ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Metabolic reprogramming， as one of the core hallmarks of malignant tumors， plays a key role in the occurrence， development and treatment of breast cancer （BC）. Abnormal changes in glucose metabolism， amino acid metabolism， lipid metabolism， as well as the tricarboxylic acid （TCA） cycle and oxidative phosphorylation （OXPHOS） pathways significantly influence the pathogenesis and progression of BC. Studies have shown that various active components of traditional Chinese medicine （TCM） （such as berberine， matrine， quercetin， curcumin， etc.） and their compound formulations （e.g. Xihuang pill， Danzhi xiaoyao powder， Yanghe decoction， etc.） can inhibit the proliferation and migration of BC cells and induce apoptosis by regulating key metabolic pathways such as glycolysis， lipid synthesis， and amino acid metabolism. TCM demonstrates multi-target and holistic regulatory advantages in intervening in BC metabolic reprogramming， showing significant potential in modulating key molecules like hypoxia inducible factor-1α， hexokinase-2， pyruvate kinase M2， lactate dehydrogenase A， glucose transporter-1， fatty acid synthase， and signaling pathways such as AKT/mTOR. However， current researches still focus predominantly on glucose metabolism， with insufficient mechanistic studies on lipid metabolism， amino acid metabolism， the TCA cycle， and OXPHOS. The precise targets， molecular mechanisms， and clinical translation value of these interventions require further validation and clarification through more high-quality experimental studies and clinical trials.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

In modern society， the comorbidity of insomnia with amnesia has shown a significantly increasing incidence and become increasingly severe， emerging as a public health issue that endangers people's physical and mental health and quality of life. Anmei Dan （AMD）， originally recorded in the Shishi Milu by CHEN Shiduo in the Qing Dynasty， possesses profound theoretical foundations and distinct clinical advantages in ameliorating insomnia with amnesia. Basic research has unequivocally confirmed its definite therapeutic effects on insomnia with amnesia and revealed partial mechanisms. AMD is therefore a veritable classic prescription embodying the principle of treating different diseases with the same method for insomnia and amnesia. However， few researchers have reviewed the related research progress. This article systematically summarized the theoretical connotations of traditional Chinese medicine in treating insomnia with amnesia， delineated the multi-component material basis of AMD in ameliorating insomnia with amnesia （including various chemical components such as ginsenosides， jujubosides， and salvianolic acids）， and evaluate its multi-dimensional clinical efficacy （e.g.， prolonging total sleep time， improving sleep efficiency， and enhancing memory）. Moreover， it systematically summarizes the multi-pathway mechanisms of action. The results indicate that AMD has a clear material basis， definite clinical efficacy， and a favorable safety profile in ameliorating insomnia and amnesia. AMD may exert the therapeutic effect by regulating sleep-wake rhythms， enhancing synaptic plasticity， inhibiting neuroimmune inflammation， and modulating autophagy， oxidative stress， and energy metabolism. In conclusion， AMD exerts synergistic effects through multi-component， multi-dimensional， and multi-pathway approaches， serving as an important prescription for enriching and developing the theory of treating different diseases with the same method for insomnia with amnesia.

