Heilongjiang University of Chinese Medicine

Sexual hormone binding globulin (SHBG) is associated with the endocrine and reproductive systems. We aimed to investigate the role of SHBG in the reproductive process. Therefore, we conducted a secondary analysis of the PCOSAct (Polycystic Ovary Syndrome and Acupuncture Clinical Trial) study, which involved 21 sites in China and a total of 1000 women with PCOS. Out of these, 954 women with SHBG were included in the analysis. Through multivariate analysis of ovulation predictors, we found that age, BMI, estradiol, testosterone, and SHBG all showed a positive predictive value for ovulation (p = 0.0211, 0.0011, 0.0211, 0.0029, 0.0434, respectively). However, the LH to FSH ratio had a negative predictive value (p = 0.0539). Higher quartiles of SHBG were associated with a higher rate of ovulation, and per quartile increased was statistically significant (HR = 1.138, 95%CI [1.054,1.229]). The association remained significant even after adjusting for testosterone (HR = 1.263, 95%CI [1.059, 1.507]). On the other hand, quartiles of testosterone and estradiol did not exhibit any significant tendency toward ovulation. SHBG demonstrated predictive ability for ovulation, conception, pregnancy, and live birth (p < 0.05), and this correlation remained significant after adjusting intervention. Kaplan-Meier curves illustrated that increased levels of SHBG were a factor in high rates of ovulation, conception, and pregnancy. In comparison to other sexual hormones, a higher baseline level of SHBG was related to increased ovulation.

To investigate the effect and mechanism of Huogu injection (HG) on steroid-induced osteonecrosis of the femoral head (SONFH), we established a SONFH model in rabbits using horse serum and dexamethasone (DEX) and applied HG locally at the hip joint. We evaluated the therapeutic efficacy at 4 weeks using scanning electron microscopy (SEM), micro-CT, and qualitative histology including H&E, Masson’s trichrome, ALP, and TUNEL staining. In vitro, we induced osteogenic differentiation of bone marrow stromal cells (BMSCs) and performed analysis on days 14 and 21 of cell differentiation. The findings, in vivo, including SEM, micro-CT, and H&E staining, showed that HG significantly maintained bone quality and trabecular number. ALP staining indicated that HG promoted the proliferation of bone cells. Moreover, the results of Masson’s trichrome staining demonstrated the essential role of HG in collagen synthesis. Additionally, TUNEL staining revealed that HG reduced apoptosis. ALP and ARS staining in vitro confirmed that HG enhanced osteogenic differentiation and mineralization, consistent with the WB and qRT-PCR analysis. Furthermore, Annexin V-FITC/PI staining verified that HG inhibited osteoblast apoptosis, in agreement with the WB and qRT-PCR analyses. Furthermore, combined with the UPLC analysis, we found that naringin enhanced the osteogenic differentiation and accelerated the deposition of calcium phosphate. Salvianolic acid B protected osteoblasts derived from BMSCs against GCs-mediated apoptosis. Thus, this study not only reveals the mechanism of HG in promoting osteogenesis and anti-apoptosis of osteoblasts but also identifies the active-related components in HG, by which we provide the evidence for the application of HG in SONFH.

Fragile X-related protein 1 (FXR1) is an RNA-binding protein that belongs to the fragile X-related (FXR) family. Studies have shown that FXR1 plays an important role in cancer cell proliferation, invasion and migration and is differentially expressed in cancers. This study aimed to gain a comprehensive and systematic understanding of the analysis of FXR1’s role in cancers. This would lead to a better understanding of how it contributes to the development and progression of various malignancies. this study conducted through The Cancer Genome Atlas (TCGA), GTEx, cBioPortal, TISIDB, GEPIA2 and HPA databases to investigated FXR1’s role in cancers. For data analysis, various software platforms and web platforms were used, such as R, Cytoscape, hiplot plateform. A significant difference in FXR1 expression was observed across molecular and immune subtypes and across types of cancer. FXR1 expression correlates with disease-specific survival (DSS), and overall survival (OS) in several cancer pathways, further in progression-free interval (PFI) in most cancers. Additionally, FXR1 showed a correlation with genetic markers of immunomodulators in different cancer types. Our study provides insights into the role of FXR1 in promoting, inhibiting, and treating diverse cancers. FXR1 has the potential to serve as a diagnostic and prognostic biomarker for cancer, with therapeutic value in immune-based, targeted, or cytotoxic treatments. Further clinical validation and exploration of FXR1 in cancer treatment is necessary.

