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Background: Accurate evaluation of level of disorder of consciousness (DOC) is clinically challenging. Objective: This study aimed to establish a distinctive DOC-related pattern (DOCRP) for assessing disease severity and distinguishing unresponsive wakefulness syndrome (UWS) from minimally conscious state (MCS). Methods: Fifteen patients with DOC and eighteen health subjects with F-18-fluorodeoxyglucose (F-18-FDG) positron emission tomography (PET) were enrolled in this study. All patients were assessed by Coma Recovery Scale-Revised (CRS-R) and all individuals were randomly divided into two cohorts (Cohort A and B). DOCRP was identified in Cohort A and subsequently validated in Cohort B and A+B. We also assessed the discriminatory power of DOCRP between MCS and UWS. Results: The DOCRP was characterized bilaterally by relatively decreased metabolism in the medial and lateral frontal lobes, parieto-temporal lobes, cingulate gyrus and caudate, associated with relatively increased metabolism in the cerebellum and brainstem. DOCRP expression exhibited high accuracy in differentiating DOC patients from controls (P

Major depressive disorder, schizophrenia, and bipolar disorder are three major psychiatric disorders that significantly impact the well-being and overall health of patients. Some researches indicate that abnormalities in the gut microbiota can trigger certain psychiatric diseases. Microbiota-derived extracellular vesicles have the ability to transfer bioactive compounds into host cells, altering signaling and biological processes, ultimately influencing the mental health and illness of the host. This review aims to investigate the emerging roles of microbiota-derived extracellular vesicles in these three major psychiatric disorders and discusses their roles as diagnostic biomarkers and therapies for these psychiatric disorders.

Schizophrenia is a serious mental disease that is regulated by multiple genes and influenced by multiple factors. Due to the complexity of its etiology, the pathogenesis is still unclear. MicroRNAs belong to a class of small non-coding RNAs that are highly conserved in endogenous evolution and play critical roles in multiple biological pathways. In recent years, aberrant miRNA expression has been implicated in schizophrenia, with certain miRNAs emerging as potential diagnostic and prognostic biomarkers for this disorder. In this review, our objective is to investigate the differential expression of miRNAs in schizophrenia, elucidate their potential mechanisms of action, and assess their feasibility as biomarkers. The PubMed electronic database and Google Scholar were searched for the years 2003 to 2024. The study focused on schizophrenia and miRNA as the research topic, encompassing articles related to biomarkers, etiology, action mechanisms, and differentially expressed genes associated with schizophrenia and miRNA. A total of 1488 articles were retrieved, out of which 49 were included in this scope review. This study reviewed 49 articles and identified abnormal expression of miRNA in different tissues of both schizophrenia patients and healthy controls, suggesting its potential role in the pathogenesis and progression of schizophrenia. Notably, several specific miRNAs, including miR-34a, miR-130b, miR-193-3p, miR-675-3p, miR-1262, and miR-218-5p, may serve as promising biological markers for diagnosing schizophrenia. Furthermore, this study summarized potential mechanisms through which miRNAs may contribute to the development of schizophrenia. The studies within the field of miRNA’s role in schizophrenia encompass a broad spectrum of focus. Several selected studies have identified dysregulated miRNAs associated with schizophrenia across various tissues, thereby highlighting the potential utility of specific miRNAs as diagnostic biomarkers for this disorder. Various mechanisms underlying dysregulated miRNAs in schizophrenia have been explored; however, further investigations are needed to determine the exact mechanisms by which these dysregulated miRNAs contribute to the pathogenesis of this condition. The exploration of miRNA’s involvement in the etiology and identification of biomarkers for schizophrenia holds significant promise in informing future clinical trials and advancing our understanding in this area.

Abstract Tumor metastasis remains a leading factor in the failure of cancer treatments and patient mortality. To address this, a silver‐induced absorption red‐shifted core‐shell nano‐particle is developed, and surface‐modified with triphenylphosphonium bromide (TPP) and hyaluronic acid (HA) to obtain a novel nanodiagnosis‐treatment agent (Ag@CuS‐TPP@HA). This diagnosis‐treatment agent can dual‐targets cancer cells and mitochondria, and exhibits maximal light absorption at 1064 nm, thereby enhancing nesr‐infrared II (NIR‐II) photoacoustic (PA) signal and photothermal effects under 1064 nm laser irradiation. Additionally, the silver in Ag@CuS‐TPP@HA can catalyze the Fenton‐like reactions with H2O2 in the tumor tissue, yielding reactive oxygen species (ROS). The ROS production, coupled with enhanced photothermal effects, instigates immunogenic cell death (ICD), leading to a substantial release of tumor‐associated antigens (TAAs) and damage‐associated molecular patterns, which have improved the tumor immune suppression microenvironment and boosting immune checkpoint blockade therapy, thus stimulating a systemic antitumor immune response. Hence, Ag@CuS‐TPP@HA, as a cancer diagnostic‐treatment agent, not only accomplishes targeted the NIR‐II PA imaging of tumor tissue and addresses the challenge of accurate diagnosis of deep cancer tissue in vivo, but it also leverages ROS/photothermal therapy to enhance immune checkpoint blockade, thereby eliminating primary tumors and effectively inhibiting distant tumor growth.

