iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets. This method adeptly addresses challenges related to cross-dataset modeling by capitalizing on high-dimensional redundant genomic features, analogous to reinforcing building pillars with redundant steel rods. Moreover, it integrates adaptive penalization of feature redundancy on a per-sample basis to prevent score flattening and mitigate overfitting. We then developed a purpose-built R package to implement this method for modeling clinical trial datasets. When applied to genomic datasets for HER2 targeted therapies, iGenSig-Rx model demonstrates consistent and reliable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We anticipate that iGenSig-Rx, as an interpretable class of multi-omics modeling methods, will find broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx .

IndepthPathway: an integrated tool for in-depth pathway enrichment analysis based on single-cell sequencing data.

MOTIVATION: Single-cell sequencing enables exploring the pathways and processes of cells, and cell populations. However, there is a paucity of pathway enrichment methods designed to tolerate the high noise and low gene coverage of this technology. When gene expression data are noisy and signals are sparse, testing pathway enrichment based on the genes expression may not yield statistically significant results, which is particularly problematic when detecting the pathways enriched in less abundant cells that are vulnerable to disturbances. RESULTS: In this project, we developed a Weighted Concept Signature Enrichment Analysis specialized for pathway enrichment analysis from single-cell transcriptomics (scRNA-seq). Weighted Concept Signature Enrichment Analysis took a broader approach for assessing the functional relations of pathway gene sets to differentially expressed genes, and leverage the cumulative signature of molecular concepts characteristic of the highly differentially expressed genes, which we termed as the universal concept signature, to tolerate the high noise and low coverage of this technology. We then incorporated Weighted Concept Signature Enrichment Analysis into an R package called "IndepthPathway" for biologists to broadly leverage this method for pathway analysis based on bulk and single-cell sequencing data. Through simulating technical variability and dropouts in gene expression characteristic of scRNA-seq as well as benchmarking on a real dataset of matched single-cell and bulk RNAseq data, we demonstrate that IndepthPathway presents outstanding stability and depth in pathway enrichment results under stochasticity of the data, thus will substantially improve the scientific rigor of the pathway analysis for single-cell sequencing data. AVAILABILITY AND IMPLEMENTATION: The IndepthPathway R package is available through: https://github.com/wangxlab/IndepthPathway.

Breakthrough COVID-19 After Tixagevimab/Cilgavimab Among Patients With Systemic Autoimmune Rheumatic Diseases.

OBJECTIVE: To determine the incidence and baseline factors associated with breakthrough coronavirus disease 2019 (COVID-19) after preexposure prophylaxis (PrEP) with tixagevimab/cilgavimab among patients with systemic autoimmune rheumatic diseases (SARDs). METHODS: We performed a retrospective cohort study among patients with SARDs who received tixagevimab/cilgavimab between January 2, 2022, and November 16, 2022. The primary outcome was breakthrough COVID-19 after tixagevimab/cilgavimab. We performed multivariable Cox regression models adjusted for baseline factors to identify risk factors for breakthrough COVID-19. RESULTS: We identified 444 patients with SARDs who received tixagevimab/cilgavimab (mean age 62.0 years, 78.2% female). There were 83 (18.7%) breakthrough COVID-19 cases (incidence rate 31.5/1000 person-months, 95% CI 24.70-38.24), 7 (1.6%) hospitalizations, and 1 (0.2%) death. Older age was inversely associated with breakthrough COVID-19 (adjusted hazard ratio [aHR] 0.86/10 years, 95% CI 0.75-0.99). Higher baseline spike antibody levels were associated with lower risk of breakthrough COVID-19 (aHR 0.42, 95% CI 0.18-0.99 for spike antibody levels > 200 vs < 0.4 units). CD20 inhibitor users had a similar risk of breakthrough COVID-19 (aHR 1.05, 95% CI 0.44-2.49) compared to conventional synthetic disease-modifying antirheumatic drug (DMARD) users. CONCLUSION: We found that patients with SARDs had frequent breakthrough COVID-19, but the proportion experiencing severe COVID-19 was low. DMARD type, including CD20 inhibitors, did not significantly affect risk of breakthrough COVID-19. Evidence of prior humoral immunity was protective against breakthrough infection, highlighting the continued need for a multimodal approach to prevent severe COVID-19 as novel PrEP therapies are being developed.

