Electrical impedance tomography (EIT) represents an emerging medical functional imaging technology, which operates by applying safe-to-human excitation currents through surface-mounted electrodes, measuring boundary voltages between electrodes, and selecting appropriate image reconstruction algorithms to visualize resistivity in tomographic cross-sections. Compared to traditional medical imaging techniques, EIT offers non-invasive and radiation-free operation, high sensitivity to tissue resistivity changes, and superior temporal resolution, meeting the real-time requirements of clinical dynamic condition monitoring. This paper comprehensively reviews the research status of brain EIT technology, systematically summarizes its advantages and technical limitations in perioperative applications, and prospectively forecasts future development directions of perioperative brain EIT based on current research foundations and clinical application demands, with the aim of providing methodological references for further optimization and clinical promotion of this technology.
Electric Impedance ; Tomography/methods* ; Humans ; Brain/diagnostic imaging*

Depression poses a severe threat to human health, placing a heavy burden on society and families. Yet, challenges remain in prevention and treatment. Lifestyle medicine aims to use evidence-based lifestyle interventions to prevent, treat, and even reverse chronic progression. Exploring breakthroughs in depression intervention prevention and treatment from the perspective of lifestyle medicine presents an opportunity for interdisciplinary research. Future research should focus on leveraging implementation science, cost-effectiveness analysis, and understanding optimal pathways and mechanisms of action. This article provides a review of this important topic.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Depression poses a severe threat to human health, placing a heavy burden on society and families. Yet, challenges remain in prevention and treatment. Lifestyle medicine aims to use evidence-based lifestyle interventions to prevent, treat, and even reverse chronic progression. Exploring breakthroughs in depression intervention prevention and treatment from the perspective of lifestyle medicine presents an opportunity for interdisciplinary research. Future research should focus on leveraging implementation science, cost-effectiveness analysis, and understanding optimal pathways and mechanisms of action. This article provides a review of this important topic.

Digital therapy shows promise in providing precise assessments and enhancing the efficacy of treatments for mental illness,offering advantages such as convenience,flexibility,and the potential to reduce costs by shifting towards preventive care.This article reviews the development and benefits of digital therapy in mental health care and discusses the challenges it faces,including concerns over privacy,ethics,security,acces-sibility issues,digital divides,and the lack of sufficient clinical validation and standardization.It also highlights specific risks to mental health patients and explores potential future developments such as integration with brain-computer interfaces and neurofeedback,the use of robot therapists based on large language models,applications of virtual reality or the metaverse,and combinations with traditional physical treatments and medications.The author calls for urgent policy recommendations to refine regulations,establish unified evidence standards,enhance train-ing and education for healthcare providers and patients,and to build multidisciplinary collaborative mechanisms to advance personalized and effective digital therapy in mental health.

This article introduces a high-magnification electronic endoscope system that utilizes a continuous zoom optical design,enabling high-magnification imaging at the cellular level.By selecting an appropriate initial retrofocus structure,the optimized modulation transfer function(MTF)curve of the zoom objective lens approaches the diffraction limit.Additionally,the tip and operation parts of the system incorporate modular gas-tight sealing and multiple layers of protective structure.The design employs efficient sealing materials and precise packaging techniques to ensure the system's sealing performance.The experimental results indicate that,under conventional imaging,the resolution is equivalent to 39.37 μm in object space,and the field of view angle is larger than 140 degrees.At magnified imaging,the resolution is equivalent to 2.78 μm in object space,and the observed actual field of view is greater than 800 μm×700 μm.When used with a 26-inch display monitor,the high-magnification electronic endoscope can achieve 500×optical magnification,allowing for the observation of features at the cellular level.Currently,this product has successfully achieved mass production and has undergone multiple animal trials,demonstrating its wide range of potential applications and significant clinical value.

Acyl-CoA synthetase long chain family member 5 (ACSL5), is a member of the acyl-CoA synthetases (ACSs) family that activates long chain fatty acids by catalyzing the synthesis of fatty acyl-CoAs. The dysregulation of ACSL5 has been reported in some cancers, such as glioma and colon cancers. However, little is known about the role of ACSL5 in acute myeloid leukemia (AML). We found that the expression of ACSL5 was higher in bone marrow cells from AML patients compared with that from healthy donors. ACSL5 level could serve as an independent prognostic predictor of the overall survival of AML patients. In AML cells, the ACSL5 knockdown inhibited cell growth both in vitro and in vivo. Mechanistically, the knockdown of ACSL5 suppressed the activation of the Wnt/β-catenin pathway by suppressing the palmitoylation modification of Wnt3a. Additionally, triacsin c, a pan-ACS family inhibitor, inhibited cell growth and robustly induced cell apoptosis when combined with ABT-199, the FDA approved BCL-2 inhibitor for AML therapy. Our results indicate that ACSL5 is a potential prognosis marker for AML and a promising pharmacological target for the treatment of molecularly stratified AML.
Humans ; Antineoplastic Agents/therapeutic use* ; Apoptosis ; beta Catenin/metabolism* ; Biomarkers, Tumor/metabolism* ; Cell Line, Tumor ; Coenzyme A Ligases/metabolism* ; Leukemia, Myeloid, Acute/metabolism* ; Lipoylation ; Prognosis ; Wnt Signaling Pathway

Abivertinib, a third-generation tyrosine kinase inhibitor, is originally designed to target epidermal growth factor receptor (EGFR)-activating mutations. Previous studies have shown that abivertinib has promising antitumor activity and a well-tolerated safety profile in patients with non-small-cell lung cancer. However, abivertinib also exhibited high inhibitory activity against Bruton's tyrosine kinase and Janus kinase 3. Given that these kinases play some roles in the progression of megakaryopoiesis, we speculate that abivertinib can affect megakaryocyte (MK) differentiation and platelet biogenesis. We treated cord blood CD34⁺ hematopoietic stem cells, Meg-01 cells, and C57BL/6 mice with abivertinib and observed megakaryopoiesis to determine the biological effect of abivertinib on MK differentiation and platelet biogenesis. Our in vitro results showed that abivertinib impaired the CFU-MK formation, proliferation of CD34⁺ HSC-derived MK progenitor cells, and differentiation and functions of MKs and inhibited Meg-01-derived MK differentiation. These results suggested that megakaryopoiesis was inhibited by abivertinib. We also demonstrated in vivo that abivertinib decreased the number of MKs in bone marrow and platelet counts in mice, which suggested that thrombopoiesis was also inhibited. Thus, these preclinical data collectively suggested that abivertinib could inhibit MK differentiation and platelet biogenesis and might be an agent for thrombocythemia.
Acrylamides/pharmacology* ; Animals ; Blood Platelets/drug effects* ; Cell Differentiation ; Megakaryocytes/drug effects* ; Mice ; Mice, Inbred C57BL ; Piperazines/pharmacology* ; Pyrimidines/pharmacology*

Intelligent and precision medical treatment is the future development trend of surgical operations. We proposed a core architecture of orthopedic robots with human-like thinking based on the growing demand for orthopedic robots and disadvantages of current robots, it consists of brain, eyes and hands three modules according to functions. The architecture design is extremely in line with the doctor's logic so that the work process of the orthopedic robot is similar to the process of traditional surgery which is mainly done by the doctor's brain-eye-hand coordination. It realizes the digitization of the doctor's thinking, the immediacy and visualization of surgical information and the accuracy of surgical operation process. The clinical application proved that the orthopedic robot has the advantages of higher accuracy, less radiation and shorter operation time, which can be further promoted clinically.
Hand ; Humans ; Robotics