The research on magnetic regulation of manganese oxide systems with strongly correlated electron properties is increasingly active due to rich physical mechanisms and experimental phenomena. Here, Co and Cr were used to substitute the Mn-site of narrow-bandwidth half-doped Pr0.5Ca0.5MnO3 to investigate an effective alternative path to manipulate the magnetism of the PrMnO3-based manganites. The charge-exchange-type charge-ordered state of the parent material is affected significantly differently due to the varying destruction degrees of the internal spin-ordered state caused by the two elements. The competition between the ferromagnetism (FM) double-exchange and antiferromagnetism (AFM) super-exchange interactions, which initially existed only in Mn3+/4+-O-Mn3+/4+ bonds, has added Co3+-O-Mn3+/4+/Co3+ and Cr3+-O-Mn3+/4+/Cr3+ bonds, and the strength is affected by changes in various microstructure. The dynamic changes of magnetic exchange interactions result in the magnetic properties of Co-doped samples developing from the FM-AFM coexisting state to the weak FM state with the increase of doping content, while Cr-doped samples evolve from the FM state to the ferrimagnetic state. The results revealed that different magnetic states are attributed to differences in the intrinsic properties of these two elements, and the rich magnetic evolution process originates from the coexistence and competition of multiple interactions. The interesting experimental phenomena and detailed mechanism analysis contribute to the modification and application of narrow-bandwidth manganese oxides.

MicroRNAs (miRNAs) bind on the 3′ untranslated region (3′UTR) of messenger RNAs (mRNAs) and regulate mRNA expression in physiological and pathological conditions, including cancer. Thus, studies have identified miRNAs as potential biomarkers by correlating the miRNA expression with the expression of important mRNAs and/or clinical outcomes in cancers. However, tumors undergo pervasive 3′UTR shortening/lengthening events through alternative polyadenylation (APA), which varies the number of miRNA target sites in mRNA, raising the number of miRNA target sites (numTS) as another important regulatory axis of the miRNA binding effects. In this study, we developed the first statistical method, BIOMATA-APA, to identify predictive miRNAs based on numTS features. Running BIOMATA-APA on The Cancer Genome Atlas (TCGA) and independent cohort data both with immunotherapy and no immunotherapy, we demonstrated for the first time that the numTS feature 1) distinguishes different cancer types, 2) predicts tumor proliferation and immune infiltration status, 3) explains more variation in the proportion of tumor-infiltrating immune cells, 4) predicts response to immune checkpoint blockade (ICB) therapy, and 5) adds prognostic power beyond clinical and miRNA expression. To the best of our knowledge, this is the first pan-cancer study to systematically demonstrate numTS as a novel type of biomarker representing the miRNA binding effects underlying tumorigenesis and pave the way to incorporate miRNA target sites for miRNA biomarker identification. Another advantage of examining the miRNA binding effect using numTS is that it requires only RNA-Seq data, not miRNAs, thus resulting in high power in the miRNA biomarker identification.

Stroke is a major cause of mortality and morbidity and most acute strokes are ischemic. Evidence-based medicine has demonstrated the effectiveness of constraint-induced movement therapy (CIMT) in the recovery of motor function in patients after ischemic stroke, but the specific treatment mechanism remains unclear. Herein, our integrated transcriptomics and multiple enrichment analysis studies, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) studies show that CIMT conduction broadly curtails immune response, neutrophil chemotaxis, and chemokine-mediated signaling pathway, CCR chemokine receptor binding. Those suggest the potential effect of CIMT on neutrophils in ischemic mice brain parenchyma. Recent studies have found that accumulating granulocytes release extracellular web-like structures composed of DNA and proteins called neutrophil extracellular traps (NETs), which destruct neurological function primarily by disrupting the blood–brain barrier and promoting thrombosis. However, the temporal and spatial distribution of neutrophils and their released NETs in parenchyma and their damaging effects on nerve cells remain unclear. Thus, utilizing immunofluorescence and flow cytometry, our analyses uncovered that NETs erode multiple regions such as primary motor cortex (M1), striatum (Str), nucleus of the vertical limb of the diagonal band (VDB), nucleus of the horizontal limb of the diagonal band (HDB) and medial septal nucleus (MS), and persist in the brain parenchyma for at least 14 days, while CIMT can reduce the content of NETs and chemokines CCL2 and CCL5 in M1. Intriguingly, CIMT failed to further reduce neurological deficits after inhibiting the NET formation by pharmacologic inhibition of peptidylarginine deiminase 4 (PAD4). Collectively, these results demonstrate that CIMT could alleviate cerebral ischemic injury induced locomotor deficits by modulating the activation of neutrophils. These data are expected to provide direct evidence for the expression of NETs in ischemic brain parenchyma and novel insights into the mechanisms of CIMT protecting against ischemic brain injury.

