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.

This article systematically analyzed the historical evolution of the origin， scientific name， producing area， quality evaluation， harvesting and processing， and other aspects of Quisqualis Fructus by consulting the ancient materia medica， medical books， prescription books， local literature and combining with the modern literature and standards， summarized and explored the development rules of its medicinal properties and efficacy along with their underlying causes， in order to provide support for the development and utilization of famous classical formulas containing this herb. According to the textual research， Shijunzi was first recorded as Liuqiuzi in Nanfang Caomuzhuang of the Jin dynasty， and the name of Shijunzi was first used in Kaibao Bencao of the Song dynasty， which has been consistently used throughout subsequent dynasties， and there were also aliases such as Junziren， Sijunzi， and Dujilizi. The mainstream source of Quisqualis Fructus used in the past dynasties has been the dried mature fruits of Quisqualis indica， a plant belonging to the family Combretaceae. In modern times， its variety Q. indica var. villosa has also been recorded as the medicinal material of Quisqualis Fructus. In 2007， the Flora of China（English edition） designated Q. indica var. villosa as a synonym of Q. indica. Today， the accepted name of Shijunzi is updated to Combretum indicum. According to ancient herbal records， the producing areas of Quisqualis Fructus were Guangdong， Hong Kong， Macao， Guangxi， Hainan， Sichuan and Fujian， and then gradually expanded to Yunnan， Taiwan， Jiangxi and Guizhou. Since the Song dynasty， two major production regions have gradually emerged in Sichuan， Chongqing and Fujian. Currently， it is primarily cultivated in Chongqing， Guangxi and other areas， with Chongqing yielding the highest output. Since modern times， superior quality has been defined by large size， a purple-black surface， plump grains， and a yellowish-white kernel. According to ancient herbal records， the harvesting period of Quisqualis Fructus was the July and August of the lunar calendar， mostly used raw after shelling or with the shell intact， it underwent processing methods such as cleaning， slicing， mixing， steaming， roasting， stewing， and frying. Currently， the harvesting period is autumn， followed by sun-drying or low-heat drying， with processing methods including cleaning， stir-frying， and stewing. In ancient and modern literature， the records of the properties， functions and indications of Quisqualis Fructus are basically the same， that is， sweet in taste， warm in nature， predominantly non-toxic， belonging to the spleen and stomach meridians. It possesses effects of insecticide， decontamination and invigorating spleen for ascariasis， enterobiasis， abdominal pain due to worm accumulation and infantile malnutrition.The contraindications for use primarily include avoiding consumption by individuals without parasitic infestations， limiting use for those with spleen-stomach deficiency-cold， refraining from drinking hot tea during medication， and avoiding excessive intake. Based on the textual research， it is suggested that the dried mature fruits of Q. indica should be used as the medicinal material for the development of famous classical formulas containing Quisqualis Fructus. Processing methods may be chosen according to prescription requirements， and the raw products is recommended for medicinal use if not specified.

ObjectiveTo evaluate the efficacy and safety of Janus kinase （JAK） inhibitors combined with Chinese herbal medicine （CHM） in treating rheumatoid arthritis （RA）. MethodsClinical data from 169 RA patients were retrospectively collected. Among them， 71 cases received JAK inhibitors as the control group， while 98 cases received JAK inhibitors plus CHM as the observation group， both treated for 24 weeks. The rheumatoid factor （RF）， cyclic citic peptide antibody （anti-CCP）， erythrocyte sedimentation rate （ESR）， C-reactive protein （CRP）， and white blood cell count （WBC） were recorded before and after treatment. Databases including CNKI， Wanfang， VIP， PubMed and Web of Science were searched from inception till August 31st， 2025 for randomized controlled trials （RCTs） on the combined use of JAK inhibitors and CHM for RA. The methodological quality of the included studies was evaluated using the risk of bias assessment tool. Meta-analyses were performed for RF， anti-CCP， ESR， CRP， 28-joint disease activity score （DAS28）， overall clinical effective rate， and incidence of adverse events. Sensitivity analysis were also performed. ResultsThe retrospective study demonstrated that after treatment， ESR， CRP， and anti-CCP levels decreased in the observation group， while ESR and CRP levels decreased in the control group （P＜0.05）. Moreover， ESR and RF levels in the observation group were lower than those in the control group （P＜0.05）. A total of 9 RCTs involving 770 patients were included in the meta-analysis. The results indicated that the JAK inhibitors plus CHM group was superior to the JAK inhibitors group in reducing RF （MD=-8.97， 95%CI -15.01 to -2.94， P=0.004）， CRP （MD=-3.34， 95%CI -3.82 to -2.86， P＜0.001）， ESR （MD=-5.33， 95%CI -7.98 to -2.69， P＜0.001）， and DAS28 score （MD=-0.54， 95%CI -0.74 to -0.34， P＜0.001）， as well as in improving the overall clinical effective rate （OR=4.53， 95%CI 2.55 to 8.03， P＜0.001）. No statistically significant differences were observed between groups in anti-CCP levels （SMD=-2.08， 95%CI -4.41 to 0.24， P=0.080） or incidence of adverse events （OR=0.93， 95%CI 0.55 to 1.57， P=0.790）. ConclusionThe combination of JAK inhibitors and CHM demonstrates remarkable efficacy in treating RA， contributing to improved disease activity and reduced inflammatory markers with a favorable safety profile.

