Fecal Microbiota Transplantation for Sleep Disturbance in Postacute COVID-19 Syndrome.

BACKGROUND & AIMS: Postacute COVID-19 syndrome (PACS) is associated with sleep disturbance, but treatment options are limited. The etiology of PACS may be secondary to alterations in the gut microbiome. Here, we report the efficacy of fecal microbiota transplantation (FMT) in alleviating post-COVID insomnia symptoms in a nonrandomized, open-label prospective interventional study. METHODS: Between September 22, 2022, and May 22, 2023, we recruited 60 PACS patients with insomnia defined as Insomnia Severity Index (ISI) ≥8 and assigned them to the FMT group (FMT at weeks 0, 2, 4, and 8; n = 30) or the control group (n = 30). The primary outcome was clinical remission defined by an ISI of <8 at 12 weeks. Secondary outcomes included changes in the Pittsburgh Sleep Quality Index, Generalized Anxiety Disorder-7 scale, Epworth Sleepiness Scale, Multidimensional Fatigue Inventory, blood cortisol and melatonin, and gut microbiome analysis on metagenomic sequencing. RESULTS: At week 12, more patients in the FMT than the control group had insomnia remission (37.9% vs 10.0%; P = .018). The FMT group showed a decrease in ISI score (P < .0001), Pittsburgh Sleep Quality Index (P < .0001), Generalized Anxiety Disorder-7 scale (P = .0019), Epworth Sleepiness Scale (P = .0057), and blood cortisol concentration (P = .035) from baseline to week 12, but there was no significant change in the control group. There was enrichment of bacteria such as Gemmiger formicilis and depletion of microbial pathways producing menaquinol derivatives after FMT. The gut microbiome profile resembled that of the donor in FMT responders but not in nonresponders at week 12. There was no serious adverse event. CONCLUSIONS: This pilot study showed that FMT could be effective and safe in alleviating post-COVID insomnia, and further clinical trials are warranted. CLINICALTRIALS: gov, Number: NCT05556733.

Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study.

OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis. DESIGN: A graph neural network was developed incorporating pathologist domain knowledge to classify 6591 whole-slides images (WSIs) of endoscopic large bowel biopsies from 3291 patients (approximately 54% female, 46% male) as normal or abnormal (non-neoplastic and neoplastic) using clinically driven interpretable features. One UK National Health Service (NHS) site was used for model training and internal validation. External validation was conducted on data from two other NHS sites and one Portuguese site. RESULTS: Model training and internal validation were performed on 5054 WSIs of 2080 patients resulting in an area under the curve-receiver operating characteristic (AUC-ROC) of 0.98 (SD=0.004) and AUC-precision-recall (PR) of 0.98 (SD=0.003). The performance of the model, named Interpretable Gland-Graphs using a Neural Aggregator (IGUANA), was consistent in testing over 1537 WSIs of 1211 patients from three independent external datasets with mean AUC-ROC=0.97 (SD=0.007) and AUC-PR=0.97 (SD=0.005). At a high sensitivity threshold of 99%, the proposed model can reduce the number of normal slides to be reviewed by a pathologist by approximately 55%. IGUANA also provides an explainable output highlighting potential abnormalities in a WSI in the form of a heatmap as well as numerical values associating the model prediction with various histological features. CONCLUSION: The model achieved consistently high accuracy showing its potential in optimising increasingly scarce pathologist resources. Explainable predictions can guide pathologists in their diagnostic decision-making and help boost their confidence in the algorithm, paving the way for its future clinical adoption.

Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence.

