PSEENet: A pseudo-siamese neural network incorporating electroencephalography and electrooculography characteristics for heterogeneous sleep staging.

Sleep staging plays a critical role in evaluating the quality of sleep. Currently, most studies are either suffering from dramatic performance drops when coping with varying input modalities or unable to handle heterogeneous signals. To handle heterogeneous signals and guarantee favorable sleep staging performance when a single modality is available, a pseudo-siamese neural network (PSN) to incorporate electroencephalography (EEG), electrooculography (EOG) characteristics is proposed (PSEENet). PSEENet consists of two parts, spatial mapping modules (SMMs) and a weight-shared classifier. SMMs are used to extract high-dimensional features. Meanwhile, joint linkages among multi-modalities are provided by quantifying the similarity of features. Finally, with the cooperation of heterogeneous characteristics, associations within various sleep stages can be established by the classifier. The evaluation of the model is validated on two public datasets, namely, Montreal Archive of Sleep Studies (MASS) and SleepEDFX, and one clinical dataset from Huashan Hospital of Fudan University (HSFU). Experimental results show that the model can handle heterogeneous signals, provide superior results under multimodal signals and show good performance with single modality. PSEENet obtains accuracy of 79.1%, 82.1% with EEG, EEG and EOG on Sleep-EDFX, and significantly improves the accuracy with EOG from 73.7% to 76% by introducing similarity information.

Layer-by-layer coated probiotics with chitosan and liposomes exhibit enhanced therapeutic effects for DSS-induced colitis in mice.

Probiotic therapy has emerged as a promising approach for the treatment of gastrointestinal diseases, offering advantages in terms of safety and convenience. However, oral probiotics encounter significant challenges, including exposure to a hostile gastric environment with low pH, bile salts, elevated levels of reactive oxygen species (ROS), and damage to the protective mucus layer. These factors reduce probiotic survival rates and limit their physiological activity. To address these challenges, we developed a layer-by-layer coated probiotics with curcumin-loaded liposome and polymer. Through DSS-induced colitis mice experiments, we demonstrated that the coated probiotics exhibited an improved survival rate in the gastrointestinal tract and enhanced adhesion to the intestinal mucosa. Furthermore, multi-layered coated probiotics exhibited remarkable efficacy in alleviating colitis by efficiently repairing the gut barrier, modulating gut microbial homeostasis, and reducing bacterial motility at sites of colonic inflammation. Our innovative approach holds promise for effectively treating gastrointestinal diseases.

Identifying autism spectrum disorder from multi-modal data with privacy-preserving.

The application of deep learning models to precision medical diagnosis often requires the aggregation of large amounts of medical data to effectively train high-quality models. However, data privacy protection mechanisms make it difficult to perform medical data collection from different medical institutions. In autism spectrum disorder (ASD) diagnosis, automatic diagnosis using multimodal information from heterogeneous data has not yet achieved satisfactory performance. To address the privacy preservation issue as well as to improve ASD diagnosis, we propose a deep learning framework using multimodal feature fusion and hypergraph neural networks for disease prediction in federated learning (FedHNN). By introducing the federated learning strategy, each local model is trained and computed independently in a distributed manner without data sharing, allowing rapid scaling of medical datasets to achieve robust and scalable deep learning predictive models. To further improve the performance with privacy preservation, we improve the hypergraph model for multimodal fusion to make it suitable for autism spectrum disorder (ASD) diagnosis tasks by capturing the complementarity and correlation between modalities through a hypergraph fusion strategy. The results demonstrate that our proposed federated learning-based prediction model is superior to all local models and outperforms other deep learning models. Overall, our proposed FedHNN has good results in the work of using multi-site data to improve the performance of ASD identification.

A pupillary contrast response in mice and humans: Neural mechanisms and visual functions.

