Effects of rhythmic visual cues on cortical activation and functional connectivity features during stepping: an fNIRS study.

Introduction: Rhythmic visual cues (RVCs) may influence gait initiation by modulating cognition resources. However, it is unknown how RVCs modulate cognitive resources allocation during gait movements. This study focused on investigating the effects of RVCs on cortical hemodynamic response features during stepping to evaluate the changes of cognitive resources. Methods: We recorded cerebral hemoglobin concentration changes of 14 channels in 17 healthy subjects using functional near-infrared spectroscopy (fNIRS) during stepping tasks under exposure to RVCs and non-rhythmic visual cues (NRVCs). We reported mean oxygenated hemoglobin (HbO) concentration changes, ß-values, and functional connectivity (FC) between channels. Results: The results showed that, the RVC conditions revealed lower HbO responses compared to the NRVC conditions during the preparation and early stepping. Correspondingly, the ß-values reflected that RVCs elicited lower hemodynamic responses than NRVCs, and there was a decreasing trend in stimulus-evoked cortical activation as the task progressed. However, the FC between channels were stronger under RVCs than under NRVCs during the stepping progress, and there were more significant differences in FC during the early stepping. Discussion: In conclusion, there were lower cognitive demand and stronger FC under RVC conditions than NRVC conditions, which indicated higher efficiency of cognitive resources allocation during stepping tasks. This study may provide a new insight for further understanding the mechanism on how RVCs alleviate freezing of gait.

Short Step Length Estimation for Parkinson's Disease Patients by Using Fusion Data From Camera-IMU in Smart Glasses.

Shortened step length is a prominent motor abnormality in Parkinson's disease (PD) patients. Current methods for estimating short step length have the limitation of relying on laboratory scenarios, wearing multiple sensors, and inaccurate estimation results from a single sensor. In this paper, we proposed a novel method for estimating short step length for PD patients by fusing data from camera and inertial measurement units in smart glasses. A simultaneous localization and mapping technique and acceleration thresholding-based step detection technique were combined to realize the step length estimation. Two sets of experiments were conducted to demonstrate the performance of our method. In the first set of experiments with 12 healthy subjects, the proposed method demonstrated an average error of 8.44% across all experiments including six fixed step lengths below 30 cm. The second set of straightly walking experiments were implemented with 12 PD patients, the proposed method exhibited an average error of 4.27% compared to a standard gait evaluation technique in total walking distance. Notably, among the results of step lengths below 40 cm, our method agreed with the standard technique (R 2=0.8659). This study offers a promising approach for estimating short step length for PD patients during smart glasses-based gait training.

Association of KDR mutation with better clinical outcomes in pan-cancer for immune checkpoint inhibitors.

Kinase insert domain receptor (KDR) activation is associated with the immunosuppressive microenvironment. However, the efficacy of immunotherapy in patients with KDR mutations is still unclear. To investigate the relationship between KDR gene mutations and the prognosis of pan-cancer, and whether immune checkpoint inhibitors (ICIs) may improve the prognosis of patients with KDR mutations, we analyzed public cohorts of pan-cancer immunotherapeutic patients including genomic and clinical data.Further analysis was performed on an internal validation data set including 67 non-small cell lung cancer. Through bioinformatics analysis, potential mechanism was studied in TCGA data. We found better responses to ICIs in patients with KDR mutation from pan-cancer public datasets (objective response rate [ORR], 45.0% vs 25.1%, P=0.0058; progression-free survival [PFS], P=0.039, HR=0.586, 95% CI 0.353-0.973) and validation cohort (overall survival (OS), P=0.05, HR=0.62; 95% CI, 0.38-1.00). Our NSCLC cohort verified the value of KDR mutation in predicting better clinical outcomes, including ORR (70.0% vs 22.81%, P=0.0057) and PFS (HR=0.158; 95% CI, 0.045-0.773, P=0.007). KDR mutation was associated with tumor mutation burden high, neoantigen burden and immune cellular activities. Meanwhile, KDR mutation was indicative of an immune-hot status, characterized by higher expression of PD-L1 and abundance of cytotoxic lymphocytes. KDR mutations may be potential positive predictors for pan-cancer received ICIs.

Deleterious AHNAK2 Mutation as a Novel Biomarker for Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer.

