Linear Mixed Model Method Research Articles

Genome wide detection of CNV and their association with body size in Danzhou chickens

Copy number variation (CNV) is a crucial component of genetic diversity in the genome, serving as the foundation for the genetic architecture and phenotypic variability of complex traits. In this study, we examined CNVs in the Danzhou (DZ) chicken, an indigenous breed exclusive to Hainan Province, China. By employing whole-genome resequencing data from 200 DZ chickens, we conducted a comprehensive genome-wide analysis of CNVs using CNVpytor and performed CNV-based genome-wide association studies (GWAS) on six body size traits, including body slope length (BSL), keel length (KeL), tibial length (TiL), tibial circumference (TiC), chest width (ChW), and chest depth (ChD) utilizing linear mixed model methods considering a genomic relationship matrix. We identified a total of 144,265 autosomal CNVs among the 200 individuals, comprising 67,818 deletions and 76,447 duplications. After merging these variants together, we obtained 4,824 distinct copy number variant regions, which accounted for approximately 20% of the chicken autosomal genome. Furthermore, we discovered several significantly associated CNV segments with body size traits located proximal to genes such as IHH, WNT6, WNT10A, LPR4, FZD2, WNT7B, and GNAS that have been extensively implicated in skeletal development and growth processes. These findings enhance our understanding of CNVs in chickens and their potential impact on body size traits by revealing candidate genes involved in the regulation of these traits. This establishes a solid framework for future studies and may prove particularly beneficial for exploring genetic structural variation in chickens.

90 Evaluating water- and feed-based arginine supplementation on newly weaned pig growth and gastrointestinal health

Abstract The objective of this experiment was to assess the influence of arginine (Arg) supplementation in water and/or feed on the growth performance and gastrointestinal health of newly weaned pigs. Pigs (n = 240; PIC 337 Χ 1050, Genus, Henderson, TN) were randomly allocated into 80 mixed-sex test pens and subjected to a 2 Χ 4 factorial design, with two levels of Arg supplementation in water (0% or 8% stock, dosed through a 1:128 proportioner) for the first phase (d 0-7), and four dietary arginine levels (0.85, 0.95, 1.05, and 1.15 standardized ileal digestible (SID) Arg to Lysine (Lys) ratios for the first two phases (d 0-7 and 7-21). All treatments were provided a common diet (0.96 SID Arg:Lys) for the last phase d 21- 42. One pig per pen underwent a dual sugar absorption test of lactulose at 500 mg/kg and mannitol at 50 mg/kg of body weight (BW) via gastric tube on d 7 and 21, with blood plasma collected 4 h post-administration. The pig tested on d 7 was subsequently euthanized for intestinal tissue collection. Pen growth performance and feed disappearance were evaluated for 3 phases; d 0-7, 7-21, and 21-42. The statistical analysis utilized generalized linear mixed model methods (SAS 9.4, Cary, NC) with the main effects of SID Arg:Lys in the feed and Arg level within the water, and the interaction between the two. Pen was the experimental unit. Orthogonal contrasts were tested for the linear and quadratic effects of the diet. Growth performance during the 1st period exhibited variability, reflected by negative gain to feed ratio (G:F), caused by health challenges of Rotavirus A. Consequently, data were analyzed separately for each phase. Increasing dietary SID Arg:Lys caused a significant linear effect (improvement; P = 0.04) on final BW (18.47 and 21.90 kg, for 0.85 and 1.15 SID Arg:Lys, respectively). However, discernible differences between dietary treatments were not observed (P > 0.1). Similarly, a trend (P = 0.09) suggested a linear impact of dietary SID Arg:Lys on average daily gain during the third phase (d 21-42). In terms of intestinal absorption and morphology, Arg supplementation, whether through water or diet, had no effect on lactulose and mannitol absorption on both d 7 and d 21, nor did it impact villous height, crypt depth, or the villi:crypt ratio in ileum tissues collected on d 7 post-weaning. In conclusion, dietary supplementation with Arg increased final BW but had no clear impacts on intestinal health within the variables measured, potentially impacted by the rotavirus diagnosis in the first week post wean.

A Preliminary Analysis of the Clinical Effectiveness of Audiologist-Delivered Cognitive Behavioral Therapy Delivered via Video Calls for Rehabilitation of Misophonia, Hyperacusis, and Tinnitus.