In the pupillary light response (PLR), increases in ambient light constrict the pupil to dampen increases in retinal illuminance. Here, we report that the pupillary reflex arc implements a second input-output transformation; it senses temporal contrast to enhance spatial contrast in the retinal image and increase visual acuity. The pupillary contrast response (PCoR) is driven by rod photoreceptors via type 6 bipolar cells and M1 ganglion cells. Temporal contrast is transformed into sustained pupil constriction by the M1's conversion of excitatory input into spike output. Computational modeling explains how the PCoR shapes retinal images. Pupil constriction improves acuity in gaze stabilization and predation in mice. Humans exhibit a PCoR with similar tuning properties to mice, which interacts with eye movements to optimize the statistics of the visual input for retinal encoding. Thus, we uncover a conserved component of active vision, its cell-type-specific pathway, computational mechanisms, and optical and behavioral significance.

Predation without direction selectivity.

Across the animal kingdom, visual predation relies on motion-sensing neurons in the superior colliculus (SC) and its orthologs. These neurons exhibit complex stimulus preferences, including direction selectivity, which is thought to be critical for tracking the unpredictable escape routes of prey. The source of direction selectivity in the SC is contested, and its contributions to predation have not been tested experimentally. Here, we use type-specific cell removal to show that narrow-field (NF) neurons in the mouse SC guide predation. In vivo recordings demonstrate that direction-selective responses of NF cells are independent of recently reported stimulus-edge effects. Monosynaptic retrograde tracing reveals that NF cells receive synaptic input from direction-selective ganglion cells. When we eliminate direction selectivity in the retina of adult mice, direction-selective responses in the SC, including in NF cells, are lost. However, eliminating retinal direction selectivity does not affect the hunting success or strategies of mice, even when direction selectivity is removed after mice have learned to hunt, and despite abolishing the gaze-stabilizing optokinetic reflex. Thus, our results identify the retinal source of direction selectivity in the SC. They show that NF cells in the SC guide predation, an essential spatial orienting task, independent of their direction selectivity, revealing behavioral multiplexing of complex neural feature preferences and highlighting the importance of feature-selective manipulations for neuroethology.

Association of urinary chlorpyrifos, paraquat, and cyproconazole levels with the severity of fatty liver based on MRI.

BACKGROUND: The objective of this study was to detect the urinary levels of chlorpyrifos, paraquat, and cyproconazole in residents living in Fuyang City and to analyze the correlation between these urinary pesticides levels and the severity of fatty liver disease (FLD). METHODS: All participants' fat fraction (FF) values were recorded by MRI (Magnetic resonance imaging). First-morning urine samples were collected from 53 participants from Fuyang Peoples'Hospital. The levels of three urinary pesticides were measured using ß-glucuronidase hydrolysis followed by a. The results were analyzed by using Pearson correlation analysis and binary logistic regression analysis to reveal the correlation between three urinary pesticides and the severity of fatty liver. RESULTS: 53 individuals were divided into 3 groups based on the results from MRI, with 20 cases in the normal control group, 16 cases in the mild fatty liver group, and 17 cases in the moderate and severe fatty liver group. Urinary chlorpyrifos level was increased along with the increase of the severity of fatty liver. Urinary paraquat level was significantly higher both in the low-grade fatty liver group and moderate & serve grade fatty liver group compared with the control group. No significant differences in urinary cyproconazole levels were observed among the three groups. Furthermore, urinary chlorpyrifos and paraquat levels were positively correlated with FF value. And chlorpyrifos was the risk factor that may be involved in the development of FLD and Receiver Operating Characteristic curve (ROC curve) analysis showed that chlorpyrifos and paraquat may serve as potential predictors of FLD. CONCLUSION: The present findings indicate urinary chlorpyrifos and paraquat were positively correlated with the severity of fatty liver. Moreover, urinary chlorpyrifos and paraquat have the potential to be considered as the predictors for development of FLD. Thus, this study may provide a new perspective from the environmental factors for the diagnosis, prevention, and treatment of FLD.

Acute kidney injury in patients treated with immune checkpoint inhibitors: a single-center retrospective study.

