With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.

Objective To observe changes of white matter function in adolescent smoker(AS)with resting-state functional MRI(rs-fMRI)fractional amplitude of low-frequency fluctuation(fALFF)technique.Methods Forty-five adolescents(AS group)and 45 control subjects(control group)were prospectively enrolled,and brain rs-fMRI were acquired.Brain regions with fALFF being different between groups were observed,and the correlations with clinical indicators were analyzed.Results Compared with that in control group,fALFF of the right superior longitudinal fasciculus significantly elevated in AS group(FDR correct Q＜0.05),in which the peak of the cluster was positively correlated with score of Fagerstr?m test for nicotine dependence(FTND)(r=0.294,P=0.049).Conclusion White matter function changed in AS,presenting as significantly increased fALFF in right superior longitudinal fasciculus,which was positively correlated with nicotine dependence.

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.

Objective To investigate the dynamic functional connectivity differences between insomnia patients and healthy controls in triple brain networks[the significant network(SN),the default mode network(DMN),and the executive control network(ECN)]using functional magnetic resonance imaging,and uncover their associations with cognitive ability.Methods Dynamic functional connectivity analysis was performed on functional magnetic resonance imaging data from 40 insomnia patients and 40 healthy controls.The changes in dynamic functional connectivity values were studied for SN,DMN,ECN[including the left executive control network(LECN)and the right executive control network(RECN)];the similarities and differences in time characteristic indicators such as time score,average dwell time,and conversion rate were explored;and their associations with clinical information were analyzed.Results The SN-LECN and DMN-RECN dynamic functional connectivity was significantly higher in insomnia patients than in healthy controls(P=0.013,0.047),while the RECN-LECN and RECN internal functional connectivity strength was lower in insomnia patients than in healthy controls(P<0.001).Additionally,the fractional time in state 2 in insomnia group was significantly higher than that in healthy controls(P<0.001),and it was positively correlated with the Pittsburgh sleep quality index(r=0.524,P=0.001).Conclusion Insomnia patients exhibit significant abnormalities in triple brain network dynamic functional connectivity,which may be related to abnormalities in cognitive control and sensory processing in insomnia patients.These findings provide a new perspective for further research on the neural mechanisms and potential intervention strategies for insomnia.

Objective:To summarize the clinical and genetic characteristics of pseudoachondroplasia and multiple epiphyseal dysplasia caused by COMP gene variants in pediatric patients.Methods:This retrospective study concluded 15 pediatric patients with COMP-related pseudoachondroplasia and multiple epiphyseal dysplasia at Shanghai Children′s Medical Center, Shanghai Jiao Tong University School of Medicine from July 2013 to August 2024. This paper analyzed clinical manifestations, laboratory findings and genetic testing.Results:This cohort comprised 15 pediatric patients (8 males and 7 females) with a diagnostic age of 5.3 (1.8,9.3) years. The major clinical presentations included abnormal gait (15/15), brachydactyly (11/15), genu varum (12/15), irregular metaphyseal changes (14/14) and epiphyseal dysplasia (14/14). Genetic analysis revealed 13 cases of pseudoachondroplasia and 2 multiple epiphyseal dysplasias cases associated with COMP gene variants. Fifteen variants were identified (8 pathogenic and 7 likely pathogenic), including 2 novel variants (c.1223A>G, c.1378G>C). Thirteen of these patients had variations clustered in exons 8-14 encoding the calmodulin-like domains, with c.1414_1419dupGACGAC emerging as a hotspot variant.Conclusions:COMP-related pseudoachondroplasia and multiple epiphyseal dysplasia predominantly manifest with gait abnormalities and skeletal deformities. COMP gene pathogenic variations were mainly located in calmodulin-like domains.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

A method that integrates the features of image patches from corneal lesions and conjunctival congestion-like complications is proposed to address the limitations of manual keratitis diagnosis(i.e.,time-consuming,laborious,high subjectivity)and the generally low accuracy of automatic keratitis diagnosis based on original slit-lamp images.Specifically,samples are acquired from the corneal and conjunctival regions.A cost-sensitive convolutional neural network is then used to extract and concatenate the high-level features of these image patches.After dimensionality reduction through principal component analysis,the processed features are input into the fully connected layer for classification.Trained and evaluated on 6414 slit-lamp images collected from Ningbo Eye Hospital,the proposed method achieves accuracies of 97.8%,98.6%,and 97.0%for keratitis,normal cornea,and other abnormal corneas,respectively.This method effectively integrates relevant features and provides a feasible solution for high-accuracy keratitis diagnosis.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.