Factors Associated With an Electronic Health Record-Based Definition of Postacute Sequelae of COVID-19 in Patients With Systemic Autoimmune Rheumatic Disease.

OBJECTIVE: Many individuals with rheumatic disease are at higher risk for severe acute coronavirus disease 2019 (COVID-19). We aimed to evaluate risk factors for postacute sequelae of COVID-19 (PASC) using an electronic health record (EHR)-based definition. METHODS: We identified patients with prevalent rheumatic diseases and COVID-19 within the Mass General Brigham healthcare system. PASC was defined by the International Classification of Diseases, 10th revision (ICD-10) codes, relevant labs, vital signs, and medications at least 30 days following the first COVID-19 infection. Patients were followed until the earliest of incident PASC, repeat COVID-19 infection, 1 year of follow-up, death, or February 19, 2023. We used multivariable Cox regression to estimate the association of baseline characteristics with PASC risk. RESULTS: Among 2459 patients (76.37% female, mean age 57.4 years), the most common incident PASC manifestations were cough (14.56%), dyspnea (12.36%), constipation (11.39%), and fatigue (10.70%). Serious manifestations including acute coronary disease (4.43%), thromboembolism (3.09%), hypoxemia (3.09%), stroke (1.75%), and myocarditis (0.12%) were rare. The Delta wave (adjusted hazard ratio [aHR] 0.63, 95% CI 0.49-0.82) and Omicron era (aHR 0.50, 95% CI 0.41-0.62) were associated with lower risk of PASC than the early pandemic period (March 2020-June 2021). Age, obesity, comorbidity burden, race, and hospitalization for acute COVID-19 infection were associated with greater risk of PASC. Glucocorticoid (GC) use (aHR 1.19, 95% CI 1.05-1.34 compared to no use) was associated with greater risk of PASC. CONCLUSION: Among patients with rheumatic diseases, following their first COVID-19 infection, we found a decreased risk of PASC over calendar time using an EHR-based definition. Aside from GCs, no specific immunomodulatory medications were associated with increased risk, and risk factors were otherwise similar to those seen in the general population.

Pharmacokinetics of polymyxin B in different populations: a systematic review.

BACKGROUND AND OBJECTIVES: Despite being clinically utilized for the treatment of infections, the limited therapeutic range of polymyxin B (PMB), along with considerable interpatient variability in its pharmacokinetics and frequent occurrence of acute kidney injury, has significantly hindered its widespread utilization. Recent research on the population pharmacokinetics of PMB has provided valuable insights. This study aims to review relevant literature to establish a theoretical foundation for individualized clinical management. METHODS: Follow PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, Pop-PK studies of PMB were searched in PubMed and EMBASE database systems from the inception of the database until March 2023. RESULT: To date, a total of 22 population-based studies have been conducted, encompassing 756 subjects across six different countries. The recruited population in these studies consisted of critically infected individuals with multidrug-resistant bacteria, patients with varying renal functions, those with cystic fibrosis, kidney or lung transplant recipients, patients undergoing extracorporeal membrane oxygenation (ECMO) or continuous renal replacement therapy (CRRT), as well as individuals with obesity or pediatric populations. Among these studies, seven employed a one-compartmental model, with the range of typical clearance (CL) and volume (Vc) being 1.18-2.5L /h and 12.09-47.2 L, respectively. Fifteen studies employed a two-compartmental model, with the ranges of the clearance (CL) and volume of the central compartment (Vc), the volume of the peripheral compartment (Vp), and the intercompartment clearance (Q) were 1.27-8.65 L/h, 5.47-38.6 L, 4.52-174.69 L, and 1.34-24.3 L/h, respectively. Primary covariates identified in these studies included creatinine clearance and body weight, while other covariates considered were CRRT, albumin, age, and SOFA scores. Internal evaluation was conducted in 19 studies, with only one study being externally validated using an independent external dataset. CONCLUSION: We conclude that small sample sizes, lack of multicentre collaboration, and patient homogeneity are the primary reasons for the discrepancies in the results of the current studies. In addition, most of the studies limited in the internal evaluation, which confined the implementation of model-informed precision dosing strategies.

