Objective To compare the benefits and drawbacks of primary patch expansion versus pericardial tube right ventricular-pulmonary artery connection in patients diagnosed with pulmonary atresia with ventricular septal defect (PA/VSD). Methods A retrospective study was conducted on patients diagnosed with PA/VSD who underwent primary right ventricular-pulmonary artery connection surgery at our center between 2010 and 2020. Patients were categorized into two groups based on the type of right ventricular-pulmonary artery connection: a pericardial tube group and a patch expansion group. Clinical data and imaging findings were compared between the two groups. Results A total of 51 patients were included in the study, comprising 31 males and 20 females, with a median age of 12.57 (4.57, 49.67) months. The pericardial tube group included 19 patients with a median age of 17.17 (7.33, 49.67) months, while the patch expansion group consisted of 32 patients with a median age of 8.58 (3.57, 52.72) months. In both groups, the diameter of pulmonary artery, McGoon index, and Nakata index significantly increased after treatment (P<0.001). However, the pericardial tube group exhibited a longer extracorporeal circulation time (P<0.001). The reoperation rate was notably high, with 74.51% of patients requiring further surgical intervention, including 26 (81.25%) patients in the patch expansion group and 12 (63.16%) patients in the pericardial tube group. No statistical differences were observed in long-term cure rates or mortality between the two groups (P＞0.005). Conclusion In patients with PA/VSD, both patch expansion and pericardial tube right ventricular-pulmonary artery connection serve as effective initial palliative treatment strategies that promote pulmonary vessel development and provide a favorable foundation for subsequent radical operations. However, compared to the pericardial tube approach, the patch expansion technique is simpler to perform and preserves some intrinsic potential for pulmonary artery development, making it the preferred procedure.

Background: This study aimed to investigate changes in gene expression related to matrix synthesis in individuals with fullthickness rotator cuff tears (RCTs) and normal tendon tissues. The study also aimed to examine the differences in gene expression according to 4 distinct tear sizes. Methods: A total of 12 patients with full-thickness RCTs were included in the study, all of whom underwent arthroscopic rotator cuff repair. The RCTs were stratified by size into small, medium, large, and massive. Tendon samples were harvested from the midpoint between the lateral end of the torn tendon and the musculotendinous junction. Subsequent analysis of the tissue samples revealed the mRNA expression levels of 11 collagen types, 6 proteoglycans, and 8 glycoproteins through real-time polymerase chain reaction techniques. For control purposes, supraspinatus tendon tissue was sourced from 3 patients who had proximal humerus fractures but did not present with RCTs. Results: Among the 11 collagens and 14 non-collagenous protein (NCP) genes examined in this study, COL3A1 and COL10A1 showed a significant increase, whereas COL4A1 and COL14A1 showed a tendency to decrease compared to those in the normal group. ACAN significantly increased by 8.92-fold (p < 0.001) compared to that in the normal group, whereas DCN and LUM showed a tendency to decrease. FN1 and TNC increased significantly by 3.47-fold (p = 0.003) and 5.38-fold (p = 0.005), respectively, and the genes ELN, LAMA2, and THBS1 were all significantly reduced compared to those in the normal group. In the NCPs, almost all the genes with increased expression levels had the highest level in small size RCTs, and gene expression decreased as the size increased. The 3 proteoglycans (ACAN, BGN, and FMOD) showed the highest levels of expression in small size RCTs compared to those in the normal group, and 5 glycoproteins (COMP, FBN1, FN1, HAPLN1, and TNC) also showed the highest expression in small size RCTs. Conclusions We confirmed that most of the detected extracellular matrix gene expression changes were related to the size of the full-thickness RCTs. In NCPs, gene expression was increased in small-size tears, and gene expression levels were significantly reduced when the size increased.