Using historical information from traffic accidents to predict accidents has always been an area of active exploration by researchers in the field of transportation. However, predicting only the occurrence of traffic accidents is insufficient for providing comprehensive information to relevant authorities. Therefore, further classification of predicted traffic accidents is necessary to better identify and prevent potential hazards and the escalation of accidents. Due to the significant disparity in the occurrence rates of different severity levels of traffic accidents, data imbalance becomes a critical issue. To address the challenge of predicting extremely imbalanced traffic accident events, this paper introduces a predictive framework named ReMAHA–CatBoost. To evaluate the effectiveness of ReMAHA–CatBoost, we conducted experiments on the US–Accidents traffic accident dataset, where the class label imbalance reaches up to 91.40 times. The experimental results demonstrate that the proposed model in this paper exhibits exceptional predictive performance in the domain of imbalanced traffic accident prediction.

Most existing road network matching algorithms are designed based on previous rules and do not fully utilize the potential of big data and historical tracks. To solve this problem, we introduce a new road network matching algorithm based on deep learning and using the topology information of the road network. Taking inspiration from the sequence-to-sequence (seq2seq) model popular in natural language processing, our algorithm builds multiple grid-dependent dictionaries based on the topology of road networks. Then the Byte Pair Encoding (BPE) algorithm is used to compress the grid dictionary, which effectively restricts the output range. A Bidirectional gated loop unit (Bi-GRU) with attention mechanisms is used as a recurrent neural network to capture information from a sequence of trajectory points. The model output feedback obtained by training the road network on Yibin City and the empirical evidence of the comparison in this experiment prove the effectiveness of the algorithm. When juxtaposed with similar algorithms, it shows superior accuracy and faster training speeds in road networks matching different scenarios.

The ability to accurately forecast the spread of coronavirus disease 2019 (COVID-19) is of great importance to the resumption of societal normality. Existing methods of epidemic forecasting often ignore the comprehensive analysis of multiple epidemic prevention measures. This paper aims to analyze various epidemic prevention measures through a compound framework. Here, a susceptible-vaccinated-infected-recovered-deceased (SVIRD) model is constructed to consider the effects of population mobility among origin and destination, vaccination, and positive retest populations. And we further use real-time observations to correct the model trajectory with the help of data assimilation. Seven prevention measures are used to analyze the short-term trend of active cases. The results of the synthetic scene recommended that four measures—improving the vaccination protection rate (IVPR), reducing the number of contacts per person per day (RNCP), selecting the region with less infected people as origin A (SES-O) and limiting population flow entering from A to B per day (LAIP-OD)—are the most effective in the short-term, with maximum reductions of 75%, 53%, 35% and 31%, respectively, in active cases after 150 days. The results of the real-world experiment with Hong Kong as the origin and Shenzhen as the destination indicate that when the daily vaccination rate increased from 5% to 9.5%, the number of active cases decreased by only 7.35%. The results demonstrate that reducing the number of contacts per person per day after productive life resumes is more effective than increasing vaccination rates.

Background and purposeThe effects of conventional protocols of repetitive transcranial magnetic stimulation (rTMS) in the chronic phase of stroke are limited. This study aimed to apply the sequential inhibitory and facilitatory rTMS for upper limb motor dysfunction post-stroke to observe the efficacy and explore the possible neurophysiological mechanism. We hypothesize that this protocol would both enhance the excitability of affected M1 and promote connections among motor areas.Case descriptionWe reported a 55-year-old female patient with a 1-year chronic stroke and right-sided hemiplegia, who underwent the 14-session rTMS with seven sessions of low frequency (LF) and with seven sessions of high frequency (HF). Clinical scales mainly including Fugl-Meyer Assessment of Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), neurophysiological measures, and functional near-infrared spectroscopy (fNIRS) were assessed before (T0), at the midpoint (T1), and after the intervention (T2).OutcomesThe patient exhibited post-intervention improvement in upper extremity function. There was increased excitability in the ipsilesional hemisphere and the opposite in the contralesional hemisphere. The interhemispheric inhibition (IHI) ratio increased from 2.70 to 10.81 and finally decreased to 1.34. Oxy-Hb signal was significantly decreased in affected M1 and mildly decreased in unaffected M1, while that of PMC and SMA on the affected side increased significantly.ConclusionThe sequential inhibitory and facilitatory rTMS significantly promoted motor recovery in the patient. Related mechanisms include upregulation of excitability in the ipsilesional hemisphere, return of interhemispheric balance, and neuroplasticity-induced cortical reorganization.

