bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surgical Factors Influencing Local Relapse and Outcome in the Treatment of Unilateral Nephroblastoma
Authors: Meier Clemens M. , Fuchs Jörg , von Schweinitz Dietrich , Stein Raimund , Wagenpfeil Stefan , Kager Leo , Schenk Jens-Peter , Vokuhl Christian , Melchior Patrick , Welter Nils , Furtwängler Rhoikos , Graf Norbert 
Published: August 2022

Objective:
This study aims to identify factors associated with the occurrence of local relapse (LR) after treatment for unilateral nephroblastoma.

Background:
Despite the fact that LR is rare (~5%) its adverse impact on the need for relapse treatment and outcome (40%–80% overall survival) cannot be neglected. Identifying the causative factors may improve initial treatment to achieve better local control.

Methods:
Altogether 2386 patients with unilateral nephroblastoma prospectively enrolled over a period of 32 years (1989–2020) by the German Society for Pediatric Oncology and Hematology (SIOP-9/GPOH, SIOP-93-01/GPOH and SIOP-2001/GPOH) were retrospectively analyzed. Hazard ratios (HR) of LR were calculated for sex, age, size, local staging, histology, type of removal, rupture, lymph node (LN) removal using univariate and multivariate Cox models.

Results:
Age >48 months, tumor volume >500 mL, histology and LN extent of removal were identified as significant risk factors for LR [HR: 1.68, P=0.018, confidence interval (CI): 1.09–2.58; HR: 1.84, P=0.015, CI: 1.13–3.00; HR: 3.19, P<0.001, CI: 2.03–5.00; HR: 2.26, P=0.002, CI: 1.36–3.576]. LR occur significantly more often in Stage I and II, even if no LN are removed. The risk of metastases is significantly increased after local recurrence (HR: 11.5, P<0.001, CI: 7.11–18.60). LR is associated with a subsequent 18.79-fold increased risk of death (HR: 18.79, P<0.001, CI: 2.07–5.28).

Conclusions:
Several factors are responsible for the occurrence of LR. Surgical ones, like LN sampling allow further reduction of LR and consequently a better outcome of patients with unilateral nephroblastoma.
Cell wall thickness has phylogenetically consistent effects on photosynthetic nitrogen-use efficiency of terrestrial plants: a meta-analysis
Authors: Liu Dan-dan , Tosens Tiina , Xiong Dong-liang , Carriquí Marc , Xiong You-cai , Xue Wei 
Published: August 2022

AbstractLeaf photosynthetic nitrogen-use efficiency (PNUE) diversified significantly among C3species. However, morpho-physiological mechanisms and interrelationships forming PNUE remain unclear on the evolutionary time scale. In this study, we compiled a novel extensive matrix of morpho-anatomical and physiological traits of leaf in 679 C3species ranging from bryophytes to angiosperms to understand the intricacy of interrelationships underlying the variations in PNUE. We found that LMA, mesophyll cell wall thickness (Tcwm), Rubisco N allocation fraction (PR), and mesophyll conductance (gm) together interpreted 83% of variations in PNUE, with PRand gmaccounting for 65% of those variations. However, the PReffects were species-dependent on gm; that is, the contribution of PRon PNUE was extensively significant in high-gmspecies in comparison to low-gmspecies. Standard major analysis (SMA) and path analysis suggested a weak correlation between PNUE and LMA, whereas the SMA correlation for PNUE–Tcwmwas strong. The PRwas inversely proportional to Tcwm, which was similar to the relationship between gmand Tcwm(p-value < 0.01), so that the internal CO2drawdown from intercellular airspace to carboxylaton sites was relatively conservative over a wide range of Tcwm. Collectively, the coordination of changes in PRand gmconnecting Tcwmsuggested the complex physiological mechanisms mediated by Tcwmmodulating PNUE across contrasting plant groups.
Protein Model Refinement for Cryo-EM Maps Using DAQ score
Authors: Terashi Genki , Wang Xiao , Kihara Daisuke 
Published: August 2022

AbstractAs more protein structure models have been determined from cryo-electron microscopy (cryo-EM) density maps, establishing how to evaluate the model accuracy and how to correct models in case they contain errors is becoming crucial to ensuring the quality of structure models deposited to the public database, PDB. Here, we present a new protocol for evaluating a protein model built from a cryo-EM map and for applying local structure refinement in case the model has potential errors. Model evaluation is performed with a deep learning-based model-local map assessment score, DAQ, which we developed recently. Then, the subsequent local refinement is performed by a modified procedure of AlphaFold2, where we provide a trimmed template and trimmed multiple sequence alignment as input to control which structure regions to refine while leaving other more confident regions in the model intact. A benchmark study showed that our protocol, DAQ-refine, consistently improves low-quality regions of initial models. Among about 20 refined models generated for an initial structure, DAQ score was able to identify most accurate models. The observed improvements by DAQ-refine were on average larger than other existing methods.
Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics
Authors: Fujita Hiroaki , Ushio Masayuki , Suzuki Kenta , Abe Masato S. , Yamamichi Masato , Iwayama Koji , Canarini Alberto , Hayashi Ibuki , Fukushima Keitaro , Fukuda Shinji , Kiers E. Toby , Toju Hirokazu 
Published: August 2022