Background: This study aimed to investigate changes in gene expression related to matrix synthesis in individuals with fullthickness rotator cuff tears (RCTs) and normal tendon tissues. The study also aimed to examine the differences in gene expression according to 4 distinct tear sizes. Methods: A total of 12 patients with full-thickness RCTs were included in the study, all of whom underwent arthroscopic rotator cuff repair. The RCTs were stratified by size into small, medium, large, and massive. Tendon samples were harvested from the midpoint between the lateral end of the torn tendon and the musculotendinous junction. Subsequent analysis of the tissue samples revealed the mRNA expression levels of 11 collagen types, 6 proteoglycans, and 8 glycoproteins through real-time polymerase chain reaction techniques. For control purposes, supraspinatus tendon tissue was sourced from 3 patients who had proximal humerus fractures but did not present with RCTs. Results: Among the 11 collagens and 14 non-collagenous protein (NCP) genes examined in this study, COL3A1 and COL10A1 showed a significant increase, whereas COL4A1 and COL14A1 showed a tendency to decrease compared to those in the normal group. ACAN significantly increased by 8.92-fold (p < 0.001) compared to that in the normal group, whereas DCN and LUM showed a tendency to decrease. FN1 and TNC increased significantly by 3.47-fold (p = 0.003) and 5.38-fold (p = 0.005), respectively, and the genes ELN, LAMA2, and THBS1 were all significantly reduced compared to those in the normal group. In the NCPs, almost all the genes with increased expression levels had the highest level in small size RCTs, and gene expression decreased as the size increased. The 3 proteoglycans (ACAN, BGN, and FMOD) showed the highest levels of expression in small size RCTs compared to those in the normal group, and 5 glycoproteins (COMP, FBN1, FN1, HAPLN1, and TNC) also showed the highest expression in small size RCTs. Conclusions We confirmed that most of the detected extracellular matrix gene expression changes were related to the size of the full-thickness RCTs. In NCPs, gene expression was increased in small-size tears, and gene expression levels were significantly reduced when the size increased.

Background: This study aimed to investigate changes in gene expression related to matrix synthesis in individuals with fullthickness rotator cuff tears (RCTs) and normal tendon tissues. The study also aimed to examine the differences in gene expression according to 4 distinct tear sizes. Methods: A total of 12 patients with full-thickness RCTs were included in the study, all of whom underwent arthroscopic rotator cuff repair. The RCTs were stratified by size into small, medium, large, and massive. Tendon samples were harvested from the midpoint between the lateral end of the torn tendon and the musculotendinous junction. Subsequent analysis of the tissue samples revealed the mRNA expression levels of 11 collagen types, 6 proteoglycans, and 8 glycoproteins through real-time polymerase chain reaction techniques. For control purposes, supraspinatus tendon tissue was sourced from 3 patients who had proximal humerus fractures but did not present with RCTs. Results: Among the 11 collagens and 14 non-collagenous protein (NCP) genes examined in this study, COL3A1 and COL10A1 showed a significant increase, whereas COL4A1 and COL14A1 showed a tendency to decrease compared to those in the normal group. ACAN significantly increased by 8.92-fold (p < 0.001) compared to that in the normal group, whereas DCN and LUM showed a tendency to decrease. FN1 and TNC increased significantly by 3.47-fold (p = 0.003) and 5.38-fold (p = 0.005), respectively, and the genes ELN, LAMA2, and THBS1 were all significantly reduced compared to those in the normal group. In the NCPs, almost all the genes with increased expression levels had the highest level in small size RCTs, and gene expression decreased as the size increased. The 3 proteoglycans (ACAN, BGN, and FMOD) showed the highest levels of expression in small size RCTs compared to those in the normal group, and 5 glycoproteins (COMP, FBN1, FN1, HAPLN1, and TNC) also showed the highest expression in small size RCTs. Conclusions We confirmed that most of the detected extracellular matrix gene expression changes were related to the size of the full-thickness RCTs. In NCPs, gene expression was increased in small-size tears, and gene expression levels were significantly reduced when the size increased.

