Nat Rev Genet. 2022 Mar 31. doi: 10.1038/s41576-022-00482-9. Online ahead of print.
NO ABSTRACT
PMID:35361926 | DOI:10.1038/s41576-022-00482-9
Sci Rep. 2022 Mar 31;12(1):5458. doi: 10.1038/s41598-022-09544-8.
ABSTRACT
Type III interferons (IFNs) play an important role in respiratory viral infections, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to determine whether the expression of serum type III IFNs predicted disease severity among patients with the coronavirus disease (COVID-19). A retrospective cohort study was conducted of patients admitted to a single hospital between March 21, 2020, and March 31, 2021. Patients were divided into mild to moderate I (MM) and moderate II to severe (MS) groups based on the COVID-19 severity classification developed by the Japanese Ministry of Health, Labor and Welfare. A total of 257 patients were included in the analysis. Human interleukin-28A (IL-28A/IFN-λ2) expression was significantly lower, and interleukin (IL)-6 expression was significantly higher in the MS group than in the MM group (both p < 0.001). In addition, IL-28A/IFN-λ2 was statistically significantly inversely correlated with the time from disease onset to negative SARS-CoV-2 PCR results (p = 0.049). Multivariable logistic regression analysis showed that IL-28A/IFN-λ2 was an independent predictor of disease severity (p = 0.021). The low expression of IL-28A/IFN-λ2 may serve as a serum biomarker that predicts the severity of COVID-19, possibly through the mechanism of delayed viral elimination.
PMID:35361913 | DOI:10.1038/s41598-022-09544-8
Professional organizations in science, technology, engineering and mathematics (STEM) fields could more effectively collect data on underrepresented groups in their fields, according to a new survey. With more robust information, STEM organizations could better target efforts to recruit and retain a more diverse membership.
Arthritis Rheumatol. 2022 Mar 31. doi: 10.1002/art.42133. Online ahead of print.
ABSTRACT
OBJECTIVE: Hand dysfunction is common in systemic sclerosis (SSc). The objective of this study was to evaluate the capacity of autologous Adipose-Derived Regenerative Cells (ADRCs) to improve hand function in SSc patients.
METHODS: The STAR Trial was a prospective, randomized, double-blind trial of ADRCs injected into each finger digit of subjects with SSc. The primary endpoint was change in hand function at 24 and 48 weeks assessed using the Cochin Hand Function Scale (CHFS). Secondary endpoint included the change in Health Assessment Questionnaire-Disability Index (HAQ-DI) at 48 weeks. Separate analysis of subjects with diffuse (dcSSc) and limited cutaneous SSc (lcSSc) was pre-specified.
RESULTS: 88 subjects were randomized to ADRCs (n=48; 32 dSSc:16 lcSSc) or Placebo (n=40; 19 dcSSc: 21 lcSSc). The primary end point was numerically higher for the ADRC group but did not achieve statistical significance (8.9±10.5 vs. 11.0±12.5, p= 0.299). For subjects with dcSSc the between group difference for the CHFS at 48 weeks was 6.3 points (nominal p=0.069). The HAQ-DI secondary endpoint exhibited a difference of 0.17 points (nominal p=0.044) for dcSSc group. 52% of ADRC-treated subjects with dcSSc reported improvement greater than the minimal clinically important difference for both CHFS and HAQ-DI compared with 16% in the placebo group (nominal p=0.016). Small volume adipose harvest and ADRC-treatment was well-tolerated.
CONCLUSION: While the primary end point of this trial was not achieved, efficacy trends were observed in subjects with dcSSc. Adipose harvest and ADRC injection were demonstrated to be feasible. Further clinical trial of this intervention in dcSSc is warranted.
PMID:35358372 | DOI:10.1002/art.42133
Am J Hematol. 2022 Mar 31. doi: 10.1002/ajh.26551. Online ahead of print.
