Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression.

Background: Coronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses. Methods: Sequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes. Results: The analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included IFI44L, IFI44, RSAD2, ISG15, IFIT3, OAS1, EIF2AK2, IFI27, OASL, and EPSTI1. Additionally, five crucial miRNAs (hsa-miR-8060, hsa-miR-6890-5p, hsa-miR-5003-3p, hsa-miR-6893-3p, and hsa-miR-6069), five essential transcription factors (CREB1, CEBPB, EGR1, EP300, and IRF1), and the top ten significant drug chemicals (estradiol, progesterone, tretinoin, calcitriol, fluorouracil, methotrexate, lipopolysaccharide, valproic acid, silicon dioxide, cyclosporine) were identified. Conclusion: This research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza.

Pollution control performance of solidified nickel-cobalt tailings on site: Bioavailability of heavy metals and microbial response.

There has been increasing attention given to nickel-cobalt tailings (NCT), which pose a risk of heavy metal pollution in the field. In this study, on site tests and sampling analysis were conducted to assess the physical and chemical characteristics, heavy metal toxicity, and microbial diversity of the original NCT, solidified NCT, and the surrounding soil. The research results show that the potential heavy metal pollution species in NCT are mainly Ni, Co, Mn, and Cu. Simultaneous solidification and passivation of heavy metals in NCT were achieved, resulting in a reduction in biological toxicity and a fivefold increase in seed germination rate. The compressive strength of the original tailings was increased by 20 times after solidification. The microbial diversity test showed that the abundance of microbial community in the original NCT was low and the population was monotonous. This study demonstrates, for the first time, that the use of NCT for solidification in ponds can effectively solidification of heavy metals, reduce biological toxicity, and promote microorganism diversity in mining areas (tended to the microbial ecosystem in the surrounding soil). Indeed, this study provides a new perspective for the environmental remediation of metal tailings.

Proteomics-derived biomarker panel facilitates distinguishing primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) from lung metastatic colorectal cancer (lmCRC).

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging (TMT)-based shotgun proteomics to characterize proteomes of formalin-fixed paraffin-embedded (FFPE) tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest and the Least Absolute Shrinkage and Selection Operator (LASSO), were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by immunochemistry (IHC) to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection (UMAP). The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of 10 candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Application of interpretable machine learning algorithms to predict distant metastasis in ovarian clear cell carcinoma.

BACKGROUND: Ovarian clear cell carcinoma (OCCC) represents a subtype of ovarian epithelial carcinoma (OEC) known for its limited responsiveness to chemotherapy, and the onset of distant metastasis significantly impacts patient prognoses. This study aimed to identify potential risk factors contributing to the occurrence of distant metastasis in OCCC. METHODS: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients diagnosed with OCCC between 2004 and 2015. The most influential factors were selected through the application of Gaussian Naive Bayes (GNB) and Adaboost machine learning algorithms, employing a Venn test for further refinement. Subsequently, six machine learning (ML) techniques, namely XGBoost, LightGBM, Random Forest (RF), Adaptive Boosting (Adaboost), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were employed to construct predictive models for distant metastasis. Shapley Additive Interpretation (SHAP) analysis facilitated a visual interpretation for individual patient. Model validity was assessed using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and the area under the receiver operating characteristic curve (AUC). RESULTS: In the realm of predicting distant metastasis, the Random Forest (RF) model outperformed the other five machine learning algorithms. The RF model demonstrated accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and AUC (95% CI) values of 0.792 (0.762-0.823), 0.904 (0.835-0.973), 0.759 (0.731-0.787), 0.221 (0.186-0.256), 0.974 (0.967-0.982), 0.353 (0.306-0.399), and 0.834 (0.696-0.967), respectively, surpassing the performance of other models. Additionally, the calibration curve's Brier Score (95%) for the RF model reached the minimum value of 0.06256 (0.05753-0.06759). SHAP analysis provided independent explanations, reaffirming the critical clinical factors associated with the risk of metastasis in OCCC patients. CONCLUSIONS: This study successfully established a precise predictive model for OCCC patient metastasis using machine learning techniques, offering valuable support to clinicians in making informed clinical decisions.

