Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the relationships between health spending, treatable mortality and economic productivity in OECD countries

Introduction Population health is one of the highest priorities for countries, which can translate into increased economic prosperity. This encourages research on health in an economic context. Methods The objective was to assess the relationships between health spending, treatable respiratory mortality, and gross domestic product (GDP) in countries of the Organization for Economic Co-operation and Development (OECD). The research was conducted with respect to health systems (tax-based, insurance-based) and gender differentiation of the productive population (aged 25–64 years). Descriptive analysis, regression analysis, and cluster analysis were used to achieve the main objective. The data covered the period from 1994 to 2016. Results The results of the regression analysis revealed negative relationships between health spending and treatable respiratory mortality in countries with a tax-based health system for male and female working-age populations, as well as in countries with an insurance-based health system for male population. This means that higher health spending was associated with lower treatable respiratory mortality. Also, lower treatable mortality was associated with higher GDP, especially in the male productive population from countries with an insurance-based health system. In this study, countries with a tax-based health system were characterized by higher health spending, lower rates of treatable mortality from respiratory system diseases, and higher GDP compared to countries with an insurance-based health system. Males reported a higher mortality rate than females. Among the countries with a tax-based health system, the United Kingdom and Latvia showed less positive outcomes, while Italy and Iceland were the countries with the most positive outcomes. Among the countries with an insurance-based health system, Hungary and Slovakia reported poor outcomes, while France, Switzerland and Luxembourg were characterized by very positive outcomes. The United States showed a high mortality rate despite its high economic outcomes, i.e., health spending and GDP. Discussion Health care financing in particular is one of the instruments of health policy. It seems that the leaders of countries should ensure a sufficient level of health financing, as higher health spending can contribute to lower mortality rates in a country. This may translate into higher productivity. Especially countries with underfunded health systems should increase their health spending.
Developing an in vitro validated 3D in silico internal carotid artery sidewall aneurysm model

Introduction: Direct quantification of hemodynamic factors applied to a cerebral aneurysm (CA) remains inaccessible due to the lack of technologies to measure the flow field within an aneurysm precisely. This study aimed to develop an in vitro validated 3D in silico patient-specific internal carotid artery sidewall aneurysm (ICASA) model which can be used to investigate hemodynamic factors on the CA pathophysiology. Methods: The validated ICASA model was developed by quantifying and comparing the flow field using particle image velocimetry (PIV) measurements and computational fluid dynamics (CFD) simulations. Specifically, the flow field characteristics, i.e., blood flowrates, normalized velocity profiles, flow streamlines, and vortex locations, have been compared at representative time instants in a cardiac pulsatile period in two designated regions of the ICASA model, respectively. One region is in the internal carotid artery (ICA) inlet close to the aneurysm sac, the other is across the middle of the aneurysmal sac. Results and Discussion: The results indicated that the developed computational fluid dynamics model presents good agreements with the results from the parallel particle image velocimetry and flowrate measurements, with relative differences smaller than 0.33% in volumetric flow rate in the ICA and relative errors smaller than 9.52% in averaged velocities in the complex aneurysmal sac. However, small differences between CFD and PIV in the near wall regions were observed due to the factors of slight differences in the 3D printed model, light reflection and refraction near arterial walls, and flow waveform uncertainties. The validated model not only can be further employed to investigate hemodynamic factors on the cerebral aneurysm pathophysiology statistically, but also provides a typical model and guidance for other professionals to evaluate the hemodynamic effects on cerebral aneurysms.
Functional MRI study of feedback-based reinforcement learning in depression

Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD.
Retinal degeneration protein 3 controls membrane guanylate cyclase activities in brain tissue

