Tag: statistics

Scand J Psychol. 2021 Sep 15. doi: 10.1111/sjop.12771. Online ahead of print.

ABSTRACT

According to the literature, avoidant personality disorder (APD) is often overlooked in research on personality disorders. In the present study, patients with APD were compared to patients with borderline personality disorder (BPD) with respect to emotional dysfunction. Emotional dysfunction was operationalized through the Affect Integration Inventory. Sixty-one patients receiving treatment at specialized outpatient hospital facilities for either BPD (n = 25) or APD (n = 36) (Diagnostic and Statistical Manual of Mental Disorders, fifth edition) were included in a cross-sectional study. Supporting our expectations of no difference in the global capacity for affect integration between groups, the estimated difference was 0.00 (95% confidence interval [CI] [-0.53, 0.53]). On the other hand, the expected increased dysfunction in APD regarding Expression could not be confirmed. Furthermore, problems with specific affects distinguished the groups; integration of Interest was worse in APD (p = 0.01), whereas integration of Jealousy was worse in BPD (p = 0.04). In terms of prototypical modes of experiencing affects, APD was characterized by decreased access to the motivational properties of Interest (p < 0.01), while BPD was more driven by Interest (p < 0.01), Anger (p < 0.01), and Jealousy (p = 0.01). In conclusion, even though the two disorders are characterized by similar overall levels of emotional dysfunction, they differ systematically and predictably regarding specific affects and modes of experiencing. These findings carry implications for the understanding of emotional dysfunction in APD and BPD, suggesting specific areas of emotional dysfunction that could be targeted in tailored psychotherapeutic interventions.

PMID:34523729 | DOI:10.1111/sjop.12771

Australas J Dermatol. 2021 Sep 15. doi: 10.1111/ajd.13721. Online ahead of print.

ABSTRACT

BACKGROUND/OBJECTIVE: Recent studies have described an association between altered skin microbial community and epidemiology of skin diseases, such as vitiligo, atopic dermatitis and psoriasis. In this study, we conducted microbiological analysis on patients at different stages of vitiligo to determine whether the dysbiosis is associated with disease progression.

METHODS: To characterise the skin microbes in vitiligo patients, we profiled samples collected from 40 patients with active and stable vitiligo using the Novaseq sequencer. Alpha diversity was used to measure richness and uniformity, while Beta diversity (Non-Metric Multi-Dimensional Scaling) analysis was used to show the differences. Moreover, the species differences were evaluated by LEfSe analysis and the flora gene function was predicted using Statistical Analysis of Metagenomic Profiles (STAMP).

RESULTS: The alpha diversity results showed no significant differences between active vitiligo and stable vitiligo, while beta diversity and LEfSe analysis results showed the differences in community composition. Streptomyces and Streptococcus were enriched in active vitiligo compared to stable vitiligo. In addition, the flora gene function of mixed acid fermentation was more pronounced in active vitiligo, while the function of lipid IVA biosynthesis was more significant in stable vitiligo.

CONCLUSION: This study has shown the differences in epidermal microbes between active vitiligo and stable vitiligo. Our results suggest that maintaining the flora balance might be a potential therapeutic target for vitiligo.

PMID:34523726 | DOI:10.1111/ajd.13721

Hum Mol Genet. 2021 Sep 15:ddab273. doi: 10.1093/hmg/ddab273. Online ahead of print.

ABSTRACT

OBJECT: Observational studies provide evidence that metabolites may be involved in the development of autoimmune diseases (ADs), but whether it is causal is still unknown.

METHODS: Based on the large-scale GWAS summary statistics, two-sample Mendelian randomization (MR) was performed to evaluate the causal association between human serum metabolites and multiple ADs, which were inflammatory bowel disease (IBD), ulcerative Colitis (UC), crohn’s disease (CD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Comprehensive sensitive analysis was used to validate the robustness of MR results and multivariable MR analysis was conducted to avoid potential pleiotropic effect of other complex traits. Finally, metabolic pathway analysis was performed based on causal metabolites for each ad, respectively.