Edge-relational window-attentional graph neural network for gene expression prediction in spatial transcriptomics analysis.

Spatial transcriptomics (ST), containing gene expression with fine-grained (i.e., different windows) spatial location within tissue samples, has become vital in developing innovative treatments. Traditional ST technology, however, rely on costly specialized commercial equipment. Addressing this, our article aims to creates a cost-effective, virtual ST approach using standard tissue images for gene expression prediction, eliminating the need for expensive equipment. Conventional approaches in this field often overlook the long-distance spatial dependencies between different sample windows or need prior gene expression data. To overcome these limitations, we propose the Edge-Relational Window-Attentional Network (ErwaNet), enhancing gene prediction by capturing both local interactions and global structural information from tissue images, without prior gene expression data. ErwaNet innovatively constructs heterogeneous graphs to model local window interactions and incorporates an attention mechanism for global information analysis. This dual framework not only provides a cost-effective solution for gene expression predictions but also obviates the necessity of prior knowledge gene expression information, a significant advantage in the field of cancer research where it enables a more efficient and accessible analytical paradigm. ErwaNet stands out as a prior-free and easy-to-implement Graph Convolution Network (GCN) method for predicting gene expression from tissue images. Evaluation of the two public breast cancer datasets shows that ErwaNet, without additional information, outperforms the state-of-the-art (SOTA) methods. Code is available at https://github.com/biyecc/ErwaNet.

Mercury abatement in the environment: Insights from industrial emissions and fates in the environment.

Mercury's neurotoxic effects have prompted the development of advanced control and remediation methods to meet stringent measures for industries with high-mercury feedstocks. Industries with significant Hg emissions, including artisanal and small-scale gold mining (ASGM)-789.2 Mg year-1, coal combustion-564.1 Mg year-1, waste combustion-316.1 Mg year-1, cement production-224.5 Mg year-1, and non-ferrous metals smelting-204.1 Mg year-1, use oxidants and adsorbents capture Hg from waste streams. Oxidizing agents such as O3, Cl2, HCl, CaBr2, CaCl2, and NH4Cl oxidize Hg0 to Hg2+ for easier adsorption. To functionalize adsorbents, carbonaceous ones use S, SO2, and Na2S, metal-based adsorbents use dimercaprol, and polymer-based adsorbents are grafted with acrylonitrile and hydroxylamine hydrochloride. Adsorption capacities span 0.2-85.6 mg g-1 for carbonaceous, 0.5-14.8 mg g-1 for metal-based, and 168.1-1216 mg g-1 for polymer-based adsorbents. Assessing Hg contamination in soils and sediments uses bioindicators and stable isotopes. Remediation approaches include heat treatment, chemical stabilization and immobilization, and phytoremediation techniques when contamination exceeds thresholds. Achieving a substantially Hg-free ecosystem remains a formidable challenge, chiefly due to the ASGM industry, policy gaps, and Hg persistence. Nevertheless, improvements in adsorbent technologies hold potential.

Deoxynivalenol and T-2 toxin cause liver damage and egg quality degradation through endoplasmic reticulum stress in summer laying hens.

