Construction and Investigation of Novel Cross-Linked Fluorine-Containing Sulfonated Polyimide Membranes for VFB Application.

Membrane with remarkable proton conductance and selectivity plays a key role in obtaining high vanadium flow battery (VFB) performance. In this work, the trade-off effect between proton conductance and vanadium ion blocking was overcome by the introduction of a cross-linking structure to prepare covalent cross-linked fluorine-containing sulfonated polyimide (CFSPI-PVA) membranes. Herein, the CFSPI-PVA-15 membrane possesses excellent comprehensive properties, including acceptable area resistance (0.21 Ω cm2), lower vanadium ion permeability (0.76 × 10-7 cm2 min-1), and remarkable proton selectivity (3.11 × 105 min cm-3) compared with the commercial Nafion 212 membrane. At the same time, the CFSPI-PVA-15 membrane exhibits higher coulomb efficiencies (97.26%-99.34%) and energy efficiencies (68.65%-88.11%) and a longer self-discharge duration (29.2 h) in contrast with the Nafion 212 membrane. Moreover, 500 cycles of the CFSPI-PVA-15 membrane at 160 mA cm-2 are also stably executed. The internal reasons for the improved chemical stability of the CFSPI-PVA-15 membrane are clarified from theoretical calculations with the mean square displacement value and fractional free volume. Therefore, the CFSPI-PVA-15 membrane exhibits great potential for application in VFB.

The nasal microbiota is a potential diagnostic biomarker for sepsis in critical care units.

This study aimed to characterize the composition of intestinal and nasal microbiota in septic patients and identify potential microbial biomarkers for diagnosis. A total of 157 subjects, including 89 with sepsis, were enrolled from the affiliated hospital. Nasal swabs and fecal specimens were collected from septic and non-septic patients in the intensive care unit (ICU) and Department of Respiratory and Critical Care Medicine. DNA was extracted, and the V4 region of the 16S rRNA gene was amplified and sequenced using Illumina technology. Bioinformatics analysis, statistical processing, and machine learning techniques were employed to differentiate between septic and non-septic patients. The nasal microbiota of septic patients exhibited significantly lower community richness (P = 0.002) and distinct compositions (P = 0.001) compared to non-septic patients. Corynebacterium, Staphylococcus, Acinetobacter, and Pseudomonas were identified as enriched genera in the nasal microbiota of septic patients. The constructed machine learning model achieved an area under the curve (AUC) of 89.08, indicating its efficacy in differentiating septic and non-septic patients. Importantly, model validation demonstrated the effectiveness of the nasal microecological diagnosis prediction model with an AUC of 84.79, while the gut microecological diagnosis prediction model had poor predictive performance (AUC = 49.24). The nasal microbiota of ICU patients effectively distinguishes sepsis from non-septic cases and outperforms the gut microbiota. These findings have implications for the development of diagnostic strategies and advancements in critical care medicine.IMPORTANCEThe important clinical significance of this study is that it compared the intestinal and nasal microbiota of sepsis with non-sepsis patients and determined that the nasal microbiota is more effective than the intestinal microbiota in distinguishing patients with sepsis from those without sepsis, based on the difference in the lines of nasal specimens collected.

Agricultural biomass/waste-based materials could be a potential adsorption-type remediation contributor to environmental pollution induced by pesticides-A critical review.

The widespread use of pesticides that are inevitable to keep the production of food grains brings serious environmental pollution problems. Turning agricultural biomass/wastes into materials addressing the issues of pesticide contaminants is a feasible strategy to realize the reuse of wastes. Several works summarized the current applications of agricultural biomass/waste materials in the remediation of environmental pollutants. However, few studies systematically take the pesticides as an unitary target pollutant. This critical review comprehensively described the remediation effects of crop-derived waste (cereal crops, cash crops) and animal-derived waste materials on pesticide pollution. Adsorption is considered a superior and highlighted effect between pesticides and materials. The review generalized the sources, preparation, characterization, condition optimization, removal efficiency and influencing factors analysis of agricultural biomass/waste materials. Our work mainly emphasized the promising results in lab experiments, which helps to clarify the current application status of these materials in the field of pesticide remediation. In the meantime, rigorous pros and cons of the materials guide to understand the research trends more comprehensively. Overall, we hope to achieve a large-scale use of agricultural biomass/wastes.

Forest-to-Cropland Conversion Reshapes Microbial Hierarchical Interactions and Degrades Ecosystem Multifunctionality at a National Scale.

