ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveTo investigate the processing technology of calcined Haematitum based on the concept of quality by design（QbD） and to assess its health risk. MethodsTaking whole iron content， Fe²⁺ dissolution content and looseness as critical quality attributes（CQAs）， and calcination temperature， calcination time， spreading thickness and particle size as critical process parameters（CPPs） determined by the failure mode and effect analysis（FMEA）， the processing technology of calcined Haematitum was optimized by orthogonal test combined with analytic hierarchy process-criteria importance through intercriteria correlation（AHP-CRITIC） hybrid weighting method. The contents of heavy metals and harmful elements were determined by inductively coupled plasma mass spectrometry， and the health risk assessment was carried out by daily exposure（EXP）， target hazard quotient（THQ） and lifetime cancer risk（LCR）， and the theoretical value of the maximum limit was deduced. ResultsThe optimal processing technology for calcined Haematitum was calcination at 650 ℃， calcination time of 1 h， particle size of 0.2-0.5 cm， spreading thickness of 1 cm， and vinegar quenching for 1 time［Haematitum-vinegar（10：3）］. The contents of 5 heavy metals and harmful elements in 13 batches of calcined Haematitum were all decreased with reductions of up to 5-fold. The cumulative THQ of 2 batches of samples was>1， while the cumulative THQ of all batches of Haematitum was>1. The LCR of As in 1 batches of Haematitum was 1×10^-6-1×10^-4， and the LCR of the rest was<1×10^-6， and the LCRs of calcined Haematitum were all<1×10^-6， indicating that the carcinogenic risk of calcined Haematitum was low， but special attention should still be paid to Haematitum medicinal materials. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg were formulated as 1 014， 25， 17， 27， 7 mg·kg^-1. ConclusionThe optimized processing technology of calcined Haematitum is stable and feasible， and the contents of heavy metals and harmful elements are reduced after processing. Preliminary theoretical values of the maximum limits of Cu， As， Cd， Pb and Hg are formulated to provide a scientific basis for the formulation of standards for the limits of harmful elements in Haematitum.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Aim To investigate the effect of Xuefu Zhuyu decoction on transforming growth factor-β1(TGF-β1 ) -induced endothelial-to-mesenchymal transition (EndMT) of pulmonary microvascular endothelial cells ( PMVEC), and further analyze the mechanism related to the TGF-β1/Smad signaling pathway. Method To construct an EndMT cell model, PMVEC was treated with TGF-β1 (5 μg · L

In this paper, the antitussive and expectorant activity of platycodin D (PD) were studied by constructing a mouse cough induced by concentrated ammonia water and a mouse trachea phenol red excretion model. The mechanism of antitussive and expectorant effect of PD was studied by metabolomics. The animal experiment was approved by the Animal Ethics Committee of Jiangxi University of Chinese Medicine (approval number: JZLLSC-20220739). Then mice were randomly divided into the normal, model, positive drug, PD low-dose, PD medium-dose and PD high-dose group. The antitussive and expectorant effects of PD were evaluated using a cough mouse model induced by concentrated ammonia water and a mouse tracheal phenol red excretion model, respectively. UHPLC-LTQ-Orbitrap-MS was used to identify the metabolites of mouse lung tissue, and multivariate statistical analysis method of orthogonal partial least squares discriminant analysis (OPLS-DA) was used for metabolites profile analysis. The differential metabolites were screened by variable projected importance value (VIP) and t-test results. Pathways for enrichment of differentiated metabolites were analyzed using the MetaboAnalyst platform. The comparative method was applied to analyze the differences in mechanisms of PD, Deapio-platycodin D (DPD) and total platycosides fraction. The results showed that PD at different concentrations could significantly prolong (P < 0.05) the incubation period of cough mice induced by ammonia water, reduce the coughs frequency, and significantly increase (P < 0.05) the amount of phenol red excretion in phenol red excretion model mice. PD could regulate 6 metabolic pathways of phenylalanine, tyrosine and tryptophan biosynthesis, linoleic acid metabolism, phenylalanine metabolism, glycerophospholipid metabolism, and tyrosine metabolism to exert antitussive effect. It could also regulate 8 metabolic pathways of linoleic acid metabolism, glyoxylic acid and dicarboxylic acid metabolism, glycerol phospholipid metabolism, citric acid cycle and arachidonic acid metabolism to exert an expectorant effect. However, only linoleic acid metabolism and glycerophospholipid metabolism could be regulated by the PD, total platycosides fraction and DPD, which may be ascribed to the structural difference of the platycosides and the interaction between platycosides and the intestinal microbiota. Functional analysis showed that these metabolic pathways are closely related to the regulatory mechanisms of anti-inflammatory response, immune function regulation, neurotransmitter release, cell signal transduction, energy metabolism and cell apoptosis. This study shows that PD possesses good antitussive and expectorant activities. In addition, the mechanism difference of PD, total platycosides fraction and DPD imply that the apiose in PD and the interaction between PD and intestinal microbiota could exert an important effect on the antitussive and expectorant mechanism of the platycosides.

