Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition of preclinical signs of dementia: A qualitative study exploring the experiences of family carers and professional care assistants

AIMS AND OBJECTIVES To identify preclinical signs of dementia by exploring the experiences of family caregivers and professional care assistants. BACKGROUND Dementia results in disability, emotional strain and financial loss for people with dementia, family members and nations. Informal identification of social and behavioural risk signifiers could facilitate timely interventions with potential to delay onset of serious disability. DESIGN A retrospective qualitative approach using a naturalistic interpretive design was used. Focus groups enabled in-depth understanding of the participants' experiences of life or work with people who subsequently developed dementia. METHODS Purposive sampling was used to recruit family carers and professional carers who had cared for people who later developed dementia. The data from focus groups were fully transcribed and anonymised, and transcripts were analysed by two researchers. These researchers coded and analysed the transcripts independently; subsequently, overlapping and similar themes were identified and consensus reached on final themes. A third researcher was invited to review the analysis and ensure trustworthiness of the study findings. RESULTS Findings revealed that preclinical signs of dementia were identifiable in retrospect Participants' accounts resulted in four themes, "Lowered Threshold of Frustration", "Insight and Coping Strategies," "Early signs of poor memory" and "Alarming Events. " CONCLUSIONS Earlier recognition of preclinical signs of dementia would allow affected individuals to follow health promotion advice and plan for the future. Identification of social exclusion prior to diagnosis has implications for antistigma campaigns and development of "dementia-friendly communities. " RELEVANCE TO CLINICAL PRACTICE Healthcare professionals could work with those at risk, facilitating lifestyle changes to postpone symptoms and advance planning for improved autonomy. Predementia should be viewed as a disability for which reasonable adjustments can be made at a community level, to enhance and extend emotional well-being and social inclusion.
PID-Controlled Particle Swarm Optimization

Premature convergence is a major challenge for particle swarm optimization algorithm (PSO) when dealing with multi-modal problems. The reason is partly due to the insufficient exploration capability because of the fast convergent speed especially in the final stage. In this paper, the PSO is regarded as a two-inputs one-output feedback system, and two PID controllers are incorporated into the methodology of PSO to improve the population diversity. Different from the integral controller, PID controller has three independent parameters and adjusts them dynamically. Theoretical results with support set theory and stability analysis both demonstrate that PID controller provides more chances to escaping from a local optimum. To validate the efficiency of this new variant, four other famous variants are used to compare including the comprehensive leaning PSO, modified time-varying accelerator coefficients PSO, integral-controlled PSO and the standard version, the test suit consists five unconstrained numerical benchmarks with dimensionality 30 and 100, respectively. Simulation results show PID-controlled PSO is suitable for highdimensional multi-modal problems due to the large exploration capability in the final stage.
Inactivation of Zika virus by solvent/detergent treatment of human plasma and other plasma‐derived products and pasteurization of human serum albumin

In 2016 the World Health Organization declared the mosquito‐borne Zika virus (ZIKV) a “public health emergency of international concern. ” ZIKV is a blood‐borne pathogen, which therefore causes concerns regarding the safety of human plasma–derived products due to potential contamination of the blood supply. This study investigated the effectiveness of viral inactivation steps used during the routine manufacturing of various plasma‐derived products to reduce ZIKV infectivity.
2016 updated EULAR evidence-based recommendations for the management of gout

Background New drugs and new evidence concerning the use of established treatments have become available since the publication of the first European League Against Rheumatism (EULAR) recommendations for the management of gout, in 2006. This situation has prompted a systematic review and update of the 2006 recommendations. Methods The EULAR task force consisted of 15 rheumatologists, 1 radiologist, 2 general practitioners, 1 research fellow, 2 patients and 3 experts in epidemiology/methodology from 12 European countries. A systematic review of the literature concerning all aspects of gout treatments was performed. Subsequently, recommendations were formulated by use of a Delphi consensus approach. Results Three overarching principles and 11 key recommendations were generated. For the treatment of flare, colchicine, non-steroidal anti-inflammatory drugs (NSAIDs), oral or intra-articular steroids or a combination are recommended. In patients with frequent flare and contraindications to colchicine, NSAIDs and corticosteroids, an interleukin-1 blocker should be considered. In addition to education and a non-pharmacological management approach, urate-lowering therapy (ULT) should be considered from the first presentation of the disease, and serum uric acid (SUA) levels should be maintained at<6 mg/dL (360 µmol/L) and <5 mg/dL (300 µmol/L) in those with severe gout. Allopurinol is recommended as first-line ULT and its dosage should be adjusted according to renal function. If the SUA target cannot be achieved with allopurinol, then febuxostat, a uricosuric or combining a xanthine oxidase inhibitor with a uricosuric should be considered. For patients with refractory gout, pegloticase is recommended. Conclusions These recommendations aim to inform physicians and patients about the non-pharmacological and pharmacological treatments for gout and to provide the best strategies to achieve the predefined urate target to cure the disease.
Contemporary Patterns of Multiple Organ Dysfunction in Trauma

