Adipose-derived stromal cells (ADSC) show promise for neuronal differentiation, but their utility is limited by late-stage cell death, which may be driven by endoplasmic reticulum stress (ERS). To investigate this mechanism, we employed an integrated approach combining immunocytochemistry, western blotting, single-cell RNA sequencing (scRNA-Seq), and transmission electron microscopy (TEM) to systematically profile ERS-related gene expression, dynamic changes of key proteins, and ultrastructural evolution of the ER during neuronal induction. Our results demonstrate that ERS pathways are activated throughout the differentiation process. In early stages, the endoplasmic reticulum (ER) chaperone GRP78 initially increased but markedly declined at 6 h and 8 h. Key UPR sensors IRE1α, XBP1s, PERK, and ATF6 peaked in undifferentiated ADSC and Pre-induction (Prei-1d) cells, then gradually decreased as differentiation progressed. In contrast, pro-apoptotic markers CHOP and Caspase-3 were continuously upregulated in later phases, accompanied by ultrastructural hallmarks of ER dilation, disrupted mitochondrial cristae, and cytoplasmic vacuolization. These findings indicate that ERS initially activates the unfolded protein response to maintain ER homeostasis and support differentiation, whereas sustained ERS at later stages shifts toward CHOP/Caspase-3-dependent apoptosis, leading to cellular injury. This study provides a theoretical basis for optimizing neuronal differentiation protocols through time-dependent modulation of ERS pathways.

The inherent heterogeneity of adipose-derived stem cells (ADSCs) complicates their characterization, as aggregated data obscure the nuanced states of individual cells and are skewed by dominant functional subpopulations affecting genetic and biological profiles. This heterogeneity presents a significant challenge for the effective deployment of ADSCs in clinical and research settings, highlighting the necessity for precise identification and isolation of specific subsets according to stringent criteria. Using single-cell RNA + ATAC multi-omics technology, we sequenced ADSCs derived from human adipose tissue through extraction, culture, and purification. This analysis identified three distinct subsets-proliferative, functional, and senescent-each exhibiting unique stemness properties. Notably, within the functional subset, cluster 6 emerged as a prime candidate for cellular engineering, showcasing robust stemness, high proliferative capacity, and low senescence. Our findings also reveal ADSCs' predisposition toward neuro-lineage differentiation, with their spatial distribution reflecting developmental trajectories and biological functions. In-depth analysis uncovered subset-specific genes with unique chromatin accessibility patterns, critical for targeted differentiation. Significantly, stemness markers BNC2 and HMGA2 were identified as indicators of non-senescent ADSCs. Through single-cell multi-omics sequencing, we have mapped a comprehensive cellular atlas of ADSCs, elucidating their transcriptional and chromatin profiles to unravel their complex heterogeneity. This atlas not only elucidates variations in composition, function, stemness, and developmental stages across subsets but also identifies essential biomarkers for ADSCs quality control, establishing a robust foundation for advancing ADSC-based therapeutic strategies.

This study aims to evaluate cognitive impairments in patients with acute cerebellar infarction using event-related potentials (ERP) and electrophysiological source imaging (ESI). Thirty patients with acute cerebellar infarction and 32 healthy volunteers were selected. Cognitive potentials were recorded and measured using a visual Oddball paradigm. Source analysis of the N170 component was performed using standardized low-resolution brain electromagnetic tomography (sLORETA) to compare the standardized current density distribution between the two groups under different stimuli. For inverted and upright face stimuli, the amplitudes of N170, VPP, and N300 in the patient group were significantly lower than those in the control group (p < 0.05). For upright house stimuli, the VPP amplitude in the patient group was also lower than that in the control group (p < 0.05). Source analysis revealed that the brain regions with significant differences between the acute cerebellar infarction group and the control group included the temporal and parietal lobes. Specifically, activation in the precuneus was reduced during inverted face stimuli; activation in the middle temporal gyrus was reduced during upright face stimuli; and activation in the middle temporal gyrus and fusiform gyrus was increased during both inverted and upright house stimuli. Patients with acute cerebellar infarction exhibit abnormal P100, N170/VPP, and N300 amplitudes. Source analysis of the N170 component revealed altered activation in the middle and inferior temporal gyri, fusiform gyrus, middle occipital gyrus, and precuneus, which play a role in selective cognitive impairments following cerebellar infarction.

