Comparison of various doses of oral cannabidiol for treating refractory epilepsy indications: a network meta-analysis.

Aim: To evaluate the comparative efficacy and safety of various doses of oral cannabidiol (CBD) in treating refractory epilepsy indications, thus providing more informative evidence for clinical decision-making. Methods: A literature search of PubMed, Embase, the Cochrane library, and Web of Science (WoS) was performed to retrieve relevant randomized controlled trials (RCTs) that compared different doses of oral CBD with placebo or each other in refractory epilepsy indications. The search was limited from the inception of each database to January 3, 2023. Relative risk [RR] with a 95% confidence interval [CI] was used to express results. STATA/SE 14 was employed for network meta-analysis. Results: Six RCTs involving 972 patients were included in the final data analysis. Network meta-analysis showed that, CBD10 (10 mg/kg/day) (RR: 1.77, 95%CI: 1.28 to 2.44), CBD20 (20 mg/kg/day) (RR: 1.91, 95%CI: 1.49 to 2.46), CBD25 (25 mg/kg/day) (RR: 1.61, 95%CI: 0.96 to 2.70), and CBD50 (50 mg/kg/day) (RR: 1.78, 95%CI: 1.07 to 2.94) were associated with higher antiseizure efficacy although the pooled result for CBD25 was only close to significant. In addition, in terms of the risk of treatment-emergent adverse events (TEAEs), the difference between different doses is not significant. However, CBD20 ranked first in terms of antiseizure efficacy, followed by CBD50, CBD10, and CBD25. For TEAEs, CBD25 ranked first, followed by CBD10, CBD50, CBD5, and CBD20. Conclusion: For refractory indications, CBD20 may be optimal option for antiseizure efficacy; however, CBD25 may be best for TEAEs. Therefore, an appropriate dose of oral CBD should be selected based on the actual situation. Due to the limitations of eligible studies and the limited sample size, more studies are needed in the future to validate our findings.

Microcavity induced by a few-layer GaSe crystal on a silicon photonic crystal waveguide for efficient optical frequency conversion.

We demonstrate the post-induction of high-quality microcavities on a silicon photonic crystal (PC) waveguide by integrating a few-layer GaSe crystal, which promises efficient on-chip optical frequency conversions. The integration of GaSe shifts the dispersion bands of the PC waveguide mode into the bandgap, resulting in localized modes confined by the bare PC waveguides. Thanks to the small contrast of refractive index at the boundaries of the microcavity, it is reliable to obtain quality factors exceeding 104. With the enhanced light-GaSe interaction by the microcavity modes and GaSe's high second-order nonlinearity, remarkable second-harmonic generation (SHG) and sum-frequency generation (SFG) are achieved with continuous-wave (CW) lasers.

Trap Depth Engineering from Persistent Luminescence Phosphors Mg2-xZnxSnO4 for Dynamic Optical Information Encryption Application.

Traditional information encryption materials that rely on fluorescent/phosphorescent molecules are facing an increasing risk of counterfeiting or tampering due to their static reading mode and advances in counterfeiting technology. In this study, a series of Mg2-xZnxSnO4 (x = 0.55, 0.6, 0.65, 0.7 0.75, 0.8) that realizes the writing, reading, and erasing of dynamic information is developed. When heated to 90 °C, the materials exhibit a variety of dynamic emission changes with the concentration of Zn2+ ions. As the doping concentration increased, the ratio of the shallow trap to deep trap changed from 7.77 to 20.86. When x = 0.55, the proportion of deep traps is relatively large, resulting in a higher temperature and longer time required to read the information. When x = 0.80, the proportion of shallow traps is larger and the encrypted information is easier to read. Based on the above features, encryption binary codes device was designed, displaying dynamic writing, reading, and erasing of information under daylight and heating conditions. Accordingly, this work provides reliable guidance on advanced dynamic information encryption.

HnRNPAB promotes pancreatic ductal adenocarcinoma extravasation and liver metastasis by stablizing MYC mRNA.