BACKGROUND: Tumour infiltrating lymphocytes (TILs) are a prognostic parameter in triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). However, their role in luminal (oestrogen receptor positive and HER2 negative (ER + /HER2-)) BC remains unclear. In this study, we used artificial intelligence (AI) to assess the prognostic significance of TILs in a large well-characterised cohort of luminal BC. METHODS: Supervised deep learning model analysis of Haematoxylin and Eosin (H&E)-stained whole slide images (WSI) was applied to a cohort of 2231 luminal early-stage BC patients with long-term follow-up. Stromal TILs (sTILs) and intratumoural TILs (tTILs) were quantified and their spatial distribution within tumour tissue, as well as the proportion of stroma involved by sTILs were assessed. The association of TILs with clinicopathological parameters and patient outcome was determined. RESULTS: A strong positive linear correlation was observed between sTILs and tTILs. High sTILs and tTILs counts, as well as their proximity to stromal and tumour cells (co-occurrence) were associated with poor clinical outcomes and unfavourable clinicopathological parameters including high tumour grade, lymph node metastasis, large tumour size, and young age. AI-based assessment of the proportion of stroma composed of sTILs (as assessed visually in routine practice) was not predictive of patient outcome. tTILs was an independent predictor of worse patient outcome in multivariate Cox Regression analysis. CONCLUSION: AI-based detection of TILs counts, and their spatial distribution provides prognostic value in luminal early-stage BC patients. The utilisation of AI algorithms could provide a comprehensive assessment of TILs as a morphological variable in WSIs beyond eyeballing assessment.

Prolonged Impairment of Short-Chain Fatty Acid and L-Isoleucine Biosynthesis in Gut Microbiome in Patients With COVID-19.

BACKGROUND AND AIMS: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with altered gut microbiota composition. Phylogenetic groups of gut bacteria involved in the metabolism of short chain fatty acids (SCFAs) were depleted in SARS-CoV-2-infected patients. We aimed to characterize a functional profile of the gut microbiome in patients with COVID-19 before and after disease resolution. METHODS: We performed shotgun metagenomic sequencing on fecal samples from 66 antibiotics-naïve patients with COVID-19 and 70 non-COVID-19 controls. Serial fecal samples were collected (at up to 6 times points) during hospitalization and beyond 1 month after discharge. We assessed gut microbial pathways in association with disease severity and blood inflammatory markers. We also determined changes of microbial functions in fecal samples before and after disease resolution and validated these functions using targeted analysis of fecal metabolites. RESULTS: Compared with non-COVID-19 controls, patients with COVID-19 with severe/critical illness showed significant alterations in gut microbiome functionality (P < .001), characterized by impaired capacity of gut microbiome for SCFA and L-isoleucine biosynthesis and enhanced capacity for urea production. Impaired SCFA and L-isoleucine biosynthesis in gut microbiome persisted beyond 30 days after recovery in patients with COVID-19. Targeted analysis of fecal metabolites showed significantly lower fecal concentrations of SCFAs and L-isoleucine in patients with COVID-19 before and after disease resolution. Lack of SCFA and L-isoleucine biosynthesis significantly correlated with disease severity and increased plasma concentrations of CXCL-10, NT- proB-type natriuretic peptide, and C-reactive protein (all P < .05). CONCLUSIONS: Gut microbiome of patients with COVID-19 displayed impaired capacity for SCFA and L-isoleucine biosynthesis that persisted even after disease resolution. These 2 microbial functions correlated with host immune response underscoring the importance of gut microbial functions in SARS-CoV-2 infection pathogenesis and outcome.

H2O2 and Phosphorylated Peptide Dual-Responsive Nanochannel Device.

Oxidation and protein phosphorylation are critical mechanisms involved in regulating various cellular activities. Increasing research has suggested that oxidative stress could affect the activities of specific kinases or phosphatases, leading to alterations in the phosphorylation status of certain proteins. Ultimately, these alterations can affect cellular signaling pathways and gene expression patterns. However, the relationship between oxidation and protein phosphorylation remains complex and not yet fully understood. Therefore, the development of effective sensors capable of detecting both oxidation and protein phosphorylation simultaneously presents an ongoing challenge. To address this need, we introduce a proof-of-concept nanochannel device that is dual-responsive to both H2O2 and phosphorylated peptide (PP). Specifically, we design a peptide GGGCEG(GPGGA)4CEGRRRR, which contains an H2O2-sensitive unit CEG, an elastic peptide fragment (GPGGA)4, and a phosphorylation site recognition fragment RRRR. When the peptides are immobilized on the inner walls of conical nanochannels in a polyethylene terephthalate membrane, this peptide-modified nanochannel device exhibits a sensitive response to both H2O2 and PPs. The peptide chains undergo a random coil-to-α-helix transition in response to H2O2, which leads to a close-to-open transition of the nanochannel, accompanied with a remarkable increase in the transmembrane ionic current. In contrast, binding of the peptides with PPs shields the positive charge of the RRRR fragments, causing a decrease of the transmembrane ionic current. These unique features enable the sensitive detection of reactive oxygen species released by 3T3-L1 cells stimulated by platelet-derived growth factor (PDGF) as well as PDGF-induced change in the PP level. Real-time kinase activity monitoring further confirms the device's potential utility for kinase inhibitor screening.

