The efficacy and safety of transcutaneous auricular vagus nerve stimulation for patients with minimally conscious state: a sham-controlled randomized double-blind clinical trial.

Background: Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a potentially effective neuromodulation technique for addressing neurological disorders, including disorders of consciousness. Expanding upon our prior clinical study, which demonstrated the superior effectiveness of a 4-week taVNS treatment in patients with minimally conscious state (MCS) compared to those in a vegetative state/unresponsive wakefulness state, the aim of this investigation was to evaluate the safety and therapeutic efficacy of taVNS in individuals with MCS through a sham-controlled randomized double-blind clinical trial. Methods: A cohort of 50 adult patients (male = 33, female = 17) diagnosed with a MCS were randomly assigned to either the active taVNS (N = 25) or sham taVNS (N = 25) groups. The treatment period lasted for 4 weeks, followed by an 8-week follow-up period. The Coma Recovery Scale-Revised (CRS-R) and Glasgow Coma Scale (GCS) were administered at baseline and weekly during the initial 4 weeks. Additionally, the Disability Rating Scale (DRS) was used to assess the patients' functional abilities via telephone at week 12. Furthermore, various neurophysiological measures, including electroencephalogram (EEG), upper-limb somatosensory evoked potentials (USEP), brainstem auditory evoked potentials (BAEP), and P300 event-related potentials (P300), were employed to monitor changes in brain activity and neural conduction pathways. Results: The scores for the active taVNS group in the CRS-R and GCS showed greater improvement over time compared to the sham taVNS group (CRS-R: 1-week, Z = -1.248, p = 0.212; 2-week, Z = -1.090, p = 0.276; 3-week, Z = -2.017, p = 0.044; 4-week, Z = -2.267, p = 0.023. GCS: 1-week, Z = -1.325, p = 0.185; 2-week, Z = -1.245, p = 0.213; 3-week, Z = -1.848, p = 0.065; 4-week, Z = -1.990, p = 0.047). Additionally, the EEG, USEP, BAEP, and P300 also demonstrated significant improvement in the active taVNS group compared to the sham taVNS group at week 4 (EEG, Z = -2.086, p = 0.037; USEP, Z = -2.014, p = 0.044; BAEP, Z = -2.298, p = 0.022; P300 amplitude, Z = -1.974, p = 0.049; P300 latency, t = 2.275, p = 0.027). Subgroup analysis revealed that patients with MCS derived greater benefits from receiving taVNS treatment earlier (CRS-R, Disease duration ≤ 1-month, mean difference = 8.50, 95% CI = [2.22, 14.78], p = 0.027; GCS, Disease duration ≤ 1-month, mean difference = 3.58, 95% CI = [0.14, 7.03], p = 0.044). By week 12, the active taVNS group exhibited lower Disability Rating Scale (DRS) scores compared to the sham taVNS group (Z = -2.105, p = 0.035), indicating a more favorable prognosis for MCS patients who underwent taVNS. Furthermore, no significant adverse events related to taVNS were observed during treatment. Conclusion: The findings of this study suggest that taVNS may serve as a potentially effective and safe intervention for facilitating the restoration of consciousness in individuals diagnosed with MCS. This therapeutic approach appears to enhance cerebral functioning and optimize neural conduction pathways. Clinical trial registration: http://www.chictr.org.cn, Identifier ChiCTR2200066629.

Stimulation of vagus nerve for patients with disorders of consciousness: a systematic review.