BACKGROUND: Immune checkpoint inhibitor-associated acute kidney injury (ICI-AKI) is the most common renal complication and has attracted increasing amounts of attention. However, studies on this topic in Chinese cancer patients are very limited. Therefore, we conducted a retrospective study on the incidence, risk factors, clinical features and renal recovery of ICI-AKI in all patients with malignancies treated with ICIs in Shandong Provincial Hospital Affiliated to Shandong First Medical University. METHODS: In this single-center retrospective cohort study, the data of 904 patients who received immune checkpoint inhibitors (ICIs) treatment were retrospectively analyzed. Multivariable logistic regression was used to identify the predictors of ICI-AKI. RESULTS: A total of 46 of 904 patients receiving ICIs developed ICI-AKI, and the incidence of ICI-AKI was 5.1%. Patients developed ICI-AKI at a median of 9 weeks (IQR 3-23) after ICIs initiation. A lower baseline estimated glomerular filtration rate (eGFR) and use of antibiotics were associated with a higher risk of ICI-AKI. Renal recovery occurred in 17 patients (46%) at a median of 4 weeks (IQR 2-8) after ICI-AKI, including 16 (43%) with complete recovery and 1 (3%) with partial recovery. Of the 14 rechallenged patients, only one developed recurrent ICI-AKI. CONCLUSIONS: Patients with ICI-AKI were more likely to have impaired renal function at baseline and after treatment with antibiotics. Approximately half of the patients achieved renal recovery.

Mitophagy defect mediates the aging-associated hallmarks in Hutchinson-Gilford progeria syndrome.

Hutchinson-Gilford progeria syndrome (HGPS) is a rare and fatal disease manifested by premature aging and aging-related phenotypes, making it a disease model for aging. The cellular machinery mediating age-associated phenotypes in HGPS remains largely unknown, resulting in limited therapeutic targets for HGPS. In this study, we showed that mitophagy defects impaired mitochondrial function and contributed to cellular markers associated with aging in mesenchymal stem cells derived from HGPS patients (HGPS-MSCs). Mechanistically, we discovered that mitophagy affected the aging-associated phenotypes of HGPS-MSCs by inhibiting the STING-NF-ĸB pathway and the downstream transcription of senescence-associated secretory phenotypes (SASPs). Furthermore, by utilizing UMI-77, an effective mitophagy inducer, we showed that mitophagy induction alleviated aging-associated phenotypes in HGPS and naturally aged mice. Collectively, our results uncovered that mitophagy defects mediated the aging-associated markers in HGPS, highlighted the function of mitochondrial homeostasis in HGPS progression, and suggested mitophagy as an intervention target for HGPS and aging.

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China.

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Anchored-fusion enables targeted fusion search in bulk and single-cell RNA sequencing data.

Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.

Positive benefit-risk ratio of Psoraleae Fructus: Comprehensive safety assessment and osteogenic effects in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Psoraleae Fructus (PF), the dried fruit of Psoralea corylifolia L., is a commonly used traditional medicine that has contributed to the treatment of orthopedic diseases for thousands of years in China. However, recent PF-related liver injury reports have drawn widespread attention regarding its potential hepatotoxicity risks. AIM OF THE STUDY: This study was aimed to evaluate the long-term efficacy and chronic toxicity of PF using a 26-week administration experiment on rats in order to simulate the clinical usage situation. MATERIALS AND METHODS: The PF aqueous extract was consecutively administrated to rats daily at dosages of 0.7, 2.0, and 5.6 g/kg (equivalent to 1-8 times the clinical doses for humans) for as long as 26 weeks. Samples were collected after 13, 26, and 32 weeks (withdrawal for 6 weeks) since the first administration. The chronic toxicity of PF was evaluated by conventional toxicological methods, and the efficacy of PF was evaluated by osteogenic effects in the natural growth process. RESULTS: In our experiments, only the H group (5.6 g/kg) for 26-week PF treatment demonstrated liver or kidney injury, which the injuries were reversible after 6 weeks of withdrawal. Notably, the PF treatment beyond 13 weeks showed significant benefits for bone growth and development in rats, with a higher benefit-risk ratio in female rats. CONCLUSIONS: PF displayed a promising benefit-risk ratio in the treatment and prevention of osteoporosis, a disease that lacks effective medicine so far. This is the first study to elucidate the benefit-risk balance associated with clinical dosage and long-term use of PF, thereby providing valuable insights for rational clinical use and risk control of PF.