Twelve compounds were isolated from the rice fermentation extracts of Penicillium expansum GY618 by silica column chromatography, Sephadex gel column chromatography, ODS column chromatography and semi preparative HPLC methods. They were determined as 11-hydroxyl-penicitrinone F (1), penicitrinone F (2), betulin (3), erythrodiol (4), ergosterol (5), ergost-5α,8α-epidioxy-6,22-dien-3β-ol (6), (5α,8α-epidioxy-(22E,24R)-ergosta-6,9(11),22-trien-3β-ol) (7), 5α,8α-epidioxy-(22E,24R)-23-methylergosta-6,22-dien-3β-ol (8), 5α,8α-epidioxy- 23,24(R)-dimethylcholesta-6,9(11),22-trien-3β-ol (9), dankasterone A (10), (17R)-4-hydroxy-17-methylincisterol (11) and ergosta-4,6,8(14),22-tetraen-3-one (12), through mass spectrometer, nuclear magnetic resonance (NMR) and comparison with the literature. Compound 1 was a new compound and compounds 2-4, 6-12 were isolated from Penicillium expansum fungus for the first time. The tyrosinase inhibitory activity experiment showed that compounds 1, 3 and 12 showed certain inhibitory activity against tyrosinase with IC₅₀ values of (75 ± 9), (69 ± 8) and (64 ± 2) μmol·L^-1, respectively. The IC₅₀ of other compounds were all greater than 100 μmol·L^-1, while IC₅₀ of the positive control kojic acid was (46 ± 4) μmol·L^-1.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

BACKGROUND:Exercise has a regulatory effect on intestinal flora and glucose metabolism,but the effects of high-intensity intermittent exercise on intestinal flora and glucose metabolism in patients with type 2 diabetes mellitus are unclear. OBJECTIVE:To investigate the effects of high-intensity intermittent exercise on glucose metabolism and intestinal flora in patients with type 2 diabetes mellitus. METHODS:Eleven patients with type 2 diabetes mellitus were recruited,among which,two were lost to the follow-up and nine were finally enrolled.High-intensity intermittent exercise intervention was conducted 3 times per week for 6 continuous weeks.Fasting blood and fecal samples were collected before and after the intervention.Glucose metabolism indexes were detected in the blood samples,and intestinal flora was detected in the fecal samples.Changes in glucose metabolism indexes and intestinal flora indexes of the patients with type 2 diabetes mellitus before and after the intervention were compared. RESULTS AND CONCLUSION:After 6 weeks of high-intensity intermittent exercise intervention,fasting blood glucose and glycosylated serum protein levels in patients were significantly reduced(P<0.05),and fasting insulin,although not significantly changed,was decreased compared with before intervention.Alpha diversity analysis showed that the diversity(Shannon index),richness(Chao index)and coverage(Coverage index)did not change significantly.Venn diagrams showed that the relative abundance of Bacteroidetes,Actinobacteria,Proteobacteria,and Fusobacteria in the intestinal flora of the patients increased,and the relative abundance of Firmicutes decreased,and a significant decrease was seen in Ruminococcus_torques and Ruminococcus_gnavus in the Firmicutes,which were both positively correlated with the abnormalities of the glycemic metabolism-related indicators,as well as with other disease development.All these findings indicate that high-intensity intermittent exercise intervention has an improvement effect on the glycemic metabolism-related indexes of patients with type 2 diabetes mellitus,and the abundance of beneficial flora in the intestinal tract increases,and the abundance of harmful flora decreased,enhancing the stability of the intestinal flora in patients.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

A 12-year-old boy was admitted with symptoms of cough and fever lasting over a month, accompanied by weight loss 2 kg. Prior anti-infective treatments proved ineffective in alleviating the symptoms. Chest imaging revealed diffuse interstitial pulmonary edema in the right lung with obstructed lymphatic drainage. Combined with histopathological examinations, the diagnosis was confirmed as lung cancer with pulmonary lymphangitic carcinomatosis. The patient underwent chemotherapy with docetaxel and carboplatin, yet the disease progressively worsened, resulting in death three months after diagnosis. This case highlights lung cancer should not be overlooked in patients with persistent respiratory symptoms of unknown etiology. Early imaging examinations, along with necessary pathological evaluations, are crucial for timely detection and diagnosis. The presence of pulmonary lymphangitic carcinomatosis often indicates an advanced-stage of cancer, associated with a poor prognosis.
Humans ; Male ; Lung Neoplasms/complications* ; Child ; Carcinoma/drug therapy*