Miracle-dz/UniFAR-FTUs huggingface dataset:
THE NEW ZEALAND MEDICAL JOURNAL

Aim Cardiovascular disease is a leading cause of death in New Zealand, but risk factors may be decreased by consuming a heart healthy diet. This pilot study investigated whether participants met the guidelines for a heart healthy diet and whether a novel heart healthy dietary pattern could be identified using principal components analysis (PCA). The second aim of this project was to assess if higher education, standard of living and nutrition literacy are associated with a heart healthy dietary pattern. Method This exploratory study was undertaken using data from the first participants enrolled in the Canterbury Health Ageing and Lifecourse study: an observational study of 50 year olds in the Canterbury District Health Board region. Eighty-two people were selected from the General and Māori electoral role and interviewed prior to the 22 February 2011 Christchurch Earthquake. PCA was conducted to identify dietary patterns, based on intake of specific nutrients as indicated by the New Zealand and international heart healthy dietary guidelines. Results 62 participants completed questionnaires and an estimated food record. No participants met all five of the heart healthy dietary guidelines. One dietary pattern was produced by PCA: a “higher CVD risk” pattern. Regression analysis indicated that higher standard of living, education and nutrition literacy were inversely associated with a “higher CVD risk” pattern. Conclusion Higher standard of living, education and nutrition literacy were associated with a healthier dietary eating pattern. However, as no participants met all the dietary recommendations more education and support is needed to help people meet these. Cardiovascular disease (CVD) is the second most common cause of death after cancer in New Zealand (NZ). The prevalence of CVD increases dramatically with age; at 45 years of age only 8% of New Zealanders are diagnosed with CVD compared to 75% of those aged 75 years. New Zealand has an aging population which will increase the burden of CVD. Among the risk factors for CVD, some are partially modifiable, including high blood pressure, high blood cholesterol, overweight and poor glycaemic control. Modifiable risk factors are known to be influenced, in part, by dietary intake. Consumption of particular heart healthy foods has been shown to improve modifiable risk factors. A heart healthy diet typically includes high intakes of fruit, vegetables, whole grain foods, fish and seafood, lean meat and poultry, low fat dairy products, nuts and seeds
Corruption: Transcending Borders

Is corruption capable of spreading across national borders? This paper uses panel data for 120 countries from 1995 to 2012 to evaluate whether the corruption levels ofneighboring countries, as weighted by the relative joint border length, affects domestic corruption. Including country fixed effects allows us to control for unobservablecountry specifc aspects and our results suggest a positive and statistically signifcant relationship. In general, a ten point increase in the weighted freedom from corruption index of neighboring countries is associated with a one point increase of the domestic freedom from corruption index. This result is robust to a variety of alternative specifcations, such as a GMM estimation or including additional control variables. The proposed effect becomes stronger as income increases and the relationship is only positive for countries with a GDP per capita above US$1,600 (in 2000 US$). For the richest countries, the estimated coe cient rises up to 0:43.
Semiparametric Bernstein–von Mises for the error standard deviation

Abstract: We study Bayes procedures for nonparametric regression problems with Gaussian errors, giving conditions under which a Bernstein–von Mises result holds for the marginal posterior distribution of the error standard deviation. We apply our general results to show that a single Bayes procedure using a hierarchical spline-based prior on the regression function and an independent prior on the error variance, can simultaneously achieve adaptive, rate-optimal estimation of a smooth, multivariate regression function and efficient, √
Behavior of a high steep loess slope strengthened by combination system of soil nails and stabilization piles

The combination of soil nails and stabilization piles(CSNSP) has been widely used as a reinforcing technique to retain excavations and stabilize slopes, but few relevant applications are found for high loess slope. Based on a high steep loess slope strengthened by CSNSP, the behavior of the strengthening system is investigated by field monitoring and finite element method. The results show that the lateral displacement, shear force and bending moment of piles increase gradually with the increment of excavation depth; and the displacement tends to be steady gradually. The location of the maximum shear force in the pile body shows a declining trend which indicates that the potential failure surface develops downwards. The distribution of soil pressure around piles in CSNSP system is compared with which appeared in deep foundation pit. The soil pressure on the back side of piles shows a trend of decrease with excavation while the soil pressure on the front side appears to be fluctuant. With the growth of excavation depth, the measured stress of the reinforced soil nails increases significantly, which indicates that the slope deformation is limited by the soil nails. The most dangerous rupture surface of the slope above piles appears to be a circular arc and the shear opening locates at the head of the piles. In addition, the proportion of soil nails to stability for the overall system is larger than the stabilization piles when the excavation depth is shallow, but the situation changes with the increment of the excavation depth.
Disease-causing Mitochondrial Heteroplasmy Segregated within Induced Pluripotent Stem Cell Clones Derived from A MELAS Patient