This review aims to explore the relationship between poor pre-stroke sleep and stroke. Pre-stroke sleep duration is associated with the risk and mortality of total stroke, exhibiting a ‘U-shaped’ or ‘J-shaped’ dose-response relationship. Regarding stroke subtypes, prolonged sleep duration is linked to an increased risk of ischemic stroke, while short sleep duration is associated with hemorrhagic and wake-up strokes. Additionally, poor sleep quality is one of the risk factors for stroke occurrence. Moreover, daytime napping can mitigate the negative consequences of sleep issues, but attention should be paid to the duration and frequency of naps. Finally, disruptions in circadian rhythms, inflammatory responses, endocrine changes, and alterations in the autonomic nervous system may be potential pathogenic mechanisms through which chronic poor sleep leads to stroke. Healthy individuals experiencing poor sleep can be considered susceptible to stroke. It is crucial to further refine stroke risk assessments for these individuals and provide targeted medical advice. Additionally, we should identify the optimal duration and frequency of naps to reduce the risk of stroke. Furthermore, closer attention should be paid to the temporal dimension to address the challenges that modern societal changes pose to circadian rhythms. Lastly, the relationship between chronic poor sleep and sleep disorders should also be closely examined.

ObjectiveTo investigate the sleep–wake circadian rhythm and phenotypic characteristics in patients with acute intracerebral hemorrhage (ICH), and to explore the relationship and potential mechanisms between sleep–wake phenotypes and circadian rhythm disruption.MethodsA retrospective analysis was conducted on 100 patients with acute ICH admitted to Kailuan General Hospital between January 2020 and December 2024, along with 67 age- and sex-matched hospitalized controls. Sleep parameters during the daytime (06:00–18:00) and nighttime (18:00–06:00) were collected using a mattress-based sleep monitoring system. Circadian rhythm indices—including interdaily stability (IS), intradaily variability (IV), and relative amplitude (RA)—as well as sleep phenotypic features were evaluated.ResultsCompared with the control group, patients with ICH exhibited significantly disrupted circadian rhythms, characterized by reductions in IS, IV, and RA (all p < 0.05). Significant alterations in sleep–wake states were observed in both daytime and nighttime periods among ICH patients. These included prolonged/increased durations and proportions of light sleep, deep sleep, NREM sleep, REM sleep, and sleep efficiency, along with shortened/decreased sleep latency, REM latency, and proportion of NREM sleep (all p < 0.05). Phenotypic analysis revealed a significantly higher prevalence of excessive daytime sleep, increased total sleep across 24 h, and reversed sleep–wake cycles in the ICH group (all p < 0.05). Regression analysis indicated that reduced IS was significantly associated with reversed sleep–wake cycles (OR = −5.831; 95% CI,: −12.577 ~ −1.350).ConclusionAcute hemorrhagic stroke is associated with excessive sleepiness, disrupted sleep architecture, and weakened circadian rhythms. These disturbances may impair recovery and long-term outcomes, underscoring the need for rhythm-based biomarkers and individualized interventions.

Objective:To evaluate the influence of the sleep-wake state on the prognosis of patients with ischemic stroke. Methods:Consecutive patients with intracranial ischemic stroke due to arterial stenosis were included (198 cases). The control group consisted of contemporaneous patients without cerebrovascular stenosis or any diagnosed cerebrovascular disease (77 cases). Collect the following variables of the patients, including the total recording time during the day and night, total sleep time, sleep latency, rapid eye movement (REM) sleep latency, wake time after falling asleep, light sleep stage (N1, N2 stage), deep sleep stage (N3 stage), and non-rapid eye movement (non-rapid eye movement) (NREM) sleep stage, rapid eye movement (REM) sleep stage, and stroke topography (anterior circulation and posterior circulation ischemic stroke). The primary outcome was the functional status at discharge, evaluated using the modified Rankin Scale (mRS): good prognosis (mRS ≤ 2) and poor prognosis (mRS > 2). Results:In the regression analysis of prognostic influencing factors in patients with ACIS, it was concluded that an increase in daytime deep sleep time was associated with an increased possibility of adverse outcomes in patients with ACIS (OR = 1.026; 95% CI, 1.003-1.048, p = 0.024). In the regression analysis of prognostic influencing factors in patients with PCIS, it was concluded that during PCIS, the duration of deep sleep was longer (OR = 1.038; 95% CI, 1.001-1.077, p = 0.046) and the duration of nocturnal NREM staging was longer (OR = 1.010; patients with 95% CI, 1.000-1.020, p = 0.042) had a higher possibility of adverse outcomes. Conclusion:The sleep-wake state of patients with intracranial artery stenoischemic stroke changes. The main characteristics are increased diurnal sleep, increased incidence of daytime sleep, and disordered sleep-wake phases. In patients with ACIS, the diurnal sleep-wake biological rhythm mainly characterized by poor daytime stability is unbalanced. The longer the duration of daytime deep sleep and nighttime NREM sleep, the higher the possibility of adverse outcomes in patients with intracranial artery stenotic ischemic stroke.