Distributed feature representations of natural stimuli across parallel retinal pathways.

How sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively. ON bipolar cell axons co-stratify within each block, but separate laminarly between them (upper block: diverse temporal, uniform spatial tuning; lower block: diverse spatial, uniform temporal tuning). ON bipolar cells extract temporal and spatial features similarly from artificial and naturalistic stimuli. In addition, they differ in sensitivity to coherent motion in naturalistic movies. Motion information is distributed across ON bipolar cells in the upper and the lower blocks, multiplexed with temporal and spatial contrast, independent features of natural scenes. Comparing the responses of different boutons within the same arbor, we find that axons of all ON bipolar cell types function as computational units. Thus, our results provide insights into the visual feature extraction from naturalistic stimuli and reveal how structural and functional organization cooperate to generate parallel ON pathways for temporal and spatial information in the mammalian retina.

Antimicrobial Guanidinylate Polycarbonates Show Oral In Vivo Efficacy Against Clostridioides Difficile.

The emerging antibiotic resistance has been named by the World Health Organization (WHO) as one of the top 10 threats to public health. Notably, methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecalis (VREF) are designated as serious threats, whereas Clostridioides difficile (C. difficile) is recognized as one of the most urgent threats to human health and unmet medical need. Herein, they report the design and application of novel biodegradable polymers - the lipidated antimicrobial guanidinylate polycarbonates. These polymers showed potent antimicrobial activity against a panel of bacteria with fast-killing kinetics and low resistance development tendency, mainly due to their bacterial membrane disruption mechanism. More importantly, the optimal polymer showed excellent antibacterial activity against C. difficile infection (CDI) in vivo via oral administration. In addition, compared with vancomycin, the polymer demonstrated a much-prolonged therapeutic effect and virtually diminished recurrence rate of CDI. The convenient synthesis, easy scale-up, low cost, as well as biodegradability of this class of polycarbonates, together with their in vitro broad-spectrum antimicrobial activity and orally in vivo efficacy against CDI, suggest the great potential of lipidated guandinylate polycarbonates as a new class of antibacterial biomaterials to treat CDI and combat emerging antibiotic resistance.

A Sequential End-to-End Neonatal Sleep Staging Model with Squeeze and Excitation Blocks and Sequential Multi-Scale Convolution Neural Networks.

Automatic sleep staging offers a quick and objective assessment for quantitatively interpreting sleep stages in neonates. However, most of the existing studies either do not encompass any temporal information, or simply apply neural networks to exploit temporal information at the expense of high computational overhead and modeling ambiguity. This limits the application of these methods to multiple scenarios. In this paper, a sequential end-to-end sleep staging model, SeqEESleepNet, which is competent for parallelly processing sequential epochs and has a fast training rate to adapt to different scenarios, is proposed. SeqEESleepNet consists of a sequence epoch generation (SEG) module, a sequential multi-scale convolution neural network (SMSCNN) and squeeze and excitation (SE) blocks. The SEG module expands independent epochs into sequential signals, enabling the model to learn the temporal information between sleep stages. SMSCNN is a multi-scale convolution neural network that can extract both multi-scale features and temporal information from the signal. Subsequently, the followed SE block can reassign the weights of features through mapping and pooling. Experimental results exhibit that in a clinical dataset, the proposed method outperforms the state-of-the-art approaches, achieving an overall accuracy, F1-score, and Kappa coefficient of 71.8%, 71.8%, and 0.684 on a three-class classification task with a single channel EEG signal. Based on our overall results, we believe the proposed method could pave the way for convenient multi-scenario neonatal sleep staging methods.

