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.

BACKGROUND:Eucommia ulmoides has a certain osteogenic effect,which can promote the proliferation and differentiation of osteoblasts.However,it is unclear whether Eucommia ulmoides has effects on alveolar bone formation and Wnt/β-Catenin signaling pathway. OBJECTIVE:To investigate the mechanism by which Eucommia ulmoides promotes alveolar bone formation in ovariectomized rats based on the Wnt/β-Catenin signaling pathway. METHODS:Sixty female Sprague-Dawley rats were selected and randomly divided into five groups:blank control group,sham-operation group,model group,low-dose group Eucommia ulmoides group,and high-dose Eucommia ulmoides group,with twelve rats in each group.Osteoporosis animal models were constructed by bilateral oophorectomy in the model group and the low-dose and high-dose Eucommia ulmoides groups.The sham-operation group underwent the same method to remove adipose tissue of equal mass around the bilateral ovaries.Three months after surgery,the low-and high-dose Eucommia ulmoides groups were given 2.1 g/kg/d and 4.2 g/kg/d Eucommia ulmoides by gavage,respectively.The sham-operation group and model group were given the same amount of physiological saline by gavage.After 12 weeks of drug intervention,the changes in alveolar bone mass of rats in each group were observed through Micro-CT;hematoxylin-eosin staining was used to observe the pathological structural changes of alveolar bone in rats;enzyme linked immunosorbent assay was used to detect the expression levels of alkaline phosphatase and osteocalcin in the serum of rats;western blot was used to detect the expression levels of β-Catenin and Frizzled9 receptor proteins in the alveolar bone of rats;and real-time fluorescence quantitative PCR was used to detect the expression of osteocalcin,Runt-related transcription factor 2(Runx2),alkaline phosphatase,β-catenin,and frizzled9 mRNAs in alveolar bone tissues of rats. RESULTS AND CONCLUSION:Compared with the blank control group,bone volume fraction,trabecular number,trabecular thickness,and bone mineral density were reduced in the model group(P＜0.05),and trabecular separation was elevated(P＜0.05).Pathological observation showed that the arrangement of trabeculae was disordered and irregular,the trabeculae were thinned or broken,and the marrow cavity was enlarged in the model group,with a significant reduction in bone volume;the level of alkaline phosphatase in the serum was increased(P＜0.05),and the level of osteocalcin was decreased(P＜0.05);mRNA expression of alkaline phosphatase,osteocalcin,Runx2,β-catenin,and frizzled9 were decreased(P＜0.05);protein expression of β-Catenin and Frizzled9 was decreased(P＜0.05).Compared with the model group,the low-and high-dose Eucommia ulmoides groups showed an increase in bone volume fraction,trabecular number,trabecular thickness,and bone mineral density(P＜0.05)and a decrease in trabecular separation(P＜0.05).In the low-and high-dose Eucommia ulmoides groups,bone trabeculae were slightly aligned and thickened,with a significant increase in bone mass.Compared with the model group,the serum level of alkaline phosphatase was reduced(P＜0.05)and the serum level of osteocalcin was elevated(P＜0.05)in the low-and high-dose Eucommia ulmoides groups.Compared with the model group,the mRNA expression of alkaline phosphatase,osteocalcin,Runx2,β-catenin,and frizzled9 were increased in the low-and high-dose Eucommia ulmoides groups(P＜0.05).Compared with the model group,the protein expression of Frizzled9 was increased in the low-dose Eucommia ulmoides group(P＜0.05),while the protein expression of β-Catenin and Frizzled9 was increased in the high-dose Eucommia ulmoides group(P＜0.05).Compared with the low-dose Eucommia ulmoides group,the high-dose Eucommia ulmoides group had a more significant improvement in the above indexes.To conclude,Eucommia ulmoides can effectively promote the alveolar bone formation,and its mechanism of action might be related to the activation of the Wnt/β-catenin signaling pathway.

