Background: Chronic kidney disease (CKD) affects over 35.5 million US adults. Serum α1-acid glycoprotein (α1-AGP), an acute-phase protein, exhibits anti-inflammatory properties in animal models, but its association with CKD in younger women remains underexplored. This study investigated the relationship between serum α1-AGP and CKD risk in US women aged 20–49 years. Methods: This nationally representative cross-sectional study used data on female adults in the US aged 20–49 years from the National Health and Nutrition Examination Survey 2015–2018 cycles. 2,137 individuals were included in the study after excluding individuals without serum α1-AGP, urine albumin, and creatinine data. Multivariate logistic regression models evaluated the association between serum α1-AGP and CKD. Moreover, we performed stratified and interaction analyses to see if the relationship was stable in different subgroups. Results: Among 2,137 participants (mean age 34.6 years, mean eGFR 111.7 mL/min/1.73 m²), CKD prevalence was 8.8% (n=188). Higher serum α1-AGP levels were associated with lower CKD risk in the fully adjusted model (OR 0.37, 95% CI 0.16–0.84, P = 0.017), with a dose-response trend across quartiles (P = 0.041). The association was stronger in women aged 40–49 years (OR 0.20, 95% CI 0.05–0.76) and Mexican Americans (OR 0.07, 95% CI 0.01–0.56), though interaction terms were not significant (P > 0.05). Conclusions: Higher serum α1-AGP levels are associated with lower CKD prevalence in young women, suggesting a protective role. Longitudinal studies are needed to confirm causality and explore α1-AGP as a biomarker for CKD risk stratification.

Beaches are known for their ability to provide people with several services – these are generally referred to as ‘ecosystem services’ and they have been identified as one of the ways through which nature relates to humans. However, beaches in Nigeria are challenged by mismanagement caused by anthropogenic factors. It is expected that people will demonstrate a certain amount of dedication to protecting this ecosystem to address this issue. Sometimes, a person's commitment to conservation is based on the advantages they anticipate or are currently experiencing from the ecosystem, which are a result of their socioeconomic traits. Against this backdrop, this study captured individuals’ commitment as their Willingness to Pay (WTP) for these ecosystem services, assessed their level of awareness of the various ecosystem services provided by beaches and investigated the impact of socioeconomic factors on participants’ willingness to pay. Data were collected using a structured questionnaire and a total of 221 responses were analyzed using descriptive statistics, logistic regression and content analysis. The results revealed that the cultural service provided by beaches was the most common ecosystem service identified by the participants. Furthermore, most of the participants were willing to pay less than $3 for beach maintenance while the major determinants of WTP were age, household size and education. This study recommended that the government should work with other stakeholders to set up programs that would boost people’s awareness of ecosystem services provided by beaches as well as reiterate the need to maintain this ecosystem to ensure continued enjoyment of the services provided.

This review aimed to analyze some problems and challenges that emerged from the COVID-19 pandemic since it has affected all global business sectors. During the pandemic, remote work was increased in response to social distance requirements to decrease the transmission of disease. In addition, increased delegation, teamwork, supply chains, sales activities, and business operations have all been disrupted. Many challenges have emerged in the management of organizations due to the pandemic including the lack of direct contact as the lockdown made many people work from home and placed restrictions on movement and travel and uncertainty about the future. The healthcare system was also affected by the COVID-19 pandemic and faced several difficulties including increased demand for medical supplies and personal protective equipment, a greater need for nurses and other skilled healthcare professionals, and increased pressure on healthcare facilities, emergency services, and critical care departments. These challenges have created some opportunities in the management systems of healthcare organizations and other sectors. It is recommended for leaders prepare and continuously work proactively to be ready for unexpected future crises. Risk management and planning for any unexpected situation are among the very important aspects of organizational management.