Purpose: The purpose of this study is to evaluate the efficacy and safety of stimulating the vagus nerve in patients with disorders of consciousness (DOCs). Methods: A comprehensive systematic review was conducted, encompassing the search of databases such as PubMed, CENTRAL, EMBASE and PEDro from their inception until July 2023. Additionally, manual searches and exploration of grey literature were performed. The literature review was conducted independently by two reviewers for search strategy, selection of studies, data extraction, and judgment of evidence quality according to the American Academy of Cerebral Palsy and Developmental Medicine (AACPDM) Study Quality Scale. Results: A total of 1,269 articles were retrieved, and 10 studies met the inclusion criteria. Among these, there were three case reports, five case series, and only two randomized controlled trials (RCTs). Preliminary studies have suggested that stimulation of vagus nerve can enhance the levels of DOCs in both vegetative state/unresponsive wakefulness state (VS/UWS) and minimally conscious state (MCS). However, due to a lack of high-quality RCTs research and evidence-based medical evidence, no definitive conclusion can be drawn regarding the intervention's effectiveness on consciousness level. Additionally, there were no significant adverse effects observed following stimulation of vagus nerve. Conclusion: A definitive conclusion cannot be drawn from this systematic review as there was a limited number of eligible studies and low-quality evidence. The findings of this systematic review can serve as a roadmap for future research on the use of stimulation of vagus nerve to facilitate recovery from DOCs.

Dynamic Prognostic Score to Predict Survival in East Asian Elderly Populations with Dysphagia.

INTRODUCTION: Dysphagia is a common disorder in older adults, leading to severe complications, including aspiration pneumonia, dehydration, malnutrition, weight loss, and even death. However, no prognostic model has been developed to predict the prognosis of older adults with dysphagia. METHODS: Data from patients with dysphagia at a single center were retrospectively reviewed between 2014 and 2017. All data were obtained from the Dryad Digital Repository. The least absolute shrinkage and selection operator regression model was used to select potentially relevant features. Multiple Cox proportional hazard analysis was used to develop a model based on the training set. RESULTS: The nomogram comprised age, sex, percutaneous endoscopic gastrostomy, chronic heart failure, total lymphocyte count, daily calorie intake, and severe pneumonia, which provided favorable calibration and discrimination in the training dataset, with AUCs for the 1-year, 2-year, and 3-year survival predictions of 0.833, 0.871, and 0.886, respectively. Furthermore, it showed acceptable discrimination in the validation cohort, with AUCs for the 1-year, 2-year, and 3-year survival predictions of 0.884, 0.834, and 0.782, respectively. Moreover, the decision curve analysis results revealed that the nomogram was clinically beneficial. CONCLUSION: A nomogram, combining seven demographic and clinical factors, provided an excellent preoperative prediction of survival probability in older individuals with dysphagia. This predictive model can be used as a reference to assist clinicians in making clinical decisions.

Prognostic model for aneurysmal subarachnoid hemorrhage patients requiring mechanical ventilation.

OBJECTIVE: Aneurysmal subarachnoid hemorrhage (aSAH) is a major cause of death and disability worldwide and imposes serious burdens on society and individuals. However, predicting the long-term outcomes in aSAH patients requiring mechanical ventilation remains challenging. We sought to establish a model utilizing the Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression to estimate the prognosis of aSAH patients requiring mechanical ventilation, based on regularly utilized and easily accessible clinical variables. METHODS: Data were retrieved from the Dryad Digital Repository. Potentially relevant features were selected using LASSO regression analysis. Multiple Cox proportional hazards analyses were performed to develop a model using the training set. Receiver operating characteristics and calibration curves were used to assess its predictive accuracy and discriminative power. Kaplan-Meier and decision curve analyses (DCA) were used to evaluate the clinical utility of the model. RESULTS: Independent prognostic factors, including the Simplified Acute Physiology Score 2, early brain injury, rebleeding, and length of intensive care unit stay, were identified and included in the nomogram. In the training set, the area under the curve values for 1-, 2-, and 4-year survival predictions were 0.82, 0.81, and 0.80, respectively. In the validation set, the nomogram exhibited excellent discrimination ability and good calibration. Moreover, DCA demonstrated that the nomogram was clinically beneficial. Finally, a web-based nomogram was constructed (https://rehablitation.shinyapps.io/aSAH). INTERPRETATION: Our model is a useful tool for accurately predicting long-term outcomes in patients with aSAH who require mechanical ventilation and can assist in making individualized interventions by providing valuable information.

Effect of single and combined median nerve stimulation and repetitive transcranial magnetic stimulation in patients with prolonged disorders of consciousness: a prospective, randomized, single-blinded, controlled trial.

