Search Results (68)

Background: Prosthetic joint infections (PJI) are complex complications of arthroplasty. Detailed sequential polymicrobial infection during long clinical courses, with multiple interventions and sustained antibiotic pressure, has been described sparingly. Methods: We present a case of a 78-year-old woman with various comorbidities, including type 2 diabetes mellitus and grade I obesity (body mass index of 31.6), who developed an early PJI after total knee arthroplasty, followed by amputation. Results: Despite serial surgical procedures and antimicrobial therapies, the patient had progressive structural failure in a complex polymicrobial PJI. Therefore, above-knee amputation was required due to reconstructive failure. During the 23-month clinical course, infections caused by six distinct bacteria, some of which were resistant and associated with intramedullary osteomyelitis, were reported at different stages. Conclusions: This case illustrates the evolution and challenging complications of a rare yet dynamic process that developed under selective surgical and antimicrobial pressure. Early recognition of host, tissue, and microbial factors is crucial to achieving optimal PJI outcomes. Full article

Despite the success of modern antiretroviral therapy in achieving virological suppression, people living with HIV face an elevated risk of cardiovascular diseases, particularly heart failure with preserved ejection fraction. This study evaluates the cardiometabolic phenotype and functional capacity in a Romanian HIV cohort to delineate the metabolic footprint of chronic infection. In this cross-sectional study based on prospectively collected, protocol-driven phenotyping, we evaluated 50 consecutive outpatients from a university-affiliated infectious diseases clinic in Timisoara. Eligibility strictly required clinical stability and sustained virological suppression (plasma HIV-RNA < 50 copies/mL for ≥12 months). The analysis revealed widespread metabolic dysregulation, with 52% exhibiting excess weight and 64% showing atherogenic dyslipidemia. Integrase strand transfer inhibitor-based regimens were significantly correlated with an increased body mass index (p = 0.034) and elevated LDL cholesterol (aOR = 2.4, 95% CI [1.18–4.95], p = 0.022). Furthermore, we observed a pronounced metabolic age gap (+4.5 ± 2.8 years), defined as the deviation of bioimpedance-estimated metabolic age from the patients’ chronological age. This gap (p = 0.028), alongside historical immunodeficiency indicated by a low nadir CD4+ count (aOR = 0.998, 95% CI [0.991–0.999], p = 0.021), strongly predicted exercise intolerance, independent of current immune reconstruction. Sarcopenic obesity (present in 18% of the cohort) and an elevated triglycerides-to-HDL ratio (aOR = 2.14, 95% CI [1.15–3.98], p = 0.016) emerged as robust independent negative predictors of functional capacity. Additionally, subclinical myocardial remodeling, evidenced by impaired Global Longitudinal Strain, significantly predicted reduced aerobic capacity (aOR = 0.72, 95% CI [0.58–0.89], p = 0.003). Consequently, contemporary HIV management must transition beyond virological control to integrated cardiometabolic screening. Utilizing cardiopulmonary exercise testing, echocardiography, and metabolic biomarkers is critical for the early identification of subclinical “functional HIV-associated frailty” and mitigating the trajectory toward overt cardiovascular diseases. Full article

Speech-based stress analysis is relevant to forensic-oriented speech processing, security screening, and behavioral monitoring, yet its reliability is often limited by speaker variability, recording conditions, and acoustic mismatch. This study proposes an interpretable multi-domain signal processing framework that models stress-related speech variation through excitation dynamics, vocal tract characteristics, and temporal modulation patterns. The framework integrates source–filter decomposition, residual-domain analysis, harmonic structure analysis, modulation spectrum characterization, and prosodic variability into a unified representation. The SUSAS corpus is used as the primary dataset for supervised stress evaluation. RAVDESS and SAVEE are employed only as controlled arousal-related proxy datasets to examine the consistency of stress-related acoustic patterns, rather than as physiological stress ground truth. VoxCeleb is used exclusively for robustness and domain-variability analysis because it lacks stress labels. For probabilistic evidence assessment, Gaussian mixture models are adopted as the more interpretable density estimator, while normalizing flow is included as a flexible performance-oriented comparator for modeling non-Gaussian feature distributions. Evaluation incorporates likelihood ratio analysis, DET curves, EER, ablation studies, and robustness testing. The proposed framework achieves an EER of 5.8% in the primary supervised evaluation, showing competitive performance while preserving physically meaningful interpretation. Full article

