Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal energy and tableting effects in benznidazole product: the impacts of industrial processing

Abstract Objective The investigation of benznidazole (BZN), excipients, and tablets aims to evaluate their thermal energy and tableting effects. They aim to understand better the molecular and pharmaceutical processing techniques of the formulation. Significance The Product Quality Review, part of Good Manufacturing Practices, is essential to highlight trends and identify product and process improvements. Methods A set of technique approaches, infrared spectroscopy, X-ray diffraction, and thermal analysis with isoconversional kinetic study, were applied in the protocol. Results X-ray experiments suggest talc and α-lactose monohydrate dehydration and conversion of β-lactose to stable α-lactose upon tableting. The signal crystallization at 167 °C in the DSC curve confirmed this observation. A calorimetric study showed a decrease in the thermal stability of BZN tablets. Therefore, the temperature is a critical process parameter. The specific heat capacity (Cp) of BZN, measured by DSC, was 10.04 J/g at 25 °C and 9.06 J/g at 160 °C. Thermal decomposition required 78 kJ mol−1. Compared with the tablet (about 200 kJ mol−1), the necessary energy is two-fold lower, as observed in the kinetic study by non-isothermal TG experiment at 5; 7.5; 10; and 15 °C min−1. Conclusions These results indicate the necessity of considering the thermal energy and tableting effects of BZN manufacturing, which contributes significantly to the molecular mechanistic understanding of this drug delivery system. Graphical Abstract
How large is large? Preliminary and relative guidelines for interpreting partial correlations in economics

An essential part of empirical economics research is the identification of the size of an empirical effect. Partial correlations offer a convenient statistically based measure of the strength of an economic relationship. A key question arises in their interpretation: When is a partial correlation large? This paper draws upon the observed distribution of 22,000 partial correlations from a diverse group of economics fields. The median absolute partial correlation from these fields is 0.173, which under Cohen’s (1988) conventional guidelines for zero order correlations is a small to moderate effect. The paper develops new guidelines for key qualitative categories (small, medium and large). According to the new guidelines, partial correlations that are larger than ± 0.33 can be deemed to be large. This is considerably different to Cohen’s guideline of ±0.50 for zero order correlations. Researchers and meta-analysts should exercise caution when applying Cohen’s guidelines to describe the importance of partial correlations in economics.
Symptoms of sleep problems and adherence to dietary guidelines in older women: evidence from the Australian Longitudinal Study on Women’s Health

Abstract Objective: This study examined adherence to dietary guidelines and symptoms of sleep problems (e.g. taking a long time to fall sleep or waking up early) and their associations in a sample of older Australian women (68–73 years of age). Design: This was a population-based cross-sectional study. Adherence to the dietary guidelines was measured using a validated FFQ and reported as a diet quality score. Symptoms of sleep problems were measured using five questions and a total score was derived. Multivariate linear regression was used to investigate the association between these outcomes, adjusted for the potential confounding influence of demographic (i.e. age and marital status) and lifestyle (i.e. physical activity, stress, alcohol intake, sleep medication use) variables. Setting: Respondents from the 1946–1951 cohort of the Australian Longitudinal Study on Women’s Health who completed Survey 9 were included. Participants: Data from n 7956 older women (mean age ± sd: 70·8 ± 1·5) were included. Results: 70·2 % reported having at least one symptom and 20·5 % had between 3 and 5 symptoms of sleep problems (mean score ± sd: 1·4 ± 1·4, range 0–5). Adherence to dietary guidelines was poor with an average diet quality score of 56·9 ± 10·7 (range 0–100). Better adherence to dietary guidelines was associated with fewer sleep problem symptoms (β: –0·065, 95 % CI: –0·012, –0·005) and remained significant after adjusting for confounding influences. Conclusions: These findings support the evidence that adherence to dietary guidelines is associated with symptoms of sleep problems in older women.
Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study.

Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.
Patients with cystic fibrosis who could not receive the CFTR modulator treatment: What did they lose in 1 year?