Objective: To investigate the efficacy of median nerve stimulation (MNS) combined with repetitive transcranial magnetic stimulation (rTMS), MNS alone, and rTMS alone in elevating the level of consciousness in patients with prolonged disorders of consciousness (pDOC). Participants and methods: We enrolled 75 eligible inpatients suffering from pDOC as a result of traumatic or non-traumatic brain injury. Participants were randomly assigned to one of the following three treatment groups: (1) rTMS+sham-MNS; (2) MNS + sham-rTMS; or (3) MNS + rTMS. The rTMS protocol involved stimulation above the left dorsolateral prefrontal cortex at a 10 Hz frequency and 90% resting motor threshold. The MNS protocol involved the delivery of a 15-20 mA current at the median nerve point 2 cm from the wrist crease of the right distal forearm. The primary outcome was the change from baseline of the Coma Recovery Scale-Revised (CRS-R) score after treatment. Secondary outcomes included post-treatment changes from baseline of the Glasgow Coma Scale (GCS) score, awaken ratio, electroencephalography (EEG) scores, and the latency and amplitude of N20 on somatosensory evoked potentials. Results: Before the intervention, there were no significant differences between groups in the CRS-R, GCS scores, age, duration of pDOC, clinical diagnosis, EEG scores, latency and amplitude of N20, sex, job, marital status, education level, or disease etiology. Within the three groups, the total CRS-R, GCS scores and amplitude of N20 on both side significantly increased and latency of N20 on poor side significantly decreased post-intervention. Significantly greater improvement in CRS-R, GCS total scores, amplitude of N20 on both side and latency of N20 on the poor side were observed in the MNS + TMS group compared to those of the groups receiving rTMS alone or MNS alone. The patients receiving TMS and MNS intervention showed a greater EEG activity improvement, and the EEG activity improved ratio significantly differ between groups, while there were no significant differences in the awakening ratios between the three groups. Conclusion: The combination of MNS + rTMS was more efficacious in improving the level of consciousness than MNS alone or rTMS alone in patients with pDOC.

Correlations between circulating methylmalonic acid levels and all-cause and cause-specific mortality among patients with diabetes.

Aims: Evidence regarding serum methylmalonic acid (MMA) levels and mortality in individuals with diabetes is limited. This study aimed to evaluate the correlation between MMA and all-cause and cause-specific deaths in patients with diabetes. Materials and methods: This is a population-based cohort study based on data from both the National Health and Nutrition Examination Survey (NHANES) and National Death Index from 1999 to 2014. We assessed the association of serum MMA concentrations with mortality using Cox proportional hazard models after adjusting for lifestyle, demographic factors, and comorbidities. Results: Among the 3,097 participants, 843 mortalities occurred during a median follow-up of 4.42 years. There were 242 deaths due to cardiovascular disease (CVD) and 131 cancer-associated deaths. After multivariate adjustment, elevated serum MMA levels were markedly correlated with a high risk of all-cause, CVD-, and cancer-related deaths. Each one-unit increase in the natural log-transformed MMA level correlated with increased risk of all-cause mortality (2.652 times), CVD mortality risk (3.153 times), and cancer-related mortality risk (4.514). Hazard ratios (95% confidence intervals [CIs]) after comparing participants with MMA < 120 and ≥250 nmol/L were 2.177 (1.421-3.336) for all-cause mortality, 3.560 (1.809-7.004) for CVD mortality, and 4.244 (1.537-11.721) for cancer mortality. Conclusion: Higher serum MMA levels were significantly associated with higher all-cause, CVD, and cancer mortality. These findings suggest that maintaining lower MMA status may lower mortality risk in individuals with diabetes.

Relationship between consciousness level and perfusion computed tomography in patients with prolonged disorders of consciousness.

