WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.

The size of image volumes in connectomics studies now reaches terabyte and often petabyte scales with a great diversity of appearance due to different sample preparation procedures. However, manual annotation of neuronal structures (e.g., synapses) in these huge image volumes is time-consuming, leading to limited labeled training data often smaller than 0.001% of the large-scale image volumes in application. Methods that can utilize in-domain labeled data and generalize to out-of-domain unlabeled data are in urgent need. Although many domain adaptation approaches are proposed to address such issues in the natural image domain, few of them have been evaluated on connectomics data due to a lack of domain adaptation benchmarks. Therefore, to enable developments of domain adaptive synapse detection methods for large-scale connectomics applications, we annotated 14 image volumes from a biologically diverse set of Megaphragma viggianii brain regions originating from three different whole-brain datasets and organized the WASPSYN challenge at ISBI 2023. The annotations include coordinates of pre-synapses and post-synapses in the 3D space, together with their one-to-many connectivity information. This paper describes the dataset, the tasks, the proposed baseline, the evaluation method, and the results of the challenge. Limitations of the challenge and the impact on neuroscience research are also discussed. The challenge is and will continue to be available at https://codalab.lisn.upsaclay.fr/competitions/9169. Successful algorithms that emerge from our challenge may potentially revolutionize real-world connectomics research and further the cause that aims to unravel the complexity of brain structure and function.

Inflammation-Targeted Nanomedicines Alleviate Oxidative Stress and Reprogram Macrophages Polarization for Myocardial Infarction Treatment.

Myocardial infarction (MI) is a critical global health challenge, with current treatments limited by the complex MI microenvironment, particularly the excessive oxidative stress and intense inflammatory responses that exacerbate cardiac dysfunction and MI progression. Herein, a mannan-based nanomedicine, Que@MOF/Man, is developed to target the inflammatory infarcted heart and deliver the antioxidative and anti-inflammatory agent quercetin (Que), thereby facilitating a beneficial myocardial microenvironment for cardiac repair. The presence of mannan on the nanoparticle surface enables selective internalization by macrophages rather than cardiomyocytes. Que@MOF/Man effectively neutralizes reactive oxygen species in macrophages to reduce oxidative stress and promote their differentiation into a reparative phenotype, reconciling the inflammatory response and enhancing cardiomyocyte survival through intercellular communication. Owing to the recruitment of macrophages into inflamed myocardium post-MI, in vivo, administration of Que@MOF/Man in MI rats revealed the specific distribution into the injured myocardium compared to free Que. Furthermore, Que@MOF/Man exhibited favorable results in resolving inflammation and protecting cardiomyocytes, thereby preventing further myocardial remodeling and improving cardiac function in MI rats. These findings collectively validate the rational design of an inflammation-targeted delivery strategy to mitigate oxidative stress and modulate the inflammation response in the injured heart, presenting a therapeutic avenue for MI treatment.

Fingerprinting black tea: When spectroscopy meets machine learning a novel workflow for geographical origin identification.

Food fraud, along with many challenges to the integrity and sustainability, threatens the prosperity of businesses and society as a whole. Tea is the second most commonly consumed non-alcoholic beverage globally. Challenges to tea authenticity require the development of highly efficient and rapid solutions to improve supply chain transparency. This study has produced an innovative workflow for black tea geographical indications (GI) discrimination based on non-targeted spectroscopic fingerprinting techniques. A total of 360 samples originating from nine GI regions worldwide were analysed by Fourier Transform Infrared (FTIR) and Near Infrared spectroscopy. Machine learning algorithms (k-nearest neighbours and support vector machine models) applied to the test data greatly improved the GI identification achieving 100% accuracy using FTIR. This workflow will provide a low-cost and user-friendly solution for on-site and real-time determination of black tea geographical origin along supply chains.

An Injectable Thermosensitive Hydrogel Containing Resveratrol and Dexamethasone-Loaded Carbonated Hydroxyapatite Microspheres for the Regeneration of Osteoporotic Bone Defects.

