Affinity gaps among B cells in germinal centers drive the selection of MPER precursors.

Current prophylactic human immunodeficiency virus 1 (HIV-1) vaccine research aims to elicit broadly neutralizing antibodies (bnAbs). Membrane-proximal external region (MPER)-targeting bnAbs, such as 10E8, provide exceptionally broad neutralization, but some are autoreactive. Here, we generated humanized B cell antigen receptor knock-in mouse models to test whether a series of germline-targeting immunogens could drive MPER-specific precursors toward bnAbs. We found that recruitment of 10E8 precursors to germinal centers (GCs) required a minimum affinity for germline-targeting immunogens, but the GC residency of MPER precursors was brief due to displacement by higher-affinity endogenous B cell competitors. Higher-affinity germline-targeting immunogens extended the GC residency of MPER precursors, but robust long-term GC residency and maturation were only observed for MPER-HuGL18, an MPER precursor clonotype able to close the affinity gap with endogenous B cell competitors in the GC. Thus, germline-targeting immunogens could induce MPER-targeting antibodies, and B cell residency in the GC may be regulated by a precursor-competitor affinity gap.

Vaccination induces broadly neutralizing antibody precursors to HIV gp41.

A key barrier to the development of vaccines that induce broadly neutralizing antibodies (bnAbs) against human immunodeficiency virus (HIV) and other viruses of high antigenic diversity is the design of priming immunogens that induce rare bnAb-precursor B cells. The high neutralization breadth of the HIV bnAb 10E8 makes elicitation of 10E8-class bnAbs desirable; however, the recessed epitope within gp41 makes envelope trimers poor priming immunogens and requires that 10E8-class bnAbs possess a long heavy chain complementarity determining region 3 (HCDR3) with a specific binding motif. We developed germline-targeting epitope scaffolds with affinity for 10E8-class precursors and engineered nanoparticles for multivalent display. Scaffolds exhibited epitope structural mimicry and bound bnAb-precursor human naive B cells in ex vivo screens, protein nanoparticles induced bnAb-precursor responses in stringent mouse models and rhesus macaques, and mRNA-encoded nanoparticles triggered similar responses in mice. Thus, germline-targeting epitope scaffold nanoparticles can elicit rare bnAb-precursor B cells with predefined binding specificities and HCDR3 features.

Antibodies from primary humoral responses modulate the recruitment of naive B cells during secondary responses.

Vaccines generate high-affinity antibodies by recruiting antigen-specific B cells to germinal centers (GCs), but the mechanisms governing the recruitment to GCs on secondary challenges remain unclear. Here, using preclinical SARS-CoV and HIV mouse models, we demonstrated that the antibodies elicited during primary humoral responses shaped the naive B cell recruitment to GCs during secondary exposures. The antibodies from primary responses could either enhance or, conversely, restrict the GC participation of naive B cells: broad-binding, low-affinity, and low-titer antibodies enhanced recruitment, whereas, by contrast, the high titers of high-affinity, mono-epitope-specific antibodies attenuated cognate naive B cell recruitment. Thus, the directionality and intensity of that effect was determined by antibody concentration, affinity, and epitope specificity. Circulating antibodies can, therefore, be important determinants of antigen immunogenicity. Future vaccines may need to overcome-or could, alternatively, leverage-the effects of circulating primary antibodies on subsequent naive B cell recruitment.

scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics.

