Context-specific eQTLs reveal causal genes underlying shared genetic architecture of critically ill COVID-19 and idiopathic pulmonary fibrosis.

Most genetic variants identified through genome-wide association studies (GWAS) are suspected to be regulatory in nature, but only a small fraction colocalize with expression quantitative trait loci (eQTLs, variants associated with expression of a gene). Therefore, it is hypothesized but largely untested that integration of disease GWAS with context-specific eQTLs will reveal the underlying genes driving disease associations. We used colocalization and transcriptomic analyses to identify shared genetic variants and likely causal genes associated with critically ill COVID-19 and idiopathic pulmonary fibrosis. We first identified five genome-wide significant variants associated with both diseases. Four of the variants did not demonstrate clear colocalization between GWAS and healthy lung eQTL signals. Instead, two of the four variants colocalized only in cell-type and disease-specific eQTL datasets. These analyses pointed to higher ATP11A expression from the C allele of rs12585036, in monocytes and in lung tissue from primarily smokers, which increased risk of IPF and decreased risk of critically ill COVID-19. We also found lower DPP9 expression (and higher methylation at a specific CpG) from the G allele of rs12610495, acting in fibroblasts and in IPF lungs, and increased risk of IPF and critically ill COVID-19. We further found differential expression of the identified causal genes in diseased lungs when compared to non-diseased lungs, specifically in epithelial and immune cell types. These findings highlight the power of integrating GWAS, context-specific eQTLs, and transcriptomics of diseased tissue to harness human genetic variation to identify causal genes and where they function during multiple diseases.

Aging promotes metabolic dysfunction-associated steatotic liver disease by inducing ferroptotic stress.

Susceptibility to the biological consequences of aging varies among organs and individuals. We analyzed hepatocyte transcriptomes of healthy young and aged male mice to generate an aging hepatocyte gene signature, used it to deconvolute transcriptomic data from humans and mice with metabolic dysfunction-associated liver disease, validated findings with functional studies in mice and applied the signature to transcriptomic data from other organs to determine whether aging-sensitive degenerative mechanisms are conserved. We discovered that the signature enriches in diseased livers in parallel with degeneration. It is also enriched in failing human hearts, diseased kidneys and pancreatic islets from individuals with diabetes. The signature includes genes that control ferroptosis. Aged mice develop more hepatocyte ferroptosis and liver degeneration than young mice when fed diets that induce metabolic stress. Inhibiting ferroptosis shifts the liver transcriptome of old mice toward that of young mice and reverses aging-exacerbated liver damage, identifying ferroptosis as a tractable, conserved mechanism for aging-related tissue degeneration.

Pore-blocking steric mass-action model for adsorption of bioparticles.

The steric mass-action (SMA) model has been widely reported to describe the adsorption of proteins in different types of chromatographic adsorbents. Here in the present work, a pore-blocking steric mass-action model (PB-SMA) was developed for the adsorption of large-size bioparticles, which usually exhibit the unique pore-blocking characteristic on the adsorbent and thus lead to a fraction of ligands in the deep channels physically inaccessible to bioparticles adsorption, instead of being shielded due to steric hindrance by adsorbed bioparticles. This unique phenomenon was taken into account by introducing an additional parameter, Lin, which is defined as the inaccessible ligand densities in the physically blocked pore area, into the PB-SMA model. This fraction of ligand densities (Lin) will be deducted from the total ligand (Lt) for model development, thus the steric factor (σ) in the proposed PB-SMA will reflect the steric shielding effect on binding sites by adsorbed bioparticles more accurately than the conventional SMA model, which assumes that all ligands on the adsorbent have the same accessibility to the bioparticles. Based on a series of model assumptions, a PB-SMA model was firstly developed for inactivated foot-and-mouth disease virus (iFMDV) adsorption on immobilized metal affinity chromatography (IMAC) adsorbents. Model parameters for static adsorption including equilibrium constant (K), characteristic number of binding sites (n), and steric factor (σ) were determined. Compared with those derived from the conventional SMA model, the σ values derived from the PB-SMA model were dozens of times smaller and much closer to the theoretical maximum number of ligands shielded by a single adsorbed iFMDV, indicating the modified model was more accurate for bioparticles adsorption. The applicability of the PB-SMA model was further validated by the adsorption of hepatitis B surface antigen virus-like particles (HBsAg VLPs) on an ion exchange adsorbent with reasonably improved accuracy. Thus, it is considered that the PB-SMA model would be more accurate in describing the adsorption of bioparticles on different types of chromatographic adsorbents.