Objective To investigate the relationship between the expression of long non-coding RNA HOXA-AS2(lncRNA HOXA-AS2),long non-coding RNA FOXD2-AS1(lncRNA FOXD2-AS1),and long non-coding RNA CRNDE(lncRNA CRNDE)in endometrial carcinoma and the clinical pathological character-istics and prognosis of patients.Methods Collect samples of endometrial carcinoma cancer tissues and adja-cent tissues excised during surgery from 119 endometrial carcinoma patients admitted to a hospital from Octo-ber 2017 to February 2020.The relative expression levels of HOXA-AS2,FOXD2-AS1 and CRNDE in tissues were retrospectively analyzed,as well as their relationship with clinicopathological features and 3-year survival rate of patients.Results The relative expression levels of HOXA-AS2,FOXD2-AS1 and CRNDE in cancer tissues of endometrial carcinoma patients were higher than those in adjacent tissues,with statistical signifi-cance(P＜0.05).The relative expression levels of HOXA-AS2,FOXD2-AS1 and CRNDE in cancer tissues of endometrial carcinoma patients were positively correlated(rHOXA-As2 vs.FOXD2-AS1=0.384,P=0.001;rHoXA-AS2 vs.CRNDE=0.576,P＜0.001;rFoXD2-AS1 vs.CRNDE=0.326,P=0.003).In the HOXA-AS2,FOXD2-AS1 and CRNDE high expression group,the proportion of patients with international federation of gynecology and ob-stetrics(FIGO)stage Ⅲ+Ⅳ,lymph node metastasis,deep infiltration and low differentiation was higher than that in the low expression group,with statistical significance(P＜0.05).The 3-year survival rate of low HOXA-AS2 expression group in endometrial cancer patients(52/60,86.67％)was higher than that of high HOXA-AS2 expression group(40/59,67.79％),the difference was statistically significant(x2=6.039,P＜0.05).The 3-year survival rate of patients with endometrial cancer with low FOXD2-AS1 expression group(53/59,89.83％)was higher than that of patients with endometrial cancer with high FOXD2-AS1 expression group(39/60,65.00％),and the difference was statistically significant(x2=10.456,P＜0.05).The 3-year sur-vival rate of low CRNDE expression group in endometrial cancer patients(51/60,85.00％)was higher than that of high CRNDE expression group(41/59,69.49％),and the difference was statistically significant(x2=4.079,P＜0.05).HOXA-AS2,FOXD2-AS1,and CRNDE were risk factors for death in endometrial carcinoma patients(P＜0.05).Conclusion The expression of HOXA-AS2,FOXD2-AS1,and CRNDE in endometrial carcinoma cancer tissue is closely related to the clinical pathological characteristics and prognosis of patients.

BACKGROUND:As the incidence of spinal cord injury increases with the years and axon regeneration after spinal cord injury was very difficult.How to promote the recovery from spinal cord injury and improve the transplantation efficiency of stem cells and other therapeutic cells after spinal cord injury has been the focus of clinical and scientific research. OBJECTIVE:To establish the efficient transplantation and replacement of mouse spinal cord microglia in the spinal cord injury model. METHODS:CX3CR1 creER-/+::LSL-BDNF-/+-tdTomato mice,CX3CR1+/GFP mice,β-actin GFP mice and C57 BL/6J wild-type mice at 8-10 weeks of age were selected.According to the requirements of the experiment,they were randomly divided into six groups.(1)Sham operation group:eight C57 BL/6J wild-type mice were used when only the lamina was removed without injury.(2)Spinal cord contusion injury group:eight C57 BL/6J wild-type mice were used.(3)Spinal cord crush injury group:eight C57 BL/6J wild-type mice were used.(4)Conjoined symbiotic spinal cord strike injury group:β-actin GFP mice with green fluorescent blood were surgically stitched together with C57 BL/6J wild-type mice,using eight β-actin GFP mice and eight C57 BL/6J wild-type mice.(5)Mr BMT-X Ray group(using PLX5622 to eliminate the spinal microglia and bone marrow transplantation with X-ray radiation):Bone marrow cells from four CX3CR1 creER-/+::LSL-BDNF-/+-tdTomato mice were extracted and transplanted into eight C57 BL/6J wild-type mice for spinal cord injury modeling.