【Objective】 To investigate the effect of double plasma molecular adsorption system and sequential half-dose plasma exchange (DPMAS+HPE) on the short-term survival rate of patients with hepatitis B associated acute-on-chronic liver failure (HBV-ACLF). 【Methods】 Data on HBV-ACLF cases hospitalized in our hospital from January 1, 2015 to December 31, 2022 were retrospectively collected, and were divided into standard comprehensive medical treatment group and DPMAS+HPE group according to different treatment methods. Propensity score matching (PSM) was used to eliminate inter group confounding bias. The baseline data and improvement of laboratory indicators after treatment between two groups were compared. Death related risk factors in HBV-ACLF patients were screened by logistic regression analysis, and cumulative survival rates at 30 and 90 days between the two groups were compared by Kaplan-Meier survival analysis. 【Results】 A total of 373 cases of HBV-ACLF were included in this study. Among them, 136 cases in the treatment group received DPMAS+HPE once on the basis of comprehensive internal medicine treatment, and 237 cases only received comprehensive internal medicine treatment. After PSM, 136 patients were included as the control group. The decrease in alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total protein (TP) in the treatment group before and after treatment was significantly greater than that in the control group (446.5 vs 159.0, 317.0 vs 92.0,5.2 vs 0.3), with statistically significant difference (P<0.05). DPMAS+HPE treatment is an independent protective factor for mortality in HBV-ACLF patients at 30 and 90 days (30 days: OR=0.497, P<0.05; 90 days: OR= 0.436, P<0.05). The cumulative survival rates at 30 and 90 days in the treatment group were significantly higher than those in the control group (30 days: 50.71% vs 44.12%, P<0.05; 90 days: 30.15% vs 22.79%, P<0.05). 【Conclusion】 DPMAS+HPE improves the short-term prognosis of HBV-ACLF patients and can serve as an effective artificial liver model for the treatment of HBV-ACLF patients.

Background::Although some well-established oncogenes are involved in cancer initiation and progression such as prostate cancer (PCa), the long tail of cancer genes remains to be defined. Goosecoid ( GSC) has been implicated in cancer development. However, the comprehensive biological role of GSC in pan-cancer, specifically in PCa, remains unexplored. The aim of this study was to investigate the role of GSC in PCa development. Methods::We performed a systematic bioinformatics exploration of GSC using datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Omnibus, German Cancer Research Center, and our in-house cohorts. First, we evaluated the expression of GSC and its association with patient prognosis, and identified GSC-relevant genetic alterations in cancers. Further, we focused on the clinical characterization and prognostic analysis of GSC in PCa. To understand the transcriptional regulation of GSC by E2F transcription factor 1 ( E2F1), we performed chromatin immunoprecipitation quantitative polymerase chain reaction (qPCR). Functional experiments were conducted to validate the effect of GSC on the tumor cellular phenotype and sensitivity to trametinib. Results::GSC expression was elevated in various tumors and significantly correlated with patient prognosis. The alterations of GSC contribute to the progression of various tumors especially in PCa. Patients with PCa and high GSC expression exhibited worse progression-free survival and biochemical recurrence outcomes. Further, GSC upregulation in patients with PCa was mostly accompanied with higher Gleason score, advanced tumor stage, lymph node metastasis, and elevated prostate-specific antigen (PSA) levels. Mechanistically, the transcription factor, E2F1, stimulates GSC by binding to its promoter region. Detailed experiments further demonstrated that GSC acted as an oncogene and influenced the response of PCa cells to trametinib treatment. Conclusions::GSC was highly overexpressed and strongly correlated with patient prognosis in PCa. We found that GSC, regulated by E2F1, acted as an oncogene and impeded the therapeutic efficacy of trametinib in PCa.

[Abstract] [Objective] To explore the risk factors of blood transfusion in patients with isolated traumatic brain injury (iTBI) based on multiple machine learning methods, so as to establish a predictive model to provide reasonable guidance for blood transfusion in patients with iTBI. [Methods] A total of 2 273 patients with iTBI from the First Affiliated Hospital of Nanchang University from January 1, 2015 to June 30, 2021 were included to compare and analyze the differences in variables such as vital signs, clinical indicators and laboratory testing indicators between transfusion and non transfusion patients. Furthermore, six machine learning models were established to compare the performance of different models through cross validation, accuracy, specificity, recall, f1 value and area under the ROC curve. The SHAP plot was used to explain the influencing factors of blood transfusion in iTBI patients. [Results] This study included 2 273 iTBI patients, with a total of 301 patients receiving blood transfusions. There were significant differences (P<0.05) in gender, age, HR, clinical diagnosis, skull fracture, treatment methods, hemorrhagic shock, GCS, K, Ca, PT, APTT, INR, RBC, Hct, Hb and Plt between transfusion and non transfusion patients; Moreover, the LOS, incidence of complications, mechanical ventilation rate, ICU admission rate, readmission rate within 90 days and in-hospital mortality rate of transfusion patients were all higher than those of the non transfusion group (P<0.05). Six machine learning algorithms were used for model construction, and the validation results on the test set showed that the CatBoost model performed the best with an AUC of 0.911. Furthermore, the SHAP framework was used to explain and visualize the optimal model CatBoost, showing that surgical treatment, lower GCS, higher INR, lower Hct, lower K, lower Ca, age ≥60 years, skull fractures and hemorrhagic shock increase the risk of blood transfusion in patients. [Conclusion] This study established a machine learning model for predicting blood transfusion in iTBI patients, and the CatBoost model performed the best. This model may be useful and beneficial for identifying transfusion risks in this population, making clinical transfusion decisions and monitoring progress.