Background: Multiple organ dysfunction syndrome (MODS) is associated with poor outcomes for trauma patients. Different forms of MODS may exist and have different consequences. The ability to distinguish them clinically may have implications for prognosis and treatment. We wished to study whether prolonged MODS (PRMODS) could be observed as a distinct clinical entity to early resolving MODS (ERMODS) in critically injured patients. Methods: Adult major trauma patients recruited to a prospective observational study at a single major trauma center were eligible for inclusion. MODS was defined as Sequential Organ Failure Assessment (SOFA) score >5; and PRMODS as lasting >7 days. Time to recovery (TTR) was calculated as the number of days before the SOFA fell below the MODS threshold (⩽5). Results: Five hundred ninety-five patients were enrolled of whom 285 developed ERMODS (48%) and 184 (31%) PRMODS. Organ dysfunction was more severe and protracted in PRMODS, especially in patients without brain injury (mean SOFA 11 vs. 6, Day 2, P < 0.001; TTR 17 vs. 3 days, P < 0.001). PRMODS exhibited higher rates of hepatic and renal dysfunction (84% vs. 56%; and 78% vs. 47%, P⩽0.001). Patterns of recovery were distinct in hepatic, renal, and neurological systems (TTR 15 vs. 4; 20 vs. 3; and 28 vs. 7 days, P < 0.01). PRMODS was associated with higher infection and mortality rates (91% vs. 41%; and 22% vs. 7%, P < 0.001). Conclusion: PRMODS appears common, a distinct clinical entity, and associated with worse patient outcomes. PRMODS may represent an important endpoint for studies evaluating outcomes following trauma.
Targeted proteomic assays for the verification of global proteomics insights

In addition to traditional antibody-based targeted assays, recent rapid advances in mass spectrometry (MS)-based proteomic technologies have positioned selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS) as powerful targeted MS-based methods that can be used to verify biological insights gained from discovery-phase proteomics studies. However, the robustness of these targeted approaches is largely dependent on factors that are instrument platform-independent, such as careful attention to experimental design, strict adherence to best practices, and the proper statistical control of the data processing.
A novel approach for fall detection in home environment

The system is specially developed for elderly people living alone in their homes. A novel method for detection of fall in home environment is presented. Video clips of certain duration specifying fall and non-fall activities are considered for experimentation. Shi-Tomasi algorithm is used to find interest points which are tracked by Pyramidal Lucas-Kanade algorithm. The speed and direction of motion is computed along with maximum displacement of interest point. Also the last positions of interest points were observed to declare the fall activity. The results show 95% accuracy for non-fall activities and 96.67% for fall activities with UR fall dataset.
Strain-cross response of heavy male broilers to dietary lysine in the finisher feed: live performance and further-processing yields.

A total of 2,560 male broilers from eight commercial strain-crosses were growth to 42 days of age on common starter (1 to 21 days; 23.06% CP, 3,217 kcal ME/kg) and grower (21 to 42 days; 20.14% CP, 3,224 kcal ME/kg) rations. All strain-crossed subsequently received finisher diets (17.95% CP; 3,186 kcal ME/kg) containing either . 85 or . 95% lysine from 42 to 53 days of age. Further-processing yields were determined on 12 birds per pen, selected within +/- 10% of the replicated pen (8 pens per strain-cross, 40 birds per pen) average weight. The strain-crosses differed significantly (P less than .05) in BW (1, 21, 42, and 53 days), weight gain (WG), feed:gain ratio (1 to 21 and 21 to 42 days), and mortality rate (1 to 21 days). The lysine effect during the finisher period was significant for 53-day BW and WG from 1 to 53 days. Chilled carcass (CC) and abdominal fat (AF) weights, CC yield (percentage, excluding AF), AF yield (percentage of CC weight), Pectoralis major, Pectoralis minor, total deboned breast (TDB), drumstick, thigh, wing, and residual "cage" and skin yields varied among the strain-crosses. A significant weight and yield response to lysine was observed for TDB. Variation observed among strain-cross in live performance, further-processing yields, and response to additional lysine is attributed to differences in rate of growth and degree of maturity at market age. Furthermore, the lysine requirement during the finisher period for optimum breast meat yield may be higher than that recommended by the National Research Council in 1984.
Manganese-Enhanced Magnetic Resonance Imaging of the Spinal Cord in Rats