Rosmarinic acid (RA) is a natural phenolic compound extracted from the Labiatae family and is a natural antioxidant. In this study, walnut oil added with RA was treated with different ultraviolet radiations, and stabilization effects in terms of the same conditions (0.2 mg/g) were compared with synthetic antioxidant (BHT). In order to compare the effectiveness of three UV treatments, different lab tests were conducted, namely, the acid value, peroxide value, iodine value, anisidine value, DPPH free radical scavenging rate, and malondialdehyde content. The enhanced UV-A, UV-B, and UV-C radiation intensities have increased the oxidation stability of RA-added walnut oil, of which UV-B has the greatest influence on the oxidative stability of walnut oil. When both RA and BHT were added at 0.2 mg/g, the antioxidant effect of RA is superior to the general antioxidant BHT.

Depression is a prevalent occurrence among Alzheimer’s disease (AD) patients, yet its underlying mechanism remains unclear. Recent investigations have revealed that several pathophysiological changes associated with Alzheimer’s disease can lead to mood disorders. These alterations include irregularities in monoamine neurotransmitters, disruptions in glutamatergic synaptic transmission, neuro-inflammation, dysfunction within the hypothalamic-pituitary-adrenocortical (HPA) axis, diminished levels of brain-derived neurotrophic factor (BDNF), and hippocampal atrophy. This review consolidates research findings from pertinent fields to elucidate the mechanisms underlying depression in Alzheimer’s disease, aiming to provide valuable insights for the study of its mechanisms and clinical treatment.

Psoriasis and chronic ulcers not only significantly impair quality of life but also pose a challenge in dermatological treatment. This study aimed to identify new therapeutic targets and biomarkers for psoriasis and chronic ulcers by comparing their gene expression profiles. The gene expression profiles of psoriatic, wound and chronic ulcer patients, as well as healthy controls, were determined via RNA extraction and next‐generation sequencing of biopsies. In order to identify biomarkers, functional enrichment, differential expression analysis and machine learning algorithms were implemented. It is worth mentioning that the genes IL17A, TNF, KRT16, MMP9, and CD44 exhibited substantial correlations with the pathogenesis of the conditions being studied. As evidenced by their AUC‐ROC values approaching 0.90, machine learning models accurately identified these biomarkers. The differential gene expression was consequently validated via qRT‐PCR, which highlighted the increased expression of matrix remodelling enzymes and inflammatory cytokines. Additionally, genes essential for maintaining epidermis integrity and facilitating wound healing exhibited downregulation. These insights into the molecular mechanisms of psoriasis and chronic ulcers pave the way for the development of targeted therapies, offering hope for improved treatment strategies.