AHNAK2 Regulates NF-κB/MMP-9 Signaling to Promote Pancreatic Cancer Progression.

Early metastasis of pancreatic cancer (PaC) is a major cause of its high mortality rate. Previous studies have shown that AHNAK2 is involved in the progression of some tumors and is predicted to be an independent prognostic factor for PaC; however, the specific mechanisms through which AHNAK2 regulates PaC remain unclear. In this study, we examined the role of AHNAK2 in PaC and its potential molecular mechanisms. AHNAK2 mRNA and protein expression in PaC tissues and cells were measured using qRT-PCR and western blot analysis. After AHNAK2 knockdown using small interfering RNA, PaC cells were subjected to CCK-8 scratch, and Transwell assays to assess cell proliferation, migration, and invasion, respectively. Furthermore, the validation of the mechanistic pathway was achieved by western blot analysis. AHNAK2 mRNA and protein levels were up-regulated in PaC and silencing AHNAK2 significantly inhibited the proliferation, migration, and invasion of PaC cells. Mechanistically, AHNAK2 knockdown decreased the expression of phosphorylated p65, phosphorylated IκBα, and matrix metalloproteinase-9 (MMP-9), suggesting that activation of the NF-κB/MMP-9 signaling pathway was inhibited. Importantly, activation of NF-κB reversed the effects of AHNAK2 knockdown. Our findings indicate that AHNAK2 promotes PaC progression through the NF-kB/MMP-9 pathway and provides a theoretical basis for targeting AHNAK2 for the treatment of PaC.

Highly Efficient Nitrogen Reduction to Ammonia through the Cooperation of Plasma and Porous Metal-Organic Framework Reactors with Confined Water.

While the ambient N2 reduction to ammonia (NH3) using H2O as hydrogen source (2N2+6H2O=4NH3+3O2) is known as a promising alternative to the Haber-Bosch process, the high bond energy of N≡N bond leads to the extremely low NH3 yield. Herein, we report a highly efficient catalytic system for ammonia synthesis using the low-temperature dielectric barrier discharge plasma to activate inert N2 molecules into the activated nitrogen species, which can efficiently react with the confined and concentrated H2O molecules in porous metal-organic framework (MOF) reactors with V3+, Cr3+, Mn3+, Fe3+, Co2+, Ni2+ and Cu2+ ions. Specially, the Fe-based catalyst MIL-100(Fe) causes a superhigh NH3 yield of 22.4 mmol g-1 h-1. The investigation of catalytic performance and systematic characterizations of MIL-100(Fe) during the plasma-driven catalytic reaction unveils that the in situ generated defective Fe-O clusters are the highly active sites and NH3 molecules indeed form inside the MIL-100(Fe) reactor. The theoretical calculation reveals that the porous MOF catalysts have different adsorption capacity for nitrogen species on different catalytic metal sites, where the optimal MIL-100(Fe) has the lowest energy barrier for the rate-limiting *NNH formation step, significantly enhancing efficiency of nitrogen fixation.

Regulated Dual Defects of Bridging Organic and Terminal Inorganic Ligands in Iron-based Metal-Organic Framework Nodes for Efficient Photocatalytic Ammonia Synthesis.

Engineering advantageous defects to construct well-defined active sites in catalysts is promising but challenging to achieve efficient photocatalytic NH3 synthesis from N2 and H2O due to the chemical inertness of N2 molecule. Here, we report defective Fe-based metal-organic framework (MOF) photocatalysts via a non-thermal plasma-assisted synthesis strategy, where their NH3 production capability is synergistically regulated by two types of defects, namely, bridging organic ligands and terminal inorganic ligands (OH- and H2O). Specially, the optimized MIL-100(Fe) catalysts, where there are only terminal inorganic ligand defects and coexistence of dual defects, exhibit the respective 1.7- and 7.7-fold activity enhancement comparable to the pristine catalyst under visible light irradiation. As revealed by experimental and theoretical calculation results, the dual defects in the catalyst induce the formation of abundant and highly accessible coordinatively unsaturated Fe active sites and synergistically optimize their geometric and electronic structures, which favors the injection of more d-orbital electrons in Fe sites into the N2 π* antibonding orbital to achieve N2 activation and the formation of a key intermediate *NNH in the reaction. This work provides a guidance on the rational design and accurate construction of porous catalysts with precise defective structures for high-performance activation of catalytic molecules.

