Although icodextrin was initially developed for rapid transporters (type 1 UFF), emerging evidence suggests its effects might be independent of peritoneal membrane transport characteristics. This study aimed to evaluate the suitability of 7.5% icodextrin for all PD patients with UFF. We enrolled 19 patients with UFF and 24 non-UFF PD controls. All participants underwent standard, modified, Mini-, and Double-Mini peritoneal equilibrium tests (PET). Key parameters assessed included sodium sieving (∆DNa60, ∆D/PNa60), osmotic conductance to glucose, small-pore ultrafiltration (UFSP), free water transport (FWT), and net ultrafiltration. Correlation analyses were conducted between icodextrin-induced UF and these metrics. Descriptive analysis revealed variations in icodextrin UF, ∆D/PNa60, and FWT were identified across the four UFF types. Numerically, icodextrin UF was highest in type 1 and type 2 UFF, while FWT appeared lower in type 2. Net icodextrin UF correlated positively with ∆D/PNa60, ∆DNa60, and UFSP. Our findings indicate that 7.5% icodextrin may be suitable for PD patients with type 1 and 2 UFF, but appears perhaps less effective in those with type 3 and 4 UFF.Moreover, icodextrin ultrafiltration may be predictable through UFSP measurement, offering a potential clinical tool for patient management.
Gambling-related harm extends beyond the individual who gambles and affects others in their social environment, referred to as affected others (AO). This study examined the prevalence of AO by relationship type and socio-demographic characteristics, and assessed health outcomes across different AO categories in the general Swedish population. Data were drawn from the national survey Gambling and Health 2021, conducted by the Public Health Agency of Sweden. The sample comprised 7,343 respondents aged 16-84 years. Past year AO status was assessed for family members or close relatives, friends, and colleagues or fellow students. Health outcomes included indicators of mental, behavioural, and relational health. Associations were examined using adjusted logistic regression analyses. Overall, 11.1% of respondents reported that someone in their close social environment had experienced gambling problems at any point during the past 12 months, most commonly a friend (5.4%). AOs reported a higher prevalence of adverse mental, behavioural, and relational health outcomes than non-AOs. After adjustment, AO status remained associated with moderate mental distress across all relationship types, with additional associations observed for serious mental distress among family AOs. Behavioural outcomes remained elevated among family and friend AOs, including at-risk gambling and hazardous alcohol use. Relational outcomes showed the most consistent associations, including increased arguments across all AO categories, experiences of violence among friend AOs, and work-related conflicts, particularly among work/school AOs. The findings indicate that AOs constitute a substantial and heterogeneous group in the population and underscore the relevance of considering relationship type when addressing gambling-related harm.
To assess the prevalence of impairment of flow-mediated epicardial vasodilation (IEV) in the presence of normal and abnormal coronary microvascular function. In 332 consecutive symptomatic patients, global and longitudinal myocardial blood flow (MBF) at rest and during pharmacologically stimulated hyperemia was evaluated with 13N-ammonia positron emission tomography/computed tomography (PET/CT). Normal coronary microvascular function (nCMF) was defined by a myocardial flow reserve (MFR = MBFstress/MBFrest) of ≥ 2.0 (group 1; n = 210 (G1)), while an abnormal MFR of < 2.0 (predominantly due to decreases in hyperemic MBF) denoted classical CMD (group 2; n = 83 (G2)) or (predominantly related to increases in resting MBF ≥ 1.0mL/g/min) signified endogen CMD (group 3; n = 39 (G3)), respectively. Furthermore, normal flow-mediated epicardial vasodilation (NEV) was defined as longitudinal hyperemic MBF gradient < -0.10 mL/g/min, whereas a value ≥ -0.10 mL/g/min signified IEV.In the entire study population, IEV was present in 34.6.% (115/332). IEV was highest in group 1 (46.2%), while there was a comparable low prevalence between group 2 and group 3 (13.3% vs. 17.9%; p = 559). The hyperemic longitudinal MBF gradient was significantly higher in G1 compared to G2 (-0.28 ± 0.10 vs. -0.19 ± 0.08 mL/g/min; p ≤ 0.008), but comparable between group 1 and group 3 (-0.28 ± 0.10 and - 0.27 ± 0.10 mL/g/min; p = 0.795). The hyperemic longitudinal MBF gradient and ΔMBF Gradient correlated inversely with the global hyperemic MBF, respectively (r = 0.41, SEE = 0.09 and r = 0.34, SEE = 0.09, both p ≤ 0.001). Nearly half of symptomatic patients with normal global MFR may have IEV. As IEV carries important diagnostic and prognostic information, it may further optimize prognostication on cardiovascular individuals deserving further clinical testing.
