Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of iron-deficiency anaemia in Brazilian children under 5 years of age: a systematic review and meta-analysis

Abstract Fe-deficiency anaemia is considered an important public health problem both in wealthier countries and in those of medium and low income, especially in children under 5 years of age. The shortage of studies with national representativity in medium-income countries, such as Brazil, prevents the knowledge of the current situation and its associated factors. We conducted a systematic review and meta-analysis to estimate the pooled prevalence of Fe-deficiency anaemia in Brazilian children under 5 years of age and determined the factors involved in the variability of the estimates of prevalence. We collected fifty-seven studies from the databases MEDLINE, LILACS and Web of Science, along with the reference lists of included articles. We contacted authors for unpublished data. We did not restrict publication timespan and language. This systematic review and meta-analysis was reported according to the guidelines by PRISMA. The pooled prevalence of anaemia in Brazil was 40·2 (95 % CI 36·0, 44·8) %. The age range of the child and the period of data collection were associated with the anaemia prevalence. The pooled prevalence of anaemia was higher in children under 24 months of age (53·5 v. 30·7 %; P < 0·001) and in studies with data collected before 2004 (51·8 v. 32·6 %; P = 0·001). The efforts made by the Brazilian government were successful in the reduction of anaemia in children under 5 years of age in Brazil in the evaluated period. However, prevalence remains beyond acceptable levels for this population group.
Surgeon Preference for Keratoplasty Techniques and Barriers to Performing Deep Anterior Lamellar Keratoplasty

Supplemental Digital Content is Available in the Text. Purpose: To identify barriers and facilitators to adopting deep anterior lamellar keratoplasty (DALK) for nonendothelial corneal pathology. Methods: An anonymous survey consisting of 22 multiple choice and free text questions was designed to gather information on demographic factors of surgeons and DALK surgical practices. The survey was emailed to members of the kera-net, a global online corneal surgeon/surgery platform. Results: A total of 100 surgeons completed the survey, most of whom practice in the United States (73%). Most surgeons (89%) reported performing DALK. Surgeons who did not learn DALK during fellowship (34%) tended to be in practice for higher numbers of years (P < 0.001). Surgeons in private practice are more likely to perform DALK versus those in other settings (92.7% vs. 80.8%, P = 0.087). Surgeons performing more corneal surgeries (at least 100 per year) are more likely to perform DALK than those who perform fewer than 100 per year (52% vs. 14%, P = 0.01). Surgeons who perform Descemet membrane endothelial keratoplasty are more likely to perform DALK than those who do not (81.7% vs. 18.3%, P = 0.014). There was also a positive correlation between PK and DALK surgical volumes (Spearman rank correlation coefficient = 0.57, P < 0.001). The main reasons for surgeon preference for DALK over PK were a desire to preserve the endothelium, intraoperative safety, and decreased complications. Longer surgical time and low patient volume were cited as barriers to adoption of DALK. Conclusions: Alterations in DALK technique that reduce surgical time and providing more learning opportunities for DALK might improve adoption.
Evaluation of the performance of various machine learning methods on the discrimination of the active compounds

Machine learning (ML) method performances, including deep learning (DL) on a diverse set with or without feature selection (FS), were evaluated. The superior performance of DL on small sets has not been approved previously. On the other hand, the available sets for the newly identified targets usually are limited in terms of size. It was explored whether the FS, hyperparameters search, and using ensemble model are able to improve the ML and DL performance on the small sets. The QSAR classifier models were developed using K‐nearest (KN) neighbors, DL, random forest (RF), naïve Bayesian (NB) classification, support vector machine (SVM), and logistic regression (LR). Generally, the best individual performers were DL and SVM. The LR had a similar performance to the DL and SVM on the small subsets. The nested cross‐validation method was able to include different feature vectors in combination with different ML methods to generate an ensemble model for the datasets with similar performance to the best performers. The general performance for the baseline NB model was Matthews correlation coefficient = 0.356, and it was improved to around 0.66 and 0.63 by NB assisted FS with subsequent SVM/DL classification and an ensemble model, respectively.
Thermal Analysis In Optical Waveguides

Analisis haba di dalam struktur pandu gelombang optik telah dijalankan untuk mengkaji taburan suhu keratan rentas apabila dipanaskan dengan elemen pemanas. Persamaan umum haba diprogramkan menggunakan kaedah berangka pembezaan terhingga. Perbezaan keputusan yang ketara telah diperoleh apabila nilai keberaliran haba yang berbeza bagi setiap elemen pandu gelombang dan mekanisma konveksi ke persekitaran dipertimbangkan. Kata kunci: Kesan termo–optik, analisis terma, kaedah pembezaan terhingga A thermal analysis in optical waveguides structure is simulated in order to predict the temperature distribution over the waveguide cross–section, when heated by a heating element. A steady state heat equation is solved by using finite difference numerical method. It is observed that by applying different value of thermal conductivities for each waveguide element and further application of convection mechanism to the ambient, obvious differences with other researchers’ work are recorded. Key words: Thermo–optic effect, thermal analysis, finite difference method
Structural analyses of the PKA RIIβ holoenzyme containing the oncogenic DnaJB1-PKAc fusion protein reveal protomer asymmetry and fusion-induced allosteric perturbations in fibrolamellar hepatocellular carcinoma