AbstractMicrobiome dynamics are both crucial indicators and drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as “dysbiosis” in human microbiomes. We here integrate theoretical and empirical bases for anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We then confirmed that the abrupt community changes observed through the time-series could be described as shifts between “alternative stable states” or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the energy landscape analysis of statistical physics or that of a stability index of nonlinear mechanics. These results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems.
Using extreme value statistics to reconceptualize psychopathology as extreme deviations from a normative reference model
Authors: Fraza Charlotte , Zabihi Mariam , Beckmann Christian F. , Marquand Andre F. 
Published: August 2022

AbstractFor many problems in neuroimaging, the most informative features occur in the tail of the distribution. For example, when considering psychiatric disorders as deviations from a ‘norm’, the tails of the distribution are considerably more informative than the bulk of the distribution for understanding risk, for stratifying and predicting such disorders and for anomaly detection. Yet, most statistical methods used in neuroimaging focus on modelling the bulk and fail to adequately capture extreme values occurring in the tails. To address this, we propose a framework that combines normative models with multivariate extreme value statistics to accurately model extreme deviations of a reference cohort for individual participants. Normative models are now widely used in clinical neuroscience and similar to the employment of normative growth charts in pediatric medicine to track a child’s weight in relation to their age, normative models can be used with neuroimaging measurements to quantify individual neurophenotypic deviations from a reference cohort. However, formal statistical treatment of how to model the extreme deviations from these models has been lacking until now. In this article we provide such an approach, inspired by applications of extreme value statistics in meteorology. Since the presentation of extreme value statistics is usually quite technical, we begin with a non-technical introduction to the fundamental principles of extreme value statistics, to accurately map the tails of the normative distribution for biological markers, including mapping multivariate tail dependence across multiple markers. Next, we give a demonstration of this approach to the UK Biobank dataset and demonstrate how extreme values can be used to accurately estimate risk and detect atypicality. This framework provides a valuable tool for the statistical modelling of extreme deviations in neurobiological data, which could provide us with more accurate and effective diagnostic tools for neurological and psychiatric disorders.
Partitioning genetic effects on birth weight at classical human leukocyte antigen loci into indirect maternal and direct fetal components using structural equation modelling
Authors: Wang Geng , Warrington Nicole M , Evans David M 
Published: August 2022

AbstractBirth weight (BW), as a proxy for intrauterine growth, is influenced by both fetal and maternal genetic factors. Single nucleotide polymorphisms in the human leukocyte antigen (HLA) region in both maternal and fetal genomes have been robustly associated with BW in previous genetic association studies suggesting the involvement of classical HLA alleles in BW etiology. However, no study to date has partitioned the association between BW and classical HLA alleles into maternal and fetal components. We used structural equation modelling (SEM) to estimate the indirect maternal (i.e. via the intrauterine environment) and direct fetal effects of classical HLA alleles on BW. Our SEM leverages the data structure of the UK Biobank (UKB), which includes participants’ own BW and/or the BW of their firstborn child (in the case of UKB females). We show via simulation that our model yields asymptotically unbiased estimates of the maternal and fetal allelic effects on BW and appropriate type I error rates, in contrast to simple regression models that estimate unconditioned maternal and fetal effects. Asymptotic power calculations show that we have sufficient power to detect moderate-sized maternal or fetal allelic effects (standardized effect size ≥ 0.01) of common HLA alleles on BW in the UKB. Applying our SEM to imputed classical HLA alleles and own and offspring BW of ∼270,000 participants from the UKB replicated the previously reported association at the HLA-C locus (C*04:01, P = 2.13×10−7, C*05:01, P= 6.91×10−5, C*03:03, P= 4.53×10−3, respectively) and revealed strong evidence for maternal (HLA-A*03:01, P = 7.90×10−8; B*35:01, P = 7.78×10−5; B*39:06, P = 8.49 ×10−5) and fetal allelic effects (HLA-B*39:06, P = 4.03×10−4) of non-HLA-C alleles on BW. These novel allelic associations between BW and classical HLA alleles provide insight into the immunogenetics of fetal growth in utero.
Show me your neighbour and I tell what you are: fisheye transformation for deep learning-based single-cell phenotyping
Authors: Toth Timea , Sukosd Farkas , Kaptas Flora , Bauer David , Horvath Peter 
Published: August 2022