Konjac glucomannan (KG)/κ-carrageenan (CG) composite gels have gained widespread attention in food processing due to synergistic gelation properties. However, the specific mechanism whereby anions regulate gelation behaviour of composite systems remains unclear. In this study, the effects of five potassium salts (KCl, KH2PO4, K2HPO4, K3C6H5O7, and KHCO3) on the structure and properties of KG/CG were systematically investigated via multi-scale characterisation. Optimal KG/CG mass ratio (3:7) and potassium ion concentration (0.1 M) were determined through TPA. HCO3- induced the formation of a denser and more uniform gel network with the highest hardness, water holding capacity, and thermal decomposition temperature. LAOS analysis revealed that the HCO3--treated gels exhibited stronger nonlinear viscoelastic behaviour and higher elastic recovery, indicating excellent network toughness. The mechanism underlying the anion-induced gelation enhancement was attributed to the combined effects of anion charge density, ionic radius, and competitive binding with K+. This study provides a theoretical basis for the design and development of composite gels.
Cervical cancer remains a significant public health challenge, particularly in low and middle-income countries, where the burden is disproportionately high. Human papillomavirus (HPV) is the principal cause of cervical cancer, yet evidence on the national prevalence of HPV infection in Ghana remains fragmented and inconsistent across studies. As Ghana prepares to scale up HPV vaccination and expand HPV-based screening, a comprehensive synthesis of HPV prevalence is essential to inform policy and guide prevention strategies. Through this systematic review and meta-analysis, we sought to estimate the pooled prevalence of any HPV infection and high-risk HPV genotypes among women in Ghana. A systematic search of published studies reporting cervical HPV prevalence among Ghanaian women was conducted. Eligible studies included cross-sectional, retrospective and cohort designs. Data were extracted on study characteristics, population type, sample size and HPV outcomes. Random-effects models were used to generate pooled prevalence estimates for any HPV, high-risk HPV and low-risk HPV types. Heterogeneity and potential publication bias were assessed using I² statistics and funnel plots. Seventeen studies with a combined sample of more than 8,000 women were included. The pooled prevalence of any HPV infection was 31% (95% CI: 25-38%). The pooled prevalence of high-risk HPV infection was 28% (95% CI: 22-33%), while low-risk HPV infection had a pooled prevalence of 12% (95% CI: 4-20%). Substantial heterogeneity was observed across all analyses (I² > 90%). Funnel plots suggested possible publication bias for any HPV and low-risk HPV, while studies reporting high-risk HPV infection demonstrated a more symmetrical distribution. The estimate for low‑risk HPV prevalence was based on a limited number of studies and should be interpreted as exploratory. HPV infection is highly prevalent among women in the studied regions, with high-risk HPV types constituting a substantial proportion of infections. These findings underscore the urgent need to strengthen national cervical cancer prevention strategies through widespread HPV vaccination, improved access to HPV-based screening and targeted interventions for high-risk groups. Establishing baseline HPV prevalence is critical for evaluating the impact of ongoing and future prevention programmes in Ghana. Findings are based on studies predominantly conducted in southern Ghana and may not fully represent the national population. Prospective Register of Systematic Reviews (PROSPERO); Registration ID: CRD42024605015.
