Objective To investigate the causal relationship between gut microbiota and idiopathic pulmonary fibrosis (IPF). Methods Genome-wide association studies (GWAS) data of gut microbiota and IPF were obtained from MiBioGen and IEU OpenGWAS, respectively. Instrumental variables were screened by means of significance, linkage disequilibrium, weak instrumental variable screening, and removal of confounding factors (genetics, smoking, host characteristics). Inverse variance weighted (IVW) was used as the main Mendelian randomization (MR) analysis method, and the weighted median, simple mode, MR-Egger, and weighted mode were used to perform MR to reveal the causal effect of gut microbiota and IPF. The Cochrane's Q, leave-one-out, MR-Egger-intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and Steiger tests were used to analyze the heterogeneity, horizontal pleiotropy, outliers, and directionality, respectively. Results IVW analysis results showed that Actinobacteria [OR=1.773, 95%CI (1.323, 2.377), P<0.001], Erysipelatoclostridium [OR=2.077, 95%CI (1.107, 3.896), P=0.023], and Streptococcus [OR=1.35, 95%CI (1.100, 1.657), P=0.004] could increase the risk of IPF. Bifidobacterium [OR=0.668, 95%CI (0.620, 0.720), P<0.001], Ruminococcus [OR=0.434, 95%CI (0.222, 0.848), P=0.015], and Tyzzerella [OR=0.479, 95%CI (0.304, 0.755), P=0.001] could reduce the risk of IPF. No significant heterogeneity, horizontal pleiotropy, outliers, and reverse causality were found. Conclusion Actinobacteria, Erysipelatoclostridium and Streptococcus may increase the risk of IPF, while Bifidobacterium, Ruminococcus and Tyzzerella may reduce the risk of IPF. Regulation of the above gut microbiota may become a new direction in the study of the pathogenesis of IPF.

Qingzao Jiufeitang is a famous classical formula for treating lung injury caused by warm and dryness， included in the Catalogue of Ancient Famous Classical Formulas（The First Batch）. By systematically organizing ancient and modern literature on this formula， this study analyzed and verified the origin， medicinal composition， original plants and processing， dosage and decoction method， efficacy and application of this formula. According to the research， Qingzao Jiufeitang was first recorded in Yimen Falyu in the Qing dynasty， and its creation was mainly inspired by the Ming dynasty physician MIAO Xiyong's idea of the moisturizing drugs with sweet flavour and cold nature. Based on the 2020 edition of the Pharmacopoeia of the People's Republic of China（hereinafter referred to as the Chinese Pharmacopoeia） and the textual research results of modern scholars on traditional Chinese herbal medicines， the botanical sources and processing methods of the herbs in this formula are basically clarified. Among them， Mori Folium， Gypsum Fibrosum， Ginseng Radix et Rhizoma， Sesami Semen Nigrum， Asini Corii Colla， Ophiopogonis Radix and Eriobotryae Folium are consistent with the 2020 edition of the Chinese Pharmacopoeia. The primary source of Glycyrrhizae Radix et Rhizoma is the dried roots and rhizomes of Glycyrrhiza uralensis， family Leguminosae， while the primary source of Armeniacae Semen Amarum is the dried mature seeds of Prunus armeniaca， family Rosaceae. It is recommended to use Gypsum Ustum， stir-fried Sesami Semen Nigrum， stir-fried Armeniacae Semen Amarum， Asini Corii Colla bead， and honey-fried Eriobotryae Folium， and the rest of the raw products. According to the conversion of ancient and modern doses， the recommended dosages are 11.19 g for Mori Folium， 9.33 g for Gypsum Fibrosum， 3.73 g for Glycyrrhizae Radix et Rhizoma， 2.61 g for Ginseng Radix et Rhizoma， 3.73 g for Sesami Semen Nigrum， 4.48 g for Ophiopogonis Radix， 2.61 g for Armeniacae Semen Amarum， 3.73 g for Eriobotryae Folium. The decoction method is to add 300 mL of water， decoct it down to 180 mL， remove the residue， and then add 2.98 g of Asini Corii Colla into the decoction. Take it warm after meals， two to three times a day. Qingzao Jiufeitang has the effects of clearing dryness and moistening the lungs， nourishing Yin and invigorating Qi. In ancient times， it was mainly used to treat stagnation and depression of various Qi， as well as paralysis， asthma and vomiting. In modern clinical practice， it is mostly used to treat diseases in respiratory system， otolaryngology， skin system and digestive system caused by warm-dry impairing lung， deficiency of both Qi and Yin. The above research results can provide a reference for the later development of Qingzao Jiufeitang.