As one of common and severe mental illnesses, schizophrenia is difficult to be diagnosed exactly. Both its pathogenesis and the causes of its development are still uncertain because of its etiology complexity. At present, the diagnosis of schizophrenia is mainly based on the patient’s symptoms and signs, lacking reliable biomarkers that can be used for diagnosis. Circular RNAs in extracellular vesicles (EV circRNAs) can be used as promising candidate biomarkers for schizophrenia and other diseases, for they are not only high stability and disease specificity, but also are rich in contents and easy to be detected. The review is to focus on the research progress of the correlation between circRNAs and schizophrenia, and then to explores the possibility of EV circRNAs as new biomarkers for the schizophrenia diagnosis.

ObjectiveThis study aimed to compare the efficacy of contralaterally controlled functional electrical stimulation (CCFES) vs. neuromuscular electrical stimulation (NMES) for motor recovery of the lower extremity in patients with subacute stroke.Materials and methodsSeventy patients within 6 months post-stroke were randomly assigned to the CCFES group (n = 35) and the NMES group (n = 35). Both groups underwent routine rehabilitation plus 20-min electrical stimulation (CCFES or NMES) on ankle dorsiflexion muscles per day, 5 days a week, for 3 weeks. Ankle AROM (dorsiflexion), Fugl-Meyer assessment-lower extremity (FMA-LE), Barthel Index (BI), Functional Ambulation Category scale (FAC), 10-meter walking test, and surface electromyography (sEMG) were assessed at the baseline and at the end of the intervention.ResultTen patients did not complete the study (five in CCFES and five in NMES), so only 60 patients were analyzed in the end. After the 3-week intervention, FMA-LE, BI, Ankle AROM (dorsiflexion), and FAC increased in both groups (p < 0.05). Patients in the CCFES group showed significantly greater improvements only in the measurement of Fugl-Meyer assessment-lower extremity compared with the NMES group after treatment (p < 0.05). The improvement in sEMG response of tibialis anterior by CCFES was greater than NMES (p < 0.05).ConclusionContralateral controlled functional electrical stimulation can effectively improve the motor function of the lower limbs better than conventional neuromuscular electrical stimulation in subacute patients after stroke, but the effect on improving the ability to walk, such as walking speed, was not good.Clinical trial registrationhttp://www.chictr.org.cn/, identifier: ChiCTR2100045423.

Microglia are considered the main phagocytic cells in the central nervous system, remodeling neural circuits by pruning synapses during development. Microglial phagocytosis is also a crucial process in maintaining adult brain homeostasis and clearing potential toxic factors, which are recognized to be associated with neurodegenerative and neuroinflammatory disorders. For example, microglia can engulf amyloid-β plaques, myelin debris, apoptotic cells, and extracellular harmful substances by expressing a variety of specific receptors on the cell surface or by reprogramming intracellular glucose and lipid metabolism processes. Furthermore, physical exercise has been implicated to be one of the non-pharmaceutical treatments for various nervous system diseases, which is closely related to neuroplasticity and microglia functions including proliferation, activation, and phagocytosis. This review focuses on the central regulatory mechanisms related to microglia phagocytosis and the potential role of exercise training in this process.

Using neural network technology, dynamic characteristics can be learned from model output or assimilation results to train the model, which has greatly progressed recently. A data-driven data assimilation method is proposed by combining fully connected neural network with ensemble Kalman filter to emulate dynamic models from sparse and noisy observations. First, the hybrid model couples the original dynamic model with the surrogate model. The surrogate model is learned from model forecast values and assimilation results, and its performance is verified using the training accuracy/loss and the validation accuracy/loss at different training times. Second, the assimilation process includes a “two-stage” procedure. Stage 0 generates the training sets and trains the surrogate model. Then, the hybrid model is used for the next assimilation period in Stage 1. Finally, several numerical experiments are conducted using the Lorenz-63 and Lorenz-96 models to demonstrate that the proposed approach is better than the ensemble Kalman filter in different model error covariances, observation error covariances, and observation time steps. The proposed approach has also been applied to sparse observations to improve assimilation performance. This hybrid model is restricted to the form of the ensemble Kalman filter. However, the basic strategy is not restricted to any particular version of the Kalman filter.