RESULTS: We identified 6 causal features of metabolite after Bonferroni adjustment, i.e. glycerol 2-phosphate for T1D, hexadecanedioate, phenylacetylglutamine and laurylcarnitine for RA, glycine and arachidonate (20:4n6) for CD. Then comprehensively sensitive analysis proved the robustness of the causal associations. We also observed some overlaps of metabolites among different ADs, indicating the similar mechanisms. After controlling for several common traits, multivariable MR analysis ruled out most of potential pleiotropic effects and validated the independence of identified metabolites. Additionally, a total of 6 metabolic pathways have been identified for different ADs.

CONCLUSIONS: This study provided novel insights into investigating causal role of serum metabolites in development of multiple ADs through a comprehensive genetic pathway.

PMID:34523675 | DOI:10.1093/hmg/ddab273

Alcohol Clin Exp Res. 2021 Sep 15. doi: 10.1111/acer.14712. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic alcohol consumption is associated with structural brain changes and increased inflammatory signaling throughout the brain and body. Increased inflammation in the brain has been associated with structural brain damage. Recent studies have also shown that neurofilament light polypeptide (NfL) is released into circulation following neuronal damage. NfL has thus been proposed as a biomarker for neurodegenerative diseases but has not been explored in connection with alcohol use disorder. For this secondary data analysis, we proposed a conceptual model linking alcohol consumption, the pro-inflammatory cytokine IL-6, brain structure and NfL in heavy-drinking participants.

METHODS: Of the 182 individuals enrolled in this study, 81 participants had useable gray matter (GM) data and 80 had useable white matter (WM) data. A subset of these had NfL (n = 78) and IL-6 (n = 117) data. GM thickness was extracted from middle frontal brain regions using Freesurfer. Mean WM diffusivity values were extracted from Tract Based Spatial Statistics. NfL and IL-6 were measured from blood. Regression models were used to test individual linkages in the conceptual model. Based on significant regression results, we created a simplified conceptual model which was tested using path analysis.

RESULTS: In regressions, negative relationships emerged between GM and both drinks per drinking day (DPDD) (p = .018) and NfL (p = .004). A positive relationship emerged between WM diffusivity and DPDD (p =.033). IL-6 was not significantly associated with alcohol use, GM or WM. The final path model demonstrated adequate fit to the data and showed significant, negative associations between DPDD and middle frontal gyrus (MFG) Thickness and between MFG Thickness and NfL, but a non-significant association between DPDD and NfL.

CONCLUSIONS: Data suggest that drinking is associated with lower GM thickness and higher WM diffusivity and that lower GM thickness is associated with higher circulating NfL. This is the first study to demonstrate an association between brain structure and NfL in a sample of heavy drinkers.

PMID:34523725 | DOI:10.1111/acer.14712

Phys Chem Chem Phys. 2021 Sep 15. doi: 10.1039/d1cp02591k. Online ahead of print.

ABSTRACT

In this paper, we have proposed a first-principles methodology to screen transition metal complexes against a particular organic solvent and organic solvents against a particular transition metal complex based on their solubility information without the knowledge of heat of fusion and melting temperature. The energy density of a non-aqueous redox flow cell directly depends on the solubility of the redox active species in the non-aqueous medium. We have used the “COSMOSAC-LANL” activity coefficient model (A. Karmakar, R. Mukundan, P. Yang and E. R. Batista, RSC Adv., 2019, 18506-18526; A. Karmakar and R. Mukundan, Phys. Chem. Chem. Phys., 2019, 19667-19685) which is based on first-principles COSMO calculations where the microscopic information is passed to the macroscopic world via a dielectric continuum solvation model, followed by a post-statistical thermodynamic treatment of the self-consistent properties of the solute particle to calculate the solubility. To model the activity coefficient at infinite dilution for the binary mixtures, a 3-suffix Margules (3sM) function is introduced for the quantitative estimation of the asymmetric interactions and, for the combinatorial term, the Staverman-Guggenheim (SG) form is used. The new activity coefficient model is separately called the “LANL” activity coefficient model. The metal complex and the organic solvent have been treated as a simple binary mixture. The present model has been applied to a set of 14 different organic solvents and 16 different transition metal complexes. Using the new LANL activity coefficient model in combination with the ADF-COSMOSAC-2013 model, we have shown how one can improve the solubility of a transition metal complex in an organic solvent. We applied our model to screen 84 binary mixtures to predict the compatible pair of redox active species and organic solvent to increase the energy density. The solvation mechanism of the transition metal complexes in the organic solvents was obtained using the new model. The results have been compared with the experimental and theoretical results where they are available.

