Miracle-dz/UniFAR-FTUs huggingface dataset:
An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice

General practice plays a prominent role in primary health care (PHC). However, evidence has shown that the quality of PHC is still unsatisfactory, and the accuracy of clinical diagnosis and treatment must be improved in China. Decision making tools based on artificial intelligence can help general practitioners diagnose diseases, but most existing research is not sufficiently scalable and explainable. An explainable and personalized cognitive reasoning model based on knowledge graph (CRKG) proposed in this article can provide personalized diagnosis, perform decision making in general practice, and simulate the mode of thinking of human beings utilizing patients’ electronic health records (EHRs) and knowledge graph. Taking abdominal diseases as the application point, an abdominal disease knowledge graph is first constructed in a semiautomated manner. Then, the CRKG designed referring to dual process theory in cognitive science involves the update strategy of global graph representations and reasoning on a personal cognitive graph by adopting the idea of graph neural networks and attention mechanisms. For the diagnosis of diseases in general practice, the CRKG outperforms all the baselines with a precision@1 of 0.7873, recall@10 of 0.9020 and hits@10 of 0.9340. Additionally, the visualization of the reasoning process for each visit of a patient based on the knowledge graph enhances clinicians' comprehension and contributes to explainability. This study is of great importance for the exploration and application of decision making based on EHRs and knowledge graph.
Preparation and performance of electrically conductive decellularized nerve matrix hydrogel conduits

Peripheral nerve injury (PNI) is one of the major clinical treatment challenges following an impact on the body. When PNI manifests as nerve gaps, surgical connections and exogenous grafts are required. Recently, electrically conductive polymers (CPs) based nerve guidance conduits have yielded promising results for treating PNI. Polypyrrole (PPy) has become one of the most commonly used CPs in PNI repair due to its advantages of high conductivity and excellent biocompatibility. In this study, we combined different PPy concentrations with a chitosan (CS) temperature-sensitive hydrogel system containing decellularized nerve matrix (DNM) to construct the electrically conductive nerve conduits. We evaluated the physical and biological properties of four groups of nerve conduits. It was found that the PPy concentrations were proportional to the electrical conductivity of the nerve conduits. The mechanical properties of the nerve conduits increased with higher PPy concentrations but decreased when the PPy concentration was as high as 8%. Meanwhile, the co-blending of PPy and DNM gave the nerve conduit suitable degradation properties. Furthermore, in vitro cytotoxicity assay and live/dead assay demonstrated these conduits could support the adhesion and growth of cells. In summary, the electrically conductive nerve conduits with high conductivity, mechanical properties, biodegradation characteristics, and cytocompatibility had potential applications in the field of peripheral nerve regeneration.
Changes in incidence trends of meningioma in Finland, 1990–2017: analysis of Finnish Cancer Registry data

Abstract Background Meningiomas are the most common primary neoplasm of the central nervous system. Previous research on the incidence of meningioma in Finland showed an increase in the age-standardized incidence rate over three decades (1968–1997). In this study, we analysed meningioma incidence in Finland during 1990–2017. Materials and methods Data on 9842 meningioma patients were obtained from the Finnish Cancer Registry, and population size by calendar year, sex, and age group from Statistics Finland. The European Standard Population was used to calculate age-standardized incidence rates. Poisson regression was used to evaluate differences by sex and age, and joinpoint regression to examine changes in trend. Results At the beginning of the study period, the age-standardized incidence of meningioma for men was 2.35/100,000 and for women 6.96/100,000. In the end, it was 4.09/100,000 and 10.19/100,000, respectively. The annual percent change (APC) for women was +4.6 (95% confidence interval, CI 3.10 to 6.20) from 1990 to 2001 and −1.0 (95% CI −1.70 to −0.30) from 2001 to 2017. For men, the APC was +3.1 (95% CI 0.80–5.40) during 1990–2002 and −0.9 (95% CI −2.10 to 0.30) in 2002–2017. The incidence of meningioma in women was 2.8 times higher than in men (rate ratio 2.81; 95% CI 2.68–2.94). Conclusions Meningioma incidence increased in both sexes from 1990, but the trend reversed in 2001–2002. Medical imaging or risk factors do not appear to explain the changes.
Assessment of Specific Learning Disabilities and Intellectual Disabilities