Cognitive behavioral therapy (CBT) is a key intervention for management of misophonia, hyperacusis, and tinnitus. The aim of this study was to perform a preliminary analysis comparing the scores for self-report questionnaires before and after audiologist-delivered CBT via video calls for adults with misophonia, hyperacusis, or tinnitus or a combination of these. This was a retrospective cross-sectional study. The data for 37 consecutive patients who received CBT for misophonia, hyperacusis, or tinnitus from a private institute in the United Kingdom were analyzed. Self-report questionnaires taken as part of routine care were as follows: 4C Questionnaires for tinnitus, hyperacusis, and misophonia (4C-T, 4C-H, and 4C-M, respectively), Tinnitus Impact Questionnaire (TIQ), Hyperacusis Impact Questionnaire (HIQ), Misophonia Impact Questionnaire (MIQ), Sound Sensitivity Symptoms Questionnaire (SSSQ), and Screening for Anxiety and Depression in Tinnitus (SAD-T). Responses were also obtained to other questionnaires related to tinnitus, hyperacusis, insomnia, and anxiety and mood disorders. A linear mixed-model method was used to assess the changes in response to the questionnaires pretreatment and posttreatment. Pretreatment-posttreatment comparisons showed that scores for the 4C-T, 4C-H, 4C-M, TIQ, HIQ, MIQ, SSSQ, and SAD-T improved, with effect sizes of 1.4, 1.2, 1.3, 2.6, 0.9, 0.7, 0.9, and 1.4, respectively (all p < .05). This preliminary analysis suggests that CBT via video calls may be effective in reducing the impact of misophonia, hyperacusis, and tinnitus. However, this study did not have a control group, so its results need to be interpreted with caution.

The use of FreeStyle libre improves glycaemic control along with reducing diabetes burden and hospital admissions in a socially deprived Northwest English population.

This retrospective study aimed to use mixed (qualitative and quantitative) methods to evaluate the role of FSL in reducing hospital admissions due to all causes, HbA1c, and reported hypoglycaemic episodes in people with diabetes living in a socially deprived region of Northwest England. Data were collected retrospectively from previous consultations, which coincided with the 6th -week, 6th -month and annual review including blood tests, hospital admissions due to any cause and reported hypoglycaemia. Also, FSL assessment and satisfaction semi-structured questionnaire was done to assess the impact of FSL on diabetes management and quality of life. Mixed-effects models were used to assess glycaemic control and reductions in hospital admissions and reported hypoglycaemic episodes. Just 127 patients met the inclusion criteria. A multivariate linear mixed model method that analyses HbA1c data longitudinally revealed mean differences (mmol/mol) between baseline and post-FSL measurements, estimated by restricted maximum likelihood method (REML) of 9.64 (six weeks), 7.68 (six months) and 7.58 (annual review); all with a corresponding p-value of < 0.0001. For DKA patients, the bootstrap method revealed a significant reduction in mean HbA1c of 25.5, 95% confidence interval (CI) [8.8, 42.6] mmol/mol. It is demonstrated that FSL use for one year resulted in 59% reduction in hospital admissions and 46% reduction in reported hypoglycaemic episodes. The use of FSL resulted in statistically significant reductions in hospital admissions, HbA1c and reported hypoglycaemic episodes among diabetics in a socially deprived Northwest region of England. These outcomes show a direct association with a higher questionnaire score. The online version contains supplementary material available at 10.1007/s40200-024-01424-4.

1087 Large Incidence and Risk Factors Meta-analysis of Dysphagia in Over 132,000 Anterior, Posterior, and Hybrid Surgeries for Cervical Spondylosis Myelopathy

INTRODUCTION: Surgical management of Cervical Spondylotic Myelopathy (CSM) is associated with complications with devastating impacts. Dysphagia is one of these major complications with the incidence rate being not completely known in different surgical approaches. METHODS: PubMed/MEDLINE, SCOPUS, and Cochrane were systematically searched until January 2023. Rates and risk of complications were assessed. Meta-analysis of rates and risks was performed with generalized linear mixed model (GLMM) and inverse variance method, respectively, and compared between techniques. RESULTS: 1196 citations were screened and 39 studies with 60 instances of dysphagia incidence/risk factors reports from over 132,442 patients were identified. Dysphagia’s overall incidence rate was 4.98%[95% confidence interval 3.23-7.61] and was significantly different between surgery groups (Chi2 p &lt; 0.01). It was found in 7.97% [4.95–12.57] of anterior surgeries, 1.52% [0.94–2.45] of posterior ones, and 11.25% [3.38–31.44] of hybrid techniques (statistical comparison: P &lt; A &lt; H). Advanced age (&gt;65) risked dysphagia significantly (OR 1.38 [95%CI 1.11-1.71]). CONCLUSIONS: Chances of posterior surgery being complicated with dysphagia is not negligible and should be discussed with patient before surgery, especially with older adults.