Effects of dietary restriction on cognitive function: a systematic review and meta-analysis.

BACKGROUND: Potential positive link between cognitive function and dietary restriction has been widely concerned. The present study describes a systematic review and preliminary meta-analysis to assess the efficacy of dietary restriction on cognitive function. We classified dietary restrictions as Calories Restriction (CR) and Intermittent Fasting (IF). METHOD: This systematic review and meta-analysis conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement (PRISMA) Checklist, Databases including PubMed, Embase, Web of Science, and the Cochrane Library were searched for randomized controlled trials (RCTs) assessing the cognition effectiveness of dietary restriction from database inception to Sep 2021. RESULT: Eleven RCTs met the inclusion criteria in the systematic review and meta-analysis. The overall effect of dietary restriction on cognitive function is SMD = 0.22 (95% CI: 0.09-0.34, p < 0.01). The effect on global function SMD = 0.35 (95% CI: 0.04-0.65, p < 0.05) and memory SMD = 0.18 (95% CI: 0.00-0.35, p = 0.05) is significant. MCI showed the best effectiveness SMD = 0.36 (95% CI: 0.05-0.68, p < 0.05), followed by the normal weight population SMD = 0.28 (95% CI: 0.03-0.52, p < 0.05) and overweight population SMD = 0.20 (95% CI: 0.06-0.34, p < 0.01). No statistically significant difference showed between IF and CR (p > 0.05). CONCLUSION: Our study demonstrated that dietary restriction has varying degrees of positive effect on cognitive function in overweight/normal-weight people and MCI. However, it should be cautious when generalizing to other populations. Additional high-quality, large-scale, cohort and intervention studies are needed to further assess the effectiveness of dietary restriction on cognition.

The adaptor protein APPL2 controls glucose-stimulated insulin secretion via F-actin remodeling in pancreatic ß-cells.

Filamentous actin (F-actin) cytoskeletal remodeling is critical for glucose-stimulated insulin secretion (GSIS) in pancreatic ß-cells, and its dysregulation causes type 2 diabetes. The adaptor protein APPL1 promotes first-phase GSIS by up-regulating soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein expression. However, whether APPL2 (a close homology of APPL1 with the same domain organization) plays a role in ß-cell functions is unknown. Here, we show that APPL2 enhances GSIS by promoting F-actin remodeling via the small GTPase Rac1 in pancreatic ß-cells. ß-cell specific abrogation of APPL2 impaired GSIS, leading to glucose intolerance in mice. APPL2 deficiency largely abolished glucose-induced first- and second-phase insulin secretion in pancreatic islets. Real-time live-cell imaging and phalloidin staining revealed that APPL2 deficiency abolished glucose-induced F-actin depolymerization in pancreatic islets. Likewise, knockdown of APPL2 expression impaired glucose-stimulated F-actin depolymerization and subsequent insulin secretion in INS-1E cells, which were attributable to the impairment of Ras-related C3 botulinum toxin substrate 1 (Rac1) activation. Treatment with the F-actin depolymerization chemical compounds or overexpression of gelsolin (a F-actin remodeling protein) rescued APPL2 deficiency-induced defective GSIS. In addition, APPL2 interacted with Rac GTPase activating protein 1 (RacGAP1) in a glucose-dependent manner via the bin/amphiphysin/rvs-pleckstrin homology (BAR-PH) domain of APPL2 in INS-1E cells and HEK293 cells. Concomitant knockdown of RacGAP1 expression reverted APPL2 deficiency-induced defective GSIS, F-actin remodeling, and Rac1 activation in INS-1E cells. Our data indicate that APPL2 interacts with RacGAP1 and suppresses its negative action on Rac1 activity and F-actin depolymerization thereby enhancing GSIS in pancreatic ß-cells.

Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems.