Cystic fibrosis (CF) is an autosomal recessive disorder caused by CF transmembrane conductance regulator (CFTR) genetic variants. CFTR modulators improve pulmonary function and reduce respiratory infections in CF. This study investigated the clinical and laboratory follow‐up parameters over 1 year in patients with CF who could not receive this treatment.
Real-time label-free detection of dynamic aptamer–small molecule interactions using a nanopore nucleic acid conformational sensor

Significance Fast, low-cost, accurate detection of time-resolved dynamic nucleic acid conformational variation in response to small molecule binding: 1) enriches our understanding of nucleic acid structure, and regulation of structure by small molecules as a key mechanism in their biological functions; 2) enables discovery of small molecule drug compounds that target nucleic acid structures as a therapeutic strategy; 3) supports development of new tools for synthetic biology based on gene expression networks regulated by small molecules; and 4) allows development of new sensors of small molecules such as neurotransmitters for studies in neurochemistry and disease diagnostics.
Constructing isospectral manifolds

In this article we construct nonisometric, isospectral manifolds modelled on semisimple Lie groups with finite center and no compact factors. Specifically, our two main results are the construction of arbitrarily large sets of closed, isospectral, nonisometric manifolds and pairs of infinite towers of finite covers that are isospectral and nonisometric at each stage. We also show the growth of these large sets of isospectral manifolds as a function of their volume is super-polynomial.
Systems pharmacology approach to explore the mechanisms of shufeng Jiedu Capsule on treating H1N1 infection

Abstract Background Influenza caused by the H1N1 virus still affects human health. There is currently no effective strategy against H1N1 virus infection. The present study is to evaluate the mechanism of Shufeng Jiedu Capsule (SFJDC) in the treatment of H1N1 infection using an integrated systems pharmacology approach and experimental validation. SFJDC is recommended for the treatment of H1N1 infection in traditional Chinese medicine (TCM), whose mechanism of action is not precise. Methods We systematically analyzed SFJDC using a systematic pharmacology and ADME screening model, and predicted effective targets using systematic drug targeting (SysDT) algorithm. Subsequently, the network of interactions between compounds and targets was built to help in the discovery of new drugs. In addition, the pathway of molecular action was determined by using enrichment analysis from the predicted targets. what is more, molecular docking also applied to predict the specific binding sites and binding capacity of active compounds and related targets, which validated the results of the compounds-targets network (C-T network). Finally, the mechanism of SFJDC effect on autophagy and virus replication in H1N1 virus-infected RAW264.7 mouse macrophage cells was experimentally verified. Results The systematic pharmacology results suggested that 68 candidate compounds were obtained from SFJDC, which interacted with 74 different targets related to inflammation and the immune system. The CCK-8 results showed that different concentrations of SFJDC serum had no significant inhibitory effect on the viability of RAW264.7 cells. LC3-II was significantly increased after virus infection compared to the control group, while it was inhibited by different concentrations of SFJDC serum. H1N1 virus nucleocapsid protein (NP protein) was significantly reduced in the high concentration group, Interleukin-1β (IL-1β), Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), and viral M1 gene were significantly reduced compared to the H1N1 group. Conclusions The integrated systemic pharmacological approach and experimental validation not only provide a precise explanation of the molecular mechanism of SFJDC in the treatment of H1N1 infection but also provide valuable clues for the development of novel drug strategies to control the H1N1 infection.
Utilization of modified spherical coordinates for satellite to satellite bearings-only tracking

A new satellite to satellite passive tracking method using Bearings-Only measurements in Modified Spherical Coordinates(MSC) is proposed.The system dynamics and measurement process are presented in three-dimensional MSC,and then the tracking method is deduced in details based on the Cartesian method.Performance of the new method is validated through computer simulations,which proved that the proposed method is effective in terms of the estimation accuracy and convergence time compared with the Cartesian method no matter the Initial State Errors(ISE) and measurement errors are large or small.
Smartphone-Based Remote Monitoring for Chronic Heart Failure: Mixed Methods Analysis of User Experience From Patient and Nurse Perspectives