PURPOSE: We assessed the relationship between consciousness level and values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP) obtained by whole-brain perfusion computed tomography (pCT) in patients with prolonged disorders of consciousness (pDOC). METHODS: This study included 29 patients in vegetative state (VS), 34 with minimally consciousness state minus (MCS-), and 13 with minimally consciousness state plus (MCS+). All patients were evaluated using the Coma Recovery Scale-Revised (CRS-R), the Glasgow Coma Scale (GCS), and the Full Outline of UnResponsiveness (FOUR). The values of CBF, CBV, MTT, and TTP were obtained from patients who underwent pCT. Differences in CBF, CBV, MTT, and TTP were compared between the three types of pDOC. Correlations between the CRS-R, GCS, and FOUR scores and the pCT results were analyzed. RESULTS: Among the three groups, patients in VS showed a significantly decreased CBF in the bilateral frontal lobe, thalamus, temporal lobe, occipital lobe, brainstem, and damaged part. CBV was significantly reduced in patients with VS in the bilateral frontal lobe, thalamus, temporal lobe, brainstem, and damaged part. The total CRS-R, GCS, and FOUR scores were positively correlated with CBF, CBV, and TTP in almost all regions of interest. CONCLUSION: Reductions in CBF and CBV calculated with pCT are associated with impaired consciousness and perfusion CT could be a promising tool in evaluating the conscious level in patients with pDOC.

Predicting mortality in acute kidney injury patients undergoing continuous renal replacement therapy using a visualization model: A retrospective study.

Background: Patients with severe acute kidney injury (AKI) require continuous renal replacement therapy (CRRT) when hemodynamically unstable. We aimed to identify prognostic factors and develop a nomogram that could predict mortality in patients with AKI undergoing CRRT. Methods: Data were extracted from the Dryad Digital Repository. We enrolled 1,002 participants and grouped them randomly into training (n = 670) and verification (n = 332) datasets based on a 2:1 proportion. Based on Cox proportional modeling of the training set, we created a web-based dynamic nomogram to estimate all-cause mortality. Results: The model incorporated phosphate, Charlson comorbidity index, body mass index, mean arterial pressure, levels of creatinine and albumin, and sequential organ failure assessment scores as independent predictive indicators. Model calibration and discrimination were satisfactory. In the training dataset, the area under the curves (AUCs) for estimating the 28-, 56-, and 84-day all-cause mortality were 0.779, 0.780, and 0.787, respectively. The model exhibited excellent calibration and discrimination in the validation dataset, with AUC values of 0.791, 0.778, and 0.806 for estimating 28-, 56-, and 84-day all-cause mortality, respectively. The calibration curves exhibited the consistency of the model between the two cohorts. To visualize the results, we created a web-based calculator. Conclusion: We created a web-based calculator for assessing fatality risk in patients with AKI receiving CRRT, which may help rationalize clinical decision-making and personalized therapy.

Median Nerve Stimulation Attenuates Traumatic Brain Injury-Induced Comatose State by Regulating the Orexin-A/RasGRF1 Signaling Pathway.

BACKGROUND: Despite the arousal effect of median nerve stimulation (MNS) being well documented in the clinical treatment of coma patients with traumatic brain injury (TBI), the mechanisms underlying the observed effect are still not completely understood. This study aimed to evaluate the protective effects and potential mechanism of MNS in comatose rats with TBI. METHODS: A total of 60 rats were randomly divided into 5 groups: the control group, sham-stimulated group, MNS group, orexins receptor type 1 (OX1R) antagonist group, and antagonist control group. The free-fall drop method was used to establish a TBI model. After administrating MNS or OX1R antagonist, consciousness was evaluated. Protein levels in the prefrontal cortex were measured using an enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence. RESULTS: In the MNS group, tissue damage and consciousness state was markedly improved compared with that in the sham-stimulated group. Administration of the OX1R antagonist attenuated the beneficial effects of MNS in TBI-induced comatose rats. Additionally, MNS also significantly enhanced the expression of orexin-A/OX1R and the activation of Ras guanine nucleotide-releasing factor 1 (RasGRF1). CONCLUSIONS: These data show that MNS exerts its wake-promoting effect by activating the OX1R-RasGRF1 pathway in TBI-induced comatose rats.

Development and Validation of a Website to Guide Decision-Making for Disorders of Consciousness.

