“Bio-narrative integration” refers to the process in which a life subject with narrative consciousness actively reviews and reintegrates their life stories， or a subject lacking life and health narrative awareness， with the intervention of healthcare professionals， tells their own life stories and integrates them into a coherent and constantly evolving life narrative process. Starting from the keyword of bio-narrative integration， this paper proposed a classification model of narrative integration. From the perspective of life stages， it was divided into “phasic narrative integration” and “holistic narrative integration.” In terms of integrated narrative style， it was categorized as “positive narrative integration style” and “negative narrative integration style.” Regarding subjective initiative， it was classified as “active narrative integration regulation” and “passive narrative integration regulation.” Then it elaborated the significant value of narrative integration for every life subject， especially in pain relief， the improvement of life resilience， the healthy aging of the elderly， and the ultimate peace of the dying. It was advocated that healthcare practitioners should enhance their professional narrative competence， effectively guide patients to engage in bio-narrative integration regulation， and help them overcome narrative closure， thereby improving the quality of medical care.

Objective To explore whether there is a causal relationship between intestinal flora and esophageal cancer. Methods Summary statistics of intestinal flora and esophageal cancer were obtained from the Genome-wide Association Studies (GWAS) database. Five methods, including inverse variance weighted (IVW), weighted median estimation, Mendelian randomization (MR)-Egger regression, single mode, and weighted mode, were used for analysis, with IVW as the main analysis method. Sensitivity analysis was used to evaluate the reliability of MR results. Results In the IVW method, Oxalobacteraceae [OR=1.001, 95%CI (1.000, 1.002), P=0.023], Faecalibacterium [OR=1.001, 95%CI (1.000, 1.002), P=0.028], Senegalimassilia [OR=1.002, 95%CI (1.000, 1.003), P=0.006] and Veillonella [OR=1.001, 95%CI (1.000, 1.002), P=0.018] were positively correlated with esophageal cancer, while Burkholderiales [OR=0.999, 95%CI (0.998, 1.000), P=0.002], Eubacterium oxidoreducens [OR=0.998, 95%CI (0.997, 0.999), P=0.038], Romboutsia [OR=0.999, 95%CI (0.998, 1.000), P=0.048] and Turicibacter [OR=0.998, 95%CI (0.997, 0.999), P=0.013] were negatively correlated with esophageal cancer. Sensitivity analysis showed no evidence of heterogeneity, horizontal pleiotropy and reverse causality. Conclusion Oxalobacteraceae, Faecalibacterium, Senegalimassilia and Veillonella increase the risk of esophageal cancer, while Burkholderiales, Eubacterium oxidoreducens, Romboutsia and Turicibacter decrease the risk of esophageal cancer. Further studies are needed to explore how these bacteria affect the progression of esophageal cancer.

Objective To identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.

"When warm evil is received,it first attacks the lungs and then spread to the pericardium reversely"is the general rule of warm diseases.Doctors of different dynasties have different views on the phrase"reverse spread to the pericardium",especially the word"reverse".Professor Tong Xiaolin proposed that the heart governs the mind,the pericardium and the heart are connected in qi,and when the heart is affected by evil,the pericardium instead suffers from the evil.The"reverse spread to the pericardium"proposed by Ye Tianshi is actually the spread of warm evil to the brain.Taking meningococcal meningitis as the basic disease,it can be matched one by one with the typical stages of the transmission of Wei-Qi-Ying-Xue.Combined with the theory of Dingjiao,it is believed that the function of"the heart governing the mind"focuses more on the brain in the modern anatomical sense.Combining traditional Chinese medicine's ideas on diagnosis and treatment of warm diseases with modern medicine,revealing the essence of the disease,grasping the core of the pathogenesis,analyzing the word"reverse"from a new perspective,and exploring its true meaning,is of great significance for clarifying its connotation,exploring the development laws of warm diseases,and guiding the diagnosis and treatment of warm disea-ses.

Objective To explore the value of combining apparent diffusion coefficient(ADC)heterogeneity with morphological indicators in assessing the pathological grading of non-muscle invasive bladder cancer(NMIBC).Methods The MRI images of 86 patients confirmed with NMIBC by surgical pathology were analyzed retrospectively.All patients underwent T2WI,diffusion weighted ima-ging(DWI),and dynamic contrast enhancement(DCE)examinations.Two radiologists independently measured tumor largest diam-eter(LD),actual tumor-wall contact length(ACTCL),ADCmean,ADCmin,and ADCmax values.ADC heterogeneity was calculated using the formula(ADCmax-ADCmin)/ADCmean.Differences in quantitative parameters between low-and high-grade NMIBC were compared using the Mann-Whitney U test,while differences in qualitative parameters were compared using the chi-square test.Univariate and multivariate logistic regression analyses were used to identify independent predictors of high-grade NMIBC,and receiver operating characteristic(ROC)curves were drawn to evaluate the performance of ADC heterogeneity combined with morphological indicators in assessing high-grade NMIBC.Results ADC heterogeneity and ACTCL were independent predictors for preoperative assessment of NMIBC pathological grading.The area under the curve(AUC)of ADC heterogeneity and ACTCL in assessing high-grade NMIBC were 0.843 and 0.744,respectively.The combined AUC was 0.902.The difference was statistically significant(P<0.05).Conclusion The combination of ADC heterogeneity with ACTCL can effectively improve the efficiency of preoperative assessment of NMIBC pathological grading,and providing more precise clinical decision-making and prognosis monitoring.

