A Single-Step Method for Harvesting Influenza Viral Particles from MDCK Cell Culture Supernatant with High Yield and Effective Impurity Removal.

Influenza vaccines, which are recommended by the World Health Organization (WHO), are the most effective preventive measure against influenza virus infection. Madin-Darby canine kidney (MDCK) cell culture is an emerging technology used to produce influenza vaccines. One challenge when purifying influenza vaccines using this cell culture system is to efficiently remove impurities, especially host cell double-stranded DNA (dsDNA) and host cell proteins (HCPs), for safety assurance. In this study, we optimized ion-exchange chromatography methods to harvest influenza viruses from an MDCK cell culture broth, the first step in influenza vaccine purification. Bind/elute was chosen as the mode of operation for simplicity. The anion-exchange Q chromatography method was able to efficiently remove dsDNA and HCPs, but the recovery rate for influenza viruses was low. However, the cation-exchange SP process was able to simultaneously achieve high dsDNA and HCP removal and high influenza virus recovery. For the SP process to work, the clarified cell culture broth needed to be diluted to reduce its ionic strength, and the optimal dilution rate was determined to be 1:2 with purified water. The SP process yielded a virus recovery rate exceeding 90%, as measured using a hemagglutination units (HAUs) assay, with removal efficiencies over 97% for HCPs and over 99% for dsDNA. Furthermore, the general applicability of the SP chromatography method was demonstrated with seven strains of influenza viruses recommended for seasonal influenza vaccine production, including H1N1, H3N2, B (Victoria), and B (Yamagata) strains, indicating that the SP process could be utilized as a platform process. The SP process developed in this study showed four advantages: (1) simple operation, (2) a high recovery rate for influenza viruses, (3) a high removal rate for major impurities, and (4) general applicability.

Preoperative prediction power of radiomics and non-radiomics methods based on MRI for early recurrence in hepatocellular carcinoma: a systemic review and meta-analysis.

OBJECTIVE: To compare radiomics and non-radiomics in predicting early recurrence (ER) in patients with hepatocellular carcinoma (HCC) after curative surgery. METHODS: We systematically searched PubMed and Embase databases. Studies with clear reference criteria were selected. Data were extracted and assessed for quality using the quality in prognosis studies tool (QUIPS) by two independent authors. All included radiomics studies underwent radiomics quality score (RQS) assessment. We calculated sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) using random or fixed models with a 95%CI. Forest maps visualized the data, and summary receiver operating characteristic (sROC) curves with the area under the curve (AUC) were generated. Meta-regression and subgroup analyses explored sources of heterogeneity. We compared sensitivity, specificity, PLR, and NLR using the z-test and compared AUC values using the Delong test. RESULTS: Our meta-analysis included 10 studies comprising 1857 patients. For radiomics, the pooled sensitivity, specificity, AUC of sROC, PLR and NLR were 0.84(95%CI: 0.78-0.89), 0.80(95%CI: 0.75-0.85), 0.89(95%CI: 0.86-0.91), 4.28(95%CI: 3.48-5.27) and 0.20(95%CI: 0.14-0.27), respectively, but with significant heterogeneity (I2 = 60.78% for sensitivity, I2 = 55.79% for specificity) and potential publication bias (P = 0.04). The pooled sensitivity, specificity, AUC of sROC, PLR, NLR for non-radiomics were 0.75(95%CI:0.68-0.81), 0.78(95%CI:0.72-0.83), 0.83(95%CI: 0.80-0.86), 3.45(95%CI: 2.68-4.44) and 0.32(95%CI: 0.24-0.41), respectively. There was no significant heterogeneity in this group (I2 = 0% for sensitivity, I2 = 17.27% for specificity). Radiomics showed higher diagnostic accuracy (AUC: 0.89 vs. 0.83, P = 0.0456), higher sensitivity (0.84 vs. 0.75, P = 0.0385) and lower NLR (0.20 vs. 0.32, P = 0.0287). CONCLUSION: The radiomics from preoperative MRI effectively predicts ER of HCC and has higher diagnostic accuracy than non-radiomics. Due to potential publication bias and suboptimal RQS scores in radiomics, these results should be interpreted cautiously.

