Miracle-dz/UniFAR-FTUs huggingface dataset:
The rate by which mortality increase with age is the same for those who experienced chronic disease as for the general population

Abstract Background Mortality doubles approximately every 6–7 years during adulthood. This exponential increase in death risk with chronological age is the population-level manifestation of ageing, and often referred to as the rate-of-ageing. Objective We explore whether the onset of severe chronic disease alters the rate-of-ageing. Methods Using Swedish register data covering the entire population of the birth cohorts 1927–30, we analyse whether being diagnosed with myocardial infarction, diabetes or cancer results in a deviation of the rate-of-ageing from those of the total population. We also quantify the long-term mortality effects of these diseases, using ages with equivalent mortality levels for those with disease and the total population. Results None of the diseases revealed a sustained effect on the rate-of-ageing. After an initial switch upwards in the level of mortality, the rate-of-ageing returned to the same pace as for the total population. The time it takes for the rate to return depends on the disease. The long-term effects of diabetes and myocardial infarction amount to mortality levels that are equivalent to those aged 5–7 years older in the total population. For cancer, the level of mortality returns to that of the total population. Conclusion Our results suggest an underlying process of ageing that causes mortality to increase at a set pace, with every year older we become. This process is not affected by disease history. The persistence of the rate-of-ageing motivates a critical discussion of what role disease prevention can play in altering the progression of ageing.
Grain security assessment in Bangladesh based on supply-demand balance analysis

Ensuring the grain supply-demand balance and achieving grain security had been the main tasks for the government of Bangladesh. On the supply side, Bangladesh’s supply of grain products has increased substantially, with an average annual growth rate of 1.99 million tons in 1998–2018. Domestic grain production, especially rice production, accounted for the largest proportion in its structure. However, under the constraints of resources and environment, imports and international aid were needed to ensure a stable and sustainable grain supply. On the demand side, Bangladesh’s demand for grain products continued to grow at an average annual rate of 2.09 million tons and its structure was constantly diversified. In recent years, domestic grain production has fully met the grain demand for food use, but the overall grain supply dependence on foreign gradually increased. From the analysis of the influencing factors, the grain supply, especially the domestic production of rice and maize, had the greatest impact on the balance of grain supply-demand in Bangladesh. Moreover, multiple cropping index, chemical fertilizer application per hectare and irrigation rate were the three main factors affecting grain production. As a typical agricultural country, Bangladesh’s grain security was faced with challenges, such as high population density, insufficient cultivated land resources, international grain trade and frequent natural disasters. It is suggested that its government should strengthen scientific and technological research, adjust agricultural structure, improve the efficient utilization of agricultural resources and grain circulation systems, and balance the grain demand between food use and indirect use, so as to achieve complete grain self-sufficiency and overall grain security.
Impact of COVID-19 on Multiple Sclerosis Topic Discussion on Twitter

INTRODUCTION Multiple sclerosis (MS) is one of the world's most common neurologic disorders. Social media have been proposed as a way to maintain and even increase social interaction for people with MS. The objective of this work is to identify and compare the topics on Twitter during the first wave of COVID-19 pandemic. METHODS Data was collected using the Twitter API between 9/2/2019 and 13/5/2020. SentiStrength was used to analyze data with the day that the pandemic was declared used as a turning point. Frequency-inverse document frequency (tf-idf) was used for each unigram and calculated the gains in tf-idf value. A comparative analysis of the relevance of words and categories among the datasets was performed. RESULTS The original dataset contained over 610k tweets, our final dataset had 147,963 tweets. After the 10th of march some categories gained relevance in positive tweets ("Healthcare professional", "Chronic conditions", "Condition burden"), while in negative tweets "Emotional aspects" became more relevant and "COVID-19" emerged as a new topic. CONCLUSIONS Our work provides insight on how COVID-19 has changed the online discourse of people with MS.
Iron-sulfur cluster deficiency can be sensed by IRP2 and regulates iron homeostasis and sensitivity to ferroptosis independent of IRP1 and FBXL5