When the J-domain of the heat shock protein DnaJB1 is fused to the catalytic (C) subunit of cAMP-dependent protein kinase (PKA), replacing exon 1, this fusion protein, J-C subunit (J-C), becomes the driver of fibrolamellar hepatocellular carcinoma (FL-HCC). Here, we use cryo-electron microscopy (cryo-EM) to characterize J-C bound to RIIβ, the major PKA regulatory (R) subunit in liver, thus reporting the first cryo-EM structure of any PKA holoenzyme. We report several differences in both structure and dynamics that could not be captured by the conventional crystallography approaches used to obtain prior structures. Most striking is the asymmetry caused by the absence of the second cyclic nucleotide binding (CNB) domain and the J-domain in one of the RIIβ:J-C protomers. Using molecular dynamics (MD) simulations, we discovered that this asymmetry is already present in the wild-type (WT) RIIβ2C2 but had been masked in the previous crystal structure. This asymmetry may link to the intrinsic allosteric regulation of all PKA holoenzymes and could also explain why most disease mutations in PKA regulatory subunits are dominant negative. The cryo-EM structure, combined with small-angle X-ray scattering (SAXS), also allowed us to predict the general position of the Dimerization/Docking (D/D) domain, which is essential for localization and interacting with membrane-anchored A-Kinase-Anchoring Proteins (AKAPs). This position provides a multivalent mechanism for interaction of the RIIβ holoenzyme with membranes and would be perturbed in the oncogenic fusion protein. The J-domain also alters several biochemical properties of the RIIβ holoenzyme: It is easier to activate with cAMP, and the cooperativity is reduced. These results provide new insights into how the finely tuned allosteric PKA signaling network is disrupted by the oncogenic J-C subunit, ultimately leading to the development of FL-HCC.
Germline Cancer-Predisposition Variants in Pediatric Rhabdomyosarcoma: A Report from the Children's Oncology Group.

BACKGROUND Several cancer-susceptibility syndromes are reported to underlie pediatric rhabdomyosarcoma (RMS); however, there have been no systematic efforts to characterize the heterogeneous genetic etiologies of this often-fatal malignancy. METHODS We performed exome-sequencing on germline DNA from 615 patients with newly diagnosed RMS consented through the Children's Oncology Group. We compared the prevalence of cancer-predisposition variants in 63 autosomal dominant cancer-predisposition genes in these patients with population controls (n = 9,963). All statistical tests were two-sided. RESULTS We identified germline cancer-predisposition variants in 45 RMS patients (7.3%; all FOXO1 fusion-negative) across 15 autosomal dominant genes, which was statistically significantly enriched compared with controls (1.4%; p = 1.3 × 10-22). Specifically, 73.3% of the predisposition variants were found in predisposition syndrome genes previously associated with pediatric RMS risk, such as Li-Fraumeni syndrome (TP53) and neurofibromatosis type I (NF1). Notably, five patients had well-described oncogenic missense variants in HRAS (p.G12V and p. G12S) associated with Costello syndrome. Also, genetic etiology differed with histology, as germline variants were more frequent in embryonal versus alveolar RMS patients (10.0% vs. 3.0%, p = .02). While patients with a cancer-predisposition variant tended to be younger at diagnosis (p = 9.9 × 10-4), 40.0% of germline variants were identified in those >3 years of age, which is in contrast to current genetic testing recommendations based on early age at diagnosis. CONCLUSIONS These findings demonstrate that genetic risk of RMS results from germline predisposition variants associated with a wide spectrum of cancer-susceptibility syndromes. Germline genetic testing for children with RMS should be informed by RMS subtypes and not be limited to only young patients.
Breast Cancer Organoids Model Patient-Specific Response to Drug Treatment