Exploring the disparities in CO2 emissions (CE) among different city types is essential for formulating effective decarbonization policies. However, due to the limitations of urban energy data, it is challenging to conduct CE analysis at the city level. This study proposes a city-level CE accounting model based on multi-source data to estimate emissions for 41 cities in the Yangtze River Delta (YRD) from 2013 to 2022. Using the K-means algorithm, cities are categorized into five distinct types, while a Geographically and Temporally Weighted Regression (GTWR) model is employed to analyze their spatiotemporal drivers. The results demonstrate that the proposed model in this study significantly enhances the accuracy of city-level CE estimation compared to traditional Nighttime Light (NTL)-based fitting methods, with the R2 value increasing from 0.63 to 0.76. Based on this improved model, the result shows that the total CE in the YRD rose from 1,700 Mt in 2013 to approximately 1,931 Mt in 2022. The region exhibits a high degree of emission concentration, where a mere 14.6% of cities with annual emissions exceeding 80 Mt contribute to 40.3% of the total regional emissions. GTWR analysis reveals that population, per capita GDP, industry structure, and energy intensity consistently drive emissions upward, while urbanization exhibits dual effects. Optimizing industrial structure and reducing energy intensity are effective ways to curb the growth of urban CE. This study improves the estimation method for urban CE based on NTL data and provides scientific support for various city types to formulate tailored mitigation pathways.
To compare the efficacy and safety of intense pulsed light (IPL) versus diode laser (DL) for female axillary hair removal in a randomized split-body trial. Women with Fitzpatrick skin types I-IV received IPL (690-nm filter) and DL (810 nm) on contralateral axillae with randomized side assignment. Four monthly sessions were performed. The primary outcome was hair count in a standardized 4-cm² area. Secondary outcomes included hair shaft thickness, pain intensity (numeric rating scale), participant satisfaction, evaluator-rated improvement (modified GAIS), quality of life (WHOQOL-bref), and adverse events. Participants and outcome assessors were blinded to side allocation. Forty-eight participants initiated treatment; 36 completed all sessions and 28 attended the 4-week post-treatment assessment (S4). Hair counts and hair shaft thickness decreased significantly over time with both modalities. At S4 (primary endpoint), the intention-to-treat analysis showed no statistically significant between-modality difference in hair counts; at 30-week (around 7 months) follow-up, DL showed more favorable objective outcomes (lower hair counts and thinner residual shafts). Pain scores were consistently higher with DL. Adverse-event profiles differed: erythema was more frequent with IPL, whereas perifollicular edema and carbonization were more frequent with DL; events were transient and required no medical intervention. Exploratory stratification by Fitzpatrick skin type showed no consistent pattern of increased adverse events in higher skin types. Satisfaction favored DL, while WHOQOL-bref scores did not change significantly. IPL and DL were both safe and effective for axillary hair removal in women with Fitzpatrick skin types I-IV. DL yielded more favorable longer-term objective outcomes but greater discomfort and transient procedure-related adverse effects. Trial registration: NCT06179186, 23 December 2023.
Understanding how complex organic contaminant mixtures change in composition, structure, and transformation behavior across wastewater treatment plants (WWTPs) is essential for improving pollutant control. However, stage-resolved knowledge of these processes remains limited. Here, we integrated non-targeted screening, paired mass distance (PMD) reactomics, CANOPUS-based structural annotation, and MS2Tox-based toxicity prediction to characterize compositional changes, dominant transformation behaviors, and toxicity implications throughout a full-scale anaerobic-anoxic-oxic (A/A/O) treatment and disinfection process through wastewater sampling in a WWTP. Across the treatments, chemical features progressively shifted toward lower molecular weight and higher hydrophilicity. Structural classification revealed the common pollutants (organic acids and derivatives, benzenoids, lipids and lipid-like molecules) and specific pollutants present in each unit. Reactomics revealed that methylation and dehydrogenation/oxidation were the most frequent transformation types, and each unit exhibited several distinct reaction types (e.g., stage-specific alkylation/dealkylation reactions during disinfection). Further correlating structure and reaction types reveal that pollutant transformations in wastewater are characterized by small mass shifts and generally retained the structural category of the reactant. Subsequently, toxicity prediction results suggested that most compounds exhibited no (65%) to low (31.6%) toxicity in WWTP. Biological treatment was associated with more predicted detoxification events, whereas chlorination disinfection showed more predicted toxicity-increase events that were frequently associated with alkylation-/methylation-related PMD signals. This study provides a stage-resolved interpretation of contaminant transformation across WWTP treatment units by linking feature attenuation, structural redistribution, PMD-derived reaction signatures, and MS2Tox-predicted toxicity shifts.