Bone defects in osteoporosis usually present excessive reactive oxygen species (ROS), abnormal inflammation levels, irregular shapes and impaired bone regeneration ability; therefore, osteoporotic bone defects are difficult to repair. In this study, an injectable thermosensitive hydrogel poly (D, L-lactide)-poly (ethylene glycol)- poly (D, L-lactide) (PLEL) system containing resveratrol (Res) and dexamethasone (DEX) is designed to create a microenvironment conducive to osteogenesis in osteoporotic bone defects. This PLEL hydrogel is injected and filled irregular defect areas and achieving a rapid sol-gel transition in situ. Res has a strong anti-inflammatory effects that can effectively remove excess free radicals at the damaged site, guide macrophage polarization to the M2 phenotype, and regulate immune responses. Additionally, DEX can promote osteogenic differentiation. In vitro experiments showed that the hydrogel effectively promoted osteogenic differentiation of mesenchymal stem cells, removed excess intracellular ROS, and regulated macrophage polarization to reduce inflammatory responses. In vivo experiments showed that the hydrogel promoted osteoporotic bone defect regeneration and modulated immune responses. Overall, this study confirmed that the hydrogel can treat osteoporotic bone defects by synergistically modulating bone damage microenvironment, alleviating inflammatory responses, and promoting osteogenesis; thus, it represents a promising drug delivery strategy to repair osteoporotic bone defects.

Enhanced Chemo-Immunotherapy Strategy Utilizing Injectable Thermosensitive Hydrogel for The Treatment of Diffuse Peritoneal Metastasis in Advanced Colorectal Cancer.

Patients with colorectal cancer (CRC) and diffuse peritoneal metastasis (PM) are not eligible for surgical intervention. Thus, palliative treatment remains the standard of care in clinical practice. Systemic chemotherapy fails to cause drug accumulation at the lesion sites, while intraperitoneal chemotherapy (IPC) is limited by high clearance rates and associated complications. Given the poor prognosis, a customized OxP/R848@PLEL hydrogel delivery system has been devised to improve the clinical benefit of advanced CRC with diffuse PM. This system is distinguished by its simplicity, security, and efficiency. Specifically, the PLEL hydrogel exhibits excellent injectability and thermosensitivity, enabling the formation of drug depots within the abdominal cavity, rendering it an optimal carrier for IPC. Oxaliplatin (OxP), a first-line drug for advanced CRC, is cytotoxic and enhances the immunogenicity of tumors by inducing immunogenic cell death. Furthermore, OxP and resiquimod (R848) synergistically enhance the maturation of dendritic cells, promote the expansion of cytotoxic T lymphocytes, and induce the formation of central memory T cells. Moreover, R848 domesticates macrophages to an anti-tumor phenotype. OxP/R848@PLEL effectively eradicates peritoneal metastases, completely inhibits ascites production, and significantly prolongs mice lifespan. As such, it provides a promising approach to managing diffuse PM in patients with CRC without surgical indications.

[The role of natural killer cells in anti-infection and tumor therapy].

Natural killer (NK) cells are an important part of the body's innate immune system. As the first line of defense against pathogens, they need to be transformed into a mature state under the control of various cell signaling molecules and transcription factors to play cytotoxic and immune regulatory roles. Under the interaction of activated receptors and inhibitory receptors, NK cells are activated to perform a direct cell killing effect by secreting perforin and granzyme, or indirectly eliminate pathogenic microorganisms in the body by secreting various cytokines, such as type I and type II interferons. These functions of NK cells play a very important role in antiviral and anti-autoimmune diseases, especially in anti-tumor.

Transformer-Empowered Invariant Grounding for Video Question Answering.

