Browse Articles

Cancer stem cells and Lon-noncRNA promotes invasion, metastasis and tumor growth in breast cancer through regulation of signaling pathway

Abstract Breast cancer (BC), the most common malignant tumor in women, continues to be a leading cause of cancer-related deaths globally. A major challenge in managing BC, especially in metastatic cases, is the lack of reliable early diagnostic biomarkers. Metastatic breast cancer stem cells (MBCSCs) play a critical role in tumor progression, resistance to therapy, and disease recurrence. This study aimed to explore the molecular pathways connecting the long non-coding RNAs (lncRNAs) HOTAIR, UCA1, and MALAT1 with breast cancer stem cell-related genes FOXC2, SNAIL, and ZEB, focusing on their involvement in transcriptional regulation, proliferation, and survival. Peripheral blood samples and plasma were collected from 30 women diagnosed with metastatic breast cancer (MBC, stage IV) and 30 healthy controls. Gene expression levels were measured using quantitative real-time PCR (qRT-PCR). Our findings revealed a significant upregulation of SNAIL and FOXC2 in MBC patients compared to healthy controls (p < 0.001). The median expression levels of SNAIL (16.4) and FOXC2 (19.5) were substantially higher in the metastatic group than in healthy individuals (SNAIL: 6.42, FOXC2: 7.23). Conversely, the expression levels of HOTAIR, UCA1, MALAT1, and ZEB did not show statistically significant differences between the two groups (p > 0.05). Correlation analysis indicated a strong positive association between FOXC2 and SNAIL expression (r = 0.41), suggesting a potential shared functional role in disease progression. These results suggest that SNAIL and FOXC2 could serve as potential prognostic biomarkers in MBCSCs, whereas HOTAIR, UCA1, MALAT1, and ZEB may not independently predict metastasis or survival outcomes. Further research is necessary to explore the therapeutic implications of these genes in metastatic breast cancer.

Early changes in corticospinal excitability for subliminally presented fearful body postures

Abstract Fearful body expressions convey critical information that is rapidly and preferentially processed, facilitating swift motor reactions to potential dangers. Consistent evidence has shown that even the subliminal presentation of fear-related expressions can impact visual processing and autonomic responses, increasing sensory vigilance for monitoring potential threats. However, it remains unclear whether the presentation of non-visible emotional bodies modulates corticospinal excitability (CSE) in the observer. To investigate this, we asked 22 healthy participants to perform a sex discrimination task involving neutral target body postures, preceded by the brief subliminal presentation of fearful, happy, or neutral body postures. CSE was tested using Transcranial Magnetic Stimulation (TMS) at early time points (70, 90, and 110 ms) after target stimulus onset. Results showed a significant CSE reduction in the dominant hemisphere for subliminal fearful primes compared to happy and neutral primes. This CSE suppression was independent of the time of stimulation, participants’ subjective or objective awareness, metacognitive sensitivity, or personality traits. Our findings highlight an early automatic activation of the motor system in response to subliminal fearful stimuli, supporting the view that fearful expressions, even when not consciously perceived, activate basic survival mechanisms for monitoring and preparing fast motor responses to potential threats.

Propensity score matching analysis of the effect of four or more antenatal care visits on basic childhood immunization in Ethiopia

Association between social determinants of health and systemic lupus erythematosus: a nationally representative analysis of 2017–2021 data

Abstract Limited US recent data is available on the prevalence of systemic lupus erythematosus (SLE) by patient’s social determinants of health (SDOH). Careful assessment of individual SDOH that affects SLE is crucial, as such evidence could help improve care and hence reduce health disparities for patients with SLE, especially for those who are most vulnerable and at the highest risk of poor outcomes. We estimated the prevalence of systemic lupus erythematosus (SLE) overall and by patient’s social determinants of health (SDOH), and also explored the associations between SDOH and SLE. We conducted a population-based cross-sectional study using Medical Expenditure Panel Survey 2017–2021 data. Patients with SLE were those with both SLE diagnosis and either had SLE-related medication use and/or visited a rheumatologist in the survey year. SDOH domains included economic stability, education, healthcare access and quality, social and community context, and neighborhood and built environment. Average annual prevalence of SLE by SDOH was determined. Separate logistic regressions were used to examine the association between each SDOH and SLE, controlling for confounders. Average annual SLE prevalence was 199 per 100,000 US adults (95% confidence intervals:170–224). In the economic stability domain, those with low family income showed higher odds of SLE than those with high family income (adjusted odds ratio (AOR) = 2.779, p < 0.05). Within the social and community context and neighborhood and built environment domains, non-Hispanic Black patients (AOR = 2.429, p < 0.05) and patients with any psychological distress (AOR = 2.127, p < 0.05) had higher odds of SLE, than their respective counterparts, respectively. Within the healthcare access and quality domain, those with Medicaid insurance had higher odds of SLE (AOR = 2.540, p < 0.05) than those with private insurance. Also, patients in the highest SDOH burden quartile had higher odds of SLE (AOR = 2.039, p < 0.05) than those in the lowest SDOH burden quartile. We identified several subgroups of patients especially those with higher social disadvantage and a higher SDOH burden. The prevalence of SLE increased with a higher SDOH burden.

Complex linear Diophantine fuzzy Dombi prioritized operators-based MULTIMOORA approach with applications to sustainable energy planning

Mathematical modeling of tumor-immune dynamics: stability, control, and synchronization via fractional calculus and numerical optimization

Obesity in chronic spinal cord injury is associated with poorer body composition and increased risk of cardiometabolic disease

Abstract With increased longevity after spinal cord injury (SCI), cardiovascular disease has emerged as a major cause of morbidity and mortality. We evaluate the association of body composition and injury level with cardiometabolic disease (CMD) risk factors. Sixty-two individuals (69% male, 31% female) with chronic SCI (mean duration 7.4, SD ± 5.8 years) were recruited. Mean age of participants was 34.4 ± 12.1 years with BMI of 23.8 ± 5, while 64% had BMI < 25 and 11% >30. Total and percent truncal fat correlated positively (p < 0.05) with serum triglycerides, non-high-density lipid cholesterol, c-reactive protein (CRP), oral glucose tolerance test (OGTT), and measures of insulin resistance. Those with obesity in SCI (defined as BMI ≥ 22) had increased total and trunk mass and fat percentage, unfavorable lipid profiles and evidence of insulin insensitivity. Total fat was associated with CMD risk factors, including insulin resistance (OGTT 60 min r = 0.47, p < 0.05; homeostasis model assessment [HOMA] r = 0.62, p < 0.05), serum triglycerides (r = 0.31, p < 0.05), and inflammation (CRP r = 0.43, p < 0.05). Obesity in SCI related to higher CMD risk, while time since injury and injury level (paraplegia versus tetraplegia) did not. Future studies may evaluate roles of nutrition, exercise, sleep-promotion, and pharmaceuticals to lower neurogenic obesity and chronic CMD risk.

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