OBJECTIVE To form an expert consensus addressing clinical issues regarding the use of parenteral direct thrombin inhibitors （DTIs） in special populations. METHODS Led by the Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital（the Affiliated Hospital of UESTC）， a multidisciplinary working group was formed comprising experts from multiple fields， including clinical pharmacy， cardiac surgery， obstetrics， pediatrics and evidence-based medicine. Through literature review and the Delphi method， clinical questions regarding the efficacy and safety of parenteral DTIs used in special populations were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” （PICO） framework；systematic searches were conducted in CJFD， PubMed， Embase and other databases. Relevant evidence from randomized controlled trials，cohort studies and systematic reviews were included and synthesized. Evidence quality was assessed using the Grading of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through three rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven clinical questions were ultimately selected （with a consensus rate exceeding 90%）， resulting in the formulation of seven recommendations on the use of parenteral DTIs in special populations， including children， pregnant women， patients with hepatic or renal impairment， patients with mesenteric venous thrombosis， and individuals with thrombophilia. These recommendations clarify the preferred agents， dosing ranges， monitoring parameters， and safety management strategies for parenteral DTIs in these special populations. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in special populations.

Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

Oxidative stress is a pivotal factor in the onset and progression of diabetic kidney disease （DKD）， and it plays an essential role in the prevention and treatment of DKD. The "Gaozhuo" pathogenesis posits that DKD is characterized by the invasion of Gaozhuo and damage to the kidney collaterals， with the underlying cause being the insufficiency of spleen Qi and the internal formation of Gaozhuo， which provides valuable guidance on oxidative stress. The insufficiency of spleen Qi and the internal formation of Gaozhuo represent a dynamic， evolving process. Gaozhuo invades the kidney collaterals， impairs kidney Qi， and progressively leads to the congealing and stagnation of Gaozhuo and blood， ultimately resulting in the failure of both the spleen and kidneys. The damage caused by Gaozhuo to the kidney collaterals and kidney Qi is analogous to the organ and functional damage of the kidneys induced by excessive reactive oxygen species and oxidative stress. Damage to the kidney collaterals means organic injuries to the glomeruli， renal tubules， and renal interstitium， and the depletion of kidney Qi refers to damage to glomerular filtration and renal tubular reabsorption. The congealing and stagnation of Gaozhuo and blood in the kidney collaterals is similar to oxidative stress-induced thickening of the glomerular basement membrane and fibrosis. The interaction between spleen and kidney Qi deficiency and the congealing and stagnation of Gaozhuo and blood creates a vicious cycle that exacerbates the condition， ultimately evolving into the failure of both the spleen and kidneys. The failure of the spleen and kidneys is analogous to renal failure， and its extreme manifestation is end-stage renal disease and uremia. The treatment of oxidative stress in DKD with traditional Chinese medicine （TCM） is based on the principles of strengthening the spleen and tonifying the kidneys， and dispelling turbidity and removing blood stasis. According to the syndrome type， it is recommended to use methods such as strengthening the spleen and tonifying Qi while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling turbidity and removing blood stasis， or consolidating the spleen and kidneys while clearing away turbidity and blood stasis.

ObjectiveTo provide a basis for the establishment of an ideal animal model of allergic asthma by statistically analyzing the modeling characteristics and the selection of indicators of the available models. MethodsWe retrieved the relevant articles from China National Knowledge Infrastructure（CNKI）， VIP， Wanfang Data， SinoMed， and PubMed with "allergic asthma" as the keyword and the time interval from January 2019 to January 2024. Through integrating the literature and extracting data， we used Excel 2021 to create a personal database and sorted out the animal strains， genders， allergenic substances， modeling routes， and test indicators and methods. Excel 2021， Cytoscape 3.10.2， and SPSS Modeler 18.0 were then used to analyze the relevant characteristics of the animal models. ResultsA total of 418 articles were included in the database， and the comparative analysis showed that the most frequently used animal strain for modeling was BALB/c mice， and female animals were mostly used. The main modeling method was sensitization by intraperitoneal injection of ovalbumin （OVA）， which was combined with intranasal inhalation. The test indicators mainly included appearance signs， cellular analysis， lung histopathology， lung function indicators， and protein and gene expression in the lung. The test methods mainly involved pathological staining， enzyme-linked immunosorbent assay， immunohistochemistry， immunofluorescence， Western blot， and polymerase chain reaction（PCR） assays. ConclusionThere is no recognized modeling method or evaluation standard for the animal models of allergic asthma. Based on the results of data analysis， the OVA-induced allergic asthma model in BALB/c mice is recommended. The main criteria for evaluating the success of modeling are the general behavioral changes， the morphological changes of the airway and inflammatory cell infiltration in the lung tissue， the changes of pro-inflammatory and anti-inflammatory cytokines in the serum， and the alterations of inflammatory cells in the bronchoalveolar lavage fluid.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