Video Question Answering (VideoQA) is the task of answering questions about a video. At its core is the understanding of the alignments between video scenes and question semantics to yield the answer. In leading VideoQA models, the typical learning objective, empirical risk minimization (ERM), tends to over-exploit the spurious correlations between question-irrelevant scenes and answers, instead of inspecting the causal effect of question-critical scenes, which undermines the prediction with unreliable reasoning. In this work, we take a causal look at VideoQA and propose a modal-agnostic learning framework, named Invariant Grounding for VideoQA (IGV), to ground the question-critical scene, whose causal relations with answers are invariant across different interventions on the complement. With IGV, leading VideoQA models are forced to shield the answering from the negative influence of spurious correlations, which significantly improves their reasoning ability. To unleash the potential of this framework, we further provide a Transformer-Empowered Invariant Grounding for VideoQA (TIGV), a substantial instantiation of IGV framework that naturally integrates the idea of invariant grounding into a transformer-style backbone. Experiments on four benchmark datasets validate our design in terms of accuracy, visual explainability, and generalization ability over the leading baselines. Our code is available at https://github.com/yl3800/TIGV.

SARS-CoV-2 vaccination and infection in ozanimod-treated participants with relapsing multiple sclerosis.

OBJECTIVE: To investigate the serologic response, predictors of response, and clinical outcomes associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination and infection in ozanimod-treated participants with relapsing multiple sclerosis (RMS) from DAYBREAK. METHODS: DAYBREAK (ClinicalTrials.gov-NCT02576717), an open-label extension study of oral ozanimod 0.92 mg, enrolled participants aged 18-55 years with RMS who completed phase 1-3 ozanimod trials. Participants who were fully vaccinated against SARS-CoV-2 with mRNA or non-mRNA vaccines, were unvaccinated, and/or had COVID-19-related adverse events (AEs, with or without vaccination) and postvaccination serum samples were included (n = 288). Spike receptor binding domain (RBD) antibody levels (seroconversion: ≥0.8 U/mL) and serologic evidence of SARS-CoV-2 infection (nucleocapsid IgG: ≥1 U/mL) were assessed (Roche Elecsys/Cobas e411 platform). RESULTS: In fully vaccinated participants (n = 148), spike RBD antibody seroconversion occurred in 90% (n = 98/109) of those without serologic evidence of prior SARS-CoV-2 exposure (100% [n = 80/80] seroconversion after mRNA vaccination) and in 100% (n = 39/39) of participants with serologic evidence of viral exposure. mRNA vaccination predicted higher spike RBD antibody levels, whereas absolute lymphocyte count (ALC), age, body mass index, and sex did not. COVID-19-related AEs were reported in 10% (n = 15/148) of fully vaccinated participants-all were nonserious and not severe; all participants recovered. INTERPRETATION: Most ozanimod-treated participants with RMS mounted a serologic response to SARS-CoV-2 vaccination and infection, regardless of participant characteristics or ALC levels. In this analysis, all COVID-19-related AEs post-full vaccination in participants taking ozanimod were nonserious and not severe.

Contrastive Video Question Answering via Video Graph Transformer.

We propose to perform video question answering (VideoQA) in a Contrastive manner via a Video Graph Transformer model (CoVGT). CoVGT's uniqueness and superiority are three-fold: 1) It proposes a dynamic graph transformer module which encodes video by explicitly capturing the visual objects, their relations and dynamics, for complex spatio-temporal reasoning. 2) It designs separate video and text transformers for contrastive learning between the video and text to perform QA, instead of multi-modal transformer for answer classification. Fine-grained video-text communication is done by additional cross-modal interaction modules. 3) It is optimized by the joint fully- and self-supervised contrastive objectives between the correct and incorrect answers, as well as the relevant and irrelevant questions respectively. With superior video encoding and QA solution, we show that CoVGT can achieve much better performances than previous arts on video reasoning tasks. Its performances even surpass those models that are pretrained with millions of external data. We further show that CoVGT can also benefit from cross-modal pretraining, yet with orders of magnitude smaller data. The results demonstrate the effectiveness and superiority of CoVGT, and additionally reveal its potential for more data-efficient pretraining.

Newly developed gas-assisted sonodynamic therapy in cancer treatment.