Mitochondrial diseases display pathological phenotypes according to the mixture of mutant versus wild-type mitochondrial DNA (mtDNA), known as heteroplasmy. We herein examined the impact of nuclear reprogramming and clonal isolation of induced pluripotent stem cells (iPSC) on mitochondrial heteroplasmy. Patient-derived dermal fibroblasts with a prototypical mitochondrial deficiency diagnosed as MELAS demonstrated mitochondrial dysfunction with reduced oxidative reserve due to heteroplasmy at iPSC clones segregate mitochondrial heteroplasmy 2 position G13513A in the ND5 subunit of complex I. Bioengineered iPSC clones acquired pluripotency with multi-lineage differentiation capacity and demonstrated reduction in mitochondrial density and oxygen consumption distinguishing them from the somatic source. Consistent with the cellular mosaicism of the original patient-derived fibroblasts, the MELASiPSC clones contained a similar range of mtDNA heteroplasmy of the disease-causing mutation with identical profiles in the remaining mtDNA. Highheteroplasmy iPSC clones were used to demonstrate that extended stem cell passaging was sufficient to purge mutant mtDNA, resulting in isogenic iPSC subclones with various degrees of disease-causing genotypes. Upon comparative differentiation of iPSC clones, improved cardiogenic yield was associated with iPSC clones containing lower heteroplasmy compared to isogenic clones with high heteroplasmy. Thus, mtDNA heteroplasmic segregation within patientderived stem cell lines enables direct comparison of genotype/phenotype relationships in progenitor cells and lineage-restricted progeny, and indicates that cell fate decisions are regulated as a function of mtDNA mutation load. The novel nuclear reprogrammingbased model system introduces a disease-in-a-dish tool to examine the impact of mutant genotypes for MELAS patients in bioengineered tissues and a cellular probe for molecular features of individual mitochondrial
Analysis of differentially expressed genes (DEGs) in Neuronal cells from the cerebral cortex of Alzheimer’s disease

Alzheimer’s disease (AD) is an aging-related neurodegenerative disorder with large implications for society and individuals. AD is a multi-factor disorder, with these factors having a direct or indirect correlation with each other. Despite many studies with different aspects on molecular and cellular pathways, there is still no specific treatment for AD. Identification of potential pathogenic factors can be done by transcriptomic studies of differentially expressed genes (DEGs), but the outcomes have been contradictory. Using both bioinformatics and meta-analysis methods can be useful for removing such inconsistencies. A useful and common approach for a better understanding of neurodegenerative disease is to assess its molecular causes, by comparing the gene expression levels in healthy and disease tissues. Next-generation RNA-sequencing is a valuable method for analyzing both coding and non-coding regions of RNA, and it has made it possible to identify differentially expressed genes in large-scale data. The aim of the current study was to get a better understanding of the transcriptional changes in AD models, and identify differentially expressed genes between healthy and AD individuals from the adult mouse brain model as well as detecting AD pathways. In this study, the transcriptomes of purified neuron, astrocyte and microglia cells from mouse brains were analyzed using publicly available RNA-seq datasets. The DEGs were identified for all three mentioned cell types using DESeq2 and EdgeR packages. All statistical analyses were performed by R software and the DEGs detected by DESeq2 and edgeR, respectively, were compared using Venn diagrams. Additionally, analyzing the AD pathway was performed using GOrilla tool for visualizing the enriched gene ontology (GO) terms in the list of ranked genes. From this project, it was found that there were very few significantly DEGs between AD and healthy samples in neuron cells, while there were more DEGs in astrocyte and microglia cells. In conclusion, comparing DESeq2 and egeR packages using Venn diagrams showed a slight advantage of DESeq2 in detection accuracy, since it was able to identify more DEGs than edgeR. Moreover, analyzing AD pathway using GOrilla tool indicated that identified enriched GO terms by each cell type differed from each other. For astrocytes, more enriched GO terms were identified than for microglia cells,
EFFECT OF WATER STRESS ON SOYBEAN YIELD AND WATER RELATIONS

