The environmental and health impacts of chemical processes have been a growing concern, leading to the establishment of Green Chemistry principles. Introducing new metrics for the assessment of methods' greenness is crucial to evaluate the exerted efforts to conserve the environment. In this work, we introduce a Modified Green Star Area (MoGSA) and software to assess the greenness of chemical reactions in laboratory settings. MoGSA refines the traditional Green Star Area Index (GSAI) by allowing users to selectively apply specific principles of Green Chemistry based on their relevance to the chemical process being evaluated. This approach addresses the limitations of GSAI, which often lacks clear boundaries between green and non-green practices and does not account for the varying applicability of the 12 Green Chemistry principles across different contexts. Through comparative case studies on catalytic stereoselective reduction of acetophenone, MoGSA demonstrates its utility in providing a more refined and flexible assessment, enhancing both educational and industrial applications of sustainable chemical practices. The software is available as an open source at https://bit.ly/MOGSA.

The COVID-19 pandemic impacted the world in every aspect. Higher institutions were greatly affected because the outbreak disrupted the teaching and learning structure. Vaccines decrease the rate of infection and transmission of the virus, but the presence of some myths has led to hesitancy towards the vaccine. The purpose of the survey was to assess the knowledge, perception, and acceptance of the COVID-19 vaccine among undergraduate students in Enugu State, Nigeria. This was a cross-sectional study carried out among undergraduate students at the University of Nigeria Nsukka (UNN), the Institute of Management and Technology (IMT), and Enugu State University of Technology Enugu state (ESUT), Nigeria between March and November 2023. These institutions were chosen based on their large student populations, diverse academic offerings, and significant geographical coverage within the state. Data collection was done using a 26-item validated self-administered questionnaire. Statistical Product and Service Solutions (SPSS) version 25 with appropriate descriptive (frequency and percentage) and inferential statistics (Chi-square) were used to analyze the data. 1,143 completed questionnaires were obtained. The modal age range was 18-24 years accounting for 814 (71.2%) of the participants. A total of 577 (50.5%) participants demonstrated a good level of knowledge while 685 (59.9%) showed a positive perception of the COVID-19 vaccine. Gender (p = 0.010) and institution (p < 0.001) were associated with their perception of the COVID-19 vaccine. In addition, knowledge and perception of the COVID-19 vaccine were significantly associated with its acceptance at p = 0.038 and < 0.001, respectively. This study reveals that COVID-19 vaccine acceptance among university students in Enugu State, Nigeria, remains low despite moderate knowledge and generally positive attitudes, with perceptions playing a more significant role than knowledge. The findings highlight the need for educational interventions that not only provide accurate information but also actively address misconceptions. To improve vaccine uptake, public health campaigns should focus on shifting perceptions through culturally sensitive, institution-specific strategies.

The early detection of Alzheimer's Disease (AD) is thought to be important for effective intervention and management. Here, we explore deep learning methods for the early detection of AD. We consider both genetic risk factors and functional magnetic resonance imaging (fMRI) data. However, we found that the genetic factors do not notably enhance the AD prediction by imaging. Thus, we focus on building an effective imaging-only model. In particular, we utilize data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), employing a 3D Convolutional Neural Network (CNN) to analyze fMRI scans. Despite the limitations posed by our dataset (small size and imbalanced nature), our CNN model demonstrates accuracy levels reaching 92.8% and an ROC of 0.95. Our research highlights the complexities inherent in integrating multimodal medical datasets. It also demonstrates the potential of deep learning in medical imaging for AD prediction.

To develop and validate a predictive model for identifying vascular crises following free tissue flap transplantation in patients undergoing surgery for oral and maxillofacial tumors. This retrospective cohort study utilized medical records from the Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, covering the period from January 2014 to December 2021. The analysis included 1,786 cases, divided into a training group (n = 1,251) and a validation group (n = 535). Variables included demographic factors, clinical characteristics, and surgical details. Univariate and multivariate logistic regression analyses were performed to identify significant predictors, which were then incorporated into a nomogram. The model's performance was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The incidence of vascular crisis was 5.8% in the training group and 4.9% in the validation group. Significant predictors included tissue flap width, D-dimer levels, preoperative hemoglobin, hemoglobin difference before and after surgery, and type of venous anastomosis. The nomogram showed strong predictive performance with an AUC of 0.780 in the training group and 0.701 in the validation group. Calibration curves indicated excellent fit, and DCA demonstrated clinical applicability. A user-friendly model was developed for detecting vascular crises in oral and maxillofacial tumor patients. This model exhibits robust discriminative ability, precise calibration, high specificity, and significant clinical applicability, effectively identifying high-risk patients prone to vascular crises.