Background: This study aimed to develop and validate a nomogram and present it on a website to be used to predict the overall survival at 16, 32, and 48 months in patients with prolonged disorder of consciousness (pDOC). Methods: We retrospectively analyzed the data of 381 patients with pDOC at two centers. The data were randomly divided into training and validation sets using a ratio of 6:4. On the training set, Cox proportional hazard analyses were used to identify the predictive variables. In the training set, two models were screened by COX regression analysis, and based on clinical evidence, model 2 was eventually selected in the nomogram after comparing the receiver operating characteristic (ROC) of the two models. In the training and validation sets, ROC curves, calibration curves, and decision curve analysis (DCA) curves were utilized to measure discrimination, calibration, and clinical efficacy, respectively. Results: The final model included age, Glasgow coma scale (GCS) score, serum albumin level, and computed tomography (CT) midline shift, all of which had a significant effect on survival after DOCs. For the 16-, 32-, and 48-month survival on the training set, the model had good discriminative power, with areas under the curve (AUCs) of 0.791, 0.760, and 0.886, respectively. For the validation set, the AUCs for the 16-, 32-, and 48-month survival predictions were 0.806, 0.789, and 0.867, respectively. Model performance was good for both the training and validation sets according to calibration plots and DCA. Conclusion: We developed an accurate, efficient nomogram, and a corresponding website based on four correlated factors to help clinicians improve their assessment of patient outcomes and help personalize the treatment process and clinical decisions.

A Ubiquitin-Proteasome Gene Signature for Predicting Prognosis in Patients With Lung Adenocarcinoma.

Background: Dysregulation of the ubiquitin-proteasome system (UPS) can lead to instability in the cell cycle and may act as a crucial factor in both tumorigenesis and tumor progression. However, there is no established prognostic signature based on UPS genes (UPSGs) for lung adenocarcinoma (LUAD) despite their value in other cancers. Methods: We retrospectively evaluated a total of 703 LUAD patients through multivariate Cox and Lasso regression analyses from two datasets, the Cancer Genome Atlas (n = 477) and GSE31210 (n = 226). An independent dataset (GSE50081) containing 128 LUAD samples were used for validation. Results: An eight-UPSG signature, including ARIH2, FBXO9, KRT8, MYLIP, PSMD2, RNF180, TRIM28, and UBE2V2, was established. Kaplan-Meier survival analysis and time-receiver operating characteristic curves for the training and validation datasets revealed that this risk signature presented with good performance in predicting overall and relapsed-free survival. Based on the signature and its associated clinical features, a nomogram and corresponding web-based calculator for predicting survival were established. Calibration plot and decision curve analyses showed that this model was clinically useful for both the training and validation datasets. Finally, a web-based calculator (https://ostool.shinyapps.io/lungcancer) was built to facilitate convenient clinical application of the signature. Conclusion: An UPSG based model was developed and validated in this study, which may be useful as a novel prognostic predictor for LUAD.

A dynamic model to predict long-term outcomes in patients with prolonged disorders of consciousness.

PURPOSE: It is important to predict the prognosis of patients with prolonged disorders of consciousness (DOC). This study established and validated a nomogram and corresponding web-based calculator to predict outcomes for patients with prolonged DOC. METHODS: All data were obtained from the First Affiliated Hospital of Nanchang University and the Shangrao Hospital of Traditional Chinese Medicine. Predictive variables were identified by univariate and multiple logistic regression analyses. Receiver operating characteristic curves, calibration curves, and a decision curve analysis (DCA) were utilized to assess the predictive accuracy, discriminative ability, and clinical utility of the model, respectively. RESULTS: Independent prognostic factors, such as age, Glasgow coma scale score, state of consciousness, and brainstem auditory-evoked potential grade were integrated into a nomogram. The model demonstrated good discrimination in the training and validation cohorts, with area-under-the-curve values of 0.815 (95% confidence interval [CI]: 0.748-0.882) and 0.805 (95% CI: 0.727-0.883), respectively. The calibration plots and DCA demonstrated good model performance and clear clinical benefits in both cohorts. CONCLUSIONS: Based on our nomogram, we developed an effective, simple, and accurate model of a web-based calculator that may help individualize healthcare decision-making. Further research is warranted to optimize the system and update the predictors.

A prediction model of clinical outcomes in prolonged disorders of consciousness: A prospective cohort study.