Iron-sulfur clusters enable cells to sense that they have the right amount of iron, and protect them from self-destruction. Intracellular iron levels are strictly regulated to support homeostasis and avoid iron-mediated ROS production. Loss of iron-sulfur cluster (ISC) synthesis can increase iron loading and promote cell death by ferroptosis. Iron-responsive element-binding proteins IRP1 and IRP2 posttranscriptionally regulate iron homeostasis. IRP1 binding to target mRNAs is competitively regulated by ISC occupancy. However, IRP2 is principally thought to be regulated at the protein level via E3 ubiquitin ligase FBXL5–mediated degradation. Here, we show that ISC synthesis suppression can activate IRP2 and promote ferroptosis sensitivity via a previously unidentified mechanism. At tissue-level O2 concentrations, ISC deficiency enhances IRP2 binding to target mRNAs independent of IRP1, FBXL5, and changes in IRP2 protein level. Deletion of both IRP1 and IRP2 abolishes the iron-starvation response, preventing its activation by ISC synthesis inhibition. These findings will inform strategies to manipulate ferroptosis sensitivity and help illuminate the mechanism underlying ISC biosynthesis disorders, such as Friedreich’s ataxia.
Learning spatiotemporal features of DSA using 3D CNN and BiConvGRU for ischemic moyamoya disease detection

Abstract Background Moyamoya disease (MMD) is a serious intracranial cerebrovascular disease. Cerebral hemorrhage caused by MMD will bring life risk to patients. Therefore, MMD detection is of great significance in the prevention of cerebral hemorrhage. In order to improve the accuracy of digital subtraction angiography (DSA) in the diagnosis of ischemic MMD, in this paper, a deep network architecture combined with 3D convolutional neural network (3D CNN) and bidirectional convolutional gated recurrent unit (BiConvGRU) is proposed to learn the spatiotemporal features for ischemic MMD detection. Methods Firstly, 2D convolutional neural network (2D CNN) is utilized to extract spatial features for each frame of DSA. Secondly, the long-term spatiotemporal features of DSA sequence are extracted by BiConvGRU. Thirdly, the short-term spatiotemporal features of DSA are further extracted by 3D convolutional neural network (3D CNN). In addition, different features are extracted when gray images and optical flow images pass through the network, and multiple features are extracted by features fusion. Finally, the fused features are utilized to classify. Results The proposed method was quantitatively evaluated on a data sets of 630 cases. The experimental results showed a detection accuracy of 0.9788, sensitivity and specificity were 0.9780 and 0.9796, respectively, and area under curve (AUC) was 0.9856. Compared with other methods, we can get the highest accuracy and AUC. Conclusions The experimental results show that the proposed method is stable and reliable for ischemic MMD detection, which provides an option for doctors to accurately diagnose ischemic MMD.
Using Computable Phenotypes in Point-of-Care Clinical Trial Recruitment

A key challenge in point-of-care clinical trial recruitment is to autonomously identify eligible patients on presentation. Similarly, the aim of computable phenotyping is to identify those individuals within a population that exhibit a certain condition. This synergy creates an opportunity to leverage phenotypes in identifying eligible patients for clinical trials. To investigate the feasibility of this approach, we use the Transform clinical trial platform and replace its archetype-based eligibility criteria mechanism with a computable phenotype execution microservice. Utilising a phenotype for acute otitis media with discharge (AOMd) created with the Phenoflow platform, we compare the performance of Transform with and without the use of phenotype-based eligibility criteria when recruiting AOMd patients. The parameters of the trial simulated are based on those of the REST clinical trial, conducted in UK primary care.
Loss of a 7q gene, CUX1, disrupts epigenetic-driven DNA repair and drives therapy-related myeloid neoplasms.

