Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping the neuroanatomical impact of very preterm birth across childhood

Those born very preterm (VPT; <32 weeks gestational age) have an increased risk in developing a wide range of cognitive deficits. In early‐to‐late childhood, brain structure has been shown to be altered in VPT compared to full‐term (FT) children; however, the results are inconsistent. The current study examined subcortical volumes, cortical thickness, and surface area in a large cohort of VPT and FT children aged 4–12 years. Structural magnetic resonance imaging (MRI) was obtained on 120 VPT and 146 FT children who returned up to three times, resulting in 176 VPT and 173 FT unique data points. For each participant, Corticometric Iterative Vertex‐based Estimation of Thickness was used to obtain global measurements of total brain, cortical grey and cortical white matter volumes, along with surface‐based measurements of cortical thickness and surface area, and Multiple Automatically Generated Templates (MAGeT) brain segmentation tool was used to segment the subcortical structures. To examine group differences and group–age interactions, mixed‐effects models were used (controlling for whole‐brain volume). We found few differences between the two groups in subcortical volumes. The VPT children showed increased cortical thickness in frontal, occipital and fusiform gyri and inferior pre–post–central areas, while thinning occurred in the midcingulate. Cortical thickness in occipital regions showed more rapid decreases with age in the VPT compared to the FT children. VPT children also showed both regional increases, particularly in the temporal lobe, and decreases in surface area. Our results indicate a delayed maturational trajectory in those born VPT.
An Alternative Method for Solving Two Problems of the Standard Model

Two problems of the Standard Model, associated with the introduction of non-gauge interactions and with the introduction of an electromagnetic field as a linear combination of fields on which various gauge groups are implemented, are analyzed. It is noticed that the existing model contains $U\left( 1 \right)-$ phase uncertainty of the matrix elements of the raising and lowering generators of the $SU\left( 2 \right)$ group. This uncertainty creates the condition for the additional local $U\left( 1 \right)-$ symmetry of the Standard Model Lagrangian with respect to the choice of various equivalent generator representations of the $SU\left( 2 \right)$ group, which is provided by the electromagnetic field. In this case, due to the different action of the raising and lowering generators on the fields of each generation of leptons and quarks, these fields interact with the electromagnetic field in different ways. It is also shown that considering the multi-particle gauge field a description of the Higgs mechanism can be obtained, free from the shortcomings of the well-known single-particle description, the main of which is the introduction of the non-gauge "phi-four" interaction, that is not reduced to the fundamental one. In the proposed model, the spontaneous symmetry breaking is achieved due to the same fundamental interaction, the mediating particle mass of which it provides.
Age- and Sex-Specific Increases in Stimulant Prescribing Rates—California, 2008-2017

Objective: To describe trends in prevalent and incident stimulant prescribing between 2008 and 2017 in California. Method: Statewide trends were estimated by age and sex category for prevalent (any) and incident (no prescriptions in the preceding 2 years) stimulant prescribing while adjusting for area-level covariates. Results: Prevalent prescribing rates increased by 126%, while incident prescribing increased 23%. Patients aged 25 to 44 years experienced over 200% increases in prevalent prescribing and 34% to 55% increases in incident prescribing. Among patients older than 25, women had consistently higher prescribing rates than men. ZIP code tabulation areas with the largest minority populations had the lowest baseline prescribing rates but experienced the greatest annual prescription rate increases. Conclusion: Adult stimulant prescribing increased substantially for early working aged adults. Prescription rates were greater for women than men.
CREATES Research Paper 2011-32 Conservatism in Corporate Valuation

Using a CCAPM based risk adjustment model, consistent with general asset pricing theory, I perform corporate valuations of a large sample of stocks listed on NYSE, AMEX and NASDAQ. The model is di¤erent from the standard CAPM model in the sense that it discounts forecasted residual income for risk in the numerator rather than trough the cost of equity, in the denominator. Further, the risk adjustment is based on assumptions about the time series properties of residual income return and consumption rather than historical returns. I compare the pricing performance of the model with the standard CAPM based valuation model, both considering the absolute valuation errors and an investment setting where simple investment strategies are made based on the results of the respective models. The CCAPM model performs substantially better than the CAPM based model when comparing absolute valuation errors. Both models are able to explain abnormal returns impressively well, when constructing investment strategies, but also in this setting the CCAPM model outperforms the CAPM model in most dimensions. I further show that the standard CAPM and the Fama-French 3 factor based approaches to risk adjustment substantially overestimate the cost of risk. This "error" more than o¤sets yet another "error", committed when using analysts forecasts of long-term growth which are 3-4 times higher than what can be considered reasonable. Using the CCAPM approach to valuation, the results imply that investors are very conservative in their valuation of long-term value generation and very conservative in risk adjusting future value generation. JEL Classi cations: C22, C32, C51, C53, G11, G12, G14, G32.
Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data

Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σa), and σa represents an average value for the depth range investigated with a specific coil separation and orientation. Multi-coil EMI data can be inverted to obtain layered bulk electrical conductivity models. However, above-ground stationary influences alter the signal and the inversion results can be unreliable. This study proposes an improved data processing chain, including EMI data calibration, conversion, and inversion. For the calibration of σa, three direct current resistivity techniques are compared: Electrical resistivity tomography with Dipole-Dipole and Schlumberger electrode arrays and vertical electrical soundings. All three methods obtained robust calibration results. The Dipole-Dipole-based calibration proved stable upon testing on different soil types. To further improve accuracy, we propose a non-linear exact EMI conversion to convert the magnetic field to σa. The complete processing workflow provides accurate and quantitative EMI data and the inversions reliable estimates of the intrinsic electrical conductivities. This improves the ability to combine EMI with, e.g., remote sensing, and the use of EMI for monitoring purposes.
Growth curve analysis using nonlinear mixed model in divergently selected Japanese quails

Growth, a trait of prime interest to the animal industry, is a complex physiological process. Mathematical models have the potential to represent the entire growth phase of the chicken and the parameters in the models have biological meaning. Growth curves, which are the graphical illustration of the mathematical functions, are generally used to describe the increase in body weight of an individual or the average growth of population over time, and are also utilized to define the effects of selection on growth or body weight at any stage of life (BLASKO and GOMEZ, 1993). Many studies have been carried out to determine the growth pattern of chicken (TZENG and BECKER, 1981; ANTHONY et al., 1991b; AGGREY, 2002), turkey (BUFFINGTON et al., 1973; ANTHONY et al., 1991a, 1991b), Japanese quail (MARKS, 1978; ANTHONY et al., 1986; ANTHONY et al., 1991b), swine (SCHINCKEL and CRAIG, 2001) and cattle (CHO et al., 2002) by fitting the most common non-linear growth curve functions such as Gompertz, Logistic, Bertalanffy, Brody and Richards models to the time-body weight information. The parameters of non-linear growth curve models are estimated by iterative procedures minimizing the error variance or maximizing the likelihood by assuming that the residuals are independently distributed. However, growth curves are built up based on repeated live body weight measurements on the same experimental unit. These serial data usually have underlying relationships or correlations among the serial body weight observations. Therefore, heavier animals at birth or hatch usually have a competitive advantage and remain heavier than the other animals of the group in the later age stages. Also, the variation among the animals for live body weight increases as age increases. This typical result contradicts the assumption that the residual values are independent and have a constant variance at each age (SCHINCKEL and CRAIG, 2001). Random effects of experimental units or individuals would stem from repeated measurements on the same animal over time. A mixed model is one that incorporates both fixed and random effects simultaneously (PEEK et al., 2002). Therefore, the objective of this study is first to com-
Amino Acid Availability of a Dairy and Vegetable Protein Blend Compared to Single Casein, Whey, Soy, and Pea Proteins: A Double-Blind, Cross-Over Trial

Protein quality is important for patients needing medical nutrition, especially those dependent on tube feeding. A blend of dairy and vegetable proteins (35% whey, 25% casein, 20% soy, 20% pea; P4) developed to obtain a more balanced amino acid profile with higher chemical scores, was compared to its constituent single proteins. Fourteen healthy elderly subjects received P4, whey, casein, soy, and pea (18 g/360 mL bolus) on five separate visits. Blood samples were collected at baseline until 240 min after intake. Amino acid availability was calculated using incremental maximal concentration (iCmax) and area under the curve (iAUC). Availability for P4 as a sum of all amino acids was similar to casein (iCmax and iAUC) and whey (iCmax) and higher vs. soy (iCmax and iAUC) and pea (iCmax). Individual amino acid availability (iCmax and iAUC) showed different profiles reflecting the composition of the protein sources: availability of leucine and methionine was higher for P4 vs. soy and pea; availability of arginine was higher for P4 vs. casein and whey. Conclusions: The P4 amino acid profile was reflected in post-prandial plasma levels and may be regarded as more balanced compared to the constituent single proteins.
Effects of Selective Genotyping and Selective Imputation in Single-Step GBLUP