The Diagnostic Accuracy Between Radiomics Model and Non-radiomics Model for Preoperative of Microvascular Invasion of Solitary Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: Microvascular invasion (MVI) is a key prognostic factor for hepatocellular carcinoma (HCC). The predictive models for solitary HCC could potentially integrate more comprehensive tumor information. Owing to the diverse findings across studies, we aimed to compare radiomic and non-radiomic methods for preoperative MVI detection in solitary HCC. MATERIALS AND METHODS: Articles were reviewed from databases including PubMed, Embase, Web of Science, and the Cochrane Library until April 7, 2023. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated using a random-effects model within a 95% confidence interval (CI). Diagnostic accuracy was assessed using summary receiver-operating characteristic curves and the area under the curve (AUC). Meta-regression and Z-tests identified heterogeneity and compared the predictive accuracy. Subgroup analyses were performed to compare the AUC of two methods according to study type, study design, tumor size, modeling methods, and imaging modality. RESULTS: The analysis incorporated 26 studies involving 3539 patients with solitary HCC. The radiomics models showed a pooled sensitivity and specificity of 0.79 (95%CI: 0.72-0.85) and 0.78 (95%CI: 0.73-0.82), with an AUC at 0.85 (95%CI: 0.82-0.88). Conversely, the non-radiomics models had sensitivity and specificity of 0.74 (95%CI: 0.65-0.81) and 0.88 (95%CI: 0.82-0.92) and an AUC of 0.88 (95%CI: 0.85-0.91). Subgroups with preoperative MRI, larger tumors, and functional imaging had higher accuracy than those using preoperative CT, smaller tumors, and conventional imaging. CONCLUSION: Non-radiomic methods outperformed radiomic methods, but high heterogeneity calls across studies for cautious interpretation.

Prediction of pathological activity in Crohn's disease based on dual-energy CT enterography.

PURPOSE: To explore the feasibility of predicting the pathological activity of Crohn's disease (CD) based on dual-energy CT enterography (DECTE). METHODS: The clinical, endoscopic, imaging and pathological data of 55 patients with CD scanned by DECTE were retrospectively analyzed; the pathological results were used as a reference standard to classify the diseased bowel segments into active and inactive phases. The normalized iodine concentration (NIC), energy-spectrum curve slope K, dual energy index (DEI), fat fraction (FF) of the arterial phases and venous phases were compared. To assess the parameters' predictive ability, receiver-operating characteristic curves were used. The Delong test was used to compare the differences between the diagnostic efficiency of each parameter. RESULTS: A total of 84 intestinal segments were included in the study, including 54 active intestinal segments and 30 inactive intestinal segments. The NIC, energy-spectrum curve slope K and DEI were significantly different between active and inactive bowel segments in the arterial and venous phases (P < 0.05), while FF were not significantly different (P > 0.05). The largest area under the curve (AUC) of NIC, energy-spectrum curve slope K and DEI were higher in arterial phase than in venous phase. For identifying the intestinal activity of CD, the maximum AUC of NIC in arterial phase was 0.908, with a sensitivity of 0.833 and a specificity of 0.800, and the DEI in arterial phase had the highest sensitivity (0.944). CONCLUSION: The NIC, energy-spectrum curve slope K and DEI can effectively distinguish the active and inactive phases of the intestinal segments of CD patients and provide good assistance for determining further treatment.

How well do neural signatures of resting-state EEG detect consciousness? A large-scale clinical study.