Background: This study aimed to investigate changes in gene expression related to matrix synthesis in individuals with fullthickness rotator cuff tears (RCTs) and normal tendon tissues. The study also aimed to examine the differences in gene expression according to 4 distinct tear sizes. Methods: A total of 12 patients with full-thickness RCTs were included in the study, all of whom underwent arthroscopic rotator cuff repair. The RCTs were stratified by size into small, medium, large, and massive. Tendon samples were harvested from the midpoint between the lateral end of the torn tendon and the musculotendinous junction. Subsequent analysis of the tissue samples revealed the mRNA expression levels of 11 collagen types, 6 proteoglycans, and 8 glycoproteins through real-time polymerase chain reaction techniques. For control purposes, supraspinatus tendon tissue was sourced from 3 patients who had proximal humerus fractures but did not present with RCTs. Results: Among the 11 collagens and 14 non-collagenous protein (NCP) genes examined in this study, COL3A1 and COL10A1 showed a significant increase, whereas COL4A1 and COL14A1 showed a tendency to decrease compared to those in the normal group. ACAN significantly increased by 8.92-fold (p < 0.001) compared to that in the normal group, whereas DCN and LUM showed a tendency to decrease. FN1 and TNC increased significantly by 3.47-fold (p = 0.003) and 5.38-fold (p = 0.005), respectively, and the genes ELN, LAMA2, and THBS1 were all significantly reduced compared to those in the normal group. In the NCPs, almost all the genes with increased expression levels had the highest level in small size RCTs, and gene expression decreased as the size increased. The 3 proteoglycans (ACAN, BGN, and FMOD) showed the highest levels of expression in small size RCTs compared to those in the normal group, and 5 glycoproteins (COMP, FBN1, FN1, HAPLN1, and TNC) also showed the highest expression in small size RCTs. Conclusions We confirmed that most of the detected extracellular matrix gene expression changes were related to the size of the full-thickness RCTs. In NCPs, gene expression was increased in small-size tears, and gene expression levels were significantly reduced when the size increased.

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.

OBJECTIVE: To explore the relationship between the effect of acupuncture and layered localization of computed tomography (CT) in treatment of lumbar disc herniation. METHODS: Based on the CT layered localization, the herniated lumbar discs were positioned in 5 layers, A, B, C, D and E among 300 patients with lumbar disc herniation. Combined with the horizontal and the frontal planes, the three-dimensional location was formed. Acupuncture was delivered at acupoints including bilateral Shenshu (BL23), Dachangshu (BL25), and Huantiao (GB30), Weizhong (BL40) on the affected side. One intervention of acupuncture was 30 min, once daily; 1 course of treatment was composed of 10 interventions and 2 courses were required. Before and after treatment, Japanese orthopaedic association (JOA) score was recorded, and the effect was evaluated. The curative effect was classified and compared with the CT layered localization. RESULTS: Of 300 patients, 226 cases were effective and the effective rate was 75.33%. The JOA scores of all patients, and in the effective group and the non-effective group were higher compared with the scores before treatment (P<0.05). With the layered localization considered, acupuncture was more effective on the cases positioned in C layer. Regarding the horizontal plane, the effect was better on the cases with zone 1 and zone 1-2 involved. In terms of the grade of frontal plane, acupuncture was more effective on the cases graded Ⅰ and Ⅱ. CONCLUSION The clinical effect of acupuncture on lumbar disc herniation is related with the layer and the horizontal zone of herniated disc positioned, as well as to the grade of the frontal plane.
Humans ; Acupuncture Therapy ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Middle Aged ; Adult ; Tomography, X-Ray Computed ; Lumbar Vertebrae/diagnostic imaging* ; Acupuncture Points ; Aged ; Young Adult ; Treatment Outcome