Impact of vaccination on postacute sequelae of SARS CoV-2 infection in patients with rheumatic diseases.

OBJECTIVE: Vaccination decreases the risk of severe COVID-19 but its impact on postacute sequelae of COVID-19 (PASC) is unclear among patients with systemic autoimmune rheumatic diseases (SARDs) who may have blunted vaccine immunogenicity and be vulnerable to PASC. METHODS: We prospectively enrolled patients with SARD from a large healthcare system who survived acute infection to complete surveys. The symptom-free duration and the odds of PASC (any symptom lasting ≥28 or 90 days) were evaluated using restricted mean survival time and multivariable logistic regression, respectively, among those with and without breakthrough infection (≥14 days after initial vaccine series). RESULTS: Among 280 patients (11% unvaccinated; 48% partially vaccinated; 41% fully vaccinated), the mean age was 53 years, 80% were female and 82% were white. The most common SARDs were inflammatory arthritis (59%) and connective tissue disease (24%). Those with breakthrough infection had more upper respiratory symptoms, and those with non-breakthrough infection had more anosmia, dysgeusia and joint pain. Compared with those with non-breakthrough COVID-19 infection (n=164), those with breakthrough infection (n=116) had significantly more symptom-free days over the follow-up period (+21.4 days, 95% CI 0.95 to 41.91; p=0.04) and lower odds of PASC at 28 and 90 days (adjusted OR, aOR 0.49, 95% CI 0.29 to 0.83 and aOR 0.10, 95% CI 0.04 to 0.22, respectively). CONCLUSION: Vaccinated patients with SARDs were less likely to experience PASC compared with those not fully vaccinated. While we cannot rule out the possibility that findings may be due to intrinsic differences in PASC risk from different SARS-CoV-2 variants, these findings support the benefits of vaccination for patients with SARDs and suggest that the immune response to acute infection is important in the pathogenesis of PASC in patients with SARDs.

Associations of DMARDs with post-acute sequelae of COVID-19 in patients with systemic autoimmune rheumatic diseases: a prospective study.

OBJECTIVE: We investigated the baseline disease-modifying antirheumatic drug (DMARD) use and post-acute sequelae of COVID-19 (PASC) risk among patients with systemic autoimmune rheumatic diseases (SARDs). METHODS: Patients with SARDs and confirmed COVID-19 infection at Mass General Brigham completed a survey ≥28 days after positive PCR/Antigen test to prospectively investigate their COVID-19 courses. We investigated DMARD use at COVID-19 onset and PASC risk. PASC was defined as any COVID-19 symptom that persisted for ≥28 days. We used logistic regression to estimate odds ratios (OR) for PASC by DMARD class. We also used restricted mean survival time to determine the difference in symptom-free days by DMARD class in the 28-day period after infection. RESULTS: We analyzed 510 patients with SARDs and COVID-19 from 11/Mar/2021-17/Jun/2023; 202 (40%) developed PASC. CD20 inhibitor (CD20i) users had significantly higher odds of developing PASC vs csDMARD users (adjusted OR 2.69, 95%CI 1.23-5.88). IL-12/23, IL-17A, or IL-23 inhibitor (IL-12/23i, IL-17Ai, IL-23i) users also had significantly higher odds of PASC (adjusted OR 3.03, 95%CI 1.08-8.49). CD20i users had significantly fewer symptom-free days vs csDMARD users (adjusted -4.12, 95%CI -7.29 to -0.94). CONCLUSION: CD20i users had significantly higher odds of PASC and fewer symptom-free days over the 28 days following COVID-19 diagnosis compared with csDMARD users. Further research is needed to investigate whether PASC risk in CD20i users may be due to prolonged infection or other immune mechanisms. The association of IL-12/23i, IL-17Ai, and IL-23i and PASC calls for additional study.

