Category: Nevin Manimala

Front Immunol. 2022 Oct 10;13:1009912. doi: 10.3389/fimmu.2022.1009912. eCollection 2022.

ABSTRACT

AIMS: We conducted this study with two aims: (1) whether TRβ could be damaged by NAFLD, thereby represent thyroid hormone resistance-like manifestation and (2) to analyze the potential role of SPP1 in TH signaling pathway on the process of NAFLD. This study is expected to provide a new perspective on the therapeutic mechanism in the pathological course of NAFLD.

METHODS: A total of 166 patients diagnosed with type 2 diabetes mellitus (T2DM) were enrolled in this study. All patients had a BMI above 24 kg/m2 and were stratified into two groups: NAFLD and Non-NAFLD groups. Ages, gender, BMI, duration of diabetes and biochemical markers were obtained from participants’ records. We downloaded the dataset GSE48452 from GEO. The Pathview library was used to make the thyroid hormone signaling pathway visualization. The CIBERSORT algorithm was applied to calculate the infiltrated immune cells in obese NAFLD patients. C57BL/6 mice were randomly selected to constitute the normal control (NC) group and were fed a normal chow diet; the rest of the mice were fed a high-fat diet (HFD). After 12 weeks HFD feeding, the mice were sacrificed by cervical dislocation, and blood samples were collected. Mouse livers were also collected; one part of each liver was fixed in 10% formalin for histological analysis, and the other part was snap-frozen for subsequent molecular analyses. To explore the relationship between SPP1, TRβ and lipid deposition in hepatocytes, HepG2 cells were treated with 50 μ M concentration of PA and/or 20 ng/ml concentration of rh-SPP1 for 48h. In addition, the PC3.1-TRβ plasmid was constructed for further validation in HepG2 cells. We used THP-1 cells to construct an M1 macrophage model in vitro. We then analyzed THP-1 cells treated with various concentrations of PA or TSH.

RESULTS: (1) After adjusting for all factors that appeared P value less than 0.1 in the univariate analysis, BMI, TSH, and FT3 were significant independent risk factors of NAFLD (ORs were 1.218, 1.694, and 2.259, respectively); (2) A further analysis with BMI stratification indiacted that both FT3 and TSH had a significant change between individuals with NAFLD and Non-NAFLD in obesity subgroup; however, there was no statistic difference in over-weight group; (3) Bioinformatics analysis of GSE48452 had shown that several key molecular (including TRβ) of thyroid hormone pathway affected by NAFLD induced transcriptomic changes and the expression levels of SPP1, FABP4 and RPS4Y1 were significantly higher, while the expression levels of PZP and VIL1 were significantly decreased in NAFLD patients(adjusted p < 0.05, |logFC| > 1.0). The CIBERSORT algorithm showed increased M0 and M1, decreased M2 macrophage infiltration in NAFLD with comparison to healthy obese group; (4) After 12 weeks of HFD-feeding, the obesity mice had significantly higher serum TSH and In IHC-stained liver sections of obesity group, the intensity of SPP1 had a significantly increased, while TRβ reduced; (5) In vitro studies have shown SPP1 aggravated lipid deposition in hepatic cells dependent on down-regulating the expression of TRβ and TSH acts to promote secretion of SPP1 in M1 macrophage cells.

CONCLUSIONS: SPP1 secretion induced by M1 macrophage polarization, which may down-regulates TRβ in hepatocytes via paracrine manner, on the one hand, the lipid deposition aggravating in liver, on the other hand, a compensatory increase of TSH in serum. The increased TSH can further lead to the following SPP1 secretion of M1 macrophage. The positive feedback crosstalk between thyroid and liver, may be plays an important role in maintaining and amplifying pathological process of NAFLD.

PMID:36300106 | PMC:PMC9589424 | DOI:10.3389/fimmu.2022.1009912

Front Oncol. 2022 Oct 10;12:1005962. doi: 10.3389/fonc.2022.1005962. eCollection 2022.

ABSTRACT

BACKGROUND: Approximately 80% of lung cancers are non-small cell lung cancers (NSCLC). Lung adenocarcinoma (LUAD) is the main subtype of NSCLC. The incidence and mortality of lung cancer are also increasing yearly. Myogenic differentiation family inhibitor (MDFI) as a transcription factor, its role in lung cancer has not yet been clarified.