Traditional Chinese medicine(TCM) resources are the essential material foundation for the development of TCM. The national survey of TCM resources serves as a periodic summary of these resources, ensuring the continuity, prosperity, and development of TCM in China. Since 1949, four national surveys of TCM resources have been conducted. The fourth survey incorporated an investigation into traditional knowledge related to TCM resources, including the traditional medicinal knowledge of Chinese ethnic minorities, with the goal of systematically exploring, preserving, and inheriting this knowledge. This manuscript provides an overview of the basic findings from the first three national surveys of TCM resources, while also clarifying the concepts, categories, forms, carriers, and acquisition pathways of traditional knowledge related to TCM resources. A preliminary summary of the findings from traditional knowledge investigations reported in current literature is also presented. Based on the fourth survey, this manuscript emphasizes the urgency of developing public medical knowledge through empirically-based investigations, the excavation, and compilation of traditional knowledge. It also outlines the potential for conducting "precise" investigations based on first-hand data obtained from the survey, as well as facilitating the discovery and evaluation of new medicines using traditional knowledge related to ethnic minority medicinal practices. This manuscript is expected to provide valuable insights for promoting the health and industrial development of ethnic minority populations in the post-"survey" phase.
Humans ; Medicine, Chinese Traditional ; China/ethnology* ; Minority Groups ; Ethnicity ; Drugs, Chinese Herbal/therapeutic use* ; Health Knowledge, Attitudes, Practice/ethnology* ; Surveys and Questionnaires

The combination of Aidi Injection(ADI) and doxorubicin(DOX) is a common strategy in the treatment of cancer, which can achieve synergistic anti-tumor effects while attenuating the cardiotoxicity caused by DOX. This study aims to investigate the mechanism of ADI in attenuating DOX-induced cardiotoxicity by multi-omics. DOX was used to induce cardiotoxicity in mice, and the cardioprotective effects of ADI were evaluated based on biochemical indicators and pathological changes. Based on the results, transcriptomics, proteomics, and metabolomics were employed to analyze the changes of endogenous substances in different physiological states. Furthermore, data from multiple omics were integrated to screen key regulatory pathways by which ADI attenuated DOX-induced cardiotoxicity, and important target proteins were selected for measurement by ELISA kits and immunohistochemical analysis. The results showed that ADI significantly reduced the levels of cardiac troponin T(cTnT) and N-terminal pro-B-type natriuretic peptide(NT-proBNP) and effectively ameliorated myocardial fibrosis and intracellular vacuolization, indicating that ADI showed therapeutic effect on DOX-induced cardiotoxicity. The transcriptomics analysis screened out a total of 400 differentially expressed genes(DEGs), which were mainly enriched in inflammatory response, oxidative stress, and myocardial fibrosis. After proteomics analysis, 70 differentially expressed proteins were selected, which were mainly enriched in the inflammatory response, cardiac function, and energy metabolism. A total of 51 differentially expressed metabolites were screened by the metabolomics analysis, and they were mainly enriched in multiple signaling pathways, including the inflammatory response, lipid metabolism, and energy metabolism. The integrated data of multiple omics showed that linoleic acid metabolism, arachidonic acid metabolism, and glycerophosphate metabolism pathways played an important role in DOX-induced cardiotoxicity, and ADI may exert therapeutic effects by modulating these pathways. Target validation experiments suggested that ADI significantly regulated abnormal protein levels of cyclooxygenase-1(COX-1), cyclooxygenase-2(COX-2), prostaglandin H2(PGH2), and prostaglandin D2(PGD2) in the model group. In conclusion, ADI may attenuate DOX-induced cardiotoxicity by regulating linoleic acid metabolism, arachidonic acid metabolism, and glycerophosphate metabolism, thus alleviating inflammation of the body.
Doxorubicin/toxicity* ; Animals ; Mice ; Cardiotoxicity/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Proteomics ; Metabolomics ; Injections ; Humans ; Multiomics