Global climate change has increased the frequency and intensity of extreme weather events, significantly impacting the net primary productivity (NPP) of vegetation. Understanding the relationship between NPP and extreme climate events in ecologically sensitive areas is essential for effective ecological strategies. This study analyzed the spatiotemporal distribution characteristics of net primary productivity (NPP) from 2000 to 2022 and its response to extreme climate conditions. Utilizing the flexible space-temporal DAta fusion (FSDAF), the study integrated MODIS and Landsat data from 2000 to 2022 to generate a high-resolution NDVI dataset (30 m, 16-day). The NPP was estimated using the Carnegie-Ames-Stanford approach (CASA) model. We also evaluated the effects of 13 extreme climate indices (ECIs) on NPP in the Gaoligong Mountains. The results showed that (1) annual NPP exhibited an upward trend (slope = 1.5), with the most significant increase occuring in January (slope = 0.35, p < 0.001); (2) the climate in the study area has displayed a clear warming trend, with significant increases in extreme temperature indices (TXx, TNx, TN90p, TX90p, TMAXmean, and TMINmean, p < 0.001), while extreme precipitation indices (RX1day, RX5day), showd a relatively small trend of change and not significant; (3) At the seasonal scale, the responses of NPP to ECIs varied significantly among different vegetation types. The correlations between NPP and ECIs were markedly stronger in spring and autumn than in summer and winter, with temperature-related indices showing the strongest explanatory power for variations in NPP. (4)The response of NPP to extreme temperatures and precipitation is primarily characterized by a lag effect, typically delayed by 1-2 months, and is observed across different vegetation types. (5) extreme temperatures, particularly TX90p, TXx, TMAXmean, and DTR, are the key climatic factors affecting NPP. These results offer insights into the impact of climate extremes on NPP, which can inform future ecological management strategies.
Forest soils play a critical role in regulating heavy metal dynamics; however, the combined influence of seasonal variability and forest type on metal accumulation and ecological risk remains insufficiently understood in subtropical ecosystems. This study investigated the seasonal distribution and ecological risk of six heavy metals (As, Cd, Cr, Hg, Ni, and Pb) across three forest types, monsoon evergreen broadleaf forest (MEBF), pine-broadleaf mixed forest (PBMF), and Pinus massoniana forest (PMF), in Dinghushan, South China. Soil samples were collected during dry and wet seasons and assessed using contamination factor (CF), geoaccumulation index (I_geo), and potential ecological risk index (PERI), complemented by multivariate statistical analyses. Heavy metal concentrations varied significantly among forest types and seasons. MEBF exhibited higher concentrations of most metals, particularly As, Cr, and Hg, likely due to greater organic matter content and enhanced retention capacity typically associated with mature broadleaf forests. In contrast, PMF showed lower overall concentrations but relatively higher Pb and Ni. Several metals displayed elevated concentrations during the wet season, indicating enhanced redistribution under increased soil moisture. Multivariate analyses revealed that Ni and Cr were strongly associated and may reflect lithogenic influences, whereas Hg, As, and Pb showed patterns consistent with possible atmospheric inputs and ecological processes. Arsenic concentrations reached 65.03 mg.kg⁻1 in MEBF during the wet season. Overall ecological risk was low to moderate but increased during the wet season. These findings highlight the interactive effects of forest type and seasonal hydrology on heavy metal dynamics in subtropical forest soils.
Human social interactions rely on the ability to reflect on one's own and others' internal states and traits-a process known as mentalizing. Impaired or altered mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total n = 390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas, respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based mentalizing about self and others-present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions.