Conversion from natural lands to cropland, primarily driven by agricultural expansion, could significantly alter soil microbiome worldwide; however, influences of forest-to-cropland conversion on microbial hierarchical interactions and ecosystem multifunctionality have not been fully understood. Here, we examined the effects of forest-to-cropland conversion on intratrophic and cross-trophic microbial interactions and soil ecosystem multifunctionality and further disclosed their underlying drivers at a national scale, using Illumina sequencing combined with high-throughput quantitative PCR techniques. The forest-to-cropland conversion significantly changed the structure of soil microbiome (including prokaryotic, fungal, and protistan communities) while it did not affect its alpha diversity. Both intrakingdom and interkingdom microbial networks revealed that the intratrophic and cross-trophic microbial interaction patterns generally tended to be more modular to resist environmental disturbance introduced from forest-to-cropland conversion, but this was insufficient for the cross-trophic interactions to maintain stability; hence, the protistan predation behaviors were still disturbed under such conversion. Moreover, key soil microbial clusters were declined during the forest-to-cropland conversion mainly because of the increased soil total phosphorus level, and this drove a great degradation of the ecosystem multifunctionality (by 207%) in cropland soils. Overall, these findings comprehensively implied the negative effects of forest-to-cropland conversion on the agroecosystem, from microbial hierarchical interactions to ecosystem multifunctionality.

Single-cell analysis of anti-BCMA CAR T cell therapy in patients with central nervous system autoimmunity.

Chimeric antigen receptor (CAR) T cell immunotherapy for the treatment of neurological autoimmune diseases is promising, but CAR T cell kinetics and immune alterations after treatment are poorly understood. Here, we performed single-cell multi-omics sequencing of paired cerebrospinal fluid (CSF) and blood samples from patients with neuromyelitis optica spectrum disorder (NMOSD) treated with anti-B cell maturation antigen (BCMA) CAR T cells. Proliferating cytotoxic-like CD8+ CAR T cell clones were identified as the main effectors in autoimmunity. Anti-BCMA CAR T cells with enhanced features of chemotaxis efficiently crossed the blood-CSF barrier, eliminated plasmablasts and plasma cells in the CSF, and suppressed neuroinflammation. The CD44-expressing early memory phenotype in infusion products was potentially associated with CAR T cell persistence in autoimmunity. Moreover, CAR T cells from patients with NMOSD displayed distinctive features of suppressed cytotoxicity compared with those from hematological malignancies. Thus, we provide mechanistic insights into CAR T cell function in patients with neurological autoimmune disease.

Towards rational design in electrochemical denitrification by analyzing pH dependence.

A small fraction of NOx (<1%) always exists in CO2 feedstock (e.g. exhausted gas), which can significantly reduce the efficiency of CO2 electroreduction by ∼30%. Hence, electrochemical denitrification is the precondition of CO2 electroreduction. The pH effect is a key factor, and can be used to tune the selectivity between N2 and N2O production in electrochemical denitrification. However, there has been much controversy for many years about the origin of pH dependence in electrocatalysis. To this end, we present a new scheme to accurately model the pH dependence of the electrochemical mechanism. An extremely small pH variation from pH 12.7 to pH 14 can be accurately reproduced for N2O production. More importantly, the obviously different pH dependence of N2 production, compared to N2O, can be attributed to a cascade path. In other words, the N2 was produced from the secondary conversion of the as-produced N2O molecule (the major product), instead of the original reactant NO. This is further supported by more than 35 experiments over varying catalysts (Fe, Ni, Pd, Cu, Co, Pt and Ag), partial pressures (20%, 50% and 100%) and potentials (from -0.2 to 0.2 V vs. reversible hydrogen electrode). All in all, the insights herein overturn long-lasting views in the field of NO electroreduction and suggest that rational design should steer away from catalyst engineering toward reactor optimization.

Moscatilin Reverses EMT Progression and its Resulting Enhanced Invasion and Migration by Affecting the TGF-ß Signaling Pathway in Bladder Cancer.