The retinal degeneration protein RD3 is involved in regulatory processes of photoreceptor cells. Among its main functions is the inhibition of photoreceptor specific membrane guanylate cyclases during trafficking from the inner segment to their final destination in the outer segment. However, any physiological role of RD3 in non-retinal tissue is unsolved at present and specific protein targets outside of retinal tissue have not been identified so far. The family of membrane bound guanylate cyclases share a high homology of their amino acid sequences in their cytoplasmic domains. Therefore, we reasoned that membrane guanylate cyclases that are activated by natriuretic peptides are also regulated by RD3. We analyzed transcript levels of the rd3 gene and natriuretic peptide receptor genes Npr1 and Npr2 in the mouse retina, cerebellum, hippocampus, neocortex, and the olfactory bulb during development from the embryonic to the postnatal stage at P60. The rd3 gene showed a lower expression level than Npr1 and Npr2 (encoding for GC-A and GC-B, respectively) in all tested brain tissues, but was at least one order of magnitude higher in the retina. RD3 and natriuretic peptide receptor GCs co-express in the retina and brain tissue leading to functional tests. We expressed GC-A and GC-B in HEK293T cells and measured the inhibition of GCs by RD3 after activation by natriuretic peptides yielding inhibitory constants around 25 nM. Furthermore, endogenous GCs in astrocytes were inhibited by RD3 to a similar extent. We here show for the first time that RD3 can inhibit two hormone-stimulated GCs, namely GC-A and GC-B indicating a new regulatory feature of these hormone receptors.
Recombinant actin-depolymerizing factor of the apicomplexan Neospora caninum (NcADF) is susceptible to oxidation

Neospora caninum is a member of Apicomplexa Phylum and the causative agent of neosporosis, a disease responsible for abortions in cattle. Apicomplexan parasites have a limited set of actin-binding proteins conducting the regulation of the dynamics of nonconventional actin. The parasite actin-based motility is implicated in the parasite invasion process in the host cell. Once no commercial strategy for the neosporosis control is available, the interference in the parasite actin function may result in novel drug targets. Actin-depolymerization factor (ADF) is a member of the ADF/cofilin family, primarily known for its function in actin severing and depolymerization. ADF/cofilins are versatile proteins modulated by different mechanisms, including reduction and oxidation. In apicomplexan parasites, the mechanisms involved in the modulation of ADF function are barely explored and the effects of oxidation in the protein are unknown so far. In this study, we used the oxidants N-chlorotaurine (NCT) and H2O2 to investigate the susceptibility of the recombinant N. caninum ADF (NcADF) to oxidation. After exposing the protein to either NCT or H2O2, the dimerization status and cysteine residue oxidation were determined. Also, the interference of NcADF oxidation in the interaction with actin was assessed. The treatment of the recombinant protein with oxidants reversibly induced the production of dimers, indicating that disulfide bonds between NcADF cysteine residues were formed. In addition, the exposure of NcADF to NCT resulted in more efficient oxidation of the cysteine residues compared to H2O2. Finally, the oxidation of NcADF by NCT reduced the ability of actin-binding and altered the function of NcADF in actin polymerization. Altogether, our results clearly show that recombinant NcADF is sensitive to redox conditions, indicating that the function of this protein in cellular processes involving actin dynamics may be modulated by oxidation.
Predictive models for endoscopic disease activity in patients with ulcerative colitis: Practical machine learning-based modeling and interpretation

Background Endoscopic disease activity monitoring is important for the long-term management of patients with ulcerative colitis (UC), there is currently no widely accepted non-invasive method that can effectively predict endoscopic disease activity. We aimed to develop and validate machine learning (ML) models for predicting it, which are desired to reduce the frequency of endoscopic examinations and related costs. Methods The patients with a diagnosis of UC in two hospitals from January 2016 to January 2021 were enrolled in this study. Thirty nine clinical and laboratory variables were collected. All patients were divided into four groups based on MES or UCEIS scores. Logistic regression (LR) and four ML algorithms were applied to construct the prediction models. The performance of models was evaluated in terms of accuracy, sensitivity, precision, F1 score, and area under the receiver-operating characteristic curve (AUC). Then Shapley additive explanations (SHAP) was applied to determine the importance of the selected variables and interpret the ML models. Results A total of 420 patients were entered into the study. Twenty four variables showed statistical differences among the groups. After synthetic minority oversampling technique (SMOTE) oversampling and RFE variables selection, the random forests (RF) model with 23 variables in MES and the extreme gradient boosting (XGBoost) model with 21 variables in USEIS, had the greatest discriminatory ability (AUC = 0.8192 in MES and 0.8006 in UCEIS in the test set). The results obtained from SHAP showed that albumin, rectal bleeding, and CRP/ALB contributed the most to the overall model. In addition, the above three variables had a more balanced contribution to each classification under the MES than the UCEIS according to the SHAP values. Conclusion This proof-of-concept study demonstrated that the ML model could serve as an effective non-invasive approach to predicting endoscopic disease activity for patients with UC. RF and XGBoost, which were first introduced into data-based endoscopic disease activity prediction, are suitable for the present prediction modeling.
Face identity and facial expression representations with adaptation paradigms: New directions for potential applications

