Autoantibodies against chemokines post-SARS-CoV-2 infection correlate with disease course.

Infection with severe acute respiratory syndrome coronavirus 2 associates with diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse coronavirus disease 2019 (COVID-19) outcomes. Here we discovered that antibodies against specific chemokines were omnipresent post-COVID-19, were associated with favorable disease outcome and negatively correlated with the development of long COVID at 1 yr post-infection. Chemokine antibodies were also present in HIV-1 infection and autoimmune disorders, but they targeted different chemokines compared with COVID-19. Monoclonal antibodies derived from COVID-19 convalescents that bound to the chemokine N-loop impaired cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising chemokine antibodies may modulate the inflammatory response and thus bear therapeutic potential.

Commensal viruses maintain intestinal intraepithelial lymphocytes via noncanonical RIG-I signaling.

Much attention has focused on commensal bacteria in health and disease, but the role of commensal viruses is understudied. Although metagenomic analysis shows that the intestine of healthy humans and animals harbors various commensal viruses and the dysbiosis of these viruses can be associated with inflammatory diseases, there is still a lack of causal data and underlying mechanisms to understand the physiological role of commensal viruses in intestinal homeostasis. In the present study, we show that commensal viruses are essential for the homeostasis of intestinal intraepithelial lymphocytes (IELs). Mechanistically, the cytosolic viral RNA-sensing receptor RIG-I in antigen-presenting cells can recognize commensal viruses and maintain IELs via a type I interferon-independent, but MAVS-IRF1-IL-15 axis-dependent, manner. The recovery of IELs by interleukin-15 administration reverses the susceptibility of commensal virus-depleted mice to dextran sulfate sodium-induced colitis. Collectively, our results indicate that commensal viruses maintain the IELs and consequently sustain intestinal homeostasis via noncanonical RIG-I signaling.

YkuR functions as a protein deacetylase in Streptococcus mutans.

Protein acetylation is a common and reversible posttranslational modification tightly governed by protein acetyltransferases and deacetylases crucial for various biological processes in both eukaryotes and prokaryotes. Although recent studies have characterized many acetyltransferases in diverse bacterial species, only a few protein deacetylases have been identified in prokaryotes, perhaps in part due to their limited sequence homology. In this study, we identified YkuR, encoded by smu_318, as a unique protein deacetylase in Streptococcus mutans. Through protein acetylome analysis, we demonstrated that the deletion of ykuR significantly upregulated protein acetylation levels, affecting key enzymes in translation processes and metabolic pathways, including starch and sucrose metabolism, glycolysis/gluconeogenesis, and biofilm formation. In particular, YkuR modulated extracellular polysaccharide synthesis and biofilm formation through the direct deacetylation of glucosyltransferases (Gtfs) in the presence of NAD+. Intriguingly, YkuR can be acetylated in a nonenzymatic manner, which then negatively regulated its deacetylase activity, suggesting the presence of a self-regulatory mechanism. Moreover, in vivo studies further demonstrated that the deletion of ykuR attenuated the cariogenicity of S. mutans in the rat caries model, substantiating its involvement in the pathogenesis of dental caries. Therefore, our study revealed a unique regulatory mechanism mediated by YkuR through protein deacetylation that regulates the physiology and pathogenicity of S. mutans.

RNA viruses promote activation of the NLRP3 inflammasome through a RIP1-RIP3-DRP1 signaling pathway.

The NLRP3 inflammasome functions as a crucial component of the innate immune system in recognizing viral infection, but the mechanism by which viruses activate this inflammasome remains unclear. Here we found that inhibition of the serine-threonine kinases RIP1 (RIPK1) or RIP3 (RIPK3) suppressed RNA virus-induced activation of the NLRP3 inflammasome. Infection with an RNA virus initiated assembly of the RIP1-RIP3 complex, which promoted activation of the GTPase DRP1 and its translocation to mitochondria to drive mitochondrial damage and activation of the NLRP3 inflammasome. Notably, the RIP1-RIP3 complex drove the NLRP3 inflammasome independently of MLKL, an essential downstream effector of RIP1-RIP3-dependent necrosis. Together our results reveal a specific role for the RIP1-RIP3-DRP1 pathway in RNA virus-induced activation of the NLRP3 inflammasome and establish a direct link between inflammation and cell-death signaling pathways.

LncRNA CHROMR/miR-27b-3p/MET axis promotes the proliferation, invasion, and contributes to rituximab resistance in diffuse large B-cell lymphoma.