Heterogeneous nuclear ribonucleoprotein AB (hnRNPAB) is considered a cancer-promoting heterogeneous nuclear ribonucleoprotein in many cancers, but its function in pancreatic ductal adenocarcinoma (PDAC) is poorly understood. HnRNPAB was highly expressed in PDAC tissues compared to normal pancreatic tissues, and high expression of hnRNPAB was associated with poor overall survival and recurrence-free survival in PDAC patients. HnRNPAB promotes migration and invasion of PDAC cells in vitro. In xenograft tumor mouse models, hnRNPAB deprivation significantly attenuated liver metastasis. HnRNPAB mRNA and protein levels are positively associated with MYC in PDAC cells. Mechanistically, hnRNPAB bound to MYC mRNA and prolonged its half-life of MYC mRNA. HnRNPAB induced PDAC cells to secret CXCL8 via MYC, which promoted neutrophils recruitment and facilitated tumor cells entrancing into the hepatic parenchyma. These findings point to a novel regulatory mechanism via which hnRNPAB promotes PDAC metastasis. Implications: Hnrnpab participates in the post-transcriptional regulation of the oncogene MYC by binding and stabilizing MYC mRNA, thereby promoting liver metastasis in PDAC.

Emergence of cooperation under punishment: A reinforcement learning perspective.

Punishment is a common tactic to sustain cooperation and has been extensively studied for a long time. While most of previous game-theoretic work adopt the imitation learning framework where players imitate the strategies of those who are better off, the learning logic in the real world is often much more complex. In this work, we turn to the reinforcement learning paradigm, where individuals make their decisions based upon their experience and long-term returns. Specifically, we investigate the prisoners' dilemma game with a Q-learning algorithm, and cooperators probabilistically pose punishment on defectors in their neighborhood. Unexpectedly, we find that punishment could lead to either continuous or discontinuous cooperation phase transitions, and the nucleation process of cooperation clusters is reminiscent of the liquid-gas transition. The analysis of a Q-table reveals the evolution of the underlying "psychologic" changes, which explains the nucleation process and different levels of cooperation. The uncovered first-order phase transition indicates that great care needs to be taken when implementing the punishment compared to the continuous scenario.

Enhanced Thermally Activated Delayed Fluorescence by Sole Coordination: From an Organic Molecule to Its Zinc Complex.

A BPAPTPyC organic molecule containing a sandwich structural chromophore is designed and synthesized to produce blue thermally activated delayed fluorescence (TADF). The chromophore is composed of two di(4-tert-butylphenyl)amino donors and one inserted terpyridyl acceptor hitched at positions 1, 8, and 9 of a single carbazole via the p-phenylene group, in which the multiple space π-π interactions between the donor and acceptor enable the molecule to possess the TADF feature with a high energy emission at 470 nm but a low photoluminescence quantum yield (PLQY) and a small proportion of the delayed component. In contrast, the corresponding Zn(BPAPTPyC)Cl2 complex has a high PLQY and a short lifetime with a red-shifted emission due to the enhanced rigidity and electron accepting ability of the terpyridyl group from coordination. A solution-processed organic light-emitting diode (OLED) based on the complex achieves a maximum external quantum efficiency (EQE) of 17.9% with an emission peak at 585 nm, while an OLED of the organic molecule produces blue emission with a maximum EQE of 2.7%.

Vaccarin alleviates septic cardiomyopathy by potentiating NLRP3 palmitoylation and inactivation.

