Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: To analyze the distribution characteristics of fluoride and trichloromethane in drinking water in rural schools in Guizhou Province and assess their health risks, so as to provide a scientific basis for ensuring the safety of drinking water in rural schools. Methods: During the dry season (March to May) and wet season (July to September) of 2020 to 2022, 788 rural primary and secondary schools in agricultural counties (districts) in Guizhou Province were selected for investigation by using a direct sampling method. A total of 1 566 drinking water samples were collected from these schools, and the mass concentrations of fluoride and trichloromethane in the water samples were detected. The Mann-Whitney U test was used for intergroup comparison, and a health risk assessment model was employed to evaluate the health risks of students oral intake of fluoride and trichloromethane. Results: From 2020 to 2022, the mass concentrations of fluoride and trichloromethane in the drinking water of rural schools in Guizhou Province all met the standards, and the ranges were no detection to 0.99 mg/L and (no detection to 0.06)×10 -3 mg/L, respectively. The mass concentrations of fluoride in dry and wet seasons were 0.05(0.05,0.10), 0.05(0.05,0.10) mg/L, the mass concentrations of trichloromethane were [0.02(0.02,1.00)]×10 -3 , [0.02(0.02,1.00)]×10 -3 mg/L, the mass concentrations of fluoride in factory water and terminal water were 0.05(0.05,0.05), 0.05(0.05,0.10) mg/L, and the differences were not statistically significant ( Z=-0.04, -0.88, - 0.98 , P >0.05). There was a statistically significant difference in the mass concentration of trichloromethane between factory water and peripheral water [0.02(0.02,0.02)×10 -3 , 0.02(0.02,1.05)×10 -3 mg/L]( Z=-2.16, P < 0.05 ). The non-carcinogenic risk assessment values for students oral exposure to fluoride and trichloromethane were in the range of 0.01(0.01,0.03)-0.03(0.03,0.06) and [0.26( 0.26 ,14.54)]×10 -4 -[0.52(0.52,48.62)]×10 -4 , respectively, all of which were at acceptable levels; the carcinogenic risk assessment values for oral exposure to trichloromethane were in the range of [0.08(0.08, 4.51 )]×10 -7 -[0.16(0.16,15.07)]×10 -7 , indicating a low risk. Conclusions The health risks of students expore to fluoride and trichloromethane in drinking water in rural schools of Guizhou Province are low. It is necessary to strengthen the standardized management of disinfection in some rural drinking water projects and the monitoring of fluoride in water sources to reduce the exposure risk to children.

This paper summarizes Professor HAN Mingxiang's clinical experience in treating chronic obstructive pulmonary disease （COPD）. He believes that the key pathomechanism of COPD in the acute exacerbation stage is the invasion of external pathogens triggering latent illness， while lung qi deficiency is the primary mechanism in the stable stage. The core pathological factors throughout disease progression are deficiency， phlegm， and blood stasis. Treatment emphasizes a staged and syndrome-based approach. During the acute exacerbation stage， for wind-cold invading the lung syndrome， the self-formulated Sanzi Wenfei Decoction （三子温肺汤） is used to relieve the exterior， dispel cold， warm the lung， and resolve phlegm. For phlegm-dampness obstructing the lung syndrome， Huatan Jiangqi Fomulation （化痰降气方） is prescribed to warm the lung， transform phlegm， descend qi， and calm wheezing. For phlegm-heat obstructing the lung syndrome， Qingfei Huatan Fomulation （清肺化痰方） is applied to clear heat， resolve phlegm， moisten the lung， and stop coughing. For phlegm and blood stasis interlocking syndrome， Qibai Pingfei Fomulation （芪白平肺方） is used to tonify qi， resolve phlegm， and activate blood circulation to remove stasis. During the stable stage， for lung qi deficiency syndrome， Shenqi Wenfei Decoction （参芪温肺汤） is employed to warm the lung， tonify qi， resolve phlegm， and eliminate turbidity. For lung-spleen qi deficiency syndrome， Shenqi Buzhong Decoction （参芪补中汤） is utilized to strengthen the spleen， tonify qi， and reinforce metal （lung） from earth （spleen）. For lung-kidney deficiency syndrome， Shenqi Tiaoshen Fomulation （参芪调肾方） is prescribed to tonify the lung， warm yang， and regulate kidney function to calm wheezing. These strategies provide insights into the traditional Chinese medicine treatment of COPD.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Mitochondria, functioning not only as the central hub of cellular energy metabolism but also as semi-autonomous organelles, orchestrate cellular fate decisions through their endogenous mitochondrial DNA (mtDNA), which encodes core components of the electron transport chain. Emerging research has identified microRNAs localized within mitochondria, termed mitochondria-located microRNAs (mitomiRs). Recent studies have revealed that mitomiRs are transcribed from nuclear DNA (nDNA), processed and matured in the cytoplasm, and subsequently transported into mitochondria. mitomiRs regulate mtDNA through diverse mechanisms, including modulation of mtDNA expression at the translational level and direct binding to mtDNA to influence transcription. Aberrant expression of mitomiRs leads to mitochondrial dysfunction and contributes to the pathogenesis of metabolic diseases. Restoring mitomiR expression to physiological levels using mitomiRs mimics or inhibitors has been shown to improve mitochondrial function and alleviate related diseases. Consequently, the regulatory mechanisms of mitomiRs have become a major focus in mitochondrial research. Given that mitomiRs are located in mitochondria, targeted delivery strategies designed for mtDNA can be adapted for the delivery of mitomiRs mimics or inhibitors. However, numerous intracellular and extracellular barriers remain, highlighting the need for more precise and efficient delivery systems in the future. The regulation of mtDNA expression mediated by mitomiRs not only expands our understanding of miRNA functions in post-transcriptional gene regulation but also provides promising molecular targets for the treatment of mitochondrial-related diseases. This review systematically summarizes recent research progress on mitomiRs in regulating mtDNA expression and discusses the underlying mechanisms of mitomiRs-mtDNA interactions. Additionally, it provides new perspectives on precision therapeutic strategies, with a particular emphasis on mitomiRs-based regulation of mitochondrial function in mitochondrial-related diseases.

Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/10⁵ [95% UI: (6.27/10⁵, 9.51/10⁵)], 0.02/10⁵ [95% UI: (0.01/10⁵, 0.02/10⁵)], and 1.32/10⁵ [95% UI: (0.99/10⁵, 1.69/10⁵)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.