Background: Cerebral hypoxia-ischemia impairs brain development in extremely preterm infants and is associated with poor neurological outcomes. Near-infrared spectroscopy (NIRS) is a noninvasive continuous monitoring method for regional cerebral oxygen saturation (rcSO2).Purpose: This study evaluated the clinical feasibility and neurological impact of a neurocritical care bundle that incorporates prolonged multidisciplinary hemodynamic monitoring and a stepwise management algorithm. Methods: Preterm infants with a gestational age (GA) ≤28 weeks or birth weight (BW) ≤1,000 g were prospectively enrolled in a bundle group subjected to NIRS for rcSO2, electrical cardiometry for cardiac output, and daily brain and cardiac echography during the first 72 hours of life. Monitoring was repeated weekly in the first month and then monthly until discharge or the term-equivalent age (TEA) was reached. We implemented a stepwise management algorithm for treating cerebral hypoxia. The primary outcome was a composite of mortality and adverse neurological events (structural abnormalities or electroencephalogram-confirmed seizures) before discharge. The secondary outcomes were the physiological pattern of rcSO2 within the initial 72 hours and up to discharge or TEA. Results: Thirty preterm infants (GA, 27.1±2.0 weeks; BW, 830±225 g) were enrolled in the bundle group. The mean time-averaged rcSO2 (66.8%±10.3%) was not associated with GA or BW. However, postnatal age appeared to influence physiological rcSO2 changes, given that rcSO2 values were higher during the initial 72 hours than at subsequent intervals. Seven infants (23.3%) had poor outcomes and significantly lower time-averaged rcSO2 (51.1% [50.0%–65.2%] vs. 71.8% [67.1%–73.1%], P=0.002). Multivariate regression indicated that a lower rcSO2 was an independent risk factor, and a 65% threshold showed an optimal predictive value for poor outcomes. Conclusion The neurocritical care bundle helped identify preterm infants at risk of cerebral hypoxia, and lower rcSO2 was an independent risk factor for composite mortality and adverse neurological outcomes.

Salvage surgery is an emerging option for carefully selected patients with advanced epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) whose disease remains controlled on tyrosine kinase inhibitor (TKI) therapy. Fourteen retrospective series report median progression-free survival (PFS) of 14–52 months and overall survival (OS) often exceeding 3 years, suggesting better disease control than continued TKI therapy alone. Although PFS generally improves, some cohorts show no OS advantage, probably because effective post-progression treatments dilute survival differences. Non-surgical local consolidative therapies remain essential for oligometastatic disease; nevertheless, resection yields intact specimens for comprehensive pathologic and molecular analysis.Access to tissue permits earlier identification of resistance mechanisms—most commonly the T790M mutation—more accurate prognostication, and more precise systemic-therapy selection. Comprehensive sampling can also identify histologic transformation and compound mutations that precede radiologic progression. Adverse prognostic factors include older age, high preoperative carcinoembryonic antigen levels, advanced pathological T stage, programmed death-ligand 1 ≥1%, and spread through air spaces. Salvage surgery is feasible and effective in carefully selected patients, especially those with oligoresidual disease and favorable tumor biology. Patient selection should integrate performance status, anatomic extent, histopathology, and genomic profile through multidisciplinary discussions. Despite regional differences (e.g., higher EGFR-mutation prevalence and wider adoption of minimally invasive approaches in East Asia) oncologic outcomes are comparable when selection criteria are applied consistently. Prospective trials are warranted to validate these retrospective observations, refine selection algorithms, establish optimal timing, and clarify how surgery can best be integrated with next-generation targeted agents and immunotherapies.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Diabetic foot (DF) is one of the most serious chronic complications of diabetes. The incidence rate among global diabetes patients is as high as 15% to 25%, and about 50% of patients will develop contralateral foot ulcers within 5 years after the first unilateral ulcer. As a non-invasive prevention and control solution, the application progress of functional insoles is mainly reflected in the following aspects:(1) Material innovation. The application of new composite materials and smart materials has significantly enhanced the pressure reduction effect and comfort. (2) Structural optimization. The development of multi-layer design and local pressure reduction structure has achieved more precise pressure distribution regulation. (3) Manufacturing process. 3D printing and parametric design have enabled the personalized customization of functional insoles. (4) Intelligent monitoring. It integrates functions such as pressure sensing and temperature monitoring, achieving real-time monitoring and early warning of foot conditions. Clinical research has confirmed that personalized functional insoles could reduce the incidence of foot ulcers and shorten the healing time of ulcers. At present, the research hotspots mainly focus on the development of smart materials, the construction of multi-functional integration and remote monitoring systems. However, in-depth research is still needed in the aspects of biomechanical mechanisms, standardized evaluation systems and long-term efficacy assessment. The development of future functional insoles should focus on the coordinated advancement of "personalization-intelligence-standardization", with the aim of providing more effective solutions for the prevention and treatment of DF.
Humans ; Diabetic Foot/therapy* ; Foot Orthoses

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.