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning.

Background: Fungal infections are associated with high morbidity and mortality in the intensive care unit (ICU), but their diagnosis is difficult. In this study, machine learning was applied to design and define the predictive model of ICU-acquired fungi (ICU-AF) in the early stage of fungal infections using Random Forest. Objectives: This study aimed to provide evidence for the early warning and management of fungal infections. Methods: We analyzed the data of patients with culture-positive fungi during their admission to seven ICUs of the First Affiliated Hospital of Chongqing Medical University from January 1, 2015, to December 31, 2019. Patients whose first culture was positive for fungi longer than 48 h after ICU admission were included in the ICU-AF cohort. A predictive model of ICU-AF was obtained using the Least Absolute Shrinkage and Selection Operator and machine learning, and the relationship between the features within the model and the disease severity and mortality of patients was analyzed. Finally, the relationships between the ICU-AF model, antifungal therapy and empirical antifungal therapy were analyzed. Results: A total of 1,434 cases were included finally. We used lasso dimensionality reduction for all features and selected six features with importance ≥0.05 in the optimal model, namely, times of arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation. The area under the curve of the model for predicting ICU-AF was 0.981 in the test set, with a sensitivity of 0.960 and specificity of 0.990. The times of arterial catheter (p = 0.011, OR = 1.057, 95% CI = 1.053-1.104) and invasive mechanical ventilation (p = 0.007, OR = 1.056, 95%CI = 1.015-1.098) were independent risk factors for antifungal therapy in ICU-AF. The times of arterial catheter (p = 0.004, OR = 1.098, 95%CI = 0.855-0.970) were an independent risk factor for empirical antifungal therapy. Conclusion: The most important risk factors for ICU-AF are the six time-related features of clinical parameters (arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation), which provide early warning for the occurrence of fungal infection. Furthermore, this model can help ICU physicians to assess whether empiric antifungal therapy should be administered to ICU patients who are susceptible to fungal infections.

Lewis Acid Catalyzed Cycloaddition of Bicyclobutanes with Ynamides for the Synthesis of Polysubstituted 2-Amino-bicyclo[2.1.1]hexenes.

Synthesis of bicyclic scaffolds has gained significant attention in drug discovery due to their potential to mimic benzene bioisosteres. Here, we present a mild and scalable Sc(OTf)3-catalyzed [3+2] cycloaddition of bicyclo[1.1.0]butanes (BCBs) with ynamides, yielding a diverse array of polysubstituted 2-amino-bicyclo[2.1.1]hexenes in good to excellent yields. These products offer valuable starting materials for the construction of novel functionalized bicyclo[1.1.0]butanes. Preliminary mechanistic studies indicate that the reaction involves a nucleophilic addition of ynamides to bicyclo[1.1.0]butanes, followed by an intramolecular cyclization of in situ generated enolate and keteniminium ion. We expect that these findings will encourage utilization of complex bioisosteres and foster further investigation into BCB-based cycloaddition chemistry.

A strong, silk protein-inspired tissue adhesive with an enhanced drug release mechanism for transdermal drug delivery.