ObjectiveDepressive symptoms and cognitive impairment are two common complications of cerebral small vascular disease (CSVD). This study aimed to investigate the P300 representation in CSVD patients with depressive symptoms and its relationship with depressive symptoms.MethodsWe selected 242 patients with CSVD (depression: n = 56; non-depression: n = 186) and 30 healthy controls. The Self-Rating Depression Scale and Self-Rating Anxiety Scale scales were used to assess depressive and anxiety symptoms.The latency and amplitude of P300 components were measured using event-related potential (ERP) technique to assess cognitive dysfunction. Cognitive function was evaluated using Mini-mental state examination and Event-Related Potential P300 waves latency & amplitude. Finally, logistic regression model was used to analyze the relationship between P300 representation and depressive symptoms in CSVD patients.ResultsCompared with NPSD group and Control group, the latency of P300 (P3a and P3b wave groups) in PSD group was longer and the amplitude was lower. Multivariate Logistic regression analysis showed that temporal lobe infarction (OR = 10.878, 95% CI = 2.890-40.939), brainstem infarction (OR = 4.185, 95% CI = 1.544-11.341), SAS score (OR = 1.275, 95% CI = 1.174-1.385),and P3b amplitude (OR = 0.779, 95% CI = 0.635-0.957) were independently correlated with depressive symptoms in CSVD patients (P < .05).ConclusionCSVD patients with depressive symptoms had worse cognitive function, and abnormalities in P300 waves amplitude and latency were more pronounced. The amplitude of P3b in patients with CSVD is decreased, which is significantly correlated with the occurrence of depression.

To investigate the changes in sleep architecture in patients with acute ischemic stroke (AIS) accompanied by sleep-disordered breathing (SDB), providing a basis for clinical treatment strategies. 1367 patients with acute ischemic stroke within 48 h of onset who were hospitalized in the Department of Neurology of Kailuan General Hospital from November 2020 to December 2022 were selected. Among them, 963 cases were male and 404 cases were female, age: 33-92 (66.12 ± 10.62) years old.From the start of hospitalization, patients were monitored for 5 consecutive days using the intelligent mattress type sleep monitoring platform system (IMTSMPS). From day 1 to day 5, there was a difference in non-rapid eye movement 3 (NREM3) sleep (min) day two, and day five compared to day one in the ACI without SDB group (p = 0.019), and rapid eye movement (REM) sleep (min) day three compared to day five in the ACI with SDB group (p = 0.001). TST (min), SL (min), WASO (min), TOB (min), NOA (min), HRV1, fluctuated between 5 d in mild SDB group (p < 0.05). SL (min), TOB (min), NOA (min), and HAV1(%) in the moderate SDB group, with fluctuations between 5 d (P < 0.05). TST (min), SL (min), REML(min), NREM3 (min), REM (min), proportion of REM sleep(%), TOB (min), NOA (min)in severe SDB group, there were fluctuations between 5 d (P < 0.05). SDB is one of the most common concomitant symptoms in AIS patients and is closely associated with multiple forms of altered sleep structure. AIS patients without SDB mainly showed changes in NREM3 sleep structure. AIS and SDB patients mainly showed changes in the structure of REM sleep. Different levels of SDB in AIS patients lead to different forms of structural changes in sleep.

