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.

Autism spectrum disorder （ASD）， also known as autism， is a series of neurodevelopmental disorders characterized by social disorders and repetitive stereotyped behaviors/narrow interests. Its pathogenesis is complex， and there is a lack of effective treatment drugs， with some cases having adverse outcomes. Recent studies have consistently revealed that individuals with autism spectrum disorder （ASD） commonly exhibit characteristics such as gut microbiota dysbiosis （abnormal Bacteroidetes/Firmicutes ratio）， impaired intestinal barrier function （elevated serum levels of zonulin and LPS）， and intestinal immune dysregulation （increased pro-inflammatory cytokines including IL-6 and TNF-α）， suggesting that gastrointestinal abnormalities may influence central nervous system development through neuroendocrine， immunoregulatory， and metabolic pathways. Consequently， growing scholarly attention has focused on dietary interventions as potential approaches to alleviate clinical symptoms in children with ASD. This review systematically summarizes the role of gut microbiota and their metabolite alterations in ASD pathogenesis， along with recent advancements in understanding the microbiota-gut-brain axis mechanisms. Additionally， it elaborates on the therapeutic effects and underlying biological basis of restrictive diet therapy， modified diet therapy， and nutritional supplementation therapy in promoting the health of children with ASD. This systematic review reveals that children with ASD exhibit significant gut microbiota dysbiosis （e.g.， increased Clostridium， decreased Faecalibacterium） and abnormal metabolite profiles （e.g.， altered short-chain fatty acid spectra， elevated 4EPS levels）. These alterations exacerbate neuroinflammation and immune dysregulation through the microbiota-gut-brain axis， thereby impacting nervous system development and function. Furthermore， interventions such as ketogenic diets， camel milk， and specific nutritional supplements can alleviate certain ASD symptoms by modulating gut microbiota， restoring intestinal barrier function， and improving metabolic pathways. Future investigations should aim to create multi-omics evaluation systems for pinpointing potential beneficiaries， devise individualized intervention strategies rooted in microbiome characteristics， and verify their therapeutic value and safety in large-scale randomized controlled trials. These efforts are crucial to transitioning ASD treatment from symptomatic control to address disease etiology， thereby paving the way for improving prognoses.

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

Objective To establish a rapid,sensitive,and specific multiplex PCR detection method for the simultaneous detection of Cryptosporidium,Eimeria,and bovine parvovirus.Methods Specific primers targeting the SSU rRNA genes of Cryptosporidium and Eimeria,as well as the VP2 gene of bovine parvovirus were designed and the corresponding recombinant plasmid standards were constructed.To establish the multiplex PCR method,the reaction conditions were optimized using temperature gradient PCR and single-variable control methods.The sensitivity,specificity,reproducibility,and clinical application of the protocol were evaluated.Results The optimal annealing temperature was found to be 60.5℃,and the forward and reverse primer concentrations were determined to be 0.2 μmol/L for Eimeria,and 0.4 μmol/L for Cryptosporidium and bovine parvovirus.The assay demonstrated high sensitivity,with detection limits of 243,260,and 3 110 copies for the recombinant plasmid standards of Cryptosporidium,Eimeria,and bovine parvovirus,respectively.Specificity testing showed no cross-reactivity with ten common bovine pathogens,including Salmonella,bovine viral diarrhea virus,and bovine rotavirus.Consistent intra-and inter-batch results confirmed the strong reproducibility of the method.Clinical application to 81 diarrhea samples from various regions in the Ganzi Prefecture,Sichuan,revealed positivity rates of 18.52%(15/81)for Cryptosporidium,34.57%(28/81)for Eimeria,and 18.52%(15/81)forbovineparvovirus,withamixedinfectionrateof3.7%(3/81).Conclusions Themultiplex PCR method established in this study offers a reliable tool for differential diagnosis and epidemiological investigation of the three common diarrheal pathogens in yaks.

