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Development of approach to an automated acquisition of static street view images using transformer architecture for analysis of Building characteristics
Abstract Static Street View Images (SSVIs) are widely used in urban studies to analyze building characteristics. Typically, camera parameters such as pitch and heading need precise adjustments to clearly capture these features. However, system errors during image acquisition frequently result in unusable images. Although manual filtering is commonly utilized to address this problem, it is labor-intensive and inefficient, and automated solutions have not been thoroughly investigated. This research introduces a deep-learning-based automated classification framework designed for two specific tasks: (1) analyzing entire building façades and (2) examining first-story façades. Five transformer-based architectures—Swin Transformer, ViT, PVT, MobileViT, and Axial Transformer—were systematically evaluated, resulting in the generation of 1,026 distinct models through various combinations of architectures and hyperparameters. Among these, the Swin Transformer demonstrated the highest performance, achieving an F1 score of 90.15% and accuracy of 91.72% for whole-building façade analysis, and an F1 score of 89.72% and accuracy of 92.27% for first-story façade analysis. Transformer-based models consistently outperformed 810 CNN-based models, offering efficient processing speeds of 0.022 s per image. However, differences in performance among most models were not statistically significant. Finally, this research discusses the practical implications and applications of these findings in urban studies.
Antibiotic treatment of honey bee colonies alters early gut microbiome assembly and induces persistent dysbiosis in newly emerged workers
Abstract The honey bee worker gut microbiome is assembled during the first days of adult life and, within the first week, matures to a relatively stable state that contributes to host health and behavior. Species composition, spatial distribution in the gut, and temporal species succession patterns all follow predictable and consistent patterns, creating a recognizable healthy worker gut microbiome. Though these quantities change with the age, task, and diet of the host, the mature microbiome is robust to minor disturbances. Mechanisms driving healthy microbiome assembly remain unclear, but abiotic, host-microbe, and microbe-microbe interactions are likely important to this development. Worker microbiomes may be altered to a dysbiotic state through nutritional, pathogen, and antibiotic stressors, increasing individual and colony susceptibility to further injury. Antibiotic use for control of bacterial diseases of larvae has been common beekeeping practice for decades, however, negative effects on the gut microbiota have been shown to decrease survivorship of affected workers and alter task-related behavioral patterns. We examined the succession of the worker gut microbiome across the first three weeks of adulthood in bees treated with the common beekeeper antibiotic tylosin. We found that both microbiome size and structure were significantly altered by tylosin treatment in 1 day old bees, and these effects persisted more than 2 weeks after last treatment application and did not recover to match control microbiomes by 21 days and the time of typical foraging onset. Certain Bifidobacterium and Bombilactobacillus species were strongly depleted by treatment, creating persistent dysbiotic states. These results illustrate early microbiome assembly in the worker gut and the negative effects of tylosin treatment on dynamic microbiome maturation.
Medical application driven content based medical image retrieval system for enhanced analysis of X-ray images
Trends and disparities in heart failure mortality with and without chronic kidney disease in a nationwide retrospective analysis
MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response
Amyloid fibrils of the myelin basic protein are an integral component of myelin in the vertebrate brain
Antimicrobial, photodegradation and BioReRAM applications of multifaceted green zinc oxide nanoparticles synthesized using coffee leaves extract
Combined stimuli of elasticity and microgrooves form aligned myotubes that characterize slow twitch muscles
Abstract Skeletal muscles are classified into slow-twitch muscles composed primarily of type I and IIa fibers with high oxidative metabolism, and fast-twitch muscles composed of type IIx and IIb fibers with high glycolytic metabolism. Fiber-type shifts occur during development and aging; however, the stimuli that shift these types remain unclear. We analyzed the role of mechanical stimuli in myotube formation and shift to the characteristics of each fiber type using crosslinked gelatin gels with tunable elastic moduli (10–230 kPa) and microgrooves (3–50 µm). C2C12 myotubes on 10 kPa gel increased the expression of marker genes for type I and IIa fibers (MYH7 and MYH2 ) and oxidative metabolism ( GLUT4 and myoglobin ) than those on stiffer gels. Upregulation of PGC-1α on soft gel induced a shift toward slow-twitch muscle genetic characteristics. Microgrooves (3–10 µm) enhanced myoblast differentiation and myotube orientation, without affecting the gene expressions characterizing fiber types. This study demonstrated an approach to create highly oriented slow-twitch muscle models by controlling the elasticity and microgrooves.
Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry
Combining single-cell and bulk RNA sequencing to identify CAF-related signature for prognostic prediction and treatment response in patients with melanoma
Abstract Cancer-associated fibroblasts (CAFs) play complex roles in the tumor microenvironment (TME) of melanoma. However, their impact on prognosis and treatment response in melanoma remains unclear. In this study, ScRNA-seq data (GSE115978) were utilized to characterize CAF heterogeneity and identify marker genes in melanoma. Prognostic CAF genes were identified from the TCGA dataset and employed to construct a risk signature, which was subsequently validated in an independent cohort (GSE65904). Mutation, copy number variation (CNV), pathway enrichment, immune infiltration, and drug sensitivity were analyzed to determine the signature’s clinical relevance. Immunohistochemistry (IHC), immunofluorescence (IF), and qPCR were performed to validate the expression of CAF signatures on clinical melanoma samples. We identified CAFs in patients with melanoma through single-cell RNA sequencing data. A 28-gene CAF signature was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression based on 271 prognostic CAF genes. This signature demonstrated excellent prediction accuracy for survival, with area under the curve (AUC) values of 0.737, 0.737, and 0.779 for 1-year, 3-year, and 5-year survival, respectively. The signature was an independent prognostic factor and was correlated with CNVs, and immunosuppressive TME features (reduced CD8+ T cells, M1 macrophages). Additionally, our CAF signature could predict the efficacy of multiple chemotherapy drugs and serve as a potential prognostic marker for immunotherapy. Experimental validation confirmed the expression of CAF signature genes in melanoma tissue. Our model may help predict the prognosis and response to chemotherapy and immunotherapy in patients diagnosed with melanoma.
SRSF3 undergoes phase separation in lung cancer and is associated with immunity and ferroptosis
C57BL/6J mice best recapitulate fibrosis and inflammatory pathophysiology in syngeneic mouse model of endometriosis
Abstract Endometriosis (ENDO), a chronic inflammatory disease affecting approximately 190 million women globally, is characterized by fibrosis, a feature often challenging to replicate in murine models. To identify an optimal syngeneic model exhibiting robust fibrosis and inflammation, we evaluated three inbred mouse strains: C57BL/6J (n = 27), BALB/c (n = 24), and Swiss albino (n = 27). Uterine fragments from donor mice were intraperitoneally transplanted into recipient mice (1 donor: 2 recipients) using an established protocol with minor modifications. All ENDO-induced mice displayed reduced burrowing and exploratory behaviors, alongside increased mechanical hyperalgesia, indicative of ENDO-associated discomfort. Peritoneal fluid analysis revealed a pro-inflammatory environment with a tendency towards an M2 macrophage-dominant profile across all strains. Histological examination confirmed endometriotic lesions with proliferating epithelium (Ki-67+), neovascularization (CD31+), and macrophage infiltration (F4/80+). Notably, C57BL/6J mice exhibited the highest ENDO incidence and a significantly pronounced fibrotic response, evidenced by increased stromal collagen deposition and elevated Col1A1, cytokeratin, α-Smooth Muscle Actin (α-SMA), and Nestin expression. Molecular analysis in C57BL/6J mice further supported epithelial-mesenchymal transition (EMT)-driven fibrosis, with decreased E-cadherin and increased N-cadherin and S100A4 mRNA levels, corroborated by corresponding protein changes (cytokeratin, vimentin, snail). Our findings establish the C57BL/6J strain as the most suitable syngeneic model for ENDO, consistently recapitulating the inflammatory and fibrotic pathophysiology observed in human disease, particularly its fibrotic component.
Multimodal Alzheimer’s disease recognition from image, text and audio
Serum IgA/C3 ratio as a diagnostic and prognostic biomarker for IgA nephropathy
Carbon dot based molecularly imprinted polymer for selective fluorometric determination of tetracycline and metronidazole in pharmaceuticals and human plasma
Abstract A highly sensitive, selective, and rapid spectrofluorometric method has been developed using fluorescence sensors. This method is based on the highly fluorescent graphene quantum dots coated with silica molecularly imprinted polymers (GQDs-SMIPs) for the determination of tetracycline HCl (TET) and metronidazole (MET). Upon excitation of the GQDs-SMIPs at 260.0 nm for TET and 245.0 nm for MET, strong fluorescence emissions at 292.0 nm were produced for both sensors. Such fluorescence was quenched by the addition of their corresponding molecularly imprinted polymer (MIPs) templates. The quenching effect was linear over the concentration ranges of 15.0–120.0 µM and 15.0–140.0 µM for TET and MET, respectively. Limits of detection (LOD) were 3.55 µM, and 4.48 µM while limits of quantification (LOQ) were 10.75 µM and 13.57 µM for TET and MET, respectively. The fabricated GQDs-SMIPs were characterized using scanning electronic microscopy, Fourier-transform IR spectroscopy, and X-ray diffraction. Selectivity of the method was investigated against potentially interfering substances, including two official impurities of TET and MET. Additionally, this fluorescent technique was successfully applied for the determination of these drugs in pharmaceutical dosage forms and spiked human plasma samples. This approach provides a selective and sensitive fluorometric platform for the determination of the studied drugs in complex matrices and quality control laboratories.