ObjectiveTo investigate the preventive and therapeutic effects of Qingfei Paidu decoction (QFPDD) on acute lung injury (ALI) in mice and its underlying molecular mechanisms based on miRNA sequencing technology. MethodsTwenty-four 4-week-old male KM mice were randomly divided into a control group, a model group, and a QFPDD group (n = 8 per group). After one week of acclimatization, mice in the control and model groups were intragastrically administered ultrapure water (0.2 mL per dose), whereas mice in the QFPDD group were intragastrically administered QFPDD (1.6 g crude drug/mL, 0.2 mL per dose), twice daily for 8 consecutive days. On days 2–8, mice in the model and QFPDD groups were exposed to aerosolized lipopolysaccharide (LPS) solution (2.5 g/L, 4 mL per exposure) for 7 consecutive days. On day 9, blood was collected via the retro-orbital venous plexus under deep anesthesia, and lung tissues were harvested. Body weight and lung weight were measured, and the lung coefficient was calculated. Serum levels of inflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 were detected by ELISA. Lung histopathological changes were observed by HE staining of paraffin-embedded sections. miRNA expression profiles in lung tissues were analyzed using the Illumina HiSeq 2500 sequencing platform. Target genes of differentially expressed miRNAs were predicted using bioinformatics databases, and functional enrichment analysis of these target genes was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Differentially expressed miRNAs were validated by reverse transcription quantitative real-time PCR (RT-qPCR). ResultsCompared with the control group, the model group showed a consistent body weight growth trend but a significantly increased lung coefficient (P < 0.01). ELISA results showed that serum levels of TNF-α and IL-6 were significantly elevated in the model group compared with the control group (P < 0.01), whereas QFPDD treatment significantly reduced serum TNF-α and IL-6 levels compared with the model group (P < 0.05). HE staining showed that, compared with the control group, the model group exhibited widened alveolar septa, massive inflammatory cell infiltration, partial alveolar expansion, and mild capillary dilation with congestion. In contrast, the QFPDD group showed only slightly widened alveolar septa and mild inflammatory cell infiltration compared with the model group. Intersection analysis of miRNA sequencing data identified 13 differentially expressed miRNAs common to both the model vs. control and QFPDD vs. model comparisons. Among them, 6 miRNAs (mmu-miR-203-3p, mmu-miR-181b-5p_R-1, hsa-miR-4286_R+1, mmu-miR-1843b-5p_L+1R-1_2, mmu-miR-22-3p, and mmu-miR-1964-3p) were significantly up-regulated in the model group (P < 0.05) and significantly down-regulated after QFPDD treatment (P < 0.05), showing a therapeutic reversal trend. GO analysis revealed that the target genes of the differentially expressed miRNAs were mainly enriched in biological processes such as RNA polymerase Ⅱ transcriptional regulation. KEGG analysis indicated that target genes were mainly enriched in signaling pathways including the mitogen-activated protein kinase (MAPK) pathway. RT-qPCR validation result for mmu-miR-203-3p was consistent with the sequencing analysis results. ConclusionQFPDD may exert preventive and therapeutic effects against ALI by regulating the expression of mmu-miR-203-3p and other miRNAs, thereby modulating inflammatory responses and the MAPK signaling pathway and participating in the pathological process of lung injury.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