Objective:To explore the plasma metabolomic characteristics of children with transfusion-dependent thalassemia(TDT),and reveal the changes of metabolic pattern in children with TDT.Methods:23 children with TDT who received regular blood transfusion in Ganzhou Women and Children's Health Care Hospital in 2021 were selected,and 11 healthy children who underwent physical examination during the same period were selected as the control group.The routine indexes between children with TDT and the control group were compared,and then the metabolic composition of plasma samples from children with TDT and the control group was detected by liquid chromatography-mass spectrometry.An OPLS-DA model was established to perform differential analysis on the detected metabolites,and the differential metabolic pathways between the two groups were analyzed based on the differential metabolites.Results:The results of routine testing showed that the indexes of ferritin,bilirubin,total bile acid,glucose and triglycerides in children with TDT were significantly higher than those in healthy controls,while hemoglobin and total cholesterol were significantly lower(all P＜0.05).However there was no significant difference in lactate dehydrogenase between the two groups(P＞0.05).Compared with the control group,190 differential metabolites(VIP＞1)were identified in TDT children.Among them,168 compounds such as arginine,proline and glycocholic acid were significantly increased,while the other 22 compounds such as myristic acid,eleostearic acid,palmitic acid and linoleic acid were significantly decreased.The metabolic pathway analysis showed that the metabolic impact of TDT on children mainly focused on the upregulation of amino acid metabolism and downregulation of lipid metabolism.Conclusion:The amino acid and lipid metabolism in children with TDT were significantly changed compared with the healthy control group.This finding is helpful to optimize the treatment choice for children with TDT,and provides a new idea for clinical treatment.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

The ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was used to conduct the qualitative analysis of the monoterpene chemical components from Paeoniae Radix Rubra. Gradient elution was performed on C_(18) HD(2.1 mm×100 mm, 2.5 μm) column with a mobile phase of 0.1% formic acid(A) and acetonitrile(B). The flow rate was 0.4 mL·min~(-1) and the column temperature was 30 ℃. MS analysis was conducted in both positive and negative ionization modes using electrospray ionization(ESI) source. Qualitative Analysis 10.0 was used for data processing. The identification of chemical components was realized by the combination of standard compounds, fragmentation patterns, and mass spectra data reported in the literature. Forty-one monoterpenoids in Paeoniae Radix Rubra extract were identified. Among them, 8 compounds were reported in Paeoniae Radix Rubra for the first time and 1 was presumed to be the new compound 5″-O-methyl-galloylpaeoniflorin or its positional isomer. The method in this study realizes the rapid identification of monoterpenoids from Paeoniae Radix Rubra and provides a material and scientific basis for quality control and further study on the pharmaceutical effect of Paeoniae Radix Rubra.
Chromatography, Liquid ; Drugs, Chinese Herbal ; Mass Spectrometry ; Monoterpenes

