暂无摘要。

Protein lysine crotonylation (Kcr) is one conserved form of posttranslational modifications of proteins, which plays an important role in a series of cellular physiological and pathological processes. Lysine ε-amino groups are the primary sites of such modification, resulting in four-carbon planar lysine crotonylation that is structurally and functionally distinct from the acetylation of these residues. High levels of Kcr modifications have been identified on both histone and non-histone proteins. The present review offers an update on the research progression regarding protein Kcr modifications in biomedical contexts and provides a discussion of the mechanisms whereby Kcr modification governs a range of biological processes. In addition, given the importance of protein Kcr modification in disease onset and progression, the potential viability of Kcr regulators as therapeutic targets is elucidated.

OBJECTIVE: Artificial intelligence (AI), be it neuronal networks, machine learning or deep learning, has numerous beneficial effects on healthcare systems; however, its potential applications and diagnostic capabilities for immunologic diseases have yet to be explored. Understanding AI systems can help healthcare workers better assimilate artificial intelligence into their practice and unravel its potential in diagnostics, clinical research, and disease management.
RESULTS: We reviewed recent advancements in AI systems and their integration in healthcare systems, along with their potential benefits in the diagnosis and management of diseases. We explored machine learning as employed in allergy diagnosis and its learning patterns from patient datasets, as well as the possible advantages of using AI in the field of research related to allergic reactions and even remote monitoring. Considering the ethical challenges and privacy concerns raised by clinicians and patients with regard to integrating AI in healthcare, we explored the new guidelines adapted by regulatory bodies. Despite these challenges, AI appears to have been successfully incorporated into various healthcare systems and is providing patient-centered solutions while simultaneously assisting healthcare workers. Artificial intelligence offers new hope in the field of immunologic disease diagnosis, monitoring, and management and thus has the potential to revolutionize healthcare systems.

Using the journal of the Dutch Diabetics Association (Nederlandse Vereniging van Suikerzieken), the article provides insight into the role of an early patient organisation in conceptualising the chronic disease diabetes and its management in the Netherlands between 1945 and 1970. The dual aims of discipline (steered by health professionals) and independence (steered by diabetics) were reconciled through the concept of balance during the 1940s and 1950s. Organised diabetics played a particularly large role, and independence got particular emphasis as a consequence. This made it possible for organised patients to reconfigure their disease and identity in terms of social health in relation to labour, family and society in the post-war reconstruction period. In the late 1960s, this social concept transformed into a personal concept of health in which the concept of balance lost its prominence, despite a short intermezzo of medicalisation in the early 1960s.

Community-based participatory research (CBPR) using barbershop interventions is an emerging approach to address health disparities and promote health equity. Barbershops serve as trusted community settings for health education, screening services, and referrals. This narrative mini-review provides an overview of the current state of knowledge regarding CBPR employing barbershop interventions and explores the potential for big data involvement to enhance the impact and reach of this approach in combating chronic disease. CBPR using barbershop interventions has shown promising results in reducing blood pressure among Black men and improving diabetes awareness and self-management. By increasing testing rates and promoting preventive behaviors, barbershop interventions have been successful in addressing infectious diseases, including HIV and COVID-19. Barbershops have also played roles in promoting cancer screening and increasing awareness of cancer risks, namely prostate cancer and colorectal cancer. Further, leveraging the trusted relationships between barbers and their clients, mental health promotion and prevention efforts have been successful in barbershops. The potential for big data involvement in barbershop interventions for chronic disease management offers new opportunities for targeted programs, real-time monitoring, and personalized approaches. However, ethical considerations regarding privacy, confidentiality, and data ownership need to be carefully addressed. To maximize the impact of barbershop interventions, challenges such as training and resource provision for barbers, cultural appropriateness of interventions, sustainability, and scalability must be addressed. Further research is needed to evaluate long-term impact, cost-effectiveness, and best practices for implementation. Overall, barbershops have the potential to serve as key partners in addressing chronic health disparities and promoting health equity.

Plant phenolics have been known for various biological activities. This study aims to extract and examine the presence of phenolics in Bao mango (Mangifera indica L. var.) peel ethanolic extract (MPE). Further, antioxidant, anti-diabetic (α-amylase, and α-glucosidase inhibitory activity), and anti- Alzheimer\'s disease (AD) (acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and β-secretase (BACE-1) inhibitory activity) efficacy of MPE were determined. The results indicated that mangiferin (8755.89 mg/ 100 g extract) was the major phenolic compound in MPE. An antioxidant mechanism revealed that MPE had a higher radical scavenging ability (4266.70 µmol TE/g extract) compared to reducing power (FRAP) or oxygen radical absorption capacity (ORAC). Further in-vitro enzyme inhibitory assay against diabetic and AD involved enzymes showed that MPE had stronger inhibitory action against an enzyme involved in diabetes compared to their standard drug (Acarbose) (P < 0.05). While a lower IC50 value was observed against AD-involved enzymes compared to their standard drug (donepezil) (P < 0.05). The results show that Thai Bao mango peel byproduct can be a potential source of nutraceuticals to lower diabetes and improve cognitive health.