Triple negative breast carcinoma (TNBC) is a rapid progressive tumor and has a poor overall survival. Therefore, it is crucial to find out effective molecular targets and develop optimal therapeutic strategies for TNBC. In this study, immunohistochemical staining was used to detect expressions of programmed death-ligand 1 (PD-L1) and phosphatase and tensin homolog (PTEN) in 136 breast carcinomas including 50 TNBC. The effect of PTEN on regulation of PD-L1 expression was assessed in vitro in the PTEN knockdown TNBC cells. We found that PD-L1(SP142) positive rate in TNBC (48.0%) was significantly higher than non-TNBC (23.3%). PTEN negative rate was 42% in TNBC. The inverse correlation between PTEN and PD-L1(SP142) expression in TNBC was statistically significant (P<0.05). After PTEN knockdown, PD-L1 expression in TNBC cells increased significantly, and the expression level of AKT increased simultaneously. PTEN knockdown promoted cell proliferation, viability and G1/S switch of TNBC cells. These results suggested that PTEN may involve in regulation of PD-L1 expression, because PTEN loss can upregulate PD-L1 expression in TNBC. Antitumor immunity of PD-L1 could be enhanced in TNBC when targeting PTEN at the same time.

Education stratum of India as well as world are worst-hit by Covid-19 and has imposed lockdown originating deleterious effect on academic life. A sheer number of learners ceased moving educational institutions and all pedagogies halted in India. Catastrophe has behaved as a stimulant for the educational institutions to cultivate and choose for platforms with technologies which were previously noviced. Education sector has been challenging to weather the crux with alternative strategy and digitizing the challenges to hoover the menaces of the pandemic. Hypothesis of digital study has prognosis to impact the ventures of higher education for eon. Findings evince that despite digital learning is a nice adventure for little skills, varying illiberalities partake. Learners are crunched and academy also exclusively in unstable job. It has yet to be established the scope whereupon digital study would climactically cover for conventional study. Covid-19 conundrum has divulged prefacing dilemma and disparities clamoring synergetic attempt to contemplate even so pandemic’s approach. This deliberate paper illuminates sparse impeccable education in India and has discussed the positive and negative impacts of Covid-19. The paper also contributes a methodical substantiation of the experience and lessons digested from the impact of the pandemic on the transitional education panorama, and the dissemination and acceptance of e-learning in education. To end, few suggestions along with policy recommendations have been made to meet didactics during the pandemic contingency.

This research is a collaboration involving a university team, a partnering corporation, and a hemodialysis clinic, which is a cross-disciplinary research initiative in the field of Artificial Intelligence of Things (AIoT) within the medical informatics domain. The research has two objectives: (1) The development of an Internet of Things (IoT)-based Information System customized for the hemodialysis machines at the clinic, including transmission bridges, clinical personnel dedicated web/app, and a backend server. The system has been deployed at the clinic and is now officially operational; (2) The research also utilized de-identified, anonymous data (collected by the officially operational system) to train, evaluate, and compare Deep Learning-based Intradialytic Blood Pressure (BP)/Pulse Rate (PR) Predictive Models, with subsequent suggestions provided. Both objectives were executed under the supervision of the Institutional Review Board (IRB) at Mackay Memorial Hospital in Taiwan. The system completed for objective one has introduced three significant services to the clinic, including automated hemodialysis data collection, digitized data storage, and an information-rich human-machine interface as well as graphical data displays, which replaces traditional paper-based clinical administrative operations, thereby enhancing healthcare efficiency. The graphical data presented through web and app interfaces aids in real-time, intuitive comprehension of the patients’ conditions during hemodialysis. Moreover, the data stored in the backend database is available for physicians to conduct relevant analyses, unearth insights into medical practices, and provide precise medical care for individual patients. The training and evaluation of the predictive models for objective two, along with related comparisons, analyses, and recommendations, suggest that in situations with limited computational resources and data, an Artificial Neural Network (ANN) model with six hidden layers, SELU activation function, and a focus on artery-related features can be employed for hourly intradialytic BP/PR prediction tasks. It is believed that this contributes to the collaborating clinic and relevant research communities.