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.

Neuroscience,a cutting-edge field in interdisciplinary research,consistently draws considerable research interest,of which quantitatively probing the neurochemical dynamics is essential for brain science research.In vivoelectrochemical analysis,featuring with high sensitivity,high spatiotemporal resolution,free from transfection,and designable electrode/solution interfaces,provides important tools for in vivo neurochemicals sensing.Fast scan cyclic voltammetry combined with microelectrodes can not only enable precise detection of dopamine but also is compatible with existing neurosurgical equipment.This offers new opportunities for the clinical application of in vivo electrochemical analysis and paves new avenues for the diagnosis and treatment of neurological diseases.This review summarized recent progress of in vivo electrochemical techniques for brain neurochemistry and addressed key clinical challenges and their potential solutions.

ObjectiveBased on analytic hierarchy process（AHP）-criteria importance through intercriteria correlation（CRITIC） hybrid weighting method， grey relational analysis and backpropagation artificial neural network（BP-ANN）， to optimize the water extraction process of Qizhi prescription， so as to provide an experimental basis for optimization of the preparation process of this prescription and the establishment of quality standards. MethodsL₉（3⁴） orthogonal test was employed， and the AHP-CRITIC hybrid weighting method was utilized to determine the weight coefficients of the quality fractions of various components， including astragaloside Ⅳ， polygalaxanthone Ⅲ， calycosin-7-O-β-D-glucoside， tenuifolin， and 3，6′-disinapoylsucrose， as well as the dry extract yield. The comprehensive score of each factor level combination in the orthogonal test were calculated as evaluation indicator to select the optimal extraction process parameters. The effects of extraction times， extraction time， and solvent dosage on the aqueous extraction process of the formula were investigated through intuitive analysis， variance analysis， and grey relational analysis. Meanwhile， a BP-ANN model was established to reverse-predict the optimal extraction process parameters of Qizhi prescription， and the optimized process parameters were validated. ResultsThe weight coefficients of the five index components（astragaloside Ⅳ， tenuifolin， calycosin-7-O-β-D-glucoside， polygalaxanthone Ⅲ， and 3，6′-disinapoylsucrose） and dry extract yield were 25.7%， 20.82%， 16.41%， 12.45%， 15.96% and 8.67%， respectively. The optimized extraction process parameters were extracted 3 times with 8， 6， 6 times the amount of water， each time for 1 h. The network prediction results of BP-ANN test samples were consistent with the orthogonal test results， and the mean square error（MSE） of the predicted and measured values of the network was <1%. The water extraction process of Qizhi prescription analyzed and predicted by relevant mathematical models was stable and feasible， which could effectively improve the extraction efficiency of the active ingredients of Astragali Radix and Polygalae Radix， and the average comprehensive score of the validation test was 90.85 with the relative standard deviation（RSD） of 1.55%. ConclusionThis study establishes a water extraction process for compound Qizhi granules， and the optimized extraction process can effectively improve the extraction efficiency of active ingredients， which provides useful references for the optimization of preparation process and the establishment of quality standards for other clinical experience formulas.

As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

Objective To explore the effect of organizational climate on work alienation in psychiatric nurses,and the mediating role of psychological capital and positive coping styles between organizational climate and work alienation,in order to provide a reference for reducing work alienation among psychiatric nurses.Methods Convenience sampling method was used to select nurses working in 6 tertiary A psychiatric hospitals in Shandong Province from January to July 2024,and the general questionnaire,Nurses' Work Alienation Questionnaire,Organizational Climate Scale for Nursing,Psychological Capital Questionnaire,and Simple Coping Style Scale were used to conduct the survey and the mediation effect test.Results A total of 606 questionnaires were recovered,of which 572 were valid,and the validity rate of the questionnaires was 94.39％.Psychiatric nurses scored(89.58±13.69)for nursing organizational climate,(32.48±11.31)for work alienation,(97.28±19.12)for psychological capital,and(23.93±7.22)for positive coping styles.There was a direct effect of nursing organizational climate on work alienation(β=-0.681,95％CI=-0.824～-0.539).Psychological capital and positive coping styles acted as separate mediators and chain mediators in the effect of nursing organizational climate on work alienation(β=-0.116,-0.048,-0.019,95％CI=-0.182～-0.034,-0.086～-0.006,-0.042～-0.002).Conclusion There are multiple mediating effects of psychiatric nurses' psychological capital,positive coping styles between nursing organizational climate and work alienation.Nursing managers can enhance psychiatric nurses' psychological capital by creating a positive and healthy organizational climate,encouraging them to adopt positive coping styles to solve problems,and reducing work alienation.

Constipation is a common functional gastrointestinal disorder with a global prevalence of approximately 10％to 20％.Its causes include functional disorders,organic diseases,and drug factors,with the majority being functional constipation.In recent years,driven by advancements in biomedicine,artificial intelligence(AI),and microbiome research,significant progress has been made in the diagnosis and treatment of constipation.This review systematically explores the latest developments in constipation treatment,including the role of the gut microbiota in constipation,the metabolic regulatory effects of short-chain fatty acids(SCFAs),the impact of mental factors on intestinal motility.Additionally,it discusses future development directions such as AI-assisted diagnosis,AI-based consultation systems,personalized microbiota transplantation,and minimally invasive neuromodulation,providing new insights for precision medicine in constipation.

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.

Objective To explore the effect of organizational climate on work alienation in psychiatric nurses,and the mediating role of psychological capital and positive coping styles between organizational climate and work alienation,in order to provide a reference for reducing work alienation among psychiatric nurses.Methods Convenience sampling method was used to select nurses working in 6 tertiary A psychiatric hospitals in Shandong Province from January to July 2024,and the general questionnaire,Nurses' Work Alienation Questionnaire,Organizational Climate Scale for Nursing,Psychological Capital Questionnaire,and Simple Coping Style Scale were used to conduct the survey and the mediation effect test.Results A total of 606 questionnaires were recovered,of which 572 were valid,and the validity rate of the questionnaires was 94.39％.Psychiatric nurses scored(89.58±13.69)for nursing organizational climate,(32.48±11.31)for work alienation,(97.28±19.12)for psychological capital,and(23.93±7.22)for positive coping styles.There was a direct effect of nursing organizational climate on work alienation(β=-0.681,95％CI=-0.824～-0.539).Psychological capital and positive coping styles acted as separate mediators and chain mediators in the effect of nursing organizational climate on work alienation(β=-0.116,-0.048,-0.019,95％CI=-0.182～-0.034,-0.086～-0.006,-0.042～-0.002).Conclusion There are multiple mediating effects of psychiatric nurses' psychological capital,positive coping styles between nursing organizational climate and work alienation.Nursing managers can enhance psychiatric nurses' psychological capital by creating a positive and healthy organizational climate,encouraging them to adopt positive coping styles to solve problems,and reducing work alienation.

Constipation is a common functional gastrointestinal disorder with a global prevalence of approximately 10％to 20％.Its causes include functional disorders,organic diseases,and drug factors,with the majority being functional constipation.In recent years,driven by advancements in biomedicine,artificial intelligence(AI),and microbiome research,significant progress has been made in the diagnosis and treatment of constipation.This review systematically explores the latest developments in constipation treatment,including the role of the gut microbiota in constipation,the metabolic regulatory effects of short-chain fatty acids(SCFAs),the impact of mental factors on intestinal motility.Additionally,it discusses future development directions such as AI-assisted diagnosis,AI-based consultation systems,personalized microbiota transplantation,and minimally invasive neuromodulation,providing new insights for precision medicine in constipation.