Painted stone carvings from Pujiang Museum in Chengdu were excavated from the Ming tombs near to Chengdu Metro Line 7. The Ming burial sites were the eunuch graves of the Shu King, and their tomb was constructed mostly of stone and decorated with paintings and carvings on its surface, which are of great value. However, during their burial, these painted stone carvings suffered significant salt damage. In this research, we performed optical microscope (OM) analysis, Raman spectra (RAM), ion chromatography (IC) analysis, X-ray fluorescence spectroscopy (XRF), X-ray powder diffraction (XRD), and petrographic microscopy (PM) to clarify the salt composition and influence. According to the results, the majority of the salt on the painted layer is CaSO4·2H2O. Before excavation, interaction between acid rain, soil, and groundwater created salt efflorescence on the paint layer’s surface. The deterioration of the paint layer caused by gypsum was divided into two stages: before excavation and during in situ preservation. This research provides a foundation for the removal and prevention of salt efflorescence.

Fourth-order autonomous nonlinear differential equations can exhibit chaotic properties. In this study, we propose a family of fourth-order chaotic systems with infinite equilibrium points whose equilibria form closed curves of different shapes. First, the phase diagrams and Lyapunov exponents (LEs) of the system family are simulated. The results show that the system family has complex phase diagrams and dynamic behaviors. Simulation analysis of the Poincarè mapping and bifurcation diagrams shows that the system has chaotic characteristics. The circuit simulation model is constructed and simulated in Multisim. The circuit simulation results coincide with the numerical simulation results, which verifies the circuit feasibility of the system. Then, based on Lyapunov stability theory and the adaptive control method, the synchronous control of the system with infinite equilibria is designed. Numerical simulation results verify that the system synchronization with the adaptive control method is well. Finally, the synchronous drive system is used for image encryption, the response system is used for decryption, and color image encryption is realized by combining deoxyribonucleic acid (DNA) coding and operating rules. Therefore, this study not only enriched the research on infinite equilibria chaotic systems but also further expanded secure communication technology by combining chaotic synchronization control and DNA coding in image encryption.

Approximately two-thirds of stroke survivors experience chronic upper-limb paresis; however, treatment options are limited. Repetitive transcranial magnetic stimulation (rTMS) can enhance motor function recovery in stroke survivors, but its efficacy is controversial. We compared the efficacy of stimulating different targets in 10 chronic stroke patients with severe upper-limb motor impairment. Motor imagery-based brain–computer interface training augmented with virtual reality was used to induce neural activity in the brain region during an imagery task. Participants were then randomly assigned to two groups: an experimental group (received high-frequency rTMS delivered to the brain region activated earlier) and a comparison group (received low-frequency rTMS delivered to the contralesional primary motor cortex). Behavioural metrics and diffusion tensor imaging were compared pre- and post rTMS. After the intervention, participants in both groups improved somewhat. This preliminary study indicates that in chronic stroke patients with severe upper-limb motor impairment, inducing activation in specific brain regions during motor imagery tasks and selecting these regions as a target is feasible. Further studies are needed to explore the efficacy of this intervention.

Epstein-Barr virus (EBV) is a ubiquitous γ-herpesvirus with latent and lytic cycles. EBV replicates in the stratified epithelium but the nasopharynx is also composed of pseudostratified epithelium with distinct cell types. Latent infection is associated with nasopharyngeal carcinoma (NPC). Here, we show with nasopharyngeal conditionally reprogrammed cells cultured at the air-liquid interface that pseudostratified epithelial cells are susceptible to EBV infection. Donors varied in susceptibility to de novo EBV infection, but susceptible cultures also displayed differences with respect to pathogenesis. The cultures from one donor yielded lytic infection but cells from two other donors were positive for EBV-encoded EBERs and negative for other lytic infection markers. All cultures stained positive for the pseudostratified markers CK7, MUC5AC, α-tubulin in cilia, and the EBV epithelial cell receptor Ephrin receptor A2. To define EBV transcriptional programs by cell type and to elucidate latent/lytic infection-differential changes, we performed single cell RNA-sequencing on one EBV-infected culture that resulted in alignment with many EBV transcripts. EBV transcripts represented a small portion of the total transcriptome (~0.17%). All cell types in the pseudostratified epithelium had detectable EBV transcripts with suprabasal cells showing the highest number of reads aligning to many EBV genes. Several restriction factors (IRF1, MX1, STAT1, C18orf25) known to limit lytic infection were expressed at lower levels in the lytic subcluster. A third of the differentially-expressed genes in NPC tumors compared to an uninfected pseudostratified ALI culture overlapped with the differentially-expressed genes in the latent subcluster. A third of these commonly perturbed genes were specific to EBV infection and changed in the same direction. Collectively, these findings suggest that the pseudostratified epithelium could harbor EBV infection and that the pseudostratified infection model mirrors many of the transcriptional changes imposed by EBV infection in NPC.

