BACKGROUND:The imbalance between bone resorption and bone formation in microgravity environments leads to significant bone loss in astronauts.Current research indicates that bone loss under microgravity conditions is the result of the combined effects of various cells,tissues,and systems. OBJECTIVE:To review different biological effects of microgravity on various cells,tissues,or systems,and summarize the mechanisms by which microgravity leads to the development of osteoporosis. METHODS:Databases such as PubMed,Web of Science,and the Cochrane Database were searched for relevant literature from 2000 to 2023.The inclusion criteria were all articles related to tissue engineering studies and basic research on osteoporosis caused by microgravity.Ultimately,85 articles were included for review. RESULTS AND CONCLUSION:(1)In microgravity environment,bone marrow mesenchymal stem cells tend to differentiate more into adipocytes rather than osteoblasts,and hematopoietic stem cells in this environment are more inclined to differentiate into osteoclasts,reducing differentiation into the erythroid lineage.At the same time,microgravity inhibits the proliferation and differentiation of osteoblasts,promotes apoptosis of osteoblasts,alters cell morphology,and reduces the mineralization capacity of osteoblasts.Microgravity significantly increases the number and activity of osteoclasts.Microgravity also hinders the differentiation of osteoblasts into osteocytes and promotes the apoptosis of osteocytes.(2)In a microgravity environment,the body experiences changes such as skeletal muscle atrophy,microvascular remodeling,bone microcirculation disorders,and endocrine disruption.These changes lead to mechanical unloading in the bone microenvironment,insufficient blood perfusion,and calcium cycle disorders,which significantly impact the development of osteoporosis.(3)At present,the mechanism by which microgravity causes osteoporosis is relatively complex.A deeper study of these physiological mechanisms is crucial to ensuring the health of astronauts during long-term space missions,and provides a theoretical basis for the prevention and treatment of osteoporosis.

Nanoparticle delivery systems have good application prospects in the field of precision therapy, but the preparation process of nanomaterial has problems such as short in vivo circulation time, easy recognition, and clearance by the immune system in the body. In recent years, biomimetic nanoparticle delivery systems mediated by natural cell membranes have become a research hotspot to address these issues. The natural membrane biomimetic nanoparticle delivery system cleverly integrates the advantages of natural biofilm "autologous" and "artificial" functional carriers by using endogenous cell membranes to modify the surface of nanocarriers, endowing them with characteristics such as tumor targeting, low immunogenicity, and long blood circulation. Currently, biomimetic nanoparticle delivery systems have been used in the treatment of malignant tumors, cardiovascular diseases, bacterial infections, and other diseases. This paper analyzes the development status and current research hotspots of natural cell membrane camouflaged biomimetic nanoparticle delivery systems mainly reviews the latest research progress of red blood cell membrane camouflaged biomimetic nanoparticle delivery systems in the field of disease treatment in recent years. It focuses on exploring the advantages, future development prospects, and limitations of biomimetic nanoparticle delivery systems based on red blood cell membrane camouflage in improving drug delivery, to provide a reference for the in-depth research and development of this system.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

First recorded in an official medical book from the Northern Song Dynasty called Taiping Huimin Heji Ju Fang （Prescriptions of the Bureau of Taiping People's Welfare Pharmacy）， Xiaoyaosan has been developed and refined over generations and is preserved to this day. It specializes in soothing the liver，resolving stagnation，fortifying the spleen，and nourishing blood. In this study，ancient traditional Chinese medicine （TCM） books and contemporary studies were reviewed to obtain information on Xiaoyaosan using bibliometrics，including its historical development，dosage，origin，processing methods，decoction dosage，and ancient and modern indications. Furthermore，a question regarding the presence of Zingiberis Rhizoma Recens and Menthae Haplocalycis Herba in Xiaoyaosan was investigated，and a table of key information on Xiaoyaosan was compiled，providing references for developing Xiaoyaosan preparations. According to the weight and measurement system of the Song dynasty，the contemporary equivalent formulation of the decocted Xiaoyaosan consists of 20.65 g of Glycyrrhizae Radix et Rhizoma and 41.3 g of Angelica Sinensis Radix，Poria，Paeoniae Radix Alba，Atractylodis Macrocephalae Rhizoma，and Bupleuri Radix. The formulation is processed to obtain a mixed powder with a particle size of 10 mesh. For each dose，8.25 g of the mixed powder is combined with 1 g of unprocessed Zingiberis Rhizoma Recens and 0.62 g of Menthae Haplocalycis Herba in 300 mL of water. The mixture is decocted until the volume reaches 210 mL，and the residue is then removed，with no specific timing required for administration. After the processing，each dose consists of approximately 0.75 g of Glycyrrhizae Radix et Rhizoma and 1.50 g of Radix Angelica Sinensis，Poria，Paeoniae Radix Alba，Atractylodis Macrocephalae Rhizoma，and Bupleuri Radix. Ancient medical literature shows that Xiaoyaosan primarily treats blood deficiency and overstrain，specifically for symptoms including heat caused by blood deficiency and fatigue，irregular menstruation，headache，eye soreness，pain in the ribs and limbs，and emaciation and bone steaming. In the Qing Dynasty，ZHANG Lu clearly proposed the pathogenesis of liver depression，and since then，the use of Xiaoyaosan in treating various syndromes associated with liver depression has been highly praised by physicians in the Qing dynasty and modern times. Xiaoyaosan has a wide application in modern clinical practices，involving digestive diseases，gynecological diseases，psychological diseases，nervous system diseases，and otorhinolaryngologic diseases. Moreover，it is most commonly used to treat depression and other diseases complicated with depression，hyperplasia of the mammary gland，etc. The key information on Xiaoyaosan and its clinical applications in ancient and modern times investigated in the study could serve as a scientific reference for in-depth research and extended clinical applications of the prescription.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.