This study proposes an explainable framework for ESG portfolio rebalancing by integrating carbon credit signals, technical indicators, and Transformer-inspired forecasting into a unified decision process. The investable universe consists of six ESG-themed ETFs, namely ESGU, SUSA, ICLN, TAN, KRBN, and KGRN. Carbon-related sustainability information is represented by four S&P carbon indices, including GCC, CCA, EUA, and UCITS. Within the proposed framework, Transformer, Informer, and Temporal Fusion Transformer are used to predict next-day returns, and the forecast outputs are translated into portfolio decisions through threshold filtering, Softmax-based allocation, and inertia smoothing under fixed transaction costs. The empirical results show that the proposed framework remains competitive against Equal Weight, Risk Parity, and Momentum benchmarks, although its advantage is conditional rather than uniformly dominant across all metrics. Informer delivers the strongest Sharpe ratio among the model-based strategies, while Transformer exhibits a more stable risk profile. The ablation results indicate that the smoothing mechanism has the clearest effect on turnover and allocation stability, whereas the incremental value of carbon-related inputs is most visible in Informer. The uncertainty assessment further shows that many benchmark differences are not consistently significant under repeated resampling, but the performance weakening caused by removing carbon inputs in Informer remains identifiable. The subperiod analysis shows that benchmark rules are more competitive in 2024H1, whereas model-based strategies gain relative strength in 2024H2. The explainability analysis indicates that carbon-feature contributions are concentrated more strongly in Intermediate and Carbon-Sensitive asset groups and remain weaker in Broad ESG assets; feature-level and SHAP beeswarm evidence further shows that the three architectures rely on GCC, CCA, EUA, and UCITS in different ways. These findings suggest that carbon-related sustainability signals can provide economically meaningful allocation information in selected settings when they are combined with suitable model architecture and disciplined rebalancing control, thereby supporting a competitive and explainable ESG portfolio rebalancing framework. Full article

Because prostate cancer proliferates in an androgen-dependent manner, various inhibitors of androgen production and antagonists of the androgen receptor (AR) are used as therapeutic agents. However, the emergence of castration-resistant prostate cancer has prompted the development of additional treatment strategies. In this study, we focused on the antiprostate cancer effects of vitamin D3 and examined novel antiproliferative effects through the crosstalk with androgen signaling. In human prostate cancer LNCaP cells, homeobox C9 (HOXC9) was identified as a common regulated target gene by dihydroxytestosterone and 1α,25-dihydroxyvitamin D3, but in opposite directions. Ligand-stimulated AR and vitamin D receptor competitively shared binding sites in the HOXC9 regulatory region, but dihydroxytestosterone stimulation preferentially suppressed HOXC9 expression due to the stronger binding properties of AR and the induction of DNA methylation. Forced expression of HOXC9 inhibited androgen signaling to eliminate the androgen-dependent proliferation by associating with the AR transcription complex, in part due to interference with AR binding to some of its targets in LNCaP cells. In summary, this study provides evidence for the involvement of HOXC9 in antiproliferative effects through a regulatory mechanism mediated by a crosstalk between vitamin D receptor and AR. Full article

Background/Objective: Type 2 diabetes mellitus (T2DM) is a known risk factor for cardiovascular disease (CVD); however, not all individuals with T2DM have the same CVD risk. Traditional glycemic cluster analyses of individuals with diabetes using the homeostatic model assessment estimate of insulin resistance (HOMA-R) as an indicator of insulin resistance have identified severe insulin-resistant diabetes as a high-risk factor for incident CVD. To extend this observation, we further classified non-diabetic individuals to identify risk clusters for incident CVD. Methods: We performed hierarchical cluster analysis of 577 non-diabetic Japanese individuals using the glycated hemoglobin level, body mass index, homeostasis model assessment estimate of β-cell function, and the triglyceride-glucose (TyG) index instead of the HOMA-R to assess incident CVD risk over up to 188 months. Results: Analysis using a multiple risk factor-adjusted Cox proportional-hazard regression model showed that in addition to impaired glucose tolerance (IGT), among the four clusters observed, a cluster labeled “low insulin secretion (Low-IS (TyG))” was a risk factor for incident CVD (hazard ratio, [95% confidence interval]: 2.77 [1.11–6.91]). Furthermore, when the participants were stratified on the basis of the presence of IGT, the Low-IS (TyG) cluster was associated with an increased risk of CVD only in the non-IGT group (3.29 [1.32–8.18]), but not in the IGT group (1.66 [0.34–8.15]). Conclusions: Glycemic clustering incorporating the TyG index identified a novel at-risk group for incident CVD among non-diabetic individuals, offering a useful tool for early CVD risk stratification beyond traditional measures of glucose tolerance. Full article