Purpose. To compare the effectiveness of contralaterally controlled functional electrical stimulation (CCFES) versus neuromuscular electrical stimulation (NMES) on motor recovery of the upper limb in subacute stroke patients. Materials and Methods. Fifty patients within six months poststroke were randomly assigned to the CCFES group (n=25) and the NMES group (n=25). Both groups underwent routine rehabilitation plus 20-minute stimulation on wrist extensors per day, five days a week, for 3 weeks. Fugl-Meyer Assessment of upper extremity (FMA-UE), action research arm test (ARAT), Barthel Index (BI), and surface electromyography (sEMG) were assessed at baseline and end of intervention. Results. After a 3-week intervention, FMA-UE and BI increased in both groups (p

Functional magnetic resonance imaging (fMRI) is a neuroimaging tool which has been applied extensively to explore the pathophysiological mechanisms of neurological disorders. Spatial neglect is considered to be the failure to attend or respond to stimuli on the side of the space or body opposite a cerebral lesion. In this review, we summarize and analyze fMRI studies focused specifically on spatial neglect. Evidence from fMRI studies have highlighted the role of dorsal and ventral attention networks in the pathophysiological mechanisms of spatial neglect, and also support the concept of interhemispheric rivalry as an explanatory model. fMRI studies have shown that several rehabilitation methods can induce activity changes in brain regions implicated in the control of spatial attention. Future investigations with large study cohorts and appropriate subgroup analyses should be conducted to confirm the possibility that fMRI might offer an objective standard for predicting spatial neglect and tracking the response of brain activity to clinical treatment, as well as provide biomarkers to guide rehabilitation for patients with SN.

Cultured cell models are an essential complement to dissecting kidney proximal tubule (PT) function in health and disease but do not fully recapitulate key features of this nephron segment. We recently determined that culture of opossum kidney (OK) cells under continuous orbital shear stress (OSS) significantly augments their morphological and functional resemblance to PTs in vivo. Here we used RNASeq to identify temporal transcriptional changes upon cell culture under static or shear stress conditions. Comparison of gene expression in cells cultured under static or OSS conditions with a database of rat nephron segment gene expression confirms that OK cells cultured under OSS are more similar to the PT in vivo compared with cells maintained under static conditions. Both improved oxygenation and mechanosensitive stimuli contribute to the enhanced differentiation in these cells, and we identified temporal changes in gene expression of known mechanosensitive targets. We observed changes in mRNA and protein levels of membrane trafficking components that may contribute to the enhanced endocytic capacity of cells cultured under OSS. Our data reveal pathways that may be critical for PT differentiation in vivo and validate the utility of this improved cell culture model as a tool to study PT function.

Shortening of 3′UTRs (3′US) through alternative polyadenylation is a post-transcriptional mechanism that regulates the expression of hundreds of genes in human cancers. In breast cancer, different subtypes of tumor samples, such as estrogen receptor positive and negative (ER+ and ER–), are characterized by distinct molecular mechanisms, suggesting possible differences in the post-transcriptional regulation between the subtype tumors. In this study, based on the profound tumorigenic role of 3′US interacting with competing-endogenous RNA (ceRNA) network (3′US-ceRNA effect), we hypothesize that the 3′US-ceRNA effect drives subtype-specific tumor growth. However, we found that the subtypes are available in different sample sizes, biasing the ceRNA network size and disabling the fair comparison of the 3′US-ceRNA effect. Using normalized Laplacian matrix eigenvalue distribution, we addressed this bias and built tumor ceRNA networks comparable between the subtypes. Based on the comparison, we identified a novel role of housekeeping (HK) genes as stable and strong miRNA sponges (sponge HK genes) that synchronize the ceRNA networks of normal samples (adjacent to ER+ and ER– tumor samples). We further found that distinct 3′US events in the ER- tumor break the stable sponge effect of HK genes in a subtype-specific fashion, especially in association with the aggressive and metastatic phenotypes. Knockdown of NUDT21 further suggested the role of 3′US-ceRNA effect in repressing HK genes for tumor growth. In this study, we identified 3′US-ceRNA effect on the sponge HK genes for subtype-specific growth of ER- tumors.

In this paper, we demonstrate a tunable absorber composed of periodically patterned elliptical ring graphene metamaterial arrays. An absorption peak at 53.6μm with the maximum absorption of 49.2% of pure graphene layer has been realized. The effects of different parameters are studied by the Finite Difference Time Domain (FDTD) method. Besides, we simulate the spectra as the surrounding refractive index changes to better evaluate the sensing performance of the structure, producing a structure with the sensitivity up to 14110 nm/RIU. Finally, this paper also analyzes the absorption characteristics of bilayer graphene structure, and has a tunable dual-band selective absorption effect with a maximum absorption of 49.6%. Based on the research, it is more convenient to design the graphene-based optoelectronic devices, biosensor and environmental monitor.