Manganese-enhanced magnetic resonance imaging (MEMRI) offers a novel neuroimaging method in visualizing the activity patterns of neural circuits. MEMRI is using the divalent manganese ion, which has been used as a cellular contrast agent. The present study was conducted to determine the contrast-enhancing effects of manganese ion administered into the spinal cord of rats. Manganese ion was administered into the spinal cord by lumbar puncture. Ex vivo magnetic resonance images were obtained at 6, 12, 24, and 48 hours after manganese ion injection. Although the highly contrasted images were not observed 6 or 12 hr after manganese injection, the distinctive manganese-enhanced images began to appear at 24 hours after manganese ion injection. These results suggest that the gray matter is the foci of intense paramagnetic signals and MEMRI may provide an effective technique to visualize the
Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point 18F-FDG PET/CT Imaging in Patients with Advanced Melanoma

The purpose of this study was to evaluate 18F-FDG PET/CT scanning as an early predictor of response to immune checkpoint inhibitors (ICIs) in patients with advanced melanoma. Methods: Twenty patients with advanced melanoma receiving ICI prospectively underwent 18F-FDG PET/CT at 3 scan intervals: before treatment initiation (SCAN-1), at days 21–28 (SCAN-2), and at 4 mo (SCAN-3). This study was approved by the institutional review board, and informed consent was received from all patients who were enrolled between April 2012 and December 2013. Tumor response at each posttreatment time point was assessed according to RECIST 1.1, immune-related response criteria, PERCIST (PERCIST 1.0), and European Organization for Research and Treatment of Cancer (EORTC) criteria. Performance characteristics of each metric to predict best overall response (BOR) at ≥ 4 mo were assessed. Results: Twenty evaluable patients were treated with ipilimumab (n = 16), BMS-936559 (n = 3), or nivolumab (n = 1). BOR at ≥ 4 mo included complete response (n = 2), partial response (n = 2), stable disease (n = 1), and progressive disease (n = 15). Response evaluations at SCAN-2 using RECIST 1.1, immune-related response criteria, PERCIST, and EORTC criteria demonstrated accuracies of 75%, 70%, 70%, and 65%, respectively, to predict BOR at ≥ 4 mo. Interestingly, the optimal PERCIST and EORTC threshold values at SCAN-2 to predict BOR were >15.5% and >14.7%, respectively. By combining anatomic and functional imaging data collected at SCAN-2, we developed criteria to predict eventual response to ICI with 100% sensitivity, 93% specificity, and 95% accuracy. Conclusion: Combining functional and anatomic imaging parameters from 18F-FDG PET/CT scans performed early in ICI appears predictive for eventual response in patients with advanced melanoma. These findings require validation in larger cohorts.
Latent class analysis of the Apathy Scale does not identify subtypes of apathy in general population‐based older persons

To identify clinically relevant subtypes of apathy in older persons using latent class analysis (LCA) and investigate the distribution of different characteristics across these subtypes. Measurements: Cross‐sectional data of 122 older persons (mean age 84 years, 60% female) participating in the general population‐based PROactive Management Of Depression in the Elderly study, with apathy according to a score of 14 or higher on the Apathy Scale, were included for LCA. All 14 items of the Apathy Scale were used as indicator variables. Several characteristics were examined including sociodemographics, depressive, and anxiety symptoms; global cognitive function; quality of life indicators; hazardous alcohol intake (drinking ≥ 14 consumptions per week); and perceived chronic pain.
On The Three-Receiver Multilevel Broadcast Channel with Random Parameters

In this paper we extend the analysis of two-receiver broadcast channels with random parameters to the three-receivers case. Specifically we base our work on Nair and El Gamal's results for the three-receiver discrete memoryless multilevel broadcast channel and assume that state information is available non-causally at the transmitter. We provide an achievable rate region for this setting and acknowledge its importance in the study of multiuser cognitive radio configurations.
High species diversity in Colletotrichum associated with citrus diseases in Europe