Simple Summary The possibility to generate in the laboratory faithful models of patients’ tumors is of primary importance to capture cancer complexity and study therapy response in a personalized setting. Tumor organoids are 3D cell cultures, obtained from patients’ tumor tissues, that recapitulate several characteristics of the original tumor, thus representing a clinically relevant patient avatar. This study reports the generation and the molecular characterization of patient-derived organoids from invasive breast carcinomas. Our results proved the usefulness of these cancer models for designing patient-specific therapeutic approaches to treat highly aggressive cancers, but also highlighted the need to further improve this methodology to overcome its current limitations. Abstract Tumor organoids are tridimensional cell culture systems that are generated in vitro from surgically resected patients’ tumors. They can be propagated in culture maintaining several features of the tumor of origin, including cellular and genetic heterogeneity, thus representing a promising tool for precision cancer medicine. Here, we established patient-derived tumor organoids (PDOs) from different breast cancer subtypes (luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple negative). The established model systems showed histological and genomic concordance with parental tumors. However, in PDOs, the ratio of diverse cell populations was frequently different from that originally observed in parental tumors. We showed that tumor organoids represent a valuable system to test the efficacy of standard therapeutic treatments and to identify drug resistant populations within tumors. We also report that inhibitors of mechanosignaling and of Yes-associated protein 1 (YAP) activation can restore chemosensitivity in drug resistant tumor organoids.
Intrusion Survivability for Commodity Operating Systems

Despite the deployment of preventive security mechanisms to protect the assets and computing platforms of users, intrusions eventually occur. We propose a novel intrusion survivability approach to withstand ongoing intrusions. Our approach relies on an orchestration of fine-grained recovery and per-service responses (e.g., privileges removal). Such an approach may put the system into a degraded mode. This degraded mode prevents attackers to reinfect the system or to achieve their goals if they managed to reinfect it. It maintains the availability of core functions while waiting for patches to be deployed. We devised a cost-sensitive response selection process to ensure that while the service is in a degraded mode, its core functions are still operating. We built a Linux-based prototype and evaluated the effectiveness of our approach against different types of intrusions. The results show that our solution removes the effects of the intrusions, that it can select appropriate responses, and that it allows services to survive when reinfected. In terms of performance overhead, in most cases, we observed a small overhead, except in the rare case of services that write many small files asynchronously in a burst, where we observed a higher but acceptable overhead.
Analysis on Influencing Factors of E-loyalty of a Chinese O2O E-commerce Food Delivery Platform

China's real economy sector has seen a general downturn in recent period, whereas the Internet industry has been playing a more significant role in driving economic growth. Since 2010, O2O (Online To Offline) business model has enjoyed a widespread application, notably in catering services. Nevertheless, the continuous proliferation of food delivery services is leading to market saturation, thus initiates a new stage of brand building and user experience enhancement. Finding approaches to effectively improve e-loyalty becomes crucial for companies. This study takes Meituan, market leader in China's e-commerce food market, as an example, applying online survey method and structural equation modeling to analyze users’ motives. The study shows variables affect the e-loyalty on O2O platforms in different levels. E-commerce companies can improve competitiveness by developing strategies and features based on these e-loyalty drivers.
Nishikaze: Self-Sustained Wind Power Supply Employing Potential Energy Conversion Method

In an IoT (Internet of Things) system, if image data can be collected in addition to sensor data, the amount of information obtained will increase significantly, which is very useful for monitoring natural disasters, for example. Considering communication speed and covering range, it is assumed that Wi-Fi multi-hop communication is appropriate for image data transmission. Since Wi-Fi consumes a large amount of power, a power supply for sensor nodes is required. Therefore, we are developing a self-sustaining wind power supply called Nishikaze which employs the potential energy conversion method. In this paper, we produced the Nishikaze second prototype. The measurement results of the amount of the generated power show that the Nishikaze second prototype can cover the power required to transmit an image of 500 kbytes at a 10 minute interval assuming that 3 m/s of wind blows for 6 hours in a day, 100 % of the generated power is available, and the active period of sensor nodes is 5 seconds.
Comparison of Trend Forecast Using ARIMA and ETS Models for S&P500 Close Price

Stock price forecast is pivotal for various financial and economic institutions and individuals. The aim of this study is to present viable and general approaches that would improve the understanding of forecasting stock market close price of individual stock. This paper explains processes of applying methods including Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing (ETS) on the close price data of S&P500 index, but the ticker of the stock can be swapped for forecasting other stocks. In terms of determining the accuracy of the models, we center on the simplest methodology. Of the two models involved in this study, we compare them on the basis of standard deviation. Stock data are obtained from yahoo finance using quantmod package in R studio. Forecasting result shows that the ARIMA model has a better fit with the data and can give a promising general trend prediction compared with existing methods.
The Research on the Influence of Virtual Feedback of Beverage Industry on Customer Loyalty and Other Factors

The research background of this article is based on the virtual feedback of new type of the beverage tea, by conducting scenario experiments and build structural equations, constructed a model of multi-dimensional transfer costs and customer loyalty. The research found that the high transfer costs will increase customer loyalty by three ways, and the relationship switching costs do not influence the customer loyalty directly. In addition, in this article, through cross-group analysis, it is found that different integral plans will have different effects on the above-mentioned way.
DNA methylation mutants in Physcomitrella patens elucidate individual roles of CG and non-CG methylation in genome regulation

Significance While DNA methylation in plants occurs at CG, CHG, and CHH sequence contexts, their comparative roles in genome regulation remain elusive. Here, we utilized Physcomitrella patens as a plant model suitable to study this question. By profiling transcriptomes in a series of context-specific methylation mutants, we found redundancy between asymmetric (CHH) methylation and symmetric methylation in silencing transposons, and that CHH methylation regulates the expression of CG/CHG-depleted transposons. Specific elimination of CG methylation had a significantly smaller effect on transcription than elimination of non-CG methylation. Additionally, we found CHG methylation as a stronger silencer than CG methylation. These results disentangle the transcriptional roles of the individual methylation contexts and elucidate the crucial role of non-CG methylation in genome regulation. Cytosine (DNA) methylation in plants regulates the expression of genes and transposons. While methylation in plant genomes occurs at CG, CHG, and CHH sequence contexts, the comparative roles of the individual methylation contexts remain elusive. Here, we present Physcomitrella patens as the second plant system, besides Arabidopsis thaliana, with viable mutants with an essentially complete loss of methylation in the CG and non-CG contexts. In contrast to A. thaliana, P. patens has more robust CHH methylation, similar CG and CHG methylation levels, and minimal cross-talk between CG and non-CG methylation, making it possible to study context-specific effects independently. Our data found CHH methylation to act in redundancy with symmetric methylation in silencing transposons and to regulate the expression of CG/CHG-depleted transposons. Specific elimination of CG methylation did not dysregulate transposons or genes. In contrast, exclusive removal of non-CG methylation massively up-regulated transposons and genes. In addition, comparing two exclusively but equally CG- or CHG-methylated genomes, we show that CHG methylation acts as a greater transcriptional regulator than CG methylation. These results disentangle the transcriptional roles of CG and non-CG, as well as symmetric and asymmetric methylation in a plant genome, and point to the crucial role of non-CG methylation in genome regulation.
Subsurface damage from helium ions as a function of dose, beam energy, and dose rate

In recent years, helium ion microscopy has produced high resolution images with novel contrast mechanisms. However, when using any charged particle beam, one must consider the potential for sample damage. In this article, the authors will consider helium ion induced damage thresholds as compared to other more traditional charged-particle-beam technologies, as a function of dose, dose rate, and beam energy, and describe potential applications operating regimes.
Promising ferrimagnetic double perovskite oxides towards high spin polarization at high temperature

We predict through our first-principles calculations that four double perovskite oxides of Bi2ABO6 (AB = FeMo, MnMo, MnOs, CrOs) are half-metallic ferrimagnets. Our calculated results shows that the four optimized structures have negative formation energy, from -0.42 to -0.26 eV per formula unit, which implies that they could probably be realized. In the case of Bi2FeMoO6, the half-metallic gap and Curie temperature are predicted to reach to 0.71 eV and 650 K, respectively, which indicates that high spin polarization could be kept at high temperatures far beyond room temperature. It is believed that some of them could be synthesized soon and would prove useful for spintronic applications.
Saturated Fatty Acid Intake Is Associated With Increased Inflammation, Conversion of Kynurenine to Tryptophan, and Delta-9 Desaturase Activity in Healthy Humans

Saturated fat ingestion has previously been linked to increases in inflammation. However the relationship between saturated fatty acid (SFA) intake and the kynureine:tryptophan ratio ([Kyn]:[Trp]), a marker of inflammation, has not been previously investigated. This study evaluated in healthy, middle aged, individuals (men = 48, women = 52), potential relationships between SFA intake, red blood cell (RBC) membrane SFAs and monounsaturated fatty acids (MUFA), the [Kyn]:[Trp] ratio, C-reactive protein (CRP), TNF-α and Δ9 desaturase activity. [Kyn]:[Trp] was positively associated with increases in Total fat (P = .034) intake, including Total SFA (P = .029) and Total MUFA (P = .042) intakes. Unexpectedly the [Kyn]:[Trp] ratio was inversely associated with the percentage of Total SFA (P = .004) and positively associated with percentage of Total MUFA (P = .012) present in the RBC membrane. We found a positive association between Δ9 desaturase activity, responsible for the desaturation of a various SFAs to MUFAs, and [Kyn]:[Trp] (P = .008). [Kyn]:[Trp] was also positively associated with CRP (P = .044), however no significant relationship between [Kyn]:[Trp] and TNF-α was found. This study shows for the first time that SFA consumption increases inflammatory pathways linked to increased tryptophan to kynurenine conversion, even in healthy humans. Our data also suggests that SFA linked increases in inflammation occur concomitantly with an upregulation of Δ9 desaturase activity resulting in increased desaturation of SFA substrates to their MUFA derivatives.