Background Studies have demonstrated that copper metabolism related genes (CMRGs) are tightly associated with a high risk of developing osteoarthritis (OA). However, the details of their regulation are not well understood. Hence, this research intends to explore the mechanism of CMRGs in OA and to provide new clues for the treatment of OA. Methods The GSE48556 and GSE63359 datasets were sourced from the Gene Expression Omnibus (GEO) database. The 133 CMRGs were collected from the literature. Differentially expressed genes (DEGs) between case and control cohorts in the GSE48556 dataset were identified through differentially expressed analysis. Moreover, differentially expressed-CMRGs (DE-CMRGs) were gained via overlapping DEGs and CMRGs. Then, we performed gene enrichment analysis for the DE-CMRGs to identify their regulatory functions. The DE-CMRGs with consistent and markedly divergent expression trends in both datasets were considered as biomarkers. Subsequently, we verified the results using real-time reverse transcription-PCR (qRT-PCR) in clinical blood specimen. Receiver Operating Characteristic (ROC) curves were mapped to assess the predictive accuracy. Finally, Gene Set Enrichment Analysis (GSEA), the Gene-Gene Interaction (GGI) network, immune-related function, and drug prediction were executed, then correlations between biomarkers as well as between biomarkers and immune-related pathways or cells were determined. Results Totally, 4,325 DEGs and 32 DE-CMRGs were selected in GSE48556 dataset, and functional enrichment analysis showed that they were involved in ‘response to copper ion’ and ‘copper ion binding’, which were consistent with the path of our research. KEGG, GSEA and GGI outcomes indicated that there were mainly involved in the pathways of ‘olfactort transduction’, ‘iron ion transport’, ‘ferroptosis’, ‘platinum drug resistance’ and so on. Through simultaneous screening of both datasets, four biomarkers (APP, CUTC, TFRC, and HEPH) were discovered. Then, all of area under curves (AUC) values of the ROC curves exhibited strong prediction accuracy. APP, CUTC and TFRC plasma levels were significantly higher in OA patients compared to controls (p < 0.05). However, the HEPH plasma level of OA patients was significantly decreased compared to controls (P < 0.01). According to correlation analysis, HEPH was positively connected with Th1 cells and the CCR immune path, and negatively correlated with APP, Th2 cells, and the check-point immune pathway. There were 35 drugs predicted by 4 biomarkers such as L-methionine (R)-S-oxide, Mercuribenzoic Acid and Copper. The expression levels of APP, CUTC, and TFRC genes in plasma of OA patients were dramatically lowered (P < 0.05) compared to the control, while the expression levels of HEPH genes were significantly elevated (P < 0.01). Conclusion Four biomakers (APP, CUTC, TFRC, and HEPH) were identified as CM biomarkers in OA, which offered a fresh standpoint to probe the connection between CMRGs and OA.

Breast cancer is a prevalent and severe form of cancer that affects women all over the world. The incidence and mortality of breast cancer continue to rise due to factors such as population growth and the aging of the population. There is a growing area of research focused on a cell death mechanism known as PANoptosis. This mechanism is primarily regulated by the PANoptosome complex and displays important characteristics of cell death, including pyroptosis, apoptosis, and/or necroptosis, without being strictly defined by the cell death pathway. PANoptosis acts as a defensive response to external stimuli and pathogens, contributing to the maintenance of cellular homeostasis and overall stability. Increasing evidence suggests that programmed cell death (PCD) plays an important role in the development of breast cancer, and PANoptosis, as a novel form of PCD, may be a crucial factor in the development of breast cancer, potentially leading to the identification of new therapeutic strategies. Therefore, the concept of PANoptosis not only deepens our understanding of PCD, but also opens up new avenues for treating malignant diseases, including breast cancer. This review aims to provide an overview of the definition of PANoptosis, systematically explore the interplay between PANoptosis and various forms of PCD, and discuss its implications for breast cancer. Additionally, it delves into the current progress and future directions of PANoptosis research in the context of breast cancer, establishing a theoretical foundation for the development of molecular targets within critical signaling pathways related to PANoptosis, as well as multi-target combination therapy approaches, with the goal of inducing PANoptosis as part of breast cancer treatment.

Endometriosis is a common disease of reproductive-age women and an important cause of dysmenorrhea and infertility. Information on endometriosis is complex and there is a lack of summarization of available results. The study aims to evaluate the overall distribution of publications related to endometriosis to provide a foundation for further research. The Web of Science Core Collection was searched for articles published in the field of endometriosis. Our survey revealed the structure, hotspots, and development trends of endometriosis-related research and publications.

Pediatric asthma is a complex disease with a multifactorial etiology. The identification of biomarkers associated with pediatric asthma can provide insights into the pathogenesis of the disease and aid in the development of novel diagnostic and therapeutic strategies. This study aimed to identify potential biomarkers for pediatric asthma using Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning algorithms. We obtained gene expression data from publicly available databases and performed WGCNA to identify gene co-expression modules associated with pediatric asthma. We then used machine learning algorithms, including random forest, lasso regression algorithm, and support vector machine-recursive feature elimination, to classify asthma cases and controls based on the identified gene modules. We also performed functional enrichment analyses to investigate the biological functions of the identified genes.We detected 24,544 genes exhibiting differential expression between controlled and uncontrolled genes from the GSE135192 dataset. In the combined WCGNA analysis, a total of 104 co-expression genes were screened, both controlled and uncontrolled. After screening, 11 hub genes were identified. They were AK2, PDK4, PER3, GZMH, NUMBL, NRL, SCO2, CREBZF, LARP1B, RXFP1, and VDAC3P1. The areas under their receiver operating characteristic curve were above 0.78. Our study identified potential biomarkers for pediatric asthma using WGCNA and machine learning algorithms. Our findings suggest that 11 hub genes could be used as novel diagnostic markers and treatment targets for pediatric asthma. These findings provide new insights into the pathogenesis of pediatric asthma and may aid in the development of novel diagnostic and therapeutic strategies.

