Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Clinical Translation of Cancer Using Nanoinformatics

Simple Summary Two fields of artificial intelligence and nanomedicine are very effective tools in moving towards the goal of personalized medicine. Combination of these fields, i.e., nanoinformatics, enables better access to patient data as well as better nanomaterials design. An ongoing challenge in all forms of drug administration for cancer patients is that drug synergy at any point in treatment is time-dependent, dose-dependent, and patient-specific. Moreover, high heterogeneities of intra-tumor and interpatient make it hard to rationally design diagnostic and dug delivery systems, as well as analyze their results. Integration of artificial intelligence methods (especially data mining, neural networks, and machine learning) can fill these gaps by using classification algorithms and pattern analysis to improve the accuracy of diagnosis, drug delivery, and treatment. In this study, the basic concepts in artificial intelligence are explained and the contributions of nanoinformatics in cancer treatment are reviewed. Abstract Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, i.e., nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.
PREVENTING CHRONIC DISEASE

Introduction Appointment nonadherence is common among people with glaucoma, making it difficult for eye care providers to monitor glaucoma progression. Our objective was to determine whether the use of patient navigators, in conjunction with social worker support, could increase adherence to recommended follow-up eye appointments. Methods A randomized, controlled trial evaluated the effectiveness of an intervention that used patient navigators and social workers to improve patient adherence to follow-up eye care compared with usual care. Participants with glaucoma and other eye diseases (N = 344) were identified at primary care clinics in community settings through telemedicine screening of imaging and then randomized to enhanced intervention (EI) or usual care (UC). Data on participants’ visits with local ophthalmologists were collected for up to 3 years from randomization. Groups were compared for timely attendance at the first visit with the local ophthalmologist and adherence to recommended follow-up visits. Results Timely attendance at the first visit was higher for EI than UC (74.4% vs 39.0%; average relative risk [aRR] = 1.85; 95% CI, 1.51–2.28; P < .001). Rates of adherence to recommended annual follow-up during year 1 were 18.6% in the EI group and 8.1% in the usual care group (aRR = 2.08; 95% CI, 1.14–3.76; P = .02). The aRR across years 2 and 3 was 3.92 (95% CI, 1.24–12.43; P = .02). Conclusion An intervention using patient navigators and social workers doubled the rate of adherence to annual recommended follow-up eye care compared with usual care in community settings, and was effective at increasing connections with local ophthalmologists. Interventions to further improve long-term adherence are needed.
AQR Capital Management, Yale School of Management, and NBER

We propose a new asset-pricing framework in which all securities’ signals are used to predict each individual return. While the literature focuses on each security’s ownsignal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictability—leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a “prediction matrix,” which we call “principal portfolios. ” Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out-of-sample alphas to standard factors in several data sets.
EEG Phase-Amplitude Coupling Strength and Phase Preference: Association with Age over the First Three Years after Birth

Abstract Phase-amplitude coupling (PAC), the coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, is thought to facilitate dynamic integration of neural activity in the brain. Although the brain undergoes dramatic change and development during the first few years of life, how PAC changes through this developmental period has not been extensively studied. Here, we examined PAC through electroencephalography (EEG) data collected during an awake, eyes-open EEG collection paradigm in 98 children between the ages of three months and three years. We employed non-parametric clustering methods to identify areas of significant PAC across a range of frequency pairs and electrode locations, and examined how PAC strength and phase preference develops in these areas. We found that PAC, primarily between the α-β and γ frequencies, was positively correlated with age from early infancy to early childhood (p = 2.035 × 10−6). Additionally, we found γ over anterior electrodes coupled with the rising phase of the α-β waveform, while γ over posterior electrodes coupled with the falling phase of the α-β waveform; this regionalized phase preference became more prominent with age. This opposing trend may reflect each region’s specialization toward feedback or feedforward processing, respectively, suggesting opportunities for back translation in future studies.
Slow-releasing property analysis of modified silicon-potash produced from desiliconized slags from Liquid Iron

Through changing the level of each factor which influences the slow-release characteristics of silicon-potash fertilizer in "The technics of modifying desiliconized slags into slow-release silicon-potash fertilizer",the release rate of potassium in the modified silicon-potash fertilizer was determined in water and citric acid solution,respectively.And then by making statistical and regression analyses of experimental data,and considering the criterions of slow-release fertilizer put forward by Trenkel,a tentative analysis was made for the slow-releasing characteristics of this modified desiliconized slag.Results showed that the silicon-potash fertilizers that were modified under different experiment conditions all had obvious slow-releasing properties and the release rate of potassium in water is less than that in citric acid solution.
PEG3 controls lipogenesis through ACLY