BACKGROUND: Sepsis often leads to significant morbidity and mortality due to severe myocardial injury. As is known, the activation of NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome crucially contributes to septic cardiomyopathy (SCM) by facilitating the secretion of interleukin (IL)-1ß and IL-18. The removal of palmitoyl groups from NLRP3 is a crucial step in the activation of the NLRP3 inflammasome. Thus, the potential inhibitors that regulate the palmitoylation and inactivation of NLRP3 may significantly diminish sepsis-induced cardiac dysfunction. PURPOSE: The present study sought to explore the effects of the prospective flavonoid compounds targeting NLRP3 on SCM and to elucidate the associated underlying mechanisms. STUDY DESIGN: The palmitoylation and activation of NLRP3 were detected in H9c2 cells and C57BL/6 J mice. METHODS/RESULTS: Echocardiography, histological staining, western blotting, co-immunoprecipitation, qPCR, ELISA and network pharmacology were used to assess the impact of vaccarin (VAC) on SCM in mice subjected to lipopolysaccharide (LPS) injection. From the collection of 74 compounds, we identified that VAC had the strongest capability to suppress NLRP3 luciferase report gene activity in cardiomyocytes, and the anti-inflammatory characteristics of VAC were further ascertained by the network pharmacology. Exposure of LPS triggered apoptosis, inflammation, oxidative stress, mitochondrial disorder in cardiomyocytes. The detrimental alterations were significantly reversed upon VAC treatment in both septic mice and H9c2 cells exposed to LPS. In vivo experiments demonstrated that VAC treatment alleviated septic myocardial injury, indicated by enhanced cardiac function parameters, preserved cardiac structure, and reduced inflammation/oxidative response. Mechanistically, VAC induced NLRP3 palmitoylation to inactivate NLRP3 inflammasome by acting on zDHHC12. In support, the NLRP3 agonist ATP and the acylation inhibitor 2-bromopalmitate (2-BP) prevented the effects of VAC. CONCLUSION: Our findings suggest that VAC holds promise in protecting against SCM by mitigating cardiac oxidative stress and inflammation via priming NLRP3 palmitoylation and inactivation. These results lay the solid basis for further assessment of the therapeutic potential of VAC against SCM.

Deep learning driven diagnosis of malignant soft tissue tumors based on dual-modal ultrasound images and clinical indexes.

Background: Soft tissue tumors (STTs) are benign or malignant superficial neoplasms arising from soft tissues throughout the body with versatile pathological types. Although Ultrasonography (US) is one of the most common imaging tools to diagnose malignant STTs, it still has several drawbacks in STT diagnosis that need improving. Objectives: The study aims to establish this deep learning (DL) driven Artificial intelligence (AI) system for predicting malignant STTs based on US images and clinical indexes of the patients. Methods: We retrospectively enrolled 271 malignant and 462 benign masses to build the AI system using 5-fold validation. A prospective dataset of 44 malignant masses and 101 benign masses was used to validate the accuracy of system. A multi-data fusion convolutional neural network, named ultrasound clinical soft tissue tumor net (UC-STTNet), was developed to combine gray scale and color Doppler US images and clinic features for malignant STTs diagnosis. Six radiologists (R1-R6) with three experience levels were invited for reader study. Results: The AI system achieved an area under receiver operating curve (AUC) value of 0.89 in the retrospective dataset. The diagnostic performance of the AI system was higher than that of one of the senior radiologists (AUC of AI vs R2: 0.89 vs. 0.84, p=0.022) and all of the intermediate and junior radiologists (AUC of AI vs R3, R4, R5, R6: 0.89 vs 0.75, 0.81, 0.80, 0.63; p <0.01). The AI system also achieved an AUC of 0.85 in the prospective dataset. With the assistance of the system, the diagnostic performances and inter-observer agreement of the radiologists was improved (AUC of R3, R5, R6: 0.75 to 0.83, 0.80 to 0.85, 0.63 to 0.69; p<0.01). Conclusion: The AI system could be a useful tool in diagnosing malignant STTs, and could also help radiologists improve diagnostic performance.

Blood-based inflammatory protein biomarker panel for the prediction of relapse and severity in patients with neuromyelitis optica spectrum disorder: A prospective cohort study.