Background Community-based management by heart failure specialist nurses (HFSNs) is key to improving self-care in heart failure with reduced ejection fraction. Remote monitoring (RM) can aid nurse-led management, but in the literature, user feedback evaluation is skewed in favor of the patient rather than nursing user experience. Furthermore, the ways in which different groups use the same RM platform at the same time are rarely directly compared in the literature. We present a balanced semantic analysis of user feedback from patient and nurse perspectives of Luscii, a smartphone-based RM strategy combining self-measurement of vital signs, instant messaging, and e-learning. Objective This study aims to (1) evaluate how patients and nurses use this type of RM (usage type), (2) evaluate patients’ and nurses’ user feedback on this type of RM (user experience), and (3) directly compare the usage type and user experience of patients and nurses using the same type of RM platform at the same time. Methods We performed a retrospective usage type and user experience evaluation of the RM platform from the perspective of both patients with heart failure with reduced ejection fraction and the HFSNs using the platform to manage them. We conducted semantic analysis of written patient feedback provided via the platform and a focus group of 6 HFSNs. Additionally, as an indirect measure of tablet adherence, self-measured vital signs (blood pressure, heart rate, and body mass) were extracted from the RM platform at onboarding and 3 months later. Paired 2-tailed t tests were used to evaluate differences between mean scores across the 2 timepoints. Results A total of 79 patients (mean age 62 years; 35%, 28/79 female) were included. Semantic analysis of usage type revealed extensive, bidirectional information exchange between patients and HFSNs using the platform. Semantic analysis of user experience demonstrates a range of positive and negative perspectives. Positive impacts included increased patient engagement, convenience for both user groups, and continuity of care. Negative impacts included information overload for patients and increased workload for nurses. After the patients used the platform for 3 months, they showed significant reductions in heart rate (P=.004) and blood pressure (P=.008) but not body mass (P=.97) compared with onboarding. Conclusions Smartphone-based RM with messaging and e-learning facilitates bilateral information sharing between patients and nurses on a range of topics. Patient and nurse user experience is largely positive and symmetrical, but there are possible negative impacts on patient attention and nurse workload. We recommend RM providers involve patient and nurse users in platform development, including recognition of RM usage in nursing job plans.
MYC regulates CSF1 expression via microRNA 17/20a to modulate tumor-associated macrophages in osteosarcoma

Osteosarcoma (OS) is the most common primary bone tumor of childhood. Approximately 20%–30% of OSs carry amplification of chromosome 8q24, which harbors the oncogene c-MYC and correlates with a poor prognosis. To understand the mechanisms that underlie the ability of MYC to alter both the tumor and its surrounding tumor microenvironment (TME), we generated and molecularly characterized an osteoblast-specific Cre-Lox-Stop-Lox-c-MycT58A p53fl/+ knockin genetically engineered mouse model (GEMM). Phenotypically, the Myc-knockin GEMM had rapid tumor development with a high incidence of metastasis. MYC-dependent gene signatures in our murine model demonstrated significant homology to the human hyperactivated MYC OS. We established that hyperactivation of MYC led to an immune-depleted TME in OS demonstrated by the reduced number of leukocytes, particularly macrophages. MYC hyperactivation led to the downregulation of macrophage colony-stimulating factor 1, through increased microRNA 17/20a expression, causing a reduction of macrophage population in the TME of OS. Furthermore, we developed cell lines from the GEMM tumors, including a degradation tag–MYC model system, which validated our MYC-dependent findings both in vitro and in vivo. Our studies utilized innovative and clinically relevant models to identify a potentially novel molecular mechanism through which MYC regulates the profile and function of the OS immune landscape.
Comparative acetylomic analysis reveals differentially acetylated proteins regulating fungal metabolism in hypovirus‐infected chestnut blight fungus

Abstract Cryphonectria parasitica, the chestnut blight fungus, and hypoviruses are excellent models for examining fungal pathogenesis and virus–host interactions. Increasing evidence suggests that lysine acetylation plays a regulatory role in cell processes and signalling. To understand protein regulation in C. parasitica by hypoviruses at the level of posttranslational modification, a label‐free comparative acetylome analysis was performed in the fungus with or without Cryphonectria hypovirus 1 (CHV1) infection. Using enrichment of acetyl‐peptides with a specific anti‐acetyl‐lysine antibody, followed by high accuracy liquid chromatography–tandem mass spectrometry analysis, 638 lysine acetylation sites were identified on 616 peptides, corresponding to 325 unique proteins. Further analysis revealed that 80 of 325 proteins were differentially acetylated between C. parasitica strain EP155 and EP155/CHV1‐EP713, with 43 and 37 characterized as up‐ and down‐regulated, respectively. Moreover, 75 and 65 distinct acetylated proteins were found in EP155 and EP155/CHV1‐EP713, respectively. Bioinformatics analysis revealed that the differentially acetylated proteins were involved in various biological processes and were particularly enriched in metabolic processes. Differences in acetylation in C. parasitica citrate synthase, a key enzyme in the tricarboxylic acid cycle, were further validated by immunoprecipitation and western blotting. Site‐specific mutagenesis and biochemical studies demonstrated that the acetylation of lysine‐55 plays a vital role in the regulation of the enzymatic activity of C. parasitica citrate synthase in vitro and in vivo. These findings provide a valuable resource for the functional analysis of lysine acetylation in C. parasitica, as well as improving our understanding of fungal protein regulation by hypoviruses from a protein acetylation perspective.
A Multi-stage Dynamic Incentive Model for Construction Project Managers From the Perspective of Work-Family Conflict