Therapy-related myeloid neoplasms (t-MN) are high-risk, late effects in cancer survivors with poorly understood pathogenesis. It has been postulated that, in some cases, hematopoietic stem and progenitor cells (HSPCs) harboring mutations are selected for by cytotoxic exposures and transform. Here, we evaluate this model in the context of deficiency of CUX1, a transcription factor encoded on chromosome 7q and deleted in half of t-MN cases. We report that CUX1 has a critical, early role in the DNA repair process in HSPCs. Mechanistically, CUX1 recruits the histone methyltransferase EHMT2 to DNA breaks to promote downstream H3K9 and H3K27 methylation, phospho-ATM retention, subsequent γH2AX foci formation and propagation and, ultimately, 53BP1 recruitment. Despite significant unrepaired DNA damage sustained in CUX1-deficient murine HSPCs after cytotoxic exposures, they continue to proliferate and expand, mimicking clonal hematopoiesis in patients post-chemotherapy. As a consequence, preexisting CUX1 deficiency predisposes mice to highly penetrant and rapidly fatal therapy-related erythroleukemias. These findings establish the importance of epigenetic regulation of HSPC DNA repair and position CUX1 as a gatekeeper in myeloid transformation.
Exploring Nursing Students’ Motivation to Prepare for Class

Abstract Although it has been proven that the classroom experience is enhanced when students come prepared to class, there is insufficient evidence on students’ perspectives about what motivates them to prepare for class. This qualitative phenomenology study included records review from 130 accelerated second-degree undergraduate nursing students and a focus group and interviews to discover what motivates students to prepare for class. The data analysis revealed five prominent themes: knowing what to study, deep learning, accountability, getting into the textbook, and content engagement. The study validated several interventions that successfully motivate students to prepare for class.
Supporting Healthcare Integration of Refugees Exploiting Reusable Learning Objects: The ASPIRE Framework

The significant increase of refugees' migration has demonstrated an overwhelming need for their access and integration to healthcare systems. E-learning, especially in the form of experiential digital learning, has been highlighted as an important ally in supporting refugees' health needs. This paper aims to discuss the design and development process of Reusable Learning Objects (RLOs) to enhance digital health applications for refugees and integrate them to healthcare systems. The participatory approach based on the "ASPIRE" framework was followed. Using the "ASPIRE" process, 9 stakeholders were involved in the first phase of the development process, where a co-creation storyboarding workshop was held in Greece by the Medical Physics Laboratory of the Aristotle University of Thessaloniki. Essential qualitative and quantitative feedback was collected from stakeholders through an online questionnaire administered in Google Forms. Overall, enlightening ideas were expressed and all stakeholders commented positively on the value and efficacy of the workshop.
Can gold nanoparticles improve delivery performance of polymeric drug-delivery systems?

During the recent developments in nanomedicine, gold nanoparticles (Au NPs) have emerged as interesting tools in the field of drug-delivery systems (DDS) due to their low toxicity, stability, easy synthesis and reproducibility [1]. Au NPs are able to link therapeutic molecules on their surface by covalent or noncovalent bonding or by a previous functionalization of Au NPs and release the drug only in a specific site without damaging the healthy tissue [2]. Moreover, the small size of gold NPs allows their accumulation in sites of tumor and inflammation and exhibit fast cell uptake using mechanisms different from those typical of small molecules [3]. Their optical property is characterized by surface plasmon resonance (SPR), by which incident light is converted into heat, which makes them very useful in promoting photothermal drug release [4]. The main drawback resides in the fact that after their administration, if not confined, they escape through the circulatory torrent without reaching the target site and so losing their efficacy. For this purpose, hybrid materials formed by the loading of Au NPs inside polymer networks are studied to improve local drug delivery. In this case, the easy injection and confinement of the hydrogel in the site of injury represent the main advantages together with local release of both small and large molecules in response to thermal stimuli [5].
Attention orientation to pleasantness and depressive symptomatology predict autonomic reactivity