Immune checkpoint inhibitors (ICIs) have exhibited promising efficacy in non-small cell lung cancer (NSCLC), but the response occurs in only a minority of patients. In clinic, biomarkers such as TMB (tumor mutation burden) and PD-L1 (programmed cell death 1 ligand 1) still have their limitations in predicting the prognosis of ICI treatment. Hence, reliable predictive markers for ICIs are urgently needed. A public immunotherapy dataset with clinical information and mutational data of 75 NSCLC patients was obtained from cBioPortal as the discovery cohort, and another immunotherapy dataset of 249 patients across multiple cancer types was collected as the validation. Integrated bioinformatics analysis was performed to explore the potential mechanism, and immunohistochemistry studies were used to verify it. AHNAK nucleoprotein 2 (AHNAK2) was reported to have pro-tumor growth effects across multiple cancers, while its role in tumor immunity was unclear. We found that approximately 11% of the NSCLC patients harbored AHNAK2 mutations, which were associated with promising outcomes to ICI treatments (ORR, p = 0.013). We further found that AHNAK2 deleterious mutation (del-AHNAK2 mut) possessed better predictive function in NSCLC than non-deleterious AHNAK2 mutation (PFS, OS, log-rank p < 0.05), potentially associated with stronger tumor immunogenicity and an activated immune microenvironment. This work identified del-AHNAK2 mut as a novel biomarker to predict favorable ICI response in NSCLC.

Deep Learning-Based Computed Tomography Imaging to Diagnose the Lung Nodule and Treatment Effect of Radiofrequency Ablation.

This study aimed to detect and diagnose the lung nodules as early as possible to effectively treat them, thereby reducing the burden on the medical system and patients. A lung computed tomography (CT) image segmentation algorithm was constructed based on the deep learning convolutional neural network (CNN). The clinical data of 69 patients with lung nodules diagnosed by needle biopsy and pathological comprehensive diagnosis at hospital were collected for specific analysis. The CT image segmentation algorithm was used to distinguish the nature and volume of lung nodules and compared with other computer aided design (CAD) software (Philips ISP). 69 patients with lung nodules were treated by radiofrequency ablation (RFA). The results showed that the diagnostic sensitivity of the CT image segmentation algorithm based on the CNN was obviously higher than that of the Philips ISP for solid nodules <5 mm (63 cases vs. 33 cases) (P < 0.05); it was the same result for the subsolid nodule <5 mm (33 case vs. 5 cases) (P < 0.05) that was slightly higher for solid and subsolid nodules with a diameter of 5-10 mm (37 cases vs. 28 cases) (P < 0.05). In addition, the CNN algorithm can reach all detection for calcified nodules and pleural nodules (7 cases; 5 cases), and the diagnostic sensitivities were much better than those of Philips ISP (2 cases; 3 cases) (P < 0.05). Patients with pulmonary nodules treated by RFA were in good postoperative condition, with a half-year survival rate of 100% and a one-year survival rate of 72.4%. Therefore, it could be concluded that the CT image segmentation algorithm based on the CNN could effectively detect and diagnose the lung nodules early, and the RFA could effectively treat the lung nodules.

Flexible Hard Coatings with Self-Evolution Behavior in a Low Earth Orbit Environment.

Lightweight, long lifetime, and flexible polymer membrane-based structures, which are tightly folded on the ground and then unfolded in space, suffer from repeated bending before launching and fatal erosion on exposure to atomic oxygen (AO) in a low Earth orbit (LEO). Although various AO-resistant coatings have been developed, a coating that can simultaneously meet the critical requirements for the mechanical robustness and long-term protection of polymer membranes is rare. Here, we fabricated a coating with mechanical robustness and long-term space endurance, starting from an inorganic polymer precursor. A hybrid coating with a nanoscale polymer/silica bicontinuous phase is first prepared on the ground, which exhibits outstanding flexibility and excellent abrasion resistance. Then, the coating shows an in situ self-evolution behavior under AO and ultraviolet (UV) synergism to afford dense and crack-free silica coating with outstanding endurance. Our strategy displays great potential for protecting deployable membrane structures serving in the LEO.

Individualized predictions of early isolated distal deep vein thrombosis in patients with acute ischemic stroke: a retrospective study.