Missing Piece in Colloidal Stability─Morphological Factor of Hydrophobic Nanoparticles.

Hydrophobic nanoparticles (NPs) in water were considered unstable because they lack the repulsive electrostatic interaction and steric effect to prevent aggregation. In this study, porous hydrophobic NPs of two star-shaped giant molecules, POSS-(R)8, were found to be stable in water and able to retain their kinetic stability in a wide range of temperatures, pH values, and ionic strengths. Unlike the solid hydrophobic NPs that aggregate even with the negative zeta potential (ζ) induced by surface-structured hydrogen-bonded (SHB) water, the porous morphology of POSS-(R)8 NPs reduces the entropically driven hydrophobic effect to prevent aggregation. With the porous morphology, the hydrophobic NPs are stable without the hydrophilic or charged surface functional groups and demonstrate good encapsulation capability. The morphological factor of colloids is thus one of the missing pieces in the theory of colloidal stability that extends our understanding of colloidal science.

Construction and Application of Multipurpose metal-organic frameworks -based Hydrogen Sulfide Probe.

Hydrogen sulfide (H2S) is a toxic gas derived from the sulfur industry and trace H2S in the environment can cause serious ecological damage while inhalation can cause serious damage and lead to disease. Therefore, the real-time and accurate detection of trace sulfur ions is of great significance for environmental protection and early disease detection. Considering the shortcoming of current H2S probes in terms of stability and sensitivity, the development of novel probes is necessary. Herein, a novel metal-organic frameworks (MOF)-based material, UiO-66-NH2@BDC, was designed and prepared for the visual detection of H2S with rapid response (< 6 s) and low detection limit of S2- (0.13 µM) by hydrogen bonding. Based on its good optical performance, the UiO-66-NH2@BDC probe can detect S2- in various water environments. More importantly, UiO-66-NH2@BDC probe realize imaging S2- in cells and live zebrafish.

Landscape analysis of adjacent gene rearrangements reveals BCL2L14-ETV6 gene fusions in more aggressive triple-negative breast cancer.

Triple-negative breast cancer (TNBC) accounts for 10 to 20% of breast cancer, with chemotherapy as its mainstay of treatment due to lack of well-defined targets, and recent genomic sequencing studies have revealed a paucity of TNBC-specific mutations. Recurrent gene fusions comprise a class of viable genetic targets in solid tumors; however, their role in breast cancer remains underappreciated due to the complexity of genomic rearrangements in this cancer. Our interrogation of the whole-genome sequencing data for 215 breast tumors catalogued 99 recurrent gene fusions, 57% of which are cryptic adjacent gene rearrangements (AGRs). The most frequent AGRs, BCL2L14-ETV6, TTC6-MIPOL1, ESR1-CCDC170, and AKAP8-BRD4, were preferentially found in the more aggressive forms of breast cancers that lack well-defined genetic targets. Among these, BCL2L14-ETV6 was exclusively detected in TNBC, and interrogation of four independent patient cohorts detected BCL2L14-ETV6 in 4.4 to 12.2% of TNBC tumors. Interestingly, these fusion-positive tumors exhibit more aggressive histopathological features, such as gross necrosis and high tumor grade. Amid TNBC subtypes, BCL2L14-ETV6 is most frequently detected in the mesenchymal entity, accounting for ∼19% of these tumors. Ectopic expression of BCL2L14-ETV6 fusions induce distinct expression changes from wild-type ETV6 and enhance cell motility and invasiveness of TNBC and benign breast epithelial cells. Furthermore, BCL2L14-ETV6 fusions prime partial epithelial-mesenchymal transition and endow resistance to paclitaxel treatment. Together, these data reveal AGRs as a class of underexplored genetic aberrations that could be pathological in breast cancer, and identify BCL2L14-ETV6 as a recurrent gene fusion in more aggressive form of TNBC tumors.

Fusion-associated carcinomas of the breast: Diagnostic, prognostic, and therapeutic significance.