ObjectiveOxygen partial pressure (pO₂) is a critical indicator of the tumor microenvironment and plays an essential role in regulating tumor progression and therapeutic response, particularly for oxygen-dependent treatments such as photodynamic therapy (PDT). Although photoacoustic imaging (PAI) has shown great potential for functional and molecular imaging, conventional oxygenation imaging approaches based on hemoglobin absorption mainly provide relative oxygen saturation information and cannot directly quantify tissue oxygen partial pressure. Therefore, this study aimed to develop a fast laser sequence-based pump-probe photoacoustic tomography (PP-PAT) system for quantitative, non-invasive, and dynamic monitoring of oxygen partial pressure in tumor tissues. MethodsThe proposed PP-PAT system was developed based on the oxygen-sensitive triplet-state lifetime characteristics of methylene blue (MB). Upon optical excitation, MB molecules undergo transitions from the ground state to an excited state and subsequently form metastable triplet states through intersystem crossing. The lifetime of the triplet state is strongly affected by surrounding oxygen concentration due to dynamic oxygen quenching, providing a direct correlation between triplet-state kinetics and local oxygen partial pressure. A dual-wavelength pump-probe excitation scheme was implemented to selectively interrogate MB triplet-state dynamics. The pump pulse was used to initiate the triplet-state population, while the delayed probe pulse was applied to detect the transient triplet-state response. By optimizing the temporal interval between the pump and probe pulses, transient triplet-state differential (TTD) signals were extracted to enhance the specificity of oxygen-dependent molecular information and suppress background interference from conventional photoacoustic signals. The performance of the PP-PAT system was systematically evaluated through phantom and in vivo experiments. First, a single-tube phantom containing MB solution was used to investigate signal stability, reproducibility, and the influence of signal averaging on imaging quality. Subsequently, a dual-tube phantom model was established to simulate oxygen consumption during PDT, where one MB-containing tube was exposed to laser irradiation and the other served as a control. Finally, in vivo experiments were performed using a subcutaneous tumor model in nude mice. MB was locally injected into the tumor region before imaging to evaluate the feasibility of tumor oxygen partial pressure mapping using the proposed PP-PAT system. ResultsPhantom experiments demonstrated that the extracted TTD signals exhibited high stability and effectively reflected MB triplet-state dynamics while reducing non-specific background contributions. Signal averaging significantly improved the signal-to-noise ratio, and 50 repeated acquisitions provided an optimal compromise between image quality and acquisition efficiency. In the dual-tube phantom experiments, continuous PDT irradiation induced progressive oxygen depletion in the treated sample. The corresponding TTD decay rate gradually decreased, accompanied by an increase in the calculated triplet-state lifetime, indicating reduced oxygen quenching and decreased oxygen partial pressure. In contrast, the control sample showed relatively stable TTD kinetics and oxygenation levels during the same period. These results demonstrated that PP-PAT could quantitatively characterize oxygen consumption dynamics associated with photochemical reactions. In vivo experiments further demonstrated the capability of PP-PAT for spatially resolved oxygen partial pressure imaging in MB-injected tumor tissues. The reconstructed pO₂ maps revealed heterogeneous oxygen distributions within tumors, showing relatively hypoxic regions in the tumor core and higher oxygenation levels near the tumor boundary. This spatial oxygen distribution pattern was consistent with the typical physiological characteristics of solid tumors, where abnormal vascular structures and limited oxygen diffusion result in intratumoral oxygen gradients. ConclusionThis study presents a fast laser sequence-based PP-PAT system capable of quantitative and non-invasive imaging of tissue oxygen partial pressure. By utilizing the oxygen-dependent triplet-state lifetime of MB and extracting TTD signals, the proposed method provides molecularly specific information related to oxygen dynamics beyond conventional photoacoustic oxygenation imaging. The system enables dynamic monitoring of oxygen consumption during PDT and reveals spatial oxygen heterogeneity within tumors. This technique provides a promising imaging approach for tumor hypoxia characterization, evaluation of oxygen-dependent therapeutic responses, and precision-guided cancer treatment.

The telomere structure in the cell nucleus is crucial for maintaining the stability and functions of chromosomes.Telomerase is a ribonucleoprotein reverse transcriptase,which catalyzes the elongation of telomeres using its own RNA as a template,thereby counteracting the shortening of telomeres caused by chromosome replication and cell division.Due to its overexpression in over 85％of malignant tumor cells,telomerase has emerged as a highly promising biomarker and a novel target for cancer therapy.In recent years,given the importance of precise quantification of telomerase activity in guiding medical diagnosis and treatment strategies,researchers have developed various high-performance telomerase detection techniques.Among these,electrochemical biosensing technique has cause much attention due to its high sensitivity,operational convenience,rapid response,and ease of miniaturization.This paper focused on the latest advances in electrochemical sensing technique for detection of telomerase activity,aiming to provide inspiration for designing novel telomerase activity detection strategies by elucidating three unique properties of telomerase primer extension products.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To establish a highly sensitive and specific method for detecting human DNA based on real time quantitative PCR(qPCR)technique for the rapid detection of potential DNA con-tamination sources in DNA laboratories.Methods Primers and probes were designed with Primer Ex-pressTM software using the reference sequence of human 18S rRNA gene as a template,and the opti-mal prime-probe combination was screened by matrix method.The PCR products of the target se-quence of human 18S rRNA gene were used to construct the plasmid,and a plasmid standard was used to draw the standard curve of the qPCR system.According to the Minimum Information for Pub-lication of Quantitative Real-time PCR Experiments(MIQE)guidelines,the specificity,sensitivity,re-peatability and application effect of the qPCR system were evaluated.Results The sensitivity of the qPCR system established in this study was 5.3×10-5 ng/μL,which showed good specificity for human DNA samples.The correlation coefficient of the qPCR system was-0.999,and amplification efficiency was 100％.Both the intra-batch and inter-batch variation coefficients were less than 2％.Conclusion The established human DNA detection method based on qPCR technique has good specificity,high sen-sitivity,and robust stability.It can be used for rapid detection of DNA contamination and daily moni-toring of the accumulated human DNA in the laboratory environment.