Single-cell RNA sequencing has achieved massive success in biological research fields. Discovering novel cell types from single-cell transcriptomics has been demonstrated to be essential in the field of biomedicine, yet is time-consuming and needs prior knowledge. With the unprecedented boom in cell atlases, auto-annotation tools have become more prevalent due to their speed, accuracy and user-friendly features. However, existing tools have mostly focused on general cell-type annotation and have not adequately addressed the challenge of discovering novel rare cell types. In this work, we introduce scNovel, a powerful deep learning-based neural network that specifically focuses on novel rare cell discovery. By testing our model on diverse datasets with different scales, protocols and degrees of imbalance, we demonstrate that scNovel significantly outperforms previous state-of-the-art novel cell detection models, reaching the most AUROC performance(the only one method whose averaged AUROC results are above 94%, up to 16.26% more comparing to the second-best method). We validate scNovel's performance on a million-scale dataset to illustrate the scalability of scNovel further. Applying scNovel on a clinical COVID-19 dataset, three potential novel subtypes of Macrophages are identified, where the COVID-related differential genes are also detected to have consistent expression patterns through deeper analysis. We believe that our proposed pipeline will be an important tool for high-throughput clinical data in a wide range of applications.

Multiplexed CRISPR/CAS9-mediated engineering of pre-clinical mouse models bearing native human B cell receptors.

B-cell receptor (BCR) knock-in (KI) mouse models play an important role in vaccine development and fundamental immunological studies. However, the time required to generate them poses a bottleneck. Here we report a one-step CRISPR/Cas9 KI methodology to combine the insertion of human germline immunoglobulin heavy and light chains at their endogenous loci in mice. We validate this technology with the rapid generation of three BCR KI lines expressing native human precursors, instead of computationally inferred germline sequences, to HIV broadly neutralizing antibodies. We demonstrate that B cells from these mice are fully functional: upon transfer to congenic, wild type mice at controlled frequencies, such B cells can be primed by eOD-GT8 60mer, a germline-targeting immunogen currently in clinical trials, recruited to germinal centers, secrete class-switched antibodies, undergo somatic hypermutation, and differentiate into memory B cells. KI mice expressing functional human BCRs promise to accelerate the development of vaccines for HIV and other infectious diseases.

Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping.

Driven by multi-omics data, some multi-view clustering algorithms have been successfully applied to cancer subtypes prediction, aiming to identify subtypes with biometric differences in the same cancer, thereby improving the clinical prognosis of patients and designing personalized treatment plan. Due to the fact that the number of patients in omics data is much smaller than the number of genes, multi-view spectral clustering based on similarity learning has been widely developed. However, these algorithms still suffer some problems, such as over-reliance on the quality of pre-defined similarity matrices for clustering results, inability to reasonably handle noise and redundant information in high-dimensional omics data, ignoring complementary information between omics data, etc. This paper proposes multi-view spectral clustering with latent representation learning (MSCLRL) method to alleviate the above problems. First, MSCLRL generates a corresponding low-dimensional latent representation for each omics data, which can effectively retain the unique information of each omics and improve the robustness and accuracy of the similarity matrix. Second, the obtained latent representations are assigned appropriate weights by MSCLRL, and global similarity learning is performed to generate an integrated similarity matrix. Third, the integrated similarity matrix is used to feed back and update the low-dimensional representation of each omics. Finally, the final integrated similarity matrix is used for clustering. In 10 benchmark multi-omics datasets and 2 separate cancer case studies, the experiments confirmed that the proposed method obtained statistically and biologically meaningful cancer subtypes.

Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration.

MOTIVATION: We have entered the multi-omics era and can measure cells from different aspects. Hence, we can get a more comprehensive view by integrating or matching data from different spaces corresponding to the same object. However, it is particularly challenging in the single-cell multi-omics scenario because such data are very sparse with extremely high dimensions. Though some techniques can be used to measure scATAC-seq and scRNA-seq simultaneously, the data are usually highly noisy due to the limitations of the experimental environment. RESULTS: To promote single-cell multi-omics research, we overcome the above challenges, proposing a novel framework, contrastive cycle adversarial autoencoders, which can align and integrate single-cell RNA-seq data and single-cell ATAC-seq data. Con-AAE can efficiently map the above data with high sparsity and noise from different spaces to a coordinated subspace, where alignment and integration tasks can be easier. We demonstrate its advantages on several datasets. AVAILABILITY AND IMPLEMENTATION: Zenodo link: https://zenodo.org/badge/latestdoi/368779433. github: https://github.com/kakarotcq/Con-AAE.