BACKGROUND: To date, most existing models for predicting neuromyelitis optica spectrum disorder (NMOSD) are based primarily on clinical characteristics. Blood-based NMOSD severity and prognostic predictive immune- and inflammation-related biomarkers are needed. We aimed to investigate the associations between plasma inflammatory biomarkers and relapse and attack severity in NMOSD. METHODS: This two-step, single-center prospective cohort study included discovery and validation cohorts. We quantified 92 plasma inflammatory proteins by using Olink's proximity extension assay and identified differentially expressed proteins in the relapse group (relapse within 1 year of follow-up) and severe attack group. To define a new molecular prognostic model, we calculated the risk score of each patient based on the key protein signatures and validated the results in the validation cohort. RESULTS: The relapse prediction model, including FGF-23, DNER, GDNF, and SLAMF1, predicted the 1-year relapse risk. The severe attack prediction model, including PD-L1 and MCP-2, predicted the severe clinical attack risk. Both the relapse and severe attack prediction models demonstrated good discriminative ability and high accuracy in the validation cohort. CONCLUSIONS: Our discovered biomarker signature and prediction models may complement current clinical risk stratification approaches. These inflammatory biomarkers could contribute to the discovery of therapeutic interventions and prevent NMOSD progression.

Aggregate-state-dependent photochromism and circularly polarized luminescence of a chiral biquinoline amphiphile.

The photophysical and chiroptical properties of a chiral biquinoline amphiphile were found to be closely related to its aggregate states. Photochromism through photo-induced radical and circularly polarized luminescence were realized in its gel state and thin film state, respectively.

Analysis of High-Risk Factors and Construction of a Nomogram Predictive Model for Deep Venous Thrombosis in Pelvic and Acetabular Fracture Patients Treated Conservatively.

PURPOSE: This study aims to develop a predictive nomogram model to assist physicians in making evidence-based decisions and potentially reduce the incidence of deep venous thrombosis (DVT). METHODS: We conducted a retrospective study, including patients admitted to the hospital from January 2014 to January 2022 with a closed, single pelvic or acetabular fracture. Comprehensive data were collected for each patient, encompassing demographics, injury characteristics, comorbidities, and results from laboratory tests and lower extremity ultrasounds. Potential risk factors were identified by univariate and multivariate logistic regression analyses. The predictive model was constructed and then internally validated. Calibration accuracy was assessed using a calibration slope and the Hosmer-Lemeshow goodness-of-fit test. The discrimination of the nomogram model was evaluated using the C-statistic. RESULTS: Out of 232 individuals who underwent conservative treatment, 57 (24.6%) were classified into the DVT group and 175 (75.4%) into the non-DVT group based on lower extremity ultrasound findings. Predominantly, patients were aged between 41 and 65 in both groups. Body mass index (BMI) comparison showed that 54.29% (95/175) of the non-DVT group fell within the healthy weight range, while 45.61% (26/57) in the DVT group were overweight. Notably, the proportion of obesity in the DVT group was more than double that in the non-DVT group, indicating a higher DVT risk with increasing BMI (P=0.0215). Lower red blood cell (RBC) counts were observed in DVT patients compared to non-DVT ones (P<0.001). A similar pattern emerged for D-dimer, a marker for blood clot formation and dissolution, with significant differences noted (P=0.029). Multivariable analysis identified age, BMI, associated organ injury (AOI), American Society of Anesthesiologists score, hemoglobin (HGB), RBC, and D-dimer as candidate predictors. Significant variables included age (OR, 3.04; 95% CI, 1.76-5.26; P<0.001), BMI (OR, 1.97; 95% CI, 1.22-3.18; P=0.006), AOI (OR, 2.05; 95% CI, 1.07-3.95; P=0.031), and HGB (HR, 0.59; 95% CI, 0.39-0.88; P=0.010). The discrimination was 0.787, with a corrected c-index of 0.753. Calibration plots and the Hosmer-Lemeshow test indicated a good fit (P=0.7729). Decision curve analysis revealed a superior net clinical benefit when the predicted probability threshold ranged from 0.05 to 0.95. CONCLUSIONS: We developed a nomogram predictive model, and it could act as a practical tool in clinical workflows to assist physicians in making favorable medical decisions, which potentially reduces the incidence of DVT in those patients with pelvic and acetabular fractures treated conservatively.

Handedness-Inverted and Stimuli-Responsive Circularly Polarized Luminescent Nano/Micromaterials Through Pathway-Dependent Chiral Supramolecular Polymorphism.