This study employs single-cell RNA sequencing (scRNA-seq) and assay for transposase-accessible chromatin with high-throughput sequencing technologies (scATAC-seq) to perform joint sequencing on cells at various time points during the induction of adipose-derived stem cells (ADSCs) into astrocytes. We applied bioinformatics approaches to investigate the differentiation trajectories of ADSCs during their induced differentiation into astrocytes. Pseudotemporal analysis was used to infer differentiation trajectories. Additionally, we assessed chromatin accessibility patterns during the differentiation process. Key transcription factors driving the differentiation of ADSCs into astrocytes were identified using motif and footprint methods. Our analysis revealed significant shifts in gene expression during the induction process, with astrocyte-related genes upregulated and stem cell-related genes downregulated. ADSCs first differentiated into neural stem cell-like cells with high plasticity, which further matured into astrocytes via two distinct pathways. Marked changes in chromatin accessibility were observed during ADSC-induced differentiation, affecting transcription regulation and cell function. Transcription factors analysis identified NFIA/B/C/X and CEBPA/B/D as key regulators in ADSCs differentiation into astrocytes. We observed a correlation between chromatin accessibility and gene expression, with ADSCs exhibiting broad chromatin accessibility prior to lineage commitment, where chromatin opening precedes transcription initiation. In summary, we found that ADSCs first enter a neural stem cell-like state before differentiating into astrocytes. ADSCs also display extensive chromatin accessibility prior to astrocyte differentiation, although transcription has not yet been initiated. These findings offer a theoretical framework for understanding the molecular mechanisms underlying this process.

To explore the characteristics of cognitive potentials and their neuroregulatory mechanisms in patients with acute cerebellar ischemic stroke. This study included 35 patients with acute cerebellar ischemic stroke and 70 healthy controls, admitted between June 2022 and July 2024. The Oddball paradigm was used to collect cognitive potentials from the P300 series, and the characteristics of the visual P3a and P3b components were analyzed. Dipole source reconstruction was performed for the P300 components in both groups, and the differences in source distribution between the two groups were analyzed. We found that in the patient group, the latencies of all components in the P300 wave were significantly prolonged, and the amplitudes of P2 and N2 in the P3a series were significantly reduced. Source analysis revealed changes or disruptions in the brain-cerebellum circuit connectivity in the patient group. Specifically, compared to the control group, the differences in P3b source distribution in the patient group were characterized by compensatory activation in the left cerebellar vermis, while the differences in P3a source distribution were characterized by disconnection between the cerebellum and the brain’s intrinsic network. Following acute cerebellar ischemic stroke, delayed processing speed and reduced efficiency of visual information are observed, accompanied by impaired attentional control and behavioral decision-making in response to novel stimuli. Alterations or disruptions in cerebro-cerebellar circuit connectivity underscore the critical role of the cerebellar vermis in post-stroke cognitive processing. Not applicable.

Background:Klebsiella pneumoniae is an important cause of nosocomial infections and community-acquired pneumonia. However, the evolutionary convergence of multidrug resistance (MDR) and virulence factors undoubtedly increases the risk of infection and lethality of K. pneumoniae, especially in intensive care units. How to effectively prevent and correctly treat K. pneumoniae infections has become a significant challenge for healthcare professionals. Objective:To assess multidrug-resistant Klebsiella pneumoniae (MDR-KP) resistance patterns in a Neurological ICU (NICU) and guide infection control strategies. Methods:A total of 156 non-repetitive K. pneumoniae isolates from the NICU underwent strain identification and antimicrobial susceptibility testing. Six MDR-KP isolates were selected for whole genome sequencing (WGS) using high-throughput sequencing technologies, followed by comparative genomics and phylogenetic analysis. Results:Antimicrobial susceptibility testing revealed that the 6 MDR-KP strains exhibited a resistance rate of 59% to 21 commonly used antibiotics, with seven antibiotics showing a resistance rate of 100%. The sequencing results provided basic genomic information such as genome size and GC content for the 6 MDR-KP strains. Six different sequence (ST)-capsular locus (KL) types were identified: ST11-KL47, ST11-KL64, ST23-KL1, ST25-KL2, ST412-KL57, and ST753-KL3. All strains carried multiple resistance genes and virulence factors. Among them (No. P14, P97) are carbapenem-resistant K. pneumoniae (CRKP) strains, which should attract our sufficient attention. Phylogenetic analysis showed that P116 was more closely related to the reference strain KP20, and P14 had the highest affinity to P97. Conclusion:NICU K. pneumoniae could colonise patients and the ward air environment for a long time, suggesting that there may be a similar evolutionary or direct transmission relationship between strains. The ST11-KL47 and ST11-KL64 phenotypes were the dominant clone types of CRKP in China, suggesting that the ST11-type MDR-KP should be the focus of infection prevention and control in our hospital. Comparative genomics revealed homology and genetic variability of NICU K. pneumoniae.

Objective:Research is limited on whether circadian rhythm and sleep architecture alterations during acute intracerebral hemorrhage (ICH) influence patient outcomes. This study aims to characterize these changes and explore their association with clinical prognosis, offering new insights for diagnosis and treatment. Methods:We enrolled 100 acute hemorrhagic stroke patients who underwent continuous, contactless sleep monitoring via a smart mattress for 3-5 consecutive days. Prognosis was evaluated at discharge using the modified Rankin Scale (mRS), and patients were classified into favorable or unfavorable outcome groups. Circadian rhythm parameters (IS, IV, RA) and sleep metrics (eg, total sleep time, sleep latency, REM latency) during day and night were compared between groups. Multivariate logistic regression identified independent prognostic factors, and ROC analysis evaluated their predictive value. Results:Group comparisons revealed statistically significant differences in RA and nighttime sleep latency between the favorable and unfavorable prognosis groups (P < 0.05). Binary logistic regression analysis identified nighttime sleep latency as an independent predictor of functional outcome (95% CI: 1.066 ~ 1.128, P < 0.05), which remained significant after adjusting for potential confounders (95% CI: 1.016 ~ 1.148, P < 0.05). The mean nighttime sleep latency was 18.14 minutes in the favorable group and 12.30 minutes in the unfavorable group. The area under the ROC curve (AUC) for nighttime sleep latency was 0.642 (95% CI: 0.526-0.757, P = 0.028), with an optimal cutoff value of 10.95 minutes, yielding a sensitivity of 72.2% and specificity of 53.6%. Conclusion:Hemorrhagic stroke patients show disrupted circadian stability, with greater RA reductions in those with worse outcomes. Nighttime sleep latency independently predicts poor prognosis with moderate accuracy. Circadian rhythm stability may serve as a prognostic marker in hemorrhagic stroke to avoid implying causality.

Objective: To investigate the neurophysiological and cognitive impairments in patients with obstructive sleep apnea (OSA) among the acute stroke population. Methods: A total of 268 acute ischemic stroke patients with OSA underwent sleep monitoring within 24 h of admission and event-related potential tests within three days. They were categorized into groups based on their AHI: stroke only, and stroke with mild, moderate, or severe OSA. This classification served to analyze the electrophysiological profiles associated with stroke and OSA severity. Results: Compared with the control group, in the P3b series, the P3b-FZ amplitude was significantly reduced in the stroke with mild, moderate, and severe OSA group; the N2-PZ latency was significantly prolonged in the stroke with severe OSA group; and the P3b-FZ, P3b-CZ, and P3b-FZ latencies were significantly prolonged in the stroke with mild, moderate, and severe OSA group; in the P3a series, the N2-CZ amplitude was decreased in the stroke with severe OSA group, P2-FZ latency was significantly prolonged in the stroke with mild and moderate OSA group, P3a-FZ latency was significantly prolonged in the stroke with mild OSA group, P3a-CZ latency was significantly prolonged in the stroke with severe OSA group, and P3a-PZ latency was significantly prolonged in the stroke with mild and severe OSA group. Conclusions: The electrophysiologic changes compared with the stroke-only group were mainly characterized by prolonged latencies of the endogenous components P3a and P3b, suggesting that they are related to attention allocation and cognitive control.

This study introduces MTAMA-DoC (Multimodal Temporal Attention Multitask Analyzer for Disorders of Consciousness), a novel deep learning approach that leverages sleep-related physiological data to predict consciousness states in patients with Disorders of Consciousness (DoC). Employing a transformer-based architecture with task-aware guided masking and joint-optimization training, MTAMA-DoC integrates time series data (heart rate and breath rate) with structured clinical information, addressing the limitations of traditional assessment methods. In a comparative analysis involving 170 patients, our model significantly outperformed existing methods in consciousness state classification (binary classification accuracy: 0.87, F1-score: 0.82; ternary classification accuracy: 0.72, F1-score: 0.64) and demonstrated competitive performance in Glasgow Coma Scale score prediction. The model’s interpretability, achieved through attention mechanisms and feature importance analysis, provides valuable insights into the temporal dynamics of physiological signals and the relative importance of clinical factors in consciousness assessment, highlighting the critical role of cardiovascular and respiratory metrics, as well as sleep architecture features. By demonstrating the efficacy of sleep-related data in consciousness evaluation, MTAMA-DoC not only enhances diagnostic capabilities but also contributes to the theoretical understanding of the sleep-consciousness relationship, offering a non-invasive, continuous monitoring approach that complements traditional clinical methods. This advancement opens new avenues for AI-driven approaches in neurology and sleep medicine, potentially improving diagnosis and care for patients with disorders of consciousness, while paving the way for future investigations into the complex interplay between sleep, consciousness, and brain function.