Species of Colletotrichum are considered important plant pathogens, saprobes, and endophytes on a wide range of plant hosts. Several species are well-known on citrus, either as agents of pre- or post-harvest infections, such as anthracnose, postbloom fruit drop, tear stain and stem-end rot on fruit, or as wither-tip of twigs. In this study we explored the occurrence, diversity and pathogenicity of Colletotrichum spp. associated with Citrus and allied genera in European orchards, nurseries and gardens. Surveys were carried out during 2015 and 2016 in Greece, Italy, Malta, Portugal and Spain. A total of 174 Colletotrichum strains were isolated from symptomatic leaves, fruits, petals and twigs. A multi-locus phylogeny was established based on seven genomic loci (ITS, GAPDH, ACT, CAL, CHS-1, HIS3 and TUB2), and the morphological characters of the isolates determined. Preliminary pathogenicity tests were performed on orange fruits with representative isolates. Colletotrichum strains were identified as members of three major species complexes. Colletotrichum gloeosporioides s.str. and two novel species (C. helleniense and C. hystricis) were identified in the C. gloeosporioides species complex. Colletotrichum karstii, C. novae-zelandiae and two novel species (C. catinaense and C. limonicola) in the C. boninense species complex, and C. acutatum s.str. was also isolated as member of C. acutatum species complex. Colletotrichum gloeosporioides and C. karstii were the predominant species of Colletotrichum isolated. This study represents the first report of C. acutatum on citrus in Europe, and the first detection of C. novae-zelandiae from outside New Zealand. Pathogenicity tests revealed C. gloeosporioides s.str. to be the most virulent species on fruits. The present study improves our understanding of species associated with several disease symptoms on citrus fruits and plants, and provides useful information for effective disease management.
Reduced natural selection associated with low recombination in Drosophila melanogaster.

Synonymous codons are not used equally in many organisms, and the extent of codon bias varies among loci. Earlier studies have suggested that more highly expressed loci in Drosophila melanogaster are more biased, consistent with findings from several prokaryotes and unicellular eukaryotes that codon bias is partly due to natural selection for translational efficiency. We link this model of varying selection intensity to the population-genetics prediction that the effectiveness of natural selection is decreased under reduced recombination. In analyses of 385 D. melanogaster loci, we find that codon bias is reduced in regions of low recombination (i.e., near centromeres and telomeres and on the fourth chromosome). The effect does not appear to be a linear function of recombination rate; rather, it seems limited to regions with the very lowest levels of recombination. The large majority of the genome apparently experiences recombination at a sufficiently high rate for effective natural selection against suboptimal codons. These findings support models of the Hill-Robertson effect and genetic hitchhiking and are largely consistent with multiple reports of low levels of DNA sequence variation in regions of low recombination.
Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography

In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG) and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with only a preoperative T1 MRI scan and a postoperative CT scan. We describe the full capabilities of our imaging pipeline and present a step-by-step protocol for users.
Interpretable Deep Convolutional Neural Networks via Meta-learning

Model interpretability is a requirement in many applications in which crucial decisions are made by users relying on a model's outputs. The recent movement for “algorithmic fairness” also stipulates explainability, and therefore interpretability of learning models. And yet the most successful contemporary Machine Learning approaches, the Deep Neural Networks, produce models that are highly non-interpretable. We attempt to address this challenge by proposing a technique called CNN-INTE to interpret deep Convolutional Neural Networks (CNN) via meta-learning. In this work, we interpret a specific hidden layer of the deep CNN model on the MNIST image dataset. We use a clustering algorithm in a two-level structure to find the meta-level training data and Random Forest as base learning algorithms to generate the meta-level test data. The interpretation results are displayed visually via diagrams, which clearly indicates how a specific test instance is classified. Our method achieves global interpretation for all the test instances on the hidden layers without sacrificing the accuracy obtained by the original deep CNN model. This means our model is faithful to the original deep CNN model, which leads to reliable interpretations.
Dextrose monohydrate as a non-animal sourced alternative diluent in high shear wet granulation tablet formulations

Abstract The feasibility of dextrose monohydrate as a non-animal sourced diluent in high shear wet granulation (HSWG) tablet formulations was determined. Impacts of granulation solution amount and addition time, wet massing time, impeller speed, powder and solution binder, and dry milling speed and screen opening size on granule size, friability and density, and tablet solid fraction (SF) and tensile strength (TS) were evaluated. The stability of theophylline tablets TS, disintegration time (DT) and in vitro dissolution were also studied. Following post-granulation drying at 60 °C, dextrose monohydrate lost 9% water and converted into the anhydrate form. Higher granulation solution amounts and faster addition, faster impeller speeds, and solution binder produced larger, denser and stronger (less friable) granules. All granules were compressed into tablets with acceptable TS. Contrary to what is normally observed, denser and larger granules (at ≥21% water level) produced tablets with a higher TS. The TS of the weakest tablets increased the most after storage at both 25 °C/60% RH and 40 °C/75% RH. Tablet DT was higher for stronger granules and after storage. Tablet dissolution profiles for 21% or less water were comparable and did not change on stability. However, the dissolution profile for tablets prepared with 24% water was slower initially and continued to decrease on stability. The results indicate a granulation water amount of not more than 21% is required to achieve acceptable tablet properties. This study clearly demonstrated the utility of dextrose monohydrate as a non-animal sourced diluent in a HSWG tablet formulation.