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Data analysis models may assist the transmission of traditional Chinese medicine （TCM） experience and clinical diagnosis and treatment， and the possibility of constructing a “data-knowledge” dual-drive model was explored by taking gastric precancerous state as an example. Data-driven is to make clinical decisions around data analysis， and its syndrome-differentiation decision-making research relies on hidden structural models and partially observable Markov decision-making processes to identify the etiology of diseases， syndrome elements， evolution of pathogenesis， and syndrome differentiation protocols； knowledge-driven is to make use of data and information to promote decision-making and action processes， and its syndrome-differentiation decision-making research relies on convolutional neural networks to improve the accuracy of local disease identification and syndrome differentiation. The “data-knowledge” dual-driven model can make up for the shortcomings of single-drive numerical simulation accuracy， and achieve a balance between local disease identification and macroscopic syndrome differentiation. On the basis of previous research， we explored the construction method of diagnostic assisted decision-making platform for gastric precancerous state， and believed that the diagnostic and decision-making ability of doctors can be extended through the assistance of machines and algorithms. Meanwhile， the related research methods were integrated and the core features of gastric precancerous state based on TCM syndrome differentiation and endoscopic pathology diagnosis and prediction were obtained， and the elements of endoscopic pathology recognition based on TCM syndrome differentiation were explored， so as to provide ideas for the in-depth research and innovative application of cutting-edge data analysis technology in the field of intelligent TCM syndrome differentiation.
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The pathological subtypes of breast cancer can be further divided into different molecular subtypes based on their immunohistochemical staining, such as estrogen receptor (ER) , progesterone receptor (PR) , human epidermal growth factor receptor2 (HER2) and Ki67 expression, including luminal subtype, HER2 overexpression subtype and triple negative subtype. The luminal subtype is defined as ER and/or PR positive. In molecular mechanism, the expression activity of ER can regulate the expression of PR, so the expression of ER and PR is usually consistent. However, in the process of detection, some breast cancers with inconsistent ER/PR expression often appear, especially those with ER (-) /PR (+) . There is still controversy about whether such cases are true. Patients with this type of breast cancer should be subjected to ER and PR immunohistochemical staining again, and then reclassified according to HER2 status. The expression of ER/PR is closely related to the efficacy of endocrine therapy for breast cancer, so its test results will directly affect the treatment options of clinician. This article will review and discuss the research progress of the causes and mechanisms of ER (-) /PR (+) breast cancer.
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Aim To investigate the effects of 17β-es-tradiol on the apoptosis induced by ketamine in primary cultured cortical neurons. Methods Primary cultured cortical neurons were treated with different concentra-tions of ketamine or 17β-estradiol respectively. 24 hours after various treatments, neuron viability was measured by MTT assay. The structure of neurons was analyzed using microscope. Apoptotic neurons were de-termined by the TUNEL assay. The level of pAkt ex-pression was analyzed by Western blot. ResultsCompared with the control group, ketamine decreased neuron viability in a dose-dependent manner. Com-pared with ketamine group, 17β-estradiol increased neuron viability in a dose-dependent manner. Lack of three-dimensional sense,faded color,uncleared outline were observed, and fractured neuron axons or neurons death were also observed in neurons treated by 100μmol · L-1 ketamine. 100 μmol · L-1 ketamine in-creased the number of apoptotic neurons and decreased the expression of pAkt. 0.1 μmol · L-1 17β-estradiol decreased the number of apoptotic neurons and in-creased the expression of pAkt. LY294002 inhibited the protective effects of 17β-estradiol, the number of apoptotic neurons increased, and the level of pAkt de-creased significantly. Conclusion 17β-estradiol ex-erts the neuroprotective effects against ketamine-in-duced neuroapoptosis by activating the PI3 K/Akt sig-naling pathway.
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Objective To investigate the changes in the expression of mitochondrial transcription factor A (mtTFA) during one-lung ventilation (OLV)-induced lung injury in rabbits.Methods Sixty healthy male New Zealand white rabbits,weighing 2.5-3.0 kg,were randomized into 2 groups (n =8 each):two-lung ventilation (TLV) group and OLV group.The animals were anesthetized with iv 3％ pentobarbital sodium 30 mg/kg and tracheostomized.A self-made double lumen catheter was then intubated.Bilateral lungs were ventilated for 3 h in group TLN.In group OLV the left lung was ventilated for 2 h followed by 1 h TLV.Arterial blood samples were taken for blood gas analysis immediately after the beginning of ventilation,at 1 and 2 h of ventilation,and immediately after the end of ventilation.The oxygenation index was calculated.The animals were sacrificed after the end of ventilation and the apex of the left lung was removed and then cut and stained with HE for microscopic examination.The pathological changes of the lung were scored.The expression of mtTFA in lung tissues was measured by Western blot.Results Oxygenation index was significantly decreased,lung injury score was increased,the expression of mtTFA was down-regulated in group OLV compared with group TLV (P ＜ 0.05).The pathological changes of the lung were aggravated in group OLV.Conclusion OLV induces lung injury by down-regulation of mtTFA expression in rabbit lung tissues.