The assessment of consciousness states, especially distinguishing minimally conscious states (MCS) from unresponsive wakefulness states (UWS), constitutes a pivotal role in clinical therapies. Despite that numerous neural signatures of consciousness have been proposed, the effectiveness and reliability of such signatures for clinical consciousness assessment still remains an intense debate. Through a comprehensive review of the literature, inconsistent findings are observed about the effectiveness of diverse neural signatures. Notably, the majority of existing studies have evaluated neural signatures on a limited number of subjects (usually below 30), which may result in uncertain conclusions due to small data bias. This study presents a systematic evaluation of neural signatures with large-scale clinical resting-state electroencephalography (EEG) signals containing 99 UWS, 129 MCS, 36 emergence from the minimally conscious state, and 32 healthy subjects (296 total) collected over 3 years. A total of 380 EEG-based metrics for consciousness detection, including spectrum features, nonlinear measures, functional connectivity, and graph-based measures, are summarized and evaluated. To further mitigate the effect of data bias, the evaluation is performed with bootstrap sampling so that reliable measures can be obtained. The results of this study suggest that relative power in alpha and delta serve as dependable indicators of consciousness. With the MCS group, there is a notable increase in the phase lag index-related connectivity measures and enhanced functional connectivity between brain regions in comparison to the UWS group. A combination of features enables the development of an automatic detector of conscious states.

Recent Advances in Hepatic Metabolic Regulation by the Nuclear Factor Rev-erbɑ.

Rev-erbɑ (NR1D1) is a nuclear receptor superfamily member that plays a vital role in mammalian molecular clocks and metabolism. Rev-erbɑ can regulate the metabolism of drugs and the body's glucose metabolism, lipid metabolism, and adipogenesis. It is even one of the important regulatory factors regulating the occurrence of metabolic diseases (e.g., diabetes, fatty liver). Metabolic enzymes mediate most drug metabolic reactions in the body. Rev-erbɑ has been recognized to regulate drug metabolic enzymes (such as Cyp2b10 and Ugt1a9). Therefore, this paper mainly reviewed that Rev-erbɑ regulates I and II metabolic enzymes in the liver to affect drug pharmacokinetics. The expression of these drug metabolic enzymes (up-regulated or down-regulated) is related to drug exposure and effects/ toxicity. In addition, our discussion extends to Rev-erbɑ regulating some transporters (such as P-gp, Mrp2, and Bcrp), as they also play an essential role in drug metabolism. Finally, we briefly describe the role and mechanism of nuclear receptor Rev-erbɑ in lipid and glucose homeostasis, obesity, and metabolic disorders syndrome. In conclusion, this paper aims to understand better the role and mechanism of Rev-erbɑ in regulating drug metabolism, lipid, glucose homeostasis, obesity, and metabolic disorders syndrome, which explores how to target Rev-erbɑ to guide the design and development of new drugs and provide scientific reference for the molecular mechanism of new drug development, rational drug use, and drug interaction.

Activating transcription factor 3 is a new biomarker correlation with renal clear cell carcinoma progression.

Background: Clear cell renal cell carcinoma (ccRCC) is the most invasive type of cancer, with a high risk of metastasis and recurrence. Therefore, there is an urgent need to identify novel prognostic predictors and therapeutic targets of ccRCC. Activating transcription factor 3 (ATF3), a tumor oncogene or repressor, has rarely been examined in ccRCC. In the present study, we comprehensively elucidate the prognostic value and potential functions of ATF3 in ccRCC.Methods: Several TCGA-based online databases were used to analyze ATF3 expression in ccRCC and determine ccRCC prognosis. The upstream-binding micro (mi) RNAs of ATF3 and long non-coding (lnc)RNAs were predicted using the StarBase database.Results: Analysis of several TCGA-based online databases showed that ATF3 expression is decreased in ccRCC, suggesting a significant association with the prognosis of patients with ccRCC. Furthermore, we found hsa-miR-221-3p to be potential regulatory miRNA of ATF3 in ccRCC. Prediction and analysis of the upstream lncRNAs indicated that PAXIP1-AS2 and OIP5-AS1 were the most potent upstream lncRNAs of the hsa-miR-221-3p/ATF3 axis in ccRCC. The results of the GO and KEGG analyses implied that ATF3 is likely involved in the regulation of apoptotic signaling in response to endoplasmic reticulum (ER) stress in ccRCC. Correlation analysis revealed a positive relationship between ATF3 expression and ER stress.Conclusions: Our in silico findings highlighted that ATF3 expression was low in ccRCC and negatively correlated with poor prognosis. Furthermore, PAXIP1-AS2 and the OIP5-AS1/hsa-miR-221-3p/ATF3 axis were identified as significant potential regulators of ER stress-mediated apoptosis in ccRCC.

