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To establish a reliable method for measuring the radiochemical purity of technetium[99mTc] methylenediphosphonate injection, analysis conditions such as stationary phase and developing solvent were studied. The analytical method was methodologically verified in accordance with the Chinese Pharmacopoeia and other relevant provisions. The results showed that the analytical method of single-system thin-layer chromatography, in which polyamide-6 thin-layer plate was used as the stationary phase, V (1 mol/L sodium acetate solution): V (0.1 mol/L hydrochloric acid solution) =1∶1 mixed solution was used as the developing solvent, could improve the tailing problem of the main peak of technetium[99mTc] methylenediphosphonate injection. The resolution of radioactive main peak and potential impurities including pertechnetate[99mTc] and colloidal technetium[99mTc] was greater than 1.0. The method had a good linear relationship in the radioactivity range of 2.7×10-2 μCi to 42.4 μCi, and the correlation coefficient r was 0.997, with good specificity, good durability and intermediate precision. Compared with the analytical method of the pharmacopoeias, the relative error of radiochemical purity met the requirement of less than 2.0%. The established thin-layer chromatography is suitable for determination of the radiochemical purity of technetium[99mTc] methylenediphosphonate injection.

The issue of antimicrobial resistance (AMR) in pathogenic microorganisms has emerged as a global public health crisis, posing a significant threat to the modern healthcare system. The advent of Artificial Intelligence (AI) and Machine Learning (ML) technologies has brought about revolutionary changes in this field. These advanced computational methods are capable of processing and analyzing large-scale biomedical data, thereby uncovering complex patterns and mechanisms behind the development of resistance. AI technologies are increasingly applied to predict the resistance of pathogens to various antibiotics based on gene content and genomic composition. This article reviews the latest advancements in AI and ML for predicting antimicrobial resistance in pathogenic microorganisms. We begin with an overview of the biological foundations of microbial resistance and its epidemiological research. Subsequently, we highlight the main AI and ML models used in resistance prediction, including but not limited to Support Vector Machines, Random Forests, and Deep Learning networks. Furthermore, we explore the major challenges in the field, such as data availability, model interpretability, and cross-species resistance prediction. Finally, we discuss new perspectives and solutions for research into microbial resistance through algorithm optimization, dataset expansion, and interdisciplinary collaboration. With the continuous advancement of AI technology, we will have the most powerful weapon in the fight against pathogenic microbial resistance in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Ellagic acid, extracted from medicinal foods like raspberries and pomegranates, enhances poultry production and disease resistance by regulating redox, inflammation, and cell death. However, the research on ellagic acid in poultry is nascent, with unclear mechanisms. This mini-review summarizes the latest 10-year findings to promote the practical use of ellagic acid in maintaining poultry health and formulating strategies. It has been approximately 2000 years since the medicinal homologous theory, which primarily holds that food has the same therapeutic value as medicine in order to improve the health of both humans and animals. In recent years, this theory has also been proposed to be used in poultry breeding. Ellagic acid (EA), a natural compound primarily extracted from medicinal homologous foods such as raspberries and pomegranates, is reported to have incomparable advantages in improving the production performance and disease resistance of poultry due to its pharmacological properties, which regulate the processes of redox homeostasis, inflammatory response, and cell apoptotic death. However, the application and research of EA in poultry production are still in the initial stage, and the potential mechanisms of its biological functions affecting animal health have not been clearly identified, which requires more attention worldwide. This mini-review collects the latest 10-year achievements of research on the effects of EA on poultry health, aiming to promote the practical application of EA in maintaining animal health and formulating corresponding targeted strategies. [ABSTRACT FROM AUTHOR]

