Sinusitis is a prevalent nasal disease in children, characterized by chronic and difficult-to-treat symptoms. Its onset is related to nasal stagnation, gallbladder and lung dysfunctions. This article explores the root cause based on Huangdi Neijing by considering the physiological and pathological characteristics of children. The core pathogenesis of pediatric sinusitis is the transmission of heat from the gallbladder and lung to the brain and nose, disrupting normal nasal function. Wind and heat pathogens often persist, accumulate, and transform into turbid qi, which are common triggers of the disease. Evil qi retention and yin depletion are internal factors that cause the prolonged and unhealed condition of the disease. This article emphasizes individualized treatment approaches based on disease duration and the severity of pathogenic factors. If external pathogens remain uncleared, treatment should focus on dispelling wind, clearing heat, dispersing with pungent medicinals, and dredging nasal orifices. If internal fire is exuberant, clearing lung qi, inhibiting hyperactive liver yang, and clearing exuberant fire should be used to relieve stagnation. In chronic cases with residual pathogens and liver-kidney yin deficiency, nourishing yin, clearing fire, and moistening the nasal orifices are essential. When exuberant heat has subsided, but the symptom of a persistent runny nose continues, leading to the loss of healthy qi and damage to the lung and spleen, treatments that tonify the spleen, benefit the lung, and reinforce healthy qi should be adopted to relieve stagnation. These treatments aim to restore the balance of the body′s vital qi by addressing both the lingering symptoms and the underlying weakness of the lung and spleen. The diagnosis and treatment of pediatric sinusitis based on the theory of "the transmission of heat from gallbladder and lung" can help reduce the recurrence of sinusitis and alleviate symptoms, with the aim of broadening the approach of traditional Chinese medicine in treating this condition.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

OBJECTIVE To evaluate the quality of diagnosis and treatment guidelines and expert consensuses on childhood immune thrombocytopenic purpura （ITP） published domestically and internationally， in order to provide reference for clinical practice and future guideline/expert consensus development and improvement. METHODS A systematic search was conducted across multiple databases， including PubMed， Cochrane Library， Embase， CNKI， Wanfang data， VIP， CBM； additionally， supplementary searches were carried out on websites such as Medlive， the Chinese Medical Association’s official website， and National Institute for Health and Clinical Excellence in the UK. The retrieval time ranged from the inception to September 2， 2024. Researchers who had undergone systematic training independently evaluated the methodology and report quality included in the guideline/consensus using the Appraisal of Guidelines Research and Evaluation Ⅱ （AGREE Ⅱ） and the Reporting Items for Practice Guidelines in Healthcare （RIGHT）. RESULTS A total of 11 guidelines/consensuses were included. The average scores for the six domains of AGREE Ⅱ tool respectively were “range and purpose” （[ 66.67±17.98）% ]， “participants” [58.33% （13.89%，73.61%）]， “rigor” （[ 41.81±23.85）% ]， “clarity”（[ 69.57±19.35）%]， “applicability” （[ 35.98±17.83）%]， and “independence” [27.08% （0，75.00%）]； out of 11 articles， 9 had a recommendation level of B， 2 had a recommendation level of C， and there were no A-level articles. The average reporting rates of the 7 areas in the RIGHT tool were “basic information” （[ 72.35±12.95）% ]， “background” （[ 54.55±15.40）%]，“ evidence” （[ 36.36±24.81）%]，“ recommended opinions” （[ 53.25±19.20）%]，“ review and quality assurance” [0 （0， 25.00%）]， “funding and conflict of interest statement and management” [12.50%（0，25.00%）]， and other aspects [8.33%（0， 50.00%）]. In addition， there was no statistically significant difference in the AGREE Ⅱ and RIGHT scores between the guidelines and consensuses （P＞0.05）. CONCLUSIONS The overall quality of the guidelines and consensuses included in this study is not high， with a recommended level of B or C. It is recommended that clinical decision-making prioritize referring to the relatively high-quality guideline/consensus among them. The quality of evidence in the existing traditional Chinese medicine guidelines for children with ITP needs to be improved， and there is no integrated guideline/consensus for traditional Chinese and Western medicine. It is recommended to revise or write relevant guideline/consensus according to the requirements of AGREE Ⅱ and RIGHT in various fields to guide clinical practice.

Macroautophagy (referred to as autophagy hereafter) is a major intracellular lysosomal degradation pathway that is responsible for the degradation of misfolded/damaged proteins and organelles. Previous studies showed that autophagy protects against acetaminophen (APAP)-induced injury (AILI) via selective removal of damaged mitochondria and APAP protein adducts. The lysosome is a critical organelle sitting at the end stage of autophagy for autophagic degradation via fusion with autophagosomes. In the present study, we showed that transcription factor EB (TFEB), a master transcription factor for lysosomal biogenesis, was impaired by APAP resulting in decreased lysosomal biogenesis in mouse livers. Genetic loss-of and gain-of function of hepatic TFEB exacerbated or protected against AILI, respectively. Mechanistically, overexpression of TFEB increased clearance of APAP protein adducts and mitochondria biogenesis as well as SQSTM1/p62-dependent non-canonical nuclear factor erythroid 2-related factor 2 (NRF2) activation to protect against AILI. We also performed an unbiased cell-based imaging high-throughput chemical screening on TFEB and identified a group of TFEB agonists. Among these agonists, salinomycin, an anticoccidial and antibacterial agent, activated TFEB and protected against AILI in mice. In conclusion, genetic and pharmacological activating TFEB may be a promising approach for protecting against AILI.

