OBJECTIVE To compare the efficacy and safety of tildrakizumab versus secukinumab in the treatment of moderate-to-severe plaque psoriasis. METHODS A retrospective analysis was conducted on 141 patients with moderate-to-severe plaque psoriasis treated at the First Affiliated Hospital of Nanyang Medical College from January 2024 to April 2025. According to the treatment regimen，the patients were divided into tildrakizumab g roup （ n ＝61） and secukinumab group （ n ＝80）. The PASI 75，PASI 90，and PASI 100 response rates， the Psoriasis Area and Severity Index （PASI） and Dermatology Life Quality Index （DLQI） scores， skin barrier function （sebum content and stratum corneum water content）， inflammatory factor levels [interleukin-17 （IL-17）， tumor necrosis factor-α （TNF-α）， and IL-23 ] before and after treatment， and the incidence of adverse drug reactions during treatment were compared between the two groups. RESULTS After 12 weeks of treatment， the PASI 75， PASI 90， and PASI 100 response rates in the tildrakizumab group were significantly higher than those in the secukinumab group （ P ＜0.05）. After treatment， PASI and DLQI scores as well as serum levels of IL-17， TNF-α， and IL-23 in both groups were significantly reduced compared to before treatment in the same group； sebum content and stratum corneum water content were significantly increased compared to before treatment in the same group （ P ＜0.05）； the tildrakizumab group showed better results than the secukinumab group （ P ＜0.05）. The overall incidence of adverse drug reactions was also significantly lower in the tildrakizumab group compared with the secukinumab group （ P ＜0.05）. CONCLUSIONS Compared with secukinumab， tildrakizumab demonstrates superior efficacy in the treatment of moderate-to-severe plaque psoriasis， providing improved symptom relief， enhanced skin barrier function， reduced levels of inflammatory factors， and higher safety.

By consulting ancient and modern literature， this article systematically reviews and verifies the historical evolution of the herbal medicine known as Baijiang across various dimensions， including name， origin， scientific name verification， medicinal parts， production area， quality， harvesting and processing， as well as its nature， taste， and therapeutic effects， in order to provide a reference for the development and utilization of famous classical formulas containing Patriniae Herba. Patriniae Herba has a long history of use. It derives its name from the distinctive musty odor of its roots， which resembles spoiled soy sauce. However， due to its alias Kucai， there has been much confusion with other plants. Since the Ming dynasty， various plants have been used interchangeably as Baijiang. Herbal textual research showed that Patriniae Herba was first recorded in Shennong Bencaojing， and throughout history， Baijiang has been recognized as its standard name， though it has also been known by alternative names such as Luchang， Lujiang， and Suanyi. The main sources used throughout the ages were Patrinia scabiosaefolia or P. villosa， which is consistent with the 1977 edition of the Pharmacopoeia of the People's Republic of China. However， while the roots were traditionally used medicinally， the whole plant is now more commonly used in modern practice. In addition， the whole plants of Thlaspi arvense from the Cruciferae family and Sonchus brachyotus from the Compositae family are commonly used as regional substitutes for Baijiang. According to ancient records， Patriniae Herba was primarily found in Jiangxia（present-day eastern Hubei province） and Jiangdong（the region south of the lower reaches of the Yangtze River）， but modern literature shows that it is distributed throughout the country without a distinct geographical origin. In ancient times， the roots were harvested in August and sun-dried， today， the whole plant is typically dug up in summer or autumn and sun-dried. In recent times， the quality has been summarized as being best when the roots are long， the leaves are abundant and green， and the aroma is strong. Regarding the processing， ancient methods often involved baking（drying over fire）， while modern methods typically involve removing impurities， washing， and then cutting and drying the segments. The effects of Patriniae Herba are to clear heat and detoxify， eliminate blood stasis and drain pus. During the Han and Northern and Southern dynasties， it was used to treat skin diseases caused by heat， abscesses， postpartum diseases， and rheumatism， during the Five dynasties period， its therapeutic applications expanded to include diseases of the five senses， and by the modern era， conditions such as neurasthenia and insomnia were added. Regarding its properties and taste， it was recorded as bitter and neutral during the Han dynasty. By the Tang dynasty， it was slightly cold， with a taste of acrid and bitter. During the Yuan and Ming dynasties， it was mostly slightly cold and neutral， with a bitter and salty taste. In the Qing dynasty and modern times， it was mostly bitter and neutral， and in contemporary times， it has evolved to a taste of acrid， bitter， and cool. Based on the results of this study， it is recommended that when developing and utilizing famous classical formulas containing Patriniae Herba， one should select the entire herb of the historically mainstream sources， P. scabiosaefolia or P. villosa from the Valerianaceae family， and choose the processing method according to the prescription requirements. It is recommended to use raw products without specific requirements.