Objective: This study aimed to establish and validate a prediction model for clinical outcomes in patients with prolonged disorders of consciousness (pDOC). Methods: A total of 170 patients with pDOC enrolled in our rehabilitation unit were included and divided into training (n = 119) and validation sets (n = 51). Independent predictors for improved clinical outcomes were identified by univariate and multivariate logistic regression analyses, and a nomogram model was established. The nomogram performance was quantified using receiver operating curve (ROC) and calibration curves in the training and validated sets. A decision curve analysis (DCA) was performed to evaluate the clinical usefulness of this nomogram model. Results: Univariate and multivariate logistic regression analyses indicated that age, diagnosis at entry, serum albumin (g/L), and pupillary reflex were the independent prognostic factors that were used to construct the nomogram. The area under the curve in the training and validation sets was 0.845 and 0.801, respectively. This nomogram model showed good calibration with good consistency between the actual and predicted probabilities of improved outcomes. The DCA demonstrated a higher net benefit in clinical decision-making compared to treating all or none. Conclusion: Several feasible, cost-effective prognostic variables that are widely available in hospitals can provide an efficient and accurate prediction model for improved clinical outcomes and support clinicians to offer suitable clinical care and decision-making to patients with pDOC and their family members.

Wakefulness-Promoting Effects of Lateral Hypothalamic Area-Deep Brain Stimulation in Traumatic Brain Injury-Induced Comatose Rats: Upregulation of α1-Adrenoceptor Subtypes and Downregulation of Gamma-Aminobutyric Acid ß Receptor Expression Via the Orexins Pathway.

OBJECTIVE: Previous studies have shown that deep brain stimulation (DBS) can improve the level of consciousness of comatose patients with traumatic brain injuries (TBIs). However, the most suitable targets for DBS are unknown, and the mechanisms underlying recovery remain to be determined. The aim of the present study was to assess the effects of lateral hypothalamic area-DBS (LHA-DBS) in comatose rats with TBIs. METHODS: A total of 55 Sprague-Dawley rats were randomly assigned to 5 groups: the control group, TBI group, stimulated (TBI+LHA-DBS) group, antagonist (TBI+SB334867+LHA-DBS) group, and antagonist control (TBI+saline+LHA-DBS) group. The rats in the control group had undergone a sham operation and anesthesia, without coma induction. Coma was induced using a free-fall drop method. The rats in the stimulated group received bilateral LHA stimulation (frequency, 200 Hz; voltage, 2-4 V; pulse width, 0.1 ms) for 1 hour, with 5-minute intervals between subsequent stimulations, which were applied alternately to the left and right sides of the lateral hypothalamus. The comatose rats in the antagonist group received an intracerebroventricular injection with an orexins receptor type 1 (OX1R) antagonist (SB334867) and then received LHA-DBS. A I-VI consciousness scale and electroencephalography were used to assess the level of consciousness in each group of rats after LHA-DBS. Western blotting and immunofluorescence were used to detect OX1R expression in the LHA and α1-adrenoceptor (α1-AR) subtype and gamma-aminobutyric acid ß receptor (GABABR) expression in the prefrontal cortex. RESULTS: In the TBI, stimulated, antagonist, and antagonist control groups, 5, 10, 6, and 9 rats were awakened. The electroencephalographic readings indicated that the proportion of δ waves was lower in the stimulated group than in the TBI and antagonist groups (P < 0.05). Western blotting and immunofluorescence analysis showed that OX1R expression was greater in the stimulated group than in the TBI group (P < 0.05). The expression of α1-AR was also greater in the stimulated group than in the TBI and antagonist groups (P < 0.05). In contrast, the GABABR levels in the stimulated group were lower than those in the TBI and antagonist groups (P < 0.05). A statistically significant difference was found between the antagonist and antagonist control groups. CONCLUSIONS: Taken together, these results suggest that LHA-DBS promotes the recovery of consciousness in comatose rats with TBIs. Upregulation of α1-AR expression and downregulation of GABABR expression in the prefrontal cortex via the orexins and OX1R pathways might be involved in the wakefulness-promoting effects of LHA-DBS.