Peg3 (Paternally expressed gene 3) is an imprinted gene encoding a DNA-binding protein that is a well-known transcriptional repressor. Previous studies have shown that the mutant phenotypes of Peg3 are associated with the over-expression of genes involved in lipid metabolism. In the current study, we investigated four potential downstream genes of Peg3, which were identified through ChIP-seq data: Acly, Fasn, Idh1, and Hmgcr. In vivo binding of PEG3 to the promoter region of these key genes involved in lipogenesis was subsequently confirmed through individual ChIP experiments. We observed the opposite response of Acly expression levels against the variable gene dosages of Peg3, involving 0x, 1x, and 2x Peg3. This suggests the transcriptional repressor role of Peg3 in the expression levels of Acly. Another set of analyses showed a sex-biased response in the expression levels of Acly, Fasn, and Idh1 against 0x Peg3 with higher levels in female and lower levels in male mammary glands. These results overall highlight that Peg3 may be involved in regulating the expression levels of several key genes in adipogenesis.
On a Quantitative Approach to Clinical Neuroscience in Psychiatry: Lessons from the Kuramoto Model.

ABSTRACT The human brain is a complex system comprising subregions that dynamically exchange information between its various parts through synchronization. These dynamic, complex interactions ultimately play a role in perception, emotion, cognition, and behavior, as well as in various maladaptive neurologic and psychiatric processes. It is therefore important to understand how brain dynamics might be implicated in these processes. Over the past few years, network neuroscience and computational neuroscience have highlighted the importance of measures such as metastability (a property whereby members of an oscillating system tend to linger at the edge of synchronicity without permanently becoming synchronized) in quantifying brain dynamics. Altered metastability has been implicated in various psychiatric illnesses, such as traumatic brain injury and Alzheimer's disease. Computational models, which range in complexity, have been used to assess how various parameters affect metastability, synchronization, and functional connectivity. These models, though limited, can act as heuristics in understanding brain dynamics. This article (aimed at the clinical psychiatrist who might not possess an extensive mathematical background) is intended to provide a brief and qualitative summary of studies that have used a specific, highly simplified computational model of coupled oscillators (Kuramoto model) for understanding brain dynamics-which might bear some relevance to clinical psychiatry.
scDetect: a rank-based ensemble learning algorithm for cell type identification of single-cell RNA sequencing in cancer

MOTIVATION Single-cell RNA sequencing (scRNA-seq) has enabled the characterization of different cell types in many tissues and tumor samples. Cell type identification is essential for single-cell RNA profiling, currently transforming the life sciences. Often, this is achieved by searching for combinations of genes that have previously been implicated as being cell-type specific, an approach that is not quantitative and does not explicitly take advantage of other scRNA-seq studies. Batch effects and different data platforms greatly decrease the predictive performance in inter-laboratory and different data type validation. RESULTS Here, we present a new ensemble learning method named as "scDetect" that combines gene expression rank-based analysis and a majority vote ensemble machine-learning probability-based prediction method capable of highly accurate classification of cells based on scRNA-seq data by different sequencing platforms. Because of tumor heterogeneity, in order to accurately predict tumor cells in the single cell RNA-seq data, we have also incorporated cell copy number variation consensus clustering and epithelial score in the classification. We applied scDetect to scRNA-seq data from pancreatic tissue, mononuclear cells, and tumor biopsies cells and show that scDetect classified individual cells with high accuracy and better than other publicly available tools. AVAILABILITY scDetect is an open source software. Source code and test data is freely available from Github (https://github.com/IVDgenomicslab/scDetect/) and Zenodo (https://zenodo.org/record/4764132#.YKCOlrH5AYN). The examples and tutorial page is at https://ivdgenomicslab.github. io/scDetect-Introduction/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
The DNMT3A PWWP domain is essential for the normal DNA methylation landscape in mouse somatic cells and oocytes

DNA methylation at CG sites is important for gene regulation and embryonic development. In mouse oocytes, de novo CG methylation requires preceding transcription-coupled histone mark H3K36me3 and is mediated by a DNA methyltransferase DNMT3A. DNMT3A has a PWWP domain, which recognizes H3K36me2/3, and heterozygous mutations in this domain, including D329A substitution, cause aberrant CG hypermethylation of regions marked by H3K27me3 in somatic cells, leading to a dwarfism phenotype. We herein demonstrate that D329A homozygous mice show greater CG hypermethylation and severer dwarfism. In oocytes, D329A substitution did not affect CG methylation of H3K36me2/3-marked regions, including maternally methylated imprinting control regions; rather, it caused aberrant hypermethylation in regions lacking H3K36me2/3, including H3K27me3-marked regions. Thus, the role of the PWWP domain in CG methylation seems similar in somatic cells and oocytes; however, there were cell-type-specific differences in affected regions. The major satellite repeat was also hypermethylated in mutant oocytes. Contrary to the CA hypomethylation in somatic cells, the mutation caused hypermethylation at CH sites, including CA sites. Surprisingly, oocytes expressing only the mutated protein could support embryonic and postnatal development. Our study reveals that the DNMT3A PWWP domain is important for suppressing aberrant CG hypermethylation in both somatic cells and oocytes but that D329A mutation has little impact on the developmental potential of oocytes.
European multicenter evaluation of Xpert® Xpress SARS‐CoV‐2/Flu/RSV test