Objective To examine the effect of low-frequency acupoint electrical stimulation (LFES) on the surface electromyographic (sEMG) signals of the thumb-to-finger movement muscles in stroke patients, and to evaluate the clinical efficacy of LFES on hand function recovery after stroke. Methods Sixty patients who met the inclusion criteria were randomly assigned to a LFES group or an electroacupuncture (EA) group, with 30 patients in each group. Both groups received conventional treatment, and the EA group was treated with acupoints from the book of Acupuncture and Moxibustion, while the LFES group was treated with acupoints from a previous study. The sEMG characteristic values (maximum value and RMS), Chinese Stroke Clinical Neurological Deficit Scale (CSS), Brunnstrom Motor Function Evaluation, Modified Ashworth Scale (MAS), Lindmark Hand Function Score and Lovett Muscle Strength Classification were measured before and after treatment. Results After treatment, both groups showed improvement in sEMG characteristic values, Brunnstrom motor function score, Lindmark hand function score, and Lovett muscle strength classification compared with before treatment, and the improvement in the LFES group was significantly better than that in the EA group (P < .05). The CSS score and MAS classification of both groups decreased compared with before treatment, and the decrease in the LFES group was significantly better than that in the EA group (P < .05). The total effective rate of the LFES group was 92.86%, and that of the EA group was 79.31%. The difference between the 2 groups was statistically significant (P < .05). Conclusion Both LFES and EA were effective in restoring thumb-to-finger movement function after stroke, as evidenced by the increased maximum value and root mean square values of the first dorsal interosseous muscle and the extensor pollicis brevis muscle, the decreased CSS score, the increased Brunnstrom motor function score, the decreased MAS classification, the increased Lindmark hand function score, and the increased Lovett muscle strength classification. However, LFES showed more obvious improvement and better efficacy than EA, which is worthy of clinical promotion.

Background The aim of this systematic review is to evaluate the effectiveness of combining acupuncture with speech rehabilitation training, compared to acupuncture alone or speech rehabilitation training alone, in the treatment of post-stroke aphasia. Methods To gather data for this study, we searched 6 databases: PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, WanFang Data, and Chongqing VIP Database. We included clinical randomized controlled trials on acupuncture combined with rehabilitation training for post-stroke aphasia published between January 1, 2011 and October 8, 2023. Two researchers independently screened the literature, evaluated its quality, and extracted the data using Stata 15.1 SE and RevMan 5.4 software. We conducted a meta-analysis using the random effects model, and expressed dichotomous variables as odds ratios (OR) with 95% confidence intervals (CIs) and continuous variables as weighted mean differences (WMD) with 95% confidence intervals. Specifically, the odds of improvement were significantly higher in the combination group (OR = 3.89, 95% CI = [2.62, 5.78]). Improvements were also seen in several language functions, including expression (WMD = 5.14, 95% CI = [3.87, 6.41]), understanding (WMD = 9.16, 95% CI = [5.20, 13.12]), retelling (WMD = 11.35, 95% CI = [8.70, 14.00]), naming (WMD = 11.36, 95% CI = [8.12, 14.61] ), reading (WMD = 9.20, 95% CI = [4.87, 13.52]), writing (WMD = 5.65, 95% CI = [3.04, 8.26]), and reading aloud (WMD = 7.45, 95% CI = [3.12, 11.78]). Scores on the Chinese Aphasia Complete Test Scale, Western Aphasia Complete Test Scale, and China Rehabilitation Research Center Aphasia Check Scale were also significantly higher in the combination group, with improvements of 7.89, 9.89, and 9.27, respectively. Results A total of 16 clinical randomized controlled trials, including 1258 patients, were included in this meta-analysis. The results showed that compared to simple rehabilitation training or acupuncture treatment alone, the combination of acupuncture and language rehabilitation training was more effective in improving clinical outcomes for patients with post-stroke aphasia. Conclusions The results of this meta-analysis indicate that acupuncture combined with language rehabilitation training can effectively improve the language function of post-stroke aphasia patients and increase clinical effectiveness. However, further research is needed to confirm these findings and provide a more reliable evidence-based basis for clinical practice. In particular, additional studies with large sample sizes, high quality, and more specific and standardized outcome measures are needed to strengthen the evidence. The limited quantity and quality of the current studies may affect the generalizability of the results.

