Miracle-dz/UniFAR-FTUs huggingface dataset:
Adherence to Orthodontic Treatment in Youth With Cleft Lip and/or Palate

Objective: To identify rates of nonadherence to orthodontic treatment among youth with cleft lip and/or palate (CL/P) and to compare demographic and clinical characteristics of patients categorized as adherent or nonadherent. Design: Retrospective chart review. Setting: Orthodontic treatment program affiliated with a US pediatric hospital-based craniofacial team. Participants: Medical charts of 54 patients with CL/P beginning phase I or phase II orthodontics between 2011 and 2014 (54% male; mean age: 11.7 ± 3.2 years) were reviewed. Main Outcome Measure(s): Data abstracted included demographic and clinical characteristics. Patients were classified as nonadherent based upon treatment termination due to nonadherence, treatment courses extending beyond 3 years, and information about missed appointments, poor oral hygiene, and broken appliances. Results: In all, 24% had treatment terminated due to nonadherence and were significantly more likely to have behavioral health diagnoses (P = .01) or visits (P = .02) and social work consults (P = .01) than patients without termination. Thirty-seven percent had treatment courses beyond 3 years; youth with longer courses were significantly more likely to have cleft lip and palate versus cleft palate only or cleft lip (P = .03). Patients who missed more than 4 appointments were less likely to have behavioral health diagnoses (P < .01) compared to those with fewer missed appointments. Poor hygiene and broken appliance notations were common. Youth with poor hygiene notations were significantly older (P < .01) at treatment initiation than those without notations. Conclusions: Nonadherence was associated with diagnosis, age, and history of behavioral health or social work involvement. An understanding of adherence and relationships with clinical and demographic factors can inform clinical care and support intervention development to improve outcomes.
Geomicrobiology of a seawater-influenced active sulfuric acid cave

Fetida Cave is an active sulfuric acid cave influenced by seawater, showing abundant microbial communities that organize themselves under three main different morphologies: water filaments, vermiculations and moonmilk deposits. These biofilms/deposits have different cave distribution, pH, macro- and microelement and mineralogical composition, carbon and nitrogen content. In particular, water filaments and vermiculations had circumneutral and slightly acidic pH, respectively, both had abundant organic carbon and high microbial diversity. They were rich in macro- and microelements, deriving from mineral dissolution, and, in the case of water filaments, from seawater composition. Vermiculations had different color, partly associated with their mineralogy, and unusual minerals probably due to trapping capacities. Moonmilk was composed of gypsum, poor in organic matter, had an extremely low pH (0–1) and low microbial diversity. Based on 16S rRNA gene analysis, the microbial composition of the biofilms/deposits included autotrophic taxa associated with sulfur and nitrogen cycles and biomineralization processes. In particular, water filaments communities were characterized by bacterial taxa involved in sulfur oxidation and reduction in aquatic, aphotic, microaerophilic/anoxic environments (Campylobacterales, Thiotrichales, Arenicellales, Desulfobacterales, Desulforomonadales) and in chemolithotrophy in marine habitats (Oceanospirillales, Chromatiales). Their biodiversity was linked to the morphology of the water filaments and their collection site. Microbial communities within vermiculations were partly related to their color and showed high abundance of unclassified Betaproteobacteria and sulfur-oxidizing Hydrogenophilales (including Sulfuriferula), and Acidiferrobacterales (including Sulfurifustis), sulfur-reducing Desulfurellales, and ammonia-oxidizing Planctomycetes and Nitrospirae. The microbial community associated with gypsum moonmilk showed the strong dominance (>60%) of the archaeal genus Thermoplasma and lower abundance of chemolithotrophic Acidithiobacillus, metal-oxidizing Metallibacterium, Sulfobacillus, and Acidibacillus. This study describes the geomicrobiology of water filaments, vermiculations and gypsum moonmilk from Fetida Cave, providing insights into the microbial taxa that characterize each morphology and contribute to biogeochemical cycles and speleogenesis of this peculiar seawater-influenced sulfuric acid cave.
Referral of patients with diabetic foot ulcers in four European countries: patient follow-up after first GP visit.

OBJECTIVE This study aimed to analyse the characteristics of patients, including demographics, medical history and treatment, with a diabetic foot ulcer (DFU) during their first follow-up visit to a general practitioner (GP). METHODS A two-part quantitative online questionnaire was distributed among GPs in France, UK, Germany and Spain. Part one entailed a survey of GPs' perceptions of referrals for DFU. Part two collected data on recently managed DFU cases. The percentage of responses was compared for each question and across the four countries for significant differences. RESULTS In part one of the study, 600 questionnaires were collected (150 per country) and 1188 patients managed for a DFU were included in the second part. About 88% of patients had type 2 diabetes, with a significant proportion of suboptimal control (average HbA1c: 10.64mmol/l). A patient complaint led to diagnosis in 60% of the cases. Wounds were found to be more frequently located in the toes and midfoot, and were superficial (according to the Texas Wound Classification system) in 80% of the cases. More than two-thirds of patients developed small wounds (<5cm2); more than half of them had infected wounds. Approximately 50% of wounds were ischaemic, which triggered the onset of a DFU. Follow-up wound examinations before and after hospitalisation were performed by nurses, except in Germany where GPs undertook this role, including prescribing offloading devices and in the UK where follow-up was managed by podiatrists. Ischaemia, wound necrosis, suspected osteomyelitis and absence of wound healing were the primary reasons for hospital admission during the first month after diagnosis. CONCLUSION Delay in specialised foot care is a recurring topic in the treatment of DFUs, even with different health-care structures across Europe. Knowledge and education on DFUs should be reinforced among GPs and nurses to establish a global DFU care network between primary and specialised care, avoid hospitalisation and adequately manage high-risk patients.
Speaker Identification Based On Discriminative Vector Quantization And Data Fusion

Speaker Identification (SI) approaches based on discriminative Vector Quantization (VQ) and data fusion techniques are presented in this dissertation. The SI approaches based on Discriminative VQ (DVQ) proposed in this dissertation are the DVQ for SI (DVQSI), the DVQSI with Unique speech feature vector space segmentation for each speaker pair (DVQSI-U), and the Adaptive DVQSI (ADVQSI) methods. The difference of the probability distributions of the speech feature vector sets from various speakers (or speaker groups) is called the interspeaker variation between speakers (or speaker groups). The interspeaker variation is the measure of template differences between speakers (or speaker groups). All DVQ based techniques presented in this contribution take advantage of the interspeaker variation, which are not exploited in the previous proposed techniques by others that employ traditional VQ for SI (VQSI). All DVQ based techniques have two modes, the training mode and the testing mode. In the training mode, the speech feature vector space is first divided into a number of subspaces based on the interspeaker variations. Then, a discriminative weight is calculated for each subspace of each speaker or speaker pair in the SI group based on the interspeaker variation. The subspaces with higher interspeaker variations play more important roles in SI than the ones with lower interspeaker variations by assigning larger discriminative weights. In the testing mode, discriminative weighted average VQ distortions instead of equally weighted average VQ distortions are used to make the SI decision. The DVQ based techniques lead to higher SI accuracies than VQSI.
Newborn Mortality in Sub-Saharan Africa: Why is Perinatal Asphyxia Still a Major Cause?

Abstract Global new-born mortality has shown steady decline over the last two decades, but this decline has been slowest in Sub-Saharan Africa (SSA). Perinatal asphyxia (PA) is a major cause of new-born deaths in this region and as such SSA now contributes a disproportionate large percentage of global asphyxia-related deaths. In this paper, we examine regional challenges affecting primary, secondary and tertiary prevention of PA and proffers locally adaptable solutions to these identified challenges.
Relational Scaffolding Enhances Children’s Understanding of Scientific Models

Models are central to the practice and teaching of science. Yet people often fail to grasp how scientific models explain their observations of the world. Realizing the explanatory power of a model may require aligning its relational structure to that of the observable phenomena. In the present study, we tested whether relational scaffolding—guided comparisons between observable and modeled events—enhances children’s understanding of scientific models. We tested relational scaffolding during instruction of third graders about the day/night cycle, a topic that involves relating Earth-based observations to a space-based model of Earth’s rotation. Experiment 1 found that participants (N = 108) learned more from instruction that incorporated relational scaffolding. Experiment 2 (N = 99) found that guided comparison—not merely viewing observable and modeled events—is a critical component of relational scaffolding, especially for children with low initial knowledge. Relational scaffolding could be applied broadly to assist the many students who struggle with science.
Drug repurposing for the treatment of alveolar echinococcosis: in vitro and in vivo effects of silica nanoparticles modified with dichlorophen

Abstract Alveolar echinococcosis is a neglected parasitic zoonosis caused by the metacestode Echinococcus multilocularis, which grows as a malignant tumour-like infection in the liver of humans. Albendazole (ABZ) is the antiparasitic drug of choice for the treatment of the disease. However, its effectiveness is low, due to its poor absorption from the gastro-intestinal tract. It is also parasitostatic and in some cases produces side-effects. Therefore, an alternative to the treatment of this severe human disease is necessary. In this context, the repositioning of drugs combined with nanotechnology to improve the bioavailability of drugs emerges as a useful, fast and inexpensive tool for the treatment of neglected diseases. The in vitro and in vivo efficacy of dichlorophen (DCP), an antiparasitic agent for intestinal parasites, and silica nanoparticles modified with DCP (NP-DCP) was evaluated against E. multilocularis larval stage. Both formulations showed a time and dose-dependent in vitro effect against protoscoleces. The NP-DCP had a greater in vitro efficacy than the drug alone or ABZ. In vivo studies demonstrated that the NP-DCP (4 mg kg−1) had similar efficacy to ABZ (25 mg kg−1) and greater activity than the free DCP. Therefore, the repurposing of DCP combined with silica nanoparticles could be an alternative for the treatment of echinococcosis.
Capacity of juvenile probation officers in low-resourced, rural settings to deliver an evidence-based substance use intervention to adolescents.

Substance use is a major public health problem with a host of negative outcomes. Justice-involved youth have even higher risks and lack access to evidence-based interventions, particularly in rural communities. Task-shifting, or redistribution of tasks downstream to an existing workforce with less training, may be an innovative strategy to increase access to evidence-based interventions. Initial findings are presented from a services research trial conducted primarily in rural communities in which an existing workforce, juvenile probation/parole officers (JPOs), were randomized either to learn and deliver contingency management (CM) or to continue delivering probation services as usual (PAU). This study used the prevailing version of CM for adolescents, that is, family-based with behavior modification and cognitive behavioral components. Data included JPOs' self-reports, as well as audio-recorded youth/family sessions with JPOs rated by expert and trained observational coders. Data also included ratings from a comparison study in which therapists were trained and supervised by experts to deliver CM to justice-involved youth/families. Results showed JPOs can feasibly incorporate CM into their services. When adherence of CM JPOs was compared against CM therapists, JPOs delivered significantly more cognitive behavioral components of CM and similar levels of behavior modification components of CM. These findings suggest that JPOs can be leveraged to provide evidence-based substance use interventions like CM in similar, or even greater, capacities to clinically trained therapists. This task-shifting approach could dramatically expand service access for these high-risk youth, particularly in rural areas where substance use services are limited or nonexistent. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Bayesian learning for data-efficient control

Applications to learn control of unfamiliar dynamical systems with increasing autonomy are ubiquitous. From robotics, to finance, to industrial processing, autonomous learning helps obviate a heavy reliance on experts for system identification and controller design. Often real world systems are nonlinear, stochastic, and expensive to operate (e.g. slow, energy intensive, prone to wear and tear). Ideally therefore, nonlinear systems can be identified with minimal system interaction. This thesis considers data efficient autonomous learning of control of nonlinear, stochastic systems. Data efficient learning critically requires probabilistic modelling of dynamics. Traditional control approaches use deterministic models, which easily overfit data, especially small datasets. We use probabilistic Bayesian modelling to learn systems from scratch, similar to the PILCO algorithm, which achieved unprecedented data efficiency in learning control of several benchmarks. We extend PILCO in three principle ways. First, we learn control under significant observation noise by simulating a filtered control process using a tractably analytic framework of Gaussian distributions. In addition, we develop the ‘latent variable belief Markov decision process’ when filters must predict under real-time constraints. Second, we improve PILCO’s data efficiency by directing exploration with predictive loss uncertainty and Bayesian optimisation, including a novel approximation to the Gittins index. Third, we take a step towards data efficient learning of high-dimensional control using Bayesian neural networks (BNN). Experimentally we show although filtering mitigates adverse effects of observation noise, much greater performance is achieved when optimising controllers with evaluations faithful to reality: by simulating closed-loop filtered control if executing closed-loop filtered control. Thus, controllers are optimised w.r. t. how they are used, outperforming filters applied to systems optimised by unfiltered simulations. We show directed exploration improves data efficiency. Lastly, we show BNN dynamics models are almost as data efficient as Gaussian process models. Results show data efficient learning of high-dimensional control is possible as BNNs scale to high-dimensional state inputs.
Ketamine as augmentation for the treatment of major depression and suicidal risk in advanced cancer: Case report

Abstract Objective Major depressive disorder (MDD) is common in patients diagnosed with advanced cancer (AC), with a prevalence of 16.5%. It is associated with great disability and worsened quality of life, increased number and intensity of physical symptoms, and lower survival. It is the main factor for the presence of suicidal ideation. Antidepressants show modest efficacy, and response requires several weeks. Ketamine has demonstrated a fast and robust antidepressant effect in subanesthetic doses. This effect may prove useful in patients with AC, MDD, and suicidal risk. Method We report a case of a patient with advanced cervical cancer who presented with uncontrollable pain, MDD, and a suicide attempt. Result A 39-year-old woman diagnosed with cervical cancer stage IVB presented to the Emergency Department after a suicide attempt by hanging. Upon evaluation by the palliative care psychiatrist, she reported intense pain, unresponsive to analgesics, and had a history of persistent suicidal ideation. Antidepressant treatment was started (sertraline 50mg/d) after a single dose of ketamine hydrochloride IV (0.5 mg/kg) was administered. Treatment response was measured using the Brief Edinburgh Depression Scale before and after the intervention. The depressive symptoms decreased by 17% on day 1, 39% on day 3, and 72% on day 17. Significance of results This case report shows ketamine's efficacy as an augmentation agent alongside conventional antidepressant treatment in patients with AC. Moreover, it shows rapid response in suicidal ideation that has not been achieved with treatment as usual. More clinical trials are needed to support the potential benefit and safety of ketamine in patients with AC, MDD, and persisting suicidal ideation.
Customized MethylC-Capture Sequencing to Evaluate Variation in the Human Sperm DNA Methylome Representative of Altered Folate Metabolism

Background: The sperm DNA methylation landscape is unique and critical for offspring health. If gamete-derived DNA methylation escapes reprograming in early embryos, epigenetic defects in sperm may be transmitted to the next generation. Current techniques to assess sperm DNA methylation show bias toward CpG-dense regions and do not target areas of dynamic methylation, those predicted to be environmentally sensitive and tunable regulatory elements. Objectives: Our goal was to assess variation in human sperm DNA methylation and design a targeted capture panel to interrogate the human sperm methylome. Methods: To characterize variation in sperm DNA methylation, we performed whole genome bisulfite sequencing (WGBS) on an equimolar pool of sperm DNA from a wide cross section of 30 men varying in age, fertility status, methylenetetrahydrofolate reductase (MTHFR) genotype, and exposures. With our targeted capture panel, in individual samples, we examined the effect of MTHFR genotype (n=13 677CC, n=8 677TT), as well as high-dose folic acid supplementation (n=6, per genotype, before and after supplementation). Results: Through WGBS we discovered nearly 1 million CpGs possessing intermediate methylation levels (20–80%), termed dynamic sperm CpGs. These dynamic CpGs, along with 2 million commonly assessed CpGs, were used to customize a capture panel for targeted interrogation of the human sperm methylome and test its ability to detect effects of altered folate metabolism. As compared with MTHFR 677CC men, those with the 677TT genotype (50% decreased MTHFR activity) had both hyper- and hypomethylation in their sperm. High-dose folic acid supplement treatment exacerbated hypomethylation in MTHFR 677TT men compared with 677CC. In both cases, >80% of altered methylation was found in dynamic sperm CpGs, uniquely measured by our assay. Discussion: Our sperm panel allowed the discovery of differential methylation following conditions affecting folate metabolism in novel dynamic sperm CpGs. Improved ability to examine variation in sperm DNA methylation can facilitate comprehensive studies of environment–epigenome interactions. https://doi.org/10.1289/EHP4812
Assessing the Intergenerational Linkage between Short Maternal Stature and Under-Five Stunting and Wasting in Bangladesh

Short maternal stature is identified as a strong predictor of offspring undernutrition in low and middle-income countries. However, there is limited information to confirm an intergenerational link between maternal and under-five undernutrition in Bangladesh. Therefore, this study aimed to assess the association between short maternal stature and offspring stunting and wasting in Bangladesh. For analysis, this study pooled the data from four rounds of Bangladesh Demographic and Health Surveys (BDHS) 2004, 2007, 2011, and 2014 that included about 28,123 singleton children aged 0–59 months born to mothers aged 15–49 years. Data on sociodemographic factors, birth history, and anthropometry were analyzed using STATA 14.2 to perform a multivariable model using ‘Modified Poisson Regression’ with step-wise backward elimination procedures. In an adjusted model, every 1 cm increase in maternal height significantly reduced the risk of stunting (relative risks (RR) = 0.960; 95% confidence interval (CI): 0.957, 0.962) and wasting (RR = 0.986; 95% CI: 0.980, 0.992). The children of the short statured mothers (<145 cm) had about two times greater risk of stunting and three times the risk of severe stunting, 1.28 times the risk of wasting, and 1.43 times the risk of severe wasting (RR = 1.43; 95% CI: 1.11, 1.83) than the tall mothers (≥155 cm). These findings confirmed a robust intergenerational linkage between short maternal stature and offspring stunting and wasting in Bangladesh.
Current Knowledge of the Potential Links between Inflammation and Prostate Cancer

Inflammation is inherent in prostatic diseases and it is now accepted that it may facilitate cellular proliferation in both benign and malignant conditions. The strong relationship between prostatic inflammation and pathogenesis of benign prostatic hyperplasia (BPH) is supported by epidemiologic, histopathologic and molecular evidence. Contrariwise, the role of inflammation in prostate carcinogenesis is still controversial, although current data indicate that the inflammatory microenvironment can regulate prostate cancer (PCa) growth and progression. Knowledge of the complex molecular landscape associated with chronic inflammation in the context of PCa may lead to the introduction and optimization of novel targeted therapies. In this perspective, evaluation of the inflammatory component in prostate specimens could be included in routine pathology reports.
BMP7 improves insulin signal transduction in the liver.

Bone morphogenetic protein 7 (BMP7), a member of the transforming growth factor-β (TGF-β) family, plays pivotal roles in energy expenditure. However, whether and how BMP7 regulates hepatic insulin sensitivity is still poorly understood. Here, we show that hepatic BMP7 expression is reduced in high-fat diet (HFD)-induced diabetic mice and palmitate (PA)-induced insulin resistant HepG2 and AML12 cells. BMP7 improves insulin signaling pathway in insulin resistant hepatocytes. On the contrary, knockdown of BMP7 further impairs insulin signal transduction in PA-treated cells. Increased expression of BMP7 by adenovirus expressing BMP7 improves hyperglycemia, insulin sensitivity and insulin signal transduction. Furthermore, BMP7 inhibits mitogen-activated protein kinases (MAPKs) in both the liver of obese mice and PA-treated cells. In addition, inhibition of MAPKs recapitulates the effects of BMP7 on insulin signal transduction in cultured hepatocytes treated with PA. Activation of p38 MAPK abolishes the BMP7-mediated up-regulation of insulin signal transduction both in vitro and in vivo. Together, our results show that hepatic BMP7 has a novel function in regulating insulin sensitivity through inhibition of MAPKs, thus providing new insights into treating insulin resistance related disorders such as type 2 diabetes.