Rapid and visual identification of ß-lactamase subtypes for precision antibiotic therapy.

The abuse of antibiotics urgently requires rapid identification of drug-resistant bacteria at the point of care (POC). Here we report a visual paper sensor that allows rapid (0.25-3 h) discrimination of the subtypes of ß-lactamase (the major cause of bacterial resistance) for precision antibiotic therapy. The sensor exhibits high performance in identifying antibiotic-resistant bacteria with 100 real samples from patients with diverse bacterial infections, demonstrating 100% clinical sensitivity and specificity. Further, this sensor can enhance the accuracy of antibiotic use from 48% empirically to 83%, and further from 50.6% to 97.6% after eliminating fungal infection cases. Our work provides a POC testing platform for guiding effective management of bacterial infections in both hospital and community settings.

Co-based Nanozymatic Profiling: Advances Spanning Chemistry, Biomedical, and Environmental Sciences.

Nanozymes, next-generation enzyme-mimicking nanomaterials, have entered an era of rational design; among them, Co-based nanozymes have emerged as captivating players over times. Co-based nanozymes have been developed and have garnered significant attention over the past five years. Their extraordinary properties, including regulatable enzymatic activity, stability, and multifunctionality stemming from magnetic properties, photothermal conversion effects, cavitation effects, and relaxation efficiency, have made Co-based nanozymes a rising star. This review presents the first comprehensive profiling of the Co-based nanozymes in the chemistry, biology, and environmental sciences. The review begins by scrutinizing the various synthetic methods employed for Co-based nanozyme fabrication, such as template and sol-gel methods, highlighting their distinctive merits from a chemical standpoint. Furthermore, a detailed exploration of their wide-ranging applications in biosensing and biomedical therapeutics, as well as their contributions to environmental monitoring and remediation is provided. Notably, drawing inspiration from state-of-the-art techniques such as omics, a comprehensive analysis of Co-based nanozymes is undertaken, employing analogous statistical methodologies to provide valuable guidance. To conclude, a comprehensive outlook on the challenges and prospects for Co-based nanozymes is presented, spanning from microscopic physicochemical mechanisms to macroscopic clinical translational applications.

Protein profiles reveal MSH6/MSH2 as a potential biomarker for hepatocellular carcinoma with microvascular invasion.

AIM: Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence and metastasis in hepatocellular carcinoma (HCC). However, the specific protein expression profiles that differentiate HCC with MVI from those without MVI remain unclear. METHODS: The profiles of proteins in early-stage HCC tissues and normal liver tissues were characterized by quantitative proteomics techniques. Immunohistochemical (IHC) staining was undertaken on tissue microarrays from 80 HCC patients to assess the expression of MSH2 and MSH6. Cell counting, colony formation, migration, and invasion assays were carried out in vitro. RESULTS: We identified 5164 proteins in both HCC tissues and adjacent normal liver tissues. Compared to HCC without MVI, 148 upregulated proteins and 97 downregulated proteins were found in HCC with MVI. Particularly noteworthy was the remarkable upregulation of MSH6/MSH2 among these dysregulated proteins in HCC with MVI. Further validation through bioinformatics prediction and IHC confirmed the elevated expression of MSH6/MSH2, which correlated with aggressive disease characteristics and poor prognosis. Receiver operating characteristic curve analyses revealed a substantial area under the curve of 0.761 (specificity 71.79%, sensitivity 73.17%) for the combined use of MSH6/MSH2. Knockdown of MSH6/MSH2 significantly inhibited HCC cell proliferation and invasion in vitro. CONCLUSIONS: Our study establishes MSH6 or MSH2 as an oncogene that is prominently overexpressed during HCC progression, which provides new targets for HCC with MVI.

Pharmacokinetics, Tissue Distribution and Excretion of Demethyleneberberine, a Metabolite of Berberine, in Rats and Mice.