Recurrent gene fusions comprise a class of viable genetic targets in solid tumors that have culminated several recent breakthrough cancer therapies. Their role in breast cancer, however, remains largely underappreciated due to the complexity of genomic rearrangements in breast malignancy. Just recently, we and others have identified several recurrent gene fusions in breast cancer with important clinical and biological implications. Examples of the most significant recurrent gene fusions to date include (1) ESR1::CCDC170 gene fusions in luminal B and endocrine-resistant breast cancer that exert oncogenic function via modulating the HER2/HER3/SRC Proto-Oncogene (SRC) complex, (2) ESR1 exon 6 fusions in metastatic disease that drive estrogen-independent estrogen-receptor transcriptional activity, (3) BCL2L14::ETV6 fusions in a more aggressive form of the triple-negative subtype that prime epithelial-mesenchymal transition and endow paclitaxel resistance, (4) the ETV6::NTRK3 fusion in secretory breast carcinoma that constitutively activates NTRK3 kinase, (5) the oncogenic MYB-NFIB fusion as a genetic driver underpinning adenoid cystic carcinomas of the breast that activates MYB Proto-Oncogene (MYB) pathway, and (6) the NOTCH/microtubule-associated serine-threonine (MAST) kinase gene fusions that activate NOTCH and MAST signaling. Importantly, these fusions are enriched in more aggressive and lethal breast cancer presentations and appear to confer therapeutic resistance. Thus, these gene fusions could be utilized as genetic biomarkers to identify patients who require more intensive treatment and surveillance. In addition, kinase fusions are currently being evaluated in breast cancer clinical trials and ongoing mechanistic investigation is exposing therapeutic vulnerabilities in patients with fusion-positive disease.

MTAGCN: predicting miRNA-target associations in Camellia sinensis var. assamica through graph convolution neural network.

BACKGROUND: MircoRNAs (miRNAs) play a central role in diverse biological processes of Camellia sinensis var.assamica (CSA) through their associations with target mRNAs, including CSA growth, development and stress response. However, although the experiment methods of CSA miRNA-target identifications are costly and time-consuming, few computational methods have been developed to tackle the CSA miRNA-target association prediction problem. RESULTS: In this paper, we constructed a heterogeneous network for CSA miRNA and targets by integrating rich biological information, including a miRNA similarity network, a target similarity network, and a miRNA-target association network. We then proposed a deep learning framework of graph convolution networks with layer attention mechanism, named MTAGCN. In particular, MTAGCN uses the attention mechanism to combine embeddings of multiple graph convolution layers, employing the integrated embedding to score the unobserved CSA miRNA-target associations. DISCUSSION: Comprehensive experiment results on two tasks (balanced task and unbalanced task) demonstrated that our proposed model achieved better performance than the classic machine learning and existing graph convolution network-based methods. The analysis of these results could offer valuable information for understanding complex CSA miRNA-target association mechanisms and would make a contribution to precision plant breeding.

Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways.

Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig.

Temporal trends in COVID-19 outcomes among patients with systemic autoimmune rheumatic diseases: from the first wave through the initial Omicron wave.

OBJECTIVES: To investigate temporal trends in incidence and severity of COVID-19 among patients with systemic autoimmune rheumatic diseases (SARDs) from the first wave through the initial Omicron wave. METHODS: We conducted a retrospective cohort study investigating COVID-19 outcomes among patientswith SARD systematically identified to have confirmed COVID-19 from 1 March 2020 to 31 January 2022 at Mass General Brigham. We tabulated COVID-19 counts of total and severe cases (hospitalisations or deaths) and compared the proportion with severe COVID-19 by calendar period and by vaccination status. We used logistic regression to estimate the ORs for severe COVID-19 for each period compared with the early COVID-19 period (reference group). RESULTS: We identified 1449 patients with SARD with COVID-19 (mean age 58.4 years, 75.2% female, 33.9% rheumatoid arthritis). There were 399 (28%) cases of severe COVID-19. The proportion of severe COVID-19 outcomes declined over calendar time (p for trend <0.001); 46% of cases were severe in the early COVID-19 period (1 March 2020-30 June 2020) vs 15% in the initial Omicron wave (17 December 2021-31 January 2022; adjusted OR 0.29, 95% CI 0.19 to 0.43). A higher proportion of those unvaccinated were severe compared with not severe cases (78% vs 60%). CONCLUSIONS: The proportion of patients with SARD with severe COVID-19 has diminished since early in the pandemic, particularly during the most recent time periods, including the initial Omicron wave. Advances in prevention, diagnosis and treatment of COVID-19 may have improved outcomes among patients with SARD.