Targeted covalent inhibitors, primarily targeting cysteine residues, have attracted great attention as potential drug candidates due to good potency and prolonged duration of action. However, their discovery is challenging. In this research, a database-assisted liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy was developed to quickly discover potential cysteine-targeting compounds. First, compounds with potential reactive groups were selected and incubated with N-acetyl-cysteine in microsomes. And the precursor ions of possible cysteine-adducts were predicted based on covalent binding mechanisms to establish in-house database. Second, substrate-independent product ions produced from N-acetyl-cysteine moiety were selected. Third, multiple reaction monitoring scan was conducted to achieve sensitive screening for cysteine-targeting compounds. This strategy showed broad applicability, and covalent compounds with diverse structures were screened out, offering structural resources for covalent inhibitors development. Moreover, the screened compounds, norketamine and hydroxynorketamine, could modify synaptic transmission-related proteins in vivo, indicating their potential as covalent inhibitors. This experimental-based screening strategy provides a quick and reliable guidance for the design and discovery of covalent inhibitors.

OBJECTIVE: To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis (TB) in the Guangdong Province between 2010 and 2019. METHOD: Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering. Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive (ST-CAR) model. RESULTS: Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000 in 2019. Spatial hotspots were found in northeastern Guangdong, particularly in Heyuan, Shanwei, and Shantou, while Shenzhen, Dongguan, and Foshan had the lowest rates in the Pearl River Delta. The ST-CAR model showed that the TB risk was lower with higher per capita Gross Domestic Product (GDP) [Relative Risk ( RR), 0.91; 95% Confidence Interval ( CI): 0.86-0.98], more the ratio of licensed physicians and physician ( RR, 0.94; 95% CI: 0.90-0.98), and higher per capita public expenditure ( RR, 0.94; 95% CI: 0.90-0.97), with a marginal effect of population density ( RR, 0.86; 95% CI: 0.86-1.00). CONCLUSION The incidence of TB in Guangdong varies spatially and temporally. Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection. Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
Humans ; China/epidemiology* ; Incidence ; Bayes Theorem ; Spatio-Temporal Analysis ; Tuberculosis/epidemiology* ; Socioeconomic Factors

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

ObjectiveTo analyze the evolutionary characteristics and genetic variations of the HA (hemagglutinin) and NA (neuraminidase) genes of influenza A(H1N1) viruses in Shanghai during 2024, to investigate their transmission patterns, and to evaluate their potential impact on vaccine effectiveness. MethodsFrom January to October 2024, throat swab specimens were collected from influenza like illness (ILI) patients at 4 hospitals in Shanghai. Real-time fluorescence ploymerase chain reaction (RT-PCR) was used for virus detection and isolation of H1N1 influenza viruses. Forty influenza A(H1N1) virus strains were sequenced using Illumina NovaSeq 6000 platform, followed by phylogenetic analyses, genetic distance analysis, and amino acid variation analyses of HA and NA genes. ResultsPhylogenetic tree of the HA and NA genes revealed that the 40 influenza A(H1N1) virus strains circulating in Shanghai in 2024 exhibited no significant geographic clustering, with a broad origin of strains and complex transmission chains. Genetic distance analyses demonstrated that the average intra-group genetic distances of HA and NA genes among the Shanghai strains were 0.005 1±0.000 6 and 0.004 6±0.000 6, respectively, which were comparable to or higher than those observed in global surveillance strains. Both HA and NA genes displayed frequent mutations. Compared to the 2023‒2024 and 2024‒2025 Northern Hemisphere A(H1N1) vaccine strains (WHO-recommended), the HA proteins of 40 Shanghai strains exhibited amino acid substitutions at positions 120, 137, 142, 169, 216, 223, 260, 277, 356 and 451, with critical mutations at positions 137 and 142 located within the Ca2 antigenic determinant. Furthermore, mutations in the NA protein were observed at positions 13, 50, 200, 257, 264, 339 and 382. ConclusionThe genetic background of the 2024 Shanghai influenza A(H1N1) virus strains is complex and diverse, and antigenic variation may affect vaccine effectiveness. Therefore, it is recommended to enhance genomic surveillance of influenza viruses, evaluate vaccine suitability, and implement more targeted prevention and control strategies against imported influenza viruses.