Single-Step genomic prediction has been advocated to be the next logical step in the development of large routine applications. Despite its intriguingly simple concept, there are still several problems to be solved from a theoretical standpoint. One problem is the inflation of genomic predictions frequently occurring in practical applications. Ad-hoc remedies have been proposed, like the use of scaling-factors when building the H matrix or pruning of data and pedigrees used for prediction. In this investigation we suppose that selective genotyping and selective imputation in Single-Step GBLUP are major components contributing to inflated predictions. Using the general reformulation of the Single-Step model given by R. Fernando as an illustration, single-step GBLUP can be conceptually divided into two separate steps of estimation: step one is the estimation of gene-contents for all animals in the pedigree from observed genotypes and step two is the estimation of SNP-effects using observed and imputed genotypes and the available phenotypic data. In recent studies we have examined the effect of selective genotyping and the role of genotypes without phenotypes in Single-Step GBLUP in simulation studies. Our conclusion is that selective genotyping and the selective quality of genotype imputation can lead to biased genomic estimates in Single-Step GBLUP. In order to support our argument we demonstrate the effect of the inclusion or exclusion of older birth years of genotyped bulls showing strong evidence for selective genotyping on two-step and single-step predictions using real Fleckvieh data and discuss the vital importance of the difference between exclusion of genotypes and exclusion of phenotypes and genotypes.
Mathematical Characterization of Protein Transmembrane Regions Amrita

Graphical bioinformatics has paved a unique way of mathematical characterization of proteins and proteomic maps. The graphics representations and the corresponding mathematical descriptors have proved to be useful and have provided unique solutions to problems related to identification, comparisons, and analyses of protein sequences and proteomics maps. Based on sequence information alone, these descriptors are independent fromphysiochemical properties of amino acids and evolutionary information. In this work, we have presented invariants from amino acid adjacency matrix and decagonal isometries matrix as potential descriptors of protein sequences. Encoding protein sequences into amino acid adjacency matrix is already well established. We have shown its application in classification of transmembrane and nontransmembrane regions of membrane protein sequences.We have introduced the dodecagonal isometries matrix, which is a novel method of encoding protein sequences based on decagonal isometries group.
CLINICAL-TRIALS OF DIFFERENTIATION THERAPY OF EPITHELIAL CANCERS

Clinical Trials of Differentiation Therapy of Epithelial Cancers F.L. Meyskens, Jr. and U. Pastorino* UC Irvine Clinical Cancer Center, 101 The City Drive, Buil<ling 44, Route 81 Orange, CA 92668, USA *lstituto Nazionale Tumori, Milan, Italy The major purpose of this session was to broadly address issues related to the control of human epithelial cancers using differentiation therapy. Two general areas were covered: Prevention of epithelial aerodigestive and respiratory malignancies, and Differentiation of human epithelial cancers in vitro with certain compounds. These two groups of studies present entirely different issues and will be covered separately. Compared to therapeutic· trials, there are relatively few chemoprevention studies being conducted. The majority of these trials use carotenoids or retinoids as the therapeutic compound. The results from four different types of studies were presented and included: A number of trials using retinoids and carotenoids in the prevention of oral cancer. A randomized trial using 13 cis-retinoic acid ( cRA) for the prevention of second malignant tumors in patients with surgically cured head and neck cancers. A randomized study of high-dose vitamin A for adjuvant treatment and prevention of stage I lung cancer.
A new Bayesian joint model for longitudinal count data with many zeros, intermittent missingness, and dropout with applications to HIV prevention trials

In longitudinal clinical trials, it is common that subjects may permanently withdraw from the study (dropout), or return to the study after missing one or more visits (intermittent missingness). It is also routinely encountered in HIV prevention clinical trials that there is a large proportion of zeros in count response data. In this paper, a sequential multinomial model is adopted for dropout and subsequently a conditional model is constructed for intermittent missingness. The new model captures the complex structure of missingness and incorporates dropout and intermittent missingness simultaneously. The model also allows us to easily compute the predictive probabilities of different missing data patterns. A zero‐inflated Poisson mixed‐effects regression model is assumed for the longitudinal count response data. We also propose an approach to assess the overall treatment effects under the zero‐inflated Poisson model. We further show that the joint posterior distribution is improper if uniform priors are specified for the regression coefficients under the proposed model. Variations of the g‐prior, Jeffreys prior, and maximally dispersed normal prior are thus established as remedies for the improper posterior distribution. An efficient Gibbs sampling algorithm is developed using a hierarchical centering technique. A modified logarithm of the pseudomarginal likelihood and a concordance based area under the curve criterion are used to compare the models under different missing data mechanisms. We then conduct an extensive simulation study to investigate the empirical performance of the proposed methods and further illustrate the methods using real data from an HIV prevention clinical trial.
Does cannabis use modify the effect of post-traumatic stress disorder on severe depression and suicidal ideation? Evidence from a population-based cross-sectional study of Canadians