Rapid diagnostics for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are paramount for reducing the spread of the current pandemic. During additional seasonal epidemics with influenza A/B and respiratory syncytial virus (RSV), the clinical signs and symptoms cannot be distinguished easily from SARS‐CoV‐2. Therefore, a new assay combining four targets in the form of the new Xpert Xpress SARS‐CoV‐2/Flu/RSV assay was evaluated. The assay was compared to the Xpert Xpress SARS‐CoV‐2, Xpert Xpress Flu/RSV, Seegene Flu/RSV, influenza A/B r‐gene® and RSV/hMPV r‐gene®. A total of 295 nasopharyngeal and throat swabs were tested at four institutes throughout Europe including 72 samples positive for SARS‐CoV‐2, 65 for influenza A, 47 for influenza B, and 77 for RSV. The sensitivity of the new assay was above 95% for all targets, with the highest for SARS‐CoV‐2 (97.2%). The overall correlation of SARS‐CoV‐2 Ct values between Xpert Xpress SARS‐CoV‐2 assay and Xpert Xpress SARS‐CoV‐2/Flu/RSV assay was high. The agreement between Ct values above 30 showed the multiplex giving higher Ct values for SARS‐CoV‐2 on average than the singleplex assay. In conclusion, the new assay is a rapid and reliable alternative with less hands‐on time for the detection of not one, but four upper respiratory tract pathogens that may circulate at the same time.
Effectiveness of two sensory-based health education methods on oral hygiene of adolescent with autism spectrum disorders: An interventional study.

AIM This study was undertaken with an aim to evaluate the effectiveness of two sensory-based interventions namely - Visual pedagogy and Mobile based application (Brush Up) on oral health education in promoting oral health status among 13-17 year old school going adolescents with Autism Spectrum Disorder (ASD) in Chennai city. METHODOLOGY An interventional parallel arm study consisting of 13- to 17-year-old school going adolescent with ASD in Chennai city. Plaque Index (Sillness and Loe, 1964) and gingival index (Loe and Sillness, 1963) were assessed at baseline, 6th week and after 12th week. RESULTS A significant difference in plaque (p = < 0.001) and gingival scores (p = < 0.001) were seen among the groups after 6 and 12 weeks post-intervention. There was no statistically significant difference in dental plaque (p = 0.912, 1.023, 0.812) and gingival scores (p = 0.932, 0.264, 0.283) between the groups at all the timelines. CONCLUSION In this present study we found that both the visual cards and mobile based application (Brush Up) had significantly reduced the dental plaque and gingival scores; hence both the modalities can be used as an effective tool in educating these children and thus improve their oral hygiene.
The development of inhibitors of leucine‐rich repeat kinase 2 (LRRK2) as a therapeutic strategy for Parkinson's disease: the current state of play

Current therapeutic approaches for Parkinson's disease (PD) are based around treatments that alleviate symptoms but do not slow or prevent disease progression. As such, alternative strategies are needed. A promising approach is the use of molecules that reduce the function of leucine‐rich repeat kinase (LRRK2). Gain‐of‐function mutations in LRRK2 account for a notable proportion of familial Parkinson's disease cases, and significantly, elevated LRRK2 kinase activity is reported in idiopathic Parkinson's disease. Here, we describe progress in finding therapeutically effective LRRK2 inhibitors, summarising studies that range from in vitro experiments to clinical trials. LRRK2 is a complex protein with two enzymatic activities and a myriad of functions. This creates opportunities for a rich variety of strategies and also increases the risk of unintended consequences. We comment on the strength and limitations of the different approaches and conclude that with two molecules under clinical trial and a diversity of alternative options in the pipeline, there is cause for optimism.
Proton Pump Inhibitors Versus Histamine-2-Receptor Antagonists for Stress Ulcer Prophylaxis in Critically Ill Patients