The deployment of Electronic Toll Collection (ETC) gantry systems marks a transformative advancement in the journey toward an interconnected and intelligent highway traffic infrastructure. The integration of these systems signifies a leap forward in streamlining toll collection and minimizing environmental impact through decreased idle times. To solve the problems of missing sensor data in an ETC gantry system with large volumes and insufficient traffic detection among ETC gantries, this study constructs a high-order tensor model based on the analysis of the high-dimensional, sparse, large-volume, and heterogeneous characteristics of ETC gantry data. In addition, a missing data completion method for the ETC gantry data is proposed based on an improved dynamic tensor flow model. This study approximates the decomposition of neighboring tensor blocks in the high-order tensor model of the ETC gantry data based on tensor Tucker decomposition and the Laplacian matrix. This method captures the correlations among space, time, and user information in the ETC gantry data. Case studies demonstrate that our method enhances ETC gantry data quality across various rates of missing data while also reducing computational complexity. For instance, at a less than 5% missing data rate, our approach reduced the RMSE for time vehicle distance by 0.0051, for traffic volume by 0.0056, and for interval speed by 0.0049 compared to the MATRIX method. These improvements not only indicate a potential for more precise traffic data analysis but also add value to the application of ETC systems and contribute to theoretical and practical advancements in the field.

Gut microbiota dynamics in a prospective cohort of patients with post-acute COVID-19 syndrome.

BACKGROUND: Long-term complications after COVID-19 are common, but the potential cause for persistent symptoms after viral clearance remains unclear. OBJECTIVE: To investigate whether gut microbiome composition is linked to post-acute COVID-19 syndrome (PACS), defined as at least one persistent symptom 4 weeks after clearance of the SARS-CoV-2 virus. METHODS: We conducted a prospective study of 106 patients with a spectrum of COVID-19 severity followed up from admission to 6 months and 68 non-COVID-19 controls. We analysed serial faecal microbiome of 258 samples using shotgun metagenomic sequencing, and correlated the results with persistent symptoms at 6 months. RESULTS: At 6 months, 76% of patients had PACS and the most common symptoms were fatigue, poor memory and hair loss. Gut microbiota composition at admission was associated with occurrence of PACS. Patients without PACS showed recovered gut microbiome profile at 6 months comparable to that of non-COVID-19 controls. Gut microbiome of patients with PACS were characterised by higher levels of Ruminococcus gnavus, Bacteroides vulgatus and lower levels of Faecalibacterium prausnitzii. Persistent respiratory symptoms were correlated with opportunistic gut pathogens, and neuropsychiatric symptoms and fatigue were correlated with nosocomial gut pathogens, including Clostridium innocuum and Actinomyces naeslundii (all p<0.05). Butyrate-producing bacteria, including Bifidobacterium pseudocatenulatum and Faecalibacterium prausnitzii showed the largest inverse correlations with PACS at 6 months. CONCLUSION: These findings provided observational evidence of compositional alterations of gut microbiome in patients with long-term complications of COVID-19. Further studies should investigate whether microbiota modulation can facilitate timely recovery from post-acute COVID-19 syndrome.

Influence of emotion on purchase intention of electric vehicles: a comparative study of consumers with different income levels.

Promoting electric vehicles (EVs) adoption has become one of the important paths for countries around the world to address climate change and accelerate the transformation of energy system for achieving sustainable development. As one of the important psychological factors, the research on the explanatory power of emotions to EVs purchase intention is still insufficient. This paper collected 400 valid questionnaires all around China. By incorporating emotions and moral norms into the Theory of Planned Behavior (TPB) model, this study used structural equation model to estimate the impact of positive anticipated emotion (PAE), negative anticipated emotion (NAE), and moral norms together with TPB elements on EVs purchase intention. In order to explore the heterogeneity effect of the above factors on EVs purchase intention among consumers of different income groups, we divided the total sample into high-income subsample and low-income subsample according to the household monthly disposable income. We concluded as follows: for the total sample, PAE has the greatest impact on EVs purchase intention, followed by attitude, NAE, and perceived behavioral control (PBC). In particular, the purchase intention of high-income consumers mainly depends on NAE, while the purchase intention of low-income consumers mainly depends on PAE. Additionally, PBC has more significant impact on EVs purchase intention of high-income group. Finally, targeted policy implications are proposed to promote EVs purchase.