The present study aimed to find whether low doses of mixed mycotoxins would affect egg quality in laying hens, and to explore the oxidative stress induced liver damage through endoplasmic reticulum during summer stress. A total of 96 Jinghong laying hens, 36 wks of age, were divided into four treatments, with eight repetitions per treatment and three hens per repetition. All the hens were raised in summer (average temperature: 31.3 ± 0.5℃; average humidity: 85.5 ± 0.2%) for 28d. One treatment was fed a basal diet as control (CON), and the other three treatments were fed the same diets containing 3.0 mg/kg deoxynivalenol (DON), 0.5 mg/kg T-2 toxin (T-2), and 1.5 mg/kg DON + 0.25 mg/kg T-2 toxin (Mix). Albumen height and Haugh unit were decreased (P < 0.05) in the Mix group on day 14 and 28. The activity of total antioxidant capacity, glutathione peroxidase, catalase, and superoxide dismutase were decreased (P < 0.05) in the DON, T-2, and Mix groups. The alkaline phosphatase level in DON, T-2, and Mix groups was significantly increased (P < 0.05). The level of interleukin-1ß, interferon-γ, and tumor necrosis factor-α in the Mix group were higher (P < 0.05) than CON, DON, and T-2 groups. Mix group upregulated the mRNA expressions of protein kinase RNA-like ER kinase, activating transcription factor4, IL-1ß, nuclear factor-κ-gene binding, and nuclear respiratory factor 2 in the liver (P < 0.05). The results showed that low doses of DON and T-2 toxin could cause oxidative stress in the liver, but DON and T-2 toxin have a cumulative effect on virulence, which can reduce egg quality and cause endoplasmic reticulum stress in the liver.

A GITRL-mTORC1-GM-CSF positive loop promotes pathogenic Th17 response in exacerbating Primary Sjögren's Syndrome.

OBJECTIVES: Glucocorticoid-induced Tumor-Necrosis-Factor-Receptor Family-related Protein (GITR), with its ligand (GITRL), plays an important role in CD4+T-cell-mediated autoimmunity. This study aimed to investigate the underlying mechanisms of GITRL in primary Sjögren's Syndrome (pSS). METHODS: pSS patients and healthy controls were recruited. Serum GITRL and Th17-related cytokines were determinated. RNA-Sequencing was performed to decipher key signal pathways. Non Obese Diabetes (NOD) mice was adopted as experimental Sjögren models and recombinant adeno-associated virus (rAAV) transduction was conducted to verify the therapeutic potentials of targeting GITRL in vivo. RESULTS: Serum GITRL was significantly higher in pSS patients and showed a positive correlation with leukopenia, thrombocytopenia, autoantibodies, lung involvement and disease activity. Serum GITRL was correlated with Th17-related cytokines. GITRL promoted expansion of Th17 and Th17.1 cells. Expansion of granulocyte-macrophage-colony-stimulating-factor (GM-CSF+)CD4+T cells induced by GITRL could be inhibited by blockade of GITRL. Moreover, GM-CSF could stimulate GITRL expression on monocytes. RNA-Sequencing revealed mammalian target of rapamycin complexes 1 (mTORC1) might be the key modulator. The increased phosphorylation of S6 and STAT3 and expansion of Th17 and Th17.1 cells induced by GITRL were effectively inhibited by rapamycin, suggesting a GITRL/mTORC1/GM-CSF positive loop in pathogenic Th17 response in pSS. Administration of rAAV vector expressing shRNA targeting GITRL alleviated disease progression in NOD mice. CONCLUSIONS: Our results identified the pathogenic role of GITRL in exacerbating disease activity and promoting pathogenic Th17 response in pSS through a GITRL/mTORC1/GM-CSF positive loop. These findings suggest GITRL might be a promising therapeutic target in the treatment of pSS.

Transport mechanism of presynaptic high-affinity choline uptake by CHT1.

Choline is a vital nutrient and a precursor for the biosynthesis of essential metabolites, including acetylcholine (ACh), that play a central role in fetal development, especially in the brain. In cholinergic neurons, the high-affinity choline transporter (CHT1) provides an extraordinarily efficient reuptake mechanism to reutilize choline derived from intrasynaptical ACh hydrolysis and maintain ACh synthesis in the presynapse. Here, we determined structures of human CHT1 in three discrete states: the outward-facing state bound with the competitive inhibitor hemicholinium-3 (HC-3); the inward-facing occluded state bound with the substrate choline; and the inward-facing apo open state. Our structures and functional characterizations elucidate how the inhibitor and substrate are recognized. Moreover, our findings shed light on conformational changes when transitioning from an outward-facing to an inward-facing state and establish a framework for understanding the transport cycle, which relies on the stabilization of the outward-facing state by a short intracellular helix, IH1.

