Reduced bone mineral density (BMD) is associated with an altered microbiota in senile osteoporosis. However, the relationship among gut microbiota, BMD and bone metabolic indexes remains unknown in postmenopausal osteoporosis. In this study, fecal microbiota profiles for 106 postmenopausal individuals with osteopenia (n=33) or osteoporosis (n=42) or with normal BMD (n=31) were determined. An integrated 16S rRNA gene sequencing and LC-MS-based metabolomics approach was applied to explore the association of estrogen-reduced osteoporosis with the gut microbiota and fecal metabolic phenotype. Adjustments were made using several statistical models for potential confounding variables identified from the literature. The results demonstrated decreased bacterial richness and diversity in postmenopausal osteoporosis. Additionally, showed significant differences in abundance levels among phyla and genera in the gut microbial community were found. Moreover, postmenopausal osteopenia-enriched N-acetylmannosamine correlated negatively with BMD, and distinguishing metabolites were closely associated with gut bacterial variation. Both serum procollagen type I N propeptide (P1NP) and C-terminal telopeptide of type I collagen (CTX-1) correlated positively with osteopenia-enriched Allisonella, Klebsiella and Megasphaera. However, we did not find a significant correlation between bacterial diversity and estrogen. These observations will lead to a better understanding of the relationship between bone homeostasis and the microbiota in postmenopausal osteoporosis.

Chronic insomnia without intervention will do harm to people’s physical and psychological health as well as the quality of life. While ensuring efficacy, traditional Chinese medicine therapy, such as acupuncture, overcomes the side effects of drugs. However, the molecular mechanism of traditional medicine is unclear and it encounters many obstacles in repetitiveness and popularization. On the other side, the placebo effects also need to be eliminated during the intervention. In this study, a number of indicators such as duration of sleep latency, serum markers, pineal gland immunohistochemistry, and gut microbes were detected in the PCPA‐induced insomnia mice to compare the effects between acupuncture and hypnotic drug treatments. Although the food intake and weight were not changed, the results show that serum maker and gut microbiota alterations were mediated by concurrent changes in sleep disorder induced by PCPA in mice. Compared with the PCPA‐induced insomnia group, dopamine, 5‐hydroxytryptamine, and norepinephrine were reduced in serum, and the melatonin was increased in the pineal gland of the acupuncture group as well as zopiclone drug group. Moreover, the analysis results from 16S tag sequencing of the gut microbiome bacterial rRNA hypervariable region show the same improvement effects between the two medical intervention groups. A co‐occurrence network analysis showed that blank and acupuncture networks exhibited higher similarity than sham and zopiclone networks and the sham network possessed the highest complexity of microbial communities. Taken together, the gut microbiome will likely be a new target for improving sleep disorders, and taking into account the side effects of hypnotic drugs, nonpharmacological interventions such as acupuncture may be an effective means and have greater clinical benefits.

To systematically assess the association between osteoporosis and cognitive impairment, and to provide new light on the prevention of cognitive impairment in patients with osteoporosis. A comprehensive research of Embase, Cochrane Library, PubMed, Web of Science, CNKI, Wangfang Data and VIP was performed from inception to January 2022, using the search term 'osteoporosis' and 'cognitive impairment'. Literature screening, data extraction and quality evaluation were conducted by two reviewers independently, and meta-analysis was performed by RevMan 5.4 software. A total of 8 studies (136222 participants) were included. Meta-analysis showed that patients with osteoporosis had an increased risk of cognitive impairment [OR=2.01, 95% CI(1.63-2.48), P<0.01]. This initial meta-analysis had significant heterogeneity, and subgroup analysis suggested that potential heterogeneity in different study types, age and outcome indicators. Patients with osteoporosis are at increased risk of cognitive impairment, and osteoporosis intervention could prevent or delay the onset of cognitive impairment for those at risk.