This study examines the mechanisms through which ecological public art influences pro-environmental behavior, addressing the urgent challenges of the global ecological crisis and sustainable urban development. Using the 5th Shanghai Urban Space Art Season (SUSAS) as a case study, a serial multiple mediation model was established, with ecological public art perception as the independent variable, environmental psychological ownership and ecological awareness as mediators, and pro-environmental behavior as the dependent variable. Based on 326 valid responses, structural equation modeling (SEM), which integrates confirmatory factor analysis (CFA) and path analysis, demonstrates that ecological public art perception significantly enhances pro-environmental behavior. Environmental psychological ownership and ecological awareness function not only as independent mediators but also jointly constitute a serial mediation pathway. The findings reveal a multidimensional process whereby ecological public art enhances pro-environmental behavior through “perceptual activation–emotional identification–cognitive enhancement–behavioral transformation”. Building on these insights, the study proposes intervention strategies focusing on multi-sensory integration, emotional narrative, digital technology application, and community-based practices to reinforce the role of ecological public art in urban environmental governance and sustainable development. Overall, this research advances the theoretical understanding of the social functions of public art and offers a valuable perspective for fostering ecological awareness and action. Full article

Background/Objectives: Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis have become a standard in the treatment of all stages of non-small lung cancer. Beyond tumor-intrinsic biomarkers like PD-L1 expression, evidence points to the role of patient-related factors, such as body mass index, sarcopenia, and cachexia. These body composition parameters may reflect metabolic reserve or even immune competence and could help stratify outcomes in patients treated with PD-1 and PD-L1. This systematic review aims to evaluate the impact of body composition—specifically BMI, pretreatment weight loss, sarcopenia, and cachexia—on clinical outcomes such as progression-free and overall survival in NSCLC patients treated with immune checkpoint inhibitors. Methods: A systematic literature search was conducted across multiple databases including PubMed, Google Scholar, and Science Direct. We included full-text original research articles (1 January 2020–1 May 2025) reporting clinical outcomes of NSCLC patients treated with PD-1 or PD-L1 inhibitors, in relation to body composition factors (BMI, pretreatment weight loss, sarcopenia, cachexia). Eligible studies involved adults (>18 years) and included observational cohorts or controlled trials; animal or in vitro studies were excluded. Data extraction and risk of bias assessments were performed independently by two reviewers, with discrepancies being resolved through a third one. Results: From 12,358 records identified, 21 studies met the inclusion criteria. Most were retrospective cohorts assessing the impact of pre-treatment weight loss, cachexia, and sarcopenia on ICI outcomes in NSCLC. These factors consistently predicted poorer survival and response, while BMI alone showed limited prognostic value. Considerable heterogeneity in body composition definitions and outcome reporting was observed. Conclusions: Body composition—particularly weight loss, cachexia, and sarcopenia—significantly impacts survival and response in NSCLC patients treated with ICIs. These factors reflect immune–metabolic dysfunction that may impair treatment efficacy. BMI alone is insufficient; routine assessment of muscle mass and cachexia could improve risk stratification. Full article

In regions with sustained air pollution, the adoption of protective health behaviors is critical, particularly among pregnant women—a population marked by physiological vulnerability and heightened receptivity to preventive guidance. Understanding and supporting patient-driven behavioral change requires attention to individual perception and awareness, which are shaped by socio-economic and spatial factors, as well as access to credible information. Objectives: This study investigates how pregnant women in Serbia perceive air quality, identifies determinants that influence these perceptions, and evaluates the extent and nature of behavioral adaptations undertaken to mitigate exposure-related risks. Methods: A cross-sectional survey was conducted among 279 pregnant women using a structured, researcher-administered questionnaire. Collected data included demographic and psychosocial variables, air quality perceptions, self-reported health effects, and behavioral responses. Residential proximity to land-use attributes was assessed using GIS-based spatial analysis. Results: Most participants perceived air quality as poor (68.8%), primarily informed by unofficial sources such as mobile applications and social media. Living close to continuous urban fabric (OR = 0.180, 95% CI: 0.059–0.558, p = 0.003) and water (OR = 0.306, 95% CI: 0.127–0.738, p = 0.008) was associated with poorer perceptions, while proximity to forests (OR = 2.938, 95% CI: 1.323–6.525, p = 0.008) correlated with more favorable assessments. Despite prevalent concern, around half of respondents (50.2%) reported no behavioral modifications. Importantly, none had received guidance from healthcare professionals on the topic. Conclusions: These findings highlight critical gaps in environmental health literacy and provider engagement. Integrating tailored communication and behavioral support in existing prenatal counseling could advance health-related quality of life in this vulnerable population. Full article