AbstractRecently we have concluded that image-based features derived from the microenvironment have an enormous impact on successfully determining the class of an object1. Here we demonstrate that deep learning-based phenotypic analysis of cells with a properly chosen microenvironment-size provides results comparable to our earlier neighbourhood-based methods that utilise hand-crafted image features. We hypothesised that treating cells with equal weight, regardless of their position within the cellular microenvironment, is suboptimal, and direct neighbours have a larger impact on the phenotype of the cell-of-interest than cells in its larger proximity. Hence we present a novel approach that (1) considers the fully featured view of the cell-of-interest, (2) includes the neighbourhood and (3) gives lesser weight to cells that are far from the cell. To achieve this, we present a transformation similar to those characteristic for fisheye cameras. Such a transformation satisfies all the above defined criteria, with a fast rate of transform for any images. Using the proposed transformation with proper settings we could significantly increase the accuracy of single-cell phenotyping, both in case of cell culture and tissue-based microscopy images. The range of potential applications of the proposed method goes beyond microscopy, as we present improved results on the iWildCam 2020 dataset containing images of wild animals.
Association between food environments and fetal growth in pregnant Brazilian women
Authors: Victor Audêncio , Gotine Ana Raquel Manuel , Falcão Ila R. , Ferreira Andrea , Flores-Ortiz Renzo , Xavier Sancho Pedro , Vasco Melsequisete Daniel , de Jesus Silva Natanael , Mahoche Manuel , Silva Rodrigues Osiyallê Akanni , da Cassia Ribeiro Rita , Rondó Patrícia H. , Barreto Maurício L. 
Published: August 2022

AbstractIntroductionBirth weight is described as one of the main determinants of newborns’ chances of survival. Among the associated causes, or risk factors, the mother’s nutritional status strongly influences fetal growth and birth weight outcomes of the concept. This study evaluates the association between food deserts, small for gestational age (SGA), large for gestational age (LGA) and low birth weight (LBW) newborns.DesignThis is a cross-sectional population study, resulting from individual data from the Live Birth Information System (SINASC), and municipal data from mapping food deserts (CAISAN) in Brazil. The newborn’s size was defined as follows: appropriate for gestational age (between 10th and 90th percentile), SGA (<10th percentile), LGA (>90th percentile), and low birth weight <2,500g. To characterize food environments, we used tertiles of the density of establishments which sell in natura and ultra-processed foods. Logistic regression modeling was conducted to investigate the associations of interest.ResultsWe analyzed 2,632,314 live births in Brazil in 2016. Following due adjustment, it was observed that women from municipalities in which there was a limited supply of in natura foods presented a higher chance of a SGA [OR2nd tertile:1.06 (1.05-1.07)] and LBW [OR2nd tertile: 1.11(1.09-1.12)] newborn. On the other hand, municipalities in which there was a greater supply of ultra-processed foods presented higher chances for a SGA [OR3rd tertile:1.04 (1.02-1.06)] and LBW [OR2nd tertile:1.13 (1.11-1.16)] newborn. Stratification showed that Black and Mixed/Brown women were associated with SGA [OR3rd tertile: 1.09 (1.01-1.18)] and [OR3rdtertile:1.06 (1.04-1.09)], respectively, and mixed-race women were also associated with LBW [OR3rd tertile:1.17 (1.14-1.20)], while indigenous women were associated with LGA [OR3rd tertile: 1.20(1.01-1.45)].ConclusionsLiving in areas with limited access to healthy foods was associated with an increased chance of SGA and low weight newborns, especially between Black and Mixed/Brown women. Initiatives focused on minimizing the effects of these food environments, and which aim to reduce social inequalities, are urgently required in the Brazilian context.
Monkeypox treatment with tecovirimat in the Central African Republic under an Expanded Access Programme
Authors: Mbrenga Festus , Nakouné Emmanuel , Malaka Christian , Bourner Josephine , Dunning Jake , Vernet Guy , Horby Peter , Olliaro Piero 
Published: August 2022