Diabetic retinopathy(DR)remains the leading cause of vision loss in patients with diabetes. Current anti-vascular endothelial growth factor(VEGF)therapies are limited by inadequate response in some patients and the necessity for repeated intravitreal injections, underscoring the urgent need for novel therapeutic targets. Angiopoietin-like protein 4(ANGPTL4), a multifunctional secreted protein, has emerged as a critical regulator in the pathogenesis and progression of DR, positioning it as a promising interventional target. This review systematically elaborates the biological characteristics of ANGPTL4, with a focus on its expression dynamics, molecular mechanisms, and regulatory networks rolesin the development of DR. Furthermore, the prospects of ANGPTL4-targeted therapeutic strategies are discussed, aiming to offer new insights and directions for understanding DR pathogenesis, advancing multi-target drug development, and improving clinical management.

By consulting ancient and modern literature， this article systematically reviews and verifies the historical evolution of the herbal medicine known as Baijiang across various dimensions， including name， origin， scientific name verification， medicinal parts， production area， quality， harvesting and processing， as well as its nature， taste， and therapeutic effects， in order to provide a reference for the development and utilization of famous classical formulas containing Patriniae Herba. Patriniae Herba has a long history of use. It derives its name from the distinctive musty odor of its roots， which resembles spoiled soy sauce. However， due to its alias Kucai， there has been much confusion with other plants. Since the Ming dynasty， various plants have been used interchangeably as Baijiang. Herbal textual research showed that Patriniae Herba was first recorded in Shennong Bencaojing， and throughout history， Baijiang has been recognized as its standard name， though it has also been known by alternative names such as Luchang， Lujiang， and Suanyi. The main sources used throughout the ages were Patrinia scabiosaefolia or P. villosa， which is consistent with the 1977 edition of the Pharmacopoeia of the People's Republic of China. However， while the roots were traditionally used medicinally， the whole plant is now more commonly used in modern practice. In addition， the whole plants of Thlaspi arvense from the Cruciferae family and Sonchus brachyotus from the Compositae family are commonly used as regional substitutes for Baijiang. According to ancient records， Patriniae Herba was primarily found in Jiangxia（present-day eastern Hubei province） and Jiangdong（the region south of the lower reaches of the Yangtze River）， but modern literature shows that it is distributed throughout the country without a distinct geographical origin. In ancient times， the roots were harvested in August and sun-dried， today， the whole plant is typically dug up in summer or autumn and sun-dried. In recent times， the quality has been summarized as being best when the roots are long， the leaves are abundant and green， and the aroma is strong. Regarding the processing， ancient methods often involved baking（drying over fire）， while modern methods typically involve removing impurities， washing， and then cutting and drying the segments. The effects of Patriniae Herba are to clear heat and detoxify， eliminate blood stasis and drain pus. During the Han and Northern and Southern dynasties， it was used to treat skin diseases caused by heat， abscesses， postpartum diseases， and rheumatism， during the Five dynasties period， its therapeutic applications expanded to include diseases of the five senses， and by the modern era， conditions such as neurasthenia and insomnia were added. Regarding its properties and taste， it was recorded as bitter and neutral during the Han dynasty. By the Tang dynasty， it was slightly cold， with a taste of acrid and bitter. During the Yuan and Ming dynasties， it was mostly slightly cold and neutral， with a bitter and salty taste. In the Qing dynasty and modern times， it was mostly bitter and neutral， and in contemporary times， it has evolved to a taste of acrid， bitter， and cool. Based on the results of this study， it is recommended that when developing and utilizing famous classical formulas containing Patriniae Herba， one should select the entire herb of the historically mainstream sources， P. scabiosaefolia or P. villosa from the Valerianaceae family， and choose the processing method according to the prescription requirements. It is recommended to use raw products without specific requirements.

Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

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.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.