With the continuous expansion of brain-computer communication, the precise identification of brain signals has become an essential task for brain-computer equipment. However, existing classification methods are primarily concentrated on the extraction features of brain signals and obtain unacceptable performance when directly used the model to a new brain signals data, which is caused by the different people has extraordinary brain signals. In this work, we utilize the deep learning methods not only extract the features of brain signals but also learn the order information of brain signals, which can satisfy the universal brain signals. Indeed, we utilize the classification features dimension distance loss function to optimize the proposed model and enhance the classification accuracy and we compare our model with existing classification methods to evaluate proposed model. From our extensive experimental results and analysis, we can conclude that our model can achieve the classification of brain signals with the reasonable accuracy and acceptable costs.

Objective Mycoplasma pneumoniae pneumonia (MPP) is a common respiratory tract infectious disease in children. The study aimed to elucidate the therapeutic efficacy of aerosolized budesonide and N‐acetylcysteine combination therapy for MP infection in children. Methods One hundred and twenty children with MP infection were included and divided into the control group (received aerosol inhalation of budesonide) and the experimental group (aerosolized budesonide and N‐acetylcysteine). After treatment, the disappearance time of clinical symptoms and efficacy were contrasted between the two groups. Results With the passage of treatment time, the children's cough score of the two groups were gradually reduced. The children in the experimental group got well from the cough faster than the control group, and the difference reached a significant level on the 5th and 7th days. The time required for fever, rale, and cough to disappear in the experimental group was shorter than those in the control group. As the treatment progressed, a gradual decrease in serum interleukin‐6, tumor necrosis factor‐α, and C‐reactive protein values was detected in both groups, and the decrease was more significant in the experimental group. The total effective rate of the experimental group was 98.33%, which surpassed the control group (93.33%). Conclusion Budesonide and N‐acetylcysteine combination therapy in the treatment of MP infection in children has a significant effect, and can quickly relieve the clinical symptoms of children with good safety. It is worthy of widespread clinical use.

Objective This study sought to evaluate and validate a method for chemical composition analysis and content determination of Goupi plaster components, a conventional prescription preparation of traditional Chinese medicine. This is geared toward providing a basis for quality control research and future development of Goupi plaster. Methods UPLC–Q-Exactive-MS was used to qualitatively analyze the chemical components of Goupi plaster from different manufacturers in positive and negative ion modes. UPLC–MS/MS method was used to establish the determination methods for the detection of sinomenine, osthole, and cinnamaldehyde in Goupi plaster from different manufacturers. Results A total of 291 chemical components were identified in Goupi plaster from four manufacturers, including 97 chemical components with known source and pharmacological activity. Further, we determined the contents of sinomenine, osthole, and cinnamaldehyde. Conclusion In summary, the UPLC–Q-Exactive-MS method was used to analyze the chemical components of Goupi plaster from different manufacturers. We established the UPLC–MS/MS method to determine the contents of sinomenine, osthole, and cinnamaldehyde in Goupi plaster from different manufacturers. The findings indicated that the method was comprehensive, rapid, and accurate, preliminarily revealing the material basis of Goupi plaster and providing a reference for follow-up development of Goupi plaster.