AbstractBackgroundThere is currently no specific treatment recommended for monkeypox. This expanded access programme (EAP) aims to provide tecovirimat to patients with monkeypox and collect data on patient treatment, disease evolution and outcomes under a protocol to contribute to the evidence-base for the use of the drug for monkeypox.MethodsPatients with confirmed monkeypox received tecovirimat according to the recommended dosing. Data on clinical signs and symptoms were recorded daily during treatment and at follow-up visits. Blood or lesion samples were taken during treatment and at day 28 to assess viral presence of monkeypox by PCR. As tecovirimat is administered via an EAP, outcome measures were not predefined. Adverse events and clinical outcomes were monitored by evaluating the total number and location of lesions, temperature, degree of incapacity, presence of adverse events, patient survival, and viral presence throughout treatment and follow-up.ResultsWe report outcomes in 14 patients who were enrolled between December 2021 and February 2022. Muscle pain, headache, lymphadenopathy, lesions, fever, back pain, and upper respiratory symptoms were commonly reported at admission and during follow-up. The rate of appearance of active lesions gradually decreased throughout treatment, with the median time to no new lesions being 5 days following the start of treatment. No death attributable to monkeypox occurred in this cohort.ConclusionsData collected through this EAP can help improve our knowledge about the use of tecovirimat for monkeypox. We have been able to document systematically the presentation and clinical and virological evolution of monkeypox under treatment.Registration numberISRCTN43307947
Analysis of a genetic region affecting mouse body weight
Authors: Leung Connie L.K. , Karunakaran Subashini , Atser Michael G. , Innala Leyla , Hu Xiaoke , Viau Victor , Johnson James D. , Clee Susanne M. 
Published: August 2022

ABSTRACTGenetic factors affect an individual’s risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Pre-clinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared to the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ~316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin alpha 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. However, we identified a previously unknown role for Pdk1 in cardiac lipid metabolism providing the basis for future investigations in that area.
The seed germination spectrum of 528 plant species: a global meta-regression in relation to temperature and water potential
Authors: Maleki Keyvan , Soltani Elias , Seal Charlotte E. , Pritchard Hugh W. , Lamichhane Jay Ram 
Published: August 2022

AbstractThe germination niche of plant species depends primarily on the seeds’ responsiveness to temperature and water potential. However, to appreciate future climate risks to natural regeneration through germination, a global level synthesis across species is needed. We performed a meta-regression of primary data from 377 studies on 528 species, including trees, grasses, crops and wild species, to determine patterns and co-correlants in the cardinal values that define species’ germination niche. A negative correlation was found between thermal time and base temperature, and positive correlations between other cardinal temperatures and base temperature. Mean values of thermal time indicate that annual crops germinate more rapidly compared to wild species, potentially as a consequence of domestication, and tropical tree seeds the slowest. Dryland species (Cactaceae and Agavaceae) have the widest upper thermal and lower moisture niche, indicative of an ability to grow under harsh conditions, while forages have the narrowest thermal and moisture niche, suggesting higher sensitivity to frost or drought. We propose a new conceptual framework for understanding germination niche as shaped by thermal and moisture traits. Our database represents a unique source of information to further determine the vegetation boundaries of wild or cultivated species, including within simulation studies on plant species adaptations under changing land-use and climate.
Targeting keratin 17-mediated reprogramming of de novo pyrimidine biosynthesis to overcome chemoresistance in pancreatic cancer
Authors: Pan Chun-Hao , Chaika Nina V. , Tseng Robert , Siraj Md Afjalus , Chen Bo , Donnelly Katie L. , Horowitz Michael , Leiton Cindy V. , Chowdhury Sumedha , Roa-Peña Lucia , Oblein Lyanne , Marchenko Natalia , Singh Pankaj K. , Shroyer Kenneth R. , Escobar-Hoyos Luisa F. 
Published: August 2022

AbstractPancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death. We previously reported keratin 17 (K17) as a novel negative prognostic and predictive biomarker, whose overexpression confers the resistance to chemotherapies. Here, we investigated the mechanisms of chemoresistance and tumor-specific vulnerabilities that can be exploited for targeted therapies for K17-expressing PDAC. Unbiased metabolomic studies in isogenic PDAC models identified several key metabolic pathways that are upregulated in the presence of K17. We demonstrate that K17 increases pyrimidine biosynthesis, a pathway that has been linked to chemoresistance. Patient dataset analysis revealed that K17 expression and enzymes involved in pyrimidine, but not purine, de novo biosynthesis is associated with shorter patient survival. Rescue experiments showed that deoxycytidine (dC) and deoxythymidine (dT) were sufficient to promote resistance to Gemcitabine (a dC analog) and 5-fluorouracil (a dT analog), respectively. Furthermore, K17-expressing cells were more sensitive to Brequinar, a specific inhibitor of dihydroorotate dehydrogenase (DHODH), the rate-limiting enzyme in de novo pyrimidine biosynthetic pathway. Targeting DHODH by small interfering RNA or by Brequinar with Gemcitabine synergistically inhibited the viability of K17-positive PDAC cells. Importantly, the combination of Gemcitabine and Brequinar significantly inhibited the growth of K17-expressing tumors and extended survival of mice bearing K17-expressing PDACs. Overall, we identified a novel pathway of chemoresistance and a metabolic target of which could lead to the development of a biomarker-based therapy for K17-expressing PDAC.