Miracle-dz/UniFAR-FTUs huggingface dataset:
IGNITE: Individualized GeNeration of Imputations in Time-series Electronic health records

Electronic Health Records present a valuable modality for driving personalized medicine, where treatment is tailored to fit individual-level differences. For this purpose, many data-driven machine learning and statistical models rely on the wealth of longitudinal EHRs to study patients' physiological and treatment effects. However, longitudinal EHRs tend to be sparse and highly missing, where missingness could also be informative and reflect the underlying patient's health status. Therefore, the success of data-driven models for personalized medicine highly depends on how the EHR data is represented from physiological data, treatments, and the missing values in the data. To this end, we propose a novel deep-learning model that learns the underlying patient dynamics over time across multivariate data to generate personalized realistic values conditioning on an individual's demographic characteristics and treatments. Our proposed model, IGNITE (Individualized GeNeration of Imputations in Time-series Electronic health records), utilises a conditional dual-variational autoencoder augmented with dual-stage attention to generate missing values for an individual. In IGNITE, we further propose a novel individualized missingness mask (IMM), which helps our model generate values based on the individual's observed data and missingness patterns. We further extend the use of IGNITE from imputing missingness to a personalized data synthesizer, where it generates missing EHRs that were never observed prior or even generates new patients for various applications. We validate our model on three large publicly available datasets and show that IGNITE outperforms state-of-the-art approaches in missing data reconstruction and task prediction.
Iterative Feedback Network for Unsupervised Point Cloud Registration

As a fundamental problem in computer vision, point cloud registration aims to seek the optimal transformation for aligning a pair of point clouds. In most existing methods, the information flows are usually forward transferring, thus lacking the guidance from high-level information to low-level information. Besides, excessive high-level information may be overly redundant, and directly using it may conflict with the original low-level information. In this letter, we propose a novel Iterative Feedback Network (IFNet) for unsupervised point cloud registration, in which the representation of low-level features is efficiently enriched by rerouting subsequent high-level features. Specifically, our IFNet is built upon a series of Feedback Registration Block (FRB) modules, with each module responsible for generating the feedforward rigid transformation and feedback high-level features. These FRB modules are cascaded and recurrently unfolded over time. Further, the Feedback Transformer is designed to efficiently select relevant information from feedback high-level features, which is utilized to refine the low-level features. What's more, we incorporate a geometry-awareness descriptor to empower the network for making full use of most geometric information, which leads to more precise registration results. Extensive experiments on various benchmark datasets demonstrate the superior registration performance of our IFNet.
Binding potential and wetting behavior of binary liquid mixtures on surfaces.

We present a theory for the interfacial wetting phase behavior of binary liquid mixtures on rigid solid substrates, applicable to both miscible and immiscible mixtures. In particular, we calculate the binding potential as a function of the adsorptions, i.e., the excess amounts of each of the two liquids at the substrate. The binding potential fully describes the corresponding interfacial thermodynamics. Our approach is based on classical density functional theory. Binary liquid mixtures can exhibit complex bulk phase behavior, including both liquid-liquid and vapor-liquid phase separation, depending on the nature of the interactions among all the particles of the two different liquids, the temperature, and the chemical potentials. Here we show that the interplay between the bulk phase behavior of the mixture and the properties of the interactions with the substrate gives rise to a wide variety of interfacial phase behaviors, including mixing and demixing situations. We find situations where the final state is a coexistence of up to three different phases. We determine how the liquid density profiles close to the substrate change as the interaction parameters are varied and how these determine the form of the binding potential, which in certain cases can be a multivalued function of the adsorptions. We also present profiles for sessile droplets of both miscible and immiscible binary liquids.
FedNC: A Secure and Efficient Federated Learning Method with Network Coding

Federated Learning (FL) is a promising distributed learning mechanism which still faces two major challenges, namely privacy breaches and system efficiency. In this work, we reconceptualize the FL system from the perspective of network information theory, and formulate an original FL communication framework, FedNC, which is inspired by Network Coding (NC). The main idea of FedNC is mixing the information of the local models by making random linear combinations of the original parameters, before uploading for further aggregation. Due to the benefits of the coding scheme, both theoretical and experimental analysis indicate that FedNC improves the performance of traditional FL in several important ways, including security, efficiency, and robustness. To the best of our knowledge, this is the first framework where NC is introduced in FL. As FL continues to evolve within practical network frameworks, more variants can be further designed based on FedNC.
Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