Objective To analyze the composition characteristics and biological functions of tumor cell subpopulations in glioblastoma(GBM)through multi-transcriptomics sequencing technology,and explore the hypoxia characteristics and spatial localization features of the mesenchymal-like(MES-like)tumor cell subpopulation in GBM and the influence on malignant biological behaviors.Methods Multi-transcriptomics sequencing data,including single-cell RNA sequencing(scRNA-seq)data(18 patients),bulk RNA sequencing(bulk RNA-seq)and spatial transcriptomics(ST)data of GBM,were employed to define cell subpopulations in GBM,and Gene Ontology(GO)and Gene Set Enrichment Analysis(GSEA)were utilized to analyze their functions.The proportions and locations of cell subpopulations in bulk RNA-seq data were evaluated with BayesPrism deconvolution.Immunofluorescence assay was conducted for verification on 12 paraffin samples of GBM from patients who visited the neurosurgical department of our hospital from 2015 to 2023 and met the pathological diagnostic criteria for GBM(10 males and 2 females,at an average age of 53.50 years and a median age of 54.50 years).pySCENIC was applied to predict specific transcription factors of tumor cell subpopulations.Results Tumor cells in GBM were highly heterogeneous,and could be mainly divided into 4 subpopulations:astrocyte-like(AC-like),neural progenitor-like(NPC-like),oligodendrocyte progenitor-like(OPC-like)and MES-like.Differential gene analysis found that the MES-like tumor cells highly expressed vascular endothelial growth factor A(VEGFA),adrenomedullin(ADM),N-myc downstream regulated 1(NDRG1),insulin like growth factor binding protein 5(IGFBP5),and A-kinase anchoring protein 12(AKAP12)(P<0.001).pySCENIC transcription factor prediction found that the high-active transcription factors of the MES-like tumor cells were AT-rich interaction domain 3A(ARID3A),FOS like 2,AP-1 transcription factor subunit(FOSL2),endothelial PAS domain protein 1(EPAS1),CCAAT enhancer binding protein delta(CEBPD),and CCAAT enhancer binding protein beta(CEBPB)(P<0.05).GO and GSEA enrichment analyses found that the MES-like tumor cells were enriched in hypoxia-related pathways,especially the pathway of cell responses to hypoxia levels(NES=2.437,P<0.001).BayesPrism deconvolution showed that the MES-like tumor cells mainly existed in PAN(Pseudopalisading cells around necrosis)and perinecrotic zone.Immunofluorescence assay confirmed CD44+(CD44 antigen)MES-like tumor cells were mainly located in hypoxia areas with highly expression of hypoxia inducible factor 1 subunit alpha(HIF1α)(P<0.01).Multivariate Cox regression analysis indicated that the MES-like tumor cells were significantly correlated with the adverse prognosis of GBM patients(HR=1.71,95%CI:1.38～2.11,P<0.001).Conclusion Tumor cells in GBM are of highly heterogeneity.They could be mainly divided into 4 subpopulations:AC-like,NPC-like,OPC-like and MES-like.MES-like tumor cells,mainly locating in PAN and perinecrotic zone,are characterized by hypoxia,which can promote the malignant progression of GBM.