Objective:To investigate the effect of atosiban on hemodynamic parameters of uterine arteries and clinical effect evaluation in patients with previous implantation failure undergoing frozen-thawed embryo transfer.Methods:A retrospective cohort study was conducted to analyze 298 cycles of FET in the Department of Reproductive Medicine of the Second Affiliated Hospital of Zhengzhou University from January 2021 to June 2023. Patients were categorized into atosiban group ( n=149) and control group ( n=149) according to whether administered atosiban or not. The related indicators and clinical outcomes were compared between the two groups. Hemodynamic parameters of the uterine arteries, including bilateral uterine artery peak systolic velocity/diastolic velocity (S/D), pulsatility index (PI), resistance index (RI), and serum levels of prostaglandin F2α (PGF2α) and oxytocin were compared before and after atosiban treatment. Univariate and multivariate logistic regression analysis were applied to assess the effect of atosiban on pregnancy outcomes. The effect of atosiban on live birth rate was analyzed by age stratification. Results:The implantation rate [51.92% (135/260)], the clinical pregnancy rate [67.11% (100/149)] and the live birth rate [59.06% (88/149)] in atosiban group were significantly higher than those in control group [41.13% (102/248), P=0.015; 51.01% (76/149), P=0.005; 40.27% (60/149), P=0.001]; and the early miscarriage rate [9.00% (9/100)] was lower than that of control group [19.74% (15/76), P=0.040]. Multivariate logistic regression analysis showed that atosiban was an independent influencing factor of live birth rate ( OR=2.236, 95% CI: 1.371-3.646, P=0.001). The post-treatment right uterine artery blood flow S/D [4.61 (4.00, 5.36)], PI [1.81 (1.58, 2.05)], RI [0.79 (0.75, 0.82)], and left uterine artery blood flow S/D [4.62 (3.83, 5.61)], PI (1.84±0.38), RI [0.79 (0.74, 0.82)] were all lower than those before treatment [right S/D 4.93 (4.06, 6.04), P<0.001; PI 1.93 (1.60, 2.17), P=0.001; RI 0.80 (0.76, 0.83), P<0.001; left S/D 5.05 (4.20, 6.32), P<0.001; PI 1.95±0.43, P<0.001; RI 0.81 (0.76, 0.84), P<0.001]. Besides, the levels of PGF2α [97.01 (85.15, 109.93) ng/L] and oxytocin [41.18 (37.16, 46.78) ng/L] after treatment in atosiban group were significantly lower than those before treatment [119.71 (108.85, 129.99) ng/L, P<0.001; 51.87 (46.44, 55.54) ng/L, P<0.001). Moreover, the endometrial peristalsis waves in atosiban group were significantly less after treatment [1.00 (0.00, 2.00) times/min] than before treatment [2.00 (1.00, 3.00) times/min], and the difference was statistically significant ( P<0.001). Conclusion:Atosiban can improve uterine artery blood flow and reduce endometrial peristalsis waves in women with previous implantation failure, which increases endometrial blood perfusion. Additionally, it can also reduce the levels of PGF2α and oxytocin, and optimize the pregnancy outcome of the frozen-thawed embryo transfer.

Objective To investigate correlations of the ratio of specific brain region volume to total brain volume(ratio％),standard uptake value(SUV)of specific brain region based on 18F-FDG PET/MR examination in Alzheimer disease(AD)patients,as well as the relationship between changes of these two.Methods Fifty AD patients were retrospectively collected.Based on FDG PET/MR,the ratio％and the mean SUV(SUVmean)of 40 specific brain regions were obtained,and the correlation between ratio％and SUVmean for each region were evaluated.According to a database of normal brains,Z-scores for ratio％and SUVmean were calculated to represent structural and functional changes in AD patients,and the correlation between these 2 Z-scores was assessed.Results Correlations were found between ratio％and SUVmean,also between Z-scores of these two parameters in 29 brain regions(r=0.288 to 0.778,all P＜0.05).Among them 7 brain regions,i.e.bilateral middle temporal gyrus,right fusiform gyrus,right hippocampus,right precuneus,left lingual gyrus and right parahippocampal gyrus exhibited correlation coefficients greater than 0.6.Conclusion There were some relationships between brain structural and metabolic functions and their changes in AD patients showed on FDG PET/MR.