In transdermal drug delivery system (TDDS) patches, achieving prolonged adhesion, high drug loading, and rapid drug release simultaneously presented a significant challenge. In this study, a PHT-SP-Cu2+ adhesive was synthesized using polyethylene glycol (PEG), hexamethylene diisocyanate (HDI), trimethylolpropane (TMP), and silk protein (SP) as functional monomers which were combined with Cu2+ to improve the adhesion, drug loading, and drug release of the patch. The structure of the adhesion chains and the formation of Cu2+-p-π conjugated network in PHT-SP-Cu2+ were characterized and elucidated using different characterization methods including FT-IR, 13C NMR, XPS, SEM imaging and thermodynamic evaluation. The formulation of pressure-sensitive adhesive (PSA) was optimized through comprehensive research on adhesion, mechanics, rheology, and surface energy. The formulation of 3 wt.% SP and 3 wt.% Cu2+ provided superior adhesion properties compared to commercial standards. Subsequently, the peel strength of PHT-SP-Cu2+ was 7.6 times higher than that of the commercially available adhesive DURO-TAK® 87-4098 in the porcine skin peel test. The adhesion test on human skin confirmed that PHT-SP-Cu2+ could adhere to the human body for more than six days. Moreover, the drug loading, in vitro release test and skin permeation test were investigated using ketoprofen as a model drug, and the results showed that PHT-SP-Cu2+ had the efficacy of improving drug compatibility, promoting drug release and enhancing skin permeation as a TDDS. Among them, the drug loading of PHT-SP-Cu2+ was increased by 6.25-fold compared with PHT, and in the in vivo pharmacokinetic analysis, the AUC was similarly increased by 19.22-fold. The mechanism of α-helix facilitated drug release was demonstrated by Flori-Hawkins interaction parameters, molecular dynamics simulations and FT-IR. Biosafety evaluations highlighted the superior skin cytocompatibility and safety of PHT-SP-Cu2+ for transdermal applications. These results would contribute to the development of TDDS patch adhesives with outstanding adhesion, drug loading and release efficiency. STATEMENT OF SIGNIFICANCE: A new adhesive, PHT-SP-Cu2+, was created for transdermal drug delivery patches. Polyethylene glycol, hexamethylene diisocyanate, trimethylolpropane, silk protein, and Cu2+ were used in synthesis. Characterization techniques confirmed the structure and Cu2+-p-π conjugated networks. Optimal formulation included 3 wt.% SP and 3 wt.% Cu2+, exhibiting superior adhesion. PHT-SP-Cu2+ showed 7.6 times higher peel strength than DURO-TAK® 87-4098 on porcine skin and adhered to human skin for over six days. It demonstrated a 6.25-fold increase in drug loading compared to PHT, with 19.22-fold higher AUC in vivo studies. α-helix facilitated drug release, proven by various analyses. PHT-SP-Cu2+ showed excellent cytocompatibility and safety for transdermal applications. This study contributes to developing efficient TDDS patches.

SifiNet: a robust and accurate method to identify feature gene sets and annotate cells.

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multi-omic cellular profiles. It is conveniently available as an open-source R package.

Validation and Evaluation of Reference Genes for Quantitative Real-Time PCR Analysis in Mythimna loreyi (Lepidoptera: Noctuidae).

Quantitative real-time PCR (qRT-PCR) is a widely applied technique for accurately assessing the expression of target genes. In practice, the evaluation of gene expression requires appropriate reference genes. To screen reliable reference genes for evaluating gene expression via qRT-PCR in Mythimna loreyi, a notorious migratory pest across Asia, Africa, Europe, and Australia, we assessed the expression stability of 13 candidate reference genes in M. loreyi using the ΔCt method, BestKeeper, Normfinder, GeNorm, and the web-based comprehensive platform RefFinder. These reference genes include RPL10, RPL27, RPL32, RPS3, TATA-box, GAPDH, AK, Actin, EF, α-tubulin, SOD, 18S rRNA, and FTZ-F1, which is frequently employed in Lepidoptera insects. Our findings revealed that the performance of the candidate reference gene depended on experimental conditions. Specifically, RPL27 and RPL10 were the most suitable for evaluating expression changes across developmental stages, tissues, and adult ages. The optimal reference genes were recommended in specific experiment conditions, for instance, EF and RPS3 were recommended for mating status, AK and RPL10 were recommended for temperature treatments, RPL27 and FTZ-F1 were recommended for larva diet, and EF and RPL27 were recommended for adult diet treatments. Additionally, expression profiles of pheromone-binding protein 2 (MlorPBP2) and glutathione S-transferase (MlorGST1) were used to validate the reference genes. This study provides reference genes for the accurate normalization of qRT-PCR data, laying the groundwork for studying the expression of target genes in M. loreyi.

