In maintaining normal function and activation processes, glycolysis, lipid metabolism, and amino acid metabolism play key roles in the energy demand of platelets. In the resting state, platelets primarily rely on glycolysis and aerobic oxidation to generate energy. Upon activation, platelets preferentially utilize glycolysis, as it can more rapidly provide the required ATP. In addition to glycolysis, platelets can also utilize glycogen and fatty acids as additional energy sources. The ATP provided by fatty acid oxidation is crucial for platelet activation. Additionally, during platelet storage, distinctive changes in energy metabolism occur. In the early stages of storage, platelets primarily rely on glycolysis and the pentose phosphate pathway (PPP) to generate energy. In the mid-storage phase, there is an increase in tricarboxylic acid cycle (TCA) metabolism. In the later stages of storage, cellular metabolism gradually declines. The regulation and flexibility of these metabolic pathways play a critical role in the survival and function of platelets in different states.

ObjectiveTo investigate the preventive effect and mechanism of Dendrobium officinale （DO） on non-alcoholic fatty liver disease （NAFLD） by network pharmacology and animal experiments. MethodsDO components in blood after administration were identified and analyzed using ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-QE-HF-MS/MS）. Network pharmacology and molecular docking methods were employed to obtain active ingredients and potential targets of DO for NAFLD control. High-fat feeds were used to replicate the NAFLD rat model. Biochemical kits were used for detecting the expression levels of blood lipids， hepatic lipids， and liver functions of rats. Hematoxylin-eosin （HE） staining and oil red O staining were employed to observe pathological changes in rat liver， and real-time fluorescence quantitative PCR （Real-time PCR） assay was performed to validate potential targets obtained from the network pharmacology analysis. ResultsA total of 13 DO components were identified in blood， including berberine， dihydrosanguinarine， and oxypeucedanin. A total of 14 potential targets were screened through network pharmacology， including Forkhead box protein O1 （FoxO1）， epidermal growth factor receptor （EGFR）， and insulin-like growth factor 1 （IGF-1R）， involving pathways such as the advanced glycation end product （AGE）/receptor for AGE （RAGE） signaling pathway， blood lipids and atherosclerosis， insulin resistance， and FoxO signaling. The results of animal experiments showed that the NAFLD rat model was successfully replicated. After the preventive treatment with DO for NAFLD rats， the indexes of blood lipids， hepatic lipids， and liver function were normalized； lipid deposition and lesions in the liver were significantly improved； the expression level of FoxO1 mRNA in the liver was significantly reduced （P<0.05）， and the mRNA expression levels of phosphatidylinositide 3-kinases （PI3K）， protein kinase B （Akt）， EGFR， and IGF-1R were significantly increased （P<0.05）. ConclusionDO has a preventive effect on NAFLD rats， and the mechanism of action may be related to the modulation of IGF1R and EGFR targets and activation of the PI3K/Akt/FoxO1 signaling pathway.

Objective To investigate the spatial distribution of Aedes albopictus in China at different time periods from 2000 to 2019, so as to provide insights into precise management of Ae. albopictus in China. Methods Data pertaining to the distribution of Ae. albopictus in China from 2000 to 2019 were collected through literature retrieval with terms of “Aedes albopictus”, “monitoring”, “survey”, “density”, “distribution”, and “outbreak” in national and international databases. The title and time of the publication, sampling sites, sampling time, mosquito capture methods, and mosquito species and density were extracted, and the longitude and latitude of sampling sites were obtained through Baidu Map. Meteorological element data at meteorological observation stations within China were obtained from the National Climatic Data Center of the United States, and the annual maximum temperature, annual minimum temperature, average temperature in January, average temperature in July, annual temperature range, daily temperature range and relative humidity were calculated and subjected to Kriging interpolation. Monthly cumulative precipitation grid data and monthly average temperature grid data with a resolution of 1 km for China from 2000 to 2019 were obtained from the National Tibetan Plateau Scientific Data Center, and the annual precipitation and annual average temperature were calculated cumulatively. Population density data in China from 2000 to 2019 were obtained from the WorldPop Hub, and the gross domestic product (GDP) in China was obtained from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. The above data were divided into 5-year intervals to calculate data during the periods from 2000 to 2004, from 2005 to 2009, from 2010 to 2014, and from 2015 to 2019. Ae. albopictus distribution data were modeled in China from 2000 to 2019 and during each period with the classification random forest (RF) model, to predict the distribution of Ae. albopictus across the country and analyze the distribution of Ae. albopictus based on the seven major climate zones in China. The performance of RF models was evaluated by accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC), and the importance of each feature in the RF model was evaluated with mean decrease accuracy (MDA). Results A total of 1 191 Chinese publictions and 391 English publications were retrieved, among which 580 articles provided detailed data on the sampling sites of Ae. albopictus and specific sampling years, meeting the inclusion criteria. A total of 2 234 Ae. albopictus sampling sites were included in China from 2000 to 2019, and RF modeling results showed that the overall Ae. Albopictus distribution area was mainly found in southeastern and southwestern provinces of China from 2000 to 2019, with scattered distribution in coastal areas of northeastern provinces, such as Liaoning Province. The accuracy, precision, recall and AUC of the RF model were 0.915 to 0.947, 0.933 to 0.975, 0.898 to 0.978, and 0.902 to 0.932 for the distribution of Ae. albopictus at different time periods from 2000 to 2019. Among all features in the RF models, population density was the most contributing factor to the distribution of Ae. albopictus in China, followed by GDP, and all meteorological variables contributed relatively less to the predictive power of the RF model. In China’s seven major climate zones, Ae. albopictus was almost entirely distributed in the marginal tropical humid region, the north subtropical humid region, and the warm temperate semi-humid region. The combined distribution area of these three zones accounted for 100.0% of the national distribution area from 2000 to 2004, from 2005 to 2009, and from 2010 to 2014, and 99.9% from 2015 to 2019, and the proportion of Ae. albopictus distribution area in the warm temperate semihumid region increased gradually from 20.2% to 30.2%. Conclusions Ae. albopictus is mainly distributed in the southeastern and southwestern provinces of China and is greatly influenced by population and economic factors. The warm temperate semi-humid region in China is gradually becoming a hot spot for the distribution of Ae. albopictus.