Blood types can influence host susceptibility to infectious diseases by modifying erythrocyte surface antigens that act as pathogen receptors. In cats, AB blood group system polymorphisms determine the expression of distinct sialic acids, with the N-glycolylneuraminic acid (NeuGc) primarily expressed in type A, the N-acetylneuraminic acid (NeuAc) in type B, and both in type AB erythrocytes. This study investigated whether feline blood type influences susceptibility to Bartonella henselae, the agent of cat-scratch disease. A total of 454 blood and serum samples from stray colony, shelter, and owned cats in northern (Milan, Lombardy) and southern (Palermo, Sicily) was analyzed. Blood phenotyping was performed using tube agglutination, and back-typing, and immunochromatography were used to confirm type B and AB samples. B. henselae infection was determined by indirect immunofluorescence antibody test (IFAT) and real-time PCR. Univariate and multivariable logistic regression analyses evaluated associations between blood type, demographic factors, and infection markers. Overall, B. henselae infection prevalence was 19.4% (95% CI:15.8-23.3). Seropositivity was 33.3% among IFAT-tested cats, while PCR positivity was 8.8%. Geographic origin and lifestyle were strong predictors of infection: cats from southern Italy and stray colony or shelter cats were at significantly higher risk, while owned cats were protected. Blood type B was independently associated with PCR positivity (OR=2.6, 95% CI:1.1-5.6, P = 0.017). This association may reflect differences in NeuAc-mediated bacterial adhesion, but causality cannot be inferred from these data. These findings support a potential role of erythrocyte glycan composition in feline-Bartonella interactions but warrant further molecular confirmation. SIGNIFICANCE STATEMENT: This study provides preliminary evidence of an association between feline AB blood group system phenotypes and Bartonella henselae infection markers. By integrating serological and molecular diagnostics across a large, geographically diverse cat population, we observed that type B cats-characterized by NeuAc-rich erythrocyte membranes-had an approximately 2.6-fold greater probability of B. henselae DNA positivity. These findings support the hypothesis of a potential receptor-mediated mechanism underlying pathogen-erythrocyte interactions in cats, analogous to human blood group-dependent infectious processes. The work highlights how naturally occurring variation in erythrocyte glycan composition may shape host-pathogen dynamics, advancing our understanding of the evolutionary immunology of vector-borne diseases in companion animals.
Sepsis-induced ARDS demonstrated greater severity and higher mortality compared to ARDS triggered by other factors. In this article, we comprehensively explored the roles of cellular senescence (CS)-related genes in sepsis-induced ARDS, highlighting their hub molecules and upstream regulatory network via machine learning (ML) methods. RNA-sequencing data of sepsis-induced ARDS and CS-related genes were obtained from online accessible databases. A total of three machine learning methods were applied to identify CS-related hub molecules in sepsis-induced ARDS. The RegNetwork database was used to explore the upstream regulatory network of CS-related hub molecules. Single-cell RNA-sequencing (scRNA-seq) data was also used to verify the expressions of these CS-related hub molecules. We further constructed a sepsis-induced ALI/ARDS mouse model and validated these hub molecules by qRT-PCR. A total of 40 CS-related differentially expressed genes (DEGs) were identified in sepsis-induced ARDS. Based on these, consensus clustering identified two potential molecular subtypes (Cluster A and B), and a total of six intersected genes (UBE2C, RPS6KA2, CCNA2, EZH2, CALM1, and E2F2) were finally regarded as hub molecules in sepsis-induced ARDS via three machine learning methods. These CS-related hub molecules were verified for their expressions at scRNA-seq levels. Correlations between these six hub molecules and 23 immune infiltration cell types were further revealed, and we also established the mRNA regulatory network of the miRNA/TF-six CS-related hub molecules. Besides, qRT-PCR results showed that the E2f2, Ezh2, and Ube2c genes had a higher expression in the sepsis-induced ALI/ARDS subgroup than in the control subgroup, while others did not (P-value < 0.05). Our study highlighted the CS-related E2F2, EZH2, and UBE2C genes as hub molecules in sepsis-induced ARDS and their upstream regulatory network by means of machine learning methods.