Multi-model genome-wide association studies for appearance quality in rice.

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

Mesocarnivores den site selection in arid ecosystems; A case study of Rüppell's fox and sand cat in central Iran

Understanding the relationships between species and their pattern of coexistence is essential in conservation planning. Rüppell's fox and sand cat are two poorly known species of desert areas that coexist in most parts of the desert belt of Africa and the Middle East. However, their habitat selection in many parts of their distribution are unknown. In this research, using the data collected from a three-year monitoring plan, we investigated the relationship between the den sites of Rüppell's fox and sand cat and habitat variables based on the generalized linear mixed model (GLMM) method. The results showed that for Rüppell's foxes, only the density of rodent burrows had a significant and positive effect. In the sand cat model, in addition to prey, vegetation density (P-value < 0.05) and vegetation height (P-value < 0.10) had significantly positive effects and elevation had a significantly negative effect (P-value < 0.10). We found that the sand cat is more specialized in habitat selection and depends more on the habitat cover. While the Rüppell's fox chose a more diverse range of soil and vegetation classes, the sand cat selected its den sites exclusively in sandy loam soils with the predominant cover of Haloxylon spp. and Caligonum spp. Acting as a generalist species, Rüppell's fox displayed a more pronounced response to human presence and selected dens with a broader view of their surroundings. These findings enhance our understanding of mesocarnivore coexistence in desert regions and provide valuable insights for the conservation planning of these species.

Development of Single-Segment Substitution Lines and Fine-Mapping of qSPP4 for Spikelets Per Panicle and qGW9 for Grain Width Based on Rice Dual-Segment Substitution Line Z783.

Single segment substitution line (SSSL) libraries are an ideal platform for breeding by design. To develop SSSLs-Xihui18 covering the whole genome, a novel rice chromosome segment substitution line (CSSL), Z783, carrying two substitution segments (average length of 6.55 Mb) on Chr.4 and Chr.9 was identified, which was a gap in the library previously. Z783 was developed from the progeny of recipient "Xihui18" (an indica restorer line) and donor "Huhan3" (a japonica cultivar) by advanced backcross combined molecular marker-assisted selection (MAS). It displayed multiple panicles and less spikelets and wide grains. Then, a F2 population derived from Xihui18/Z783 was used to map quantitative trait loci (QTLs) for yield-related traits by the mixed linear model method. Nine QTLs were detected (p < 0.05). Furthermore, three SSSLs were constructed by MAS, and all 9 QTLs could be validated, and 15 novel QTLs could be detected by these SSSLs by a one-way ANOVA analysis. The genetic analysis showed that qSSP4 for less spikelets and qGW9 for wide grain all displayed dominant gene action in their SSSLs. Finally, qSSP4 and qGW9 were fine-mapped to intervals of 2.75 Mb and 1.84 Mb, on Chromosomes 4 and 9, respectively. The results lay a solid foundation for their map cloning and molecular breeding by design.

Differential gene expression analysis based on linear mixed model corrects false positive inflation for studying quantitative traits

Differential gene expression (DGE) analysis has been widely employed to identify genes expressed differentially with respect to a trait of interest using RNA sequencing (RNA-Seq) data. Recent RNA-Seq data with large samples pose challenges to existing DGE methods, which were mainly developed for dichotomous traits and small sample sizes. Especially, existing DGE methods are likely to result in inflated false positive rates. To address this gap, we employed a linear mixed model (LMM) that has been widely used in genetic association studies for DGE analysis of quantitative traits. We first applied the LMM method to the discovery RNA-Seq data of dorsolateral prefrontal cortex (DLPFC) tissue (n = 632) with four continuous measures of Alzheimer’s Disease (AD) cognitive and neuropathologic traits. The quantile–quantile plots of p-values showed that false positive rates were well calibrated by LMM, whereas other methods not accounting for sample-specific mixed effects led to serious inflation. LMM identified 37 potentially significant genes with differential expression in DLPFC for at least one of the AD traits, 17 of which were replicated in the additional RNA-Seq data of DLPFC, supplemental motor area, spinal cord, and muscle tissues. This application study showed not only well calibrated DGE results by LMM, but also possibly shared gene regulatory mechanisms of AD traits across different relevant tissues.

Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat

BackgroundDrought is most likely the most significant abiotic stress affecting wheat yield. The discovery of drought-tolerant genotypes is a promising strategy for dealing with the world’s rapidly diminishing water resources and growing population. A genome-wide association study (GWAS) was conducted on 298 Iranian bread wheat landraces and cultivars to investigate the genetic basis of yield, yield components, and drought tolerance indices in two cropping seasons (2018–2019 and 2019–2020) under rainfed and well-watered environments.ResultsA heatmap display of hierarchical clustering divided cultivars and landraces into four categories, with high-yielding and drought-tolerant genotypes clustering in the same group. The results of the principal component analysis (PCA) demonstrated that selecting genotypes based on the mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), and stress tolerance index (STI) can help achieve high-yield genotypes in the environment. Genome B had the highest number of significant marker pairs in linkage disequilibrium (LD) for both landraces (427,017) and cultivars (370,359). Similar to cultivars, marker pairs on chromosome 4A represented the strongest LD (r2 = 0.32). However, the genomes D, A, and B have the highest LD, respectively. The single-locus mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) identified 1711 and 1254 significant marker-trait association (MTAs) (-log10 P > 3) for all traits, respectively. A total of 874 common quantitative trait nucleotides (QTNs) were simultaneously discovered by both MLM and mrMLM methods. Gene ontology revealed that 11, 18, 6, and 11 MTAs were found in protein-coding regions (PCRs) for spike weight (SW), thousand kernel weight (TKW), grain number per spike (GN), and grain yield (GY), respectively.ConclusionThe results identified rich regions of quantitative trait loci (QTL) on Ch. 4A and 5A suggest that these chromosomes are important for drought tolerance and could be used in wheat breeding programs. Furthermore, the findings indicated that landraces studied in Iranian bread wheat germplasm possess valuable alleles, that are responsive to water-limited conditions. This GWAS experiment is one of the few types of research conducted on drought tolerance that can be exploited in the genome-mediated development of novel varieties of wheat.

Genome-wide association study discovers novel germplasm resources and genetic loci with resistance to Gibberella ear rot caused by Fusarium graminearum.

Gibberella ear rot (GER) in maize caused by Fusarium graminearum is one of the most devastating maize diseases reducing grain yield and quality worldwide. The genetic bases of maize GER resistance remain largely unknown. Using artificial inoculation across multiple environments, GER severity of an association panel consisting of 316 diverse inbred lines was observed with wide phenotypic variation. In the association panel, a genome-wide association study (GWAS) using a general linear model (GLM) identified 69 single-nucleotide polymorphisms (SNPs) significantly associated with GER resistance at the threshold of 2.04 x 10-5, and the average phenotypic variation explained (PVE) of these SNPs was 5.09%. We also conducted a GWAS analysis using a mixed linear model (MLM) at a threshold of 1.0 x 10-4, and 16 significant association SNPs with an average PVE of 4.73% were detected. A combined GLM and MLM method obtained 10 co-localized significant association SNPs linked to GER resistance including the most significant SNP (PZE-105079915) with the greatest PVE value, 9.07%, at bin 5.05 following ten candidate genes. These findings are significant for the exploration of the complicated genetic variations in maize GER resistance. The regions and genes identified herein provide a list of candidate targets for further investigation, in addition to the elite germplasm resources that can be used for breeding GER resistance in maize.

Early-initiated childhood reading for pleasure: associations with better cognitive performance, mental well-being and brain structure in young adolescence.