Efficacy and safety of mesenchymal stem cells therapy in COVID-19 patients: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a serious public health issue. In COVID-19 patients, the elevated levels of inflammatory cytokines lead to the manifestation of COVID-19 symptoms, such as lung tissue edema, lung diffusion dysfunction, acute respiratory distress syndrome (ARDS), secondary infection, and ultimately mortality. Mesenchymal stem cells (MSCs) exhibit anti-inflammatory and immunomodulatory properties, thus providing a potential treatment option for COVID-19. The number of clinical trials of MSCs for COVID-19 has been rising. However, the treatment protocols and therapeutic effects of MSCs for COVID-19 patients are inconsistent. This meta-analysis was performed to systematically determine the safety and efficacy of MSC infusion in COVID-19 patients. METHODS: We conducted a comprehensive literature search from PubMed/Medline, Web of Science, EMBASE, and Cochrane Library up to 22 November 2023 to screen for eligible randomized controlled trials. Inclusion and exclusion criteria for searched literature were formulated according to the PICOS principle, followed by the use of literature quality assessment tools to assess the risk of bias. Finally, outcome measurements including therapeutic efficacy, clinical symptoms, and adverse events of each study were extracted for statistical analysis. RESULTS: A total of 14 randomized controlled trials were collected. The results of enrolled studies demonstrated that patients with COVID-19 pneumonia who received MSC inoculation showed a decreased mortality compared with counterparts who received conventional treatment (RR: 0.76; 95% CI [0.60, 0.96]; p = 0.02). Reciprocally, MSC inoculation improved the clinical symptoms in patients (RR: 1.28; 95% CI [1.06, 1.55]; p = 0.009). In terms of immune biomarkers, MSC treatment inhibited inflammation responses in COVID-19 patients, as was indicated by the decreased levels of CRP and IL-6. Importantly, our results showed that no significant differences in the incidence of adverse reactions or serious adverse events were monitored in patients after MSC inoculation. CONCLUSION: This meta-analysis demonstrated that MSC inoculation is effective and safe in the treatment of patients with COVID-19 pneumonia. Without increasing the incidence of adverse events or serious adverse events, MSC treatment decreased patient mortality and inflammatory levels and improved the clinical symptoms in COVID-19 patients. However, large-cohort randomized controlled trials with expanded numbers of patients are required to further confirm our results.

Bio-inspired foveal super-resolution method for multi-focal-length images based on local gradient constraints.

Most existing super-resolution (SR) imaging systems, inspired by the bionic compound eye, utilize image registration and reconstruction algorithms to overcome the angular resolution limitations of individual imaging systems. This article introduces a multi-aperture multi-focal-length imaging system and a multi-focal-length image super-resolution algorithm, mimicking the foveal imaging of the human eye. Experimental results demonstrate that with the proposed imaging system and an SR imaging algorithm inspired by the human visual system, the proposed method can enhance the spatial resolution of the foveal region by up to 4 × compared to the original acquired image. These findings validate the effectiveness of the proposed imaging system and computational imaging algorithm in enhancing image texture and spatial resolution.

Joint constraints of guided filtering based confidence and nonlocal sparse tensor for color polarization super-resolution imaging.

This paper introduces a camera-array-based super-resolution color polarization imaging system designed to simultaneously capture color and polarization information of a scene in a single shot. Existing snapshot color polarization imaging has a complex structure and limited generalizability, which are overcome by the proposed system. In addition, a novel reconstruction algorithm is designed to exploit the complementarity and correlation between the twelve channels in acquired color polarization images for simultaneous super-resolution (SR) imaging and denoising. We propose a confidence-guided SR reconstruction algorithm based on guided filtering to enhance the constraint capability of the observed data. Additionally, by introducing adaptive parameters, we effectively balance the data fidelity constraint and the regularization constraint of nonlocal sparse tensor. Simulations were conducted to compare the proposed system with a color polarization camera. The results show that color polarization images generated by the proposed system and algorithm outperform those obtained from the color polarization camera and the state-of-the-art color polarization demosaicking algorithms. Moreover, the proposed algorithm also outperforms state-of-the-art SR algorithms based on deep learning. To evaluate the applicability of the proposed imaging system and reconstruction algorithm in practice, a prototype was constructed for color polarization image acquisition. Compared with conventional acquisition, the proposed solution demonstrates a significant improvement in the reconstructed color polarization images.