Background: High-grade serous ovarian cancer (HGSOC) remains the most lethal gynecologic malignancy despite new therapeutic concepts, including poly-ADP-ribose polymerase inhibitors (PARPis) and antiangiogenic therapy. The efficacy of immunotherapies is modest, but clinical trials investigating the potential of combination immunotherapy with PARPis are underway. Homologous recombination repair deficiency (HRD) or BRCAness and the composition of the tumor microenvironment appear to play a critical role in determining the therapeutic response. Methods: We conducted comprehensive immunogenomic analyses of HGSOC using data from several patient cohorts, including a new cohort from the Medical University of Innsbruck (MUI). Machine learning methods were used to develop a classification model for BRCAness from gene expression data. Integrated analysis of bulk and single-cell RNA sequencing data was used to delineate the tumor immune microenvironment and was validated by immunohistochemistry. The impact of PARPi and BRCA1 mutations on the activation of immune-related pathways was studied in vitro using ovarian cancer cell lines, RNA sequencing, and immunofluorescence analysis. Results: We identified a predictive 24-gene signature to determine BRCAness. Comprehensive analysis of the tumor microenvironment allowed us to identify patient samples with BRCAness and high immune infiltration. Further characterization of these samples revealed increased infiltration of immunosuppressive cells, including tumor-associated macrophages (TAMs) expressing TREM2, C1QA, and LILRB4, as identified by further analysis of single-cell RNA sequencing data and gene expression analysis of samples from patients receiving combination therapy with PARPi and anti-PD-1. PARPi activated the cGAS-STING signaling pathway and the downstream innate immune response in a similar manner to HGSOC patients with BRCAness status. We have developed a web application (https://ovrseq.icbi.at) and an associated R package OvRSeq, which allow for comprehensive characterization of ovarian cancer patient samples and assessment of a vulnerability score that enables stratification of patients to predict response to the mentioned combination immunotherapy. Conclusions: Genomic instability in HGSOC affects the tumor immune environment, and TAMs play a crucial role in modulating the immune response. Based on various datasets, we have developed a diagnostic application that uses RNA sequencing data not only to comprehensively characterize HGSOC but also to predict vulnerability and response to combination immunotherapy. Keywords: High-grade serous ovarian cancer, BRCAness, PARP inhibitor, immunotherapy, vulnerability, RNA sequencing, tumor-associated macrophages, tumor immune microenvironment
Optimizing CO2 field flooding during sternotomy: In vitro confirmation of the Karolinska studies

Although CO2 field-flooding was first used during cardiac surgery more than 60 years ago, its efficacy is still disputed. The invisible nature of the gas and the difficulty in determining the “safe” quantity to protect the patient are two of the main obstacles to overcome for its validation. Moreover, CO2 concentration in the chest cavity is highly sensitive to procedural aspects, such suction and hand movements. Based on our review of the existing literature, we identified four major factors that influence the intra-cavity CO2 concentration during open-heart surgery: type of delivery device (diffuser), delivery CO2 flow rate, diffuser position around the wound cavity, and its orientation inside the cavity. In this initial study, only steady state conditions were considered to establish a basic understanding on the effect of the four above-mentioned factors. Transient factors, such as suction or hand movements, will be reported separately.
Challenges with pediatric antiretroviral therapy administration: Qualitative perspectives from caregivers and HIV providers in Kenya

Background Current formulations of pediatric antiretroviral therapy (ART) for children with HIV present significant barriers to adherence, leading to drug resistance, ART ineffectiveness, and preventable child morbidity and mortality. Understanding these challenges and how they contribute to suboptimal adherence is an important step in improving outcomes. This qualitative study describes how regimen-related challenges create barriers to adherence and impact families. Methods We conducted key informant interviews (KIIs) with 30 healthcare providers and 9 focus group discussions (FGDs) with a total of 72 caregivers, across three public hospitals in Siaya and Mombasa Kenya. The KIIs and FGDs were audio recorded, translated, and transcribed verbatim. The transcripts were hand coded based on emergent and a-priori themes. Results Caregivers discussed major regimen-related challenges to adherence included poor palatability of current formulations, complex preparation, and administration (including measuring, crushing, dissolving, mixing), complex drug storage, and frequent refill appointments and how these regimen-related challenges contributed to individual and intrapersonal barriers to adherence. Caregivers discussed how poor taste led to child anxiety, refusal of medications, and the need for caregivers to use bribes or threats during administration. Complex preparation led to concerns and challenges about maintaining privacy and confidentiality, especially during times of travel. Providers corroborated this patient experience and described how these challenges with administration led to poor infant outcomes, including high viral load and preventable morbidity. Providers discussed how the frequency of refills could range from every 2 weeks to every 3 months, depending on the patient. Caregivers discussed how these refill frequencies interrupted work and school schedules, risked unwanted disclosure to peers, required use of financial resources for travel, and ultimately were a challenge to adherence. Conclusion These findings highlight the need for improved formulations for pediatric ART to ease the daily burden on caregivers and children to increase adherence, improve child health, and overall quality of life of families.
The Combined Treatment with Ketogenic Diet and Metformin Slows Tumor Growth in Two Mouse Models of Triple Negative Breast Cancer