Long non-coding RNAs (LncRNAs) could regulate chemoresistance through sponging microRNAs (miRNAs) and sequestering RNA binding proteins. However, the mechanism of lncRNAs in rituximab resistance in diffuse large B-cell lymphoma (DLBCL) is largely unknown. Here, we investigated the functions and molecular mechanisms of lncRNA CHROMR in DLBCL tumorigenesis and chemoresistance. LncRNA CHROMR is highly expressed in DLBCL tissues and cells. We examined the oncogenic functions of lncRNA CHROMR in DLBCL by a panel of gain-or-loss-of-function assays and in vitro experiments. LncRNA CHROMR suppression promotes CD20 transcription in DLBCL cells and inhibits rituximab resistance. RNA immunoprecipitation, RNA pull-down, and dual luciferase reporter assay reveal that lncRNA CHROMR sponges with miR-27b-3p to regulate mesenchymal-epithelial transition factor (MET) levels and Akt signaling in DLBCL cells. Targeting the lncRNA CHROMR/miR-27b-3p/MET axis reduces DLBCL tumorigenesis. Altogether, these findings provide a new regulatory model, lncRNA CHROMR/miR-27b-3p/MET, which can serve as a potential therapeutic target for DLBCL.

Accelerating multipool CEST MRI of Parkinson's disease using deep learning-based Z-spectral compressed sensing.

PURPOSE: To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for Parkinson's disease (PD) while maintaining sufficient prediction accuracy. METHOD: A deep learning approach based on a modified one-dimensional U-Net, termed Z-spectral compressed sensing (CS), was proposed to recover dense Z-spectra from sparse ones. The neural network was trained using simulated Z-spectra generated by the Bloch equation with various parameter settings. Its feasibility and effectiveness were validated through numerical simulations and in vivo rat brain experiments, compared with commonly used linear, pchip, and Lorentzian interpolation methods. The proposed method was applied to detect metabolism-related changes in the 6-hydroxydopamine PD model with multipool CEST MRI, including APT, CEST@2 ppm, nuclear Overhauser enhancement, direct saturation, and magnetization transfer, and the prediction performance was evaluated by area under the curve. RESULTS: The numerical simulations and in vivo rat-brain experiments demonstrated that the proposed method could yield superior fidelity in retrieving dense Z-spectra compared with existing methods. Significant differences were observed in APT, CEST@2 ppm, nuclear Overhauser enhancement, and direct saturation between the striatum regions of wild-type and PD models, whereas magnetization transfer exhibited no significant difference. Receiver operating characteristic analysis demonstrated that multipool CEST achieved better predictive performance compared with individual pools. Combined with Z-spectral CS, the scan time of multipool CEST MRI can be reduced to 33% without distinctly compromising prediction accuracy. CONCLUSION: The integration of Z-spectral CS with multipool CEST MRI can enhance the prediction accuracy of PD and maintain the scan time within a reasonable range.

sLASER and PRESS perform similarly at revealing metabolite-age correlations at 3 T.

PURPOSE: To compare the respective ability of PRESS and sLASER to reveal biological relationships, using age as a validation covariate at 3 T. METHODS: MRS data were acquired from 102 healthy volunteers using PRESS and sLASER in centrum semiovale and posterior cingulate cortex (PCC). Acquisition parameters included TR/TE = 2000/30 ms, 96 transients, and 2048 datapoints sampled at 2 kHz. Spectra were analyzed using Osprey. SNR, FWHM linewidth of total creatine, and metabolite concentrations were extracted. A linear model was used to compare SNR and linewidth. Paired t-tests were used to assess differences in metabolite measurements between PRESS and sLASER. Correlations were used to evaluate the relationship between PRESS and sLASER metabolite estimates, as well as the strength of each metabolite-age relationship. Coefficients of variation were calculated to assess inter-subject variability in each metabolite measurement. RESULTS: SNR and linewidth were significantly higher (p < 0.01) for sLASER than PRESS in PCC. Paired t-tests showed significant differences between PRESS and sLASER in most metabolite measurements. PRESS-sLASER measurements were significantly correlated (p < 0.05) for most metabolites. Metabolite-age relationships were consistently identified using both methods. Similar coefficients of variation were observed for most metabolites. CONCLUSION: The study results suggest strong agreement between PRESS and sLASER in identifying relationships between brain metabolites and age in centrum semiovale and PCC data acquired at 3 T. sLASER is technically desirable due to the reduced chemical shift displacement artifact; however, PRESS performed similarly in homogeneous brain regions at clinical field strength.