We review literature related to the assessment and identification of Specific Learning Disabilities (SLD) and Intellectual Disabilities (ID). SLD and ID are the only two disorders requiring psychometric test performance for identification within the group of neurodevelopmental disorders in Diagnostic and Statistical Manual – 5. SLD and ID are considered exclusionary of one another, but the processes for assessment and identification of each disorder vary. There is controversy about the identification and assessment methods for SLD, with little consensus. Unlike ID, SLD is weakly related to full-scale IQ, and there is insufficient evidence that the routine assessment of IQ or cognitive skills adds value to SLD identification and treatment. We have proposed a hybrid method based on the assessment of low achievement with norm-referenced tests, instructional response, and other disorders and contextual factors that may be comorbid or contraindicative of SLD. In contrast to SLD, there is strong consensus for a three-prong definition for the identification and assessment of ID: (a) significantly subaverage IQ, (b) adaptive behavior deficits that interfere with independent living in the community, and (c) age of onset in the developmental period. For both SLD and ID, we identify areas of controversy and best practices for identification and assessment.
Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation

The pectoralis muscle is an important indicator of respiratory muscle function and has been linked to various parenchymal biomarkers, such as airflow limitation severity and diffusing capacity for carbon monoxide, which are widely used in diagnosing parenchymal diseases, including asthma and chronic obstructive pulmonary disease. Pectoralis muscle segmentation is a method for measuring muscle volume and mass for various applications. The segmentation method is based on deep-learning techniques that combine a muscle area detection model and a segmentation model. The training dataset for the detection model comprised multichannel images of patients, whereas the segmentation model was trained on 7,796 cases of the computed tomography (CT) image dataset of 1,841 patients. The dataset was expanded incrementally through an active learning process. The performance of the model was evaluated by comparing the segmentation results with manual annotations by radiologists and the volumetric differences between the CT image datasets of the same patients. The results indicated that the machine learning model is promising in segmenting the pectoralis major muscle, with good agreement between the automatic segmentation and manual annotations by radiologists. The training accuracy and loss values of the validation set were 0.9954 and 0.0725, respectively, and for segmentation, the loss value was 0.0579. This study shows the potential clinical usefulness of the machine learning model for pectoralis major muscle segmentation as a quantitative biomarker for various parenchymal and muscular diseases.
Fibrin Stiffness Regulates Phenotypic Plasticity of Metastatic Breast Cancer Cells

The extracellular matrix (ECM)‐regulated phenotypic plasticity is crucial for metastatic progression of triple negative breast cancer (TNBC). While ECM faithful cell‐based models are available for in situ and invasive tumors, such as cell aggregate cultures in reconstituted basement membrane and in collagenous gels, there are no ECM faithful models for metastatic circulating tumor cells (CTCs). Such models are essential to represent the stage of metastasis where clinical relevance and therapeutic opportunities are significant. Here, CTC‐like DU4475 TNBC cells are cultured in mechanically tunable 3D fibrin hydrogels. This is motivated, as in circulation fibrin aids CTC survival by forming a protective coating reducing shear stress and immune cell‐mediated cytotoxicity and promotes several stages of late metastatic processes at the interface between circulation and tissue. This work shows that fibrin hydrogels support DU4475 cell growth, resulting in spheroid formation. Furthermore, increasing fibrin stiffness from 57 to 175 Pa leads to highly motile, actin and tubulin containing cellular protrusions, which are associated with specific cell morphology and gene expression patterns that markedly differ from basement membrane or suspension cultures. Thus, mechanically tunable fibrin gels reveal specific matrix‐based regulation of TNBC cell phenotype and offer scaffolds for CTC‐like cells with better mechano‐biological properties than liquid.
Cost-Effectiveness of Vericiguat in Patients With Heart Failure With Reduced Ejection Fraction: The VICTORIA Randomized Clinical Trial