BACKGROUND Many tumors contain hypoxic microenvironments caused by inefficient tumor vascularization. Hypoxic tumors have been shown to resist conventional cancer therapies. Hypoxic cancer cells rely on glucose to meet their energetic and anabolic needs to fuel uncontrolled proliferation and metastasis. This glucose dependency is linked to a metabolic shift in response to hypoxic conditions. METHODS To leverage the glucose dependency of hypoxic tumor cells, we assessed the effects of a controlled reduction in systemic glucose by combining dietary carbohydrate restriction, using a ketogenic diet, with gluconeogenesis inhibition, using metformin, on two mouse models of triple-negative breast cancer (TNBC). RESULTS We confirmed that MET − 1 breast cancer cells require abnormally high glucose concentrations to survive in a hypoxic environment in vitro. Then, we showed that, compared to a ketogenic diet or metformin alone, animals treated with the combination regimen showed significantly lower tumor burden, higher tumor latency and slower tumor growth. As a result, lowering systemic glucose by this combined dietary and pharmacologic approach improved overall survival in our mouse model by 31 days, which is approximately equivalent to 3 human years. CONCLUSION This is the first preclinical study to demonstrate that reducing systemic glucose by combining a ketogenic diet and metformin significantly inhibits tumor proliferation and increases overall survival. Our findings suggest a possible treatment for a broad range of hypoxic and glycolytic tumor types, one that can also augment existing treatment options to improve patient outcomes.
An investigation of the modulatory effects of empathic and autistic traits on emotional and facial motor responses during live social interactions

A close relationship between emotional contagion and spontaneous facial mimicry has been theoretically proposed and is supported by empirical data. Facial expressions are essential in terms of both emotional and motor synchrony. Previous studies have demonstrated that trait emotional empathy enhanced spontaneous facial mimicry, but the relationship between autistic traits and spontaneous mimicry remained controversial. Moreover, previous studies presented faces that were static or videotaped, which may lack the “liveliness” of real-life social interactions. We addressed this limitation by using an image relay system to present live performances and pre-recorded videos of smiling or frowning dynamic facial expressions to 94 healthy female participants. We assessed their subjective experiential valence and arousal ratings to infer the amplitude of emotional contagion. We measured the electromyographic activities of the zygomaticus major and corrugator supercilii muscles to estimate spontaneous facial mimicry. Individual differences measures included trait emotional empathy (empathic concern) and the autism-spectrum quotient. We did not find that live performances enhanced the modulatory effect of trait differences on emotional contagion or spontaneous facial mimicry. However, we found that a high trait empathic concern was associated with stronger emotional contagion and corrugator mimicry. We found no two-way interaction between the autism spectrum quotient and emotional condition, suggesting that autistic traits did not modulate emotional contagion or spontaneous facial mimicry. Our findings imply that previous findings regarding the relationship between emotional empathy and emotional contagion/spontaneous facial mimicry using videos and photos could be generalized to real-life interactions.
Argan Oil, Functional Food, and the Sustainable Development of the Argan Forest

For years, in southwestern Morocco, the decline of the argan forest has been accompanied by the concomitant desert encroachment. Preservation of this forest by increasing the economic value of argan tree was proposed twenty years ago, but successful large scale production of certified, high quality argan oil, an edible oil introduced as a functional food, has only been recently achieved. Argan oil is now marketed in most developed countries, despite its elevated price, and protection of the argan forest is now seriously being considered. The aim of this work is to present the recent progress made in argan oil production, the ways explored to commercialize the oil extraction by-products, and recent attempts to use other argan tree parts as part of a long term aim to preserve the argan forest.
Risk Management for Replication Devices

This publication provides guidance on protecting the confidentiality, integrity, and availability of information processed, stored, or transmitted on replication devices (RDs). It suggests appropriate countermeasures in the context of the System Development Life Cycle. A security risk assessment template in table and flowchart format is also provided to help organizations determine the risk associated with replication devices.
A Humane Social Learning-Informed Metaverse: Cultivating Positive Technology Experiences in Digital Learning Environments