Fractional Excretion of Urate is Positively Associated with Type 2 Diabetes in HUA Patients: A Cross-Sectional Study.

Purpose: People with hyperuricemia (HUA) are often related to metabolic disorders such as diabetes, metabolic syndrome (MetS), and obesity. However, the correlation between excretion of uric acid and these diseases is unclear. Our study aimed to explore the relationship between uric acid excretion and type 2 diabetes (T2D). Methods: A total of 228 HUA patients from Tianjin Medical University General Hospital from 2022 to 2023 were included in this study. We collected demographic, biochemical, and anthropometric data on each subject. Urine uric acid excretion (UUAE) was calculated enzymatically from a single urine collection that lasted 24 hours. And fractional excretion of uric acid (FEUA) was calculated from serum uric acid and creatinine and uric acid and creatinine. Binary logistic regression modeling assessed the association between uric acid excretion and T2D. Results: Of the 228 subjects, 13.4% had T2D and 48.7% had obesity. The obesity group had a lower FEUA (p<0.05) and a higher UUAE compared to the control group (p<0.05). And FEUA had a stronger correlation with the risk of T2D (p<0.001). Also, there was a negative association between BMI and FEUA and a positive link between BMI and UUAE in the outpatients. Conclusion: Increased FEUA levels were significantly associated with T2D in HUA patients. Therefore, routine calculating of FEUA is essential for proper diagnosis and appropriate treatment T2D of in HUA patients.

The role of MrUbp4, a deubiquitinase, in conidial yield, thermotolerance, and virulence in Metarhizium robertsii.

Ubiquitin-specific proteases (UBPs), the largest subfamily of deubiquitinating enzymes, regulate ubiquitin homeostasis and play diverse roles in eukaryotes. Ubp4 is essential for the growth, development, and pathogenicity of various fungal pathogens. However, its functions in the growth, stress responses, and virulence of entomopathogenic fungi remain unclear. In this study, we elucidated the role of the homolog of Ubp4, MrUbp4, in the entomopathogenic fungus Metarhizium robertsii. Deletion of MrUbp4 led to a notable increase in ubiquitination levels, demonstrating the involvement of MrUbp4 in protein deubiquitination. Furthermore, the ΔMrUbp4 mutant displayed a significant reduction in conidial yield, underscoring the pivotal role of MrUbp4 in conidiation. Additionally, the mutant exhibited heightened resistance to conidial heat treatment, emphasizing the role of MrUbp4 in thermotolerance. Notably, insect bioassays unveiled a substantial impairment in the virulence of the ΔMrUbp4 mutant. This was accompanied by a notable decrease in cuticle penetration ability and appressorium formation upon further analysis. In summary, our findings highlight the essential role of MrUbp4 in regulating the conidial yield, thermotolerance, and contributions to the virulence of M. robertsii.

Dual roles of α1,4-galactosyltransferase 1 in spermatogenesis of Drosophila melanogaster.

Spermatogenesis is critical for insect reproduction and the process is regulated by multiple genes. Glycosyltransferases have been shown to participate in the development of Drosophila melanogaster; however, their role in spermatogenesis is still unclear. In this study, we found that α1,4-galactosyltransferase 1 (α4GT1) was expressed at a significantly higher level in the testis than in the ovary of Drosophila. Importantly, the hatching rate was significantly decreased when α4GT1 RNA interference (RNAi) males were crossed with w1118 females, with only a few mature sperm being present in the seminal vesicle of α4GT1 RNAi flies. Immunofluorescence staining further revealed that the individualization complex (IC) in the testes from α4GT1 RNAi flies was scattered and did not move synchronically, compared with the clustered IC observed in the control flies. Terminal deoxyribonucleotide transferase (TdT)-mediated dUTP nick end labeling (TUNEL) assay showed that apoptosis signals in the sperm bundles of α4GT1 RNAi flies were significantly increased. Moreover, the expression of several individualization-related genes, such as Shrub, Obp44a and Hanabi, was significantly decreased, whereas the expression of several apoptosis-related genes, including Dronc and Drice, was significantly increased in the testes of α4GT1 RNAi flies. Together, these results suggest that α4GT1 may play dual roles in Drosophila spermatogenesis by regulating the sperm individualization process and maintaining the survival of sperm bundles.