BACKGROUND: The VICTORIA trial (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction) demonstrated that, in patients with high-risk heart failure, vericiguat reduced the primary composite outcome of cardiovascular death or heart failure hospitalization relative to placebo. The hazard ratio for all-cause mortality was 0.95 (95% CI, 0.84–1.07). In a prespecified analysis, treatment effects varied substantially as a function of baseline NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels, with survival benefit for vericiguat in the lower NT-proBNP quartiles (hazard ratio, 0.82 [95% CI, 0.69–0.97]) and no benefit in the highest NT-proBNP quartile (hazard ratio, 1.14 [95% CI, 0.95–1.38]). An economic analysis was a major secondary objective of the VICTORIA research program. METHODS: Medical resource use data were collected for all VICTORIA patients (N=5050). Costs were estimated by applying externally derived US cost weights to resource use counts. Life expectancy was projected from patient-level empirical trial survival results with the use of age-based survival modeling methods. Quality-of-life adjustments were based on prospectively collected EQ-5D–based utilities. The primary outcome was the incremental cost-effectiveness ratio, comparing vericiguat with placebo, assessed from the US health care sector perspective over a lifetime horizon. Cost-effectiveness was estimated using the total VICTORIA cohort, both with and without interaction between treatment and baseline NT-proBNP. RESULTS: Life expectancy modeling results varied according to whether the observed heterogeneity of treatment effect by baseline NT-proBNP values was incorporated into the modeling. Including the interaction term, the vericiguat arm had an estimated quality-adjusted life expectancy of 4.56 quality-adjusted life-years (QALYs) compared with 4.13 QALYs for placebo (incremental discounted QALY, 0.43). Without the treatment heterogeneity/interaction term, vericiguat had 4.50 QALYs compared with 4.33 QALYs for placebo (incremental discounted QALY, 0.17). Incremental discounted costs (vericiguat minus placebo) were $28 546 with the treatment interaction and $20 948 without it. Corresponding incremental cost-effectiveness ratios were $66 509 per QALY allowing for treatment heterogeneity and $124 512 without heterogeneity. CONCLUSIONS: Vericiguat use in the VICTORIA trial met criteria for intermediate value, but the incremental cost-effectiveness ratio estimates were sensitive to whether the analysis accounted for observed NT-proBNP treatment effect heterogeneity. The cost-effectiveness of vericiguat was driven by the projected incremental life expectancy among patients in the lowest 3 quartiles of NT-proBNP. REGISTRATION: URL: https://www.clinicaltrials. gov; Unique identifier: NCT02861534.
FunTaxIS-lite: a simple and light solution to investigate protein functions in all living organisms

Abstract Motivation Defining the full domain of protein functions belonging to an organism is a complex challenge that is due to the huge heterogeneity of the taxonomy, where single or small groups of species can bear unique functional characteristics. FunTaxIS-lite provides a solution to this challenge by determining taxon-based constraints on Gene Ontology (GO) terms, which specify the functions that an organism can or cannot perform. The tool employs a set of rules to generate and spread the constraints across both the taxon hierarchy and the GO graph. Results The taxon-based constraints produced by FunTaxIS-lite extend those provided by the Gene Ontology Consortium by an average of 300%. The implementation of these rules significantly reduces errors in function predictions made by automatic algorithms and can assist in correcting inconsistent protein annotations in databases. Availability and implementation FunTaxIS-lite is available on https://www.medcomp. medicina.unipd. it/funtaxis-lite and from https://github.com/MedCompUnipd/FunTaxIS-lite.
T-matrix Approach to the Nonlinear Waveform Inversion Problem in 4D Seismics