ABSTRACT Depression is characterised by attentional bias to emotional information and dysregulated autonomic reactivity. Despite its relevance to understanding depressive mechanisms, the association between attentional bias and autonomic reactivity to emotional information remains poorly characterised. This study compared behavioural and autonomic responses to emotional images in 32 participants in whom subclinical depressive symptomatology was quantified using the Beck Depression Inventory. Pairs of emotional and neutral images (unpleasant-neutral, U-N; pleasant-neutral, P-N; neutral-neutral, N-N) were presented while attentional indices (eye movements) and autonomic activity (skin conductance responses, SCRs; heart rate, HR) were recorded. Results showed that all recorded ocular parameters indicated a preferential orientation and maintenance of attention to emotional images. SCRs were associated with a valence effect on fixation latency: lower fixation latency to pleasant stimuli leads to lower SCRs whereas the opposite was observed for unpleasant stimuli. Finally, stepwise linear regression analysis revealed that latency of fixation to pleasant images and scores of depression predicted SCRs of participants. Thus, our research reveals an association between autonomic reactivity and attentional bias to pleasant information, on the one hand, and depressive symptomatology on the other. Present findings therefore suggest that depressive individuals may benefit from attention training towards pleasant information in association with autonomic biofeedback procedures.
Interesting Morphological Behavior of Organic Salt Choline Fenofibrate: Effect of Supersaturation and Polymeric Impurity

Crystal habit of drug molecules can have significant influence on the processing and performance of pharmaceutical products. During the development of Trilipix, a pharmaceutical product used for the treatment of mixed dyslipidemia, several crystal habits were observed for the active ingredient choline fenofibrate. The dissolution and performance of the drug product were not impacted by changes in crystal habit of the active ingredient due to high solubility of the drug. However, the formulation process was impacted by variations in crystal habit of the active ingredient, requiring robust control of the crystal habit. The crystal habit was greatly influenced by supersaturation during crystallization from a mixed solvent system comprising methanol and isopropanol. In addition to supersaturation, trace levels of a polymeric impurity in the starting material fenofibrate had a detrimental effect on the crystal habit. This article discusses the effects of these factors on the crystal habit of choline fenofibrat.
Titanium nanoparticles potentially affect gingival tissue through IL-13α2 receptor expression.

PURPOSE To determine the effects of titanium nanoparticles, that may have been scattered after dental implant placement, on gene and promoter expression, and gingival tissue. METHODS Ca9-22 cell lines were used as gingival epithelial cells to assess the effects of titanium dioxide nanomaterials as titanium nanoparticles. Cells were cocultured with or without titanium dioxide nanomaterials prior to gene and promoter expression analysis. Expression of interleukin-13α2 receptor was investigated using real-time quantitative reverse-transcription polymerase chain reaction and immunofluorescence staining. Additionally, the enhanced messenger ribonucleic acid (mRNA) expression of transforming growth factor β1 was analyzed using the same method. RESULTS Titanium dioxide nanomaterials affected gene and promoter expression in Ca9-22 cells: among the 160 upregulated genes, the upregulation of IL13RA2, which encodes interleukin-13α2 receptor, was the highest (8.625 log2 fold change). Immunofluorescence staining confirmed the increased expression of interleukin-13α2 receptor, which enhanced transforming growth factor β1 expression by stimulation with interleukin-13. CONCLUSION Titanium dioxide nanomaterials applied on the gingival epithelium around the dental implant may increase interleukin-13α2 receptor expression. In turn, this can enhance the secretion of transforming growth factor β1, which is known to promote the differentiation of osteoclasts involved in bone resorption, and potentially affect gingival tissue.
The roles of lower- and higher-order surface statistics in tactile texture perception.