Reliable biomarkers are needed to support the early diagnosis of UTI. This study investigated the diagnostic value of urinary Neutrophil Gelatinase-Associated Lipocalin (uNGAL) and conventional inflammatory markers in the diagnosis and differentiation of UTI types. In this prospective study (2024-2025), 259 adults with positive urine cultures were classified as having asymptomatic bacteriuria, uncomplicated UTI, complicated UTI, recurrent UTI, or catheter-associated UTI according to the 2025 IDSA Complicated UTIs Guideline. uNGAL was measured by ELISA. uNGAL levels were numerically higher in UTI patients than controls (p=0.458). uNGAL levels did not show significant discrimination between controls and UTI subtypes (p=0.643). uNGAL levels were slightly higher in patients with recurrent UTI than in those without recurrent UTI and in patients with catheter-associated UTI than in non-catheterized patients (p=0.657 and p=0.058, respectively). Although NGAL could not distinguish complicated from uncomplicated UTI (p=0.272), CRP and WBC levels were significantly higher in complicated UTI (median 21 vs. 6 mg/L, p< 0.001; median 9800 vs. 7300 /mm³, p< 0.001, respectively). ROC analysis identified optimal cut-off values of 10.5 mg/L for CRP and 7850/mm³ for WBC; with sensitivities of 65% and 76% and specificities of 75% and 60%, respectively. Multivariate analysis showed that each 10 mg/L increase in CRP and each 1000/mm³ increase in WBC was associated with a 1.2 fold higher likelihood of complicated UTI. uNGAL does not provide diagnostic value beyond conventional inflammatory markers and should not be used as a standalone biomarker in adult UTI. CRP and WBC remain more reliable markers for predicting complicated UTI.
Reliable quality assessment in digital pathology is essential to ensure the diagnostic usability of whole slide images (WSIs), as artifacts introduced during tissue preparation and scanning can degrade image quality and affect clinical interpretation. In this paper, we propose a framework that combines subjective usability evaluation with an objective no-reference quality assessment method. A dataset was constructed from WSIs of four tissue types (breast, fertility, gastrointestinal, and lung), where pristine patches were systematically degraded using simulated artifacts including blur, contrast, and color variations. A subjective study with eight pathologists was conducted using a five-point diagnostic usability scale, from which Mean Usability Scores (MUS) were derived and statistically validated. An objective metric was then developed based on contrastive learning-driven pseudo-reference generation, followed by a siamese feature extraction and regression model to predict usability. The proposed method shows strong correlation with expert scores and outperforms several existing quality assessment metrics, while demonstrating consistent performance across multiple distortion types and tissue categories. Our proposed model outperforms competing objective metrics, achieving strong consistency with subjective scores with SRCC of 0.945, PLCC of 0.952, and AUC of 0.98 on the benchmark dataset. The proposed objective metric, together with the designed subjective assessment method and the publicly available dataset, provides a reliable framework for expert-aligned quality assessment in digital pathology.
The mechanical responses and properties of breast epithelial cells are known to change during malignant transformation and progression due to the dynamics of their actin cytoskeleton network organization and the resulting viscoelastic deformability. Studying the viscoelastic creep behavior of breast cells may reveal new avenues for developing novel cancer diagnostic and therapeutic biomarkers and improving fundamental biophysical understanding of the disease. Here we present an approach that uses functional principal component analysis (fPCA) to distinguish between the viscoelastic responses of malignant and non-malignant live breast cells that are subjected to shear flow in microfluidic channels under in-situ observation with optical, fluorescence, and confocal microscopy. The fPCA method extracts critical features of cell viscoelasticity from the in-situ measured creep responses of non-tumorigenic breast cells (MCF-10A), less metastatic triple-negative breast cancer (TNBC) cells (MDA-MB-468), and highly metastatic breast cancer cells (MDA-MB-231). The results demonstrate distinguishable clustering patterns for the three types of cells in the first principal component (PC) and the second PC space. The first PC, indicative of the overall level of creep compliance, accounts for more than 98% of the total variance in the observed creep responses. The scores of the cells examined on the first PC axis increase with increasing cancer malignancy. They also correlate highly with the average moduli and viscosities extracted from viscoelastic models (-83% correlation with moduli and -85% correlation with viscosities). This suggests a direct link between the malignancy of cancer and the overall creep compliance level that is governed by cell viscoelastic properties. The implications of the results are discussed for the detection of non-tumorigenic and tumorigenic breast cells at different stages of cancer progression.