This paper analyses the degree of persistence in the level of consumption of alcohol in the Group of Seven (G7) countries by using fractional integration. The series under examination are annual sales of pure alcohol in litres per person aged 15 years and older, annually from 1960 to 2021, and we look at the influence that external shocks might have had on the series in these countries. The results indicate that only France displays a significant negative trend and thus a continuous decrease in the level of alcohol consumption. For the rest of the countries, the time trend is insignificant. Dealing with persistence, Japan is the only country that shows clear evidence of reversion to the mean. Policy recommendations are reported at the end of the manuscript.

The most prevalent head and neck cancer type is laryngeal cancer. Laryngeal cancer susceptibility is increased by a combination of genetic variables and environmental factors. Genetic predispositions that influence the functioning of the immune system can affect tumor development. Our study investigates the impact of alterations in CD40 (rs1883832) and CD40L (rs1126535) genes and the levels of their proteins on the development of laryngeal cancer. The PCR-RFLP method was used for genotyping SNPs in 96 patients with laryngeal cancer and 127 healthy individuals. Additionally, ELISA was utilized to measure circulating levels of sCD40 and sCD40L. We identified a significant difference in the genotype distribution of CD40 (rs1883832) between laryngeal cancer patients and healthy individuals (p = 0.05). The C allele was dominant, and the CC genotype was more frequently observed in patients with laryngeal cancer (OR: 2.34, 95% CI: 0.98-5.54). In contrast, no statistically significant difference in the genotypes of CD40L (rs1126535) was detected between laryngeal cancer patients and the control group (p = 0.12). Additionally, no significant differences in serum sCD40 or sCD40L levels were observed between the groups (p = 0.48 and p = 0.15, respectively). However, a moderate positive correlation was found between sCD40 and sCD40L levels in the laryngeal cancer group (r = 0.52, p<0.01), a relationship that was not observed in the control group. According to the current findings, it is suggested that the CD40 (rs1883832) gene variation found in patients may indicate an individual's susceptibility to developing laryngeal cancer. On the other hand, CD40L (rs1126535) seems to not play a significant role. While serum sCD40 and sCD40L levels did not show significant differences between patients and controls, the correlation in cancer patients suggests that these markers may be relevant in tumor progression. Further research is required to clarify the functional implications of these genetic variants and their potential use as biomarkers for laryngeal cancer.

The common house mosquito Culex pipiens s.l., widely distributed in Europe, Africa, and North America has two recognized biotypes, Cx. pipiens biotype pipiens and Cx. pipiens biotype molestus, which hybridize. Despite their morphological similarities, these biotypes may exhibit ecological differences. This complex ecological mosaic may affect the interaction of Cx. pipiens with pathogens like avian Plasmodium, which is transmitted to wildlife. Although the vector competence for Cx. pipiens biotype molestus has been well studied, there is a lack of studies comparing the vector competence of Cx. pipiens biotype pipiens and their hybrids for the transmission of avian Plasmodium. Here, we evaluated the vector competence of the Cx. pipiens biotypes pipiens, molestus and their hybrids for the transmission of two avian Plasmodium species. Mosquitoes were allowed to feed on blood of wild infected birds and the presence of DNA of Plasmodium in head-thorax and saliva of mosquitoes was molecularly evaluated at 13 day-post exposure. The transmission rates (i.e., the detection of parasite DNA in mosquito saliva) for Plasmodium cathemerium were similar for the two biotypes of Cx. pipiens and their hybrids while Plasmodium relictum DNA was only found in the saliva of Cx. pipiens biotype pipiens. In addition, P. cathemerium was significantly more prevalent than P. relictum in the saliva of Cx. pipiens biotype pipiens. Our results suggest that avian Plasmodium is transmitted by both Cx. pipiens biotypes and their hybrids although differences could be found depending of the parasite species studied. Differences in the abundance of each biotype and their hybrids within areas characterized by distinct environmental conditions, along with variations in their blood-feeding patterns and the parasites infecting birds, could ultimately determine differences in the relevance of each Cx. pipiens biotype in the transmission of avian Plasmodium.

