Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Objective:To understand the psychosomatic experience and needs of patients with lumbar cistern drainage after transnasal endoscopic sinus surgery in neurosurgery while lying in bed.Methods:Using the purposeful sampling method, one-to-on, face-to-face semi-structured interviews were conducted among 12 patients with lumbar cistern catheter drainage who were treated in Beijing Tiantan Hospital Affiliated to Capital Medical University from July to August 2020. Colaizzi phenomenology study was used to analyze the interview data, and summarized the themes.Results:The experience and needs of patients with lumbar cistern catheterization during the catheter placement were summarized into 3 themes. Obvious physical and mental discomfort: pain, discomfort of body position restriction, expectation minimization constraint scheme. Knowledge and cognitive needs: understand the reasons for intubation, intubation time and precautions. Affectionate and professional care needs: eager for professional care and more attention from medical staff, eager to be accompanied by family member to achieve greater improvement of comfort.Conclusions:Clinical nursing should be based on the patient′s psychosomatic feelings and needs, actively explore personalized intervention measures suitable for patients with lumbar cistern drainage, and formulate corresponding predictive care content to improve patients′ compliance, comfort and satisfaction.

Tumor recurrence after surgery is the main cause of treatment failure. However, the initial stage of recurrence is not easy to detect, and it is difficult to cure in the late stage. In order to improve the life quality of postoperative patients, an efficient synergistic immunotherapy was developed to achieve early diagnosis and treatment of post-surgical tumor recurrence, simultaneously. In this paper, two kinds of theranostic agents based on gold nanorods (AuNRs) platform were prepared. AuNRs and quantum dots (QDs) in one agent was used for the detection of carcinoembryonic antigen (CEA), using fluorescence resonance energy transfer (FRET) technology to indicate the occurrence of

Objective To explore the program of convolutional neural networks for the diagnosis of schizophrenia and evaluate its effects. Methods Using the convolutional neural network,the training model was trained in the lead data of 138 normal people and 183 schizophrenic patients,and the model was valida-ted by 20-fold cross-validation. Results The true positive rate of schizophrenia prediction using the convolu-tional neural network training model was 0. 749, the false positive rate was 0. 275, and the accuracy was 0. 738. Conclusion This model can achieve a strong diagnostic ability for patients with schizophrenia. Therefore,convolutional neural network for the diagnosis of schizophrenia will become an important research direction in the future.