40%-60% of patients do not benefit from this approach. The complex interactions between immune cell subtypes and tertiary lymphoid structures (TLSs) within the tumor microenvironment (TME) may influence prognosis and the response to immunochemotherapy.

Network Pharmacology and Metabolomics Reveal Anti-Ferroptotic Effects of Curcumin in Acute Kidney Injury.

Introduction: Acute kidney injury (AKI) is linked to high rates of mortality and morbidity worldwide thereby posing a major public health problem. Evidences suggest that ferroptosis is the primary cause of AKI, while inhibition of monoamine oxidase A(MAOA) and 5-hydroxytryptamine were recognized as the defender of ferroptosis. Curcumin (Cur) is a natural polyphenol and the main bioactive compound of , which has been found nephroprotection in AKI.

Invasive carcinoma segmentation in whole slide images using MS-ResMTUNet.

Identifying the invasive cancer area is a crucial step in the automated diagnosis of digital pathology slices of the breast. When examining the pathological sections of patients with invasive ductal carcinoma, several evaluations are required specifically for the invasive cancer area. However, currently there is little work that can effectively distinguish the invasive cancer area from the ductal carcinoma in situ in whole slide images.

Embracing the informative missingness and silent gene in analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel.

Heuristic dense reward shaping for learning-based map-free navigation of industrial automatic mobile robots.

This paper presents a map-free navigation approach for industrial automatic mobile robots (AMRs), designed to ensure computational efficiency, cost-effectiveness, and adaptability. Utilizing deep reinforcement learning (DRL), the system enables real-time decision-making without fixed markers or frequent map updates. The central contribution is the Heuristic Dense Reward Shaping (HDRS), inspired by potential field methods, which integrates domain knowledge to improve learning efficiency and minimize suboptimal actions.

Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation.

The accuracy of a fuzzy system's approximation is closely tied to the performance of fuzzy control systems design, while this system's interpretability depends on the description of a mechanical model using human language. This research introduces a quasi-Gaussian membership function characterized by a pair of parameters to achieve the sensitivity of a triangular membership function along with the interpretability of Gaussian membership functions. Consequently, a two-dimensional (2-D) quasi-Gaussian membership function is derived, and a method for establishing quasi-Gaussian fuzzy systems (QGFS) using a rectangular grid is proposed.

Reduction of RAD23A extends lifespan and mitigates pathology in TDP-43 mice.

Protein misfolding and aggregation are cardinal features of neurodegenerative disease (NDD) and they contribute to pathophysiology by both loss-of-function (LOF) and gain-of-function (GOF) mechanisms. This is well exemplified by TDP-43 which aggregates and mislocalizes in several NDDs. The depletion of nuclear TDP-43 leads to reduction in its normal function in RNA metabolism and the cytoplasmic accumulation of TDP-43 leads to aberrant protein homeostasis.

Enhanced pharmacological activities of AKR1C3-activated prodrug AST-3424 in cancer cells with defective DNA repair.

AST-3424 is a novel and highly tumor-selective prodrug. AST-3424 is activated by AKR1C3 to release a toxic bis-alkylating moiety, AST 2660. In this study, we have investigated the essential role of DNA repair in AST-3424 mediated pharmacological activities in vitro and in vivo.

Prognostic Nomograms for Patients With NF-Pan-NET After Pancreatectomy: A Retrospective Analysis Based on SEER Database.

Aims: Surgical resection is the primary treatment option for patients diagnosed with nonfunctional pancreatic neuroendocrine tumors (NF-Pan-NETs). However, the postoperative prognostic evaluation for NF-Pan-NET patients remains obscure. This study aimed to construct an efficient model to predict the prognosis of NF-Pan-NET patients who have received surgical resection.

Keratinocyte-Derived Exosomes in Painful Diabetic Neuropathy.

Painful diabetic neuropathy (PDN) is a challenging complication of diabetes with patients experiencing a painful and burning sensation in their extremities. Existing treatments provide limited relief without addressing the underlying mechanisms of the disease. PDN involves the gradual degeneration of nerve fibers in the skin.

Anti-PD-1 combined with hypomethylating agent and CAG regimen bridging to allogeneic hematopoietic stem cell transplantation: a novel strategy for relapsed/refractory acute myeloid leukemia.

Introduction: The prognosis of relapsed/refractory acute myeloid leukemia (r/rAML) is dismal, and allogeneic hematopoietic stem cell transplant (allo-HSCT) is a potential cure. Combining anti-PD-1, hypomethylating agent (HMA), and CAG (cytarabine, aclarubicin/idarubicin, granulocyte colony-stimulating factor) regimen has showed primary efficacy in r/rAML. However, pre-transplant exposure to anti-PD-1 may lead to severe graft-versus-host disease (GVHD).

Genetic Diversity Analysis and Prediction of Potential Suitable Areas for the Rare and Endangered Wild Plant .

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Immunotherapy and liver cancer research trends and the 100 most cited articles: A bibliometric analysis.

Background: Bibliometric analysis of liver cancer research, particularly in immunotherapy, reveals crucial insights. The US leads in liver cancer mortality but ranks fifth globally.

Objective: Scopus database analysis identified 2,349 papers, with the top 100 ranging from 127 to 4,959 citations.

I/O-efficient iterative matrix inversion with photonic integrated circuits.

Photonic integrated circuits have been extensively explored for optical processing with the aim of breaking the speed and energy efficiency bottlenecks of digital electronics. However, the input/output (IO) bottleneck remains one of the key barriers. Here we report a photonic iterative processor (PIP) for matrix-inversion-intensive applications.

Fucoidan alleviates doxorubicin-induced cardiotoxicity by inhibiting ferroptosis via Nrf2/GPX4 pathway.

Doxorubicin (Dox), a chemotherapeutic agent frequently used to treat cancer, elicits cardiotoxicity, a condition referred to as Dox-induced cardiotoxicity (DIC), and ferroptosis plays a contributory role in its pathophysiology. Fucoidan, a polysaccharide with various biological activities and safety profile, has potential therapeutic and pharmaceutical applications. This study aimed to investigate the protective effects and underlying mechanisms of fucoidan in DIC.

DDN3.0: determining significant rewiring of biological network structure with differential dependency networks.

Motivation: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent.