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IntroductionBrain computer interface-based action observation (BCI-AO) is a promising technique in detecting the user's cortical state of visual attention and providing feedback to assist rehabilitation. Peripheral nerve electrical stimulation (PES) is a conventional method used to enhance outcomes in upper extremity function by increasing activation in the motor cortex. In this study, we examined the effects of different pairings of peripheral nerve electrical stimulation (PES) during BCI-AO tasks and their impact on corticospinal plasticity.Materials and methodsOur innovative BCI-AO interventions decoded user's attentive watching during task completion. This process involved providing rewarding visual cues while simultaneously activating afferent pathways through PES. Fifteen stroke patients were included in the analysis. All patients underwent a 15 min BCI-AO program under four different experimental conditions: BCI-AO without PES, BCI-AO with continuous PES, BCI-AO with triggered PES, and BCI-AO with reverse PES application. PES was applied at the ulnar nerve of the wrist at an intensity equivalent to 120% of the sensory threshold and a frequency of 50 Hz. The experiment was conducted randomly at least 3 days apart. To assess corticospinal and peripheral nerve excitability, we compared pre and post-task (post 0, post 20 min) parameters of motor evoked potential and F waves under the four conditions in the muscle of the affected hand.ResultsThe findings indicated that corticospinal excitability in the affected hemisphere was higher when PES was synchronously applied with AO training, using BCI during a state of attentive watching. In contrast, there was no effect on corticospinal activation when PES was applied continuously or in the reverse manner. This paradigm promoted corticospinal plasticity for up to 20 min after task completion. Importantly, the effect was more evident in patients over 65 years of age.ConclusionThe results showed that task-driven corticospinal plasticity was higher when PES was applied synchronously with a highly attentive brain state during the action observation task, compared to continuous or asynchronous application. This study provides insight into how optimized BCI technologies dependent on brain state used in conjunction with other rehabilitation training could enhance treatment-induced neural plasticity.

BackgroundPredicting the bed occupancy rate (BOR) is essential for efficient hospital resource management, long-term budget planning, and patient care planning. Although macro-level BOR prediction for the entire hospital is crucial, predicting occupancy at a detailed level, such as specific wards and rooms, is more practical and useful for hospital scheduling. ObjectiveThe aim of this study was to develop a web-based support tool that allows hospital administrators to grasp the BOR for each ward and room according to different time periods. MethodsWe trained time-series models based on long short-term memory (LSTM) using individual bed data aggregated hourly each day to predict the BOR for each ward and room in the hospital. Ward training involved 2 models with 7- and 30-day time windows, and room training involved models with 3- and 7-day time windows for shorter-term planning. To further improve prediction performance, we added 2 models trained by concatenating dynamic data with static data representing room-specific details. ResultsWe confirmed the results of a total of 12 models using bidirectional long short-term memory (Bi-LSTM) and LSTM, and the model based on Bi-LSTM showed better performance. The ward-level prediction model had a mean absolute error (MAE) of 0.067, mean square error (MSE) of 0.009, root mean square error (RMSE) of 0.094, and R2 score of 0.544. Among the room-level prediction models, the model that combined static data exhibited superior performance, with a MAE of 0.129, MSE of 0.050, RMSE of 0.227, and R2 score of 0.600. Model results can be displayed on an electronic dashboard for easy access via the web. ConclusionsWe have proposed predictive BOR models for individual wards and rooms that demonstrate high performance. The results can be visualized through a web-based dashboard, aiding hospital administrators in bed operation planning. This contributes to resource optimization and the reduction of hospital resource use.

BackgroundMetabolic reprogramming plays a significant role in the advancement of lung adenocarcinoma (LUAD), yet the precise metabolic changes remain incompletely understood. This study aims to uncover metabolic indicators associated with the progression of LUAD.MethodsA total of 1083 subjects were recruited, including 670 LUAD, 135 benign lung nodules (BLN) and 278 healthy controls (HC). Gas chromatography-mass spectrometry (GC/MS) was used to identify and quantify plasma metabolites. Odds ratios (ORs) were calculated to determine LUAD risk factors, and machine learning algorithms were utilized to differentiate LUAD from BLN.ResultsHigh levels of oxalate, glycolate, glycine, glyceric acid, aminomalonic acid, and creatinine were identified as risk factors for LUAD (adjusted ORs>1.2, P

Abstract Perovskite solar cells offer a promising future for next‐generation photovoltaics owing to numerous advantages such as high efficiency and ease of processing. However, two significant challenges, air stability, and manufacturing costs, hamper their commercialization. This study proposes a solution to these issues by introducing a floating catalyst‐based carbon nanotube (CNT) electrode into all‐inorganic perovskite solar cells for the first time. The use of CNT eliminates the need for metal electrodes, which are primarily responsible for high fabrication costs and device instability. The nanohybrid film formed by combining hydrophobic CNT with polymeric hole‐transporting materials acted as an efficient charge collector and provided moisture protection. Remarkably, the metal‐electrode‐free CNT‐based all‐inorganic perovskite solar cells demonstrated outstanding stability, maintaining their efficiency for over 4000 h without encapsulation in air. These cells achieved a retention efficiency of 13.8%, which is notable for all‐inorganic perovskites, and they also exhibit high transparency in both the visible and infrared regions. The obtained efficiency was the highest for semi‐transparent all‐inorganic perovskite solar cells. Building on this, a four‐terminal tandem device using a low‐band perovskite solar cell achieved a power conversion efficiency of 21.1%. These CNT electrodes set new benchmarks for the potential of perovskite solar cells with groundbreaking device stability and tandem applicability, demonstrating a step toward industrial applications.

BackgroundTo evaluate the cumulative summation (CUSUM) analysis of the learning curve for Endoscopic Endonasal Transsphenoidal resection of craniopharyngioma (EETC).MethodsRetrospectively analyzed the clinical data of 113 patients who underwent EETC by the same neurosurgery team of the first affiliated Hospital of Nanchang University from June 2012 to November 2020. The learning curve was created by the CUSUM method and analyzed, which was divided into two groups: the learning stage and stable stage based on the learning curve trend. The median operation time and minimum surgical case number was calculated and the operation time and postoperative complications were compared between the two groups.ResultsThe median operation time was 318 min. The best fitting curve equation was y = 227.72 + 49.06x + 0.14x2 − 0.05x3, R2 = 0.949, (p

Consumption of fried foods is highly prevalent in the Western dietary pattern. Western diet has been unfavorably linked with high risk of developing cardiovascular diseases. Heart failure (HF) as a cardiovascular disease subtype is a growing global pandemic with high morbidity and mortality. However, the causal relationship between long-term fried food consumption and incident HF remains unclear. Our population-based study revealed that frequent fried food consumption is strongly associated with 15% higher risk of HF. The causal relationship may be ascribed to the dietary acrylamide exposure in fried foods. Further cross-sectional study evidenced that acrylamide exposure is associated with an increased risk of HF. Furthermore, we discover and demonstrate that chronic acrylamide exposure may induce HF in zebrafish and mice. Mechanistically, we reveal that acrylamide induces energy metabolism disturbance in heart due to the mitochondria dysfunction and metabolic remodeling. Moreover, acrylamide exposure induces myocardial apoptosis via inhibiting NOTCH1-phosphatidylinositol 3-kinase/AKT signaling. In addition, acrylamide exposure could affect heart development during early life stage, and the adverse effect of acrylamide exposure is a threat for next generation via epigenetic change evoked by DNA methyltransferase 1 (DNMT1). In this study, we reveal the adverse effects and underlying mechanism of fried foods and acrylamide as a typical food processing contaminant on HF from population-based observations to experimental validation. Collectively, these results both epidemiologically and mechanistically provide strong evidence to unravel the mechanism of acrylamide-triggered HF and highlight the significance of reducing fried food consumption for lower the risk of HF.

Abstract The mid‐high latitude intraseasonal oscillation (ISO) has remarkable impacts on the Northern Hemisphere. However, the interannual variance of the mid‐high latitude ISO and its underlying mechanism are rarely explored. Here, we find that the tropical stratospheric Quasi‐Biennial Oscillation (QBO) has notable impacts. A statistically significant contrast in the interannual variability of intraseasonal 2‐m temperature (T2m) over northern Eurasia is detected between the easterly (EQBO) and westerly (WQBO) QBO phase. The influence of the QBO could be attributed to the interactions of ISO perturbation and QBO‐related winter‐mean flow. Specifically, the ISO perturbation is more efficient in extracting kinetic and potential energy from the winter‐mean flow in EQBO. Additionally, the northern Eurasia ISO propagates southeastward and exert effects on China. Due to this, the subseasonal forecast system of NUIST (NUIST CFS1.1) displays higher skill in predicting the T2m in China during EQBO phase at 3, 4, and 5 pentads in advance.

IntroductionDespite the current effective treatments for acute promyelocytic leukemia (APL), early mortality (EM), defined as death within 30 days of presentation, is a major hurdle to long-term survival.MethodsWe performed a multicenter retrospective study to evaluate the incidence and clinical characteristics of EM in patients with newly diagnosed APL and to develop a risk stratification model to predict EM.ResultsWe identified 313 eligible patients diagnosed between 2000 and 2021 from five academic hospitals. The median age was 50 years (range 19-94), and 250 (79.9%) patients were 24 hours of presentation (HR, 2.95). Based on these factors, patients were stratified into three categories with a significantly increasing risk of EM: 4.1% for low risk (54.3%; no risk factors; HR 1), 18.5% for intermediate risk (34.5%; 1 factor; HR 4.81), and 40.5% for high risk (11.2%; 2-3 factors; HR 13.16).DiscussionThe risk of EM is still not negligible in this era of ATRA-based therapies. Our risk model serves as a clinically useful tool to identify high-risk patients for EM who may be candidates for novel treatments and aggressive supportive strategies.

Background and Objective: Although interest in predicting drug-drug interactions is growing, many predictions are not verified by real-world data. This study aimed to confirm whether predicted polypharmacy side effects using public data also occur in data from actual patients. Methods: We utilized a deep learning-based polypharmacy side effects prediction model to identify cefpodoxime-chlorpheniramine-lung edema combination with a high prediction score and a significant patient population. The retrospective study analyzed patients over 18 years old who were admitted to the Asan medical center between January 2000 and December 2020 and took cefpodoxime or chlorpheniramine orally. The three groups, cefpodoxime-treated, chlorpheniramine-treated, and cefpodoxime & chlorpheniramine-treated were compared using inverse probability of treatment weighting (IPTW) to balance them. Differences between the three groups were analyzed using the Kaplan-Meier method and Cox proportional hazards model. Results: The study population comprised 54,043 patients with a history of taking cefpodoxime, 203,897 patients with a history of taking chlorpheniramine, and 1,628 patients with a history of taking cefpodoxime and chlorpheniramine simultaneously. After adjustment, the 1-year cumulative incidence of lung edema in the patient group that took cefpodoxime and chlorpheniramine simultaneously was significantly higher than in the patient groups that took cefpodoxime or chlorpheniramine only (p=0.001). Patients taking cefpodoxime and chlorpheniramine together had an increased risk of lung edema compared to those taking cefpodoxime alone [hazard ratio (HR) 2.10, 95% CI 1.26–3.52, p

Kinesin-3 is a family of microtubule-dependent motor proteins that transport various cargos within the cell. However, the mechanism underlying kinesin-3 activations remains largely elusive. In this study, we compared the biochemical properties of two Caenorhabditis elegans kinesin-3 family proteins, KLP-6 and UNC-104. Both KLP-6 and UNC-104 are predominantly monomeric in solution. As previously shown for UNC-104, non-processive KLP-6 monomer is converted to a processive motor when artificially dimerized. We present evidence that releasing the autoinhibition is sufficient to trigger dimerization of monomeric UNC-104 at nanomolar concentrations, which results in processive movement of UNC-104 on microtubules, although it has long been thought that enrichment in the phospholipid microdomain on cargo vesicles is required for the dimerization and processive movement of UNC-104. In contrast, KLP-6 remains to be a non-processive monomer even when its autoinhibition is unlocked, suggesting a requirement of other factors for full activation. By examining the differences between KLP-6 and UNC-104, we identified a coiled-coil domain called coiled-coil 2 (CC2) that is required for the efficient dimerization and processive movement of UNC-104. Our results suggest a common activation mechanism for kinesin-3 family members, while also highlighting their diversification.

It is currently a challenge to perform noninvasive molecular biological analysis of in vitro fertilized embryos. In this issue of Cell Genomics, Wu et al.1 developed a non-invasive method to evaluate human pre-implantation embryos by characterizing the extracellular RNAs in spent media from the culture of in vitro fertilization embryos.

The COVID-19 pandemic has led to an abrupt transition from face-to-face learning to online learning, which has also affected the mental health of college students. In this study, we examined the relationship between students adjustment to online learning and their mental health by using the Dual-Continua Model. The model assumes that mental disorder and mental well-being are related yet distinct factors of mental health. For this purpose, 2,933 college students completed an online survey around the beginning of the Fall semester of 2020 (N = 1,724) and the Spring semester of 2021 (N = 1,209). We assessed participants mental well-being, mental disorders, and academic distress by means of the online survey. In addition, we incorporated grades and log data accumulated in the Learning Management System (LMS) as objective learning indicators of academic achievement and engagement in online learning. Results revealed that two dimensions of mental health (i.e., mental well-being and mental disorder) were independently associated with all objective and subjective online learning indicators. Specifically, languishing (i.e., low levels of mental well-being) was negatively associated with student engagement derived from LMS log data and academic achievement and was positively associated with self-reported academic distress even after we controlled for the effects of mental disorder. In addition, mental disorder was negatively related to student engagement and academic achievement and was positively related to academic distress even after we controlled for the effects of mental well-being. These results remained notable even when we controlled for the effects of sociodemographic variables. Our findings imply that applying the Dual-Continua Model contributes to a better understanding of the relationship between college students mental health and their adaptation to online learning. We suggest that it is imperative to implement university-wide interventions that promote mental well-being and alleviate psychological symptoms for students successful adjustment to online learning.