Childhood is a crucial neurodevelopmental period. We investigated whether childhood reading for pleasure (RfP) was related to young adolescent assessments of cognition, mental health, and brain structure. We conducted a cross-sectional and longitudinal study in a large-scale US national cohort (10 000 + young adolescents), using the well-established linear mixed model and structural equation methods for twin study, longitudinal and mediation analyses. A 2-sample Mendelian randomization (MR) analysis for potential causal inference was also performed. Important factors including socio-economic status were controlled. Early-initiated long-standing childhood RfP (early RfP) was highly positively correlated with performance on cognitive tests and significantly negatively correlated with mental health problem scores of young adolescents. These participants with higher early RfP scores exhibited moderately larger total brain cortical areas and volumes, with increased regions including the temporal, frontal, insula, supramarginal; left angular, para-hippocampal; right middle-occipital, anterior-cingulate, orbital areas; and subcortical ventral-diencephalon and thalamus. These brain structures were significantly related to their cognitive and mental health scores, and displayed significant mediation effects. Early RfP was longitudinally associated with higher crystallized cognition and lower attention symptoms at follow-up. Approximately 12 h/week of youth regular RfP was cognitively optimal. We further observed a moderately significant heritability of early RfP, with considerable contribution from environments. MR analysis revealed beneficial causal associations of early RfP with adult cognitive performance and left superior temporal structure. These findings, for the first time, revealed the important relationships of early RfP with subsequent brain and cognitive development and mental well-being.

Using machine learning to realize genetic site screening and genomic prediction of productive traits in pigs.

Genomic prediction, which is based on solving linear mixed-model (LMM) equations, is the most popular method for predicting breeding values or phenotypic performance for economic traits in livestock. With the need to further improve the performance of genomic prediction, nonlinear methods have been considered as an alternative and promising approach. The excellent ability to predict phenotypes in animal husbandry has been demonstrated by machine learning (ML) approaches, which have been rapidly developed. To investigate the feasibility and reliability of implementing genomic prediction using nonlinear models, the performances of genomic predictions for pig productive traits using the linear genomic selection model and nonlinear machine learning models were compared. Then, to reduce the high-dimensional features of genome sequence data, different machine learning algorithms, including the random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost) and convolutional neural network (CNN) algorithms, were used to perform genomic feature selection as well as genomic prediction on reduced feature genome data. All of the analyses were processed on two real pig datasets: the published PIC pig dataset and a dataset comprising data from a national pig nucleus herd in Chifeng, North China. Overall, the accuracies of predicted phenotypic performance for traits T1, T2, T3 and T5 in the PIC dataset and average daily gain (ADG) in the Chifeng dataset were higher using the ML methods than the LMM method, while those for trait T4 in the PIC dataset and total number of piglets born (TNB) in the Chifeng dataset were slightly lower using the ML methods than the LMM method. Among all the different ML algorithms, SVM was the most appropriate for genomic prediction. For the genomic feature selection experiment, the most stable and most accurate results across different algorithms were achieved using XGBoost in combination with the SVM algorithm. Through feature selection, the number of genomic markers can be reduced to 1 in 20, while the predictive performance on some traits can even be improved compared to using the full genome data. Finally, we developed a new tool that can be used to execute combined XGBoost and SVM algorithms to realize genomic feature selection and phenotypic prediction.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Internal Ventricular Cerebrospinal Fluid Shunt for Adult Hydrocephalus: A Systematic Review and Meta-Analysis of the Infection Rate.

Hydrocephalus is a common neurological condition that usually requires internal ventricular cerebrospinal fluid shunt (IVCSFS). The reported infection rate (IR) varies greatly from below 1% up to over 50%, but no meta-analysis to assess the overall IR has ever been performed. To determine the IVCSFS overall IR in the adult population and search for associated factors. Six databases were searched from January 1990 to July 2022. Only original articles reporting on adult IVCSFS IR were included. Random-effects meta-analysis with generalized linear mixed model method and logit transformation was used to assess the overall IR. Of 1703 identified articles, 44 were selected, reporting on 57 259 patients who had IVCSFS implantation and 2546 infections. The pooled IR value and its 95% CI were 4.75%, 95% CI (3.8 to 5.92). Ninety-five percent prediction interval ranged from 1.19% to 17.1%. The patients who had IVCSFS after intracranial hemorrhage showed a higher IR (7.65%, 95% CI [5.82 to 10], P -value = .002). A meta-regression by year of publication found a decreasing IR (-0.031, 95% CI [-0.06 to 0.003], P -value = .032) over the past 32 years. IVCSF is a procedure that every neurosurgeon should be well trained to perform. However, the complication rate remains high, with an estimated overall IR of 4.75%. The IR is especially elevated for hydrocephalic patients who require IVCSFS after intracranial hemorrhage. However, decades of surgical advances may have succeeded in reducing IR over the past 32 years.