Improved Prediction of Epidermal Growth Factor Receptor Status by Combined Radiomics of Primary Nonsmall-Cell Lung Cancer and Distant Metastasis.

OBJECTIVES: This study aimed to investigate radiomics based on primary nonsmall-cell lung cancer (NSCLC) and distant metastases to predict epidermal growth factor receptor (EGFR) mutation status. METHODS: A total of 290 patients (mean age, 58.21 ± 9.28) diagnosed with brain (BM, n = 150) or spinal bone metastasis (SM, n = 140) from primary NSCLC were enrolled as a primary cohort. An external validation cohort, consisting of 69 patients (mean age, 59.87 ± 7.23; BM, n = 36; SM, n = 33), was enrolled from another center. Thoracic computed tomography-based features were extracted from the primary tumor and peritumoral area and selected using the least absolute shrinkage and selection operator regression to build a radiomic signature (RS-primary). Contrast-enhanced magnetic resonance imaging-based features were calculated and selected from the BM and SM to build RS-BM and RS-SM, respectively. The RS-BM-Com and RS-SM-Com were developed by integrating the most important features from the primary tumor, BM, and SM. RESULTS: Six computed tomography-based features showed high association with EGFR mutation status: 3 from intratumoral and 3 from peritumoral areas. By combination of features from primary tumor and metastases, the developed RS-BM-Com and RS-SM-Com performed well with areas under curve in the training (RS-BM-Com vs RS-BM, 0.936 vs 0.885, P = 0.177; RS-SM-Com vs RS-SM, 0.929 vs 0.843, P = 0.003), internal validation (RS-BM-Com vs RS-BM, 0.920 vs 0.858, P = 0.492; RS-SM-Com vs RS-SM, 0.896 vs 0.859, P = 0.379), and external validation (RS-BM-Com vs RS-BM, 0.882 vs 0.805, P = 0.263; RS-SM-Com vs RS-SM, 0.865 vs 0.816, P = 0.312) cohorts. CONCLUSIONS: This study indicates that the accuracy of detecting EGFR mutations significantly enhanced in the presence of metastases in primary NSCLC. The established radiomic signatures from this approach may be useful as new predictors for patients with distant metastases.

MET overexpression correlated with prognosis of EGFR-mutant treatment­naïve advanced lung adenocarcinoma: a real­world retrospective study.

BACKGROUND: About 50-60% treatment-naïve advanced non-small-cell lung cancers were coexistence of epidermal growth factor receptor (EGFR) and mesenchymal epithelial transition (MET) overexpression. However, few studies demonstrated the prognostic value of MET protein expression in untreated EGFR-mutant lung adenocarcinoma (LUAD). METHODS: A total of 235 EGFR-mutant untreated advanced LUAD patients were retrospectively enrolled. MET expression was determined using immunohistochemistry, and MET positivity was defined as 2 + or 3 + using the METmab scoring algorithm. Progression-free survival (PFS) and overall survival (OS) were analysed according to MET expression status. Independent factors predicting prognosis were identified using multivariate Cox regression analyses. RESULTS: Of the 235 patients, 113 (48.1%) harboured exon 19 deletion (19_del), 103 (43.8%) had exon 21 L858R mutations, and 19 (8.1%) had other mutation types, including exon 21 L861Q, exon 18 G719A/C, exon 20 S768I, and L858R/19_del double mutations. MET-positive expression was observed in 192 (81.7%) cases. There was no significant difference in baseline clinicopathological characteristics between MET positivity and MET negativity groups. Patients were stratified by different EGFR mutation subtypes. MET-positive patients in the L858R mutation subgroup had markedly shorter PFS and OS than MET-negative patients (median PFS: 13 versus 27.5 months, p < 0.001; median OS: 29 versus not reached, p = 0.008), but no significant difference was observed in the 19_del subgroup. Multivariate Cox regression analyses indicated that MET positivity was an independent predictor for poor PFS and OS in L858R subgroup (PFS: HR = 3.059, 95% CI 1.552-6.029, p = 0.001; OS: HR = 3.511, 95% CI 1.346-9.160, p = 0.010). Additionally, an inferior survival outcome of MET positivity was observed in the L858R mutation subgroup when treated with EGFR-tyrosine kinase inhibitor (TKI) monotherapy as the first-line regimen (median PFS: 13 versus 36.5 months, p < 0.001; median OS: 29 versus not reached, p = 0.012) but not with EGFR-TKI plus platinum doublet chemotherapy. CONCLUSIONS: MET positive expression was an independent predictor of poor outcomes in untreated EGFR L858R mutation advanced LUAD patients treated with first-line EGFR-TKI monotherapy.

