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LDHB silencing enhances the effects of radiotherapy by impairing nucleotide metabolism and promoting persistent DNA damage
Abstract Lung cancer is the leading cause of cancer-related deaths globally, with radiotherapy as a key treatment modality for inoperable cases. Lactate, once considered a by-product of anaerobic cellular metabolism, is now considered critical for cancer progression. Lactate dehydrogenase B (LDHB) converts lactate to pyruvate and supports mitochondrial metabolism. In this study, a re-analysis of our previous transcriptomic data revealed that LDHB silencing in the NSCLC cell lines A549 and H358 dysregulated 1789 genes, including gene sets associated with cell cycle and DNA repair pathways. LDHB silencing increased H2AX phosphorylation, a surrogate marker of DNA damage, and induced cell cycle arrest at the G1/S or G2/M checkpoint depending on the p53 status. Long-term LDHB silencing sensitized A549 cells to radiotherapy, resulting in increased DNA damage and genomic instability as evidenced by increased H2AX phosphorylation levels and micronuclei accumulation, respectively. The combination of LDHB silencing and radiotherapy increased protein levels of the senescence marker p21, accompanied by increased phosphorylation of Chk2, suggesting persistent DNA damage. Metabolomics analysis revealed that LDHB silencing decreased nucleotide metabolism, particularly purine and pyrimidine biosynthesis, in tumor xenografts. Nucleotide supplementation partially attenuated DNA damage caused by combined LDHB silencing and radiotherapy. These findings suggest that LDHB supports metabolic homeostasis and DNA damage repair in NSCLC, while its silencing enhances the effects of radiotherapy by impairing nucleotide metabolism and promoting persistent DNA damage.
Digital twin-assisted graph matching multi-task object detection method in complex traffic scenarios
Network pharmacology and AI in cancer research uncovering biomarkers and therapeutic targets for RALGDS mutations
Abstract The lack of target therapies is accountable for the higher mortality of various types of cancer. To address this issue, we selected a target mutated Kirsten rat sarcoma virus oncogene homologue, which plays a significant role in various cancers. Our study aims to identify selective biomarkers and develop diagnostic and therapeutic strategies for KRAS-associated genes using artificial intelligence. Initially, Genomic data, cancer epidemiology, proteomics network interactions, and omics enrichment were analyzed. Structured E-pharmacophore model aided in capturing the binding cavity using eraser algorithms and fabricating a new selective lead compound for the KRSA. The selective molecule was abridged inside the binding cavity and stability was validated through 100 ns molecular dynamics simulations. Epidemiological-neural network studies indicated KRAS mutations leads 40 types of cancer, exclusively pancreatic and colorectal cancers, with diploid and missense mutations as primary factors. Pathway analysis highlighted the involvement of the MAPK and RAS signaling pathways in cancer development and proteomics analysis identified RALGDS as a key protein. Protein-based pharmacophore analysis mapped the biologically active features such as donor, acceptor and aromatic ring with the designed ligands. The results of interaction interpretation illustrate that the amino acid Tyr566 formed an H-bond interaction with the amine group of the octyl ring system and 20 amino acids crafted to properly orient the molecule to fit inside the polar cavity of KRAS protein. The MMGBSA score of − 53.33 kcal/mol conformed to the well-configured binding with KRSA and realistic model simulation exposed the π–π, π–cationic and hydrophobic interactions stabilised the molecule inside the KRSA protein throughout 100 ns simulation. The study demonstrates the vitality of AI and network pharmacology to identify potential-target biomarkers for KRAS-associated genes, paving the way for improved cancer diagnostics and therapeutics.
SEPDNet: simple and effective PCB surface defect detection method
Synthesize multiple V/H directional beams for high altitude platform station based on deep-learning algorithm
Abstract This paper investigates the integration of High-Altitude Platform Stations (HAPS) with Deep Learning (DL) models to enhance coverage capabilities. Recognizing the inherent limitations of traditional HAPS coverage, which is typically confined to a circular area, this work proposes a novel approach utilizing a 60-element Concentric Circular Array (CCA) operating at 2.1 GHz. To dynamically generate multiple vertical/horizontal (V/H) directional beams, the system integrates a Deep Neural Network (DNN) with a modified version of the Gravitational Search Algorithm and Particle Swarm Optimization (MGSA-PSO) algorithm. This hybrid approach optimizes the feeding phases of the CCA elements, enabling the system to effectively cover diverse road paths. Furthermore, the study incorporates realistic scenarios by utilizing the Computer Simulation Technology-Microwave Studio Suite (CST) with the Earth Explorer (EE) user interface tool to model real-world road paths, including those traversing challenging terrains such as rugged deserts with mountain chains and forested areas.