PMID:34523634 | DOI:10.1039/d1cp02591k

Clin Infect Dis. 2021 Sep 15:ciab808. doi: 10.1093/cid/ciab808. Online ahead of print.

ABSTRACT

BACKGROUND: In the US, norovirus is the leading cause of healthcare-associated gastroenteritis outbreaks. To inform prevention efforts, we describe the epidemiology of norovirus outbreaks in long-term care facilities (LTCFs).

METHODS: CDC collects epidemiologic and laboratory data on norovirus outbreaks from U.S. health departments through the National Outbreak Reporting System (NORS) and CaliciNet. Reports from both systems were merged, and norovirus outbreaks in nursing homes, assisted living, and other LTCFs occurring in 2009-2018 were analyzed. Data from the Centers for Medicare and Medicaid Services and the National Center for Health Statistics were used to estimate state LTCF counts.

RESULTS: During 2009-2018, 50 states, Washington D.C., and Puerto Rico reported 13,092 norovirus outbreaks and 416,284 outbreak-associated cases in LTCFs. Participation in NORS and CaliciNet increased from 2009-2014 and median reporting of LTCF norovirus outbreaks stabilized at 4.1 outbreaks per 100 LTCFs (IQR: 1.0-7.1) annually since 2014. Most outbreaks were spread via person-to-person transmission (90.4%) and 75% occurred during December-March. Genogroup was reported for 7,292 outbreaks with 862 (11.8%) positive for GI and 6,370 (87.3%) for GII. Among 4,425 GII outbreaks with typing data, 3,618 (81.8%) were GII.4. LTCF residents had higher attack rates than staff (median 29.0% versus 10.9%; p<0.001). For every 1,000 cases, there were 21.6 hospitalizations and 2.3 deaths.

CONCLUSIONS: LTCFs have a high burden of norovirus outbreaks. Most LTCF norovirus outbreaks occurred during winter months and were spread person-to-person. Outbreak surveillance can inform development of interventions for this vulnerable population, such as vaccines targeting GII.4 norovirus strains.

PMID:34523674 | DOI:10.1093/cid/ciab808

Am J Epidemiol. 2021 Sep 14:kwab227. doi: 10.1093/aje/kwab227. Online ahead of print.

ABSTRACT

The sex/gender and aging-related cognitive decline association remains poorly understood due to inconsistencies in findings. Such heterogeneity could be attributable to the cognitive functions studied and study population characteristics, but also to a differential selection by drop-out and death between men and women. This work aims to evaluate the impact of selection by drop-out and death on the association between sex/gender and cognitive decline. We first compared the most frequently used statistical methods for longitudinal data, targeting either population estimands (marginal models estimated by Generalized Estimating Equations) or subject-specific estimands (mixed/joint models estimated by likelihood maximization) on eight aging studies: six population-based (ACTIVE(1996-2009), Paquid(1988-2014), REGARDS(2003-2016), 3-City(1999-2016), WHICAP(1992-2017), Whitehall II(2007-2016)) and two clinic-based (ADNI(2004-2017), MEMENTO(2011-2016)) studies. We illustrated the differences in the estimands of the sex/gender association with cognitive decline in selected examples and highlighted the critical role of differential selection by drop-out and death. By using the same estimand, we then contrasted the sex/gender association across cohorts and cognitive measures suggesting residual differential sex/gender association depending on the targeted cognitive measure (memory or animal fluency) and the initial cohort selection. We recommend focusing on subject-specific estimands in the alive population for assessing sex/gender differences while handling differential selection over time.

PMID:34521111 | DOI:10.1093/aje/kwab227

Brain Behav. 2021 Sep 14:e32349. doi: 10.1002/brb3.2349. Online ahead of print.