A novel GATA3 frameshift mutation causes hypoparathyroidism, sensorineural deafness, and renal dysplasia syndrome.

Background: Hypoparathyroidism, sensorineural deafness, and renal dysplasia (HDR) syndrome (Barakat syndrome) is a rare autosomal dominant disorder caused by mutations in the gene encoding GATA3 on chromosome 10p14. Method: Informed consent was obtained from a 38-year-old female patient. 5 mL of venous blood was collected and sent for whole-exome sequencing. GATA3 constructs of both wild-type and mutant were transfected into HEK-293 T cells. Three-dimensional modeling, luciferase-reporter gene test, western blotting and cellular immunofluorescence were used to evaluate the effect of the mutation. Results: A novel frameshift mutation c. 677dup(p.Pro227AlafsTer77), named P227Afs, was found in GATA3. Three-dimensional modeling revealed that the mutation caused the loss of the dual zinc finger structures 1 and 2 (ZNF1 and ZNF2) of the synthesized protein. Expression of wild-type GATA3 produced a six-fold increase in luciferase activity when compared with pcDNA3.1 vector only (P < 0.001), whereas the P227Afs mutant showed no increase. The mutation significantly reduced the transcriptional activity of GATA3. Immunofluorescence and western blotting analyses demonstrated that the mutation changed the nuclear location of GATA3 and caused difficulty in nuclearization. Conclusion: A novel heterozygous frameshift mutation in GATA3 was identified and showed to result in difficult nuclearization, and a dominant-negative effect on the wild-type.

Selective activation of IFNγ-ipilimumab enhances the therapeutic effect and safety of ipilimumab.

INTRODUCTION: Immune checkpoint inhibitor therapy is a highly promising strategy for clinical treatment of cancer. Among these inhibitors, ipilimumab stands out for its ability to induce cytotoxic T cell proliferation and activation by binding to CTLA-4. However, ipilimumab also gives rise to systemic immune-related adverse effects and tumor immune evasion, limiting its effectiveness. OBJECTIVES: We developed IFNγ-ipilimumab and confirmed that the addition of INF-γ does not alter the fundamental properties of ipilimumab. RESULTS: IFNγ-ipilimumab can be activated by matrix metalloproteinases, thereby promoting the IFNγ signaling pathway and enhancing the cytotoxicity of T cells. In vivo studies demonstrated that IFNγ-ipilimumab enhances the therapeutic effect of ipilimumab against colorectal cancer by increasing CD8+ and CD4+ lymphocyte infiltration into the tumor area and inducing MHC-I expression in tumor cells. Mice treated with IFNγ-ipilimumab showed higher survival rates and body weight, as well as lower CD4+ and CD8+ lymphocyte activation rates in the blood and reduced organ damage. CONCLUSION: IFNγ-ipilimumab improved the effectiveness of ipilimumab while reducing its side effects. It is likely that future immunotherapies would rely on such antibodies to activate local cancer cells or immune cells, thereby increasing the therapeutic effectiveness of cancer treatments and ensuring their safety.