ST218 Klebsiella pneumoniae became a high-risk clone for multidrug resistance and hypervirulence.

BACKGROUND: The occurrence of multidrug-resistant and hypervirulent Klebsiella pneumoniae (MDR-hvKp) worldwide poses a great challenge for public health. Few studies have focused on ST218 MDR-hvKp. METHODS: Retrospective genomic surveillance was conducted at the Peking University Third Hospital from 2017 and clinical information was obtained. To understand genomic and microbiological characteristics, antimicrobial susceptibility testing, plasmid conjugation and stability, biofilm formation, serum killing, growth curves and whole-genome sequencing were performed. We also assessed the clinical and microbiological characteristics of ST218 compared with ST23. RESULTS: A total of eleven ST218 Kp isolates were included. The most common infection type was lower respiratory tract infection (72.7%, 8/11) in our hospital, whereas ST23 hvKp (72.7%, 8/11) was closely associated with bloodstream infection. Notably, nosocomial infections caused by ST218 (54.5%, 6/11) was slightly higher than ST23 (36.4%, 4/11). All of the ST218 and ST23 strains presented with the virulence genes combination of iucA + iroB + peg344 + rmpA + rmpA2. Interestingly, the virulence score of ST218 was lower than ST23, whereas one ST218 strain (pPEKP3107) exhibited resistance to carbapenems, cephalosporins, ß-lactamase/inhibitors and quinolones and harbored an ~ 59-kb IncN type MDR plasmid carrying resistance genes including blaNDM-1, dfrA14 and qnrS1. Importantly, blaNDM-1 and qnrS1 were flanked with IS26 located within the plasmid that could successfully transfer into E. coli J53. Additionally, PEKP2044 harbored an ~ 41-kb resistance plasmid located within tetA indicating resistance to doxycycline. CONCLUSION: The emergence of blaNDM-1 revealed that there is great potential for ST218 Kp to become a high-risk clone for MDR-hvKp, indicating the urgent need for enhanced genomic surveillance.

Low-input lipidomics reveals lipid metabolism remodelling during early mammalian embryo development.

Lipids are indispensable for energy storage, membrane structure and cell signalling. However, dynamic changes in various categories of endogenous lipids in mammalian early embryonic development have not been systematically characterized. Here we comprehensively investigated the dynamic lipid landscape during mouse and human early embryo development. Lipid signatures of different developmental stages are distinct, particularly for the phospholipid classes. We highlight that the high degree of phospholipid unsaturation is a conserved feature as embryos develop to the blastocyst stage. Moreover, we show that lipid desaturases such as SCD1 are required for in vitro blastocyst development and blastocyst implantation. One of the mechanisms is through the regulation of unsaturated fatty-acid-mediated fluidity of the plasma membrane and apical proteins and the establishment of apical-basal polarity during development of the eight-cell embryo to the blastocyst. Overall, our study provides an invaluable resource about the remodelling of the endogenous lipidome in mammalian preimplantation embryo development and mechanistic insights into the regulation of embryogenesis and implantation by lipid unsaturation.

MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach.

Identifying pathogenic variants from the vast majority of nucleotide variation remains a challenge. We present a method named Multimodal Annotation Generated Pathogenic Impact Evaluator (MAGPIE) that predicts the pathogenicity of multi-type variants. MAGPIE uses the ClinVar dataset for training and demonstrates superior performance in both the independent test set and multiple orthogonal validation datasets, accurately predicting variant pathogenicity. Notably, MAGPIE performs best in predicting the pathogenicity of rare variants and highly imbalanced datasets. Overall, results underline the robustness of MAGPIE as a valuable tool for predicting pathogenicity in various types of human genome variations. MAGPIE is available at https://github.com/shenlab-genomics/magpie .