Background: Women suffer from various distress and disturbances after menopause, including osteoporosis, a risk factor associated with multiple diseases. Altered gut microbiota has been implicated in postmenopausal osteoporosis. In this study, to understand gut microbiota signatures and fecal metabolite changes in postmenopausal women with osteoporosis, 108 postmenopausal women were recruited for intestinal microbiota and fecal metabolite detection. Among these participants, 98 patients, who met the inclusion criteria, were divided into postmenopausal osteoporosis (PMO) and non-postmenopausal osteoporosis (non-PMO) groups based on bone mineral density (BMD). The compositions of gut bacteria and fungi were examined by 16 S rRNA gene sequencing and ITS sequencing, respectively. Meanwhile, fecal metabolites were analyzed using liquid chromatography coupled with mass spectrometry (LC-MS). Results: We found that bacterial α-diversity and β-diversity were significantly altered in PMO compared to non-PMO patients. Interestingly, fungi composition showed larger changes, and the differences in β-diversity were more significant between PMO and non-PMO patients. Metabolomics analysis revealed that fecal metabolites, such as levulinic acid, N-Acetylneuraminic acid, and the corresponding signaling pathways were also changed significantly, especially in the alpha-Linolenic acid metabolism and selenocompound metabolism. The screened differential bacteria, fungi, and metabolites closely correlated with clinical findings between these two groups, for example, the bacterial genus, Fusobacterium, the fungal genus, Devriesia, and the metabolite, L-pipecolic acid, were significantly associated with BMD. Conclusions: Our findings indicated that there were remarkable changes in gut bacteria, fungi, and fecal metabolites in postmenopausal women, and such changes were notably correlated with patients’ BMD ​​and clinical findings. These correlations provide novel insights into the mechanism of PMO development, potential early diagnostic indicators, and new therapeutic approaches to improve bone health in postmenopausal women.

Dachengqi decoction (DCQD) is a classical prescription in traditional Chinese medicine (TCM). It has been used to treat abdominal pain and acute pancreatitis (AP) for thousands of years in China. To predict the active components and signaling pathway of DCQD and to further explore the potential molecular mechanism of DCQD as a treatment of AP using network pharmacology. Network pharmacology and bioinformatics were used to determine the active components of DCQD and its potential target in the treatment of AP. The AP model was induced by Cerulein (Cer) combined with lipopolysaccharide (LPS). The pharmacodynamic basis of DCQD in the treatment of AP was evaluated in vitro and in vivo and Western blot analysis and immunofluorescence were used to determine the molecular mechanism of DCQD. Screening using relevant databases and topological analysis revealed 71 active components and 535 potential target proteins in DCQD. In addition, 445 differential genes for AP were also screened. Pathway enrichment analysis, PPI network analysis and transcription factor prediction showed that DCQD played an important role in the PI3K-Akt signal pathway, and 17 DCQD monomers were found in this signal pathway. In the AP model, DCQD promoted pancreatic acinar cell apoptosis, reduction in inflammation, and regulation of the PI3K-AKT signaling pathway. DCQD inhibited the expression of p-AKT and p- NF-kB proteins in pancreatic tissue of the AP model both in vitro and in vivo. This study reveals that 17 active components of DCQD improve AP by regulating the PI3K/AKT signaling pathway and promoting apoptosis and suppressing pathological injury and inflammation.

Background: Flat foot deformity is a prevalent and challenging condition often leading to various clinical complications. Accurate identification of abnormal foot types is essential for appropriate interventions.Method: A dataset consisting of 1573 plantar pressure images from 125 individuals was collected. The performance of the You Only Look Once v5 (YOLO-v5) model, improved YOLO-v5 model, and multi-label classification model was evaluated for foot type identification using the collected images. A new dataset was also collected to verify and compare the models.Results: The multi-label classification algorithm based on ResNet-50 outperformed other algorithms. The improved YOLO-v5 model with Squeeze-and-Excitation (SE), the improved YOLO-v5 model with Convolutional Block Attention Module (CBAM), and the multilabel classification model based on ResNet-50 achieved an accuracy of 0.652, 0.717, and 0.826, respectively, which is significantly higher than those obtained using the ordinary plantar-pressure system and the standard YOLO-v5 model.Conclusion: These results indicate that the proposed DL-based multilabel classification model based on ResNet-50 is superior in flat foot type detection and can be used to evaluate the clinical rehabilitation status of patients with abnormal foot types and various foot pathologies when more data on patients with various diseases are available for training.