The precise manipulation of supramolecular polymorphs has been widely applied to control the morphologies and functions of self-assemblies, but is rarely utilized for the fabrication of circularly polarized luminescence (CPL) materials with tailored properties. Here, this work reports that an amphiphilic naphthalene-histidine compound (NIHis) readily self-assembled into distinct chiral nanostructures through pathway-dependent supramolecular polymorphism, which shows opposite and multistimuli responsive CPL signals. Specifically, NIHis display assembly-induced CPL from the polymorphic keto tautomer, which become predominant during enol-keto tautomerization shifting controlled by a bulk solvent effect. Interestingly, chiral polymorphs of nanofiber and microbelt with inverted CPL signals can be prepared from the same NIHis monomer in exactly the same solvent compositions and concentrations by only changing the temperature. The tunable CPL performance of the solid microbelts is realized under multi external physical or chemical stimuli including grinding, acid fuming, and heating. In particular, an emission color and CPL on-off switch based on the microbelt polymorph by reversible heating-cooling protocol is developed. This work brings a new approach for developing smart CPL materials via supramolecular polymorphism engineering.

Alginate oligosaccharide assimilation by gut microorganisms and the potential role in gut inflammation alleviation.

Dietary fiber metabolism by gut microorganisms plays important roles in host physiology and health. Alginate, the major dietary fiber of daily diet seaweeds, is drawing more attention because of multiple biological activities. To advance the understanding of alginate assimilation mechanism in the gut, we show the presence of unsaturated alginate oligosaccharides (uAOS)-specific alginate utilization loci (AUL) in human gut microbiome. As a representative example, a working model of the AUL from the gut microorganism Bacteroides clarus was reconstructed from biochemistry and transcriptome data. The fermentation of resulting monosaccharides through Entner-Doudoroff pathway tunes the metabolism of short-chain fatty acids and amino acids. Furthermore, we show that uAOS feeding protects the mice against dextran sulfate sodium-induced acute colitis probably by remodeling gut microbiota and metabolome. IMPORTANCE: Alginate has been included in traditional Chinese medicine and daily diet for centuries. Recently discovered biological activities suggested that alginate-derived alginate oligosaccharides (AOS) might be an active ingredient in traditional Chinese medicine, but how these AOS are metabolized in the gut and how it affects health need more information. The study on the working mechanism of alginate utilization loci (AUL) by the gut microorganism uncovers the role of unsaturated alginate oligosaccharides (uAOS) assimilation in tuning short-chain fatty acids and amino acids metabolism and demonstrates that uAOS metabolism by gut microorganisms results in a variation of cell metabolites, which potentially contributes to the physiology and health of gut.

Expression landscape of cancer-FOXP3 and its prognostic value in pancreatic adenocarcinoma.

FOXP3, a key identifier of Treg, has also been identified in tumor cells, which is referred to as cancer-FOXP3 (c-FOXP3). Human c-FOXP3 undergoes multiple alternative splicing events, generating several isoforms, like c-FOXP3FL and c-FOXP3Δ3. Previous research on c-FOXP3 often ignore its cellular source (immune or tumor cells) and isoform expression patterns, which may obscure our understanding of its clinical significance. Our immunohistochemistry investigations which conducted across 18 tumors using validated c-FOXP3 antibodies revealed distinct expression landscapes for c-FOXP3 and its variants, with the majority of tumors exhibited a predominantly expression of c-FOXP3Δ3. In pancreatic ductal adenocarcinoma (PDAC), we further discovered a potential link between nuclear c-FOXP3Δ3 in tumor cells and poor prognosis. Overexpression of c-FOXP3Δ3 in tumor cells was associated with metastasis. This work elucidates the expression pattern of c-FOXP3 in pan-cancer and indicates its potential as a prognostic biomarker in clinical settings, offering new perspectives for its clinical application.

Detection and treatment of mono and polycyclic aromatic hydrocarbon pollutants in aqueous environments based on electrochemical technology: recent advances.