Neutrophil extracellular traps induce pyroptosis of pulmonary microvascular endothelial cells by activating the NLRP3 inflammasome.

Excessive formation of neutrophil extracellular traps (NETs) may lead to myositis-related interstitial lung disease (ILD). There is evidence that NETs can directly injure vascular endothelial cells and play a pathogenic role in the inflammatory exudation of ILD. However, the specific mechanism is unclear. This study aimed to investigate the specific mechanism underlying NET-induced injury to human pulmonary microvascular endothelial cells (HPMECs). HPMECs were stimulated with NETs (200 ng/ml) in vitro. Cell death was detected by propidium iodide staining. The morphological changes of the cells were observed by transmission electron microscopy (TEM). Pyroptosis markers were detected by western blot, immunofluorescence, and quantitative real-time polymerase chain reaction, and the related inflammatory factor Interleukin-1ß (IL-1ß) was verified by enzyme-linked immunosorbent assay (ELISA). Compared with the control group, HPMECs mortality increased after NET stimulation, and the number of pyroptosis vacuoles in HPMECs was further observed by TEM. The pulmonary microvascular endothelial cells (PMECs) of the experimental autoimmune myositis mouse model also showed a trend of pyroptosis in vivo. Cell experiment further confirmed the significantly high expression of the NLRP3 inflammasome and pyroptosis-related markers, including GSDMD and inflammatory factor IL-1ß. Pretreated with the NLRP3 inhibitor MCC950, the activation of NLRP3 inflammasome and pyroptosis of HPMECs were effectively inhibited. Our study confirmed that NETs promote pulmonary microvascular endothelial pyroptosis by activating the NLRP3 inflammasome, suggesting that NETs-induced pyroptosis of PMECs may be a potential pathogenic mechanism of inflammatory exudation in ILD.

In-Situ Formed Electron Inhibitor Enabling Dendrite-free Garnet Electrolytes: A Case Study of Fumed Silica.

Ta-doped Li7La3Zr2O12 (LLZTO) solid-state electrolytes (SEs) show great promise for solid-state batteries due to its high conductivity and safety. However, one of the challenges it faces is lithium dendrite propagation upon long-term cycling. To address this issue, we propose the incorporation of fumed silica (FS) at the grain boundaries of LLZTO to modify the properties of the garnet pellet, which effectively inhibits the dendrite growth. The introduction of FS has demonstrated several beneficial effects. Firstly, it reduces the migration barrier of lithium ions, which helps prevent dendrite formation and propagation. Additionally, FS reduces the electronic conductivity of the SEs pellet, suppressing the dendrite formation. Moreover, the formed lithium silicates from FS might also be acted as electron inhibitor, thus inhibiting the lithium dendrite growth upon cycling. By investigating the use of FS as a modifier in LLZTO-based electrolytes, our study contributes to advancing dendrite-free solid-state electrolytes and thus the development of high-performance all-solid-state batteries.

In situ bio-mineralized Mn nanoadjuvant enhances anti-influenza immunity of recombinant virus-like particle vaccines.