Public perceptions of governance and tax evasion: insights from developed and developing economies

Purpose This paper aims to explore how the role of the perception of good public governance reduces tax evasion (TE). Besides, this study investigates whether the nexus of public governance and TE differs between developed and developing economies. Design/methodology/approach Apart from the ordinary least squares (OLS) model, this study uses the linear mixed modeling technique. The World Governance Indicators and the multiple causes estimation (MIMIC) method are used to measure public governance. The shadow economy is used as a proxy for TE. Findings The results show that people's perceptions of public governance and the quality of government institutions are core elements that influence tax-evasion behavior. Besides, the rule of law (RoL) and political stability (PS) significantly impact tax-evasion behavior in developing countries. Nevertheless, the RoL, the control of corruption and PS are the most critical tax-evasion determinants among public governance indicators for developed countries. Regulatory quality shows a substantial positive relationship with TE in developed but not developing countries. Practical implications This paper provides a guide for policymakers on reducing tax-evasion behavior by paying more attention to maintaining the RoL and PS and fighting corruption. Additionally, this study highlights the importance of people's perceptions of the government's pursuit of the above policy-related improvements, which, in turn, affect their tax behavior. Originality/value To the best of the authors’ knowledge, this study is the first to explore the role of people's perceptions of improvements in public governance and how this can reduce TE behavior in developed and developing economies. Unlike prior studies, this study used the linear mixed model method, which is more advantageous than OLS and produces robust estimators.

Clinical Outcomes of Arthroscopic Ligament-Sparing Dorsal Capsulodesis for Partial Scapholunate Ligament Tear.

Introduction Various wrist arthroscopy techniques can be used in the management of scapholunate ligament (SLL) partial tears but their success has not been proven. Arthroscopic techniques including thermal shrinkage are becoming more popular in the management of partial SLL injuries. We hypothesized that arthroscopic ligament-sparing capsular tightening yields reliable and satisfactory results for the management of partial SLL tears. Methods A prospective cohort study was conducted on adult (age ≥18 years) patients with chronic partial SLL tears. All patients failed a trial of conservative management consisting of scapholunate strengthening exercises. Patients underwent an arthroscopic dorsal capsular tightening of the radiocarpal joint capsule radial to the origin of the dorsal radiocarpal ligament and proximal to the dorsal intercarpal ligament by either thermal shrinkage or dorsal capsule abrasion. Demographic data, radiological outcomes, patient-rated outcome measures and objective measures of wrist range of motion (ROM), and grip and pinch strength were recorded. Postoperative outcome scores were collected at 3, 6, 12, and 24 months. Data are reported as median and interquartile range, and comparisons were drawn between baseline and last follow-up. Clinical outcome data were analyzed using a linear mixed model method, while radiographic outcomes were assessed with nonparametric analysis with p < 0.05 indicating statistical significance. Results Twenty-three wrists (22 patients) underwent SLL treatment by thermal capsular shrinkage (19 wrists) or dorsal capsular abrasion (4 wrists). Median age at surgery was 41 years (range: 32-48) and median follow-up time was 12 months (range: 3-24). Pain significantly decreased from 62 (45-76) to 18 (7-41) and satisfaction significantly increased from 2 (0-24) to 86 (52-92). Patient-Rated Wrist and Hand Evaluation and Quick Disabilities of the Arm, Shoulder, and Hand significantly improved from 68 (38-78) to 34 (13-49) and from 48 (27-55) to 36 (4-58), respectively. Median grip and tip pinch strength significantly increased at final review. Range of movement and lateral pinch strength were satisfactory and maintained. Four patients required further surgery for ongoing pain or reinjury. All were successfully managed with partial wrist fusion or wrist denervation. Conclusion Arthroscopic ligament-sparing dorsal capsular tightening is a safe and effective treatment for partial SLL tears. Dorsal capsular tightening demonstrates good pain relief and patient satisfaction while improving patient-reported outcomes, grip strength, and maintaining ROM. Longer term studies are required to determine the longevity of these results.

Retinal nerve fiber layer in frontotemporal lobar degeneration and amyotrophic lateral sclerosis.