Two field experiments were conducted at Giza Agricultural Research Station, Agricultural Research Center, Egypt in 2006 and 2007 growing seasons to study the effect of three irrigation treatments (irrigation using 1.2 pan evaporation coefficient, irrigation using 1.0 pan evaporation coefficient and irrigation using 0.8 pan evaporation coefficient) on yield and water relations of soybean and to use YieldStress model to simulate the effect of saving irrigation water on soybean yield. Results showed that all yield components were significantly affected by irrigation treatments over the two growing seasons, except for number of pods/plant in 2006 growing season and number of branches/plant and 100-seed weight in 2007 growing season. Results also showed that the highest soybean yield and its components were obtained under irrigation using evaporation pan coefficient equal to 1.2, over all the two growing seasons. Furthermore, under irrigation with 1.0 pan evaporation coefficient, soybean seed yield was reduced by 3.28 and 3.37% and biological yield was reduced by 5.61 and 3.54% over the two growing seasons, respectively. Moreover, soybean seed yield was reduced by 47.54 and 58.43% and biological yield was reduced by 37.38 and 58.59% under irrigation with 0.8 pan evaporation coefficient over the two growing seasons, respectively. The highest consumptive water used was obtained under irrigation with 1.2 pan evaporation coefficient i.e. 2395 and 2413 m 3 /fed for both growing seasons, respectively. The highest water use efficiency was obtained under irrigation with 1.0 evaporation pan coefficient. Yield-Stress model prediction showed good agreement between measured and predicted values of soybean seed and biological yield and consumptive water use, which facilitate using it in yield prediction under irrigation water saving. Running the model under deducting 10% of the amount of irrigation water of the control showed that soybean seed yield could be reduced by 4.91 and 5.49% for both growing seasons, respectively. Whereas, biological yield could be reduced by 5.61 and 5.05% for both growing seasons, respectively. Therefore, it could be concluded that to increase water use efficiency and to save irrigation water, it could be recommended to irrigate soybean with 1.0 evaporation pan coefficient. Furthermore, saving about 10% of the applied irrigation amount compared with the control treatment could reduce soybean seed yield and biological yield by an averge of 5.20 and 5.33% over the two growing seasons.
Depression in Parkinson's disease. A positron emission study.

BACKGROUND This study investigated biological correlates of depression in patients with idiopathic Parkinson's disease (PD). We tested the hypothesis that in patients with PD and depression, there was regional dysfunction involving brain areas previously implicated in functional imaging studies of patients with primary depression. METHOD Using positron emission tomographic measurements of regional cerebral blood flow (rCBF), patterns of resting rCBF were measured in ten patients with PD and major depression, and ten patients with PD alone. The results were compared with findings from ten patients with primary depression and ten normal controls, scanned using identical methods as part of an earlier study. Groups were matched for age, sex and symptom severity. RESULTS Bilateral decreases in rCBF were observed in anteromedial regions of the medial frontal cortex and the cingulate cortex (Brodmann's areas (BA) 9 and 32) in the depressed PD group, compared with those with PD alone and compared with normal controls. This regional disturbance overlapped that observed in patients with primary depression. CONCLUSIONS The findings indicate that the medial prefrontal cortex is a common area of neural dysfunction in the manifestation of both primary depression and depression in PD.
Diversity, nomenclature, and taxonomy of protists.

the origin of echolocation and flight in bats. Nature 403:188– 192. van Rheede, T. , T. Bastiaans, D. N. Boone, S. B. Hedges, W. W. de Jong, and O. Madsen. 2006. The platypus in its place: nuclear genes and indels confirm the sister group relation of monotremes and therians. Mol. Biol. Evol. 23:587–597. Waddell, P. J., H. Kishino, and R. Ota. 2001. A phylogenetic foundation for comparative mammalian genomics. Genome Informatics 12:141– 154. Waddell, P. J., N. Okada, and M. Hasegawa. 1999. Towards resolving the interordinal relationships of placental mammals. Syst. Biol. 48:1–5. Waddell, P. J., and S. Shelley. 2003. Evaluating placental inter-ordinal phylogenies with novel sequences including RAG1, γ -fibrinogen, ND6, and mt-tRNA, plus MCMC-driven nucleotide, amino acid, and codon models. Mol. Phylogenet. Evol. 28:197–224.
Working Memory An Evolving Concept

Traditionally, working memory is conceptualized as a system involved in the maintenance and manipulation of information in the absence of external stimulation. Intuitively, working memory might be considered a formalized system for describing thought (Jonides, 1995). When you consider what is “on your mind”—from mental images to inner speech—you are considering your working memory. In this conceptualization, working memory is transient—lasting for however long the thought remains useful, typically on the order of seconds. Functionally, working memory is a mental work space that is critical for higher-level cognitive abilities. Several tasks have been devised to measure the capacity of working memory or the amount of information one can hold in mind (Luck & Vogel, 1997; Turner & Engle, 1989). Individual differences in performance on these tasks predict reasoning, planning, problem-solving, and a variety of other cognitive abilities (Carpenter, Just, & Shell, 1990; Daneman & Carpenter, 1980; Daneman & Merikle, 1996; Fukuda, Vogel, Mayr, & Awh, 2010; Just & Carpenter, 1992), demonstrating the importance of having a large mental work space. As a result of its broad impact, a clear understanding of working memory is essential for understanding cognition. Because of its central importance, working memory has been a topic of intense interest in psychology and neuroscience. Foundational research in working memory was performed by Baddeley and colleagues, and to this day Baddeley’s multicomponent model remains one of the most influential models of working memory (Baddeley, 1986, 2012; Baddeley & Hitch, 1974). Although a full treatment of the model and the data that support it is outside the scope of this chapter, certain key assumptions of the model lay the groundwork for the issues to come. First, the model assumes that working memory is distinct from long-term memory. That is, the processes that underlie the temporary maintenance of information for working memory can be distinguished from the processes that underlie the more permanent retention of information associated with long-term memory. Second, the model assumes distinct representational bases for different kinds of information. For example, materials that can be verbalized (e.g., words, letters) are represented in a qualitatively distinct way from materials that can be visualized (e.g., faces, scenes). Finally, the model assumes that processes that select, modulate, and manipulate retained information are
Working Memory : Neural Mechanisms Visual working memory in early development : a developmental cognitive neuroscience perspective