With the advance of research, non-coding RNA has been found to surpass the traditional definition to directly code functional proteins by coding sequence elements and binding with ribosomes. Among the non-coding RNAs, the function of circRNA encoded proteins has been most extensively studied. This study has used \"circRNA\", \"encoded\", and \"translation\" as the key words to search the PubMed and Web of Science databases. The retrieved literature was screened and traced, with the translation mechanism, related research methods, and correlation with diseases of circRNA reviewed. CircRNA can translate proteins through a non-cap-dependent pathway. Multiple molecular techniques, in particular mass spectrometry analysis, have important value in identifying unique peptide segments of circRNA encoded proteins for confirming their existence. The proteins encoded by the circRNA are involved in the pathogenesis of diseases of the digestive, neurological, urinary systems and the breast, and have the potential to serve as novel targets for disease diagnosis and treatment. This article has provided a comprehensive review for the basic theory, experimental methods, and disease-related research in the field of circRNA translation, which may provide clues for the identification of new diagnostic and therapeutic targets.

Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.

Encounters between animals occur when animals are close in space and time. Encounters are important in many ecological processes including sociality, predation and disease transmission. Despite this, there is little theory regarding the spatial distribution of encounters and no formal framework to relate environmental characteristics to encounters. The probability of encounter could be estimated with resource selection functions (RSFs) by comparing locations where encounters occurred to available locations where they may have occurred, but this estimate is complicated by the hierarchical nature of habitat selection. We developed a method to relate resources to the relative probability of encounter based on a scale-integrated habitat selection framework. This framework integrates habitat selection at multiple scales to obtain an appropriate estimate of availability for encounters. Using this approach, we related encounter probabilities to landscape resources. The RSFs describe habitat associations at four scales, home ranges within the study area, areas of overlap within home ranges, locations within areas of overlap, and encounters compared to other locations, which can be combined into a single scale-integrated RSF. We apply this method to intraspecific encounter data from two species: white-tailed deer (Odocoileus virginianus) and elk (Cervus elaphus) and interspecific encounter data from a two-species system of caribou (Rangifer tarandus) and coyote (Canis latrans). Our method produced scale-integrated RSFs that represented the relative probability of encounter. The predicted spatial distribution of encounters obtained based on this scale-integrated approach produced distributions that more accurately predicted novel encounters than a naïve approach or any individual scale alone. Our results highlight the importance of accounting for the conditional nature of habitat selection in estimating the habitat associations of animal encounters as opposed to \'naïve\' comparisons of encounter locations with general availability. This method has direct relevance for testing hypotheses about the relationship between habitat and social or predator-prey behaviour and generating spatial predictions of encounters. Such spatial predictions may be vital for understanding the distribution of encounters driving disease transmission, predation rates and other population and community-level processes.

UNASSIGNED: Since the resurgence of mpox disease in 2017, Nigeria alone has accounted for about 60% of confirmed cases reported in the African region. This study therefore aimed to understand the knowledge and perception of the general public towards the mpox infection.
UNASSIGNED: We conducted a cross-sectional study among 958 community members across three states (Oyo, Lagos and Jigawa) in Nigeria. Knowledge of mpox infection was assessed across four domains: (1) general knowledge, (2) transmission, (3) signs and symptoms, and (4) prevention and treatment where we assigned a score of 1 for each correct response. Binary logistic regression was conducted to explore factors associated with knowledge of mpox infection at 5% level of significance. We assessed perception of mpox infection across 5 constructs (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and self-efficacy) from the health belief model, using 3-point Likert scales. We used Kruskal-Wallis and Mann-Whitney- U tests to assess factors associated with each construct.
UNASSIGNED: Overall, only about one-third (38.3%) of community members were aware of mpox infection. There were variations in perceptions and knowledge across the three states. Knowledge of mpox infection transmission, prevention, and treatment was low across the states. Only 28.9% of respondents knew that sharing utensils with an infected person is a means of contracting the disease, and just 15.9% were aware that mpox infection may resolve spontaneously. The mean of general knowledge scores was higher in Jigawa 14.8 (±3.2) compared to Lagos 12.1 (±4.1) and Oyo states 12.5 (±5.6) (p<0.001).Respondents with tertiary-level education (p=0.001) were significantly more likely to perceive themselves as susceptible to mpox while males (p<0.001) and respondents who live in Jigawa state (p=0.002) were significantly more likely to perceive mpox as severe with 90.5% believing that being infected will stop their daily activity (p<0.001). Perceived barriers to adherence to mpox preventive strategies were higher in Jigawa state (p<0.001), with 68.3% reporting that use of hand sanitizers might be expensive for them.
UNASSIGNED: The analysis of our findings revealed significant knowledge gaps and a very low level of public awareness about mpox. Key areas of limited knowledge included the disease\'s route of transmission, as well as its prevention and treatment. To control the spread of mpox infection, there is need to strengthen public health risk communication focusing on the transmission and preventive actions.