Background: Post-traumatic stress disorder sharply increases the risk of depression and suicide. Individuals living with post-traumatic stress disorder frequently use cannabis to treat associated symptoms. We sought to investigate whether cannabis use modifies the association between post-traumatic stress disorder and experiencing a major depressive episode or suicidal ideation. Methods: We used data from the 2012 Canadian Community Health Survey-Mental Health, a nationally representative cross-sectional survey of non-institutionalized Canadians aged ⩾15 years. The relationship between post-traumatic stress disorder and each outcome was modelled using logistic regression with an interaction term for cannabis and post-traumatic stress disorder, controlling for demographic characteristics, mental health, and substance use comorbidities. The ratio of odds ratios and relative excess risk due to interaction was calculated to measure interaction on the multiplicative and additive scales, respectively. Results: Among 24,089 eligible respondents, 420 (1.7%) reported a current clinical diagnosis of post-traumatic stress disorder. In total, 106 (28.2%) people with post-traumatic stress disorder reported past-year cannabis use, compared to 11.2% of those without post-traumatic stress disorder (p < 0.001). In multivariable analyses, post-traumatic stress disorder was significantly associated with recent major depressive episode (adjusted odds ratio = 7.18, 95% confidence interval: 4.32–11.91) and suicidal ideation (adjusted odds ratio = 4.76, 95% confidence interval: 2.39–9.47) among cannabis non-users. post-traumatic stress disorder was not associated with either outcome among cannabis-using respondents (both p > 0.05). Conclusions: This study provides preliminary epidemiological evidence that cannabis use may contribute to reducing the association between post-traumatic stress disorder and severe depressive and suicidal states. There is an emerging need for high-quality experimental investigation of the efficacy of cannabis/cannabinoids for the treatment of post-traumatic stress disorder.
Survival and Prognosis of Patients with Pilocytic Astrocytoma: A Single-Center Study

Background Pilocytic astrocytoma (PA) is a brain tumor that is relatively more common in children and young adults. Methods We retrospectively reviewed the medical records of patients with PA treated at a single center between 1988 and 2018. Results We included 31 subjects with PA. The median age at diagnosis was 13.4 years, and the median follow-up duration was 9.9 years. The total PA group had a 10-year disease-specific survival (DSS) rate of 92.6% [95% confidence interval (CI), 82.6–100] and 10-year progression-free survival (PFS) rate of 52.8% (95% CI, 32.0–73.6). In patients aged <20 years, tumors were more likely to be located in sites in which gross total tumor resection (GTR) was impossible. No statistically significant difference in 10-year DSS was found between the GTR (100%) and non-GTR (89.7%; 95% CI, 76.2–100; p=0.374) groups. However, a statistically significant difference in 10-year PFS was found between the GTR (100%) and non-GTR groups (30.7%; 95% CI, 8.6–52.8; p=0.012). In the non-GTR group, no statistically significant difference in 10-year DSS was found between the patients who received immediate additional chemotherapy and/or radiotherapy (Add-Tx group, 92.9%; 95% CI, 79.4–100) and the non-Add-Tx group (83.3%; 95% CI, 53.5–100; p=0.577). No statistically significant difference in 10-year PFS was found between the Add-Tx group (28.9%; 95% CI, 1.7–56.1) and non-Add-Tx group (33.3%; 95% CI, 0–70.9; p=0.706). Conclusion The PFS of the patients with PA in our study depended only on the degree of surgical excision associated with tumor location. This study is limited by its small number of patients and retrospective nature. A multicenter and prospective study is necessary to confirm these findings.
Molecular epidemiology and the evolution of human coxsackievirus A 6

Received 24 May 2016 Accepted 28 September 2016 Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Department of Virology, University of Turku, 20520 Turku, Finland Department of Clinical Virology, Turku University Hospital, 20520 Turku, Finland Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, 17177 Stockholm, Sweden Department of Clinical Microbiology, Karolinska University Hospital, 17177 Stockholm, Sweden Department of Microbiological Diagnostics & Virology, Artillerivej 5, DK-2300 Copenhagen, Denmark Institute for Virology, University of Bonn Medical Center, Sigmund-Freud-Str. 25, D-53105 Bonn, Germany Instituto de Salud Carlos III, 28220 Majadahonda, Madrid, Spain Infection and Immunity Division, Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK
Distinguishing Different Industry Technologies and Localized Technical Change

When different technologies are present in an industry, assuming a homogeneous technology will lead to misleading implications about technical change and inefficient policy recommendations. In this paper a latent class modelling approach and flexible estimation of the production structure is used to distinguish different technologies for a representative sample of E.U. dairy producers, as an industry exhibiting significant structural changes and differences in production systems in the past decades. The model uses a transformation function to recognize multiple outputs; separate technological classes based on multiple characteristics, a flexible generalized linear functional form, a variety of inputs, and random effects to capture firm heterogeneity; and measures of first- and second-order elasticities to represent technical change and biases. We find that if multiple production frontiers are embodied in the data, different firms exhibit different output or input intensities and changes associated with different production systems that are veiled by overall (average) measures. In particular, we find that farms that are larger and more capital intensive experience greater productivity, technical progress and labor savings, and enjoy scale economies that have increased over time.