Positive‐sense RNA viruses remodel cellular cytoplasmic membranes as the membranous sources for the formation of viral replication organelles (VROs) for viral genome replication. In plants, they traffic through plasmodesmata (PD), plasma membrane‐lined pores enabling cytoplasmic connections between cells for intercellular movement and systemic infection. In this study, we employed turnip mosaic virus (TuMV), a plant RNA virus to investigate the involvement of RTNLB3 and RTNLB6, two ER (endoplasmic reticulum) membrane‐bending, PD‐located reticulon‐like (RTNL) non‐metazoan group B proteins (RTNLBs) in viral infection. We show that RTNLB3 interacts with TuMV 6K2 integral membrane protein and RTNLB6 binds to TuMV coat protein (CP). Knockdown of RTNLB3 promoted viral infection, whereas downregulation of RTNLB6 restricted viral infection, suggesting that these two RTNLs play contrasting roles in TuMV infection. We further demonstrate that RTNLB3 targets the α‐helix motif 42LRKSM46 of 6K2 to interrupt 6K2 self‐interactions and compromise 6K2‐induced VRO formation. Moreover, overexpression of AtRTNLB3 apparently promoted the selective degradation of the ER and ER‐associated protein calnexin, but not 6K2. Intriguingly, mutation of the α‐helix motif of 6K2 that is required for induction of VROs severely affected 6K2 stability and abolished TuMV infection. Thus, RTNLB3 attenuates TuMV replication, probably through the suppression of 6K2 function. We also show that RTNLB6 promotes viral intercellular movement but does not affect viral replication. Therefore, the proviral role of RTNLB6 is probably by enhancing viral cell‐to‐cell trafficking. Taken together, our data demonstrate that RTNL family proteins may play diverse complex, even opposite, roles in viral infection in plants. [ABSTRACT FROM AUTHOR]

Background: Young-onset dementia (YOD) refers to dementia occurring before the age of 65, with Alzheimer's disease being the most common form, posing distinct challenges for spousal caregivers. Objective: This study aims to investigate the unique experiences of spousal caregivers of persons with YOD in China, where dementia-specific community care services and primary healthcare professionals are relatively lacking, in order to inform the tailored support services development. Methods: This qualitative-design study utilized semi-structured interviews with 11 spousal caregivers of persons with YOD dwelling in the community. Traditional content analysis was employed to analyze the interview data. Results: Limited dementia-specific healthcare professionals and low public awareness made diagnosing and accepting YOD a prolonged and challenging journey. Spousal caregivers faced skepticism when seeking diagnosis, exacerbating their burden and emotional stress. Disparities in healthcare professionals and insufficient collaboration between institutions worsened the situation. YOD significantly impacted family dynamics and led to changes in emotional communication within the family. The stigma surrounding YOD raised concerns among spousal caregivers about their children's future in marriage and career, emphasizing genetic risks. Conclusions: In settings where dementia-specific community care services and primary healthcare professionals are limited and unevenly distributed, integrating support services at both the primary and community levels is crucial for families dealing with YOD in the community. Additionally, raising public awareness about YOD can foster a more understanding and supportive environment, addressing challenges related to stigma faced by affected families, contributing to increased investment in supporting resources, and encouraging individuals to seek help early on. [ABSTRACT FROM AUTHOR]

Introduction: Solitary fibrous tumor (SFT) is a fibroblastic tumor with malignant potential that is underpinned by a recurrent inv12(q13q13)-derived NAB2::STAT6 fusion. Breast and axilla are uncommon locations for this entity. Methods: Records of two academic institutions were electronically searched for breast and axillary SFTs. Clinical and pathologic data were reviewed. Literature review for breast or axillary SFTs was performed. Present study and previously reported tumors were stratified using five SFT risk models: original and modified Demicco metastatic risk, Salas local recurrence risk, Salas metastatic risk, and Thompson local recurrence risk. Results: Five patients with breast or axillary SFT were identified. Median age was 49 years, and median follow-up (available for four patients) was 82 months. Three patients showed no evidence of disease, and one developed recurrence. Literature review identified 58 patients with breast or axillary SFT. Median age was 54 years, and median follow-up (available for 35 patients) was 24 months. Thirty-one patients showed no evidence of disease, three developed recurrence, and one developed metastasis. Original and modified Demicco models and Thompson model showed the highest sensitivity; original and modified Demicco models and Salas metastatic risk model demonstrated the highest specificity. Kaplan–Meier models were used to assess recurrence-free probability (RFP). Original and modified Demicco models predicted RFP when stratified by "low risk" and "moderate/intermediate and high risk" tumor, though sample size was small. Conclusions: While many SFTs of breast and axilla remain indolent, a subset may develop recurrence and rarely metastasize. The modified Demicco risk model demonstrated optimal performance characteristics. [ABSTRACT FROM AUTHOR]