In this paper,teaching idea,teaching method,study motives,study method,study strategy and other aspects have been investigated,analysed and studied according to the problem "spending more time studying English and taking less effect"in English teaching in order to change teaching idea,reform English teaching cotent and teaching methord,train good study strategy,arouse the enthusilasm of students,raise the English teaching.quality and train fine talents.

Objective: To investigate the effects of culture medium osmolarity on the proliferation of human hepatoma cell line HHCC. Methods:Cell proliferation was analyzed by MTT assay and cell cycle analysis was carried out by flow cytometry. Results:Hyperosmolarity decreased significantly the absorbance (A) of HHCC cells and cell number, and hyposmolarity have counter effects. Compared with control, hyperosmolarity blocked cell cycle progression at the G 1 phase, while hyposmolarity accelerated cells into S phase from G 1 phase, and the effect of hyposmolarity was weakened by chloride channel blocker NFA. Conclusion:Culture medium osmolarity influenced the proliferation of HHCC cells by mediating cell cycle.

Objective To explore the key initiatives and effective methods for preparing the constructions of emergency-oriented hospitals under COVID-19 pandemic. Methods The wartime mechanism was strengthened by adhering to unified leadership, trengthening the top-level design and clarifying the division of responsibilities. Objective management was used as a means to take into account the key of personnel allocation and training, prevention and control of hospital infection, transformation of contagious ward, logistic support, equipment and material supply and construction of system and process. Results The preparations and constructions of the emergency-oriented hospitals were completed in 72 hours，which passed the acceptance and inspections from infection control experts，who appraised our work to be “the highest in difficulty, the fastest in project progress and the highest in quality". Totally, upon to the preparations，14 medical teams were set up and the layout process reestablishment of 14 wards was completed, the installation and preparation of nearly 10000 sets/pieces of medical equipment and medical materials were completed as well and more than 80 work systems and process systems for 9 major modules were established. Conclusion The preparations and constructions of emergency-oriented hospitals should be performed upon the thorough implementation of the decisions and arrangements by the municipal Party committee and the municipal government, insisting on the wartime thinking and establishment of high-quality management team and effective goal management focusing on details and actual needs of medical staff.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.