Sonodynamic therapy (SDT) is an emerging noninvasive treatment modality that utilizes low-frequency and low-intensity ultrasound (US) to trigger sensitizers to kill tumor cells with reactive oxygen species (ROS). Although SDT has attracted much attention for its properties including high tumor specificity and deep tissue penetration, its anticancer efficacy is still far from satisfactory. As a result, new strategies such as gas-assisted therapy have been proposed to further promote the effectiveness of SDT. In this review, the mechanisms of SDT and gas-assisted SDT are first summarized. Then, the applications of gas-assisted SDT for cancer therapy are introduced and categorized by gas types. Next, therapeutic systems for SDT that can realize real-time imaging are further presented. Finally, the challenges and perspectives of gas-assisted SDT for future clinical applications are discussed.

Data fusion and multivariate analysis for food authenticity analysis.

A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods. Eighteen robust lipid markers and nine elemental markers are found, which provide robust evidence of the provenance of the salmon. Thus, we demonstrate that our mid-level data fusion - multivariate analysis strategy greatly improves the ability to correctly identify the geographical origin and production method of salmon, and this innovative approach can be applied to many other food authenticity applications.

Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence.

This study is directed towards developing a fast, non-destructive, and easy-to-use handheld multimode spectroscopic system for fish quality assessment. We apply data fusion of visible near infra-red (VIS-NIR) and short wave infra-red (SWIR) reflectance and fluorescence (FL) spectroscopy data features to classify fish from fresh to spoiled condition. Farmed Atlantic and wild coho and chinook salmon and sablefish fillets were measured. Three hundred measurement points on each of four fillets were taken every two days over 14 days for a total of 8400 measurements for each spectral mode. Multiple machine learning techniques including principal component analysis, self-organized maps, linear and quadratic discriminant analyses, k-nearest neighbors, random forest, support vector machine, and linear regression, as well as ensemble and majority voting methods, were used to explore spectroscopy data measured on fillets and to train classification models to predict freshness. Our results show that multi-mode spectroscopy achieves 95% accuracy, improving the accuracies of the FL, VIS-NIR and SWIR single-mode spectroscopies by 26, 10 and 9%, respectively. We conclude that multi-mode spectroscopy and data fusion analysis has the potential to accurately assess freshness and predict shelf life for fish fillets and recommend this study be expanded to a larger number of species in the future.

X-Ray2EM: Uncertainty-Aware Cross-Modality Image Reconstruction from X-Ray to Electron Microscopy in Connectomics.

Comprehensive, synapse-resolution imaging of the brain will be crucial for understanding neuronal computations and function. In connectomics, this has been the sole purview of volume electron microscopy (EM), which entails an excruciatingly difficult process because it requires cutting tissue into many thin, fragile slices that then need to be imaged, aligned, and reconstructed. Unlike EM, hard X-ray imaging is compatible with thick tissues, eliminating the need for thin sectioning, and delivering fast acquisition, intrinsic alignment, and isotropic resolution. Unfortunately, current state-of-the-art X-ray microscopy provides much lower resolution, to the extent that segmenting membranes is very challenging. We propose an uncertainty-aware 3D reconstruction model that translates X-ray images to EM-like images with enhanced membrane segmentation quality, showing its potential for developing simpler, faster, and more accurate X-ray based connectomics pipelines.

Overexpression screen of chromosome 21 genes reveals modulators of Sonic hedgehog signaling relevant to Down syndrome.

Trisomy 21 and mutations in the Sonic hedgehog (SHH) signaling pathway cause overlapping and pleiotropic phenotypes including cerebellar hypoplasia, craniofacial abnormalities, congenital heart defects and Hirschsprung disease. Trisomic cells derived from individuals with Down syndrome possess deficits in SHH signaling, suggesting that overexpression of human chromosome 21 genes may contribute to SHH-associated phenotypes by disrupting normal SHH signaling during development. However, chromosome 21 does not encode any known components of the canonical SHH pathway. Here, we sought to identify chromosome 21 genes that modulate SHH signaling by overexpressing 163 chromosome 21 cDNAs in a series of SHH-responsive mouse cell lines. We confirmed overexpression of trisomic candidate genes using RNA sequencing in the cerebella of Ts65Dn and TcMAC21 mice, model systems for Down syndrome. Our findings indicate that some human chromosome 21 genes, including DYRK1A, upregulate SHH signaling, whereas others, such as HMGN1, inhibit SHH signaling. Individual overexpression of four genes (B3GALT5, ETS2, HMGN1 and MIS18A) inhibits the SHH-dependent proliferation of primary granule cell precursors. Our study prioritizes dosage-sensitive chromosome 21 genes for future mechanistic studies. Identification of the genes that modulate SHH signaling may suggest new therapeutic avenues for ameliorating Down syndrome phenotypes.