Metabolic-bariatric surgery(MBS)has become an important treatment for pathological obesity and metabolic diseases.However,common postoperative nutritional complications—such as protein-energy malnutrition,iron deficiency anemia,and vitamin B12 deficiency—significantly affect patients' long-term prognosis.Traditional nutritional management models rely on static monitoring and standardized supplementation,which are insufficient to address individual variability and dynamic postoperative changes.Artificial intelligence(AI),through integrating multimodal data(such as biochemical indicators,imaging information,and wearable device monitoring)and intelligent modeling,offers new approaches for dynamic monitoring,risk prediction,and personalized intervention.Based on literature from 2017 to 2025,this article systematically evaluates the application of AI in perioperative nutritional management for MBS,covering key technologies including machine learning,deep learning,and natural language processing.It also analyzes current challenges in clinical translation,such as data fragmentation,lack of model interpretability,and limited long-term validation.In the future,enhanced multi-center collaboration,the development of standardized databases,and explainable models will be essential to advancing nutritional management in MBS from empirical practice to precision medicine.

Objective To investigate correlations of the ratio of specific brain region volume to total brain volume(ratio％),standard uptake value(SUV)of specific brain region based on 18F-FDG PET/MR examination in Alzheimer disease(AD)patients,as well as the relationship between changes of these two.Methods Fifty AD patients were retrospectively collected.Based on FDG PET/MR,the ratio％and the mean SUV(SUVmean)of 40 specific brain regions were obtained,and the correlation between ratio％and SUVmean for each region were evaluated.According to a database of normal brains,Z-scores for ratio％and SUVmean were calculated to represent structural and functional changes in AD patients,and the correlation between these 2 Z-scores was assessed.Results Correlations were found between ratio％and SUVmean,also between Z-scores of these two parameters in 29 brain regions(r=0.288 to 0.778,all P＜0.05).Among them 7 brain regions,i.e.bilateral middle temporal gyrus,right fusiform gyrus,right hippocampus,right precuneus,left lingual gyrus and right parahippocampal gyrus exhibited correlation coefficients greater than 0.6.Conclusion There were some relationships between brain structural and metabolic functions and their changes in AD patients showed on FDG PET/MR.

Objective:To investigate the effect of atosiban on hemodynamic parameters of uterine arteries and clinical effect evaluation in patients with previous implantation failure undergoing frozen-thawed embryo transfer.Methods:A retrospective cohort study was conducted to analyze 298 cycles of FET in the Department of Reproductive Medicine of the Second Affiliated Hospital of Zhengzhou University from January 2021 to June 2023. Patients were categorized into atosiban group ( n=149) and control group ( n=149) according to whether administered atosiban or not. The related indicators and clinical outcomes were compared between the two groups. Hemodynamic parameters of the uterine arteries, including bilateral uterine artery peak systolic velocity/diastolic velocity (S/D), pulsatility index (PI), resistance index (RI), and serum levels of prostaglandin F2α (PGF2α) and oxytocin were compared before and after atosiban treatment. Univariate and multivariate logistic regression analysis were applied to assess the effect of atosiban on pregnancy outcomes. The effect of atosiban on live birth rate was analyzed by age stratification. Results:The implantation rate [51.92% (135/260)], the clinical pregnancy rate [67.11% (100/149)] and the live birth rate [59.06% (88/149)] in atosiban group were significantly higher than those in control group [41.13% (102/248), P=0.015; 51.01% (76/149), P=0.005; 40.27% (60/149), P=0.001]; and the early miscarriage rate [9.00% (9/100)] was lower than that of control group [19.74% (15/76), P=0.040]. Multivariate logistic regression analysis showed that atosiban was an independent influencing factor of live birth rate ( OR=2.236, 95% CI: 1.371-3.646, P=0.001). The post-treatment right uterine artery blood flow S/D [4.61 (4.00, 5.36)], PI [1.81 (1.58, 2.05)], RI [0.79 (0.75, 0.82)], and left uterine artery blood flow S/D [4.62 (3.83, 5.61)], PI (1.84±0.38), RI [0.79 (0.74, 0.82)] were all lower than those before treatment [right S/D 4.93 (4.06, 6.04), P<0.001; PI 1.93 (1.60, 2.17), P=0.001; RI 0.80 (0.76, 0.83), P<0.001; left S/D 5.05 (4.20, 6.32), P<0.001; PI 1.95±0.43, P<0.001; RI 0.81 (0.76, 0.84), P<0.001]. Besides, the levels of PGF2α [97.01 (85.15, 109.93) ng/L] and oxytocin [41.18 (37.16, 46.78) ng/L] after treatment in atosiban group were significantly lower than those before treatment [119.71 (108.85, 129.99) ng/L, P<0.001; 51.87 (46.44, 55.54) ng/L, P<0.001). Moreover, the endometrial peristalsis waves in atosiban group were significantly less after treatment [1.00 (0.00, 2.00) times/min] than before treatment [2.00 (1.00, 3.00) times/min], and the difference was statistically significant ( P<0.001). Conclusion:Atosiban can improve uterine artery blood flow and reduce endometrial peristalsis waves in women with previous implantation failure, which increases endometrial blood perfusion. Additionally, it can also reduce the levels of PGF2α and oxytocin, and optimize the pregnancy outcome of the frozen-thawed embryo transfer.