SB431542 alleviates lupus nephritis by regulating B cells and inhibiting the TLR9/TGFß1/PDGFB signaling.

Lupus nephritis (LN) is the most common cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Currently, immunosuppressive treatments for LN are suboptimal and can induce significant side effects. SB431542 is a selective and potent inhibitor of the TGFß/Activin/NODAL pathway. Here, we study the effects of SB431542 treatment on LN and discuss the potential mechanisms. SB431542 ameliorated clinical outcomes with a consequent histological improvement in NZB/W mice. A comparative transcriptional profiling analysis revealed 586 differentially expressed genes (247 downregulated genes) in the SB431542 group compared to the control group. We found that the downregulated genes were mainly enriched in the biological processes of B cell activation, B cell proliferation, B cell differentiation, and B cell receptor signaling. Kyoto encyclopedia of genes and genomes pathway analysis revealed that the hematopoietic cell linage pathway was significantly downregulated in the SB431542 group. In addition, we observed that SB431542 reduced the splenic or renal levels of CD20 and the serum levels of anti-dsDNA antibody (IgG) in NZB/W mice. Furthermore, qRT-PCR and immunohistochemistry confirmed that SB431542 inhibits the production of TLR9, TGFß1, and PDGFB. Thus, due to its immunomodulatory activities, SB431542 could be considered for clinical therapy development for LN.

The effect of hydration and dehydration on the conformation, assembling behavior and photoluminescence of PBLG.

Hydration and dehydration play crucial roles in hydrophobic effects (HEs) and are yet to be understood. Poly(γ-benzyl-L-glutamate) (PBLG) homopolymers in THF/water with various water contents were investigated. We discovered that PBLG was hydrated at low water contents and adopted a helical conformation. The chain became dehydrated with increasing water content, which converted the PBLG100 helix to a PPII-helix. The variation in the conformation resulted in an alteration of the self-assembled morphologies from fibers to particles. For PBLG12 with a shorter chain, the chain underwent an α-to-ß transition in the conformation due to dehydration as the water content increased, and correspondingly the morphologies varied from tapes to helical ribbons, and eventually to toroids at a higher water content. We also observed that this α-to-ß transition is accompanied by an increase in intensity of the fluorescence, which is attributed to the through-space-conjugation of tightly packed phenyl groups within the ß-sheet. The discovered effect of hydration and dehydration on the PBLG chain conformation, self-assembling behavior and optical function is essential for the innovation of polypeptide materials and understanding of water-mediated biological systems.

Preparation of novel fluorescent probe based on carbon dots for sensing and imaging Fe(III) and pyrophosphate in cells and zebrafish.

Ferric ions (Fe3+) and pyrophosphate anions (PPi) are involved in many physiological processes and play important roles in biological systems. The abnormal level of Fe3+ and PPi will cause serious damage to the environment and life. At present, the application of such probes in life, especially in vivo, is still very scarce. So, the development of a fluorescent probe to simultaneously detect Fe3+ and PPi has great significance to the health of the environment and organisms. Herein, nitrogen-doped carbon quantum dots (N-CDs) were synthesized via solvothermal treatment, using biuret and citric acid as precursors. The synthesized N-CDs showed highly selective and sensitive detection of Fe3+ through a photoluminescence quenching effect. The fluorescence of N-CDs quenched by Fe3+ could be restored with PPi, rendering the N-CDs/Fe3+ sensor promising for PPi detection ('OFF-ON'). The linear ranges of detection for Fe3+ and PPi were 3-30 and 2-12 µM, and the limits of detection were 2.71 and 1.12 µM, respectively. The practical applications of N-CDs were tested using tap water samples. Furthermore, N-CDs can be used for the detection and imaging of Fe3+ and PPi in HeLa cells and zebrafish owing to their excellent optical properties.