BACKGROUND: Bladder cancer metastasis is an essential process in the progression of muscle-invasive bladder cancer. EMT plays a crucial role in facilitating the spread of cancer cells. Identifying compounds that can inhibit these abilities of cancer cells is a significant international endeavor. OBJECTIVE: To explore the migration and invasion effect of Moscatilin on the bladder and clarify the mechanism of action Method: The anti-bladder cancer effect of Moscatilin was observed by a cell proliferation experiment. The migration and invasion of bladder cancer cells inhibited by Moscatilin were detected by Transwell and Wound healing. The effects of Moscatilin on EMT-related proteins E-cadherin, N-cadherin, Snail1, Vimentin, and TGF-ß signaling pathways were detected by Western blot, and nucleic acid levels were verified by qPCR Results: Our study revealed that Moscatilin reduced the viability of bladder cancer cells in vitro and impeded their migration and invasion in experimental settings. Furthermore, we observed that Moscatilin decreased the activation levels of active proteins, specifically Smad3, Samd2, and MMP2. Additionally, we found that moscatilin significantly reduced the expression level of TGF-ß and was also capable of reversing the overexpression effect of TGF-ß. Treatment with Moscatilin also led to significant inhibition of interstitial cell markers Ncadherin and Snail1, which are associated with EMT. CONCLUSION: These findings indicate that Moscatilin impedes the migration and invasion of bladder cancer cells by influencing cell survival, modulating TGF-ß/Smad signaling, and inhibiting EMT.

MedicalCLIP: Anomaly-Detection Domain Generalization with Asymmetric Constraints.

Medical data have unique specificity and professionalism, requiring substantial domain expertise for their annotation. Precise data annotation is essential for anomaly-detection tasks, making the training process complex. Domain generalization (DG) is an important approach to enhancing medical image anomaly detection (AD). This paper introduces a novel multimodal anomaly-detection framework called MedicalCLIP. MedicalCLIP utilizes multimodal data in anomaly-detection tasks and establishes irregular constraints within modalities for images and text. The key to MedicalCLIP lies in learning intramodal detailed representations, which are combined with text semantic-guided cross-modal contrastive learning, allowing the model to focus on semantic information while capturing more detailed information, thus achieving more fine-grained anomaly detection. MedicalCLIP relies on GPT prompts to generate text, reducing the demand for professional descriptions of medical data. Text construction for medical data helps to improve the generalization ability of multimodal models for anomaly-detection tasks. Additionally, during the text-image contrast-enhancement process, the model's ability to select and extract information from image data is improved. Through hierarchical contrastive loss, fine-grained representations are achieved in the image-representation process. MedicalCLIP has been validated on various medical datasets, showing commendable domain generalization performance in medical-data anomaly detection. Improvements were observed in both anomaly classification and segmentation metrics. In the anomaly classification (AC) task involving brain data, the method demonstrated a 2.81 enhancement in performance over the best existing approach.

Microglial P2Y6 calcium signaling promotes phagocytosis and shapes neuroimmune responses in epileptogenesis.

Microglial calcium signaling is rare in a baseline state but strongly engaged during early epilepsy development. The mechanism(s) governing microglial calcium signaling are not known. By developing an in vivo uridine diphosphate (UDP) fluorescent sensor, GRABUDP1.0, we discovered that UDP release is a conserved response to seizures and excitotoxicity across brain regions. UDP can signal through the microglial-enriched P2Y6 receptor to increase calcium activity during epileptogenesis. P2Y6 calcium activity is associated with lysosome biogenesis and enhanced production of NF-κB-related cytokines. In the hippocampus, knockout of the P2Y6 receptor prevents microglia from fully engulfing neurons. Attenuating microglial calcium signaling through calcium extruder ("CalEx") expression recapitulates multiple features of P2Y6 knockout, including reduced lysosome biogenesis and phagocytic interactions. Ultimately, P2Y6 knockout mice retain more CA3 neurons and better cognitive task performance during epileptogenesis. Our results demonstrate that P2Y6 signaling impacts multiple aspects of myeloid cell immune function during epileptogenesis.

Ldl-stimulated microglial activation exacerbates ischemic white matter damage.

The role of microglia in triggering the blood-brain barrier (BBB) impairment and white matter damage after chronic cerebral hypoperfusion is unclear. Here we demonstrated that the vessel-adjacent microglia were specifically activated by the leakage of plasma low-density lipoprotein (LDL), which led to BBB breakdown and ischemic demyelination. Interestingly, we found that LDL stimulation enhanced microglial phagocytosis, causing excessive engulfment of myelin debris and resulting in an overwhelming lipid burden in microglia. Surprisingly, these lipid-laden microglia exhibited a suppressed profile of inflammatory response and compromised pro-regenerative properties. Microglia-specific knockdown of LDLR or systematic medication lowering circulating LDL-C showed protective effects against ischemic demyelination. Overall, our findings demonstrated that LDL-stimulated vessel-adjacent microglia possess a disease-specific molecular signature, characterized by suppressed regenerative properties, which is associated with the propagation of demyelination during ischemic white matter damage.