Mono and polycyclic aromatic hydrocarbons are widely distributed and severely pollute the aqueous environment due to natural and human activities, particularly human activity. It is crucial to identify and address them in order to reduce the dangers and threats they pose to biological processes and ecosystems. In the fields of sensor detection and water treatment, electrochemistry plays a crucial role as a trustworthy and environmentally friendly technology. In order to accomplish trace detection while enhancing detection accuracy and precision, researchers have created and studied sensors using a range of materials based on electrochemical processes, and their results have demonstrated good performance. One cannot overlook the challenges associated with treating aromatic pollutants, including mono and polycyclic. Much work has been done and good progress has been achieved in order to address these challenges. This study discusses the mono and polycyclic aromatic hydrocarbon sensor detection and electrochemical treatment technologies for contaminants in the aqueous environment. Additionally mentioned are the sources, distribution, risks, hazards, and problems in the removal of pollutants. The obstacles to be overcome and the future development plans of the field are then suggested by summarizing and assessing the research findings of the researchers.

Effectiveness and safety of glucagon-like peptide 1 receptor agonists in patients with type 2 diabetes: evidence from a retrospective real-world study.

Introduction: Global phase III clinical trials have shown superior hypoglycemic efficacy to insulin and other oral hypoglycemic agents. However, there is a scarcity of real-world data comparing different glucagon-like peptide 1 receptor agonist (GLP-1RA) directly. This study aimed to assess the safety and effectiveness of various GLP-1RA in treating type 2 diabetes mellitus (T2DM) in a real-world clinical setting and identify predictive factors for favorable treatment outcomes. Methods: This was a retrospective, single-center, real-world study. The changes in HbA1c, fasting plasma glucose (FPG), body weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), and the percentage of participants who achieved HbA1c of <7%, 7%-8%, and ≥ 8% after GLP-1RA treatment was analyzed. The clinical factors that affect the effectiveness of GLP-1RA were analyzed. Results: At baseline, the 249 participants had a mean baseline HbA1c of 8.7 ± 1.1%. After at least three months of follow-up, the change in HbA1c was -0.89 ± 1.3% from baseline. Dulaglutide exerted a more significant hypoglycemic effect than immediate-release exenatide. The percentage of participants who achieved HbA1c<7% was substantial, from 6.0% at baseline to 28.9%. Average body weight decreased by 2.02 ± 3.8 kg compared to baseline. After GLP-1RA treatment, the reduction in SBP was 2.4 ± 7.1 mmHg from baseline. A shorter duration of diabetes and a higher baseline HbA1c level were more likely to achieve a good response in blood glucose reduction. Conclusions: This study provided real-world evidence showing that GLP-1RA significantly improved HbA1c, body weight, and SBP. The results can inform the decision-making about GLP-1RA treatment in daily clinical practice.

High Resolution Multi-delay Arterial Spin Labeling with Transformer based Denoising for Pediatric Perfusion MRI.

Multi-delay arterial spin labeling (MDASL) can quantitatively measure cerebral blood flow (CBF) and arterial transit time (ATT), which is particularly suitable for pediatric perfusion imaging. Here we present a high resolution (iso-2mm) MDASL protocol and performed test-retest scans on 21 typically developing children aged 8 to 17 years. We further proposed a Transformer-based deep learning (DL) model with k-space weighted image average (KWIA) denoised images as reference for training the model. The performance of the model was evaluated by the SNR of perfusion images, as well as the SNR, bias and repeatability of the fitted CBF and ATT maps. The proposed method was compared to several benchmark methods including KWIA, joint denoising and reconstruction with total generalized variation (TGV) regularization, as well as directly applying a pretrained Transformer model on a larger dataset. The results show that the proposed Transformer model with KWIA reference can effectively denoise multi-delay ASL images, not only improving the SNR for perfusion images of each delay, but also improving the SNR for the fitted CBF and ATT maps. The proposed method also improved test-retest repeatability of whole-brain perfusion measurements. This may facilitate the use of MDASL in neurodevelopmental studies to characterize typical and aberrant brain development.