There is limited research on the circadian rhythm and sleep state in patients with acute cerebral infarction (ACI) accompanied by sleep-breathing disorders (SDB). This study aims to provide a scientific basis for individualized diagnosis and treatment for stroke-related SDB patients. The SC-500 sleep monitor was used to continuously monitor 1367 ACI patients over 5 days. Based on the apnea–hypopnea index (AHI), patients were divided into non-SDB group (normal) and SDB group (mild, moderate, severe, fluctuating). Interdaily stability (IS) and intradaily variability (IV) were calculated through heart rate monitoring, and sleep states and their correlations were analyzed. Compared to the non-SDB group, patients with moderate-to-severe ACI accompanied by SDB showed decreased IS, increased IV, and sleep fragmentation. Significant statistical differences were observed in total sleep time (TST), rapid eye movement latency (REML), sleep efficiency (SE), non-rapid eye movement stages 1–2 (NREM stages1–2), non-rapid eye movement stages 3–4 (NREM stages 3–4), proportion of non-rapid eye movement (NREM%), wake after sleep onset (WASO), and number of awakenings (NOA) between the SDB group and the non-SDB group ( P < 0.05). AHI showed a strong negative correlation with IS and a strong positive correlation with IV. AHI was positively correlated with sleep latency (SL), REML, NREM stages1–2, NREM%, proportion of rapid eye movement (REM%), WASO, time out of bed (TOB), and NOA, and negatively correlated with TST, SE, NREM stages 3–4, and rapid eye movement (REM), all with statistical significance ( P < 0.05). There were significant statistical differences in the Mini-Mental State Examination (MMSE) between patients with and without SDB, and among mild, moderate, severe, and fluctuating groups ( P < 0.05). Patients with moderate-to-severe ACI accompanied by SDB are more likely to experience changes in circadian rhythm and sleep states, which in turn affect cognitive functions.

PURPOSE:To continuously and dynamically monitor the sleep status of patients in the acute phase of cerebral infarction, and to investigate the characteristics of acute cerebral infarction(ACI)associated with sleep-disordered breathing (SDB), variations in sleep structure, and changes in sleep circadian rhythms. METHODS:Patients with ACI within 48 h of onset who were admitted to the Department of Neurology at Kailuan General Hospital from November 2020 to December 2022 were selected. Detailed baseline information such as age, gender, smoking history, drinking history, were recorded for the selected participants. From the beginning of their hospitalization, the selected participants were monitored for their sleep status continuously for 5 days using the Intelligent Mattress-based Sleep Monitoring Platform System(IMSMPS). Based on the heart rate data obtained from the monitoring, the interdaily stability (IS) and intradaily variability (IV) of the sleep circadian rhythm were calculated. RESULTS:1,367 patients with ACI were selected. Monitoring results over 5 days indicated 147 cases (10.75%) without SDB, and 1,220 cases (89.25%) with SDB. Among the group with SDB, there were 248 cases (18.14%) with continuous mild SDB, 395 cases (28.90%) with moderate SDB, 295 cases (21.58%) with severe SDB, and 282 cases (20.63%) that fluctuated between different severity levels. Within this fluctuating group, 152 cases (53.90%) fluctuated between two severity levels, 120 cases (42.55%) between three levels, and 10 cases (3.55%) among all four levels. There were statistically significant differences (P < 0.05) in the sleep latency, sleep efficiency, non-rapid eye movement stages 1-2, rapid eye movement, proportion of non-rapid eye movement, proportion of rapid eye movement, wake after sleep onset, time out of bed, number of awakenings, respiratory variability index, and heart rate variability index among patients with ACI monitored from day 1 to 5. However, other monitored sleep structure parameters did not show statistically significant differences (P > 0.05). The coefficient of variation for all sleep monitoring parameters ranged between 14.54 and 36.57%. The IV in the SDB group was higher than in the group without SDB (P < 0.05), and the IS was lower than in the group without SDB (P < 0.05). CONCLUSION:Patients in the acute phase of cerebral infarction have a high probability of accompanying SDB. The sleep structure of these patients shows significant variability based on the onset time of the stroke, and some patients experience fluctuations among different severity levels of SDB. ACI accompanied by SDB can further reduce the IS of a patient's sleep circadian rhythm and increase its IV.

We employed single-cell transcriptome sequencing to reveal the dynamic gene expression changes during the differentiation of adipose-derived stromal cells (ADSCs) into astrocytes. Single-cell RNA sequencing was conducted on cells from the ADSCs group and the induced groups at 2, 7, 14, and 21 days using the 10 × Chromium platform. Data underwent quality control and dimensionality reduction. Cell differentiation trajectories were constructed using Monocle2, and differentially expressed genes (DEGs) in each cell cluster were identified using differential selection algorithms. DEGs at each time point were annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and regulatory intensities of transcription factors were analyzed using SCENIC. Integrating all groups, a total of five samples were divided into 13 cell clusters (0–12 clusters). DEGs between clusters and those compared with ADSCs at various induced time points showed distinct specificities. Monocle2 constructed cell differentiation trajectories; ADSCs can differentiate into mature astrocytes not only through the direct pathway from the 1 branch to the 3 branch but also through an indirect pathway, involving the 1 branch to the 2 branch before progressing to the 3 branch. SCENIC analysis highlighted the critical regulatory roles of STAT1, MYEF2, and SOX6 transcription factors during the differentiation of ADSCs into astrocytes. ADSCs can differentiate into mature astrocytes through two distinct pathways: direct and indirect. By the 14th day of induction, mature astrocytes have formed, characterized by a cell cycle arrest in mitosis. Further induction leads to degenerative senescence changes in differentiated cells.

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

Adipose-derived stromal cells (ADSCs) can be induced to differentiate into neurons, representing the most promising avenue for cell therapy. However, the molecular mechanism and genomic characteristics of the differentiation of ADSCs into neurons remain poorly understood. In this study, cells from the adult ADSCs group, induction 1h, 3h, 5h, 6h, and 8h groups were selected for single-cell RNA sequencing (scRNA-Seq). Samples from these seven-time points were sequenced and analyzed. The expression of neuron marker genes, including NES, MAP2, TMEM59L, PTK2B, CHN1, DNM1, NRSN2, FBLN2, SCAMP1, SLC1A1, DLG4, CDK5, and ENO2, was found to be low in the ADSCs group, but highly expressed in differentiated cell clusters. The expression of stem cell marker genes, including CCND1, IL1B, MMP1, MMP3, MYO10, and BMP2, was the highest in the ADSCs cluster. This expression decreased significantly with the extension of induction time. Gene ontology (GO) enrichment analysis of upregulated genes in the induced samples showed that the biological processes related to neuronal differentiation and development, such as neuronal differentiation, projection, and apoptosis, were significantly upregulated with a longer induction time during cell cluster differentiation. The results of the cell communication analysis demonstrated the gradual formation of complex neural network connections between ADSC-derived neurons through receptor and ligand pairs at 5h after the induction of differentiation.

Synapses are essential for facilitating the transmission of information between neurons and for executing neurophysiological processes. Following the exocytosis of neurotransmitters, the synaptic vesicle may quickly undergo endocytosis to preserve the structural integrity of the synapse. When converting adipose-derived stromal cells (ADSCs) into neurons, the ADSCs have already demonstrated comparable morphology, structure, and electrophysiological characteristics to neurons. Nevertheless, there is currently no published study on the endocytotic function of neurons that are produced from ADSCs. This study aimed to examine synaptic endocytosis in neurons derived from ADSCs by qualitatively and quantitatively analyzing the presence of Ap-2, Clathrin, Endophilin, Dynamin, and Hsc70, which are the key proteins involved in clathrin-mediated endocytosis (CME), as well as by using FM1-43 and cadmium selenide quantum dots (CdSe QDs). Additionally, single-cell RNA sequencing (scRNA-seq) was used to look at the levels of both neuronal markers and markers related to CME at the same time. The results of this study provide evidence that synapses in neurons produced from ADSCs have a role in endocytosis, mainly through the CME route.