Buss AT, Ross-Sheehy S, Reynolds GD. Visual working memory in early development: a developmental cognitive neuroscience perspective. J Neurophysiol 120: 1472–1483, 2018. First published June 13, 2018; doi:10.1152/jn.00087. 2018. —In this article, we review the literature on the development of visual working memory (VWM). We focus on two major periods of development, infancy and early childhood. First, we discuss the innovative methods that have been devised to understand how the development of selective attention and perception provide the foundation of VWM abilities. We detail the behavioral and neural data associated with the development of VWM during infancy. Next, we discuss various signatures of development in VWM during early childhood in the context of spatial and featural memory processes. We focus on the developmental transition to more adult-like VWM properties. Finally, we discuss computational frameworks that have explained the complex patterns of behavior observed in VWM tasks from infancy to adulthood and attempt to explain links between measures of infant VWM and childhood VWM.
Assessment of image processing techniques and ASTER SWIR data for the delineation of evaporates and carbonate outcrops along the Salt Lake Fault, Turkey

ABSTRACT The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral sensor allows a variety of minerals to be diagnosed with the availability of six shortwave infrared (SWIR) bands. The study area located in a semi-arid region in central Turkey was flanked by the Salt Lake Fault in the west. ASTER SWIR bands and the adopted image processing techniques such as decorrelation stretch, band ratio, and feature-oriented principle component selection (FPCS) were applied for mapping both gypsum and carbonate rocks in the study area. Initially, the application of the decorrelation stretch method with a novel band combination successfully delineated the gypsum and carbonate outcrops. In addition to that, the principle component 4 (PC4) image obtained from the FPCS technique applied to a new band selection of ASTER data distinguished explicitly the carbonate outcrops. The resultant images, consistent with the geologic map of the study area, were compared with another and demonstrated that the gypsum and carbonate rocks were clearly identifiable. In addition to that, quantitative analyses of parallelepiped supervised classification images, band 9/band 8 ratio, and PC4 images in particular, yielded very compatible results.
The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT

Background Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. Methods With the approval of NHS England, we developed OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Results We used data from 6,070 participants where 24.7% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a high probability of reporting loss in quality-of-life (OR: 22, 95% CI:12.35-39.29) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 60.2, 95% CI: 27.79-130.57) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Conclusions We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease.
Structural Equation Modeling (SEM): Gaming Disorder Leading Untreated Attention-Deficit/Hyperactivity Disorder to Disruptive Mood Dysregulation

(1) Background: Internet gaming disorder (IGD) in youths likely leads to disruptive mood dysregulation, especially among those with attention-deficit/hyperactivity disorder (ADHD). Whether IGD mediates the pathways leading ADHD to disruptive emotional dysfunction remains unclear. This study aims to elucidate the direct or indirect influence of IGD on ADHD; (2) Method: The Swanson, Nolan, and Pelham Version IV questionnaire was used to evaluate symptoms of ADHD and oppositional defiant disorder, and the Chen gaming disorder scale was used to measure IGD. A psychiatrist diagnosed ADHD, IGD, and disruptive mood dysregulation disorder (DMDD)-like symptoms. Structural equation modeling was applied to evaluate the role of IGD in mediating ADHD progression to disruptive mood dysregulation; (3) Results: Among a total of 102 ADHD youths, 53 (52%) of them with IGD were significantly more likely to have poor interpersonal relationships (p < 0.01) and DMDD-like symptoms (p < 0.01) than ADHD youths without IGD. IGD played a mediating role in increasing the risk of disruptive mood dysregulation in ADHD youths; (4) Conclusions: The findings suggest that IGD mediates ADHD’s progression to disruptive mood dysregulation. Intensive biopsychosocial interventions are warranted for ADHD youths with IGD. More children and adolescents became mood-dysregulated after excessive gaming during the COVID-19 pandemic; this study’s results suggest that child mental health experts develop earlier detection and prevention strategies for children and adolescents hidden behind internet addiction.