Malaria continues to be the most prevalent life-threatening parasitic illness in Ethiopia. Its clinical spectrum ranges from mild to severe, with a propensity for death. In Ethiopia, it accounts for 10% of hospital admission. Identifying predictors of malaria-related mortality is crucial for aiding high-risk patient identification and enabling timely intervention. Our study aimed to assess treatment outcomes and factors associated with mortality among severe malaria patients at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia. A retrospective cross-sectional study examined 383 randomly chosen patients with severe malaria, spanning a four-year period leading up to the data collection date, encompassing July 2023 back to June 2020. Data were collected from the hospital records. A structured questionnaire was used to collect the data. EpiData version 3.1 and SPSS version 20 were used to clean and analyze the data, respectively. Logistic regression analysis was conducted to determine associations and reported by the odds ratio at p < 0.05 with 95% confidence intervals. Among the 383 eligible patients, the majorities were males (56.66%) and resided in rural areas (66.32%). Over 84% of them were referred from health facilities. Plasmodium falciparum was the major parasite identified in 78% of cases. The magnitude of death among severe malaria patients was 10.97%. Impaired consciousness, convulsions, jaundice, parasitemia level >2, and creatinine level ≥3 were significantly associated with death, with adjusted odds ratios (AOR) of 3.4 (95% CI: 1.3-8.3), 2.7 (95% CI: 1.004-7.492), 3.2 (95% CI: 1.173-9.182), 3.7 (95% CI: 1.516-9.113), and 11.7 (95% CI: 4.756-29.239), respectively. Our study revealed a significant number of malaria-related deaths, with predictors such as age, impaired consciousness, convulsions, jaundice, parasitemia level, and creatinine level identified. Hence, it is imperative to implement intense and timely interventions for patients exhibiting these clinical manifestations to prevent malaria-related fatalities.

Fetal alcohol spectrum disorder (FASD) is a complex neurodevelopmental disability characterized by a range of brain- and body-based difficulties which, when left unsupported, can lead to experiences of significant adversity across the lifespan. Caregivers of individuals with FASD play a critical role in advocating and supporting healthy outcomes for individuals with FASD, and most caregiver research to date has been focused on stressors and challenges. Very few studies have been conducted to systematically capture the full experience of caring for someone with FASD across the lifespan, including perspectives, concerns, as well as strengths and successes of caregivers and their families. Collaborative research with individuals with living experience is essential for understanding needs and supporting healthy outcomes for individuals with FASD and their families, and caregivers are in a unique and important position to provide perspectives and share living expertise. Therefore, the current study was developed collaboratively with caregivers and researchers to capture the many aspects of caregivers' contexts, concerns, needs, and successes in raising individuals with FASD. In this study protocol paper, we describe the rationale, development, design, and anticipated impacts of this research. The goal of this paper is to share information about why and how this study is being done, and potentially guide other teams in developing similar projects to better understand caregivers' experiences, needs, and successes. Documenting and giving voice to the breadth and depth of caregiver experiences will help us to tailor services and supports, develop resources, stimulate knowledge translation based in resilience and protective factors, guide future studies, and inform evidence-based policy initiatives.

Climate warming can precipitate mismatches in plant-pollinator interactions by altering their phenologies of both parties, impacting ecosystem services. While most studies have focused on long-term, seasonal phenological shifts, the effect of warming on short-term phenological match-mismatch in these interactions remains unclear. Here, we investigate how experimental warming affects within-day foraging behavior of the honey bee (Apis mellifera) and plant anthesis, and whether the resulting changes in bee pollen composition, in terms of the relative abundance of pollen from different plant species, influences larval development. Experimental warming advanced both the within-day foraging by bees and anthesis of Bidens pilosa-the predominant pollen source among all plant species represented in the collected pollen. Through experimental manipulation of pollen composition, we demonstrated that an increased proportion of B. pilosa pollen in the diet enhanced bee larval growth efficiency. Overall, our study demonstrates that warming may influence pollinator interactions with the many plant species by affecting pollinator behaviors and plant anthesis on short-term temporal scales, with potential implications for pollinator larval development.