Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Objective To analyze the application of dual-energy CT virtual monoenergetic imaging(Mono+)technology com-bined with personalized contrast agent injection protocols in the diagnosis of lower extremity artery atherosclerosis in diabetes patients.Methods A total of 102 diabetes patients with suspected lower extremity artery atherosclerosis were selected.All patients received dual-energy CT Mono+technology combined with personalized contrast agent injection protocols.Based on personalized contrast agent injection protocols,the patients were divided into group A(34 cases,1.5 m L/kg),group B(34 cases,1.2 m L/kg),and group C(34 cases,1.0 m L/kg).All patients underwent dual-source CT scanning,and the results of ultrasound Doppler vascular imaging within one week were used as the gold standard to evaluate the consistency between dual-energy CT Mono+technology and ultra-sound Doppler vascular imaging under personalized contrast agent injection protocols.Results The CT values,signal-to-noise ratio and contrast-to-noise ratio of the abdominal iliac segment,femoral popliteal segment and lower knee segment in group B were higher than those in group A and group C(P<0.05).The CT values of the femoral popliteal and lower knee segments in group C were higher than those in group A(P<0.05).Among the 102 diabetes patients,84 were diagnosed with lower extremity artery athero-sclerosis confirmed by ultrasound Doppler vascular imaging.The positive predictive values for diagnosing lower extremity artery ath-erosclerosis in groups A,B,and C were 93.90%,97.65%,and 93.98%,respectively.The negative predictive values were 65.00%,94.14%,and 68.42%,respectively.The consistency with ultrasound Doppler vascular imaging was 0.690,0.897,and 0.715,respec-tively.Group B exhibited a higher diagnostic accuracy than groups A and C(P<0.05).Conclusion The dual-energy CT Mono+technology combined with personalized contrast agent injection protocols demonstrate good efficacy in diagnosing lower extremity artery atherosclerosis in diabetes patients,with the best imaging quality observed with the contrast agent injection protocol of 1.2 m L/kg.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

Objective To explore the expression characteristics of BAIAP2L1 in cervical cancer (CC) and its regulatory role in tumor cell metastasis. Methods The correlation between BAIAP2L1 expression and clinical prognosis was analyzed by using a public database. GO pathway enrichment and clinicopathological correlation analyses were conducted by employing R language. The effect of BAIAP2L1 knockdown on CC cell proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) were further investigated through gene silencing approaches. Results BAIAP2L1 expression was significantly upregulated in CC tissues (P_adj <0.001) and it was identified as an independent risk factor for patient mortality (HR=2.808, P=0.03). Elevated BAIAP2L1 levels showed significant correlations with poor overall survival, advanced T/N stage, recurrence, and metastasis (all P<0.05). Functional enrichment analysis revealed its involvement in tumor metastasis-related pathways. The knockdown of BAIAP2L1 significantly attenuated CC cell proliferation, invasion, and migration and suppressed key EMT processes (all P<0.05). Conclusion BAIAP2L1 is overexpressed in CC tissues and associated with patient prognosis and metastasis. The targeted inhibition of BAIAP2L1 can effectively curb tumor progression.

Objective: To analyze the characteristics of first-visit cases of herpes zoster in Zhoushan City, Zhejiang Province from 2021 to 2023, so as to provide the reference for improving herpes zoster prevention and control measures. Methods: Data on the incidence and vaccination of first-visit herpes zoster cases at all levels of public medical institutions in Zhoushan City from 2021 to 2023 were collected through the Zhoushan Comprehensive Health Information Platform and Zhoushan Immunization Program Information Management System. The incidence and outpatient proportion were calculated. The population distribution, seasonal distribution, and clinical consultation status of first-visit herpes zoster cases were described. Results: From 2021 to 2023, a total of 15 156 first-visit herpes zoster cases were reported in Zhoushan City, with an average annual incidence of 5.36‰. The incidences for each year were 5.78‰, 5.29‰ and 5.02‰, respectively, and the outpatient proportions were 0.15%, 0.14% and 0.11%, respectively, showed decreasing trends (both P<0.05). The number of doses of recombinant herpes zoster vaccine or live attenuated herpes zoster vaccine administered were 130, 312, and 633, respectively. The main consultation department was dermatology, with 11 004 cases (72.60%). The primary clinical diagnosis was visceral herpes zoster, with 5 901 cases (38.94%). A total of 1 936 cases (12.77%) had at least one underlying medical condition. The mean age of onset was (56.08±16.23) years, and the incidence showed an upward trend with increasing age (P<0.05). There were 7 386 male cases and 7 770 female cases, with a male-to-female ratio of 0.95∶1. The incidence among males aged ≥50 years was lower than that among females (6.53‰ vs. 8.69‰, P<0.05). The onset of the disease exhibited a significant seasonal pattern, with a peak period from June 21st to August 21st, covering 75% of the cases Conclusions From 2021 to 2023, the incidence and outpatient proportion of herpes zoster in Zhoushan City decreased. Summer was the peak season for onset, and women and the elderly were the key populations. It is necessary to strengthen the collaborative diagnostic and treatment capabilities of key departments such as dermatology and enhance the enthusiasm for vaccination among key populations.