As gestational diabetes mellitus (GDM) rises as a major public health concern, various factors have been identified as potential contributors, with air pollution drawing increasing attention. The mechanisms by which air pollutants lead to detrimental impacts are largely attributed to oxidative stress. However, the role of air pollution is still not entirely clarified, suggesting that additional factors, such as genetic variability, particularly of genes involved in redox homeostasis, influence the GDM risk. This study addresses three questions: (1) whether ambient PM_2.5, PM₁₀, O₃, and NO₂ exposures associate with GDM risk; (2) if GSTM1-/GSTT1-null genotypes affect the risk of GDM; and (3) whether these genotypes modify pollution–GDM associations. This case–control study comprised 133 women in the case group and 144 in the control group. Exposure to air pollutants was assessed based on the participants’ residential addresses and during different time windows: pre-pregnancy period, first trimester, and second trimester. GSTM1/GSTT1 genotyping was conducted from blood samples. Higher PM_2.5, PM₁₀, and O₃ levels increased GDM risk in women. While GSTM1-/GSTT1-null genotypes showed no overall link to GDM, non-smokers with GSTM1-null had higher GDM risk when exposed to PM_2.5 during the first trimester. While further research on gene–environment interactions is needed, our findings highlight that reducing air pollution may lower GDM risk. Full article

Leading-edge analog/mixed-signal LSI designs are still hand-crafted using graphic editors. These graphic editors do not include functionality for parameterized topologies in variable designs. Instead of graphic editors, we have developed the SWA (SoftWare Analog) language, which can describe and display placements and routing for analog/mixed-signal LSI layouts with less or similar labor time. By using SWA, we have developed an R-DAC (resistive digital–analog converter) layout with a parameterized topology and various parameters, such as ~1 Gsps, 4~12-bit (upper segment type + lower R-2R type) R-DAC, and 1~3.3 V logic with 1~3.3 V_pp analog output. Full article

Sulfonylureas (SUs)—a class of drugs primarily used to treat type 2 diabetes—have recently attracted interest for their potential anticancer properties. While some studies have explored the chemical modification or design of new SU derivatives, our work instead centers on biological evaluations of all commercially available SUs in combination with doxorubicin (DOXO). These antidiabetic agents act by stimulating insulin secretion via K_ATP channel inhibition, and because K_ATP channels share structural features with ATP-binding cassette (ABC) transporters involved in multidrug resistance (e.g., P-glycoprotein, MRP1, and MRP2), SUs may also reduce cancer cell drug efflux. In this study, we systematically examined each commercially available SU for potential synergy with DOXO in a panel of human cancer cell lines. Notably, combining DOXO with glimepiride (GLIM), the newest SU, results in a 4.4-fold increase in cytotoxicity against MCF-7 breast cancer cells relative to DOXO alone. Mechanistic studies suggest that the observed synergy may arise from increased intracellular accumulation of DOXO. Preliminary in vivo experiments support these findings, showing that DOXO (5 mg/kg, i.v.) plus GLIM (4 mg/kg, i.p.) is more effective at inhibiting 4T1 tumor growth in mice than DOXO alone. Additionally, we show that adding a small amount of the surfactant Tween-80 to culture media affects SU binding to bovine serum albumin (BSA), potentially unmasking anticancer effects of SUs that strongly bind to proteins. Overall, these results underscore the potential of repurposing existing SUs to enhance standard chemotherapy regimens. Full article