Prognostic peripheral blood biomarkers at ICU admission predict COVID-19 clinical outcomes.

The COVID-19 pandemic continues to challenge the capacities of hospital ICUs which currently lack the ability to identify prospectively those patients who may require extended management. In this study of 90 ICU COVID-19 patients, we evaluated serum levels of four cytokines (IL-1ß, IL-6, IL-10 and TNFα) as well as standard clinical and laboratory measurements. On 42 of these patients (binned into Initial and Replication Cohorts), we further performed CyTOF-based deep immunophenotyping of peripheral blood mononuclear cells with a panel of 38 antibodies. All measurements and patient samples were taken at time of ICU admission and retrospectively linked to patient clinical outcomes through statistical approaches. These analyses resulted in the definition of a new measure of patient clinical outcome: patients who will recover after short ICU stays (< 6 days) and those who will subsequently die or recover after long ICU stays (≥6 days). Based on these clinical outcome categories, we identified blood prognostic biomarkers that, at time of ICU admission, prospectively distinguish, with 91% sensitivity and 91% specificity (positive likelihood ratio 10.1), patients in the two clinical outcome groups. This is achieved through a tiered evaluation of serum IL-10 and targeted immunophenotyping of monocyte subsets, specifically, CD11clow classical monocytes. Both immune biomarkers were consistently elevated ( ≥15 pg/ml and ≥2.7 x107/L for serum IL-10 and CD11clow classical monocytes, respectively) in those patients who will subsequently die or recover after long ICU stays. This highly sensitive and specific prognostic test could prove useful in guiding clinical resource allocation.

The Impact of Childhood Socioeconomic Status on Adolescents' Risk Behaviors: The Role of Physiological and Psychological Threats.

Adolescence is a period of high levels of risk behavior. The present research aims to examine the influences of childhood socioeconomic status (SES) on risk behaviors in gain or loss domains among adolescents and the roles of threats in this effect. In experiment 1, a total of 107 adolescents (Mage = 14.80; SDage = 1.15) were asked to complete the childhood socioeconomic status scale before they took part in a risk behavior task under the gain and loss situation. A total of 149 adolescents (Mage = 14.24; SDage = 1.11) in experiment 2a and 139 adolescents (Mage = 13.88; SDage = 1.09) in experiment 2b completed the childhood socioeconomic status scale before they took part in a risk behavior task under the gain and loss situation under physiological threats and psychological threats, respectively. The results showed that high-childhood-SES adolescents tend to take more risks than low-childhood-SES adolescents in the gain domain, while low-childhood-SES adolescents tend to take more risks than high-childhood-SES adolescents in the loss domain. Threats amplified the impact of childhood socioeconomic status on adolescents' risk behaviors in the gain and loss domains. When a physiological threat or psychological threat was primed, compared to the control group, in the gain situation, the extent to which high-childhood-SES adolescents showed greater risk seeking than low-childhood-SES adolescents became larger; in the loss domain, the extent to which low-childhood-SES adolescents showed greater risk seeking than high-childhood-SES adolescents became larger.

LiDAR integrated IR OWC system with the abilities of user localization and high-speed data transmission.