Human taste is an important function of chemical perception. In recent years, brain taste evoked potentials have received more and more attention as a feasible tool for objective assessment of taste dysfunction. This paper reviews the main characteristics of gustatory evoked potential signals, the most widely used recording and processing techniques, and the scientific advances and relevance of gustatory evoked potentials in many important applications. In particular, taste evoked potentials are used to study the central effects of food intake and taste disorders, which may affect cognition and personality, or may be potential indicators of the onset or progression of neurological disorders. For these reasons, this paper presents and analyzes the latest scientific results and future challenges of using gustatory evoked potentials as an attractive solution to objective monitoring techniques for taste disorders. Human taste is an important function of chemical perception. In recent years, brain gustatory evoked potentials have received more and more attention as a feasible tool for objective assessment of taste dysfunction. This paper reviews the main characteristics of gustatory evoked potential signals, the most widely used recording and processing techniques, and the scientific advances and relevance of gustatory evoked potentials in many important applications. In particular, gustatory evoked potentials are used to study the central effects of food intake and taste disorders, which may affect cognition and personality, or may be potential indicators of the onset or progression of neurological disorders. For these reasons, this paper presents and analyzes the latest scientific results and future challenges of using gustatory evoked potentials as an attractive solution to objective monitoring techniques for taste disorders.
Humans ; Evoked Potentials ; Taste/physiology* ; Taste Perception/physiology*

Mitochondrial dysfunction in chondrocytes is a key pathogenic factor in osteoarthritis (OA), but directly modulating mitochondria in vivo remains a significant challenge. This study is the first to verify a correlation between mitochondrial dysfunction and the downregulation of the FOXO3 gene in the cartilage of OA patients, highlighting the potential for regulating mitophagy via FOXO3 gene modulation to alleviate OA. Consequently, we developed a chondrocyte-targeting CRISPR/Cas9-based FOXO3 gene-editing tool (FoxO3) and integrated it within a nanoengineered 'truck' (NETT, FoxO3-NETT). This was further encapsulated in injectable hydrogel microspheres (FoxO3-NETT@SMs) to harness the antioxidant properties of sodium alginate and the enhanced lubrication of hybrid exosomes. Collectively, these FoxO3-NETT@SMs successfully activate mitophagy and rebalance mitochondrial function in OA chondrocytes through the Foxo3 gene-modulated PINK1/Parkin pathway. As a result, FoxO3-NETT@SMs stimulate chondrocytes proliferation, migration, and ECM production in vitro, and effectively alleviate OA progression in vivo, demonstrating significant potential for clinical applications.

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

With the accelerated progress of population aging and the shift in the disease spectrum, the prevention and management of chronic diseases and multimorbidity are facing great challenges. Multimorbidity measurement is a process that assesses and quantifies the complexity and severity of multiple disease states in a population, which is of great significance for understanding the epidemiology and disease burden of multimorbidity, as well as for optimizing medical services and policy. This article reviews existing multimorbidity measurement indicators, tools, and applications from two dimensions, static and dynamic attributes, aiming to improve the accuracy and comprehensiveness of multimorbidity epidemiology, diagnosis, and treatment.

Objective:To carry out carrier screening among people of childbearing age, detect the pathogenic genes of monogenic genetic diseases and analyze the carrier status of pathogenic variants, so as to provide fertility guidance and intervention measures for high-risk families.Methods:From August 2022 to August 2023, 1 533 families of childbearing age who met the criteria were recruited in the Chinese PLA General Hospital, including a total of 3 044 subjects. According to the standard enrollment procedure, 223 genes (197 autosomal recessive genes and 26 X-linked genes) of the subjects were tested. According to the screening results, genetic counseling and fertility guidance were provided to the subjects. Invasive prenatal diagnosis was performed for high-risk couples (both couples being carriers of the same autosomal recessive disease gene or the woman was a carrier of X-linked disease gene), and their pregnancy pattern, outcome and offspring phenotype were followed up.Results:(1) A total of 3 044 cases from 1 511 couples and women of childbearing age from 22 families were included for carrier screening. Totally 1 503 families chose simultaneous screening and 30 families chose sequential screening out of the 1 533 families. Among the 3 044 subjects, 1 603 individuals carried at least one pathogenic or likely pathogenic variant, and the overall carrier rate was 52.66% (1 603/3 044). A total of 2 292 pathogenic or likely pathogenic variants were detected, and 0.75 variants (2 292/3 044) were detected per capita. (2) The three genes with the highest carrier rates were GJB2 (8.67%, 264/3 044), CYP21A2 (3.19%, 97/3 044) and PAH (3.09%, 94/3 044). There were 32 genes with a carrier rate ≥1/200, 17 genes with a carrier rate ≥1/100, and 7 genes with a carrier rate ≥1/50. (3) Thirty-eight high-risk families were identified. After excluding G6PD gene mutation, there were 33 high-risk families, of which 25 couples were carriers of the same autosomal recessive gene, 9 women were carriers of X-linked gene, and 1 family was double high-risk couple with both autosomal recessive and X-linked gene. After further excluding the GJB2 c.109G>A mutation, 21 high-risk families were identified. Preimplantation genetic testing for monogenic disease was performed in 12 families after genetic counseling. Prenatal diagnosis was completed in 4 out of 5 high-risk families who conceived naturally. Two fetuses carried the parental variants and terminated the pregnancy, one fetus did not carry the parental variants but was induced due to trisomy 21 syndrome, and one fetus was a carrier of congenital disorders of glycosylation type 1a.Conclusions:Carrier screening effectively identifies high-risk genetic disease families and provides reproductive guidance to prevent the birth of affected children. However, establishing multidisciplinary team is essential for managing complex cases. Implementation should prioritize prenatal institutions with genetic counseling or diagnostic expertise for monogenic disorders or established referral networks.