Background and Objectives: Klebsiella pneumoniae is a major nosocomial pathogen with a remarkable ability to develop resistance to multiple antibiotics, posing significant treatment challenges. This study aims to evaluate the antimicrobial resistance patterns among multidrug-resistant (MDR) and non-MDR strains of K. pneumoniae isolated over a six-year period (2018–2023) at the Clinical Hospital of Infectious Diseases and Pulmonology “Dr. Victor Babes” in Timisoara, Romania. The objectives include categorizing isolates based on their antibiotic resistance profiles and identifying trends in resistance to key antibiotics to optimize treatment strategies and enhance infection control measures. Materials and Methods: A cross-sectional analysis was conducted on K. pneumoniae isolates obtained from various clinical samples between January 2018 and December 2023. Identification was performed using standard bacteriological procedures, and antimicrobial susceptibility testing was conducted using the Kirby–Bauer disk diffusion method in accordance with EUCAST guidelines. Isolates were classified as susceptible, resistant, MDR, extensively drug-resistant (XDR), or pandrug-resistant (PDR) based on ECDC definitions. Data were analyzed using GraphPad Prism 6, with chi-square tests and Cochran–Armitage trend tests applied where appropriate. Statistical significance was set at p < 0.05. Results: A total of 1,081 K. pneumoniae isolates were identified over the six-year period, increasing from 118 isolates in 2018 to 319 in 2023. The proportion of XDR and PDR strains showed a significant upward trend from 30.5% in 2018 to 57.4% in 2023 (p < 0.001). Specifically, XDR strains increased from 22.9% in 2018 to 39.8% in 2023, while PDR strains rose from 7.6% to 17.6%. Among monomicrobial infections in 2023, XDR and PDR strains accounted for 42.4% and 16.5%, respectively. Resistance to carbapenems also showed a significant increase; for instance, resistance to ertapenem rose from 35.6% in 2018 to 54.2% in 2023 (p < 0.001). Subgroup analysis revealed that isolates from bronchial aspirates had the highest rates of XDR and PDR strains in 2023, at 38.0% and 17.2%, respectively. Additionally, polymicrobial infections where both K. pneumoniae and co-infecting pathogens were XDR/PDR increased from 24.2% in 2018 to 46.6% in 2023 (p < 0.001). Conclusions: The study demonstrates a significant escalation in antimicrobial resistance among K. pneumoniae isolates over the six-year period, particularly in XDR and PDR strains. The rising trend of resistance to critical antibiotics like carbapenems underscores the urgent need for enhanced antimicrobial stewardship and infection control measures. Targeted interventions are essential to curb the spread of these resistant strains and to optimize therapeutic strategies. Full article

Background/Objectives: Antimicrobial resistance (AMR) is a critical global health threat, leading to increased morbidity, mortality, and healthcare costs. This study aimed to identify the most common bacterial pathogens and their resistance profiles from 2179 positive clinical cultures from inpatients at “Victor Babes” Hospital of Infectious Disease and Pneumoftiziology Timisoara in 2023. Methods: Samples were collected from sputum, bronchial aspiration, hemoculture, urine, wound secretions, catheter samples, and other clinical specimens. Results: Key pathogens identified included Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii, with notable resistance patterns, observed K. pneumoniae exhibited high resistance rates, notably 41.41% in Quarter 1, while E. coli showed 35.93% resistance in the same period. S. aureus, particularly MRSA, remained a persistent challenge, with 169 cases recorded over the year. A. baumannii and P. aeruginosa displayed alarming levels of multi-drug resistance, especially in Quarter 3 (88.24% and 22.02%, respectively). Although there was a general decline in resistance rates by Quarter 4, critical pathogens such as S. aureus and K. pneumoniae continued to exhibit significant resistance (81.25% and 21.74%, respectively). Conclusions: The study’s findings align with the broader antimicrobial resistance trends observed in Romania, where high resistance rates in K. pneumoniae, E. coli, S. aureus (MRSA), Acinetobacter, and Pseudomonas species have been widely reported, reflecting the country’s ongoing struggle with multi-drug-resistant infections. Despite some reductions in resistance rates across quarters, the persistent presence of these resistant strains underscores the critical need for strengthened antimicrobial stewardship, infection control measures, and continuous surveillance to combat the growing threat of AMR in Romania and similar healthcare settings. Full article

We have developed SWA: SoftWare for Analog design automation. Its commands can describe analog and mixed-signal (AMS) layouts and schematics to replace the graphic editor with a program reflecting the knowledge of design experts. Also, it is able to utilize variables to parameterize schematics and layouts to fulfill design needs. We programmed a 10b 1 GS/s DAC using SWA with 8.3 K lines of code, which is about 1/10 compared with conventional programs. The programmed DAC is configurable with multiple voltages and multiple resolutions from 4 to 12 bits. The DAC schematic and layout generation with DRC and LVS SWA API can be finished in about 1 min. Full article