BACKGROUND: Although isolated distal deep vein thrombosis (IDDVT) is a clinical complication for acute ischemic stroke (AIS) patients, very few clinicians value it and few methods can predict early IDDVT. This study aimed to establish and validate an individualized predictive nomogram for the risk of early IDDVT in AIS patients. METHODS: This study enrolled 647 consecutive AIS patients who were randomly divided into a training cohort (n = 431) and a validation cohort (n = 216). Based on logistic analyses in training cohort, a nomogram was constructed to predict early IDDVT. The nomogram was then validated using area under the receiver operating characteristic curve (AUROC) and calibration plots. RESULTS: The multivariate logistic regression analysis revealed that age, gender, lower limb paralysis, current pneumonia, atrial fibrillation and malignant tumor were independent risk factors of early IDDVT; these variables were integrated to construct the nomogram. Calibration plots revealed acceptable agreement between the predicted and actual IDDVT probabilities in both the training and validation cohorts. The nomogram had AUROC values of 0.767 (95% CI: 0.742-0.806) and 0.820 (95% CI: 0.762-0.869) in the training and validation cohorts, respectively. Additionally, in the validation cohort, the AUROC of the nomogram was higher than those of the other scores for predicting IDDVT. CONCLUSIONS: The present nomogram provides clinicians with a novel and easy-to-use tool for the prediction of the individualized risk of IDDVT in the early stages of AIS, which would be helpful to initiate imaging examination and interventions timely.

Weaker Braking Force, A New Marker of Worse Gait Stability in Alzheimer Disease.

Background: Braking force is a gait marker associated with gait stability. This study aimed to determine the alteration of braking force and its correlation with gait stability in Alzheimer disease (AD). Methods: A total of 32 AD patients and 32 healthy controls (HCs) were enrolled in this study. Gait parameters (braking force, gait variability, and fall risk) in the walking tests of Free walk, Barrier, and Count backward were measured by JiBuEn® gait analysis system. Gait variability was calculated by the coefficient of variation (COV) of stride time, stance time, and swing time. Results: The braking force of AD was significantly weaker than HCs in three walking tests (P < 0.001, P < 0.001, P = 0.007). Gait variability of AD showed significant elevation than HCs in the walking of Count backward (COVstride: P = 0.013; COVswing: P = 0.006). Fall risk of AD was significantly higher than HCs in three walking tests (P = 0.001, P = 0.001, P = 0.001). Braking force was negatively associated with fall risks in three walking tests (P < 0.001, P < 0.001, P < 0.001). There were significant negative correlations between braking force and gait variability in the walking of Free walk (COVstride: P = 0.018; COVswing: P = 0.013) and Barrier (COVstride: P = 0.002; COVswing: P = 0.001), but not Count backward (COVstride: P = 0.888; COVswing: P = 0.555). Conclusion: Braking force was weaker in AD compared to HCs, reflecting the worse gait stability of AD. Our study suggests that weakening of braking force may be a new gait marker to indicate cognitive and motor impairment and predict fall risk in AD.

Individualized Prediction Of Stroke-Associated Pneumonia For Patients With Acute Ischemic Stroke.

BACKGROUND: Stroke-associated pneumonia (SAP) is a serious and common complication in stroke patients. PURPOSE: We aimed to develop and validate an easy-to-use model for predicting the risk of SAP in acute ischemic stroke (AIS) patients. PATIENTS AND METHODS: The nomogram was established by univariate and multivariate binary logistic analyses in a training cohort of 643 AIS patients. The prediction performance was determined based on the receiver operating characteristic curve (ROC) and calibration plots in a validation cohort (N=340). Individualized clinical decision-making was conducted by weighing the net benefit in each AIS patient by decision curve analysis (DCA). RESULTS: Seven predictors, including age, NIHSS score on admission, atrial fibrillation, nasogastric tube intervention, mechanical ventilation, fibrinogen, and leukocyte count were incorporated to construct the nomogram model. The nomogram showed good predictive performance in ROC analysis [AUROC of 0.845 (95% CI: 0.814-0.872) in training cohort, and 0.897 (95% CI: 0.860-0.927) in validation cohort], and was superior to the A2DS2, ISAN, and PANTHERIS scores. Furthermore, the calibration plots showed good agreement between actual and nomogram-predicted SAP probabilities, in both training and validation cohorts. The DCA confirmed that the SAP nomogram was clinically useful. CONCLUSION: Our nomogram may provide clinicians with a simple and reliable tool for predicting SAP based on routinely available data. It may also assist clinicians with respect to individualized treatment decision-making for patients differing in risk level.