Emerging therapeutic frontiers in cancer: insights into posttranslational modifications of PD-1/PD-L1 and regulatory pathways.

The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research.

Diagnosis model of early Pneumocystis jirovecii pneumonia based on convolutional neural network: a comparison with traditional PCR diagnostic method.

BACKGROUND: Pneumocystis jirovecii pneumonia (PJP) is an interstitial pneumonia caused by pneumocystis jirovecii (PJ). The diagnosis of PJP primarily relies on the detection of the pathogen from lower respiratory tract specimens. However, it faces challenges such as difficulty in obtaining specimens and low detection rates. In the clinical diagnosis process, it is necessary to combine clinical symptoms, serological test results, chest Computed tomography (CT) images, molecular biology techniques, and metagenomics next-generation sequencing (mNGS) for comprehensive analysis. PURPOSE: This study aims to overcome the limitations of traditional PJP diagnosis methods and develop a non-invasive, efficient, and accurate diagnostic approach for PJP. By using this method, patients can receive early diagnosis and treatment, effectively improving their prognosis. METHODS: We constructed an intelligent diagnostic model for PJP based on the different Convolutional Neural Networks. Firstly, we used the Convolutional Neural Network to extract CT image features from patients. Then, we fused the CT image features with clinical information features using a feature fusion function. Finally, the fused features were input into the classification network to obtain the patient's diagnosis result. RESULTS: In this study, for the diagnosis of PJP, the accuracy of the traditional PCR diagnostic method is 77.58%, while the mean accuracy of the optimal diagnostic model based on convolutional neural networks is 88.90%. CONCLUSION: The accuracy of the diagnostic method proposed in this paper is 11.32% higher than that of the traditional PCR diagnostic method. The method proposed in this paper is an efficient, accurate, and non-invasive early diagnosis approach for PJP.

Prelimbic cortex-nucleus accumbens core projection positively regulates itch and itch-related aversion.

Itch is one of the most common clinical symptoms in patients with diseases of the skin, liver, or kidney, and it strongly triggers aversive emotion and scratching behavior. Previous studies have confirmed the role of the prelimbic cortex (Prl) and the nucleus accumbens core (NAcC), which are reward and motivation regulatory centers, in the regulation of itch. However, it is currently unclear whether the Prl-NAcC projection, an important pathway connecting these two brain regions, is involved in the regulation of itch and its associated negative emotions. In this study, rat models of acute neck and cheek itch were established by subcutaneous injection of 5-HT, compound 48/80, or chloroquine. Immunofluorescence experiments determined that the number of c-Fos-immunopositive neurons in the Prl increased during acute itch. Chemogenetic inhibition of Prl glutamatergic neurons or Prl-NAcC glutamatergic projections can inhibit both histaminergic and nonhistaminergic itch-scratching behaviors and rectify the itch-related conditioned place aversion (CPA) behavior associated with nonhistaminergic itch. The Prl-NAcC projection may play an important role in the positive regulation of itch-scratching behavior by mediating the negative emotions related to itch.

CCR2+ monocytes replenish border-associated macrophages in the diseased mouse brain.

Border-associated macrophages (BAMs) are tissue-resident macrophages that reside at the border of the central nervous system (CNS). Since BAMs originate from yolk sac progenitors that do not persist after birth, the means by which this population of cells is maintained is not well understood. Using two-photon microscopy and multiple lineage-tracing strategies, we determine that CCR2+ monocytes are significant contributors to BAM populations following disruptions of CNS homeostasis in adult mice. After BAM depletion, while the residual BAMs possess partial self-repopulation capability, the CCR2+ monocytes are a critical source of the repopulated BAMs. In addition, we demonstrate the existence of CCR2+ monocyte-derived long-lived BAMs in a brain compression model and in a sepsis model after the initial disruption of homeostasis. Our study reveals that the short-lived CCR2+ monocytes transform into long-lived BAM-like cells at the CNS border and subsequently contribute to BAM populations.

Catalytic Asymmetric Synthesis of Vicinal Quaternary Stereocenters Enabled by Alkylation of α,α-Disubstituted Aldehydes with 3-Bromooxindoles.