Orexin-A Attenuates Inflammatory Responses in Lipopolysaccharide-Induced Neural Stem Cells by Regulating NF-KB and Phosphorylation of MAPK/P38/Erk Pathways.

BACKGROUND: Neuronal damage is the main cause of neurological diseases. Neural stem cells (NSCs) have the functions of cell repair and replacement of neurons, secretion of neurotrophic factors, and immune regulation of the neural microenvironment. OBJECTIVE: Previous study found that Orexin-A had a protective effect on neurons in the central nervous system, but it is lacking in making great efforts on the function of Orexin-A on NSCs. This study aimed to investigate the anti-inflammatory responses and signaling mechanisms of Orexin-A on lipopolysaccharide (LPS)-induced NSCs. METHODS: Quantitative real-time polymerase chain reaction was used to detect the mRNA level. Signaling pathway-related protein expression was detected by Western blot. The proliferation and migration of NSCs were investigated by Cell Counting Kit-8 (CCK-8) detection kit and transwell assay. Besides, the staining of hematoxylin and eosin (HE) was performed to study the morphology of cell. RESULTS: Orexin-A decreased the pro-inflammatory cytokines of IL-1ß, TNF-α, and IL-6 induced by LPS by regulating nuclear factor-k-gene binding (NF-kB) and phosphorylation of P38/Erk-mitogen-activated protein kinases (MAPKs) pathways, but not p-JNK signaling. CONCLUSION: Our findings indicate that Orexin-A can alleviate the inflammatory response of NSC. It can provide beneficial help in neural stem cell therapy applications.

A simple-to-use web-based calculator for survival prediction in Parkinson's disease.

BACKGROUND: To establish and validate a nomogram and corresponding web-based calculator to predict the survival of patients with Parkinson's disease (PD). METHODS: In this cohort study, we retrospectively evaluated patients (n=497) with PD using a two-stage design, from March 2004 to November 2007 and from July 2005 to July 2015. Predictive variables included in the model were identified by univariate and multiple Cox proportional hazard analyses in the training set. RESULTS: Independent prognostic factors including age, PD duration, and Hoehn and Yahr stage were determined and included in the model. The model showed good discrimination power with the area under the curve (AUC) values generated to predict 4-, 6-, and 8-year survival in the training set being 0.716, 0.783, and 0.814, respectively. In the validation set, the AUCs of 4- and 6-year survival predictions were 0.85 and 0.924, respectively. Calibration plots and decision curve analysis showed good model performance both in the training and validation sets. For convenient application, we established a web-based calculator (https://tangyl.shinyapps.io/PDprognosis/). CONCLUSIONS: We developed a satisfactory, simple-to-use nomogram and corresponding web-based calculator based on three relevant factors to predict prognosis and survival of patients with PD. This model can aid personalized treatment and clinical decision-making.

Liuzijue is a promising exercise option for rehabilitating discharged COVID-19 patients.

BACKGROUND: Among discharged COVID-19 patients, the health-related quality of life is poor, and patients suffer from significant physical and psychological impairment. This study was designed to investigate the effects of Liuzijue exercise on the rehabilitation of COVID-19 patients. METHODS: Thirty three eligible patients with COVID-19 were enrolled in the study after discharge. All the participants practiced Liuzijue exercise once per day for 20 minutes over 4 weeks. Data were collected at baseline and the end of the intervention. Primary outcomes involved functional capacity and secondary outcomes involved quality of life. RESULTS: The maximal inspiratory pressure (MIP), peak inspiratory flow (PIF), and diaphragm movement in deep breathing (DM-DB) of patients increased significantly after 4 weeks of intervention. The dyspnea was also alleviated and exercise capacity was significantly improved. In terms of quality of life, physical functioning and role-physical scores were significantly increased. Moreover, Liuzijue could significantly alleviate the depression and anxiety status of the patients. CONCLUSION: Liuzijue exercise is a viable alternative home exercise program that produced better functional capacity and quality of life in discharged patients with COVID-19. These findings also showed the necessity of rehabilitation intervention for cured COVID-19 patients.

Systematic construction and validation of an epithelial-mesenchymal transition risk model to predict prognosis of lung adenocarcinoma.