Nitroreductase-Responsive Photosensitizers for Selective Imaging and Photo-Inactivation of Intracellular Bacteria.

Intracellular Staphylococcus aureus (S. aureus), especially the methicillin resistant staphylococcus aureus (MRSA), are difficult to detect and eradicate due to the protection by the host cells. Antibacterial photodynamic therapy (aPDT) offers promise in treating intracellular bacteria, provided that selective damage to the bacteria ranther than host cells can be realized. According to the different nitroreductase (NTR) levels in mammalian cells and S. aureus, herein NTR-responsive photosensitizers (PSs) (T)CyI-NO2 were designed and synthesized. The emission and 1O2 generation of (T)CyI-NO2 are quenched by the 4-nitrobenzyl group, but can be specifically switched on by bacterial NTR. Therefore, selective imaging and photo-inactivation of intracellular S. aureus and MRSA were achieved. Our findings may pave the way for the development of more efficient and selective aPDT agents to combat intractable intracellular infections.

CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer.

MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10 554 samples from 33 TCGA projects and 28 633 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.

Recurrent patellar dislocation patients with high-grade J-sign have multiple structural bone abnormalities in the lower limbs.

PURPOSE: To explore the relationship between preoperative J-sign grading and structural bone abnormalities in patients with recurrent patellar dislocation (RPD). METHODS: A retrospective study was conducted on RPD patients over 5 years. Patients were categorised based on J-sign grade into low (J- and J1+), moderate (J2+) and high groups (J3+). Trochlear dysplasia (TD) and osseous structures (femoral anteversion angle [FAA], knee torsion, tibial tuberosity-trochlear groove [TT-TG] distance, Caton-Deschamps index) were assessed and grouped according to risk factor thresholds. The χ2 test was used to compare composition ratio differences of structural bone abnormalities among the groups. RESULTS: A total of 256 patients were included, with 206 (80.5%) females. The distribution of J-sign grade was as follows: 89 knees (34.8%) of low grade, 86 moderate (33.6%) and 81 high (31.6%). Among the five structural bone abnormalities, TD was the most common with a prevalence of 78.5%, followed by increased TT-TG at 47.4%. Excessive tibiofemoral rotation had the lowest occurrence at 28.9%. There were 173 (67.6%) patients who had two or more abnormalities, while 45 (17.6%) had four to five bony abnormalities. Among patients with any bony abnormality, the proportion of high-grade J-sign surpassed 40%. Patients with moderate and high-grade J-sign had more increased FAA and more pronounced patella alta (all p < 0.001). The proportion of excessive knee torsion and TD increased with increasing each J-sign grade, with the more notable tendency in knee torsion (high vs. moderate vs. low-grade: 61% vs. 22% vs 7%, p < 0.001). Furthermore, the higher J-sign grade was also associated with more combined bony abnormalities (p < 0.001). In the high-grade J-sign group, 90.2% of the knees had two or more bony risk factors and 40.7% had four or more, which were significantly higher than the moderate and low-grade J-sign groups (40.7% vs. 11.6% vs. 2.2%, p < 0.001). CONCLUSION: In patients with a high-grade J-sign, over 90% of the lower limbs had two or more structural bone risk factors, and more than 40% had four or more. These proportions were significantly higher compared to knees with low-grade and moderate J-sign. In clinical practice, when treating high-grade patellar mal-tracking, it is important to focus on and correct these strongly correlated abnormal bone structures. LEVEL OF EVIDENCE: Level III.