SMU_1361c regulates the oxidative stress response of Streptococcus mutans.

Dental caries is the most common chronic infectious disease around the world and disproportionately affects the marginalized socioeconomic group. Streptococcus mutans, considered a primary etiological agent of caries, depends on the coordinated physiological response to tolerate the oxidative stress generated by commensal species within dental plaque, which is a critical aspect of its pathogenicity. Here, we identified and characterized a novel tetracycline repressor family regulator, SMU_1361c, which appears to be acquired by the bacteria via horizontal gene transfer. Surprisingly, smu_1361c functions as a negative transcriptional regulator to regulate gene expression outside its operon and is involved in the oxidative stress response of S. mutans. The smu_1361c overexpression strain UA159/pDL278-1361c was more susceptible to oxidative stress and less competitive against hydrogen peroxide generated by commensal species Streptococcus gordonii and Streptococcus sanguinis. Transcriptomics analysis revealed that smu_1361c overexpression resulted in the significant downregulation of 22 genes, mainly belonging to three gene clusters responsible for the oxidative stress response. The conversed DNA binding motif of SMU_1361c was determined by electrophoretic mobility shift and DNase I footprinting assay with purified SMU_1361c protein; therefore, smu_1361c is directly involved in gene transcription related to the oxidative stress response. Crucially, our finding provides a new understanding of how S. mutans deals with the oxidative stress that is required for pathogenesis and will facilitate the development of new and improved therapeutic approaches for dental caries.IMPORTANCEStreptococcus mutans is the major organism associated with the development of dental caries, which globally is the most common chronic disease. To persist and survive in biofilms, S. mutans must compete with commensal species that occupy the same ecological niche. Here, we uncover a novel molecular mechanism of how tetracycline repressor family regulator smu_1361c is involved in the oxidative stress response through transcriptomics analysis, electrophoretic mobility shift assay, and DNase I footprinting assay. Furthermore, we demonstrated that smu_1361c mediates S. mutans sensitivity to oxidative stress and competitiveness with commensal streptococci. Therefore, this study has revealed a previously unknown regulation between smu_1361c and genes outside its operon and demonstrated the importance of smu_1361c in the oxidative stress response and the fitness of S. mutans within the plaque biofilms, which can be exploited as a new therapy to modulate ecological homeostasis and prevent dental caries.

Simple, sensitive, and visual detection of 12 respiratory pathogens with one-pot-RPA-CRISPR/Cas12a assay.

Respiratory infections pose a serious threat to global public health, underscoring the urgent need for rapid, accurate, and large-scale diagnostic tools. In recent years, the CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, combined with isothermal amplification methods, has seen widespread application in nucleic acid testing (NAT). However, achieving a single-tube reaction system containing all necessary components is challenging due to the competitive effects between recombinase polymerase amplification (RPA) and CRISPR/Cas reagents. Furthermore, to enable precision medicine, distinguishing between bacterial and viral infections is essential. Here, we have developed a novel NAT method, termed one-pot-RPA-CRISPR/Cas12a, which combines RPA with CRISPR molecular diagnostic technology, enabling simultaneous detection of 12 common respiratory pathogens, including six bacteria and six viruses. RPA and CRISPR/Cas12a reactions are separated by paraffin, providing an independent platform for RPA reactions to generate sufficient target products before being mixed with the CRISPR/Cas12a system. Results can be visually observed under LED blue light. The sensitivity of the one-pot-RPA-CRISPR/Cas12a method is 2.5 × 100 copies/µL plasmids, with no cross-reaction with other bacteria or viruses. Additionally, the clinical utility was evaluated by testing clinical isolates of bacteria and virus throat swab samples, demonstrating favorable performance. Thus, our one-pot-RPA-CRISPR/Cas12a method shows immense potential for accurate and large-scale detection of 12 common respiratory pathogens in point-of-care testing.

Autophagy-related protein 5 (ATG5) interacts with bone marrow stromal cell antigen 2 (BST2) to stimulate HBV replication through antagonizing the antiviral activity of BST2.