An organocatalytic enantioselective alkylation of α,α-disubstituted aldehydes with 3-bromooxindoles is reported. Enantioenriched oxindoles with vicinal quaternary stereocenters are accessed by an asymmetric conjugate addition process of branched aldehydes with o-azaxylylene intermediates (indol-2-ones). Key to the success of highly diastereo- and enantioselective transformations is the combined use of a triphenylsilyl-protected ß-amino alcohol catalyst derived from the spiropyrrolidine scaffold and 3,5-dinitrobenzoic acid. This study also presents a rare example of aldehyde alkylation with the formation of consecutive quaternary stereocenters.

Seasonal variations of profiles of antibiotic resistance genes and virulence factor genes in household dust from Beijing, China revealed by the metagenomics.

Household-related microbiome is closely related with human health. However, the knowledge about profiles of antibiotic resistance genes (ARGs) and virulence factor genes (VFGs) which are carried by microbes inside homes and their temporal dynamics are rather limited. Here we monitored the seasonal changes of bacterial community (especially pathogenic bacteria), ARGs, and VFGs in household dust samples during two years. Based on metagenomic sequencing, the dust-related bacterial pathogenic community, ARGs, and VFGs all harbored the lowest richness in spring among four seasons. Their structure (except that of VFGs) also exhibited remarkable differences among the seasons. The structural variations of ARGs and VFGs were almost explained by mobile genetic elements (MGEs), bacterial pathogens, and particulate matter-related factors, with MGEs explaining the most. Moreover, the total normalized abundance of ARGs or VFGs showed no significant change across the seasons. Results of metagenomic binning and microbial network both showed that several pathogenic taxa (e.g., Ralstonia pickettii) were strongly linked with numerous ARGs (mainly resistant to multidrug) and VFGs (mainly encoding motility) simultaneously. Overall, these findings underline the significance of MGEs in structuring ARGs and VFGs inside homes along with seasonal variations, suggesting that household dust is a neglected reservoir for ARGs and VFGs.

Acute to long-term characteristics of impedance recordings during neurostimulation in humans.

Objective.This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Approach.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24 h impedance cycle throughout the multi-month recording.Main results.Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 d to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24 h impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.Significance.Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.

Developing Air-Stable n-Type SWCNT-Based Composites with High Thermoelectric and Robust Mechanical Properties for Wearable Electronics.

Flexible organic thermoelectric generators are gaining prominence in wearable electronics, leveraging body heat as an energy source. Their advancement is hindered by the scarcity of air-stable n-type organic materials with robust mechanical properties. This study introduces two new polymers (HDCN4 and HDCN8), created through polycondensation of paraformaldehyde and diamine-terminated poly(ethylene glycol) (PEGDA) with molecular weights of 4000 and 8000 g/mol into single-walled carbon nanotubes (SWCNTs). The resulting HDCN4/SWCNT and HDCN8/SWCNT composites show impressive power factors of 225.9 and 108.2 µW m-1 K-2, respectively, and maintain over 90% in air for over four months without encapsulation. The HDCN4/SWCNT composite also demonstrates significant tensile strength (33.2 MPa) and flexibility (up to 10% strain), which is currently the best mechanically n-type thermoelectric material with such a high power factor reported in the literature. A thermoelectric device based on HDCN4/SWCNT generates 4.2 µW of power with a 50 K temperature difference. Additionally, when used in wearable temperature sensors, these devices exhibit high mechanical reliability and a temperature resolution of 0.1 K. This research presents a viable method to produce air-stable n-type thermoelectric materials with excellent performance and mechanical properties.

Nanomaterials Boost CAR-T Therapy for Solid Tumors.

T cell engineering, particularly via chimeric antigen receptor (CAR) modifications for enhancing tumor specificity, has shown efficacy in treating hematologic malignancies. The extension of CAR-T cell therapy to solid tumors, however, is impeded by several challenges: The absence of tumor-specific antigens, antigen heterogeneity, a complex immunosuppressive tumor microenvironment, and physical barriers to cell infiltration. Additionally, limitations in CAR-T cell manufacturing capacity and the high costs associated with these therapies restrict their widespread application. The integration of nanomaterials into CAR-T cell production and application offers a promising avenue to mitigate these challenges. Utilizing nanomaterials in the production of CAR-T cells can decrease product variability and lower production expenses, positively impacting the targeting and persistence of CAR-T cells in treatment and minimizing adverse effects. This review comprehensively evaluates the use of various nanomaterials in the production of CAR-T cells, genetic modification, and in vivo delivery. It discusses their underlying mechanisms and potential for clinical application, with a focus on improving specificity and safety in CAR-T cell therapy.