In this paper, the electric field distributions and transmission characteristics of subwavelength Y-shaped metal hole arrays are studied by using the finite element method (FEM). The results show that the Y-shaped metal hole arrays can achieve light-enhanced transmission in the subwavelength region, and the electric field distributions around the corners are stronger. When the energy of surface plasmon polaritons (SPPs) and local surface plasmon (LSP) are similar, it is more favorable for the transmission of metal nanohole structure. In addition, the influence of the inclined angle, thickness, width, and period on the transmission of this structure is also discussed. The effect of the inclined angle on the transmission characteristics is particularly obvious. As the angle increases, the transmittance increases from 0.558 to 0.628 at the wavelength of 0.67 μm, and the transmittance of 0.289 at the wavelength of 1.08 μm increases to 0.840 at 1.17 μm. Through the optimization of structural parameters, we achieve a theoretical value of the refractive index sensitivity (S) as high as 900 nm/RIU, and the corresponding sensing resolution is 2.22 × 10−4 RIU. These results would be helpful in designing the refractive index sensor of high-sensitivity and band-pass filters, and have guiding significance for biological sensor applications. Keywords: Surface plasmon polaritons, Enhanced optical transmission, Subwavelength metallic hole arrays, Finite element method

ObjectiveMirror training (MTr) is a rehabilitation technique for patients with neurological diseases. There is no consensus on its effects on motor function in healthy individuals. This systematic review and meta-analysis considers the effects of MTr on motor function in healthy individuals.DesignThis is a systematic review and meta-analysis.Data sourcesWe searched six databases for studies assessing the effects of MTr on motor function in healthy individuals, published between January 1995 and December 2018. The Cochrane risk of bias was used to assess the quality of the studies. A meta-analysis was conducted with narrative synthesis.Eligibility criteria for selecting studiesEnglish-language randomised controlled trials reporting the behavioural results in healthy individuals were included.ResultsFourteen randomised controlled trials involving 538 healthy individuals were eligible. Two short-term studies showed MTr was inferior to passive vision pattern (standardised mean difference 0.57 (95% CI 0.06 to 1.08), I2=0%, p=0.03). The methods varied and there is limited evidence supporting the effectiveness of MTr compared with three alternative training patterns, with insufficient evidence to support analyses of age, skill level or hand dominance.ConclusionThe limited evidence that MTr affects motor performance in healthy individuals is weak and inconsistent among studies. It is unclear whether the effects of MTr on motor performance are more pronounced than the direct vision pattern, passive vision pattern or action observation. Further studies are needed to explore the short-term and long-term benefits of MTr and its effects on motor learning in healthy individuals.PROSPERO registration numberCRD42019128881.

Based on the transmission characteristics of surface plasmonic subwavelength structure, a multichannel plasmonic notch filter comprising two slot resonators and a nano-disk cavity with the metal-insulator-metal waveguide is proposed and investigated numerically using the finite element method (FEM). It demonstrates that our proposed structure has the novel multichannel notch filter characteristics in optical regime. And the three resonance trough wavelengths of the notch filter can be tuned by changing the radius of the nano-disk and width of the slot, which is in good agreement with the results of the coupled mode theory (CMT). Moreover, the second resonance trough wavelength of the transmission spectrum increases in almost the same intervals of 30 nm when the radius of nano-disk cavity increases in intervals of 10 nm, showing a Fano line and an obvious red-shift. At the third resonance trough, the results show that the plasmon-induced transparency (PIT) is produced. And the PIT response is strongly influenced by the separation gap between the adjacent slot cavities. Additionally, the FOM* (figure of merit) and sensitivity of this structure can be as high as 99 and 750 nm/RIU, respectively. The results of this study not only present a tunable multichannel plasmonic notch filter, but also aid in developing ultra-compact refractive index sensor in optical highly integration circuits. Keywords: Surface plasmon polaritons, Metal-insulator-metal waveguides, Plasmon-induced transparency, Plasmonic filter

In ensemble data assimilation systems, the impracticalities of full sampling and systematic error often lead to spurious correlations between two variables with low actual correlations. To solve these problems, researchers have previously proposed a covariance localization (CL) method, which mainly involves the Schur product between a state error covariance matrix and a distance-based correlation matrix. Although this CL method can reduce spurious correlations to a certain extent, observational data remain difficult to be used effectively, which results in unreasonable assimilation. In this study, we develop a new CL method coupled with a fuzzy logic control algorithm, which we call the covariance fuzzy (CF) method. The proposed CF method is a distance-based localization method with “fuzzy” vanishing correlations in data assimilation (DA) systems. To verify the effectiveness of the new algorithm, we conducted a set of experiments using an ensemble Kalman filter (EnKF) that combines the nonlinear Lorenz-96 model or the quasi-geostrophic (QG) models. First, the performances of the CL and CF methods are discussed with respect to different strength forcings, ensemble sizes, and covariance inflation factors. The experimental results show that the proposed CF method can obtain a more effective observation weight than the CL method and can reduce the errors caused by spurious correlations. Additionally, using power spectral density (PSD) as a performance evaluation index, the robustness of the proposed fuzzy logic localization method is demonstrated. However, the application of the fuzzy logic-based localization methodology to a real atmospheric model remains to be tested.