Demethyleneberberine is an active component extracted from the Chinese herbal drug Cortex Phellodendri. It is also a metabolite of berberine in animals and humans. However, the pharmacokinetics, tissue distribution and excretion of demethyleneberberine have not been reported. The present study aimed to investigate the pharmacokinetic parameters of demethyleneberberine by applying high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). After intragastric administration of demethyleneberberine in rats and mice, the pharmacokinetics, tissue distribution and excretion of demethyleneberberine were comparatively studied for the first time. The plasma concentration of demethyleneberberine reached its peak within 5 min after intragastric administration in both rats and mice. Furthermore, its bioavailability was comparable, ranging from 4.47% to 5.94%, higher than that of berberine. The total excretion of demethyleneberberine in the urine, feces and bile was 7.28~9.77%. These findings provide valuable insights into the pharmacological and clinical research on demethyleneberberine.

Phase Property of Envelope-Tracking EEG Response Is Preserved in Patients with Disorders of Consciousness.

When listening to speech, the low-frequency cortical response below 10 Hz can track the speech envelope. Previous studies have demonstrated that the phase lag between speech envelope and cortical response can reflect the mechanism by which the envelope-tracking response is generated. Here, we analyze whether the mechanism to generate the envelope-tracking response is modulated by the level of consciousness, by studying how the stimulus-response phase lag is modulated by the disorder of consciousness (DoC). It is observed that DoC patients in general show less reliable neural tracking of speech. Nevertheless, the stimulus-response phase lag changes linearly with frequency between 3.5 and 8 Hz, for DoC patients who show reliable cortical tracking to speech, regardless of the consciousness state. The mean phase lag is also consistent across these DoC patients. These results suggest that the envelope-tracking response to speech can be generated by an automatic process that is barely modulated by the consciousness state.

Machine learning identifies ferroptosis-related genes as potential diagnostic biomarkers for osteoarthritis.

Background: Osteoarthritis (OA) is one of the most common forms of degenerative arthritis and a major cause of pain and disability. Ferroptosis, a novel mode of cell death, has been verified to participate in the development of OA, but its mechanism is still unclear. This paper analyzed the ferroptosis-related genes (FRGs) in OA and explored their potential clinical value. Methods: We downloaded data through the GEO database and screened for DEGs. Subsequently, FRGs were obtained using two machine learning methods, LASSO regression and SVM-RFE. The accuracy of the FRGs as disease diagnosis was identified using ROC curves and externally validated. The CIBERSORT analyzed the immune microenvironment rug regulatory network constructed through the DGIdb. The competitive endogenous RNA (ceRNA) visualization network was constructed to search for possible therapeutic targets. The expression levels of FRGs were verified by qRT-PCR and immunohistochemistry. Results: In this study, we found 4 FRGs. The ROC curve showed that the combined 4 FRGs had the highest diagnostic value. Functional enrichment analysis showed that the 4 FRGs in OA could influence the development of OA through biological oxidative stress, immune response, and other processes. qRT-PCR and immunohistochemistry verified the expression of these key genes, further confirming our findings. Monocytes and macrophages are heavily infiltrated in OA tissues, and the persistent state of immune activation may promote the progression of OA. ETHINYL ESTRADIOL was a possible targeted therapeutic agent for OA. Meanwhile, ceRNA network analysis identified some lncRNAs that could regulate the FRGs. Conclusion: We identify 4 FRGs (AQP8, BRD7, IFNA4, and ARHGEF26-AS1) closely associated with bio-oxidative stress and immune response, which may become early diagnostic and therapeutic targets for OA.

Cortical responses to auditory stimulation predict the prognosis of patients with disorders of consciousness.

OBJECTIVE: This study aimed to assess the prognosis of patients with disorders of consciousness (DoC) using auditory stimulation with electroencephalogram (EEG) recordings. METHODS: We enrolled 72 patients with DoC in the study, which involved subjecting patients to auditory stimulation while EEG responses were recorded. Coma Recovery Scale-Revised (CRS-R) scores and Glasgow Outcome Scale (GOS) were determined for each patient and followed up for three months. A frequency spectrum analysis was performed on the EEG recordings. Finally, the power spectral density (PSD) index was used to predict the prognosis of patients with DoC based on a support vector machine (SVM) model. RESULTS: Power spectral analyses revealed that the cortical response to auditory stimulation showed a decreasing trend with decreasing consciousness levels. Auditory stimulation-induced changes in absolute PSD at the delta and theta bands were positively correlated with the CRS-R and GOS scores. Furthermore, these cortical responses to auditory stimulation had a good ability to discriminate between good and poor prognoses of patients with DoC. CONCLUSIONS: Auditory stimulation-induced changes in the PSD were highly predictive of DoC outcomes. SIGNIFICANCE: Our findings showed that cortical responses to auditory stimulation may be an important electrophysiological indicator of prognosis in patients with DoC.

