ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Japanese spotted fever(JSF)is an infectious disease caused by Rickettsia japonica,with nonspecific clinical symptoms and a high risk of misdiagnosis.We reported a case of JSF,in which Rickettsia japonica was detected in blood cells by metagenomic next-generation sequencing.The patient recovered after treatment with doxycycline.This report provides a reference for the clinical diagnosis and treatment of JSF.
Humans ; High-Throughput Nucleotide Sequencing ; Metagenomics ; Rickettsia/isolation & purification* ; Spotted Fever Group Rickettsiosis/microbiology*

Objective: To investigate the expression and functional role of FK506 binding protein 10 (FKBP10) in oral squamous cell carcinoma (OSCC), and to provide a research basis for the estimated prognosis and targeted therapy of OSCC. Methods: A total of 284 OSCC samples and 19 normal samples were selected from the Cancer Genome Atlas (TCGA) database, and diagnostic analysis was performed to determine mRNA expression. Survival analysis for FKBP10 and OSCC was conducted on a gene expression profile interaction analysis website. Real-time fluorescence quantitative PCR and Western Blot were used to detect the mRNA and protein expression of FKBP10 in four OSCC cell lines and SAS and SCC9 cells transfected with siRNA. The cell proliferation ability of FKBP10-silenced cells was detected using the CCK8 method, and the cell cycle distribution and apoptosis were detected by flow cytometry. Cell migration and invasion ability were detected through wound healing and invasion experiments. The expression changes of total protein and phosphatidylinositol 3-kinase (PI3K)-serine/threonine kinase (AKT) after FKBP10 silencing were analyzed by proteomics and Western Blot. Results: According to the analysis of gene expression levels, the mRNA expression level of FKBP10 in OSCC was significantly higher than that in normal tissues (P < 0.001). In terms of diagnosis, the expression level of FKBP10 has unique diagnostic value for OSCC (P < 0.05). The survival analysis of FKBP10 and OSCC showed that a high expression of FKBP10 led to a decrease in patient survival and poor prognosis (P < 0.05). The expression of FKBP10 mRNA and protein in OSCC cell lines was higher than that in normal oral keratinocytes (P < 0.001). Silencing FKBP10 can reduce the proliferation, invasion, and migration ability of SAS and SCC9 (P < 0.001), and also block their cell cycle in the G0/G1 phase (P < 0.001), with a significant increase in apoptosis (P < 0.05). Protein mass spectrometry and Western blot analysis revealed that FKBP10 silencing significantly downregulated the expression of multiple proteins in the RAP1 signaling pathway, mainly RAP guanine nucleotide exchange factor 1 (RAPGEF1) (P < 0.05) and the phosphorylation of PI3K-AKT proteins (P < 0.05). Conclusion FKBP10 is highly expressed in OSCC, leading to poor prognosis for patients. Downregulated FKBP10 expression can inhibit the proliferation, migration, and invasion ability of OSCC cells, hinder cell cycle progression, and promote apoptosis via the RAP1-PI3K-AKT axis. FKBP10 is a potential therapeutic target and prognostic biomarker for OSCC.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Objective To analyze and summarize the acupoint selection patterns for acupuncture-moxibustion treatment of chloasma using data mining techniques.Methods Computerized searches were conducted in major databases including the CNKI,Wanfang,VIP,CBM,PubMed,Embase,and the Cochrane Library.Clinical research literature on acupuncture-moxibustion treatment of chloasma published between January 1,2003 and August 31,2024 was retrieved.A database for acupuncture-moxibustion treatment of chloasma was established using Microsoft Excel 2019,and SPSS Modeler 18.0,Cytoscape 3.9.1,and SPSS 26.0 were employed to analyze the frequency of acupoint usage,meridian tropism,regional distribution,and specific acupoint categories,as well as to perform association rule analysis and cluster analysis.Results A total of 122 articles were included,involving 185 acupuncture-moxibustion prescriptions and 131 acupoints,with a total application frequency of 1 532.High-frequency acupoints included Sanyinjiao(SP6),Zusanli(ST36),Xuehai(SP10),and Hegu(LI4).Commonly used meridians were the spleen meridian of foot-taiyin,stomach meridian of foot-yangming,conception vessel(ren mai),bladder meridian of foot-taiyang,and large intestine meridian of hand-yangming.Specific acupoints were predominantly front-mu points,five-shu points,and lower he-sea points.Acupoints were mostly distributed in the chest/abdomen and lower limbs.Association rule analysis revealed that the core acupoint combination was"Sanyinjiao-Zusanli-Xuehai-Hegu".Cluster analysis classified high-frequency acupoints into five major categories.Conclusion The acupoint selection patterns for acupuncture-moxibustion treatment of chloasma reflect the principle of combining holistic concepts with syndrome differentiation.The core acupoint combination is"Sanyinjiao-Zusanli-Xuehai-Hegu".During treatment,acupoints in the chest/abdomen and lower limbs are frequently selected,often combined with acupoints on the head and face.

The morphological characteristics of hepatocellular carcinoma(HCC)tumor margins are pivotal in influencing patient's prognosis and the selection of therapeutic strategies.This paper re-viewed the classification methods of HCC tumor margins,ranging from traditional macroscopic classifi-cations to refined classification systems based on multi-omics analysis,and analyzed the role of these classification methods in guiding the formulation of personalized treatment plans.Additionally,this paper emphasized the crucial role of three-dimensional imaging techniques in assessing tumor margin morphology and outlined future research directions,including validating the effectiveness of multi-omics classification systems and developing new imaging and molecular biomarkers to achieve more precise treatment plans and prolong patient survival.

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires