Miracle-dz/UniFAR-FTUs huggingface dataset:
Tissue Engineered Materials in Cardiovascular Surgery: The Surgeon's Perspective

In cardiovascular surgery, reconstruction and replacement of cardiac and vascular structures are routinely performed. Prosthetic or biological materials traditionally used for this purpose cannot be considered ideal substitutes as they have limited durability and no growth or regeneration potential. Tissue engineering aims to create materials having normal tissue function including capacity for growth and self-repair. These advanced materials can potentially overcome the shortcomings of conventionally used materials, and, if successfully passing all phases of product development, they might provide a better option for both the pediatric and adult patient population requiring cardiovascular interventions. This short review article overviews the most important cardiovascular pathologies where tissue engineered materials could be used, briefly summarizes the main directions of development of these materials, and discusses the hurdles in their clinical translation. At its beginnings in the 1980s, tissue engineering (TE) was defined as “an interdisciplinary field that applies the principles of engineering and the life sciences toward the development of biological substitutes that restore, maintain, or improve tissue function” (1). Currently, the utility of TE products and materials are being investigated in several fields of human medicine, ranging from orthopedics to cardiovascular surgery (2–5). In cardiovascular surgery, reconstruction and replacement of cardiac and vascular structures are routinely performed. Considering the shortcomings of traditionally used materials, the need for advanced materials that can “restore, maintain or improve tissue function” are evident. Tissue engineered substitutes, having growth and regenerative capacity, could fundamentally change the specialty (6). This article overviews the most important cardiovascular pathologies where TE materials could be used, briefly summarizes the main directions of development of TE materials along with their advantages and shortcomings, and discusses the hurdles in their clinical translation.
Fungicide Sensitivity Shifting of Zymoseptoria tritici in the Finnish-Baltic Region and a Novel Insertion in the MFS1 Promoter

Septoria tritici blotch (STB) is caused by the ascomycete Zymoseptoria tritici and one of the predominating diseases in wheat (Triticum aestivum) in Europe. The control of STB is highly reliant on frequent fungicide applications. The primary objective of this study was to assess sensitivity levels of Z. tritici to different fungicide groups. The fungicides included in this study were epoxiconazole, prothioconazole-desthio, tebuconazole, and fluxapyroxad. A panel of 63 isolates from Estonia, Latvia, and Lithuania, and 10 isolates from Finland were tested. Fungicide sensitivity testing was carried out as a bioassay analyzing single pycnidium isolates on different fungicide concentrations. The average EC50 value in Baltic countries and Finland to epoxiconazole was high ranging from 1.04 to 2.19 ppm. For prothioconazole-desthio and tebuconazole, EC50 varied from 0.01 to 0.24 ppm, and 1.25 to 18.23 ppm, respectively. The average EC50 value for fluxapyroxad varied from 0.07 to 0.33 ppm. To explain the range of sensitivity, the samples were analyzed for CYP51 and Sdh mutations, as well as cytb G143A, CYP51 overexpression, and multidrug resistance (MDR). Frequencies of ZtCYP51 mutations D134G, V136A/C, A379G, I381V, and S524T in the Finnish-Baltic region were lower than in other European countries, but have increased compared to previous years. The frequency of cytb G143A conferring strobilurin resistance also augmented to 50–70% in the Z. tritici populations from Estonia, Finland, Latvia, and Lithuania. No Sdh mutations were found in this study, and neither strains of MDR phenotypes. However, we found a strain harboring a previously unknown transposon insertion in the promoter of the MFS1 gene, involved in drug efflux and multi-drug resistance. This new insert, however, does not confer an MDR phenotype to the strain.
Toward an Automated Measure of Social Engagement for Children With Autism Spectrum Disorder—A Personalized Computational Modeling Approach

Social engagement is a key indicator of an individual's socio-emotional and cognitive states. For a child with Autism Spectrum Disorder (ASD), this serves as an important factor in assessing the quality of the interactions and interventions. So far, qualitative measures of social engagement have been used extensively in research and in practice, but a reliable, objective, and quantitative measure is yet to be widely accepted and utilized. In this paper, we present our work on the development of a framework for the automated measurement of social engagement in children with ASD that can be utilized in real-world settings for the long-term clinical monitoring of a child's social behaviors as well as for the evaluation of the intervention methods being used. We present a computational modeling approach to derive the social engagement metric based on a user study with children between the ages of 4 and 12 years. The study was conducted within a child-robot interaction setting that targets sensory processing skills in children. We collected video, audio and motion-tracking data from the subjects and used them to generate personalized models of social engagement by training a multi-channel and multi-layer convolutional neural network. We then evaluated the performance of this network by comparing it with traditional classifiers and assessed its limitations, followed by discussions on the next steps toward finding a comprehensive and accurate metric for social engagement in ASD.
Neutrophil Extracellular Trap Induced Dendritic Cell Activation Leads to Th1 Polarization in Type 1 Diabetes

Neutrophils releasing neutrophil extracellular traps (NETs) infiltrate the pancreas prior to type 1 diabetes (T1D) onset; however, the precise nature of their contribution to disease remains poorly defined. To examine how NETs affect immune functions in T1D, we investigated NET composition and their effect on dendritic cells (DCs) and T lymphocytes in T1D children. We showed that T1D patient NET composition differs substantially from that of healthy donors and that the presence of T1D-NETs in a mixed peripheral blood mononuclear cell culture caused a strong shift toward IFNγ-producing T lymphocytes, mediated through activation of innate immunity cells in T1D samples. Importantly, in a monocyte-derived DC (moDC) culture, NETs induced cytokine production, phenotypic change and IFNγ-producing T cells only in samples from T1D patients but not in those from healthy donors. RNA-seq analysis revealed that T1D-NETs presence causes TGFβ downregulation and IFNα upregulation and creates pro-T1D signature in healthy moDCs.
Overexpression of OsMYB305 in Rice Enhances the Nitrogen Uptake Under Low-Nitrogen Condition

Excessive nitrogen fertilizer application causes severe environmental degradation and drives up agricultural production costs. Thus, improving crop nitrogen use efficiency (NUE) is essential for the development of sustainable agriculture. Here, we characterized the roles of the MYB transcription factor OsMYB305 in nitrogen uptake and assimilation in rice. OsMYB305 encoded a transcriptional activator and its expression was induced by N deficiency in rice root. Under low-N condition, OsMYB305 overexpression significantly increased the tiller number, shoot dry weight and total N concentration. In the roots of OsMYB305-OE rice lines, the expression of OsNRT2.1, OsNRT2.2, OsNAR2.1, and OsNiR2 was up-regulated and 15NO3– influx was significantly increased. In contrast, the expression of lignocellulose biosynthesis-related genes was repressed so that cellulose content decreased, and soluble sugar concentration increased. Certain intermediates in the glycolytic pathway and the tricarboxylic acid cycle were significantly altered and NADH-GOGAT, Pyr-K, and G6PDH were markedly elevated in the roots of OsMYB305-OE rice lines grown under low-N condition. Our results revealed that OsMYB305 overexpression suppressed cellulose biosynthesis under low-nitrogen condition, thereby freeing up carbohydrate for nitrate uptake and assimilation and enhancing rice growth. OsMYB305 is a potential molecular target for increasing NUE in rice.
Site-Dependent Lineage Preference of Adipose Stem Cells

Adult stem cells have unique properties in both proliferation and differentiation preference. In this study, we hypothesized that adipose stem cells have a depot-dependent lineage preference. Four rabbits were used to provide donor-matched adipose stem cells from either subcutaneous adipose tissue (ScAT) or infrapatellar fat pad (IPFP). Proliferation and multi-lineage differentiation were evaluated in adipose stem cells from donor-matched ScAT and IPFP. RNA sequencing (RNA-seq) and proteomics were conducted to uncover potential molecular discrepancy in adipose stem cells and their corresponding matrix microenvironments. We found that stem cells from ScAT exhibited significantly higher proliferation and adipogenic capacity compared to those from donor-matched IPFP while stem cells from IPFP displayed significantly higher chondrogenic potential compared to those from donor-matched ScAT. Our findings are strongly endorsed by supportive data from transcriptome and proteomics analyses, indicating a site-dependent lineage preference of adipose stem cells. Graphical Abstract Lineage preference of adult stem cells might be influenced by local matrix microenvironment. In this study, stem cells from subcutaneous adipose tissue (ScAT) had more adipogenic capacity and those from infrapatellar fat pad (IPFP) possessed advantageous chondrogenic potential; these findings are fully endorsed by molecular evidence from RNA Seq and proteomic analyses.
Development and Validation of a Deep Learning Radiomics Model Predicting Lymph Node Status in Operable Cervical Cancer

Aim: To develop and validate a deep learning radiomics model, which could predict the lymph node metastases preoperatively in cervical cancer patients. Patients and methods: We included a cohort of 226 pathological proven operable cervical cancer patients in two academic medical institutions from December 2014 to November 2017. Then this dataset was split into training set (n = 176) and independent testing set (n = 50) randomly. Five radiomic features were selected and a radiomic signature was established. We then combined these five radiomic features with the preoperative tumor histology and grade of these patients together. Baseline logistic regression model (LRM) and support vector machine model (SVM) were established for the comparison. We then explored the performance of a deep neural network (DNN), which is a popular deep learning model nowadays. Finally, performance of this DNN was validated in another independent test set including 50 cases of operable cervical cancer patients. Results: One thousand forty-five radiomic features were extracted for each patient. Twenty-eight features were found to be significantly correlated with the lymph node status in these patients (P < 0.05). Five radiomic features were further selected for further study due to their higher predictive powers. Baseline LRM incorporating these five radiomic and two clinicopathological features was established, which had an area under receiver operating characteristic curve (ROC) of 0.7372 and an accuracy of 89.20%. The established DNN model had four neural layers, in which layer there were 10 neurons. Adagrad optimizer and 1,500 iterations were used in training. The trained DNN had an area under curve (AUC) of 0.99 and an accuracy of 97.16% in the internal validation. To exclude the overfitting, independent external validation was also performed. AUC and accuracy in test set could still retain 0.90 and 92.00% respectively. Conclusion: This study used deep learning method to provide a comprehensive predictive model using preoperative CT images, tumor histology, and grade in cervical cancer patients. This model showed an acceptable accuracy in the prediction of lymph node status in cervical cancer. Our model may help identifying those patients who could benefit a lot from radiation therapy rather than primary hysterectomy surgery if this model could resist strict testing of future randomized controlled trials (RCTs).
Uncovering the behaviour of road accidents in urban areas

Different patterns in the incidence of road accidents are revealed when considering areas with increased levels of urbanization. To understand these patterns, road accident data from England and Wales is explored. In particular, the data are used to (i) generate time series for comparison of the incidence of road accidents in urban as opposed to rural areas, (ii) analyse the relationship between the number of road accidents and the population size of a set of urban areas, and (iii) model the likelihood of suffering an accident in an urban area and its dependence with population size. It is observed that minor and serious accidents are more frequent in urban areas, whereas fatal accidents are more likely in rural areas. It is also shown that, generally, the number of accidents in an urban area depends on population size superlinearly, with this superlinear behaviour becoming stronger for lower degrees of severity. Finally, given an accident in an urban area, the probability that the accident is fatal or serious decreases with population size and the probability that it is minor, increases sublinearly. These findings promote the question as to why such behaviours exist, the answer to which will lead to more sustainable urban policies.
Attribution of Mental States in Glossolalia: A Direct Comparison With Schizophrenia

Glossolalia (“speaking in tongues”) is a rhythmic utterance of pseudo-words without consistent semantic meaning and syntactic regularities. Although glossolalia is a culturally embedded religious activity, its connection with psychopathology (e.g., psychotic thought disorder and altered mental state attribution/mentalization) is still a matter of debate. To elucidate this issue, we investigated 32 glossolalists, 32 matched control participants, and 32 patients with schizophrenia using the Animated Triangle Test (ATT) and the Reading the Mind in the Eyes Test (RMET). The ATT can detect hypo- and hypermentalization using animations of two moving triangles. Healthy adults describe these as random movements (e.g., bouncing), willed actions (e.g., playing), or they mentalize (e.g., tricking). We found that glossolalists provided more mentalizing descriptions in the ATT random and intentional movement animations relative to the control participants. They also recognized more mental states in the RMET than the controls. None of them had a diagnosis of mental disorders. In contrast, patients with schizophrenia hypermentalized only in the ATT random movement condition, whereas they showed hypomentalization in the ATT intentional movement condition and in the RMET relative the control subjects. Hypermentalization in the ATT positively correlated with intrinsic religiosity in the glossolalia group. In conclusion, our results demonstrated a substantial difference in the mentalizing ability of glossolalists (generalized hypermentalization) and patients with schizophrenia (both hypo- and hypermentalization).
The Apple Autophagy-Related Gene MdATG9 Confers Tolerance to Low Nitrogen in Transgenic Apple Callus

Autophagy is an efficient degradation system for maintaining cellular homeostasis when plants are under environmental stress. ATG9 is the only integral membrane protein within the core ATG machinery that provides a membrane source for autophagosome formation. In this study, we isolated an ATG9 homologs gene in apple, MdATG9, from Malus domestica. The analysis of its sequence, subcellular localization, promoter cis-elements, and expression patterns revealed the potential function of MdATG9 in response to abiotic stressors. Overexpression of MdATG9 in apple callus conferred enhanced tolerance to nitrogen depletion stress. During the treatment, other important MdATGs were expressed at higher levels in transgenic callus than in the wild type. Furthermore, more free amino acids and increased sucrose levels were found in MdATG9-overexpression apple callus compared with the wild type in response to nitrogen starvation, and the expression levels of MdNRT1.1, MdNRT2.5, MdNIA1, and MdNIA2 were all increased higher in transgenic lines. These data suggest that, as an important autophagy gene, MdATG9 plays an important role in the maintenance of amino acids and sugars in response to nutrient starvation in apple.
Perinatal Determinants of Child Maltreatment in Japan

Background: Child maltreatment induces significant health problems, both during childhood and into adulthood. To prevent child maltreatment, it is important to detect perinatal risk factors for earlier intervention. The aim of this study was to evaluate the perinatal risk factors associated with child maltreatment during pregnancy. Methods: A case-control study was conducted to compare perinatal data from the Maternal and Child Health Handbook between the case and control groups. Cases were collected from children registered in two Child Guidance Centers in Japan. The control group consisted of 3.5-year-old children in a city in Osaka Prefecture whose mothers responded to questionnaires containing information from the Maternal and Child Health Handbook. The association between perinatal factors and child maltreatment was assessed using multiple logistic regression analysis. Results: The data of 70 cases and 345 controls were collected. The following were found to be perinatal factors related to child maltreatment: teenage pregnancy (OR: 257.3, 95% CI: 17.3–3832.7), a mother aged 20–24 years (OR: 22.8, 95% CI: 4.4–117.8), a father who is older than the mother by 10 years or more (OR: 14.1, 95% CI: 2.1–94.8), an unmarried mother (OR: 15.7, 95% CI: 2.6–93.6), maternal mental disorder (OR: 48.9, 95% CI: 9.3–258.3), the first maternal prenatal visit being later than 20 weeks (OR: 132, 95% CI: 12.7–1384.7), little prenatal care (<10 visits) (OR: 21.4, 95% CI: 2.9–157.1), a low-birth-weight baby (OR: 5.1, 95% CI: 1.1–24.1), and congenital disease (OR: 7.9, 95% CI: 1.1–56.4). Conclusions: This study revealed that young mothers, fathers much older than mothers, unmarried mothers, and maternal mental disorder, mothers with late first visit or little perinatal care, and low-birth-weight babies and babies with congenital disease were associated with child maltreatment. These findings can be used to detect high-risk families for child maltreatment during or after pregnancy.
Nonalcoholic Fatty Liver Disease Is Associated With Low Skeletal Muscle Mass in Overweight/Obese Youths

Background: Recent studies in adult non-elderly and elderly individuals have reported a link between nonalcoholic fatty liver disease (NAFLD) and sarcopenia. Nonetheless, whether this relationship would be found outside these populations it is still unknown. Hence, we evaluated the relationship between NAFLD and skeletal muscle mass in children and adolescents with overweight/obesity. Methods: Two-hundred and thirty-four overweight/obese youths were enrolled. NAFLD was diagnosed by ultrasononography, after exclusion of infectious and metabolic disorders. Forty of the patients with NAFLD had also liver biopsy. Total and regional lean body mass and total fat mass measurements were obtained by dual-energy X-ray absorptiometry. The relative muscle mass (RMM) was defined as the percent of muscle mass (kg) relative to the sum of muscle and fat (kg) mass. Appendicular skeletal muscle mass (ASM) was calculated by the sum of muscle masses of the four limbs (kg), and expressed as percent of body weight. Results: Subjects were stratified according to tertiles of RMM. The prevalence of abdominal obesity, dyslipidemia, insulin resistance, metabolic syndrome, NAFLD as well as biopsy-proven nonalcoholic steatohepatitis (NASH) was significantly increased in the lowest tertile of RMM. After controlling for age, sex and Tanner stage, children in the lowest tertile of RMM had an increased risk for NAFLD (OR= 2.80, 95% CI=1.57–5.02) compared to those in the other two tertiles. This association persisted after additional adjustments for clinical and metabolic variables. Similarly, the risk of NAFLD in the lowest tertile of ASM/weight index was significantly higher compared to those in the other two tertiles after adjustment for the above confounders. Conclusions: This is the first study to establish an independent association between low muscle mass and NAFLD/NASH in overweight/obese youths. Considering the worldwide increase of pediatric obesity, measurements of muscle mass may serve as useful method of identifying among obese children those at high metabolic risk who may need intensive lifestyle interventions to prevent NAFLD and its progression.
Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci

Genome-wide association studies (GWAS) have revealed thousands of genetic loci that underpin the complex biology of many human traits. However, the strength of GWAS – the ability to detect genetic association by linkage disequilibrium (LD) – is also its limitation. Whilst the ever-increasing study size and improved design have augmented the power of GWAS to detect effects, differentiation of causal variants or genes from other highly correlated genes associated by LD remains the real challenge. This has severely hindered the biological insights and clinical translation of GWAS findings. Although thousands of disease susceptibility loci have been reported, causal genes at these loci remain elusive. Machine learning (ML) techniques offer an opportunity to dissect the heterogeneity of variant and gene signals in the post-GWAS analysis phase. ML models for GWAS prioritization vary greatly in their complexity, ranging from relatively simple logistic regression approaches to more complex ensemble models such as random forests and gradient boosting, as well as deep learning models, i.e., neural networks. Paired with functional validation, these methods show important promise for clinical translation, providing a strong evidence-based approach to direct post-GWAS research. However, as ML approaches continue to evolve to meet the challenge of causal gene identification, a critical assessment of the underlying methodologies and their applicability to the GWAS prioritization problem is needed. This review investigates the landscape of ML applications in three parts: selected models, input features, and output model performance, with a focus on prioritizations of complex disease associated loci. Overall, we explore the contributions ML has made towards reaching the GWAS end-game with consequent wide-ranging translational impact.
A Standard Lipid Panel Is Insufficient for the Care of a Patient on a High-Fat, Low-Carbohydrate Ketogenic Diet

High-fat, low-carbohydrate ketogenic diets have recently become popular for weight loss and the treatment of numerous chronic diseases; however, the general medical community still expresses concern regarding the impact of high-fat diets on serum lipids and cardiovascular risk. Herein, we report on a young man who adopted a ketogenic diet to treat his inflammatory bowel disease. Incidentally, changes in his serum lipids that would be considered adverse by current standards were noted. A more critical analysis of his lipid profile suggests that the changes he experienced may not be dangerous and may, at least with regard to several parameters, represent improvements. This case study demonstrates how the manner in which lipid panels are often reported and reviewed can lead to misleading conclusions and highlights that, at least in the care of those on a ketogenic diet, more nuanced analyses of lipid subfractionations should be conducted in order for physicians to provide optimal care and clinical recommendations.