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Acanthospermum hispidum DC. is a plant with extensive traditional use in folk medicine for treatment of various infections in Sudan including jaundice, stomach discomfort, constipation, and viral infections. This research was carried out to explore the biological and chemical properties of the crude extract of A. hispidum. Ethanol crude extract was prepared from the aerial parts of the plant and investigated for antibacterial action against standard monoderm and diderm bacteria using the cup plate method. Free radical scavenging was investigated out by using the DPPH method. Cytotoxicity assay was performed against human breast cancer cell line MCF7 using the MTT assay. Bioactive compounds were identified using GC‐MS. The ethanolic extract of A. hispidum revealed antibacterial activity against all the tested bacteria. Also, the extract exhibited potent antioxidant activity at 0.5 mg/ml using DPPH (83% ± 00.09). The cytotoxicity against MCF7 revealed potent growth inhibition activity (IC50 75.8 µg/ml). GC‐MS analysis revealed the presence of ethyl α‐d‐glucopyranoside, hexadecanoic acid, stigmasterol, β‐sitosterol, undecanoic acid, phytol, alloaromadendrene oxide, 3‐cyclopentylpropionic acid, 2‐dimethylaminoethyl ester, and longifolenaldehyde in aerial parts of A. hispidum, all of which support antibacterial, antioxidant, and cytotoxic properties. [ABSTRACT FROM AUTHOR]

Purpose: The natural history and clinical manifestations of dural metastases (DM) in castrate-resistant prostate cancer (CRPC) will change with advances in new hormonal therapy. Here, we characterised the incidence, clinical presentation, and outcomes of patients with DM in a contemporary patient cohort with CRPC. Methods: We retrospectively reviewed our CRPC database from 2012 to 2020. The primary outcome was the diagnosis of DM, defined as metastasis to the dura mater in the brain or spine. We describe the presenting symptoms, biochemistry, radiologic findings, and therapy sequence for all DM patients. Multivariable logistic regression was performed to identify predictors of DM. Results: Six of the 275 patients (2.2%) with CRPC developed DM. The average age of CRPC diagnosis for patients with DM was 65.6 years. Mean patient survival was 4.5 months after the diagnosis of DM. At the time of CRPC diagnosis, patients who developed DM were significantly younger, had lower baseline haemoglobin, higher lactate dehydrogenase (LDH), and elevated alkaline phosphatase (ALP) compared to those without DM. On multivariable analysis, younger age of CRPC diagnosis was found to be a predictor for DM. Conclusion: The presence of neurological symptoms in the context of younger age, anaemia, and elevated baseline LDH and ALP are associated with DM in CRPC. Level of Evidence: 4 [ABSTRACT FROM AUTHOR]

Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore, during the early stages of the pandemic tests were not available in any capacity. We utilized an automated machine learning (ML) approach to train and evaluate thousands of models on a clinical dataset consisting of commonly available clinical and laboratory data, along with cytokine profiles for patients (n = 150). These models were then further tested for generalizability on an out-of-sample secondary dataset (n = 120). We were able to develop a ML model for rapid and reliable screening of patients as COVID-19 positive or negative using three approaches: commonly available clinical and laboratory data, a cytokine profile, and a combination of the common data and cytokine profile. Of the tens of thousands of models automatically tested for the three approaches, all three approaches demonstrated > 92% sensitivity and > 88 specificity while our highest performing model achieved 95.6% sensitivity and 98.1% specificity. These models represent a potential effective deployable solution for COVID-19 status classification for symptomatic patients in resource-limited settings and provide proof-of-concept for rapid development of screening tools for novel emerging infectious diseases. [ABSTRACT FROM AUTHOR]

The old methods used to manage attendance for students, employees, or even teaching staff using a paper attendance record are considered tiring methods that take time. In addition to errors and repetitions or forgetting to register attendance, even with the presence of manual fingerprinting, due to the diseases that the world has experienced in previous years, it has become undesirable for some because it is considered a means of transmitting infection. In this research, we propose a method to record attendance relying on face recognition technology with real-time video processing by using multi-layer perceptron algorithm with two of python libraries, where the camera device is accessed, a picture of the person is taken, and the image is processed and framed, comparing captured faces with images within the stored database, performing face recognition, then dealing with file operations, and managing time-related tasks. Once the desired person is found, attendance is recorded with the actual time entered into an Excel file, and the file is saved with the date of the day on which attendance was recorded. The designed system works efficiently in the real-time implementation of counting and detection, proven to combine high face-detection accuracy and performance. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the moderating effect of turnover intention on the relationship between intrinsic motivation and the employee performance model. The moderation effect analysis was conducted using SmartPLS software version 3.0. The model was constructed within the software, and the analysis was conducted in two stages. The first stage involved a bootstrapping process to generate and determine the significance level and strength of the path. The second stage employed the PLS Algorithm process, generating a simple slope graph. Results from the bootstrapping process revealed a noticeable moderating effect attributed to turnover intention, supported by a t-statistics value of 2.514 and a statistically significant p-value of 0.006. Investigating the specifics of the path coefficient, the moderating impact on the relationship was quantified at -0.097, indicating a negative moderating influence. In practical terms, this suggests that turnover intention exerts a dampening effect on the connection between motivation and employee job performance. Regarding the simple slope analysis, it was found that the moderation effect of turnover intention on the relationship between intrinsic motivation and employee performance is particularly robust when turnover intention is lower. However, this effect diminishes to some extent when turnover intention is higher. These findings provide valuable insights into how the dynamics of these variables interact under varying levels of turnover intention. [ABSTRACT FROM AUTHOR]

