Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding developed a strategy for platelet and plasma infusion management in critically ill children based on systematic reviews and consensus meetings of international multidisciplinary experts. One good practice statement and six expert consensus statements were proposed for plasma and platelet transfusions in critically ill children following severe trauma, traumatic brain injury, and/or intracranial hemorrhage. This article introduces the specific methods and basis for the formation of recommendations in this part of the guide.

Natural arabinogalactan， an important polysaccharide， has a wide range of sources， a complex structure， various biological activities， and great application potential. Natural arabinogalactan is mainly rich in plants and microorganisms， and its structure varies due to different sources， including types Ⅰ， type Ⅱ， type Ⅱ-related types， and new configurations. Natural arabinogalactan has shown a variety of biological activities， such as anti-tumor， anti-oxidation， anti-coagulation， anti-aging， blood glucose-lowering， intestinal health-maintaining， anti-inflammatory， and immunomodulatory activities. In addition， natural arabinogalactan shows good biocompatibility and low toxicity， serving as a potential material in the biomedical field. Natural arabinogalactan has been designed as a carrier in the drug delivery system to effectively improve drug stability and targeting. Natural arabinogalactan is often added to skin care products to help delay skin aging and enhance skin barrier function because of their moisturizing and antioxidant properties. Additionally， natural arabinogalactan acts as a thickener， stabilizer， and emulsifier to improve the texture and taste while enhancing the nutritional value of food products. The review of latest research reports is helpful to further understand the relationship between the structure， biological activity， and functional application of natural arabinogalactan and provides an important reference for future research and development.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

ObjectiveTo investigate the correlation of the serum levels of aminotransferases and their ratios with liver inflammation activity in pediatric chronic hepatitis B （pCHB） patients， and to provide a basis for selecting the dominant population for treatment. MethodsThis study was conducted among 1 267 pCHB patients who were admitted to The Fifth Medical Center of Chinese PLA General Hospital from January 2010 to August 2022 and these patients did not receive antiviral therapy. The patients were analyzed in terms of demographic features， blood routine， blood biochemistry， HBV serological markers， and liver biopsy data. According to liver inflammation activity based on liver biopsy， the patients were divided into no or mild inflammation activity （G0‍ ‍—‍ ‍G1） group and significant inflammation activity （G2‍ ‍—‍ ‍G4） group. The serum levels of aminotransferases and their ratios were compared between groups， and their correlation with liver inflammation activity in pCHB patients was analyzed. Additionally， the patients were stratified by the age， and the relationship between serum aminotransferase levels and liver inflammation activity was analyzed in each age group. For comparison of continuous data between two groups， the independent samples t-test was used when the data were normally distributed， while the Mann-Whitney U test was used when the data were not normally distributed； the chi-square test was employed for comparison of categorical data between two groups. A Spearman’s correlation analysis was performed for correlation assessment. ResultsAmong the 1 267 pCHB patients， there were 468 （36.9%） in the G0‍ ‍—‍ ‍G1 group and 799 （63.1%） in the G2‍ ‍—‍ ‍G4 group， and there were significant differences between the two groups in the levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， AST/ALT ratio， gamma-glutamyl transpeptidase （GGT）， total bilirubin， direct bilirubin， HBeAg quantification， low-density lipoprotein， and platelet count （PLT） （all P<0.05）. The correlation analysis showed that liver inflammation activity was negatively correlated with PLT and low-density lipoprotein （both P<0.05） and was positively correlated with GGT， total bilirubin， direct bilirubin， and HBeAg titer （all P<0.05）， while it was not significantly correlated with ALT， AST， and AST/ALT ratio （all P>0.05）. In the 0‍ ‍—‍ ‍12 years group， the 13‍ ‍—‍ ‍18 years male group， and the 13‍ ‍—‍ ‍18 years female group， liver inflammation activity aggravated with the increases in the serum levels of ALT and AST， and there were significant differences between groups （all P<0.05）. In the 0‍ ‍—‍ ‍12 years group， there was a significant difference in significant liver inflammation activity between the AST/ALT ratio >1 group and the AST/ALT ratio ≤1 group （P<0.001）. Among the 1 267 patients， 447 （35.28%） had an ALT level of <2×upper limit of normal （ULN）， among whom 196 （43.85%） had G≥2 liver inflammation， accounting for 15.47% of all children enrolled. ConclusionLiver inflammation activity is not significantly correlated with ALT， AST， and AST/ALT ratio in pCHB patients， suggesting that the serum levels of aminotransferases cannot truly reflect liver inflammation activity in pCHB patients with an aminotransferase level of <2×ULN. In clinical practice， liver biopsy should be performed for children with an aminotransferase level of <2×ULN to clarify whether antiviral therapy should be performed.

The immunomodulatory， repair， and regeneration-promoting functions of mesenchymal stem cells make them one of the potential treatment methods for liver diseases. At present， viral and non-viral delivery methods have been developed to genetically modify mesenchymal stem cells， and gene modification can promote the survival， homing， and cytokine secretion of mesenchymal stem cells， thereby enhancing the ability of mesenchymal stem cells to treat liver diseases. This article mainly summarizes the research advances in gene-modified mesenchymal stem cells in the treatment of liver diseases， in order to provide new insights and strategies for the clinical treatment of liver diseases.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

Image 1.

Discoidin domain receptor 1 (DDR1) is overexpressed in various tumors, such as triple-negative breast cancer (TNBC), and is rarely expressed in normal tissues. These characteristics make DDR1 a preferable target candidate for the construction of an antibody-drug conjugate (ADC) for targeted therapy. Here, we investigated the preparation and preclinical efficacy of DDR1-DX8951, an ADC that includes an anti-DDR1 monoclonal antibody conjugated to DX8951 by a cleavable Gly-Gly-Phe-Gly (GGFG) linker. The anti-DDR1 monoclonal antibody was coupled to DX8951 (i.e., DDR1-DX8951), producing the targeted therapy ADC. The antitumor activities of DDR1-DX8951 monotherapy or DDR1-DX8951 plus pembrolizumab were assessed in TNBC mouse models. DDR1-DX8951 can specifically target DDR1, be quickly internalized by TNBC cells, and reduce the viability of TNBC cells in vitro. The potent antitumor activity of DDR1-DX8951 was revealed in TNBC xenograft models. Importantly, our investigation demonstrated that DDR1-DX8951 plus pembrolizumab not only revealed the inhibitory efficacy on tumor growth and metastasis but also played an important role in improving the immunosuppressive tumor microenvironment (TME) of TNBC. Taken together, this investigation provides justification for large-sample studies to further assess the safety and efficacy of DDR1-DX8951 plus pembrolizumab for TNBC clinical trials.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.