(6)Mr BMT-Busulfan group(using PLX5622 to eliminate the spinal microglia and bone marrow transplantation with Busulfan):Bone marrow cells from four CX3CR1+/GFP mice were transplanted into eight C57 BL/6J wild-type mice.The percentage of cell transplantation replacement in this group was observed,and the spinal cord injury model was not established in this group.The sham operation group,spinal cord contusion injury group and spinal cord crush injury group were sampled by perfusion on day 14 after spinal cord injury.The conjoined symbiotic spinal cord strike injury group was sampled by perfusion on day 7 after spinal cord injury.Mr BMT-X Ray group was sampled by perfusion on day 28 after spinal cord injury.Mr BMT-Busulfan group was sampled by perfusion on day 28 after transplantation.The sampling site was a 1.2 cm long spinal cord with the T10 segment as the center.In the Mr BMT-X Ray group and Mr BMT-Busulfan group,additional mouse brain tissue was retained to see if it would lead to brain transplantation and replacement.The number and proportion of transplanted and replaced cells in the damaged area were measured using transgenic mice,symbiosis and immunofluorescence. RESULTS AND CONCLUSION:Compared with the traditional peripheral blood transplantation(9.8%)of mice in the conjoined symbiotic spinal cord strike injury group,the new transplantation methods,Mr BMT-X Ray and Mr BMT-Busulfan,could greatly improve the proportion of spinal microglia transplantation and replacement,which could reach 84.8%and 95.6%,respectively.The difference was significant(P<0.05).The results showed that Mr BMT-X Ray and Mr BMT-Busulfan could achieve efficient replacement of spinal microglia cells,and could improve the problems of low cell transplantation efficiency,few survival numbers and unclear differentiation of the traditional cell transplantation methods.In addition,Mr BMT-X Ray can only replace the microglia in the spinal cord,while Mr BMT-Busulfan could avoid brain inflammation and injury caused by X-ray radiation transplantation.

BACKGROUND:Hypoxia is strongly associated with the development and progression of osteoarthritic chondrocyte injury,but the specific targets and regulatory mechanisms are unclear. OBJECTIVE:A machine learning approach was used to identify KDEL(Lys-Asp-Glu-Leu)receptor 3(KDELR3)as a characteristic gene for osteoarthritis hypoxia and immune infiltration analysis,to provide new ideas and methods for the treatment of osteoarthritis. METHODS:The osteoarthritis-related datasets were downloaded from the GEO database and the GSEA website to obtain hypoxia-related genes.The osteoarthritis datasets were batch-corrected and immune infiltration analyzed using R language,and osteoarthritis hypoxia genes were extracted for differential analysis.Differentially expressed genes were analyzed for GO function and KEGG signaling pathway.Weighted correlation network analysis(WGCNA)and machine learning were also used to screen osteoarthritis hypoxia signature genes,and in vitro cellular experiments were performed to validate expression and correlate immune infiltration analysis using the datasets and qPCR. RESULTS AND CONCLUSION:(1)8492 osteoarthritis genes were obtained by batch correction and principal component analysis,mainly strongly associated with immune cells such as Macrophages M2 and Mast cells resting;200 hypoxia genes were also obtained,resulting in 41 osteoarthritis hypoxia differentially expressed genes.(2)GO analysis involved mainly biological processes such as response to nutrient levels and glucocorticoids;cellular components such as lysosomal lumen and Golgi lumen;and molecular functions such as 14-3-3 protein binding and DNA-binding transcriptional activator activity.(3)KEGG analysis of osteoarthritis hypoxia differentially expressed genes was associated with signaling pathways such as PI3K-Akt,FoxO,and microRNAs in cancer.(4)The characteristic gene KDELR3 was obtained after using WGCNA analysis and machine learning screening.(5)The gene expression of KDELR3 was found to be higher in the test group than in the control group in the synovium(P=0.014)but lower in the meniscus(P=0.024)after validation by gene microarray.(6)In vitro chondrocyte assay showed that the expression of KDELR3 was higher in cartilage than in the control group(P=0.005),while KDELR3 was closely associated with Macrophages M0(P=0.014)and T cells follicular helper(P=0.014).Using a machine learning approach,we confirmed that KDELR3 can be used as a hypoxic signature gene for osteoarthritis and may intervene in osteoarthritis pathogenesis by improving hypoxia,expecting to provide a new direction for better treatment of osteoarthritis.