Reduced Vitamin D Levels are Associated with Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke.

BACKGROUND AND AIM: Stroke-associated pneumonia (SAP) is a common complication in patients with acute ischemic stroke (AIS). This study explored the potential relationship between serum vitamin D levels and SAP. METHODS: This study recruited 863 consecutive AIS patients. In-hospital SAP was defined as a complication that occurred after stroke, during hospitalization, that was confirmed radiographically. Serum vitamin D levels were measured within 24 hrs of admission and the patients were divided into vitamin D sufficient (>50 nmol/L), insufficient (25-50 nmol/L), and deficient (<25 nmol/L) groups. RESULTS: In this study, 102 (11.8%) patients were diagnosed with SAP. Compared to the patients without SAP, patients with SAP had significantly lower vitamin D levels (P = 0.023). The incidence of SAP was significantly higher in patients with vitamin D deficiency than in those with vitamin D insufficiency or sufficiency (21.2% vs 16.2% & 9.5%, P = 0.006). After adjusting for confounders, vitamin D deficiency and insufficiency were independently associated with SAP (OR = 3.034, 95% CI = 1.207-7.625, P = 0.018; OR = 1.921, 95% CI = 1.204-3.066, P = 0.006, respectively). In multiple-adjusted spline regression, vitamin D levels showed a linear association with the risk of SAP (P < 0.001 for linearity). CONCLUSION: Reduced vitamin D is a potential risk factor of in-hospital SAP, which can help clinicians identify high-risk SAP patients.

Low levels of serum magnesium are associated with poststroke cognitive impairment in ischemic stroke patients.

PURPOSE: Population-based studies have revealed a high prevalence of cognitive impairment after stroke. We aimed to determine the impact of serum magnesium (Mg2+) levels on the occurrence of poststroke cognitive impairment (PSCI). PATIENTS AND METHODS: Acute ischemic stroke patients (n = 327) were enrolled in our study and serum Mg2+ levels were assessed on admission. The cognitive performance of each patient was evaluated using the Mini-Mental State Examination (MMSE) at a 1-month follow-up visit. RESULTS: One hundred five (32.1%) patients were diagnosed with PSCI at 1-month poststroke. The serum Mg2+ levels in both the PSCI group and the non-PSCI group were significantly lower than those in normal control group (P<0.001). In addition, the PSCI group had lower levels of serum Mg2+ compared to the non-PSCI group (P=0.003). In the binary logistic regression analysis, a serum Mg2+ level of ≤0.82 mmol/L was significantly associated with an increased risk of developing PSCI by the 1-month follow-up (OR 2.236, 95% CI 1.232-4.058, P=0.008), as was age (OR 1.043, 95% CI 1.014-1.073, P=0.003). CONCLUSION: Our results demonstrate the existence of a significant association between low levels of serum Mg2+ and the occurrence of PSCI 1-month poststroke, and these results suggest that low levels of serum Mg2+ on admission may serve as a risk factor for developing PSCI by 1-month poststroke.

Low Tri-iodothyronine Syndrome Is Associated With Cognitive Impairment in Patients With Acute Ischemic Stroke: A Prospective Cohort Study.

OBJECTIVE: Low tri-iodothyronine (T3) syndrome is a predictor of poor prognosis in patients with stroke. Poststroke cognitive impairment (PSCI) is a common and important complication after stroke. The association between low T3 syndrome and PSCI is unclear. We aimed to explore the potential relationship between low T3 syndrome and PSCI in the acute phase of ischemic stroke at a 1-month follow-up visit. METHODS: In total, 314 ischemic stroke patients were consecutively enrolled in the study and followed up at 1 month. Thyroid hormones were measured within 24 hours after admission. Cognitive function was evaluated by the Mini-Mental State Exam (MMSE) 1 month after acute ischemic stroke. Cognitive impairment was defined as an MMSE score of less than 27. Cognitive impairment severity was categorized as severe, mild, or none (MMSE score <23, 23-26, or ≥27, respectively). RESULTS: According to the MMSE score, 182 participants (58.0%) had cognitive impairment 1 month after stroke. Patients with low T3 syndrome were more prone to have cognitive impairment than patients with normal levels of T3 (p < 0.001). After adjusting for potential confounders in our logistic model, low T3 syndrome was independently associated with PSCI (odds ratio 4.319, 95% confidence interval 1.553-12.013, p = 0.005). CONCLUSION: Low T3 syndrome in the acute phase of ischemic stroke was associated with a higher prevalence of 1-month PSCI, independently of established risk factors.