Adaptation and aftereffect are well-known procedures for exploring our neural representation of visual stimuli. It has been reported that they occur in face identity, facial expressions, and low-level visual features. This method has two primary advantages. One is to reveal the common or shared process of faces, that is, the overlapped or discrete representation of face identities or facial expressions. The other is to investigate the coding system or theory of face processing that underlies the ability to recognize faces. This study aims to organize recent research to guide the reader into the field of face adaptation and its aftereffect and to suggest possible future expansions in the use of this paradigm. To achieve this, we reviewed the behavioral short-term aftereffect studies on face identity (i.e., who it is) and facial expressions (i.e., what expressions such as happiness and anger are expressed), and summarized their findings about the neural representation of faces. First, we summarize the basic characteristics of face aftereffects compared to simple visual features to clarify that facial aftereffects occur at a different stage and are not inherited or combinations of low-level visual features. Next, we introduce the norm-based coding hypothesis, which is one of the theories used to represent face identity and facial expressions, and adaptation is a commonly used procedure to examine this. Subsequently, we reviewed studies that applied this paradigm to immature or impaired face recognition (i.e., children and individuals with autism spectrum disorder or prosopagnosia) and examined the relationships between their poor recognition performance and representations. Moreover, we reviewed studies dealing with the representation of non-presented faces and social signals conveyed via faces and discussed that the face adaptation paradigm is also appropriate for these types of examinations. Finally, we summarize the research conducted to date and propose a new direction for the face adaptation paradigm.
A full-chip 3D computational lithography framework

3D lithography simulations capable of modeling 3D effects in all lithographic processes are becoming critical in OPC and verification applications as semiconductor feature sizes continue to shrink. These effects include mask topography, resist profile and wafer topography. In this work we present an efficient computational framework for full-chip 3D lithography simulations. Since fast modeling of mask topography effects has been studied for many years and is a relatively mature area, we will only briefly review a full-chip 3D mask model, Tachyon M3D, to highlight the importance and modeling requirements for accurate prediction of best focus variations among different device features induced by mask topography. We will focus our discussions on a full-chip 3D resist model, Tachyon R3D, its derivation and simplification from a full physical resist model. The resulting model form is fully compatible with the existing 2D resist model with added capabilities for resist profile and top loss prediction. A benchmark against the full physical model will be presented as well. We will also describe the development of a full-chip 3D wafer topography model, Tachyon W3D, and the preliminary results against rigorous simulations.
Age and sex differences in in-air vocalization characteristics of spotted seal pups from newborn to 1 year old in captivity

Acoustic parameters of spotted seals (Phoca largha), including the duration, peak frequency, and peak-to-peak source level, are reported to vary between different ages and sexes; however, to our knowledge, the vocal ontogeny of the spotted seal from newborn to 1 year old is yet to be studied. In the present study, we recorded and analyzed vocalizations of human-cared spotted seals from the Liaodong Bay colony from newborn to 1 year old, aiming to document the first-year development of seal vocalizations. We divided the spotted seal pups into four age groups (i.e., 1–3-month, 4–6-month, 7–9-month, and 10–12-month groups) for both sexes. The results show significant differences in sex patterns in sound parameters in terms of duration, peak frequency, and peak-to-peak source level. The vocalizations of female seal pups were longer in duration but lower in peak frequency and peak-to-peak source level than those of male pups. All three sound parameters were significantly different across different age groups. Specifically, the 1–3-month group had significantly lower values in duration, peak frequency, and peak-to-peak source level than the three other age groups. The 10–12-month group had significantly higher values in duration and peak-to-peak source level than the three other age groups. Our results also indicate a sex-specific development pattern of seal vocalizations from 1 year old until sexual maturity. Our findings will benefit the evaluation of anthropogenic noise impacts on spotted seal pups and further conservation of the seal population.
Subclinical dysfunction of remote myocardium is related to high NT-proBNP and affects global contractility at follow-up, independently of infarct area