PurposeTauopathy and transactive response DNA binding protein 43 (TDP-43) proteinopathy are associated with neurodegenerative diseases. These proteinopathies are difficult to detect in vivo. This study examined if spectral-domain optical coherence tomography (SD-OCT) can differentiate in vivo the difference in peripapillary retinal nerve fibre layer (pRNFL) thickness and macular retinal thickness between participants with presumed tauopathy (progressive supranuclear palsy) and those with presumed TDP-43 proteinopathy (amyotrophic lateral sclerosis and semantic variant primary progressive aphasia).Study designProspective, multi-centre, observational study.Materials and methodspRNFL and macular SD-OCT images were acquired in both eyes of each participant using Heidelberg Spectralis SD-OCT. Global and pRNFL thickness in 6 sectors were analyzed, as well as macular thickness in a central 1 mm diameter zone and 4 surrounding sectors. Linear mixed model methods adjusting for baseline differences between groups were used to compare the two groups with respect to pRNFL and macular thickness.ResultsA significant difference was found in mean pRNFL thickness between groups, with the TDP-43 group (n = 28 eyes) having a significantly thinner pRNFL in the temporal sector than the tauopathy group (n = 9 eyes; mean difference = 15.46 μm, SE = 6.98, p = 0.046), which was not significant after adjusting for multiple comparisons. No other significant differences were found between groups for pRNFL or macular thickness.ConclusionThe finding that the temporal pRNFL in the TDP-43 group was on average 15.46 μm thinner could potentially have clinical significance. Future work with larger sample sizes, longitudinal studies, and at the level of retinal sublayers will help to determine the utility of SD-OCT to differentiate between these two proteinopathies.

Analysis of Multidimensional Stunting Intervention Factor Using Mixed Model

The mixed model combines fixed effect for all groups and random effect representing the diversity inter groups in the model (province) to increase the model precision. This study provides information on the significance of multidimensional stunting intervention factors (predictor variables) on stunting prevalence (response variables as indicator 2.2.1 Sustainable Development Goals/SDGs) with district/city as observation units. Using official data from Statistics Indonesia (National Socio Economic Survey) and Ministry of Health (Basic Health Research), this study expects to be one basis of information for the government, stakeholders, and further research to accelerate Indonesia’s SDGs targets in 2030. Comparison of classical linear mixed model method and linear mixed model with Least Absolute Shrinkage and Selection Operator (Lasso) variable selection conduct with relatively better results of mixed linear modelling with Lasso. The results showed that the predictor variables, namely complete immunization, ease of access to health facilities, diversity of food intake, improve water, food expenditure per capita, children’s participation in early childhood education, maternal education, and ownership of National Health Insurance for toddlers, significantly affected the stunting prevalence decrease. The predictor variables, namely low birth weight, households with social protection cards, and the percentage of poor people, significantly increase the stunting prevalence.

A Combination of Generalized Linear Mixed Model and LASSO Methods for Estimating Number of Patients Covid 19 in the Intensive Care Units

Generalized linear mixed models (GLMM) combined with the L1 penalty (Least Absolute Shrinkage and Selection Operator/LASSO) is called LASSO GLMM. LASSO GLMM reduces overfitting and selects predictor variables in modeling. The aim of this study is to evaluate the model's performance for predicting Covid-19 patients with certain congenital disease that require ICU based on the results of blood tests laboratory and patient’s vital signs. This study used binary response variables, 1 if the patient was admitted to the ICU and 0 if the patient was not admitted to the ICU. The fixed effect predictor variables are the results of blood tests laboratory and patient’s vital signs. The random effect predictor variable is patient's congenital disease. The result showed that the average of accuracy and AUC from LASSO GLMM is more than the average of accuracy and AUC from LASSO GLM by using 5% level of significance. Respiratory rate and Lactate show a significance effect to predict the ICU needs of Covid-19 patients. The random effects patient's congenital disease has significance effect at 5% level of significance. It means that the ICU needs for Covid-19 patients varies among patient's congenital disease. We can conclude that GLMM LASSO with the random effect of patient’s congenital diseases has better modeling performance to predict the ICU needs of Covid-19 patients based on the results of blood tests laboratory and patient’s vital signs. The results of this modeling can quickly detect Covid-19 patients who need the ICU and can help medical staff use ICU resources optimally