Epithelial-mesenchymal transition (EMT) has been shown to be linked to a poor prognosis, particularly in patients with non-small-cell lung cancer. Nevertheless, little is known regarding the existence of EMT-related gene signatures and their prognostic values in lung adenocarcinoma (LUAD). In the current study, we systematically profiled the mRNA expression data of patients with LUAD in The Cancer Genome Atlas and Gene Expression Omnibus databases using a total of 1,184 EMT-related genes. The prognostic values of the EMT-related genes used to develop risk score models for overall survival were determined using LASSO and Cox regression analyses. A prognostic signature that consisted of nine unique EMT-related genes was generated using a training set. A nomogram, incorporating this EMT-related gene signature and clinical features of patients with LUAD, was constructed for potential clinical use. Calibration plots, decision-making curves, and receiver operating characteristic curve analysis showed that this model had a good ability to predict the survival of patients with LUAD. The EMT-associated gene signature and prognostic nomogram established in this study were reliable in predicting the survival of patients with LUAD. Thus, we first identified a novel EMT-related gene signature and developed a nomogram for predicting the prognosis of patients with LUAD.

Development and validation of a nomogram for predicting nonalcoholic fatty liver disease in the non-obese Chinese population.

The purpose of this study was to construct and validate a model for predicting nonalcoholic fatty liver disease (NAFLD) in the non-obese Chinese population. A total of 13240 NAFLD-free individuals at baseline from a 4-y longitudinal study were allocated to a training cohort (n=8872) and a validation cohort (n=4368). The overall incidence of NAFLD was 13%. Nine significant predictors including age, gender, body mass index, fasting blood glucose, total cholesterol, triglycerides, high-density lipoprotein cholesterol, uric acid and alanine aminotransferase were identified and constructed for the nomogram using cox proportional hazards regression analyses. The concordance index was 0.804 and 0.802 in the training and validation cohorts, respectively. In the training cohort, the area under the ROC curve (AUC) for 1-y, 2-y, 3-y and 4-y risk was 0.835, 0.825, 0.816 and 0.782, respectively. Likewise, in the validation cohort, the AUC for 1-y, 2-y, 3-y and 4-y risk was 0.817, 0.820, 0.814 and 0.813. The calibration curves for NAFLD risk showed excellent accuracy in the predictive modeling of the nomogram, internally and externally. The nomogram categorized individuals into high- and low-risk groups, and the DCA displayed the clinical usefulness of the nomogram for predicting NAFLD incidence. Our nomogram can predict a personalized risk of NAFLD in the non-obese Chinese population. This nomogram can serve as a simple and affordable tool for stratifying individuals at a high risk of NAFLD, and thus serve to expedite treatment of NAFLD.

Development and validation of a nomogram with an epigenetic signature for predicting survival in patients with lung adenocarcinoma.

Epigenetic factors play crucial roles in carcinogenesis by modifying chromatin architecture. Here, we established an epigenetic biosignature-based model for examining survival in patients with lung adenocarcinoma (LUAD). We retrieved gene-expression profiles and clinical data from The Cancer Genome Atlas and Gene Expression Omnibus and clustered the data into training (n = 490) and Validation (n = 226) datasets, respectively. To establish an epigenetic model, we identified prognostic epigenetic regulation-related genes by LASSO and Cox regression analyses, and established a novel 11-gene signature, including EPC1, GADD45A, HCFC2, RCOR1, SMARCAL1, TLE2, TRIM28, and ZNF516, for predicting LUAD overall survival (OS). The biosignature performed optimally in both the training and validation sets according to receiver operating characteristic and calibration plots. Moreover, the biosignature classified patients into high- and low-risk clusters with distinct survival times, with Cox regression analysis revealing the biosignature as an independent LUAD prognostic index. Furthermore, the generated nomogram integrating the prognostic gene biosignature and clinical indices predicted LUAD OS with high efficiency and outperformed tumor-node-metastasis staging in LUAD survival prediction. These results demonstrated the efficacy of the epigenetic signature prognostic nomogram for reliably predicting LUAD OS and its potential application for informing clinical decision making and individualized treatment.