Cue combination and individual differences during weight judgements using familiar and newly learned cues
Abstract Human perception is often characterised by efficient combination of sensory signals (cues). In recent studies, people could also improve precision via newly learned cues, with applications to enhance perception in healthy and clinical groups. However, it is unclear whether new cues can enhance manual object interactions. To study how new cues are used for object weight perception, people compared weights of containers. With haptic information plus the familiar visual cue of volume, participants showed precision improvements indicating cue combination. By contrast, a group of participants briefly trained with a novel visual cue to weight (line orientation) did not show improvements expected from combination. We then asked whether prolonged training (12 h) with the novel cue would promote combination, testing for significant precision gains individually in six participants. Half of participants showed combination benefits, but these were not clearly related to training, as some combined cues before training. Using an illusion analogous to the size-weight illusion, we also asked whether the novel cue would become an automatic predictor of weight: two participants were susceptible to the illusion. We conclude that weight perception is susceptible to some enhancement, but subject to training effects and individual differences that are not yet understood.
A comparison of three kinds of balloon dilatations for patients with benign esophageal strictures
Electrospun preparation of nickel and Cobalt-doped ZnO fibers: study on the physical properties
Longitudinal changes in the intraocular pressure and their related factors among adults aged 40 to 64 years
Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms
An ESG-ConvNeXt network for steel surface defect classification based on hybrid attention mechanism
Diagnostic features of Acanthamoeba keratitis via in vivo confocal microscopy
Abstract In vivo confocal microscopy (IVCM) offers a non-invasive, rapid method for diagnosing Acanthamoeba keratitis (AK) by detecting cysts or trophozoites in the initial clinic visit images. In this retrospective observational study, we reviewed HRT3 IVCM images from patients presenting to Manchester Royal Eye Hospital with clinically- suspected AK for IVCM morphological features (IVCM-MF) of both Acanthamoeba and corneal cells. Twenty-seven patients were included in the study: median age 29 years (range 16–71 years), female gender (59%; n = 16/27) and contact lens wear as the main risk factor. Median symptom duration before the initial ophthalmologist visit was 9 days (range 2 to 42 days). IVCM had a higher detection rate for AK in 85% of patients (n = 23/27), with culture positivity in only 74% (n = 20/27; 17 of whom were also IVCM-positive). Acanthamoeba IVCM-MF included: bright spots (87%, n = 20/23), double-walled cysts (56%, n = 13/23), signet-ring (22%, n = 5/23) and trophozoites (30%, n = 7/23). Bright spots and double-walled cysts coalesced in lines/clusters in 1 patient. Corneal epithelial cells had a “koilocyte” appearance in 64% (n = 14/22). Microtubules connecting adjacent keratocytes were visible in 52% (n = 12/23), particularly associated with A. polyphaga ulcers (p = 0.02). These IVCM features observed in corneal epithelial cells and keratocytes may represent potential imaging biomarkers for AK diagnosis and warrant further investigation to validate their diagnostic utility. By demonstrating IVCM’s superior diagnostic performance, providing rapid and accurate diagnostics, this study advocates for its inclusion in standard diagnostic workflows for AK, paving the way for future advancements in clinical practice.
Gait kinematic and kinetic characteristics among older adults with varying degrees of frailty: a cross-sectional study
Characterization of a new mutation of mitochondrial ND6 gene in hepatocellular carcinoma and its effects on respiratory complex I
Abstract Hepatocellular carcinoma (HCC) is the most common form of liver cancer, which often arises from previous liver pathologies such as HBV, HCV, and alcohol abuse. It is typically associated with an enlarged cirrhotic organ. In this study, we analyzed tumor and distal tissues from a patient who underwent liver resection for HCC with no previous pathologies and whose liver showed normal function without signs of cirrhosis. Genetic analysis of mitochondrial DNA (mtDNA) revealed a novel variant of the gene encoding the NADH dehydrogenase subunit 6 (ND6) protein in the tumor tissue. The deletion of a thymidine generated an early stop codon, resulting in a truncated form of the protein (ΔND6) with 50% of the C-terminal primary sequence missing. ND6 is a subunit of the NADH dehydrogenase complex, also known as Complex I, the largest complex in the electron transport chain. Previous studies have linked mtDNA Complex I mutations to mitochondrial disorders and cancer. Through biochemical analyses, we characterized this new mutation and showed that the expression of ΔND6 negatively affects the stability and functionality of Complex I. Data were confirmed by molecular dynamics simulations suggesting conformational rearrangements, overall revealing a leading role of ND6 in the assembly of Complex I.