NO ABSTRACT
PMID:35358346 | DOI:10.1002/ajh.26551
Med Phys. 2022 Mar 31. doi: 10.1002/mp.15639. Online ahead of print.
ABSTRACT
PURPOSE: Novel CT reconstruction techniques strive to maintain image quality and processing efficiency. The purpose of this study is to investigate the impact of a newer hybrid iterative reconstruction technique, Adaptive Statistical Iterative Reconstruction-V (ASIR-V) in combination with various CT scan parameters on the semi-automated quantification using various lung nodules.
METHODS: A chest phantom embedded with eight spherical objects was scanned using varying CT parameters such as tube current and ASIR-V levels. We calculated absolute percentage error (APE) and mean APE (MAPE) using differences between the semi-automated measured diameters and known dimensions. Predictive variables were assessed using a multivariable general linear model. The linear regression slope coefficients (β) were reported to demonstrate effect size and directionality.
RESULTS: The APE of the semi-automated measured diameters was higher in ground-glass than solid nodules (β = 9.000, p<0.001). APE had an inverse relationship with nodule diameter (mm; β = -3.499, p<0.001) and tube current (mA; β = -0.006, p<0.001). MAPE did not vary based on the ASIR-V level (range: 5.7-13.1%).
CONCLUSION: Error is dominated by nodule characteristics with a small effect of tube current. Regardless of phantom size, nodule size accuracy is not affected by tube voltage or ASIR-V level, maintaining accuracy while maximizing radiation dose reduction. This article is protected by copyright. All rights reserved.
PMID:35358333 | DOI:10.1002/mp.15639
J Pathol. 2022 Mar 31. doi: 10.1002/path.5900. Online ahead of print.
ABSTRACT
A thickened, white patch – leukoplakia – in the oral cavity is usually benign, but sometimes (in ~9% of individuals) progresses to malignant tumour. Because the genomic basis of this progression is poorly understood, we undertook this study and collected samples of four tissues – leukoplakia, tumour, adjacent normal and blood -from each of 28 patients suffering from gingivobuccal oral cancer. We performed multi-omics analysis of the 112 collected tissues (4 tissues per patient from 28 patients) and integrated information on progressive changes in mutational and transcriptional profiles of each patient to create this genomic narrative. Additionally, we generated and analysed whole-exome sequence data from leukoplakia tissues collected from 11 individuals not suffering from oral cancer. Non-synonymous somatic mutations in CASP8 gene were identified as the likely events to initiate malignant transformation, since these were frequently shared between tumour and co-occurring leukoplakia. CASP8 alterations were also shown to enhance expressions of genes that favours lateral spread of mutant cells. During malignant transformation, additional pathogenic mutations are acquired in key genes (TP53, NOTCH1, HRAS) (41% of patients); chromosomal-instability (arm-level deletions of 19p and q, focal-deletion of DNA-repair pathway genes and NOTCH1, amplification of EGFR) (77%) and increased APOBEC-activity (23%) are also observed. These additional alterations were present singly (18% of patients) or in combination (68%). Some of these alterations likely impact on immune-dynamics of the evolving transformed tissue; progression to malignancy is associated with immune suppression through infiltration of regulatory T-cells (56%), depletion of cytotoxic T-cells (68%) and antigen presenting dendritic cells (72%) with concomitant increase in inflammation (92%). Patients can be grouped into three clusters by the estimated time to development of cancer from precancer by acquiring additional mutations (Range: 4-10 years). Our findings provide deep molecular insights into the evolutionary processes and trajectories of oral cancer initiation and progression. This article is protected by copyright. All rights reserved.
PMID:35358331 | DOI:10.1002/path.5900
Spec Care Dentist. 2022 Mar 31. doi: 10.1111/scd.12716. Online ahead of print.
ABSTRACT
AIM: To compare prevalence of oral hygiene status, dental trauma and malocclusion among institutionalized visually impaired (VI) and non-visually impaired (NVI) adolescents in Lagos State, Nigeria.