ABSTRACT

OBJECTIVES: There are controversies about the role of zinc in the development of both types 1 and 2 diabetes. The aim of this study was to assess serum zinc level in diabetic patients with and without peripheral neuropathy in comparison to healthy controls and to explore the possible relationship between serum zinc level and severity of peripheral neuropathy.

METHODS: This case control study was conducted on 120 subjects: 40 patients fulfilled the criteria for diagnosis of probable diabetic polyneuropathy (DPN), 40 diabetic patients without polyneuropathy (N-DPN) and 40 healthy controls. DPN patients were submitted to clinical assessment of diabetic neuropathy using neuropathy symptom and change (NSC) scale, Michigan Neuropathy Screening Instrument Physical Assessment (MNSI) scale and electrophysiological assessment using nerve conduction study. Zinc serum level was measured in all subjects included in this study using direct colorimetric test method.

RESULTS: Diabetic patients with and without neuropathy were found to have significantly lower mean values of serum zinc than healthy controls (p = .025, .03 respectively). There is a statistically significant negative correlation between zinc serum level and hemoglobin A1C (HA1C) (p ˂ .001), NSC score (p = .001) and MNSI score (p = .003) in DPN group. There were also statistically significant correlations between zinc serum level and nerve conduction study values.

CONCLUSION: Zinc deficiency significantly correlates with the severity of DPN and glycemic control.

PMID:34521153 | DOI:10.1002/brb3.2349

Forensic Sci Int. 2021 Sep 2;327:110988. doi: 10.1016/j.forsciint.2021.110988. Online ahead of print.

ABSTRACT

The development of fingermarks on reflective surfaces is often a challenge regarding the photography of images with overlapping lines, low contrast and reflections, especially considering that many forensic laboratories are supplied only with basic instrumentation for fingerprint analysis. The present study overviews these difficulties and proposes a combination of chemical and optical procedures, using low-cost products and equipment, to develop fingermarks on silver mirror surfaces. The chemical treatment promotes the delimitation of the substrate, transforming the reflective surface into a transparent surface. The results were statistically analyzed, indicating quality improvement of natural fingermarks pictures taken with standard digital camera on transparent surface. There was good observation of details and minutiae, even for samples recovered several days or weeks after deposition. The suggested method substantially modifies the composition of the substrate without any contact with the fingermark, preserving its characteristics and properties. Like other nondestructive methodologies, this approach could be prioritized over methods that directly change the evidence itself and allows for the photography of the fingermark in unaltered condition. Lastly, it does not impact on the efficiency of subsequent exams.

PMID:34521020 | DOI:10.1016/j.forsciint.2021.110988

Comput Biol Med. 2021 Aug 26;137:104802. doi: 10.1016/j.compbiomed.2021.104802. Online ahead of print.

ABSTRACT

An in silico trial simulates a disease and its corresponding therapies on a cohort of virtual patients to support the development and evaluation of medical devices, drugs, and treatment. In silico trials have the potential to refine, reduce cost, and partially replace current in vivo studies, namely clinical trials and animal testing. We present the design and implementation of an in silico trial for treatment of acute ischemic stroke. We propose an event-based modelling approach for the simulation of a disease and injury, where changes to the state of the system (the events) are assumed to be instantaneous. Using this approach we are able to combine a diverse set of models, spanning multiple time scales, to model acute ischemic stroke, treatment, and resulting brain tissue injury. The in silico trial is designed to be modular to aid development and reproducibility. It provides a comprehensive framework for application to any potential in silico trial. A statistical population model is used to generate cohorts of virtual patients. Patient functional outcomes are also predicted with a statistical model, using treatment and injury results and the patient’s clinical parameters. We demonstrate the functionality of the event-based modelling approach and trial framework by running proof of concept in silico trials. The proof of concept trials simulate the same cohort of patients twice: once with successful treatment (successful recanalisation) and once with unsuccessful treatment (unsuccessful treatment). Ways to overcome some of the challenges and difficulties in setting up such an in silico trial are discussed, such as validation and computational limitations.

PMID:34520989 | DOI:10.1016/j.compbiomed.2021.104802