Virus like particles (VLPs) have been well recognized as one of the most important vaccine platforms due to their structural similarity to natural viruses to induce effective humoral and cellular immune responses. Nevertheless, lack of viral nucleic acids in VLPs usually leads the vaccine candidates less efficient in provoking innate immune against viral infection. Here, we constructed a biomimetic dual antigen hybrid influenza nanovaccines THM-HA@Mn with robust immunogenicity via in situ synthesizing a stimulator of interferon genes (STING) agonist Mn3O4 inside the cavity of a recombinant Hepatitis B core antigen VLP (HBc VLP) having fused SpyTag and influenza M2e antigen peptides (Tag-HBc-M2e, THM for short), followed by conjugating a recombinant hemagglutinin (rHA) antigen on the surface of the nanoparticles through SpyTag/SpyCatcher ligating. Such inside Mn3O4 immunostimulator-outside rHA antigen design, together with the chimeric M2e antigen on the HBc skeleton, enabled the synthesized hybrid nanovaccines THM-HA@Mn to well imitate the spatial distribution of M2e/HA antigens and immunostimulant in natural influenza virus. In vitro cellular experiments indicated that compared with the THM-HA antigen without Mn3O4 and a mixture vaccine consisting of THM-HA + MnOx, the THM-HA@Mn hybrid nanovaccines showed the highest efficacies in dendritic cells uptake and in promoting BMDC maturation, as well as inducing expression of TNF-α and type I interferon IFN-ß. The THM-HA@Mn also displayed the most sustained antigen release at the injection site, the highest efficacies in promoting the DC maturation in lymph nodes and germinal center B cells activation in the spleen of the immunized mice. The co-delivery of immunostimulant and antigens enabled the THM-HA@Mn nanovaccines to induce the highest systemic antigen-specific antibody responses and cellular immunogenicity in mice. Together with the excellent colloid dispersion stability, low cytotoxicity, as well as good biosafety, the synthetic hybrid nanovaccines presented in this study offers a promising strategy to design VLP-based vaccine with robust natural and adaptive immunogenicity against emerging viral pathogens.

PPSNO: A Feature-Rich SNO Sites Predictor by Stacking Ensemble Strategy from Protein Sequence-Derived Information.

The protein S-nitrosylation (SNO) is a significant post-translational modification that affects the stability, activity, cellular localization, and function of proteins. Therefore, highly accurate prediction of SNO sites aids in grasping biological function mechanisms. In this document, we have constructed a predictor, named PPSNO, forecasting protein SNO sites using stacked integrated learning. PPSNO integrates multiple machine learning techniques into an ensemble model, enhancing its predictive accuracy. First, we established benchmark datasets by collecting SNO sites from various sources, including literature, databases, and other predictors. Second, various techniques for feature extraction are applied to derive characteristics from protein sequences, which are subsequently amalgamated into the PPSNO predictor for training. Five-fold cross-validation experiments show that PPSNO outperformed existing predictors, such as PSNO, PreSNO, pCysMod, DeepNitro, RecSNO, and Mul-SNO. The PPSNO predictor achieved an impressive accuracy of 92.8%, an area under the curve (AUC) of 96.1%, a Matthews correlation coefficient (MCC) of 81.3%, an F1-score of 85.6%, an SN of 79.3%, an SP of 97.7%, and an average precision (AP) of 92.2%. We also employed ROC curves, PR curves, and radar plots to show the superior performance of PPSNO. Our study shows that fused protein sequence features and two-layer stacked ensemble models can improve the accuracy of predicting SNO sites, which can aid in comprehending cellular processes and disease mechanisms. The codes and data are available at https://github.com/serendipity-wly/PPSNO .

Breaking NGF-TrkA immunosuppression in melanoma sensitizes immunotherapy for durable memory T cell protection.

Melanoma cells, deriving from neuroectodermal melanocytes, may exploit the nervous system's immune privilege for growth. Here we show that nerve growth factor (NGF) has both melanoma cell intrinsic and extrinsic immunosuppressive functions. Autocrine NGF engages tropomyosin receptor kinase A (TrkA) on melanoma cells to desensitize interferon γ signaling, leading to T and natural killer cell exclusion. In effector T cells that upregulate surface TrkA expression upon T cell receptor activation, paracrine NGF dampens T cell receptor signaling and effector function. Inhibiting NGF, either through genetic modification or with the tropomyosin receptor kinase inhibitor larotrectinib, renders melanomas susceptible to immune checkpoint blockade therapy and fosters long-term immunity by activating memory T cells with low affinity. These results identify the NGF-TrkA axis as an important suppressor of anti-tumor immunity and suggest larotrectinib might be repurposed for immune sensitization. Moreover, by enlisting low-affinity T cells, anti-NGF reduces acquired resistance to immune checkpoint blockade and prevents melanoma recurrence.