[Study on Test Method of Radiation Emission of Proton Therapy Equipment].

Electromagnetic compatibility testing of proton therapy system is different from that of traditional products in an anechoic chamber. It has high requirements on the division of sample composition, the understanding of applicable standards, the formulation of operation mode, the selection of test location, and the test of ambient noise. According to the requirements of GB 4824-2019 standard, the test method of radiation emission of proton therapy equipment was developed to provide reference advice for the industry, and the problems encountered in the actual test were studied.

Alterations in Fecal Fungal Microbiome of Patients With COVID-19 During Time of Hospitalization until Discharge.

BACKGROUND & AIMS: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects intestinal cells, and might affect the intestinal microbiota. We investigated changes in the fecal fungal microbiomes (mycobiome) of patients with SARS-CoV-2 infection during hospitalization and on recovery. METHODS: We performed deep shotgun metagenomic sequencing analysis of fecal samples from 30 patients with coronavirus disease 2019 (COVID-19) in Hong Kong, from February 5 through May 12, 2020. Fecal samples were collected 2 to 3 times per week from time of hospitalization until discharge. We compared fecal mycobiome compositions of patients with COVID-19 with those from 9 subjects with community-acquired pneumonia and 30 healthy individuals (controls). We assessed fecal mycobiome profiles throughout time of hospitalization until clearance of SARS-CoV-2 from nasopharyngeal samples. RESULTS: Patients with COVID-19 had significant alterations in their fecal mycobiomes compared with controls, characterized by enrichment of Candia albicans and a highly heterogeneous mycobiome configuration, at time of hospitalization. Although fecal mycobiomes of 22 patients with COVID-19 did not differ significantly from those of controls during times of hospitalization, 8 of 30 patients with COVID-19 had continued significant differences in fecal mycobiome composition, through the last sample collected. The diversity of the fecal mycobiome of the last sample collected from patients with COVID-19 was 2.5-fold higher than that of controls (P < .05). Samples collected at all timepoints from patients with COVID-19 had increased proportions of opportunistic fungal pathogens, Candida albicans, Candida auris, and Aspergillus flavus compared with controls. Two respiratory-associated fungal pathogens, A. flavus and Aspergillus niger, were detected in fecal samples from a subset of patients with COVID-19, even after clearance of SARS-CoV-2 from nasopharyngeal samples and resolution of respiratory symptoms. CONCLUSIONS: In a pilot study, we found heterogeneous configurations of the fecal mycobiome, with enrichment of fungal pathogens from the genera Candida and Aspergillus, during hospitalization of 30 patients with COVID-19 compared with controls. Unstable gut mycobiomes and prolonged dysbiosis persisted in a subset of patients with COVID-19 up to 12 days after nasopharyngeal clearance of SARS-CoV-2. Studies are needed to determine whether alterations in intestinal fungi contribute to or result from SARS-CoV-2 infection, and the effects of these changes in disease progression.

Discerning Tyrosine Phosphorylation from Multiple Phosphorylations Using a Nanofluidic Logic Platform.

Discerning tyrosine phosphorylation (pTyr) catalyzed by Tyr kinase is central to the revelation of oncogenic mechanisms and the development of targeted anticancer drugs. Despite some techniques, this goal remains challenging, especially when faced with the interference of multiple phosphorylation events, including serine (pSer) and threonine phosphorylation (pThr). We describe here a functional polymer-modified artificial ion nanochannel, which enables the sensitive and selective recognition of phosphotyrosine (pY) peptide by the distinct ionic current change. Such a recognition effect allows for the nanochannel to work in a complex protein digest condition. Further, the implementation of nanofluidic logic functions with the addition of Ca2+ dramatically improves the selectivity of the nanochannel to pY peptide and thus can discern pTyr by the Tyr kinase from pSer by the Ser/Thr kinase through simultaneously monitoring multisite phosphorylation at the same or different peptide substrates in one-pot. This logic sensing platform displays the potential in differentiating Tyr kinase and Ser/Thr kinase and assessing multi-kinase activities in multi-targeted drug design.

Propagation characteristics of terahertz wave in inductively coupled plasma.