Objective To analyze the respective abnormal brain regions and commonly altered brain regions of spontaneous brain ac-tivity in post-stroke aphasia(PSA)and post-stroke depression(PSD),and to explore the potential pathological mechanisms underlying single disease and comorbidity.Methods Literatures were retrieved from PubMed,Embase,Web of Science,Cochrane Library,CNKI,Wanfang data,VIP and SinoMed,from establishment to April 19th,2025.Resting-state functional magnetic resonance imaging(fMRI)studies were included if they focused on patients with PSA or PSD,with healthy controls(HC)serving as control group,and amplitude of low-frequency fluctuation(ALFF),fractional amplitude of low-frequency fluctu-ation(fALFF)and regional homogeneity(ReHo)were adopted as outcome indicator.Data regarding differential brain regions were extracted from the original studies,and a neuroimaging meta-analysis was conducted using SDM-PSI V6.23 beta.Results A total of 17 articles on PSA(339 patients and 351 HC)and five articles on PSD(102 patients and 149 HC)were included.The spontaneous brain activity in the left cerebellar area 9,right middle temporal gyrus and right insula was significantly higher in PSA patients than in HC(P<0.05),while activity in the right cerebellar area 6,left medial superior frontal gyrus(SFGmed),left middle frontal gyrus and right anterior cingulate/paracingulate gyrus was lower(P<0.05).For PSD,spontaneous brain activity was elevated in the right cuneus gyrus and right superior occipital gyrus compared to HC(P<0.05),while it was reduced in the left SFGmed and left inferior pa-rietal lobe(P<0.05).Additionally,spontaneous brain activity in the left medial superior frontal gyrus was lower in both diseases compared to HC(P<0.05).Conclusion The pathological mechanism of PSA may involve a pattern of right-sided compensatory hyperfunction and left-sided inhibitory damage within the language-related network,accompanied by cross-hemispheric synergistic activity of the cerebellum.The occurrence of PSD may be attributed to hyperactivity of the right occipital net-work,and functional inhibition involving the left inferior parietal lobe.The inhibition observed in the left SFG-med(MNI coordinates x=0,y=26,z=44)likely represents the language-emotion integration hub,mediating the co-occurrence of PSA and PSD.

Distal transradial access(dTRA)was first applied in coronary heart disease intervention by Kiemeneij in 2017,dTRA has become an important technological advancement of coronary interventional therapy.This approach,performed by puncturing the distal radial artery within the anatomical snuffbox or Hegu point,significantly reduces the incidence of radial artery occlusion compared with conventional transradial access and shortens compression time to 2-3 hours after procedure.Clinical evidence confirms the efficacy of dTRA in facilitating complex percutaneous coronary interventions,including stenting of left main coronary artery bifurcation lesions and recanalization of chronic total occlusions.Its application has progressively expanded to neurointerventional procedures(cerebral angiography),tumor embolization(transarterial chemoembolization for hepatocellular carcinoma),and peripheral vascular interventions.Despite increasing clinical adoption,dTRA still faces challenges,including a long learning curve and relatively lower initial puncture success rates.Combined with the current paucity of robust evidence-based data,the viability of dTRA as a routine interventional access route remains a subject of debate.This article systematically reviews the anatomical landmarks,clinical advantages,limitations,and multidisciplinary applications of dTRA.This article aims to provide practical guidance for interventionalists and promote the standardization of this technique in daily clinical practice.