Goals and Background: Stress ulcer prophylaxis has been shown to lower gastrointestinal bleeding (GIB) rates. Various agents have been studied, and the optimal strategy continues to be contested. This study evaluates the efficacy between proton pump inhibitors (PPIs) and histamine-2-receptor antagonists. Small sample sizes and methodology flaws limited prior studies. Study: A systematic search of MEDLINE, EMBASE, CENTRAL, Web of Science, and ClinicalTrials.gov for randomized controlled trials reporting the use of PPI and histamine-2-receptor antagonist reporting rates of GIB and standardized intensive care outcomes. Risk ratios (RR) and standardized mean difference (SMD) with 95% confidence intervals (CIs). A trial sequential analysis was performed to guard against errors. Results: A total of 14 randomized controlled trials of 28,526 patients with a mean age of 57.83±17.35 years and 30.82% females. In our pooled analysis, PPI outperformed its comparator (RR: 0.68; 95% CI: 0.57-0.82) in clinically significant GIB. PPI re-demonstrated significant reduction in overt GIB (RR: 0.61; 95% CI: 0.39-0.97). No differences between groups was noted toward all-cause mortality (RR: 1.05; 95% CI: 1.00-1.10) or incidence of pneumonia (RR: 1.11; 95% CI: 0.82-1.51). Duration of stay (SMD: 0.07; 95% CI: −0.04-0.17) and ventilator days (SMD: 0.01; 95% CI: −0.01-0.04) were indifferent between the groups. Conclusions: Among critically ill patients, PPI was associated with reduced clinically significant or overt GIB. No differences in pneumonia were seen with the use of either agent. Trial sequential analysis for clinically significant GIB ruled out the risk for false-positive results, and thereby it is unlikely that future trials will affect our conclusions.
The Cross-Cultural Adaptation for Assessment of Chronic Illness Care Questionnaire Into Indonesian Version

This study aimed to translate and adapt the Assessment of Chronic Illness Care (ACIC) version 3.5 into Indonesian version (ACIC-ID) and examine its validity and reliability as a practical tool for quality care measurement. A 3-phase process according to the World Health Organization Guideline for Instruments Translation and Adaptation was followed: (1) translation process by independent translators and adaptation by multidisciplinary expert panel review, (2) pretesting and face validity followed by cognitive interviewing with 10 general practitioners, and (3) final testing on 31 general practitioners for internal consistency and item-total correlation analysis. As a result, the content of ACIC-ID and the original version were conceptually equivalent. This version achieved excellent internal consistency (Cronbach's α 0.97), and item-total correlation was high (Pearson's r > 0.30) for the majority of items. The findings indicate that ACIC-ID is valid and reliable to identify areas that need to be improved in increasing the quality of chronic care.
Abundance estimation for line transect sampling: A comparison of distance sampling and spatial capture-recapture models

Accurate and precise abundance estimation is vital for informed wildlife conservation and management decision-making. Line transect surveys are a common sampling approach for abundance estimation. Distance sampling is often used to estimate abundance from line transect survey data; however, search encounter spatial capture-recapture can also be used when individuals in the population of interest are identifiable. The search encounter spatial capture-recapture model has rarely been applied, and its performance has not been compared to that of distance sampling. We analyzed simulated datasets to compare the performance of distance sampling and spatial capture-recapture abundance estimators. Additionally, we estimated the abundance of North Atlantic right whales in the southeastern United States with two formulations of each model and compared the estimates. Spatial capture-recapture abundance estimates had lower root mean squared error than distance sampling estimates. Spatial capture-recapture 95% credible intervals for abundance had nominal coverage, i.e., contained the simulating value for abundance in 95% of simulations, whereas distance sampling credible intervals had below nominal coverage. Moreover, North Atlantic right whale abundance estimates from distance sampling models were more sensitive to model specification compared to spatial capture-recapture estimates. When estimating abundance from line transect data, researchers should consider using search encounter spatial capture-recapture when individuals in the population of interest are identifiable, when line transects are surveyed over multiple occasions, when there is imperfect detection of individuals located on the line transect, and when it is safe to assume the population of interest is closed demographically. When line transects are surveyed over multiple occasions, researchers should be aware that individual space use may induce spatial autocorrelation in counts across transects. This is not accounted for in common distance sampling estimators and leads to overly precise abundance estimates.
Assistance in dying: A comparative look at legal definitions

Abstract Euthanasia, assisted suicide, medical assistance in dying, death with dignity: these and many other different terms are used around the world to capture various types of assistance in dying. This diversity in terminology can create confusion both in academic debates and in policy-making if it is unclear what type of action or inaction is intended to be captured, by whom, and under what circumstances. By defining and contrasting several terms and legal status of assistance in dying in jurisdictions authorizing it, this comparative glossary aims to lay a foundation that prevents linguistic and conceptual confusion.