Firstly, the electron density distribution of inductively coupled plasma (ICP) is measured by laser Thomson scattering (TS) method and the features of the ICP under the same experimental conditions are simulated by finite element method (FEM). The simulated results are in good agreement with the experimental results, which verifies the accuracy of the ICP generation simulation model. Secondly, the propagation characteristics of terahertz wave in ICP are measured by terahertz time domain spectroscopy (THz-TDS) and calculated by FEM according to the electron density distribution of ICP simulated in the first step above. The high consistency between the experimental and simulation results of terahertz wave propagation characteristics in ICP further proves the accuracy of terahertz wave transmission model in plasma and the feasibility of joint simulation with ICP generation simulation model.

The psychological impact on patients with memory disorders and their caregivers during COVID-19.

BACKGROUND: COVID-19 is erupting globally. Mass quarantine had been implemented all around China which could influence the psychological status of patients with memory disorders and their caregivers. AIM: To investigate the psychological impact of mass quarantine on patients with memory disorders and their caregivers in China. METHODS: We completed a cross-sectional study in 787 patients and their caregivers registered from 2010 to 2019 in Memory Clinic, The First Affiliated Hospital of Chongqing Medical University, by telephone interviews. The performance in neuropsychiatric symptoms (NPSs), sleep, nutrition, chronic diseases of patients, and the burden of care, anxiety and depression of caregivers was assessed by six assessment scales (MNA-SF, PSQI, NPI, RSS, PHQ-9 and GAD-7). RESULTS: Only 68 (8.6%) patients worried about the outbreak of COVID-19. The prevalence of NPSs among all subjects was nearly 60.0%. Approximately 50.0% of the caregivers reported distress. More than 70.0% of patients remained stable in NPSs. However, anxiety, depression, aberrant motor disorder and delusion were exacerbated (22.9%, 18.6%, 17.1% and 16.8%, respectively). Appetite and eating disorder led alleviation rate by 25.8% while disappearing rate of agitation led by 5.8%. 7.5% of caregivers manifested depressive symptoms while 4.9% expressed anxiety symptoms, and 40.8% showed care burden. The coefficients of RSS and PHQ-9, RSS and GAD-7, RSS and NPI-D, PHQ-9 and GAD-7 were 0.7, 0.5, 0.5 and 0.6, respectively (p < 0.01). CONCLUSION: Changes in NPSs during COVID-19 were observed in some patients with memory disorders and their caregivers, and adherence to medication contributed to the stabilization of NPSs.

Controlling the Connected Vehicle with Bi-Directional Information: Improved Car-Following Models and Stability Analysis.

Connected vehicle (CV) technologies are changing the form of traditional traffic models. In the CV driving environment, abundant and accurate information is available to vehicles, promoting the development of control strategies and models. Under these circumstances, this paper proposes a bidirectional vehicles information structure (BDVIS) by making use of the acceleration information of one preceding vehicle and one following vehicle to improve the car-following models. Then, we deduced the derived multiple vehicles information structure (DMVIS), including historical movement information of multiple vehicles, without the acceleration information. Next, the paper embeds the four kinds of basic car-following models into the framework to investigate the stability condition of two structures under the small perturbation of traffic flow and explored traffic response properties with different proportions of forward-looking or backward-looking terms. Under the open boundary condition, simulations on a single lane are conducted to validate the theoretical analysis. The results indicated that BDVIS and the DMVIS perform better than the original car-following model in improving the traffic flow stability, but that they have their own advantages for differently positioned vehicles in the platoon. Moreover, increasing the proportions of the preceding and following vehicles presents a benefit to stability, but if traffic is stable, an increase in any of the parameters would extend the influence time, which reveals that neither ß1 or ß2 is the biggest the best for the traffic.

Relationship between neuropsychiatric symptoms and cognitive functions in patients with cognitive impairment.