Humans can haptically discriminate surface textures when there is a significant difference in the statistics of the surface profile. Previous studies on tactile texture discrimination have emphasized the perceptual effects of lower-order statistical features such as carving depth, inter-ridge distance, and anisotropy, which can be characterized by local amplitude spectra or spatial-frequency/orientation subband histograms. However, the real-world surfaces we encounter in everyday life also differ in the higher-order statistics, such as statistics about correlations of nearby spatial-frequencies/orientations. For another modality, vision, the human brain has the ability to utilize the textural differences in both higher- and lower-order image statistics. In this work, we examined whether the haptic texture perception can utilize higher-order surface statistics as visual texture perception does, by 3D-printing textured surfaces transcribed from different 'photos' of natural scenes such as stones and leaves. Even though the maximum carving depth was well above the haptic detection threshold, some texture pairs were hard to discriminate. Specifically, those texture pairs with similar amplitude spectra were difficult to discriminate, which suggests that the lower-order statistics have the dominant effect on tactile texture discrimination. To directly test the poor sensitivity of the tactile texture perception to higher-order surface statistics, we matched the lower-order statistics across different textures using a texture synthesis algorithm and found that haptic discrimination of the matched textures was nearly impossible unless the stimuli contained salient local features. We found no evidence for the ability of the human tactile system to use higher-order surface statistics for texture discrimination.
Use of Information Systems in an Intensive Form of Mental Health Home Treatment

This paper reports findings from a case study on the use of information systems in Germany's mental health home treatment. Data were collected following an ethnographic approach, three themes were identified: (i) misfit of systems, (ii) whiteboards as central planning tools, and (iii) patients and their environment. We conclude by highlighting the specific nature of home treatment.
Construction of a Physical Factor Resource for Exposome Informatics Research

Exposome research is focused on all the exposures individuals experience during their lifetime and how it shapes their health and development of disease. The chemical and biological aspects of the exposome are readily available in data formats. In comparison there is a lack of data frameworks available for physical factors (e.g. noise, lighting, electromagnetic fields) and their biological relationships which would allow a greater understanding of the contribution of the physical environment on disease development and burden. We present the construction of a prototype that captures knowledge on physical factors and their interactions with genes and diseases derived from the biomedical literature to reflect the physical exposome.
Identification of Similar Patients Through Medical Concept Embedding from Electronic Health Records: A Feasibility Study for Rare Disease Diagnosis

To identify patients with similar clinical profiles and derive insights from the records and outcomes of similar patients can help fast and precise diagnosis and other clinical decisions for rare diseases. Similarity methods are required to take into account the semantic relations between medical concepts and also the different relevance of all medical concepts presented in patients' medical records. In this paper, we introduce the methods developed in the context of rare disease screening/diagnosis from clinical data warehouse using medical concept embedding and adjusted aggregations. Our methods provided better preliminary results than baseline methods, with a significant improvement of precision among the top ranked similar patients, which is encouraging for further fine-tuning and application on a large-scale dataset for new/candidate patient identification.
Blinding and expectancy confounds in psychedelic randomized controlled trials

ABSTRACT Introduction: There is increasing interest in the potential for psychedelic drugs such as psilocybin, LSD and ketamine to treat several mental health disorders, with a growing number of randomized controlled trials (RCTs) being conducted to investigate the therapeutic effectiveness of psychedelics. Areas covered: We review previous literature on expectancy effects and blinding in the context of psychedelic RCTs – literature which strongly suggest that psychedelic RCTs might be confounded by de-blinding and expectancy. We conduct systematic reviews of psychedelic RCTs using Medline, PsychInfo and EMBASE (Jan 1990 – Nov 2020) and show that currently reported psychedelic RCTs have generally not reported pre-trial expectancy, nor the success of blinding procedures. Expert opinion: While psychedelic RCTs have generally shown promising results, with large effect sizes reported, we argue that treatment effect sizes in psychedelic RCTs are likely over-estimated due to de-blinding of participants and high levels of response expectancy. We suggest that psychedelic RCTs should routinely measure de-blinding and expectancy. Careful attention should be paid to clinical trial design and the instructions given to participants to allow these confounds to be reduced, estimated and removed from effect size estimates. We urge caution in interpreting effect size estimates from extant psychedelic RCTs.