Evaluation of Reference Genes for Quantitative Real-Time PCR Analysis in the Bean Bug, Riptortus pedestris (Hemiptera: Alydidae).

Quantitative real-time PCR (qRT-PCR) is widely accepted as a precise and convenient method for quantitatively analyzing the expression of functional genes. The data normalization strongly depends upon stable reference genes. The bean bug, Riptortus pedestris (Hemiptera: Alydidae), is a significant pest of leguminous crops and broadly distributed across Southeast Asia. In this study, a total of 16 candidate reference genes (RPL32, RPS23, SDHA, UBQ, UCCR, GST, TATA-box, HSP70, GAPDH, RPL7A, SOD, RPS3, Actin, α-tubulin, AK, and EF1) were carefully chosen in R. pedestris, and their expression levels were assessed across various conditions, including different developmental stages, diverse tissues, temperature treatments, adult age, molting time, and mating status. Following this, the stability of these reference genes was evaluated using four algorithms (ΔCt, GeNorm, NormFinder, and BestKeeper). Ultimately, the comprehensive rankings were determined using the online tool RefFinder. Our results demonstrate that the reference gene for qRT-PCR analysis in R. pedestris is contingent upon the specific experimental conditions. RPL7A and EF1 are optimal reference genes for developmental stages. Furthermore, α-tubulin and EF1 exhibit the most stable expression across various adult tissues. RPL32 and RPL7A exhibit the most stable expression for adult age. For nymph age, RPL32 and SOD display the most stable expression. For temperature conditions, RPS23 and RPL7A were identified as the most suitable for monitoring gene expression. Lastly, we verified the practicability of evaluating expression levels of odorant-binding protein 37 (RpedOBP37) and cytochrome P450 6a2 (RpedCYP6) throughout developmental stages, tissues, and temperature conditions. These findings are a significant addition to the qRT-PCR analysis studies on R. pedestris, serving as a fundamental groundwork for future investigations on stable reference genes in R. pedestris as well as other organisms.

Two-Drug Combinations Therapy of Different Doses of Valsartan Existing Diverse Significance for Hypertensive Patients.

Background: The incidence of hypertension and clinical complications (e.g., heart, cerebrovascular and kidney injury) is increasing worldwide. It is widely known that a relatively large dose of valsartan (320 mg) could alleviate clinical complications. The current network meta-analysis assessed which drug could be combined with a relatively large dose of valsartan to control blood pressure (BP) more effectively. And which combination therapy with different dosages of valsartan did not induce excessive BP reduction with increasing dosages of valsartan. Methods: The PubMed, Embase, Medline, Cochrane Library, CNKI, Wanfang, and CSTJ databases were searched from inception to October 2022 for relevant randomized controlled trials (RCTs). The search strategies included concepts related to hypertension and two-drug combination therapy of different doses of valsartan, and there were no language or data restrictions. The outcomes included adverse effects and changes in systolic BP and diastolic BP. Permanent discontinuations related to treatment were the most accurate and objective measure of adverse effects. The common adverse effects of most studies (i.e., dizziness, headache, nasopharyngitis, asthenia and urticaria) were also included. A Bayesian network meta-analysis was performed, and mean differences with 95% confidence intervals were calculated. ADDIS and STATA were used for Bayesian model network meta-calculation. Results: Thirty-four RCTs were included involving 26,752 patients, and the interventions included different doses of valsartan combined with various types and doses of drugs. Among many combination therapies, the combination of valsartan 320 mg with amlodipine 10 mg (p < 0.01) had the best antihypertensive effect without significant adverse effects. Compared with valsartan 80 mg and 160 mg, valsartan 320 mg combined with hydrochlorothiazide 25 mg (p > 0.05) did not further reduce BP and was not shown to increase the incidence of adverse effects. Conclusions: Combination therapy with a relatively large dose of valsartan could control BP and improve clinical complications effectively. However, for hypertensive patients with different treatment requirements, specific choices should be made regarding whether to control BP, treat clinical complications, or both.