【Objective】 To construct a blood transfusion prediction model for patients with severe traumatic brain injury (TBI), in order to predict the risk of blood transfusion and guide blood transfusion decision-making. 【Methods】 The clinical data of 756 patients with severe TBI admitted to the hospital from January 1, 2015 to June 30, 2021 were retrospectively analyzed. According to whether the patients were transfused with red blood cells after admission, the patients were divided into blood transfusion group (n=354) and non-blood transfusion group (n=402). The basic clinical data and prognostic indicators of the two groups were compared. Logistic regression algorithm was used to screen the risk factors related to blood transfusion in hospital to establish a nomogram prediction model, and the performance of the model was evaluated. 【Results】 No significant differences were noticed in gender, age, body temperature, cause of injury, ABO blood group, Rh blood group, serum Na and K concentrations between the two groups (P>0.05). Significant differences were found in Glasgow coma score (GCS), heart rate (HR), systolic blood pressure (SP), diastolic blood pressure (DP), shock index (SI), respiratory rate (RR), clinical diagnosis, treatment, hemoglobin concentration (Hb), hematocrit (Hct), platelet count (Plt) and coagulation function between the two groups (P<0.05). The length of stay, complication rate, ventilator utilization rate, ICU admission rate and 90-day readmission rate in the blood transfusion group were significantly higher than those in the non-blood transfusion group (P<0.05). However, there was no significant difference in in-hospital mortality between the two groups (P>0.05). Multivariate logistic regression analysis showed that surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR were independent risk factors for blood transfusion. A nomogram prediction model was constructed and the area under the ROC curve of the training set and the test set was 0.819(95% CI: 0.784-0.854) and 0.866(95% CI: 0.818-0.910), respectively, which had good predictive performance. 【Conclusion】 Surgical treatment, skull fracture, hemorrhagic shock, decreased Plt, decreased Hct and increased INR are independent risk factors for blood transfusion in adult patients with severe traumatic brain injury. The nomogram prediction model can better predict the blood transfusion demand of TBI patients and has high application value.

A primary liver cancer patient complicated by hepatic cystic echinococcosis was reported. The case was admitted to the hospital due to intermittent upper abdominal discomfort for more than half a month, and an auxiliary examination revealed primary liver cancer complicated by hepatic cystic echinococcosis. Then, hepatic artery infusion and chemoembolization was performed, and no treatment was given to cystic echinococcosis lesions. Following treatment, the patient had remarkable improvements in the liver functions.

Sterol-regulatory element binding proteins (SREBPs) are the key transcriptional regulators of lipid metabolism. The activation of SREBP requires translocation of the SREBP precursor from the endoplasmic reticulum to the Golgi, where it is sequentially cleaved by site-1 protease (S1P) and site-2 protease and releases a nuclear form to modulate gene expression. To search for new genes regulating cholesterol metabolism, we perform a genome-wide CRISPR/Cas9 knockout screen and find that partner of site-1 protease (POST1), encoded by C12ORF49, is critically involved in the SREBP signaling. Ablation of POST1 decreases the generation of nuclear SREBP and reduces the expression of SREBP target genes. POST1 binds S1P, which is synthesized as an inactive protease (form A) and becomes fully mature via a two-step autocatalytic process involving forms B'/B and C'/C. POST1 promotes the generation of the functional S1P-C'/C from S1P-B'/B (canonical cleavage) and, notably, from S1P-A directly (non-canonical cleavage) as well. This POST1-mediated S1P activation is also essential for the cleavages of other S1P substrates including ATF6, CREB3 family members and the α/β-subunit precursor of N-acetylglucosamine-1-phosphotransferase. Together, we demonstrate that POST1 is a cofactor controlling S1P maturation and plays important roles in lipid homeostasis, unfolded protein response, lipoprotein metabolism and lysosome biogenesis.

Tumors are new organisms formed by uncontrollable cell proliferation of local tissues driven by various oncogenic factors. The cause of tumors is unknown with life-threating outcome. Tumors can be classified into benign tumors， borderline tumors， and malignant tumors according to their pathological properties. Among them， malignant tumor is commonly known as cancer， with no specific medicines or reliable cure means， so this is a hot spot and difficult point in current medical research. In ancient literatures， there are many records about the efficacy of Chinese herbal medicine in treating tumor， and modern pharmacological researches have shown that more and more active ingredients of traditional Chinese medicine（TCM） have gradually highlighted their inhibitory effect on various types of tumor. Caulis sinomenii has been used for treatment of rheumatic diseases in TCM for a long history. Sinomenine is a major bioactive alkaloid presented in C. sinomenii， which has demonstrated a wide range of pharmacological activities such as anti-inflammation， immunosuppression， analgesia and sedation， and due to its slightly soluble in water， it is commonly used in clinic in the form of hydrochloride， with its commercial name of Zhengqing Fengtongning. Recent studies show that sinomenine alone or combined with chemoradiotherapy can inhibit growth of several tumors significantly or in a synergistic way， so it is termed as an inhibitor of tumors. Anti-tumor effect of sinomenine involve inhibition of tumor cell proliferation， induction of tumor cell apoptosis， blockade of tumor cell cycle， suppression of tumor invasion and metastasis， induction of autophagy of tumor cells， and reversal of multidrug resistance of tumor cells. Upon combination with nanomaterials， it can enhance efficiency and reduce toxicity. Here we summarized and reviewed recent advances on basic anti-tumor research of sinomenine， and then made a classification and description according to its in vivo and in vitro pharmacological action and mechanism of action， so as to elucidate the great potential of sinomenine as a promising anti-tumor drug， and provide reference for further research on its anti-tumor mechanism.