Objective:To explore the longitudinal relationship between adolescents' future self-continuity and depression, providing insights into their future development.Methods:A total of 419 adolescents from a school in Shandong Province were selected, and two followed-up surveys were conducted at 6-month intervals in April (T1) and October (T2) of 2023 using the future self-continuity questionnaire and Beck depression inventory-Ⅱ. Cross-lagged analysis was performed using Mplus 8.0.Results:The scores of future self-continuity were 36.01±8.69 at baseline (T1) and 35.89±9.92 after six months (T2), while the scores of depression were 2.00(0, 14.00) and 1.00(0, 9.00), respectively. There was a negative correlation between future self-continuity and depression at both time points (T1: r=-0.195, T2: r=-0.239, both P<0.01). Adolescents' future self-continuity could predict depression six months later ( β=-0.098, P<0.01), and depression also could predict the level of future self-continuity six months later ( β=-0.114, P<0.01). Conclusion:There is an interactively influence effect between adolescents' future self-continuity and depression.While enhancing adolescents' future self-continuity level to alleviate depression, attention should also be paid attention to the impact of depression on their future self-continuity, which can help adolescents overcome the interference of depressive emotions and grow into a better future self.

Objective:To investigate the effect of uridine diphosphate ceramide galactosyltransferase 8(UGT8)on colorectal cancer(CRC)cell growth and migration,elucidate an underlying mechanism,and assess the potential regulatory role of SRY-box transcription factor 9(SOX9)on UGT8.Methods:UGT8 and SOX9 mRNA expression levels in CRC tissues,and correlation between their expression levels,were analyzed using GEPIA2,UALCAN,and TIMER 2.0 online databases.UGT8 and SOX9 protein expression in CRC and adjacent tissues was detec-ted using immunohistochemistry,and relationships between their expression and clinicopathological characteristics were analyzed.Impact of UGT8 knockdown on CRC cell proliferation was assessed using a CCK-8 assay,and cell migration was evaluated using Transwell and wound healing assays.Western blot was performed to detect expression of epithelial-mesenchymal transition(EMT)markers(E-cadherin and ZEB1).RT-qPCR and Western blot were used to measure UGT8 mRNA and protein expression levels after SOX9 knockdown.The JASPAR online database was used to assess SOX9 potential for binding to the UGT8 promoter.Results:Bioinformatics analyses revealed significantly higher mRNA expression levels of both UGT8 and SOX9 in CRC tissues than in normal tissues.Positive correlation was observed between expres-sion levels.Immunohistochemistry results showed that tumor UGT8 and SOX9 protein levels were significantly higher than those in adjacent tissues.UGT8 protein level was found to correlates with N stage,and SOX9 protein level correlated with T stage.A positive correlation was observed between UGT8 and SOX9 expression levels.Following UGT8 knockdown,cell proliferation capacity was attenuated and cell migra-tion ability was reduced.E-cadherin expression concurrently increased and ZEB1 expression decreased.RT-qPCR and Western blot results showed that SOX9 knockdown significantly reduced UGT8 mRNA and protein levels.The JASPER website predicts that SOX9 will bind to the UGT8 promoter.Conclusions:UGT8 and SOX9 are highly expressed in CRC tissues,and their expression levels correlate with clinicopatholo-gical features.UGT8 and SOX9 expression levels display significant positive correlation.Mechanistically,UGT8 promotes CRC cell prolifera-tion and migration by facilitating epithelial-mesenchymal transition(EMT).SOX9 enhances UGT8 mRNA and protein expression and may bind to the UGT8 promoter region.

Objective:To explore the longitudinal relationship between adolescents' future self-continuity and depression, providing insights into their future development.Methods:A total of 419 adolescents from a school in Shandong Province were selected, and two followed-up surveys were conducted at 6-month intervals in April (T1) and October (T2) of 2023 using the future self-continuity questionnaire and Beck depression inventory-Ⅱ. Cross-lagged analysis was performed using Mplus 8.0.Results:The scores of future self-continuity were 36.01±8.69 at baseline (T1) and 35.89±9.92 after six months (T2), while the scores of depression were 2.00(0, 14.00) and 1.00(0, 9.00), respectively. There was a negative correlation between future self-continuity and depression at both time points (T1: r=-0.195, T2: r=-0.239, both P<0.01). Adolescents' future self-continuity could predict depression six months later ( β=-0.098, P<0.01), and depression also could predict the level of future self-continuity six months later ( β=-0.114, P<0.01). Conclusion:There is an interactively influence effect between adolescents' future self-continuity and depression.While enhancing adolescents' future self-continuity level to alleviate depression, attention should also be paid attention to the impact of depression on their future self-continuity, which can help adolescents overcome the interference of depressive emotions and grow into a better future self.