The present study focuses on the adaptive development of a key peripheral component of conventional electrohydrodynamic atomisation (EHDA) systems, namely spraying needles (also referred to as nozzles or spinnerets). Needle geometry and planar alignment are often overlooked. To explore potential impact, curcumin-loaded polylactic-co-glycolic acid (PLGA) and methoxypolyethylene glycol amine (PEG)-based nanoparticles were fabricated. To elucidate these technological aspects, a horizontal electrospraying needle regime was adapted, and three formulations containing different polymeric ratios of PLGA: PEG (50:50, 75:25, and 25:75) were prepared and utilised. Furthermore, processing head tip geometries e.g. blunt (a flat needle exit) or slanted (a 45° inclination angle), were subjected to various flow rates (5 µL-100 µL). Successful engineering of curcumin-loaded polymeric nanoparticles (< 150 nm) was observed. In-silico analysis demonstrated stable properties of curcumin, PEG and PLGA (molecular docking studies) and fluid flow direction towards the Taylor-Cone (also known as the stable jet mode), was shown by the assessment of fluid dynamics simulations in various needle outlets. Curcumin-loaded nanoparticles were characterised using an array of methods including Scanning electron microscopy, Differential scanning calorimetry, Fourier transform infrared spectroscopy, X-ray diffraction, as well as their contact angles, encapsulation efficiencies and finally release patterns. The discrepancy when spraying with blunt and angled needles was evidenced by electron micrographs and deposition patterns. Spraying plumes utilising slanted needles enhanced particle collection efficiency and distribution of resultant atomised structures. In addition to needle design, fine-tuning the applied voltage and flow rate impacted the electrospraying process. The coefficient of variation was calculated as 30.5% and 25.6% for blunt and angled needle outlets, respectively, presenting improved particle uniformity with the employment of angled needle tips (8-G needle at 25 µL). The interplay of processing parameters with the utilisation of a slanted exit at a capillary optimised the spray pattern and formation of desired nanoparticulates. These demonstrate great applicability for controlled deposition and up-scaling processes in the pharmaceutical industry. These advances elaborate on EHDA processes, indicating a more cost-effective and scalable approach for industrial applications, facilitating the generation of a diverse range of particle systems in a controlled and more uniform fashion., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Introduction: In this cross-sectional study, the authors explored the knowledge, attitudes, and practices related to artificial intelligence (AI) among medical students in Sudan. With AI increasingly impacting healthcare, understanding its integration into medical education is crucial. This study aimed to assess the current state of AI awareness, perceptions, and practical experiences among medical students in Sudan. The authors aimed to evaluate the extent of AI familiarity among Sudanese medical students by examining their attitudes toward its application in medicine. Additionally, this study seeks to identify the factors influencing knowledge levels and explore the practical implementation of AI in the medical field., Method: A web-based survey was distributed to medical students in Sudan via social media platforms and e-mail during October 2023. The survey included questions on demographic information, knowledge of AI, attitudes toward its applications, and practical experiences. The descriptive statistics, χ 2 tests, logistic regression, and correlations were analyzed using SPSS version 26.0., Results: Out of the 762 participants, the majority exhibited a basic understanding of AI, but detailed knowledge of its applications was limited. Positive attitudes toward the importance of AI in diagnosis, radiology, and pathology were prevalent. However, practical application of these methods was infrequent, with only a minority of the participants having hands-on experience. Factors influencing knowledge included the lack of a formal curriculum and gender disparities., Conclusion: This study highlights the need for comprehensive AI education in medical training programs in Sudan. While participants displayed positive attitudes, there was a notable gap in practical experience. Addressing these gaps through targeted educational interventions is crucial for preparing future healthcare professionals to navigate the evolving landscape of AI in medicine., Recommendations: Policy efforts should focus on integrating AI education into the medical curriculum to ensure readiness for the technological advancements shaping the future of healthcare., Competing Interests: The author declares no conflicts of interest.Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objective: The COVID-19 pandemic has drastically altered the medical landscape. Various strategies have been employed to preserve hospital beds, personal protective equipment, and other resources to accommodate the surges of COVID-19 positive patients, hospital overcapacities, and staffing shortages. This has had a dramatic effect on vascular surgical practice. The objective of this study is to analyze the impact of the COVID-19 pandemic on surgical delays and adverse outcomes for patients with chronic venous disease scheduled to undergo elective operations., Methods: The Vascular Surgery COVID-19 Collaborative (VASCC) was founded in March 2020 to evaluate the outcomes of patients with vascular disease whose operations were delayed. Modules were developed by vascular surgeon working groups and tested before implementation. A data analysis of outcomes of patients with chronic venous disease whose surgeries were postponed during the COVID-19 pandemic from March 2020 through February 2021 was performed for this study., Results: A total of 150 patients from 12 institutions in the United States were included in the study. Indications for venous intervention were: 85.3% varicose veins, 10.7% varicose veins with venous ulceration, and 4.0% lipodermatosclerosis. One hundred two surgeries had successfully been completed at the time of data entry. The average length of the delay was 91 days, with a median of 78 days. Delays for venous ulceration procedures ranged from 38 to 208 days. No patients required an emergent intervention due to their venous disease, and no patients experienced major adverse events following their delayed surgeries., Conclusions: Interventions may be safely delayed for patients with venous disease requiring elective surgical intervention during the COVID-19 pandemic. This finding supports the American College of Surgeons' recommendations for the management of elective vascular surgical procedures. Office-based labs may be safe locations for continued treatment when resources are limited. Although the interventions can be safely postponed, the negative impact on quality of life warrants further investigation., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Competing Interests: The authors report no conflicts of interest.