METHODS: LUAD data were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO), analyzed and plotted using the R language. Associations between Clinical information and MDFI expression were assessed using logistic regression analyses to explore the effects of MDFI on LUAD. Two sets of tissue microarrays (TMAs) further confirmed the overexpression of MDFI in LUAD and its impact on prognosis. In addition, we examined the correlation between MDFI and immune infiltration. To investigate the effect of MDFI on the biological behavior of LUAD tumor cells by GSEA and GO/KEGG analysis. The survival status and somatic mutational characteristics of patients according to MDFI levels were depicted and analyzed.

RESULTS: Expression of high MDFI in LUAD tissues via analyzing TCGA dataset (P <0.001). Kaplan-Meier survival analysis indicated a poor prognosis for those patients with LUAD who had upregulated MDFI expression levels (P <0.001). This was also verified by two groups of TMAs (P=0.024). Using logistic statistics analysis, MDFI was identified as an independent predictive factor and was associated with poor prognosis in LUAD (P <0.001, P =0.021). Assessment of clinical characteristics, tumor mutation burden (TMB), and tumor microenvironment (TME) between high- and low-expression score groups showed lower TMB, richer immune cell infiltration, and better prognosis in the low-risk group.

CONCLUSION: This study showed that MDFI was overexpressed in LUAD and was significantly associated with poor prognosis, indicating that MDFI may be used as a potential novel biomarker for the diagnosis and prognosis of LUAD. MDFI is associated with immune infiltration of LUAD and it is reasonable to speculate that it plays an important role in tumor proliferation and spread. In view of the significant differences in MDFI expression between different biological activities, LUAD patients with MDFI overexpression may obtain more precise treatment strategies in the clinic.

PMID:36300089 | PMC:PMC9589366 | DOI:10.3389/fonc.2022.1005962

Commun Biol. 2022 Oct 26;5(1):1133. doi: 10.1038/s42003-022-04073-6.

ABSTRACT

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome.

PMID:36289370 | DOI:10.1038/s42003-022-04073-6

Sci Rep. 2022 Oct 26;12(1):17955. doi: 10.1038/s41598-022-22839-0.

ABSTRACT

Progress has been made in COVID-19 vaccine development, with encouraging safety and efficacy data. The purpose of this study was to investigate the immunogenicity of inactivated COVID-19 vaccine in patients with autoimmune inflammatory rheumatic diseases (AIIRD). Patients with AIIRD (n = 101) were included in this study. All patients received 2 doses of inactivated COVID-19 vaccine. Serum anti-S1/RBD protein IgG was detected 2-16 weeks after the second vaccination. Seropositivity was defined as IgG ≥ 1.00 bound antibody unit S/CO. Immunogenicity of inactivated COVID-19 vaccine was assessed by seropositivity rate and the levels of serum IgG antibody against anti-S1/RBD protein, compared with the general population (n = 46). There was no difference by statistical significance in the seropositivity rate between patients with AIIRD (82.2%) and SLE (86.1%) and the control group (93.5%), p > 0.05. The level of anti-S1/RBD protein IgG antibodies in patients with AIIRD (median [IQR], 8.8 [2.2-17.3]) and SLE (median [IQR], 9.6 [2.4-20.4]) was comparable to that in the control group (median [IQR], 7.2 [3.1-14.2]), p > 0.05. Patients treated with glucocorticoids(GCs) (median dose, [IQR]: 2.5 mg/day [IQR 2.5-5.0]) or hydroxychloroquine(HCQ) or GCs + HCQ without other immunomodulatory medications, had an appropriate immunogenic response(88.1%) with high levels of anti-S1/RBD protein IgG(median [IQR], 12.1 [6.5-20.4]). Neither of patients treated with rituximab had positive serum antibodies, which was statistically significant, compared with the control group (p < 0.01). Compared with the control group, methotrexate(MTX) and iguratimod(IGU) was significantly reduced the level of anti-S1/RBD protein IgG antibodies. Inactivated COVID-19 vaccine had appropriate immunogenicity in patients with AIIRD. Immunogenicity of inactivated COVID-19 vaccine was severely impaired by rituximab, and also suppressed by MTX and IGU, while low doses of GC and HCQ had negligible effect.

PMID:36289319 | DOI:10.1038/s41598-022-22839-0

Sci Rep. 2022 Oct 26;12(1):17916. doi: 10.1038/s41598-022-22933-3.