Gradient-Based Instance-Specific Visual Explanations for Object Specification and Object Discrimination.

We propose the gradient-weighted Object Detector Activation Maps (ODAM), a visual explanation technique for interpreting the predictions of object detectors. Utilizing the gradients of detector targets flowing into the intermediate feature maps, ODAM produces heat maps that show the influence of regions on the detector's decision for each predicted attribute. Compared to previous works on classification activation maps (CAM), ODAM generates instance-specific explanations rather than class-specific ones. We show that ODAM is applicable to one-stage, two-stage, and transformer-based detectors with different types of detector backbones and heads, and produces higher-quality visual explanations than the state-of-the-art in terms of both effectiveness and efficiency. We discuss two explanation tasks for object detection: 1) object specification: what is the important region for the prediction? 2) object discrimination: which object is detected? Aiming at these two aspects, we present a detailed analysis of the visual explanations of detectors and carry out extensive experiments to validate the effectiveness of the proposed ODAM. Furthermore, we investigate user trust on the explanation maps, how well the visual explanations of object detectors agrees with human explanations, as measured through human eye gaze, and whether this agreement is related with user trust. Finally, we also propose two applications, ODAM-KD and ODAM-NMS, based on these two abilities of ODAM. ODAM-KD utilizes the object specification of ODAM to generate top-down attention for key predictions and instruct the knowledge distillation of object detection. ODAM-NMS considers the location of the model's explanation for each prediction to distinguish the duplicate detected objects. A training scheme, ODAM-Train, is proposed to improve the quality on object discrimination, and help with ODAM-NMS. The code of ODAM is available: https://github.com/Cyang-Zhao/ODAM.

The changes of intestinal flora and its relevance with memory Tfh and B cells in rheumatoid arthritis patients treated with csDMARDs and csDMARDs + bDMARDs.

BACKGROUND: A growing body of experimental and clinical evidence has implicated gut microbiota in the onset and course of rheumatoid arthritis (RA). The imbalance of intestinal flora in RA patients may lead to abnormal expression of immune cells and related cytokines. PURPOSE: Conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) and conventional synthetic disease-modifying antirheumatic drugs combined with biological disease-modifying antirheumatic drugs (csDMARDs + bDMARDs) are widely used to treat RA, but the characteristics of gut microbiota before and after treatment and their relationship with memory Tfh/B cells and cytokines remain unclear. METHODS: Stool samples were collected from 50 RA patients and 25 healthy controls (HCs) for 16SrRNA gene sequencing. We examined the proportion of lymphocyte subsets in healthy controls and RA patients. Enzyme linked immunosorbent assay (ELISA) was used to detect the levels of related cytokines in serum. The α and ß diversity of intestinal flora, and the correlation between intestinal flora and clinical indicators, lymphocyte subsets, cytokines were analyzed. RESULT: At the genus level, Ruminococcaceae_Ruminococcus was decreased in the csDMARDs and csDMARDs + bDMARDs treatment group, whereas Faecalibacterium was reduced in the csDMARDs treatment group, compared to untreated group. CD4+CD45RO+CCR7+CXCR5+central memory Tfh cells and CD4+CD45RO+CCR7-CXCR5+effector memory Tfh cells were significantly lower in the csDMARDs + bDMARDs treatment group than in untreated group. CD19+CD27+IgD+pre-switched memory B cells were higher in the csDMARDs and csDMARDs + bDMARDs treatment groups, whereas CD19+CD27+IgD-switched memory B cells were significantly lower than in untreated group. Ruminococcaceae_Ruminococcus was negatively correlated with CD19+CD27+IgD+ pre-switched memory B cells but positively correlated with CD4+CD45RO+CCR7-CXCR5+effector memory Tfh and CD19+CD27+IgD-switched memory B cells in patients with RA treated with DMARDs. CONCLUSION: The gut microbiota, memory Tfh cells, memory B cells, and cytokines of patients with RA changed significantly under different treatment regimens and had certain correlations with the clinical indicators of RA.