Metabolic-bariatric surgery(MBS)has become an important treatment for pathological obesity and metabolic diseases.However,common postoperative nutritional complications—such as protein-energy malnutrition,iron deficiency anemia,and vitamin B12 deficiency—significantly affect patients' long-term prognosis.Traditional nutritional management models rely on static monitoring and standardized supplementation,which are insufficient to address individual variability and dynamic postoperative changes.Artificial intelligence(AI),through integrating multimodal data(such as biochemical indicators,imaging information,and wearable device monitoring)and intelligent modeling,offers new approaches for dynamic monitoring,risk prediction,and personalized intervention.Based on literature from 2017 to 2025,this article systematically evaluates the application of AI in perioperative nutritional management for MBS,covering key technologies including machine learning,deep learning,and natural language processing.It also analyzes current challenges in clinical translation,such as data fragmentation,lack of model interpretability,and limited long-term validation.In the future,enhanced multi-center collaboration,the development of standardized databases,and explainable models will be essential to advancing nutritional management in MBS from empirical practice to precision medicine.

Aim To perform high-throughput screen-ing of immunomodulatory traditional Chinese medicine(TCMs)based on an in vitro B cell differentiation-antibody secretion model,identifying active herbal candidates with immune-enhancing properties to pro-vide novel therapeutic options and theoretical support for influenza virus treatment in immunocompromised in-dividuals.Methods B cells were stimulated with dif-ferent concentrations of cytosine-phosphate-guanine oli-godeoxynucleotide 2006(CpG)and nterleukin-2(IL-2)to promote proliferation,differentiation,and anti-body secretion,and the effects of varying concentra-tions of the solvent DMSO were also evaluated.The op-timal conditions for the B cell differentiation-anti-body secretion model were determined based on the se-cretion levels of three antibody isotypes.The feasibility of the model was further validated using rapamycin,a known B cell function inhibitor.On this basis,a high-throughput screening platform for immunomodulatory a-gents was optimized and established.Subsequently,the immune-enhancing activity of 465 polarity extract from TCMs was evaluated.Results The optimal con-ditions for the model were determined as 2 mg·L-1 CpG,1.67 × 106 nkat·L-1 IL-2,and DMSO with a volume fraction of 0.1％.Rapamycin effectively inhib-ited B cell differentiation into plasmablast and signifi-cantly reduced antibody production,indicating the reli-ability of the model.Multiple rounds of screening re-vealed that the dichloromethane extract of licorice,the dichloromethane extract of Vinegar-processed Curcumae Rhizoma,the cyclohexane extract of Honey-prepared Radix Asteris,and the aqueous extract of Siphonostegia chinensis Benth were identified to significantly promote both B cell proliferation and differentiation and anti-body secretion at a concentration of 600 μg·L-1.Conclusion This study successfully optimizes an in vitro B cell differentiation-antibody secretion model and identifies several TCM extracts,including licorice,with potential immune-enhancing activity.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.