Recurrent spontaneous abortion （RSA） is a common gynecological disease during pregnancy， clinically characterized by repeated spontaneous abortions， yet its pathological mechanism remains incompletely understood. Traditional Chinese medicine attributes the pathogenesis of RSA to the deficiency of Chong Ren and the lack of fetal solidity. It has amassed experience in treating RSA， with Shoutaiwan being widely utilized for addressing miscarriage symptoms such as habitual abortion due to kidney deficiency， bleeding during pregnancy， and fetal movement. In recent years， there has been a gradual increase in experimental studies on the application of Shoutaiwan in treating RSA and on related experiments. These studies have demonstrated that Shoutaiwan preserves the fetus mainly by modulating hormone balance， alleviating immune inflammation， and enhancing blood coagulation equilibrium during pregnancy. Besides， through the modulation of key signaling pathways such as nuclear factor， erythroid 2 like 2 （Nrf2）/heme oxygenase-1 （HO-1） and Janus kinase 1 （JAK1）/signal transducer and activator of transcription （STAT）， as well as mitogen-activated protein kinase （MAPK）， Shoutaiwan has improved cellular antioxidant capacity， adjusted the phenotype of trophoblast and metaphase cells， and inhibited immune rejection， thus improving the pregnancy success rate. These findings not only elucidate the diverse biological foundations underlying Shoutaiwan's efficacy in treating RSA but also offer a scientific rationale for its clinical application and further mechanism research. Nonetheless， there remains a dearth of systematic reviews on RSA treatment with Shoutaiwan. Therefore， this review summarizes and synthesizes existing research findings to systematically analyze existing literature and studies， delving deeply into the principal pharmacological effects and associated signaling pathways of Shoutaiwan in regulating RSA. It aims to establish crucial reference points for its clinical application in RSA treatment and future experiments and research.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective Zhuanyao decoction is a traditional Chinese herbal compound prescription orignated from Bianzhenglu in Ming Dynasty;Baizhu Zhuanyao decoction(BZZYD),adding spatholobus suberectus,sappanwood,and cyathula root,is intended to enhance the therapeutic effects on the waist and hips.We aimed to investigate the effects of BZZYD on lumbar ligamentum flavum fibrosis and its possible immune regulation mechanism.Methods(i)By using a random number table method,twenty-four male SD rats were divided into the normal,model,chlorophosphate,and BZZYD groups,with six rats per group.The rats in all groups,except for the normal group,were used to establish a rat model of lumbar ligamentum flavum fibrosis using lumbar instability method.The rats in the BZZYD group received Baizhu Zhuanyao decoction through gavage(13.6 g/kg),and the other groups were administered the same amount of saline by gavage once a day for 30 days.The rats in the chlorophosphate group were subcutaneously injected with disodium chlorophosphate liposome(5 g/L,0.5 mL)at the original incision immediately after surgery and at Day 9,18,and 27.After 30 days,the rats were sarcrificed through excessive anesthesia,and the ligamentum flavum was histologically evaluated using HE and Masson staining.The collagen volume fraction(CVF)was calculated.Transforming growth factor-β1(TGF-β1),tumor necrosis factor-α(TNF-α),and interleukin-1β(IL-1β)protein expressions in the ligamentum flavum were detected using immunohistochemical staining.CD163 and TGF-β1 protein expression in M2 macrophages were detected using the immunofluorescence double-labeling method.(ⅱ)M2 macrophage and fibroblast were cultured in the three ways:separately,co-culture,and co-culture of pre-treatment of BZZYD containing serum on M2 macrophage and fibroblast.TGF-β1,TNF-α,and IL-1β mRNA expressions in M2 macrophage and fibroblast were compared using RT-qPCR.Results(ⅰ)Compared with those in the normal group,the ligamentum flavum fibers were dense and twisted,immune cells infiltrated,and the CVF was increased in the model group.TGF-β1,TNF-α,and IL-1β protein expression in the ligamentum flavum tissues of the model group were increased,and TGF-β1 and TNF-α protein expression in the BZZYD group were increased(P<0.05).Compared with that of the model group,extracellular matrix accumulation decreased in the chlorophosphate and BZZYD groups,the CVF was decreased,and TGF-β1,TNF-α,and IL-1β protein expressions in ligamentum flavum tissue were decreased(P<0.05).Compared with that of the chlorophosphate group,extracellular matrix accumulation increased,the CVF was increased,TGF-β1 and IL-1β protein expressions in ligamentum flavum tissue were increased(P<0.05).CD163 and TGF-β1 proteins were not expressed in the normal and chlorophosphate groups.CD163 and TGF-β1 proteins were expressed and co-localized in the model group,and CD163 protein expression was observed in the BZZYD group,however,TGF-β1 expression was low.(ⅱ)The co-culture system increased mRNA expressions of TGF-β1 and IL-1β in M2 macrophages,TNF-α and IL-1β in fibroblasts,compared to the two kinds of cells cultured separately.And after pre-treatment on M2 macrophages,the mRNA expressions all decreased compared co-culture system(P<0.05).Conclusion BZZYD can significantly inhibit lumbar ligamentum flavum fibrosis,reduce TGF-β1 and IL-1β expression in M2 macrophages,affect TNF-α and IL-1β expression in fibroblasts,and inhibit the positive feedback of ligamentum flavum inflammation-fibrosis.