The results of this study will help organizations to focus on the mental health of CPMs in high-pressure occupations, helping them to alleviate negative psychological emotions and encouraging them to work positively, and to some extent, providing clinical trial data for related medical research. Objective This study aims to design incentives for organizations to improve the work engagement of construction project managers (CPMs) when they experience work-family conflict. Methods Based on principal-agent theory, a multistage dynamic incentive model for CPMs’ work engagement under the perspective of work-family conflict is constructed by integrating contract and reputation effect incentive mechanisms. Then MATLAB software was used to simulate the theoretical model for the arithmetic example. Finally, 182 valid questionnaires were tested for the conclusions of the model. Results In the two stages of the incentive model, work resources significantly positively influence CPMs’ work engagement, and work-family conflict harms CPMs’ work engagement. Including a reputation mechanism has two effects on the first stage of the incentive model. First, reputation has an incentive effect on CPMs’ work engagement. Second, it reduces the negative impact of work-family conflict on work engagement. The combination of contract- and reputation-based incentives will improve CPMs’ work engagement. Conclusions The results suggest that incentives targeted at increasing the work engagement of CPMs may be necessary.
Can repeated intranasal oxytocin administration affect reduced neural sensitivity towards expressive faces in autism? A randomized controlled trial.

BACKGROUND Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication and interaction. Crucial for efficient social interaction is the ability to quickly and accurately extract information from a person's face. Frequency-tagging electroencephalography (EEG) is a novel tool to quantify face-processing sensitivity in a robust and implicit manner. In terms of intervention approaches, intranasal administration of oxytocin (OT) is increasingly considered as a potential pharmacological approach for improving socio-communicative difficulties in ASD, through enhancing social salience and/or reducing (social) stress and anxiety. METHODS In this randomized, double-blind, placebo-controlled, mechanistic pharmaco-neuroimaging clinical trial, we implemented frequency-tagging EEG to conduct an exploratory investigation into the impact of repeated OT administration (4 weeks, 12 IU, twice daily) on neural sensitivity towards happy and fearful facial expressions in children with ASD (8-12 years old; OT: n = 29; placebo: n = 32). Neural effects were assessed at baseline, post-nasal spray (24 hr after the last nasal spray) and at a follow-up session, 4 weeks after the OT administration period. At baseline, neural assessments of children with ASD were compared with those of an age- and gender-matched cohort of neurotypical (NT) children (n = 39). RESULTS Children with ASD demonstrated reduced neural sensitivity towards expressive faces, as compared to NT children. Upon nasal spray administration, children with ASD displayed a significant increase in neural sensitivity at the post- and follow-up sessions, but only in the placebo group, likely reflecting an implicit learning effect. Strikingly, in the OT group, neural sensitivity remained unaffected from the baseline to the post-session, likely reflecting a dampening of an otherwise typically occurring implicit learning effect. CONCLUSIONS First, we validated the robustness of the frequency-tagging EEG approach to assess reduced neural sensitivity towards expressive faces in children with ASD. Furthermore, in contrast to social salience effects observed after single-dose administrations, repeated OT administration dampened typically occurring learning effects in neural sensitivity. In line with OT's social anxiolytic account, these observations possibly reflect a predominant (social) stress regulatory effect towards emotionally evocative faces after repeated OT administration.
A Review of Image-Based Food Recognition and Volume Estimation Artificial Intelligence Systems

The daily healthy diet and balanced intake of essential nutrients play an important role in modern lifestyle. The estimation of a meal's nutrient content is an integral component of significant diseases, such as diabetes, obesity and cardiovascular disease. Lately, there has been an increasing interest towards the development and utilization of smartphone applications with the aim of promoting healthy behaviours. The semi – automatic or automatic, precise and in real-time estimation of the nutrients of daily consumed meals is approached in relevant literature as a computer vision problem using food images which are taken via a user's smartphone. Herein, we present the state-of-the-art on automatic food recognition and food volume estimation methods starting from their basis, i.e., the food image databases. First, by methodically organizing the extracted information from the reviewed studies, this review study enables the comprehensive fair assessment of the methods and techniques applied for segmenting food images, classifying their food content and computing the food volume, associating their results with the characteristics of the used datasets. Second, by unbiasedly reporting the strengths and limitations of these methods and proposing pragmatic solutions to the latter, this review can inspire future directions in the field of dietary assessment systems.