Objective To explore the traditional Chinese medicine(TCM)syndrome character-istics and medication patterns of cerebral small vessel disease(CSVD)using data mining techniques.Methods Clinical research literature on TCM treatment of CSVD,published from the establishment of the database to September 1,2024,was retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang,and VIP databases.Analyses were conducted on syndromes,drug frequencies,properties,flavors,and meridian tropisms.Data mining was performed using R4.4.1 software to ex-plore associations,correlations,and clustering of TCM herbs,aiming to elucidate medication patterns in CSVD treatment.Results A total of 60 prescription formulas for treating CSVD were screened,involving 142 TCM herbs with a total usage frequency of 1,312 times.The top five most frequently used herbs were Chuanxiong,Danggui,Dilong,Huangqi,and Chishao.Herb properties were pre-dominantly warm and cold;flavors were mainly pungent,bitter,and sweet;and meridian tropisms were primarily to the liver,spleen,and heart meridians.Twenty-nine strong association rules were identified,and association analysis revealed core herbal combinations centered around Chuanxiong,Chishao,and Danggui.Clustering analysis yielded five herbal combinations.Conclusion CSVD is characterized by a deficiency in essence and excess in superficiality.Treatment should focus on tonify-ing deficiencies and eliminating excesses,combining both tonification and purgation methods.Medication patterns predominantly involve herbs for promoting blood circulation and removing blood stasis,often combined with herbs for nourishing the kidney and marrow,calming the liver and suppressing wind,and awakening the mind and opening the orifices.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

Objective To explore the value of CT signs and quantitative parameters of artificial intelligence (AI) in predicting the efficacy of neoadjuvant chemotherapy for colorectal cancer. Methods A total of 349 colorectal cancer patients who received neoadjuvant chemotherapy at Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine in Hebei Province from January 2022 to January 2025 were selected and and divided into the effective group (n = 267) and the ineffective group (n = 82) according to the evaluation criteria for the efficacy of solid tumors. Conduct a CT examination and extract AI quantitative parameters from the CT images based on the lesion. The data were analyzed using SPSS21.0 software, Logistic regression was used to screen the influencing factors of ineffective neoadjuvant chemotherapy in patients with colorectal cancer, and separate and combined models of CT signs and AI quantitative parameters were established. The predictive effect of the model was verified by using the ROC curve, calibration curve and decision curve. Results Compared with the effective group, the proportion of regular tumor morphology and the proportion of non-enlarged lymph nodesin the ineffective group were smaller. The tumor volume, peak value and entropy value were larger (P < 0.05). Multivariable analysis showed that irregular shape (OR= 4.216), presence of lymph node enlargement (OR = 8.998), larger tumor volume (OR = 1.109), higher average CT value (OR = 1.120), elevated peak value (OR = 2.528), and increased entropy value (OR = 1.390) were independent risk factors for ineffective neoadjuvant chemotherapy in colorectal cancer (P < 0.05). The areas under the ROC curves of the individual and combined models of CT signs and AI quantitative parameters were 0.777, 0.818, and 0.877, respectively(P < 0.05). The calibration curve showed a Brier score of 0.091. The decision curve showed that the threshold was between 0.10 and 0.85, and the combined model achieved a relatively high net clinical benefit. Conclusion CT signs combined with AI quantitative parameters has a predictive value for the efficacy of neoadjuvant chemotherapy in colorectal cancer. To provide evidence-based basis for clinical screening of the population benefiting from chemotherapy and optimization of treatment strategies.

Endotoxins are common exogenous pyrogens. Excessive endotoxins in medical devices and injections can lead to serious consequences such as sepsis, septic shock, and even death. Therefore, endotoxin detection plays a crucial role in medical, pharmaceutical, and food sectors. The wide application of Limulus amebocyte lysate (LAL) has led to a sharp decline in the number of horseshoe crabs. Moreover, the LAL assay has limitations such as interbatch variations and difficulty in quantification. The recombinant factor C (rFC) assay is stable between batches, highly sensitive, and capable of quantitation, and thus it can be used as an alternative for the LAL assay. However, the high cost and complex procedures involved in producing recombinant factor C have limited the widespread application of this method. In order to simplify the preparation and reduce the production cost of recombinant factor C, this study focuses on the production of recombinant factor C based on the baculovirus expression system. Multiple measures such as a high-yield and anti-apoptotic vector qBac-IIIG, the optimal signal peptide, and the optimized codon were used to reach the goal of endotoxin detection with cell supernatant. This method simplifies the steps of protein purification. The sensitivity of the supernatant reached 0.05 EU/mL in a 1-L fermentation system, and 500 000 detecting reactions can be supported per liter of fermentation broth. This study increases the yield and activity of recombinant factor C, simplifies the procedures of protein purification, and reduces the cost, laying a foundation for the promotion and application of recombinant factor C in endotoxin detection.
Animals ; Recombinant Proteins/genetics* ; Horseshoe Crabs/chemistry* ; Baculoviridae/metabolism* ; Endotoxins/analysis* ; Protein C/biosynthesis* ; Genetic Vectors/genetics* ; Arthropod Proteins/genetics* ; Enzyme Precursors ; Serine Endopeptidases