ABSTRACT

Feature classification in digital medical images like mammography presents an optimization problem which researchers often neglect. The use of a convolutional neural network (CNN) in feature extraction and classification has been widely reported in the literature to have achieved outstanding performance and acceptance in the disease detection procedure. However, little emphasis is placed on ensuring that only discriminant features extracted by the convolutional operations are passed on to the classifier, to avoid bottlenecking the classification operation. Unfortunately, since this has been left unaddressed, a subtle performance impairment has resulted from this omission. Therefore, this study is devoted to addressing these drawbacks using a metaheuristic algorithm to optimize the number of features extracted by the CNN, so that suggestive features are applied for the classification process. To achieve this, a new variant of the Ebola-based optimization algorithm is proposed, based on the population immunity concept and the use of a chaos mapping initialization strategy. The resulting algorithm, called the immunity-based Ebola optimization search algorithm (IEOSA), is applied to the optimization problem addressed in the study. The optimized features represent the output from the IEOSA, which receives the noisy and unfiltered detected features from the convolutional process as input. An exhaustive evaluation of the IEOSA was carried out using classical and IEEE CEC benchmarked functions. A comparative analysis of the performance of IEOSA is presented, with some recent optimization algorithms. The experimental result showed that IEOSA performed well on all the tested benchmark functions. Furthermore, IEOSA was then applied to solve the feature enhancement and selection problem in CNN for better prediction of breast cancer in digital mammography. The classification accuracy returned by the IEOSA method showed that the new approach improved the classification process on detected features when using CNN models.

PMID:36289321 | DOI:10.1038/s41598-022-22933-3

Sci Rep. 2022 Oct 26;12(1):18002. doi: 10.1038/s41598-022-22927-1.

ABSTRACT

Human body awareness is adaptive to context changes. The illusory sense of body ownership has been studied since the publication of the rubber hand illusion, where ambiguous body ownership feeling was first defined. Phenomenologically, the ambiguous body ownership is attributed to a conflict between feeling and judgement: it characterises a discrepancy between first- and third-person processes. Although Bayesian inference can explain this malleability of body image, it still fails to relate the subjective feeling to physiological data. This study attempts to explain subjective experience during rubber hand illusions by using integrated information theory (IIT). The integrated information [Formula: see text] in IIT measures the difference between the whole system and its subsystems. By analysing seven different time-series of physiological data representing a small body-brain system, we demonstrate that the integrity of the whole system during the illusion decreases, while the integrity of its subsystems increases. These general tendencies agree with many brain-image analyses and subjective reports; furthermore, we found that subjective ratings as ambiguous body ownership were associated with [Formula: see text]. Our result suggests that IIT can explain the general tendency of the sense of ownership illusions and individual differences in subjective experience during the illusions.

PMID:36289318 | DOI:10.1038/s41598-022-22927-1

Sci Rep. 2022 Oct 26;12(1):18023. doi: 10.1038/s41598-022-20416-z.

ABSTRACT

Rubber tree (Hevea brasiliensis) is the main feedstock for commercial rubber; however, its long vegetative cycle has hindered the development of more productive varieties via breeding programs. With the availability of H. brasiliensis genomic data, several linkage maps with associated quantitative trait loci have been constructed and suggested as a tool for marker-assisted selection. Nonetheless, novel genomic strategies are still needed, and genomic selection (GS) may facilitate rubber tree breeding programs aimed at reducing the required cycles for performance assessment. Even though such a methodology has already been shown to be a promising tool for rubber tree breeding, increased model predictive capabilities and practical application are still needed. Here, we developed a novel machine learning-based approach for predicting rubber tree stem circumference based on molecular markers. Through a divide-and-conquer strategy, we propose a neural network prediction system with two stages: (1) subpopulation prediction and (2) phenotype estimation. This approach yielded higher accuracies than traditional statistical models in a single-environment scenario. By delivering large accuracy improvements, our methodology represents a powerful tool for use in Hevea GS strategies. Therefore, the incorporation of machine learning techniques into rubber tree GS represents an opportunity to build more robust models and optimize Hevea breeding programs.

PMID:36289298 | DOI:10.1038/s41598-022-20416-z

Sci Rep. 2022 Oct 26;12(1):17979. doi: 10.1038/s41598-022-22341-7.

ABSTRACT

Currently, there is no specific pharmaceutical agent for treating acute pancreatitis (AP). Somatostatin and its analogues have been used to prevent the autolysis of the pancreas in AP, however, their effectiveness has not been confirmed. This investigation aimed to examine the efficacy of ulinastatin, a protease inhibitor, combined with somatostatin analogues in the treatment of AP. We conducted a systematic database search in 4 databases to identify randomized controlled trials in which the efficacy of ulinastatin in combination with somatostatin analogue was compared to somatostatin analogue alone in patients with AP. Since the patient populations of analysed papers were slightly different, we used random effect models to pool odds ratios (OR) and mean differences (MD) and the corresponding 95% confidence intervals (CI). A total of 9 articles comprising 1037 patients were included in the meta-analysis. The combination therapy significantly reduced the complication rates for acute respiratory distress syndrome, acute kidney injury, and multiple organ dysfunction. Symptoms were relieved threefold with the combination therapy compared to somatostatin alone, and combination therapy significantly shortened the length of hospital stay. The decrease in mortality was not statistically significant..