BACKGROUND:Neuregulin 1 has been shown to be characterized in cell proliferation,differentiation,and vascular growth.Human amniotic mesenchymal stem cells are important seed cells in the field of tissue engineering,and have been shown to be involved in tissue repair and regeneration. OBJECTIVE:To construct human amniotic mesenchymal stem cells overexpressing neuregulin 1 and investigate their proliferation and migration abilities,as well as their effects on wound healing. METHODS:(1)Human amniotic mesenchymal stem cells were in vitro isolated and cultured and identified.(2)A lentivirus overexpressing neuregulin 1 was constructed.Human amniotic mesenchymal stem cells were divided into empty group,neuregulin 1 group,and control group,and transfected with empty lentivirus and lentivirus overexpressing neuregulin 1,or not transfected,respectively.(3)Edu assay was used to detect the proliferation ability of the cells of each group,and Transwell assay was used to detect the migration ability of the cells.(4)The C57 BL/6 mouse trauma models were constructed and randomly divided into control group,empty group,neuregulin 1 group,with 8 mice in each group.Human amniotic mesenchymal stem cells transfected with empty lentivirus or lentivirus overexpressing neuregulin-1 were uniformly injected with 1 mL at multiple local wound sites.The control group was injected with an equal amount of saline.(5)The healing of the trauma was observed at 1,7,and 14 days after model establishment.Histological changes of the healing of the trauma were observed by hematoxylin-eosin staining.The expression of CD31 on the trauma was observed by immunohistochemistry. RESULTS AND CONCLUSION:(1)Human amniotic mesenchymal stem cells overexpressing neuregulin-1 were successfully constructed.The mRNA and protein expression of intracellular neuregulin 1 was significantly up-regulated compared with the empty group(P<0.05).(2)The overexpression of neuregulin 1 promoted the migratory ability(P<0.01)and proliferative ability of human amniotic mesenchymal stem cells(P<0.05).(3)Human amniotic mesenchymal stem cells overexpressing neuregulin 1 promoted wound healing in mice(P<0.05)and wound angiogenesis(P<0.05).The results showed that overexpression of neuregulin 1 resulted in an increase in the proliferative and migratory capacities of human amniotic mesenchymal stem cells,significantly promoting wound healing and angiogenesis.

Protozoan infections(e.g.,malaria,trypanosomiasis,and toxoplasmosis)pose a considerable global burden on public health and socioeconomic problems,leading to high rates of morbidity and mortality.Due to the limited arsenal of effective drugs for these diseases,which are associated with devastating side effects and escalating drug resistance,there is an urgent need for innovative antiprotozoal drugs.The emergence of drug repurposing offers a low-cost approach to discovering new therapies for pro-tozoan diseases.In this review,we summarize recent advances in drug repurposing for various human protozoan diseases and explore cost-effective strategies to identify viable new treatments.We highlight the cross-applicability of repurposed drugs across diverse diseases and harness common chemical motifs to provide new insights into drug design,facilitating the discovery of new antiprotozoal drugs.Chal-lenges and opportunities in the field are discussed,delineating novel directions for ongoing and future research.

Objective:To construct and evaluate the nomogram prediction model of spontaneous rupture of primary liver cancer (STRPLC), and make the web-based dynamic online nomogram.Methods:Clinical data of 346 patients with PLC treated in the Second Affiliated Hospital of Kunming Medical University were retrospectively analyzed, including 87 males and 15 females, aged 58.15±10.32 years. Single factor and multiple factor logistic regression analysis were used to screen the influencing factors of STRPLC, and the prediction model was constructed based on the nomogram. Receiver operating characteristic (ROC) curve, calibration curve and clinical decision analysis were used to evaluate the model. The web-based dynamic online nomogram was developed using the DynNom package in R4.3.1 software.Results:Multivariate logistic regression analysis showed that the independent risk factors for spontaneous rupture and hemorrhage of tumor were no history of systematic anti-tumor therapy, alpha-fetoprotein (AFP) level, tumor protrusion on liver surface, tumor length, invasion of major blood vessels, and moderate to large amount of ascites (all P<0.05). The area under the receiver operating characteristic curve (AUC) of the prediction model constructed by this nomogram is 0.913 (95% CI: 0.884-0.943), the best cutoff value is 0.254, with a sensitivity of 0.892, and a specificity of 0.803. The calibration curve shows a good agreement between the predicted probability and the actual probability. The decision curve of the model is above the two invalid lines of " none" and " all" in the horizontal range of 0.07-0.98, and the clinical net benefit of the model is >0. Then user-friendly web-based dynamic online nomogram is constructed. Conclusion:Large tumor size, superficial location, no history of systematic anti-tumor therapy, high AFP level, invasion of major blood vessels, and moderate to large amount of ascites are independent risk factors for STRPLC. The prediction model and dynamic online nanogram constructed by this method can effectively assess the risk of STRPLC.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.