Background In ST-segment elevation myocardial infarction (STEMI), predictors of subclinical dysfunction of remote myocardium are unknown. We prospectively aimed at identifying clinical and biochemical correlates of remote subclinical dysfunction and its impact on left ventricular ejection fraction (LVEF). Methods One-hundred thirty-three patients (63.9 ± 12.1 years, 68% male) with first successfully treated (54% anterior, 46% non-anterior, p = 0.19) STEMI underwent echocardiography at 5 ± 2 days after onset and at 8 ± 2-month follow-up, and were compared to 13 age and sex-matched (63.3 ± 11.4) healthy controls. All 16 left ventricular (LV) segments were grouped into ischemic, border, and remote myocardium: mean value of longitudinal strain (LS) within grouped segments were expressed as iLS, bLS, rLS, respectively. LV end-diastolic (EDV), end-systolic (ESV) volumes indexed for body surface area (EDVi, ESVi, respectively), LVEF and global LS (GLS) were determined. Creatinine, glomerular filtration rate, admission level of NT-pro-brain-natriuretic peptide (NT-proBNP) and troponin peaks were considered for the analysis. Results At baseline, rLS (15.5 ± 4.4) was better than iLS (12.9 ± 4.8, p < 0.001), but lower than that in controls (19.1 ± 2.7, p < 0.001) and similar to bLS (15 ± 5.4, p = ns), and did not differ between patients with single or multivessel coronary artery disease (CAD). At multivariate regression analysis, only admission NT-proBNP levels but not peak Tn levels independently predicted rLS (β = −0.58, p = 0.001), as well as iLS (β = −0.52, p = 0.001). Both at baseline and at follow-up, rLS correlated to LVEF similarly to iLS and bLS (p < 0.001 for all). Median value of rLS at baseline was 15%: compared to patients with rLS ≥ 15% at baseline, patients with rLS < 15% showed lower LVEF (52.3 ± 9.4 vs. 58.6 ± 7.6, p < 0.001) and GLS (16.3 ± 3.9 vs. 19.9 ± 3.2), and higher EDVi (62.3 ± 19.9 vs. 54 ± 12, p = 0.009) and ESVi (30.6 ± 15.5 vs. 22.3 ± 7.6, p < 0.001) at follow-up. Conclusion In optimally treated STEMI, dysfunction of remote myocardium assessed by LS: (1) is predicted by elevated NT-proBNP; (2) could be independent of CAD extent and infarct size; (3) is associated to worse LV morphological and functional indexes at follow-up.
Diagnosing an operational numerical model using Q-vector and potential vorticity concepts

Abstract A quasigeostrophic (QG) diagnostic model is used to evaluate the nested grid model's (NGM) predictions for a December cyclone whose impact on northeastern Colorado was underpredicted. Although the NGM predicted deepening of the associated 500-mb low, the model was 12 h slow in the onset of deepening and moved the storm too far east too quickly. Synthetic soundings, generated from 12-h predicted data initialized 24 h before cyclogenesis became apparent, were submitted to the same QG diagnostic algorithms used to analyze verifying rawinsonde data. Comparisons reveal that the NGM apparently 1) transported too much potential vorticity, westerly momentum, and cold air into the lower troposphere along the axis of the jet stream; 2) moved the first of two short-wavelength jet streaks too far northeastward and with too much strength; 3) failed to predict the strength of the following jet maximum; and 4) failed to develop an apparent tropopause fold. It is established that these errors were not caused by .
On Behavior Strategy Solutions in Two-Person Zero-Sum Finite Extended Games with Imperfect Information. Part I: A Method for Determination of Minimally Complex Behavior Strategy Solutions

In any two-person zero-sum finite extended game with imperfect information, an upper bound on the quality of each player’s strategies is established by his choice of a scheme for gathering and retaining the information that becomes available to him as the game progresses. Further, for a given game, strategies of the maximum possible quality may exist for each player on a number of information schemes of widely differing complexities.By analyzing the relationship between any given two-person zero-sum finite extended game with given information schemes for its players, and an associated N-person noncooperative game, a heuristic scheme is uncovered for searching for minimally complex information schemes which support behavior strategies having within $\varepsilon $ of the maximum possible quality, for any given $\varepsilon $. In the course of this analysis, a minimax theorem in behavior strategies is obtained, which is similar to von Neumann’s minimax theorem in mixed strategies.