Due to the ever-increasing environmental pollution becoming progressively more serious, wind power has been widely used around the world in recent years. However, because of their randomness and intermittence, the accurate prediction of wind speeds is difficult. To address this problem, this article proposes a hybrid system for short-wind-speed prediction. The system combines the autoregressive differential moving average (ARIMA) model with a three-layer feedforward neural network. An ARIMA model was employed to predict linear patterns in series, while a feedforward neural network was used to predict the nonlinear patterns in series. To improve accuracy of the predictions, the neural network models were trained by using two methods: first-order transition rules and fuzzy first-order transition rules. The Levenberg–Marquardt (LM) algorithm was applied to update the weight and deviation of each layer of neural network. The dominance matrix method was employed to calculate the weight of the hybrid system, which was used to establish the linear hybrid system. To evaluate the performance, three statistical indices were used: the mean square error (MSE), the root mean square error (RMSE) and the mean absolute percentage error (MAPE). A set of Lorenz-63 simulated values and two datasets collected from different wind fields in Qilian County, Qinghai Province, China, were utilized as to perform a comparative study. The results show the following: (a) compared with the neural network trained by first-order transition rules, the prediction accuracy of the neural network trained by the fuzzy first-order transition rules was higher; (b) the proposed hybrid system attains superior performance compared with a single model; and (c) the proposed hybrid system balances the forecast accuracy and convergence speed simultaneously during forecasting. Therefore, it was feasible to apply the hybrid model to the prediction of real time-series.

As a therapeutic strategy for ischemic stroke, to restore or increase cerebral blood flow (CBF) is the most fundamental option. Laminar shear stress (LS), as an important force generated by CBF, mainly acts on brain microvascular endothelial cells (BMECs). In order to study whether LS was a protective factor in stroke, we investigated LS-intervented ischemic apoptosis of rat BMECs (rBMECs) through PE Annexin V/7-AAD, JC-1 and Hoechst 33258 staining to observe the membranous, mitochondrial and nuclear dysfunction. Real-time PCR and western blot were also used to test the gene and protein expressions of Tie-2, Bcl-2 and Akt, which were respectively related to maintain membranous, mitochondrial and nuclear norm. The results showed that LS could be a helpful stimulus for ischemic rBMECs survival. Simultaneously, membranous, mitochondrial and nuclear regulation played an important role in this process.

Recently, recommender systems have witnessed the fast evolution of Internet services. However, it suffers hugely from inherent bias and sparsity issues in interactions. The conventional uniform embedding learning policies fail to utilize the imbalanced interaction clue and produce suboptimal representations to users and items for recommendation. Towards the issue, this work is dedicated to bias-aware embedding learning in a decomposed manner and proposes a counterfactual graph convolutional learning (CGCL) model for personalized recommendation. Instead of debiasing with uniform interaction sampling, we follow the natural interaction bias to model users' interests with a counterfactual hypothesis. CGCL introduces bias-aware counterfactual masking on interactions to distinguish the effects between majority and minority causes on the counterfactual gap. It forms multiple counterfactual worlds to extract users' interests in minority causes compared to the factual world. Concretely, users and items are represented with a causal decomposed embedding of majority and minority interests for recommendation. Experiments show that the proposed CGCL is superior to the state-of-the-art baselines. The performance illustrates the rationality of the counterfactual hypothesis in bias-aware embedding learning for personalized recommendation. [ABSTRACT FROM AUTHOR]

Stroke is the third leading cause of long-term disability. Effective stroke rehabilitation should be provided to patients with a moderate or severe stroke so as to achieve functional recovery. Also, stroke rehabilitation is moving towards more intense therapy models that incorporate technologies such as robotics and computer games. Evidence-based guidelines are useful for promoting the best possible clinical practices. This guideline summarises the modes of stroke rehabilitation in China—three-stage rehabilitation network, rehabilitation of stroke dysfunction, training for activities of daily living, stroke complications and rehabilitation care. The aim of this guideline was to provide a synopsis of best clinical practices in the stroke rehabilitation of adult patients in China.