Hepatitis B virus (HBV) infection is a major global health burden with 820 000 deaths per year. In our previous study, we found that the knockdown of autophagy-related protein 5 (ATG5) significantly upregulated the interferon-stimulated genes (ISGs) expression to exert the anti-HCV effect. However, the regulation of ATG5 on HBV replication and its underlying mechanism remains unclear. In this study, we screened the altered expression of type I interferon (IFN-I) pathway genes using RT² Profiler™ PCR array following ATG5 knock-down and we found the bone marrow stromal cell antigen 2 (BST2) expression was significantly increased. We then verified the upregulation of BST2 by ATG5 knockdown using RT-qPCR and found that the knockdown of ATG5 activated the Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway. ATG5 knockdown or BST2 overexpression decreased Hepatitis B core Antigen (HBcAg) protein, HBV DNA levels in cells and supernatants of HepAD38 and HBV-infected NTCP-HepG2. Knockdown of BST2 abrogated the anti-HBV effect of ATG5 knockdown. Furthermore, we found that ATG5 interacted with BST2, and further formed a ternary complex together with HBV-X (HBx). In conclusion, our finding indicates that ATG5 promotes HBV replication through decreasing BST2 expression and interacting with it directly to antagonize its antiviral function.

Metabolite T1 relaxation times decrease across the adult lifespan.

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray- and white-matter-rich voxels using publicly available metabolite and metabolite-nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20-69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N-acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite-nulled spectrum to the full metabolite signal was calculated using the single-inversion-recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = -0.27; p < 0.006) and tCr3.0 (rs = -0.40; p < 0.001) decreased significantly with age in white-matter-rich CSO, and less steeply for tNAA2.0 (rs = -0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = -0.13; p = 0.196) in graymatter-rich PCC. The analysis harnessed a large publicly available cross-sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age-normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging.

Application of high-resolution MRI in evaluating statin efficacy on symptomatic intracranial atherosclerosis.

OBJECTIVES: To investigate the efficacy of statins on symptomatic intracranial atherosclerotic plaques using high-resolution 3.0 T MR vessel wall imaging (HR-MRI). METHODS: Patients with symptomatic intracranial atherosclerotic plaques (cerebral ischemic events within the last three months) confirmed by HR-MRI from July 2017 to August 2022 were retrospectively included in this study. The enrolled patients started statin therapy at baseline. All the patients underwent the follow-up HR-MRI examination after statin therapy for at least 3 months. A paired sample t-test and Wilcoxon rank sum test were used to evaluate the changes in plaque characteristics after statin therapy. Multivariate linear regression was further used to investigate the clinical factors associated with statin efficacy. RESULTS: A total of 48 patients (37 males; overall mean age = 60.2 ± 11.7 years) were included in this study. The follow-up time was 7.0 (5.6-12.0) months. In patients treated with statins for > 6 months (n = 31), plaque length, wall thickness, plaque burden, luminal stenosis and plaque enhancement were significantly reduced. Similar results were found in patients with good lipid control (n = 21). Younger age, lower BMI and hypertension were associated with decreased plaque burden. Lower BMI, hypertension and longer duration of statin therapy were associated with decreased plaque enhancement. Younger age and hypertension were associated with decreased luminal stenosis (all p < 0.05). CONCLUSION: HR-MRI can effectively evaluate plaques changes after statin therapy. Statins can reduce plaque burden and stabilize plaques. The effect of statin may have a relationship with age, BMI, hypertension, and duration of statin therapy. CLINICAL RELEVANCE STATEMENT: High-resolution MRI can be applied to evaluate the efficacy of statins on symptomatic intracranial atherosclerotic plaques. Long-term statin use and well-controlled blood lipid levels can help reduce plaque burden and stabilize plaques. KEY POINTS: High-resolution MRI provides great help evaluating the changes of plaque characteristics after statin therapy. Efficacy of statins is associated with duration of use, controlled lipid levels, and clinical factors. High-resolution MRI can serve as an effective method for following-up symptomatic intracranial atherosclerosis.

Time-Lapse Macro Imaging with Dissolution Tests for Exploring the Interrelationship Between Disintegration and Dissolution Behaviors of Solid Dosages.