The molecular basis for specific pairing between transcriptional enhancers and promoters remains a highly active area of investigation, even over four decades after enhancers were first discovered. Numerous studies have explored general mechanisms such as those involving the cohesin/CTCF system and the core transcriptional machinery, including RNA polymerase 2, but these fail to account for the specificity of gene expression across cell types, maturation stages, and cell cycle intervals. Genetic loss of tissue-specific transcription factors provided early insights, but the findings were fraught with potentially confounding secondary effects. The advent of tools permitting rapid protein degradation has changed that. Here we discuss recent studies of illustrative mammalian transcription (co-) factors with architectural roles that contribute to enhancer-promoter communication, and contextualize their functions within generic chromatin-organizing principles.
Terconazole is an effective antifungal drug with a broad spectrum of activity against many types of fungi. In the study, a spectrofluorimetric method was developed for the quantification of terconazole. Eosin Y, an efficient fluorescence probe, was used in the developed work. The developed method is based on forming a non-fluorescent association complex between terconazole and eosin Y, which quenches eosin Y's inherent fluorescence intensity at both excitation and emission spectra. This quenching effect is highly correlated with the concentration of terconazole, with a linear range of 0.15-1.2 µg/mL. Furthermore, Stern-Volmer analysis was carried out to study the quenching fluorescence strength of eosin Y by terconazole. Moreover, the developed method exhibits an LOD of 0.041 µg/mL and a LOQ of 0.125 µg/mL. Moreover, the recommended method was verified in accordance with ICH guidelines. In addition, with respectable recovery values, the established procedures were successfully applied to the analysis of terconazole in vaginal cream dosage forms. Furthermore, the greenness of the entire proposed project was assessed using the following assessment tools: MoGAPI, Complex MoGAPI, MoGSA, BAGI, and RAPI. The green profiles provided outstanding evidence of the greenness and environmental friendliness of the proposed approach.
Orphan nuclear receptors (ONRs) are members of the nuclear receptor superfamily initially identified without clearly defined endogenous high-affinity ligands. Nevertheless, increasing evidence demonstrates that they play essential roles in regulating metabolism, development, neural function, and tumorigenesis. Recent advances in structural biology, chemical biology, and systems biology have improved understanding of ligand recognition and regulatory mechanisms in these receptors. This review summarizes current progress in ONRs ligand research. ONRs are categorized according to their physiological roles in metabolic homeostasis, development and reproduction, and neuro-immune and cancer-related regulation, highlighting their involvement in diseases such as metabolic disorders, cancers, neurological diseases, and reproductive abnormalities. We discuss the structural basis of ligand recognition, focusing on conserved features of the ligand-binding domain (LBD) and structural variations, particularly in the α10 and AF-2 helices, that influence ligand accessibility and transcriptional regulation. Structural studies have revealed ligand-receptor complexes for representative ONRs, including ROR, HNF-4, REV-ERB, ERR, SF-1, and LRH-1, identifying ligand types such as lipids, heme, and phospholipids. In contrast, other receptors, including TR4, DAX-1, COUP-TFII, and Nur77, currently have only functional evidence supporting potential ligand interactions. Key strategies for ligand discovery include endogenous ligand co-purification, phenotype-based high-throughput screening, structural biology approaches, and structure-based virtual screening combined with molecular dynamics simulations. Major challenges include difficulties in endogenous ligand identification, context-dependent regulation, and limitations in achieving receptor subtype selectivity in drug development. Future progress will rely on integrating structural, biochemical, and multi-omics approaches to facilitate therapeutic targeting of ONRs.
This study examines how COVID-19 affected educational disparities among 652 university students in Guangxi, China, through quantitative cross-sectional analysis. Data collected via online survey in spring 2022 captured demographic variables, resource access, and academic performance across diverse institution types. Results show significant differences: 28.3% of low-income students lacked adequate digital tools versus 8.7% of high-income peers; 37.8% of low-SES students reported grade declines-nearly double the high-SES rate. Regression analysis identifies SES as a significant predictor of learning effectiveness (β = 0.25, p < 0.001), with teacher and family support moderating its impact. Psychological distress was prevalent, particularly among rural and female students, yet only 15% accessed institutional support services. Findings align with social reproduction theories and identify potential policy interventions to address these disparities in higher education during emergency contexts.