Objective To correctly identify the blood group of ABO and study its molecular biological characteristics.Methods Blood samples from blood donors with discrepancies in forward and reverse typing using the microplate method were subjected to both saline tube agglutination test for serological identification and polymerase chain reaction-sequence specific primers(PCR-SSP)for genotyping.Additionally,direct sequencing of exons 1 to 7 of the ABO gene was performed on some donor samples to analyze their blood phenotype,genotype and gene sequence.Results For 256 samples showing discrepancy between forward and reverse typing in microwell method,119 were identified as normal ABO blood types,90 were weakened ABO antibodies and 47 were ABO subtypes by serology tube test.According to the PCR-SSP genotyping test,233 of 256(91.02%)were consistent with serological phenotype and genotype,17 of 256(6.64%)were inconsistent,and 6 samples can′t read genotype based on the kit result typing table.A total of 17 genotypes were identified in 250 samples as AO1 in 56,AO2 in 58,AA in 50,BO1 in 31,BO2 in 17,BB in 8,O1O1 in 2,O1O2 in 7,AB in 13,AO4 in 1,A205O2 in 1,A205A in 1,A201A in 1,O1O4 in 1,O2O2 in 1,A201B in 1 and A205B in 1.Sequencing of exons 1 to 7 of the ABO gene was carried out in 78 samples,and 29 ABO alleles were detected,seven of which were common alleles(?A101,?A102,?A104,?B101,?O01,?O02,?O04),22 of which were rare alleles(?A201,?A205,?Ax01,?Ax03,?Ax13,?Ax19,?Ax22,?Ael10,?B305,?Bel03,?Bel06/?Bx02,?Bw07,?Bw12,?Bw17,?Bw37,?O05,?O26,?O61,?B(A)04,?B(A)07,?cisAB01 and ?cisAB01var).In addition,six rare allele mutation sites were identified(c.101A＞G;c.103_106delG;c.146_147insGC;c.259G＞T;c.322C＞T;c.932T＞C).Conclusion The identification of ambiguous ABO blood group requires the combination of serological testing and molecular biological examination to correctly identify the blood type and ensure the safety of clinical blood transfusion.

The clinical practice guidelines of traditional Chinese medicine （TCM） have problems such as limited clinical application and unclear implementation effects， which may be related to the lack of clinical practice evidence. To provide reliable and precise evidence for clinical practice， this article proposes a model of combining TCM guidelines with real-world study， which includes 4 steps. Firstly， during the implementation process of the guidelines， a high-quality research database is established. Secondly， the recommendations in the guidelines are evaluated based on the established database in multiple dimensions， including applicability， effectiveness， safety， and cost-effectiveness， and thus their effectiveness in practical applications can be determined. Thirdly， based on the established database， core prescriptions are identified， and the targeted populations and medication plans are determined. That is， the best treatment regimen is established based on the analysis of abundant clinical data regarding the effects of different medication frequencies， dosages， and duration on efficacy. Fourthly， the guidelines are updated according to the real-world evidence. The research based on this model can provide real-world evidence for ancient and empirical prescriptions， improving their application in clinical practice. Moreover， this model can reduce research costs and improve research efficiency. When applying this model， researchers need to pay attention to the quality of real-world evidence， ensuring that it can truly reflect the situation in clinical practice. In addition， importance should be attached to the clinical application of guideline recommendations， ensuring that doctors can conduct standardized diagnosis and treatment according to the guidelines. Finally， full-process participation of multidisciplinary experts is encouraged to ensure the comprehensiveness and scientificity of the study. In conclusion， the application of this model will contribute to the development of TCM guidelines responsive to the needs of clinical practice and achieve the goal of promoting the homogenization of TCM clinical diagnosis and treatment.

As a supplement to randomized controlled trials， observational studies can provide evidence for the effectiveness of traditional Chinese medicine （TCM） treatment measures. They can also study influencing factors of diseases， etiology， and prognosis. However， there is a confounding effect due to the lack of randomization， which seriously affects the causal inference between the study factors and the outcome， resulting in confounding bias. Therefore， identifying and controlling confounding factors are key issues to be addressed in TCM observational studies. According to the causal network and the characteristics of TCM theory， confounding factors can be categorized into measured and unmeasured confounding factors. In addition， attention must be paid to identifying confounding factors and intermediate variables， as well as the interaction between confounding factors and study factors. For methods of controlling confounding factors， measured confounding factors can be controlled by stratification， multifactor analysis， propensity scores， and disease risk scores. Unmeasured and unknown confounding factors can be corrected using instrumental variable methods， difference-in-difference methods， and correction for underlying event rate ratios. Correcting and controlling confounding factors can ensure a balance between groups， and confounding bias can be reduced. In addition， methods such as sensitivity analysis and determination of interactions make the control of confounding factors more comprehensive. Due to the unique characteristics of TCM， observational studies of TCM face unique challenges in identifying and controlling confounding factors， including the ever-changing TCM treatment measures received by patients， the often-overlooked confounding effects in the four diagnostic information of TCM， and the lack of objective criteria for TCM evidence-based diagnosis. Some scholars have already conducted innovative explorations to address these issues， providing a methodological basis for conducting higher-quality TCM observational studies， so as to obtain more rigorous real-world evidence of TCM and gradually develop quality evaluation criteria for OS that are consistent with the characteristics of TCM.