OBJECTIVE: This study aims to establish a Flow-through Visualization Dissolution System (FVDS) that combines time-lapse macro-imaging and a flow-through cell to simultaneously elucidate dissolution and disintegration profiles. METHODS: Three cefaclor extended-release tablets (CEC-1, CEC-2, CEC-3) from different manufacturers were subjected to dissolution tests using both the US Pharmacopeia basket method and the FVDS method. Two dissolution media plans were implemented in FVDS: i) Plan I involved dissolution in pH1.0 medium for 12 h; ii) Plan II initiated dissolution in pH1.0 medium for 1 h, followed by pH6.8 phosphate buffer for 11 h. The resulting dissolution data were fitted using classic mathematical models. Pixel information was further extracted from images obtained using FVDS and plotted over time. RESULTS: The basket method showed the cumulative dissolution of all three tablets in pH1.0, pH4.0 and water reached 80% within 6 h, but remained below 60% in the pH6.8 medium. The f2 values indicated CEC-2 was similar to CEC-1 in the pH4.0 medium, pH6.8 medium and water. Using FVDS with medium plan II, the cumulative dissolution of CEC-1 and CEC-2 reached about 80% showing similarity, while no similarity was observed between CEC-3 and CEC-1. The f2 factor of the percentage area change profiles also showed consistent results in the dissolution profile of medium plan II. However, FVDS with medium plan I cannot distinguish between CEC-2 and CEC-3. CONCLUSION: FVDS offers an alternative to traditional dissolution methods by integrating imaging analysis as a complementary tool to disintegration and dissolution testing methods.

Development and validation of outcome prediction model for reperfusion therapy in acute ischemic stroke using nomogram and machine learning.

OBJECTIVE: To develop logistic regression nomogram and machine learning (ML)-based models to predict 3-month unfavorable functional outcome for acute ischemic stroke (AIS) patients undergoing reperfusion therapy. METHODS: Patients undergoing reperfusion therapy (intravenous thrombolysis and/or endovascular treatment) were prospectively recruited. Unfavorable outcome was defined as 3-month modified Rankin Scale (mRS) score 3-6. The independent risk factors associated with unfavorable outcome were obtained by regression analysis and included in the prediction model. The performance of nomogram was assessed by the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). ML models were compared with nomogram using AUC; the generalizability of all models was ascertained in an external cohort. RESULTS: A total of 505 patients were enrolled, with 256 in the model construction, and 249 in the external validation. Five variables were identified as prognostic factors: baseline NIHSS, D-dimer level, random blood glucose (RBG), blood urea nitrogen (BUN), and systolic blood pressure (SBP) before reperfusion. The AUC values of nomogram were 0.865, 0.818, and 0.779 in the training set, test set, and external validation, respectively. The calibration curve and DCA indicated appreciable reliability and good net benefits. The best three ML models were extra trees (ET), CatBoost, and random forest (RF) models; all of them showed favorable discrimination in the training cohort, and confirmed in the test and external sets. CONCLUSION: Baseline NIHSS, D-dimer, RBG, BUN, and SBP before reperfusion were independent predictors for 3-month unfavorable outcome after reperfusion therapy in AIS patients. Both nomogram and ML models showed good discrimination and generalizability.

Benefits of Virtual Reality Training for Cardiopulmonary Resuscitation Skill Acquisition and Maintenance.

OBJECTIVES: To investigate the benefits of virtual reality (VR) first-aid training in acquiring cardiopulmonary resuscitation (CPR) skills. METHODS: A total of 100 non-medical professional volunteers from Nanchang were selected in March 2021 using the convenience sampling method. They were randomly divided into two groups: the VR training group (VR group) and the traditional simulation scenario training group (traditional group). The VR Group underwent immersive virtual reality CPR training with interactive feedback, while the Traditional Group received standard simulation-based CPR training using mannequins and instructor guidance. After training, relevant data were collected for comparative analysis. RESULTS: The study revealed that the VR group consistently outperforming the traditional group in theoretical knowledge test (cardiac arrest recognition, chest compressions, airway management, and artificial respiration) scores at 1, 3, 6, and 12 months post-training (p < 0.05). Similarly, the VR group showed superior performance in overall skills test scores and individual CPR quality metrics at all post-training assessments. The VR group scored higher in total skills, assessment, post-resuscitation assessment, chest compressions (at 1, 3, and 6 months), airway opening, and artificial respiration compared to the traditional group (p < 0.05). Despite these findings, both groups exhibited a gradual decrease in skills test scores over time. CONCLUSIONS: Virtual reality training can significantly improve non-medical professional volunteers' CPR knowledge and skill levels, helping them master and maintain these competencies. However, a decrease in CPR knowledge and skills among the participants over time was observed after VR training, suggesting the need for further retraining sessions.

Immunotherapy of microsatellite stable colorectal cancer: resistance mechanisms and treatment strategies.

In recent years, immunotherapy strategies based on immune checkpoint inhibitors have yielded good efficacy in colorectal cancer (CRC)especially in colorectal cancer with microsatellite instability-high. However, microsatellite-stable (MSS) CRCs account for about 85% of CRCs and are resistant to immunotherapy. Previous studies have shown that compared with MSS CRC, high microsatellite instability CRC possesses a higher frequency of mutations and can generate more neoantigens. Therefore, improving the sensitivity of immunotherapy to MSS CRC is a hot topic which is crucial for the treatment of MSS CRC. This review aims to discuss the factors contributing to MSS CRC insensitivity to immunotherapy and explored potential solutions to overcome immunotherapy resistance.

Cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of Shigella flexneri.

Pathogen infections including Shigella flexneri have posed a significant threat to human health for numerous years. Although culturing and qPCR were the gold standards for pathogen detection, time-consuming and instrument-dependent restrict their application in rapid diagnosis and economically less-developed regions. Thus, it is urgently needed to develop rapid, simple, sensitive, accurate, and low-cost detection methods for pathogen detection. In this study, an immunomagnetic beads-recombinase polymerase amplification-CRISPR/Cas12a (IMB-RPA-CRISPR/Cas12a) method was built based on a cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of S. flexneri in the laboratory. Firstly, S. flexneri was specifically captured and enriched by IMB (Shigella antibody-coated magnetic beads), and the genomic DNA was released and used as the template in the RPA reaction. Then, the RPA products were mixed with the pre-loaded CRISPR/Cas12a for fluorescence visualization. The results were observed by naked eyes under LED blue light, with a sensitivity of 5 CFU/mL in a time of 70 min. With no specialized equipment or complicated technical requirements, the IMB-RPA-CRISPR/Cas12a diagnostic method can be used for visual, rapid, and simple detection of S. flexneri and can be easily adapted to monitoring other pathogens.

Exploring the Processing Paradigm of Input Data for End-to-End Deep Learning in Tool Condition Monitoring.

Tool condition monitoring technology is an indispensable part of intelligent manufacturing. Most current research focuses on complex signal processing techniques or advanced deep learning algorithms to improve prediction performance without fully leveraging the end-to-end advantages of deep learning. The challenge lies in transforming multi-sensor raw data into input data suitable for direct model feeding, all while minimizing data scale and preserving sufficient temporal interpretation of tool wear. However, there is no clear reference standard for this so far. In light of this, this paper innovatively explores the processing methods that transform raw data into input data for deep learning models, a process known as an input paradigm. This paper introduces three new input paradigms: the downsampling paradigm, the periodic paradigm, and the subsequence paradigm. Then an improved hybrid model that combines a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) was employed to validate the model's performance. The subsequence paradigm demonstrated considerable superiority in prediction results based on the PHM2010 dataset, as the newly generated time series maintained the integrity of the raw data. Further investigation revealed that, with 120 subsequences and the temporal indicator being the maximum value, the model's mean absolute error (MAE) and root mean square error (RMSE) were the lowest after threefold cross-validation, outperforming several classical and contemporary methods. The methods explored in this paper provide references for designing input data for deep learning models, helping to enhance the end-to-end potential of deep learning models, and promoting the industrial deployment and practical application of tool condition monitoring systems.

Hsp70-Targeting and Size-Tunable Nanoparticles Combine with PD-1 Checkpoint Blockade to Treat Glioma.

Invasive glioma usually disrupts the integrity of the blood-brain barrier (BBB), making the delivery of nanodrugs across the BBB possible, but sufficient targeting ability is still avidly needed to improve drug accumulation in glioma. Membrane-bound heat shock protein 70 (Hsp70) is expressed on the membrane of glioma cells rather than adjacent normal cells, therefore it can serve as a specific glioma target. Meanwhile, prolonging the retention in tumors is important for active-targeting nanoparticles to overcome receptor-binding barriers. Herein, the Hsp70-targeting and acid-triggered self-assembled gold nanoparticles (D-A-DA/TPP) are proposed to realize selective delivery of doxorubicin (DOX) to glioma. In the weakly acidic glioma matrix, D-A-DA/TPP formed aggregates to prolong retention, improve receptor-binding efficiency and facilitate acid-responsive DOX release. DOX accumulation in glioma induced immunogenic cell death (ICD) to promote antigen presentation. Meanwhile, combination with the PD-1 checkpoint blockade further activate T cells and provokes robust anti-tumor immunity. The results showed that D-A-DA/TPP can induce more glioma apoptosis. Furthermore, in vivo studies indicated D-A-DA/TPP plus PD-1 checkpoint blockade significantly improved median survival time. This study offeres a potential nanocarrier combining size-tunable strategy with active targeting ability to increase drug enrichment in glioma and synergizes with PD-1 checkpoint blockade to achieve chemo-immunotherapy.