By using narrow infrared (IR) optical beams, optical wireless communication (OWC) system can realize ultra-high capacity and high-privacy data transmission. However, due to the point-to-point connection approach, a high accuracy localization system and beam-steering antenna (BSA) are required to steer the signal beam to user terminals. In this paper, we proposed an indoor beam-steering IR OWC system with high accuracy and calibration-free localization ability by employing a coaxial frequency modulated continuous wave (FMCW) light detection and ranging (LiDAR) system. In the meantime, benefitting from the mm-level ranging accuracy of the LiDAR system, a useful approach to assess the feasibility of the link alignment between beam-steering antenna and users is first demonstrated. With the assistance of the LiDAR system, we experimentally achieved the localization of user terminals with a 0.038-degree localization accuracy and on-off keying (OOK) downlink error-free transmission of 17 Gb/s in free space at a 3-m distance is demonstrated. The highest transmission data rate under the forward error correction (FEC) criterion (Bit error rate (BER) <3.8×103) can reach 24 Gb/s.

Near-infrared light and redox dual-activatable nanosystems for synergistically cascaded cancer phototherapy with reduced skin photosensitization.

Currently, activatable photodynamic therapy (PDT) that is precisely regulated by endogenous or exogenous stimuli to selectively produce cytotoxic reactive oxygen species at the tumor site is urgently in demand. Herein, we fabricated a dual-activatable PDT nanosystem regulated by the redox tumor microenvironment and near-infrared (NIR) light-induced photothermal therapy (PTT). In this study, photosensitizer chlorin e6 (Ce6) was conjugated to hyaluronic acid (HA) via a diselenide bond to form an amphiphilic polymer (HSeC) for loading PTT agent IR780 to produce HSeC/IR nanoparticles (NPs). The photoactivity of Ce6 for PDT was "double-locked" by the aggregation-caused quenching (ACQ) effect and the fluorescence resonance energy transfer (FRET) from Ce6 to IR780 during blood circulation. After selective accumulation into tumors, HSeC/IR NPs were subsequently dissociated due to the "double-key", which included diselenide bond dissociation under high redox conditions and IR780 degradation upon NIR laser irradiation, resulting in recovering Ce6. In vitro studies indicated that Ce6 photoactivity in HSeC/IR NPs was significantly suppressed when compared with free Ce6 or in HSeC NPs. Moreover, BALB/c mice treated with HSeC/IR NPs displayed distinctly alleviated skin damage during PDT. Synergetic cascaded PTT-PDT with superior tumor suppression was observed in SCC7 tumor-bearing mice. Therefore, the study findings could provide a promising treatment strategy for PTT-facilitated PDT with high antitumor efficacies and reduced skin phototoxicity levels.

Genetic features of bovine viral diarrhea virus subgenotype 1c in newborn calves at nucleotide and synonymous codon usages.

Bovine viral diarrhea virus (BVDV), serving as an important pathogen for newborn calves, poses threat to reproductive and economic losses in the cattle industry. To survey the infection rate and genetic diversity of BVDV in newborn calves in northern China, a total of 676 sera samples of newborn calves were collected from four provinces between 2021 and 2022. All sera samples were individually detected for BVDV infection by RT-PCR and ELISA. Our results showed that the overall serological rate was 9.76% (66/676) and the average positive rate of BVDV RNA was 8.14% (55/676) in the newborn calves. Eight BVDV strains were successfully isolated from RT-PCR positive sera samples, and four isolates displayed the cytopathic effect (CPE). Based on phylogenetic tree at the genome level, the eight strains were classified into subgenotype 1c. Moreover, the BVDV isolates had a close genetic relationship with the GSTZ strain at either nucleotide or codon usage level. Interestingly, in comparison of synonymous codon usage patterns between the BVDV isolates with CPE and ones without CPE, there were four synonymous codons (UCG, CCC, GCA, and AAC) which displayed the significant differences (p < 0.05) at codon usage pattern, suggesting that synonymous codon usage bias might play a role in BVDV-1c biotypes. In addition, the usage of synonymous codons containing CpG dinucleotides was suppressed by the BVDV-1c isolates, reflecting one of strategies of immune evasion of BVDV to its host. Taken together, our study provided data for monitoring and vaccination strategies of BVDV for newborn calves in northern China.