METHODS AND RESULTS: A cross sectional study conducted among institutionalized VI and NVI adolescents in Lagos State, Nigeria. One hundred and thirty-two randomly selected VI adolescents aged between 9 and 23 years and 138 NVI participants aged between 9 and 17 years were recruited using a multi-stage random sampling technique. Oral examination assessed oral hygiene status, dental trauma and malocclusion. Data entry and analysis was by SPSS version 20. Associations were analyzed using chi-square test. Statistical significance was set at p < .05. Male to female ratio among the VI and NVI participants, were 1.5:1 and 1:3, mean ages were 15.03 ± 3.36 and 12.96 years ± 1.89 SD, prevalence of dental injury were 16.67% and 7.2% and malocclusion were 15.2% and 11.6% respectively. More of the NVI participants had good oral hygiene status (29.0%).
CONCLUSION: Uncomplicated dental injury was more prevalent among the VI male participants than their NVI counterparts while malocclusion was significantly less among the NVI participants. There is an urgent need for the development of policy and protocol on oral health of persons with special needs.
PMID:35358330 | DOI:10.1111/scd.12716
Cancer Res. 2022 Mar 31:canres.3074.2021. doi: 10.1158/0008-5472.CAN-21-3074. Online ahead of print.
ABSTRACT
Overtreatment remains a pervasive problem in prostate cancer (PCa) management due to the highly variable and often indolent course of disease. Molecular signatures derived from gene expression profiling have played critical roles in guiding PCa treatment decisions. Many gene expression signatures have been developed to improve the risk stratification of PCa and some of them have already been applied to clinical practice. However, no comprehensive evaluation has been performed to compare the performance of these signatures. In this study, we conducted a systematic and unbiased evaluation of 15 machine learning (ML) algorithms and 30 published PCa gene expression-based prognostic signatures leveraging 10 transcriptomics datasets with 1,558 primary PCa patients from public data repositories. This analysis revealed that survival analysis models outperformed binary classification models for risk assessment, and the performance of the survival analysis methods – Cox model regularized with ridge penalty (Cox-Ridge) and partial least squares regression for Cox model (Cox-PLS) – were generally more robust than the other methods. Based on the Cox-Ridge algorithm, several top prognostic signatures displayed comparable or even better performance than commercial panels. These findings will facilitate the identification of existing prognostic signatures that are promising for further validation in prospective studies and promote the development of robust prognostic models to guide clinical decision-making. Moreover, this study provides a valuable data resource from large primary PCa cohorts, which can be used to develop, validate, and evaluate novel statistical methodologies and molecular signatures to improve PCa management.
PMID:35358302 | DOI:10.1158/0008-5472.CAN-21-3074
Biostatistics. 2022 Mar 31:kxac005. doi: 10.1093/biostatistics/kxac005. Online ahead of print.
ABSTRACT
Integrative analysis of multiple data sets has the potential of fully leveraging the vast amount of high throughput biological data being generated. In particular such analysis will be powerful in making inference from publicly available collections of genetic, transcriptomic and epigenetic data sets which are designed to study shared biological processes, but which vary in their target measurements, biological variation, unwanted noise, and batch variation. Thus, methods that enable the joint analysis of multiple data sets are needed to gain insights into shared biological processes that would otherwise be hidden by unwanted intra-data set variation. Here, we propose a method called two-stage linked component analysis (2s-LCA) to jointly decompose multiple biologically related experimental data sets with biological and technological relationships that can be structured into the decomposition. The consistency of the proposed method is established and its empirical performance is evaluated via simulation studies. We apply 2s-LCA to jointly analyze four data sets focused on human brain development and identify meaningful patterns of gene expression in human neurogenesis that have shared structure across these data sets.
PMID:35358296 | DOI:10.1093/biostatistics/kxac005