Chronic exposure to ambient air pollution and the risk of non-alcoholic fatty liver disease: A cross-sectional study in Taiwan and Hong Kong.

BACKGROUND: Information on the relation of air pollution with non-alcoholic fatty liver disease (NAFLD) is scarce. We thus conducted a large cross-sectional study in Asia to investigate the role of air pollution in NAFLD. METHODS: We recruited 329,048 adults (mean age: 41.0 years) without other liver disease (hepatitis and cirrhosis) or excessive alcohol consumption in Taiwan and Hong Kong from 2001 to 2018. The concentrations of nitrogen dioxide (NO2) and ozone (O3) were estimated using a space-time regression model, and the concentrations of fine particulate matter (PM2.5) was evaluated using a satellite-based spatio-temporal model. NAFLD was determined using either the fatty liver index (FLI) or the hepatic steatosis index (HSI). The NAFLD-related advanced fibrosis was defined according to BARD score or the fibrosis-4 (FIB-4). A logistic regression model was adopted to explore the relationships of ambient air pollution with the odds of NAFLD and NAFLD-related advanced fibrosis. RESULTS: We found positive relationships between PM2.5 and the odds of NAFLD and advanced fibrosis, with every standard deviation (SD, 7.5 µg/m3) increases in PM2.5 exposure being associated with a 10% (95% confidence interval [CI]: 9%-11%) increment in the prevalence of NAFLD and an 8% (95% CI: 7%-9%) increment in the prevalence of advanced fibrosis. Similarly, the prevalence of NAFLD and advanced fibrosis increased by 8% (95% CI: 7%-9%) and 7% (95% CI: 6%-8%) with per SD (18.9 µg/m3) increasement in NO2 concentration, respectively. Additionally, for every SD (9.9 µg/m3) increasement in O3 concentration, the prevalence of NAFLD and advanced fibrosis decreased by 12% (95% CI: 11%-13%) and 11% (95% CI: 9%-12%), respectively. CONCLUSION: Higher ambient PM2.5 and NO2 are linked with higher odds of NAFLD and advanced fibrosis. Our findings indicate that reducing PM2.5 and NO2 concentrations may be an effective way for preventing NAFLD. Further studies on O3 are warranted.

The Phase Control of Transition Metallic Elements via Facile Chemical and Physical Syntheses.

The crystal phases of metals are important factors to tune the properties of metals, and therefore received extensive attention. Traditionally, phase control is performed within limited numbers of elements by harsh conditions, such as face-centered cubic Fe by high temperature. This review summarizes most reports in metal phase control area, including elements of Fe, Co, Ni, Cu, Ru, Pd, Rh, Os and Au. For every metallic element, the facile phase control methods are systematically introduced, such as epitaxial growth, ball milling, chemical reduction, etc. Their corresponding applications and the mechanisms for phase control are thoroughly discussed.

Angiotensin-converting enzyme 2 alleviates liver fibrosis through the renin-angiotensin system.

The present letter to the editor is related to the study titled 'Angiotensin-converting enzyme 2 improves liver fibrosis in mice by regulating autophagy of hepatic stellate cells'. Angiotensin-converting enzyme 2 can alleviate liver fibrosis by regulating autophagy of hepatic stellate cells and affecting the renin-angiotensin system.

The second complete mitochondrial genome of Capillidium rhysosporum within the family Capillidiaceae, Entomophthorales.

The complete mitochondrial genome of the entomophthoroid fungus Capillidium rhysosporum (strain no.: ATCC 12588) was sequenced using next-generation sequencing technology. The assembled circular genome has a length of 46,756 base pairs with a GC content of 27.06%. Gene prediction identified 15 core protein-coding genes (PCGs), two rRNA genes, and 27 tRNA genes. Phylogenetic analysis confirmed that C. rhysosporum belongs to the Zoopagomycota clade and is closely related to C. heterosporum. This study presents the second complete mitochondrial genome within the family Capillidiaceae, contributing to the mitochondrial DNA database of entomophthoroid fungi.