This study aimed to investigate the angelica sinensis - radix rehmanniae (AR) role in polycystic ovary syndrome (PCOS), employing network pharmacology and molecular docking techniques for active ingredient, targets, and pathway prediction. AR active components were obtained through TCMSP platform and literature search. The related targets of AR and PCOS were obtained through the disease and Swiss Target Prediction databases. An “active ingredient-target” network map was constructed using Cytoscape software, and gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis was conducted through Hiplot. Finally, Auto Dock Tools software was used to conduct molecular docking between active ingredients and core targets. The main bioactive ingredients of AR in the treatment of PCOS are acteoside, baicalin, caffeic acid, cistanoside F, geniposide, etc. These ingredients involve 10 core targets, such as SRC, HSP90AA1, STAT3, MAPK1, and JUN. The effect of AR on anti-PCOS mainly involves the AGE-RAGE signaling pathway, Relaxin signaling pathway, TNF signaling pathway, and ErbB signaling pathway. Molecular docking results showed that the main active components and key targets of AR could be stably combined. AR can improve hyperandrogen status, regulate glucose homeostasis, and correct lipid metabolism and other physiological processes through multi-component, multi-target, and multi-pathway. Thus, it could play a significant role in PCOS treatment. The results of our study provide a scientific foundation for basic research and clinical applications of AR for the treatment of PCOS.

To explore the mechanism of Zhenwu Decoction (ZWD) in the treatment of heart failure (HF) by network pharmacology analysis, so as to provide a basis for the innovation and application of drugs. The effective components and targets of 5 Chinese herbal medicines in ZWD were retrieved by TCM Pharmacology Database and Analysis Platform (TCMSP).Gene card, OMIM and TTD databases were used to obtain the disease targets of HF, and the intersection with the targets of ZWD was obtained. We used Cytoscape3.9.1 software to construct a drug-active component-disease-target interaction network for ZWD treatment of HF, and performed protein-protein interaction (PPI) network and topology analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed. Fifty-nine effective components and 229 targets of ZWD were screened. Among them, ZWD for HF has 27 active components and 38 common targets, and the core targets of PPI are IL-6, ATK1 and TNF. Pathway enrichment analysis included lipid and atherosclerotic and TNF signaling pathways. This study preliminarily clarified the main active components, targets and related pathways of ZWD in the treatment of HF, and laid a foundation for further study of the pharmacological effects of ZWD.

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder. With the aging population and the continuous development of risk factors associated with AD, it will impose a significant burden on individuals, families, and society. Currently, commonly used therapeutic drugs such as Cholinesterase inhibitors, N-methyl-D-aspartate antagonists, and multiple AD pathology removal drugs have been shown to have beneficial effects on certain pathological conditions of AD. However, their clinical efficacy is minimal and they are associated with certain adverse reactions. Furthermore, the underlying pathological mechanism of AD remains unclear, posing a challenge for drug development. In contrast, natural plant molecules, widely available, offer multiple targeting pathways and demonstrate inherent advantages in modifying the typical pathologic features of AD by influencing the blood–brain barrier (BBB). We provide a comprehensive review of recent in vivo and in vitro studies on natural plant molecules that impact the BBB in the treatment of AD. Additionally, we analyze their specific mechanisms to offer novel insights for the development of safe and effective targeted drugs as well as guidance for experimental research and the clinical application of drugs for the prevention and treatment of AD.

Vascular cognitive impairment not dementia (VCIND) is one of the three subtypes of vascular cognitive impairment (VCI), with cognitive dysfunction and symptoms ranging between normal cognitive function and vascular dementia. The specific mechanisms underlying VCIND are still not fully understood, and there is a lack of specific diagnostic markers in clinical practice. With the rapid development of magnetic resonance imaging (MRI) technology, structural MRI (sMRI) and functional MRI (fMRI) have become effective methods for exploring the neurobiological mechanisms of VCIND and have made continuous progress. This article provides a comprehensive overview of the research progress in VCIND using multimodal MRI, including sMRI, diffusion tensor imaging, resting-state fMRI, and magnetic resonance spectroscopy. By integrating findings from these multiple modalities, this study presents a novel perspective on the neuropathological mechanisms underlying VCIND. It not only highlights the importance of multimodal MRI in unraveling the complex nature of VCIND but also lays the foundation for future research examining the relationship between brain structure, function, and cognitive impairment in VCIND. These new perspectives and strategies ultimately hold the potential to contribute to the development of more effective diagnostic tools and therapeutic interventions for VCIND.