A numerical method for seismic waveform inversion is developed, using the methods of quantum scattering theory. The method, which is based on a convenient matrix reprentation of the relevant integral operators, is completely general, but we focus on novel applications to 4D seismics. It is shown that the unknown scattering potential matrix (diagonal) is related to the partially observable T-matrix (non-diagonal) in a nonlinear manner, associated with the well-known Lippmann-Schwinger integral equation. We develop an iterative numerical scheme for inversion of 4D seismic waveform data with respect to the scattering potential, where the T-matrix is updated after each iteration, either by inverting a relatively large matrix or by using the forward scattering series. The connection between this simple numerical realization of the inverse scattering series and the ISS employed by Weglein et al. (which appears to contain redundant terms) will also be discussed. In a numerical experiment, where we generated synthetic 4D seismic waveform data using a full numerical (T-matrix) solution of the Schwinger-Dyson integral equation, we obtained a dramatic improvement on the Born inversion result after just 3 iterations. This suggest that internal multiples should be regarded as an additonal source of information, and not just noise.
Probabilistic computing with voltage-controlled dynamics in magnetic tunnel junctions

Probabilistic (p-) computing is a physics-based approach to addressing computational problems which are difficult to solve by conventional von Neumann computers. A key requirement for p-computing is the realization of fast, compact, and energy-efficient probabilistic bits. Stochastic magnetic tunnel junctions (MTJs) with low energy barriers, where the relative dwell time in each state is controlled by current, have been proposed as a candidate to implement p-bits. This approach presents challenges due to the need for precise control of a small energy barrier across large numbers of MTJs, and due to the need for an analog control signal. Here we demonstrate an alternative p-bit design based on perpendicular MTJs that uses the voltage-controlled magnetic anisotropy (VCMA) effect to create the random state of a p-bit on demand. The MTJs are stable (i.e. have large energy barriers) in the absence of voltage, and VCMA-induced dynamics are used to generate random numbers in less than 10 ns/bit. We then show a compact method of implementing p-bits by using VC-MTJs without a bias current. As a demonstration of the feasibility of the proposed p-bits and high quality of the generated random numbers, we solve up to 40 bit integer factorization problems using experimental bit-streams generated by VC-MTJs. Our proposal can impact the development of p-computers, both by supporting a fully spintronic implementation of a p-bit, and alternatively, by enabling true random number generation at low cost for ultralow-power and compact p-computers implemented in complementary metal-oxide semiconductor chips.
Beam theory predicts muscle deformation and vertebral curvature during feeding in rainbow trout (Oncorhynchus mykiss)

ABSTRACT Muscle shortening underpins most skeletal motion and ultimately animal performance. Most animal muscle generates its greatest mechanical output over a small, homogeneous range of shortening magnitudes and speeds. However, homogeneous muscle shortening is difficult to achieve for swimming fish because the whole body deforms like a bending beam: as the vertebral column flexes laterally, longitudinal muscle strain increases along a medio-lateral gradient. Similar dorsoventral strain gradients have been identified as the vertebral column flexes dorsally during feeding in at least one body location in one fish. If fish bodies also deform like beams during dorsoventral feeding motions, this would suggest the dorsal body (epaxial) muscles must homogenize both dorsoventral and mediolateral strain gradients. We tested this hypothesis by measuring curvature of the anterior vertebral column with XROMM and muscle shortening in 14 epaxial subregions with fluoromicrometry during feeding in rainbow trout (Oncorhynchus mykiss). We compared measured strain with the predicted strain based on beam theory's curvature–strain relationship. Trout flexed the vertebrae dorsally and laterally during feeding strikes, yet when flexion in both planes was included, the strain predicted by beam theory was strongly and significantly correlated with measured strain (P<0.01, R2=0.60). Beam theory accurately predicted strain (slope=1.15, compared with ideal slope=1) across most muscle subregions, confirming that epaxial muscles experience dorsoventral and mediolateral gradients in longitudinal strain. Establishing this deformation–curvature relationship is a crucial step to understanding how these muscles overcome orthogonal strain gradients to produce powerful feeding and swimming behaviours.
Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder

Processing social information from faces is difficult for individuals with autism spectrum disorder (ASD). However, it remains unclear whether individuals with ASD make high-level social trait judgments from faces in the same way as neurotypical individuals. Here, we comprehensively addressed this question using naturalistic face images and representatively sampled traits. Despite similar underlying dimensional structures across traits, online adult participants with self-reported ASD showed different judgments and reduced specificity within each trait compared with neurotypical individuals. Deep neural networks revealed that these group differences were driven by specific types of faces and differential utilization of features within a face. Our results were replicated in well-characterized in-lab participants and partially generalized to more controlled face images (a preregistered study). By investigating social trait judgments in a broader population, including individuals with neurodevelopmental variations, we found important theoretical implications for the fundamental dimensions, variations, and potential behavioral consequences of social cognition.
Supermarket Transaction Records In Dietary Evaluation: the STRIDE study: validation against self-reported dietary intake

Abstract Objective: Scalable methods are required for population dietary monitoring. The Supermarket Transaction Records In Dietary Evaluation (STRIDE) study compares dietary estimates from supermarket transactions with an online FFQ. Design: Participants were recruited in four waves, accounting for seasonal dietary variation. Purchases were collected for 1 year during and 1 year prior to the study. Bland–Altman agreement and limits of agreement (LoA) were calculated for energy, sugar, fat, saturated fat, protein and sodium (absolute and relative). Setting: This study was partnered with a large UK retailer. Participants: Totally, 1788 participants from four UK regions were recruited from the retailer’s loyalty card customer database, according to breadth and frequency of purchases. Six hundred and eighty-six participants were included for analysis. Results: The analysis sample were mostly female (72 %), with a mean age of 56 years (sd 13). The ratio of purchases to intakes varied depending on amounts purchased and consumed; purchases under-estimated intakes for smaller amounts on average, but over-estimated for larger amounts. For absolute measures, the LoA across households were wide, for example, for energy intake of 2000 kcal, purchases could under- or over-estimate intake by a factor of 5; values could be between 400 kcal and 10000 kcal. LoA for relative (energy-adjusted) estimates were smaller, for example, for 14 % of total energy from saturated fat, purchase estimates may be between 7 % and 27 %. Conclusions: Agreement between purchases and intake was highly variable, strongest for smaller loyal households and for relative values. For some customers, relative nutrient purchases are a reasonable proxy for dietary composition indicating utility in population-level dietary research.
Inhibiting astrocyte connexin‐43 hemichannels blocks radiation‐induced vesicular VEGF‐A release and blood–brain barrier dysfunction

Therapeutic brain irradiation with ionizing radiation exerts multiple side effects including barrier leakage that disturbs glial‐neuronal functioning and may affect cognition. Astrocytes contribute to barrier leakage by endfeet release of various vasoactive substances acting on capillary endothelial cells forming the barrier. Here, we investigated X‐ray effects on astrocytic vesicular transport in mice and determined whether interfering with astrocyte connexins affects radiation‐induced barrier leakage. We found that astrocytic VEGF‐A‐loaded VAMP3 vesicles drastically reorganize starting from 6 h post‐irradiation and move in a calcium‐ and Cx43‐dependent manner towards endfeet where VEGF‐A is released, provoking barrier leakage. Vesicular transport activation, VEGF‐A release and leakage 24 h post‐irradiation were all potently inhibited by astrocytic Cx43 KO, Cx43S255/262/279/282A (MK4) mutant mice and TATGap19 inhibition of Cx43 hemichannel opening. Astrocyte VEGF release is a major player in complications of brain irradiation, which can be mitigated by anti‐VEGF treatments. Targeting Cx43 hemichannels allows to prevent astrocyte VEGF release at an early stage after brain irradiation.