Association of maternal methionine synthase reductase gene polymorphisms with the risk of congenital heart disease in offspring: a hospital-based case-control study.

BACKGROUND: Evidence suggests that periconceptional folic acid supplementation may prevent congenital heart disease (CHD). Methionine synthase reductase (MTRR) is one of the key regulatory enzymes in the folate metabolic pathway. This study aimed to comprehensively evaluate the association of single nucleotide polymorphisms (SNPs) in the maternal MTRR gene with CHD risk in offspring. METHODS: A hospital-based case-control study involving 740 mothers of CHD cases and 683 health controls was conducted. RESULTS: The study showed that maternal MTRR gene polymorphisms at rs1532268 (C/T vs. C/C: aOR = 1.524; T/T vs. C/C: aOR = 3.178), rs1802059 (G/A vs. G/G: aOR = 1.410; A/A vs. G/G: aOR = 3.953), rs2287779 (G/A vs. G/G: aOR = 0.540), rs16879334 (C/G vs. C/C: aOR = 0.454), and rs2303080 (T/A vs. T/T: aOR = 0.546) were associated with the risk of CHD. And seven haplotypes were observed to be associated with the risk of CHD, T-G-A haplotype (OR = 1.298), C-A-C-C (OR = 4.824) and A-G haplotype (OR = 1.751) were associated with increased risk of CHD in offspring; A-A-A (OR = 0.773), T-A-A (OR = 0.557), G-A-C-C (OR = 0.598) and G-C (OR = 0.740) were associated with decreased risk of CHD in offspring. CONCLUSIONS: Maternal MTRR gene polymorphisms were associated with CHD in offspring, and its haplotypes have affected the occurrence of CHD. Furthermore, given the complexity and heterogeneity of CHD, the mechanisms by which these factors influence offspring cardiac development remain unknown, and studies in larger samples in an ethnically diverse population are needed.

Rhodium-Based Nanozymes: Recent Advances and Challenges.

Rhodium (Rh) is a non-toxic transition metal used as various nanomaterials with unique structures and properties. Rh-based nanozymes can mimic the activities of natural enzymes, overcome the limitation of the application scope of natural enzymes, and interact with various biological microenvironments to play a variety of functions. Rh-based nanozymes can be synthesized in various ways, and different modification and regulation methods can also enable users to control catalytic performance by adjusting enzyme active sites. The construction of Rh-based nanozymes has attracted great interest in the biomedical field and impacted the industry and other areas. This paper reviews the typical synthesis and modification strategies, unique properties, applications, challenges, and prospects of Rh-based nanozymes. Next, the unique features of Rh-based nanozymes are emphasized, including adjustable enzyme-like activity, stability, and biocompatibility. In addition, we discuss Rh-based nanozymes biosensors and detection, biomedical therapy, and industrial and other applications. Finally, the future challenges and prospects of Rh-based nanozymes are proposed.

Statistical learning in patients in the minimally conscious state.

When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.

Sleep patterns correlates with the efficacy of tDCS on post-stroke patients with prolonged disorders of consciousness.