Objective To clarify the effects of 5G mobile phone radiofrequency radiation exposure on male mouse fertility and to preliminarily explore the underlying mechanisms. Methods Healthy male C57BL/6 mice aged 7-8 weeks were randomly assigned to Sham group, 3.5 GHz radiofrequency radiation group, and 4.9 GHz radiofrequency radiation group, with 16 mice in each group. The mice were exposed to 3.5 GHz or 4.9 GHz mobile phone radiofrequency radiation for 42 consecutive days (1 h per day). The sperm quality was evaluated using sperm count, deformity rate, and motility. H&E staining was performed to assess testicular tissue structure by observing the morphology of spermatogenic cells at various development stages, the diameter of seminiferous tubules, and the thickness of seminiferous epithelium. The sperm mitochondrial function was assessed using sperm mitochondrial membrane potential and testicular ATP content. The fertility of mice was evaluated through fertility rate, litter size, and survival rate of offspring. The underlying mechanisms were explored by detecting the methylation of LRGUK gene and its mRNA and protein levels. Results Compared with the Sham group, there were no significant changes in sperm count in the 3.5 GHz and 4.9 GHz groups; however, the sperm abnormality rate significantly increased (P < 0.05) and sperm motility significantly decreased (P < 0.05). The structure of testicular tissue, the function of sperm mitochondria, and fertility of mice showed no significant changes as compared with the Sham group. The methylation level of LRGUK gene in the testes significantly increased, while the mRNA and protein expression levels significantly decreased. Conclusion Exposure to 3.5 GHz and 4.9 GHz mobile phone radiofrequency radiation for 42 consecutive days can lead to an increase in sperm deformity rate and a decrease in sperm motility in mice, but has no significant effect on fertility, which may be related to an increase in methylation level of the LRGUK gene in the testes.

Most chemical medicines have polymorphs. The difference of medicine polymorphs in physicochemical properties directly affects the stability, efficacy, and safety of solid medicine products. Polymorphs is incomparably important to pharmaceutical chemistry, manufacturing, and control. Meantime polymorphs is a key factor for the quality of high-end drug and formulations. Polymorph prediction technology can effectively guide screening of trial experiments, and reduce the risk of missing stable crystal form in the traditional experiment. Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry, and then was developed by the key technology of machine learning using the artificial intelligence. Nowadays, the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure. Recently, predicting medicine polymorphs has still been a challenging problem. It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

ObjectiveTePixD (Tll0078) is a blue light-using flavin (BLUF) photoreceptor protein from Thermosynechococcus elongatus BP-1. TePixD protein has a conserved Tyr8-Gln50-Met93 triad around the FAD pocket to mediate the proton-coupled electron transfer (PCET) process. But the detailed light response mechanism needs further study. We aimed to elucidate the structure and biochemical properties of TePixD mutants at key light response sites to analyze the light response process of TePixD. MethodsWe employed X-ray crystallography to resolve the crystal structure of the TePixD Y8F mutant. The side chain of Tyr8 is involved in PCET while Phe8 in mutation loses the function due to the loss of its hydroxyl group. We compared the structure of TePixD Y8F mutation to TePixD wild type (WT) and its homology protein SyPixD Y8F. Using multi-angle light scattering (MALS), we analyzed the oligomerization of multiple TePixD mutations (Y8F, Q50L, W91F, Y8F/W91F, and Q50L/W91F), focusing specifically on mutational sites that are critical residues for the protein’s photo response to dark and light conditions. ResultsWe resolved the crystal structure of TePixD Y8F mutant at a resolution of 2.54 Å and found that it shares a similar overall structure with the TePixD WT but exhibits significant differences from the SyPixD Y8F structure. Biochemical analysis revealed differences in molecular mass and elution profiles between the TePixD mutants and the WT under dark and light conditions, indicating the perturbation on the light-induced conformational change by the mutants. ConclusionOur structure determination and biochemical analyses will add information to reveal the light response mechanism of BLUF proteins.

Cuproptosis is a new type of cell death that depends on intracellular copper accumulation to trigger the aggregation of mitochondrial lipoacylated protein and the degradation of iron-sulfur cluster protein,with a different mechanism of action from autophagy,ferroptosis,pyroptosis,and necroptosis.Cuproptosis is closely association with the development of liver cancer and resistance to antitumor drugs,as well as the progression of various liver diseases such as hereditary liver diseases,nonalcoholic fatty liver disease,viral hepatitis,and liver cirrhosis.This article summarizes the mechanism of cuproptosis and its role in liver diseases,in order to provide a reference for further research and treatment of liver diseases.