Metal-Free Cascade Formation of C-C and C-N Bond for the Construction of 3-Cyano-2-Pyridones with Insecticidal Properties.

A straightforward and efficient methodology has been developed for the synthesis of 3-cyano-2-pyridones via the C-C and C-N bond formation processes. A total of 51 diverse 3-cyano-2-pyridone derivatives were obtained in moderate to excellent yields. This reaction featured advantages such as a metal-free process, wide functional group tolerance, simple operation, and mild conditions. A plausible mechanism for the reaction was proposed. 3-cyano-2-pyridones as ricinine analogues for insecticidal properties were evaluated, and the compound 3ci (LC50 = 2.206 mg/mL) showed the best insecticidal property.

Construction and validation of chronic pain prediction model after total knee arthroplasty.

Objective: To explore the risk factors of chronic pain after total knee arthroplasty (TKA) and to establish and verify a prediction model. Methods: As a retrospective observational study, medical records of 239 patients who underwent TKA in Affiliated Hospital of Jiangnan University from January 2020 to December 2022 were reviewed. Fifty four patients suffered from chronic pain after TKA surgery. Univariate and multivariate logistic regression were used to analyze factors associated with the occurrence of chronic pain after TKA. A nomogram prediction model was established based on the identified independent risk factors, and its predictive effectiveness was evaluated. Results: Gender, postoperative 24-hourss numerical rating scale (NRS) and postoperative three months Hospital for Special Surgery Knee-Rating (HSS) scores were independent risk factors for chronic pain after TKA (p<0.05). The area of the receiver operating characteristic (ROC) of the nomogram model based on these factors was 0.904 (95% confidence interval [CI): 0.861-0.947), which indicates a good predictive value for the postoperative chronic pain. When the optimal cut off value was selected, the sensitivity and specificity of the model were 92.6% and 74.1%, respectively, indicating that the predictive model is effective. Conclusions: Gender, postoperative 24-hours NRS and postoperative three months HSS score are independent risk factors for chronic pain after TKA. The nomogram prediction model based on these factors is effective and can provide auxiliary reference for patients with chronic pain after TKA.

Exploration of s new biomarker in osteosarcoma and association with clinical outcomes: TOP2A+ cancer associated fibroblasts.

BACKGROUND: Osteosarcoma (OS) is the leading malignant primary bone tumor in young adults and children and has a high mortality rate. Cancer-associated fibroblasts (CAFs) are major components of the tumor microenvironment, influencing cancer progression and metastasis. However, there is no systematic study on the role of CAF in OS. METHODS: We collected six OS patients' single-cell RNA sequencing data from the TISCH database, which was processed using the Seurat package. We selected gene sets from the well-known MSigDB database and resorted to the clusterprofiler package for gene set enrichment analysis (GSEA). The least absolute shrinkage and selection operator (LASSO) regression model was used for identification of the variables. Receiver operating characteristic and decision curve analyses were utilized for determining the efficacy of the monogram model. RESULTS: TOP2A+ CAFs was recognized as the carcinogenic CAFs subset, given its intense interaction with OS malignant cells and association with the critical cancer driver pathway. We intersected the differentially expressed genes of TOP2A+ CAFs with the prognostic genes selected from 88 OS samples. The acquired gene set was selected using the LASSO regression model and integrated with clinical factors to obtain a monogram model of high prognosis predicting power (area under the curve of 5 year survival at 0.883). Functional enrichment analysis revealed the detailed difference between two risk groups. CONCLUSION: We identified TOP2A+ CAFs as a subset of oncogenic CAFs in OS. Based on differentially expressed genes derived from TOP2A+ CAFs, combined with bulk transcriptome prognostic genes, we constructed a risk model that can efficiently predict OS prognosis. Collectively, our study may provide new insights for future studies to elucidate the role of CAF in OS.

Cancer-related somatic mutations alter adenosine A1 receptor pharmacology-A focus on mutations in the loops and C-terminus.