Distal transradial access(dTRA)was first applied in coronary heart disease intervention by Kiemeneij in 2017,dTRA has become an important technological advancement of coronary interventional therapy.This approach,performed by puncturing the distal radial artery within the anatomical snuffbox or Hegu point,significantly reduces the incidence of radial artery occlusion compared with conventional transradial access and shortens compression time to 2-3 hours after procedure.Clinical evidence confirms the efficacy of dTRA in facilitating complex percutaneous coronary interventions,including stenting of left main coronary artery bifurcation lesions and recanalization of chronic total occlusions.Its application has progressively expanded to neurointerventional procedures(cerebral angiography),tumor embolization(transarterial chemoembolization for hepatocellular carcinoma),and peripheral vascular interventions.Despite increasing clinical adoption,dTRA still faces challenges,including a long learning curve and relatively lower initial puncture success rates.Combined with the current paucity of robust evidence-based data,the viability of dTRA as a routine interventional access route remains a subject of debate.This article systematically reviews the anatomical landmarks,clinical advantages,limitations,and multidisciplinary applications of dTRA.This article aims to provide practical guidance for interventionalists and promote the standardization of this technique in daily clinical practice.

Lattice retinal degeneration is a common peripheral retinal degenerative condition and is widely recognized as a significant precursor to retinal detachment, resulting in severe visual loss. Recent advances in deep learning technologies have driven the development and adoption of automated screening systems for lattice retinal degeneration using ultra-widefield fundus imaging. These systems have demonstrated notable success in large-scale screening of peripheral retinal diseases, offering valuable support for the early identification and risk stratification of lattice degeneration. Currently, retinal laser photocoagulation remains the mainstay treatment for lattice degeneration. This intervention effectively mitigates the risk of rhegmatogenous retinal detachment. However, controversies persist regarding the optimal selection of treatment candidates and the evaluation of therapeutic efficacy. In the future, the continuous evolution of imaging analysis techniques and artificial intelligence holds promise for the development of personalized and precision-based intervention strategies. Such advancements are expected to provide more robust evidence to guide the diagnosis and treatment of lattice retinal degeneration, ultimately improving patient outcomes.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective To analyze the respective abnormal brain regions and commonly altered brain regions of spontaneous brain ac-tivity in post-stroke aphasia(PSA)and post-stroke depression(PSD),and to explore the potential pathological mechanisms underlying single disease and comorbidity.Methods Literatures were retrieved from PubMed,Embase,Web of Science,Cochrane Library,CNKI,Wanfang data,VIP and SinoMed,from establishment to April 19th,2025.Resting-state functional magnetic resonance imaging(fMRI)studies were included if they focused on patients with PSA or PSD,with healthy controls(HC)serving as control group,and amplitude of low-frequency fluctuation(ALFF),fractional amplitude of low-frequency fluctu-ation(fALFF)and regional homogeneity(ReHo)were adopted as outcome indicator.Data regarding differential brain regions were extracted from the original studies,and a neuroimaging meta-analysis was conducted using SDM-PSI V6.23 beta.Results A total of 17 articles on PSA(339 patients and 351 HC)and five articles on PSD(102 patients and 149 HC)were included.The spontaneous brain activity in the left cerebellar area 9,right middle temporal gyrus and right insula was significantly higher in PSA patients than in HC(P<0.05),while activity in the right cerebellar area 6,left medial superior frontal gyrus(SFGmed),left middle frontal gyrus and right anterior cingulate/paracingulate gyrus was lower(P<0.05).For PSD,spontaneous brain activity was elevated in the right cuneus gyrus and right superior occipital gyrus compared to HC(P<0.05),while it was reduced in the left SFGmed and left inferior pa-rietal lobe(P<0.05).Additionally,spontaneous brain activity in the left medial superior frontal gyrus was lower in both diseases compared to HC(P<0.05).Conclusion The pathological mechanism of PSA may involve a pattern of right-sided compensatory hyperfunction and left-sided inhibitory damage within the language-related network,accompanied by cross-hemispheric synergistic activity of the cerebellum.The occurrence of PSD may be attributed to hyperactivity of the right occipital net-work,and functional inhibition involving the left inferior parietal lobe.The inhibition observed in the left SFG-med(MNI coordinates x=0,y=26,z=44)likely represents the language-emotion integration hub,mediating the co-occurrence of PSA and PSD.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.