The association between mean platelet volume levels and poststroke depression.

OBJECTIVE: High levels of mean platelet volume (MPV) had been found in depression subjects. We sought to examine the relationship between MPV and poststroke depression (PSD). METHODS: One hundred and eighty-five patients with acute ischemic stroke were enrolled in our study. Peripheral venous blood samples were drawn at admission and MPV levels were measured by the automated hematology analyzer. Patients with a HAMD-17 score >7 were diagnosed as having PSD. RESULTS: We found that 60 patients (32.4%) developed PSD, the MPV levels in PSD patients were significantly higher (9.3 ± 1.8 fl) compared to non-PSD patients (8.5 ± 1.6 fl). High MPV levels (≥9.1 fl) were independently correlated with PSD (OR 2.762, 95% CI 1.138-6.702, p = 0.025). CONCLUSIONS: Patients with higher levels of MPV at admission were correlated with the development of PSD at 1 month after stroke and might be a predictor of its presence.

Coffee consumption and risk of lung cancer: a meta-analysis.

Epidemiologic studies have evaluated the potential association between coffee consumption and lung cancer risk. However, results were inconsistent. To clarify the role of coffee in lung cancer, we conducted a meta-analysis on this topic. We searched PubMed and EMBASE databases (from 1966 to January 2009) and the reference lists of retrieved articles. Study-specific risk estimates were pooled using random-effects model. Five prospective studies and 8 case-control studies involving 5347 lung cancer cases and 104,911 non-cases were included in this meta-analysis. The combined results indicated a significant positive association between highest coffee intake and lung cancer [relative risk (RR)=1.27, 95% confidence interval (CI)=1.04-1.54). Furthermore, an increase in coffee consumption of 2 cups/day was associated with a 14% increased risk of developing lung cancer (RR=1.14, 95% CI=1.04-1.26). In stratified analyses, the highest coffee consumption was significantly associated with increased risk of lung cancer in prospective studies, studies conducted in America and Japan, but borderline significantly associated with decreased risk of lung cancer in non-smokers. In addition, decaffeinated coffee drinking was associated with decreased lung cancer risk, although the number of studies on this topic was relative small. In conclusion, results from this meta-analysis indicate that high or an increased consumption of coffee may increase the risk of lung cancer. Because the residual confounding effects of smoking or other factors may still exist, these results should be interpreted with caution.

Green tea, black tea consumption and risk of lung cancer: a meta-analysis.

Studies investigating the association of green tea and black tea consumption with lung cancer risk have reported inconsistent findings. To provide a quantitative assessment of this association, we conducted a meta-analysis on the topic. Studies were identified by a literature search in PubMed from 1966 to November 2008 and by searching the reference lists of relevant studies. Summary relative risk (RR) estimates and their corresponding 95% confidence intervals (CIs) were calculated based on random-effects model. Our meta-analysis included 22 studies provided data on consumption of green tea or black tea, or both related to lung cancer risk. For green tea, the summary RR indicated a borderline significant association between highest green tea consumption and reduced risk of lung cancer (RR=0.78, 95% CI=0.61-1.00). Furthermore, an increase in green tea consumption of two cups/day was associated with an 18% decreased risk of developing lung cancer (RR=0.82, 95% CI=0.71-0.96). For black tea, no statistically significant association was observe through the meta-analysis (highest versus non/lowest, RR=0.86, 95% CI=0.70-1.05; an increment of two cups/day, RR=0.82, 95% CI=0.65-1.03). In conclusion, our data suggest that high or an increase in consumption of green tea but not black tea may be related to the reduction of lung cancer risk.