BACKGROUND: The subclassification of prolonged disorders of consciousness (DoC) based on sleep patterns is important for the evaluation and treatment of the disease. This study evaluates the correlation between polysomnographic patterns and the efficacy of transcranial direct current stimulation (tDCS) in patients with prolonged DoC due to stroke. METHODS: In total, 33 patients in the vegetative state (VS) with sleep cycles or without sleep cycles were randomly assigned to either active or sham tDCS groups. Polysomnography was used to monitor sleep changes before and after intervention. Additionally, clinical scale scores and electroencephalogram (EEG) analysis were performed before and after intervention to evaluate the efficacy of tDCS on the patients subclassified according to their sleep patterns. RESULTS: The results suggest that tDCS improved the sleep structure, significantly prolonged total sleep time (TST) (95%CI: 14.387-283.527, P = 0.013) and NREM sleep stage 2 (95%CI: 3.157-246.165, P = 0.040) of the VS patients with sleep cycles. It also significantly enhanced brain function of patients with sleep cycles, which were reflected by the increased clinical scores (95%CI: 0.340-3.440, P < 0.001), the EEG powers and functional connectivity in the brain and the 6-month prognosis. Moreover, the changes in NREM sleep stage 2 had a significant positive correlation with each index of the ß band. CONCLUSION: This study reveals the importance of sleep patterns in the prognosis and treatment of prolonged DoC and provides new evidence for the efficacy of tDCS in post-stroke patients with VS patients subclassified by sleep pattern. Trial registration URL: https://www. CLINICALTRIALS: gov . Unique identifier: NCT03809936. Registered 18 January 2019.

Rhythmic musical-electrical trigeminal nerve stimulation improves impaired consciousness.

Accumulating evidence shows that consciousness is linked to neural oscillations in the thalamocortical system, suggesting that deficits in these oscillations may underlie disorders of consciousness (DOC). However, patient-friendly non-invasive treatments targeting this functional anomaly are still missing and the therapeutic value of oscillation restoration has remained unclear. We propose a novel approach that aims to restore DOC patients' thalamocortical oscillations by combining rhythmic trigeminal-nerve stimulation with comodulated musical stimulation ("musical-electrical TNS"). In a double-blind, placebo-controlled, parallel-group study, we recruited 63 patients with DOC and randomly assigned them to groups receiving gamma, beta, or sham musical-electrical TNS. The stimulation was applied for 40 min on five consecutive days. We measured patients' consciousness before and after the stimulation using behavioral indicators and neural responses to rhythmic auditory speech. We further assessed their outcomes one year later. We found that musical-electrical TNS reliably lead to improvements in consciousness and oscillatory brain activity at the stimulation frequency: 43.5 % of patients in the gamma group and 25 % of patients in the beta group showed an improvement of their diagnosis after being treated with the stimulation. This group of benefitting patients still showed more positive outcomes one year later. Moreover, patients with stronger behavioral benefits showed stronger improvements in oscillatory brain activity. These findings suggest that brain oscillations contribute to consciousness and that musical-electrical TNS may serve as a promising approach to improve consciousness and predict long-term outcomes in patients with DOC.

Altered Intestinal Microbiomes and Lipid Metabolism in Patients With Prolonged Disorders of Consciousness.

The intestinal microbiota regulate the brain function of the host through the production of a myriad of metabolites and are associated with various neurological diseases. Understanding the intestinal microbiome of patients with prolonged disorders of consciousness (DoC) is important for the evaluation and treatment of the disease. To investigate the differences in the intestinal microbiome and short-chain fatty acids (SCFAs) among patients in a vegetative state (VS), a minimally conscious state (MCS), and emerged from MCS (EMCS), as well as the influence of antibiotics on these patients, 16S ribosomal RNA (16S rRNA) sequencing and targeted lipidomics were performed on fecal samples from patients; in addition, analysis of the electroencephalogram (EEG) signals was performed to evaluate the brain function of these patients. The results showed that the intestinal microbiome of the three groups differed greatly, and some microbial communities showed a reduced production of SCFAs in VS patients compared to the other two groups. Moreover, reduced microbial communities and five major SCFAs, along with attenuated brain functional connectivity, were observed in MCS patients who were treated with antibiotics compared to those who did not receive antibiotic treatment, but not in the other pairwise comparisons. Finally, three genus-level microbiota-Faecailbacterium, Enterococcus, and Methanobrevibacter-were considered as potential biomarkers to distinguish MCS from VS patients, with high accuracy both in the discovery and validation cohorts. Together, our findings improved the understanding of patients with prolonged DoC from the intestinal microbiome perspective and provided a new reference for the exploration of therapeutic targets.