BACKGROUND: Cognitive decline and neuropsychiatric symptoms (NPS) are main clinical manifestations in Alzheimer disease (AD). It is unclear whether the link between specific NPS and cognitive domains exists in AD or mild cognitive impairment (MCI). Our study aimed to examine the association between specific cognitive domain and NPS in AD and MCI, and to evaluate whether this association showed variety in different stages of cognitive impairment. METHODS: A total of 458 patients diagnosed as AD or MCI were included in this study. Neuropsychological batteries were applied in the study. The association between NPS and cognitive function were evaluated by multiple linear regression, and its correlation was evaluated by Spearman correlation coefficient. RESULTS: The prevalence of NPS increased with the severity of cognitive impairment, and there were significant differences between MCI and AD. NPS were predominantly associated with cognitive domains, including memory, language, attention, and executive function. Both regression liner analysis and correlation analysis showed delusion, hallucination, and aberrant motor behaviour (AMB) were linked to language and attention. In addition, regression liner analysis illustrated depression, anxiety, and apathy were related to learning and episodic memory. Generally, the delusion, hallucination, and AMB have the broadest impact on cognition. CONCLUSION: Specific NPS was predominantly associated with different cognitive domains. Symptoms of agitation, delusion and irritability indicate worse cognitive performance. Therefore, cognitive improvement should be a therapeutic strategy in managing NPS in AD.

Functional Nanochannels for Sensing Tyrosine Phosphorylation.

Tyrosine phosphorylation (pTyr), much of which occurred on localized multiple sites, initiates cellular signaling, governs cellular functions, and its dysregulation is implicated in many diseases, especially cancers. pTyr-specific sensing is of great significance for understanding disease states and developing targeted anticancer drugs, however, it is very challenging due to the slight difference from serine (pSer) or threonine phosphorylation (pThr). Here we present polyethylenimine-g-phenylguanidine (PEI-PG)-modified nanochannels that can address the challenge. Rich guanidinium groups enabled PEI-PG to form multiple interactions with phosphorylated residues, especially pTyr residue, which triggered the conformational change of PEI-PG. By taking advantage of the "OFF-ON" change of the ion flux arising from the conformational shrinkage of the grafted PEI-PG, the nanochannels could distinguish phosphorylated peptide (PP) from nonmodified peptide, recognize PPs with pSer, pThr, or pTyr residue and PPs with different numbers of identical residues, and importantly could sense pTyr peptides in a biosample. Benefiting from the strong interaction between the guanidinium group and the pTyr side-chain, the specific sensing of pTyr peptide was achieved by performing a simple logic operation based on PEI-PG-modified nanochannels when Ca2+ was introduced as an interferent. The excellent pTyr sensing capacity makes the nanochannels available for real-time monitoring of the pTyr process by c-Abl kinase on a peptide substrate, even under complicated conditions, and the proof-of-concept study of monitoring the kinase activity demonstrates its potential in kinase inhibitor screening.

Intestinal NCoR1, a regulator of epithelial cell maturation, controls neonatal hyperbilirubinemia.

Severe neonatal hyperbilirubinemia (SNH) and the onset of bilirubin encephalopathy and kernicterus result in part from delayed expression of UDP-glucuronosyltransferase 1A1 (UGT1A1) and the inability to metabolize bilirubin. Although there is a good understanding of the early events after birth that lead to the rapid increase in serum bilirubin, the events that control delayed expression of UGT1A1 during development remain a mystery. Humanized UGT1 (hUGT1) mice develop SNH spontaneously, which is linked to repression of both liver and intestinal UGT1A1. In this study, we report that deletion of intestinal nuclear receptor corepressor 1 (NCoR1) completely diminishes hyperbilirubinemia in hUGT1 neonates because of intestinal UGT1A1 gene derepression. Transcriptomic studies and immunohistochemistry analysis demonstrate that NCoR1 plays a major role in repressing developmental maturation of the intestines. Derepression is marked by accelerated metabolic and oxidative phosphorylation, drug metabolism, fatty acid metabolism, and intestinal maturation, events that are controlled predominantly by H3K27 acetylation. The control of NCoR1 function and derepression is linked to IKKß function, as validated in hUGT1 mice with targeted deletion of intestinal IKKß. Physiological events during neonatal development that target activation of an IKKß/NCoR1 loop in intestinal epithelial cells lead to derepression of genes involved in intestinal maturation and bilirubin detoxification. These findings provide a mechanism of NCoR1 in intestinal homeostasis during development and provide a key link to those events that control developmental repression of UGT1A1 and hyperbilirubinemia.