Objective: To accurately determine the ABO blood group of samples exhibiting forward/reverse grouping discrepancies by combining first-generation (Sanger) and third-generation (long-read) sequencing technologies. Methods: Five samples with ABO forward/reverse grouping discrepancies were selected. Serological testing was conducted using automated blood typing instruments and the tube method. Genotyping was conducted using both Sanger and long-read sequencing technologies. Results: Sanger sequencing identified specific genetic mutations in two samples, with genotypes of ABO BA. 04/ABO O.01.01 and ABO B3.05/ABO O.01.02. Further analysis with long-read sequencing revealed specific mutations in the +5.8kb region of intron 1 (c.28+5885C>T and c.28+5861T>G) in three samples where mutations were not detected by Sanger sequencing. These mutations affect the expression of the ABO antigens and are likely responsible for the ABO subgroup phenotypes. Conclusion: The integration of Sanger and long-read sequencing technologies effectively identifies genetic variations causing ABO subtypes, providing a scientific basis for enhancing clinical transfusion safety and ensuring accurate blood group determination.

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

Objective: To accurately determine the ABO blood group of samples exhibiting forward/reverse grouping discrepancies by combining first-generation (Sanger) and third-generation (long-read) sequencing technologies. Methods: Five samples with ABO forward/reverse grouping discrepancies were selected. Serological testing was conducted using automated blood typing instruments and the tube method. Genotyping was conducted using both Sanger and long-read sequencing technologies. Results: Sanger sequencing identified specific genetic mutations in two samples, with genotypes of ABO BA. 04/ABO O.01.01 and ABO B3.05/ABO O.01.02. Further analysis with long-read sequencing revealed specific mutations in the +5.8kb region of intron 1 (c.28+5885C>T and c.28+5861T>G) in three samples where mutations were not detected by Sanger sequencing. These mutations affect the expression of the ABO antigens and are likely responsible for the ABO subgroup phenotypes. Conclusion: The integration of Sanger and long-read sequencing technologies effectively identifies genetic variations causing ABO subtypes, providing a scientific basis for enhancing clinical transfusion safety and ensuring accurate blood group determination.

The Consolidated Standards of Reporting Trials (CONSORT) statement aims to enhance the quality of reporting for randomized controlled trial (RCT) by providing a minimum item checklist. It was first published in 1996, and updated in 2001 and 2010, respectively. The latest version was released in April 2025, continuously reflecting new evidence, methodological advancements, and user feedback. CONSORT 2025 includes 30 essential checklist items and a template for a participant flow diagram. The main changes to the checklist include the addition of 7 items, revision of 3 items, and deletion of 1 item, as well as the integration of multiple key extensions. This article provides a comprehensive interpretation of the statement, aiming to help clinical trial staff, journal editors, and reviewers fully understand the essence of CONSORT 2025, correctly apply it in writing RCT reports and evaluating RCT quality, and provide guidance for conducting high-level RCT research in China.

ObjectiveThe proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence’s proteome data. MethodsThe software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine—either pFind or MaxQuant—to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual’s exome-derived nsSNP profile and outputs the comparison report. ResultsSAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. ConclusionAn automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

Most patients with pancreatic cancer are already in the locally advanced or metastatic stage at initial diagnosis. While systemic chemotherapy provides clinical benefits for those with mid-to-late-stage pancreatic cancer, its efficacy is often limited by patient tolerance. In response to the dual clinical demands of robust antitumor activity and high targeting specificity, antibody-drug conjugate (ADC) has emerged as a promising solution. By conjugating highly selective monoclonal antibodies with potent cytotoxic small-molecule drugs, ADC achieves precise tumor-targeting while minimizing damage to healthy tissues, which thereby improves treatment tolerance. However, due to the complex pathological features of pancreatic cancer, no ADC has yet been approved for clinical use for this disease. A comprehensive evaluation of factors including ADC-specific targets, payload selection, antibody-drug linkage strategies, drug delivery mechanisms, tissue distribution variability, and tumor heterogeneity will be crucial to advancing the clinical translation of ADC for pancreatic cancer treatment.

Humans ; Arthritis, Psoriatic/drug therapy* ; Interleukin-17 ; Interleukin Inhibitors ; Antirheumatic Agents/therapeutic use* ; Tumor Necrosis Factor-alpha/therapeutic use* ; Interleukin-23/therapeutic use*