BACKGROUND:Ferroptosis is strongly associated with the occurrence and progression of osteoarthritis,but the specific characteristic genes and regulatory mechanisms are not known. OBJECTIVE:To identify osteoarthritis ferroptosis signature genes and immune infiltration analysis using the WGCNA and various machine learning methods. METHODS:The osteoarthritis dataset was downloaded from the GEO database and ferroptosis-related genes were obtained from the FerrDb website.R language was used to batch correct the osteoarthritis dataset,extract osteoarthritis ferroptosis genes and perform differential analysis,analyze differentially expressed genes for GO function and KEGG signaling pathway.WGCNA analysis and machine learning(random forest,LASSO regression,and SVM-RFE analysis)were also used to screen osteoarthritis ferroptosis signature genes.The in vitro cell experiments were performed to divide chondrocytes into normal and osteoarthritis model groups.The dataset and qPCR were used to verify expression and correlate immune infiltration analysis. RESULTS AND CONCLUSION:(1)12 548 osteoarthritis genes were obtained by batch correction and PCA analysis,while 484 ferroptosis genes were obtained,resulting in 24 differentially expressed genes of osteoarthritis ferroptosis.(2)GO analysis mainly involved biological processes such as response to oxidative stress and response to organophosphorus,cellular components such as apical and apical plasma membranes,and molecular functions such as heme binding and tetrapyrrole binding.(3)KEGG analysis exhibited that differentially expressed genes of osteoarthritis ferroptosis were related to signaling pathways such as the interleukin 17 signaling pathway and tumor necrosis factor signaling pathway.(4)After using WGCNA analysis and machine learning screening,we obtained the characteristic gene KLF2.After validation by gene microarray,we found that the gene expression of KLF2 was higher in the test group than in the control group in the meniscus(P=0.000 14).(5)In vitro chondrocyte assay showed that type Ⅱ collagen and KLF2 expression was lower in the osteoarthritis group than in the control group in chondrocytes(P<0.05),while in osteoarthritis ferroptosis,mast cells activated was closely correlated with dendritic cells(r=0.99);KLF2 was closely correlated with natural killer cells(r=-1,P=0.017)and T cells follicular helper(r=-1,P=0.017).(6)The findings indicate that using WGCNA analysis and machine learning methods confirmed that KLF2 can be a characteristic gene for osteoarthritis ferroptosis and may improve osteoarthritis ferroptosis by interfering with KLF2.

Objective:To compare the short-term efficacy of robotic-assisted sacrocolpopexy(RASC)and lap-aroscopic sacrocolpopexy(LSC)in overweight/obese patients with pelvic organ prolapse(POP),and to evaluate the advantages of RASC.Methods:We retrospectively collected the clinical data of overweight/obese(body mass index≥24 kg/m2)patients over 50 years old with POP who underwent sacrocolpopexy in the Department of Gynecology of the First Affiliated Hospital of Zhengzhou University from November 2014 to June 2023.According to the surgical method,they were divided into robotic group(68 cases)and laparoscopic group(110 cases).The intraoperative,postoperative and short-term follow-up outcomes of the two groups were compared.Pelvic Floor Distress Inventory-short form 20(PFDI-20),Pelvic Floor Impact Questionnaire-short form 7(PFIQ-7)and the Patient Global Impression of Improvement(PGI-Ⅰ)were used to evaluate surgical outcomes.Results:①No intra-operative conversion to laparotomy was found in both groups.Compared with the laparoscopic group,the robotic group had shorter operation time,less intraoperative blood loss,shorter postoperative anal exhaust time,and shor-ter postoperative hospital stay.The difference was statistically significant(P＜0.05).②There were no intraopera-tive complications in the robot group.While in the laparoscopic group,there was 1 case of bladder injury.③Within the two groups,the PFDI-20 and PFIQ-7 scores at 3 and 12 months after surgery were lower than those before surgery,and the difference was statistically significant(P＜0.05).PGI-Ⅰ scores were both"significantly im-proved".Subjective and objective cure rate were 100％.④The POP-Q indicator points(Aa,Ba,C,Ap,Bp,gh,pb,TVL)of both groups at 3 and 12 months after surgery were better than those before surgery(P＜0.05),achie-ving satisfactory anatomical reduction.Conclusions:RASC is safe and feasible in the treatment of overweight and obese patients with POP.Compared to LSC,RASC has significantly shorter operation time,less blood loss,faster postoperative intestinal function recovery,shorter postoperative hospital stay,and stable short-term effect.Therefore,RASC can provide a new choice for overweight/obese patients with POP.