G protein-coupled receptors (GPCRs) are known to be involved in tumor progression and metastasis. The adenosine A1 receptor (A1 AR) has been detected to be over-expressed in various cancer cell lines. However, the role of A1 AR in tumor development is not yet well characterized. A series of A1 AR mutations were identified in the Cancer Genome Atlas from cancer patient samples. In this study, we have investigated the pharmacology of mutations located outside of the 7-transmembrane domain by using a "single-GPCR-one-G protein" yeast system. Concentration-growth curves were obtained with the full agonist CPA for 12 mutant receptors and compared to the wild-type hA1 AR. Most mutations located at the extracellular loops (EL) reduced the levels of constitutive activity of the receptor and agonist potency. For mutants at the intracellular loops (ILs) of the receptor, an increased constitutive activity was found for mutant receptor L211R5.69 , while a decreased constitutive activity and agonist response were found for mutant receptor L113F34.51 . Lastly, mutations identified on the C-terminus did not significantly influence the pharmacological function of the receptor. A selection of mutations was also investigated in a mammalian system. Overall, similar effects on receptor activation compared to the yeast system were found with mutations located at the EL, but some contradictory effects were observed for mutations located at the IL. Taken together, this study will enrich the insight of A1 AR structure and function, enlightening the consequences of these mutations in cancer. Ultimately, this may provide potential precision medicine in cancer treatment.

Case of concurrence of bullous pemphigoid and Norwegian scabies.

Bullous pemphigoid (BP) with scabies is a condition rarely encountered in clinical practice, and when it is encountered, it is often due to the use of immunosuppressants. This paper is a report on a patient with BP and scabies, who developed scabs after taking dexamethasone. It should be noted that BP antibody is necessary, which can distinguish BP with scabies and bullous scabies, and the treatment options for the two diseases are different.

Morbidity and mortality of newborns born to immigrant and nonimmigrant females residing in low-income neighbourhoods.

BACKGROUND: Living in low-income neighbourhoods and being an immigrant are each independently associated with adverse neonatal outcomes, but it is unknown if disparities exist in the neonatal period for children of immigrant and nonimmigrant females living in low-income areas. We sought to compare the risk of severe neonatal morbidity and mortality (SNMM) between newborns of immigrant and nonimmigrant mothers who resided in low-income neighbourhoods. METHODS: This population-based cohort study used administrative data for females residing in low-income urban neighbourhoods in Ontario, who had an in-hospital, singleton live birth at 20-42 weeks' gestation, from 2002 to 2019. We defined immigrant status as nonrefugee immigrant or nonimmigrant, further detailed by country of birth and duration of residence in Ontario. The primary outcome was a SNMM composite (with 16 diagnoses, including neonatal death and 7 neonatal procedures as indicators), arising within 0-27 days after birth. We estimated relative risks (RRs) and 95% confidence intervals (CIs) using modified Poisson regression with generalized estimating equations. RESULTS: Our cohort included 148 050 and 266 191 live births among immigrant and nonimmigrant mothers, respectively. Compared with newborns of non-immigrant females, SNMM was less frequent among newborns of immigrant females (49.7 v. 65.6 per 1000 live births), with an adjusted RR of 0.76 (95% CI 0.74 to 0.79). The most frequent SNMM indicator was receipt of ventilatory support. Relative to neonates of nonimmigrant females, the risk of SNMM was highest among those of immigrants from Jamaica (adjusted RR 1.14, 95% CI 1.05 to 1.23) and Ghana (adjusted RR 1.20, 95% CI 1.05 to 1.38), and lowest among those of immigrants from China (adjusted RR 0.44, 95% CI 0.40 to 0.48). Among immigrants, the risk of SNMM declined with shorter duration of residence before the index birth. INTERPRETATION: Within low-income urban areas, newborns of immigrant females had an overall lower risk of SNMM than those of nonimmigrant females, with considerable variation by maternal birthplace and duration of residence. Initiatives should focus on improving preconception health and perinatal care within subgroups of females residing in low-income neighbourhoods.