PMID:36289288 | DOI:10.1038/s41598-022-22341-7

Sci Rep. 2022 Oct 26;12(1):18003. doi: 10.1038/s41598-022-21979-7.

ABSTRACT

Bloodstream infections (BSIs) are a prominent cause of death and hospitalization among hemodialysis (HD) patients. The emergence of multidrug-resistant organisms (MDRO) is making the management of these infections more challenging. This study describes the clinical characteristics, microbial profiles and antibiotic resistance patterns in patients with BSIs. A retrospective cross-sectional study was conducted at An-Najah National University Hospital from January 2019 to December 2020. Clinical and demographic data regarding BSIs were collected from the hospital information system. Data regarding bacterial isolates and the antimicrobial resistance of BSIs were collected from the microbiology lab. Data were entered and analyzed using version 21 of the Statistical Package for Social Sciences program (IBM-SPSS). 111 BSIs occurred during the study period, with a rate of 1.5 infections per 100 patient-months. These patients had been on HD for the median duration of 747 (360, 1825) days and 62.2% had already had a BSI before the study period. 118 microorganisms were isolated; 99 (83.89%) were gram-positive and 19 (16.1%) were gram-negative. Among the gram-positive isolates, coagulase-negative staphylococci (CoNS) (88, 74.57%) were predominant. As for the gram-negative isolates, the most frequent were both Stenotrophomonas maltophilia and Escherichia coli, with five (4.23%) positive cultures each. Among the latter, two were Extended-Spectrum Beta-Lactamase producing (ESBL) (1.69%). The most frequently used empiric antibiotics were a combination of vancomycin and gentamicin (27%), followed by vancomycin alone (24.3%). Regarding gram-positive isolates, vancomycin was the most frequently used and effective antibiotic after cultures, whereas for gram-negative bacteria, it was found to be gentamicin. MDROs were defined as those resistant to at least one agent in three or more antimicrobial categories. 89 (75.4%) isolates were found to be MDRO, 85 (85.85%) gram-positive bacteria and 4 (21%) gram-negative bacteria. When comparing patients according to the type of vascular access, 66 (75%) infections with MDRO were found among patients with central venous catheters (CVCs). However, no statistically significant relationship was found between the type of vascular access and infection with MDRO (p = 0.523). MDRO cause a remarkably high proportion of BSIs in Palestinian patients. The results of this study support the empiric use of vancomycin and gentamicin to treat these infections. It is vital that health care providers prevent these infections via instituting and adhering to infection control policies in hemodialysis centers and providing proper antibiotic therapy of limited use and duration when necessary to avoid breeding resistance.

PMID:36289278 | DOI:10.1038/s41598-022-21979-7

Sci Rep. 2022 Oct 26;12(1):17950. doi: 10.1038/s41598-022-22932-4.

ABSTRACT

People with type 1 diabetes have a substantially increased risk of premature death. This nationwide, register-based cohort study evaluated the significance of risk factors and previous cardiovascular disease (CVD), heart failure and chronic kidney disease (CKD), for mortality in type 1 diabetes. Nationwide, longitudinal, register-based cohort study. Patients (n = 36,303) listed in the Swedish National Diabetes Register between January 1 2015 and December 31 2017 were included and followed until December 31, 2018. Data were retrieved from national health registries through each patient’s unique identifier, to capture data on clinical characteristics, outcomes, or deaths, to describe mortality rates in risk groups. The mean follow-up time was 3.3 years, with 119,800 patient years of observation and 1127 deaths, corresponding to a crude overall mortality of 0.92% deaths/year. Statistically significant increased risk in multivariate analyzes was found in older age groups, in men, and in underweight or people with normal BMI, high HbA1c or blood pressure. A history of CVD, albuminuria and advanced stages of CKD was associated with an increased risk of mortality. Each combination of these conditions further increased the risk of mortality. These results emphasize the importance of risk factors and cardiovascular and renal diabetes complications. People with a combination of CKD, CVD, and heart failure, exhibit a markedly increased risk of dying prematurely. These findings provide strong arguments for optimized and individualized treatment of these groups of people with type 1 diabetes in clinical everyday life.

PMID:36289275 | DOI:10.1038/s41598-022-22932-4