Online environments, such as metaverses, provide distinct social environments for people to engage in complex, cognitive, and multidirectional learning and meaning-making experiences. These engaging and influential environments highlight important factors associated with the Social Learning Theory (a process through which external settings influence behavior in specific environments). According to this theory, environments provide a space for youth to engage in reciprocal interactions of interpersonal, behavioral, and environmental cues. Online environments designed by social media companies have been scrutinized, given their dependence on algorithms (artificial intelligence systems). Research has revealed the effects of systems that use machine learning to subversively maintain engagement on their platforms for as long as possible. Given the constant changes in socializing environments, younger generational cohorts need to be adequately prepared for systems that determine what type of content they are exposed to, and shape the timing, frequency, and agentic influencers they engage with. Therefore, this article proposes a necessity to expand our understanding about social learning and current technology design principles. This article demonstrates the need for a paradigm shift toward exploring an innovative construct referred to as the digital learning environment. We examine existing issues in the design of digital spaces, provide a positive developmental psychology framework that informs further research, and propose solutions for researchers, educators, policymakers, and caregivers as they navigate healthy technology use and predominant mental health issues in the 21st century.
Acute endoplasmic reticulum stress-induced mitochondria respiratory chain damage: The role of activated calpains.

The induction of acute endoplasmic reticulum (ER) stress damages the electron transport chain (ETC) in cardiac mitochondria. Activation of mitochondria-localized calpain 1 (CPN1) and calpain 2 (CPN2) impairs the ETC in pathological conditions, including aging and ischemia-reperfusion in settings where ER stress is increased. We asked if the activation of calpains causes the damage to the ETC during ER stress. Control littermate and CPNS1 (calpain small regulatory subunit 1) deletion mice were used in the current study. CPNS1 is an essential subunit required to maintain CPN1 and CPN2 activities, and deletion of CPNS1 prevents their activation. Tunicamycin (TUNI, 0.4 mg/kg) was used to induce ER stress in C57BL/6 mice. Cardiac mitochondria were isolated after 72 h of TUNI treatment. ER stress was increased in both control littermate and CPNS1 deletion mice with TUNI treatment. The TUNI treatment activated both cytosolic and mitochondrial CPN1 and 2 (CPN1/2) in control but not in CPNS1 deletion mice. TUNI treatment led to decreased oxidative phosphorylation and complex I activity in control but not in CPNS1 deletion mice compared to vehicle. The contents of complex I subunits, including NDUFV2 and ND5, were decreased in control but not in CPNS1 deletion mice. TUNI treatment also led to decreased oxidation through cytochrome oxidase (COX) only in control mice. Proteomic study showed that subunit 2 of COX was decreased in control but not in CPNS1 deletion mice. Our results provide a direct link between activation of CPN1/2 and complex I and COX damage during acute ER stress.
The Nexus of Energy Supply and Human Health

Uses of main primary energy resources, such as coal, oil, and solid biomass, are directly linked with adverse impacts on human health. Air pollution emitted from various activities in the energy supply chains is the main risk factor to human health, along with accidental and occupational risk exposures. Estimates of premature deaths are over four million per year for ambient air pollution (2015) and household or indoor air pollution (2012). More than 80 percent of the mortality from ambient air pollution emitted from the energy supply chains occurs in developing countries. The impact of household air pollution, mainly from traditional biomass used for cooking and space heating, disproportionately falls on women and children under age five years. Acute respiratory infections, mainly caused by household air pollution, are one of the largest categories of deaths (64 percent) of children under age five years in developing countries. These statistics indicate the deep nexus between the energy supply chain and human health. Yet, the negative implications for human health from energy use often receive inadequate consideration. It is critically important to take account of these human health impacts in developing energy supply plans and energy policies in developing countries.
Inequalities in Mortality in the Asia-Pacific: A Cross-National Comparison of Socioeconomic Gradients

Abstract Objectives Social inequalities in mortality are poorly studied in much of the Asia-Pacific. Using data from harmonized nationally representative longitudinal health and aging surveys our study systematically assesses mortality disparities across 3 standardized measures of socioeconomic status in 7 Asia-Pacific countries. Methods We used data from multiple waves of 7 representative sample surveys: the Health, Income and Labour Dynamics in Australia survey, China Health and Retirement Longitudinal Study, the Indonesian Family Life Survey, the New Zealand Health, Work and Retirement survey, the Korean Longitudinal Study on Ageing and the Health, Aging and Retirement in Thailand survey, and the Japanese Study of Aging and Retirement. We use Cox proportional hazards modeling to examine how the hazard of mortality differs across domains of social stratification including educational attainment, wealth, and occupational status across countries. Results We found consistent and pervasive gradients in mortality risk in the high-income countries by all available measures of social stratification. In contrast, patterns of inequality in adult mortality in middle-income and recently transitioned high-income countries investigated varied depending on the measure of social stratification, with strong gradients by wealth but mixed gradients by education. Discussion Analyzing social gradients in mortality in the Asia-Pacific shows that inequalities, especially wealth-based inequalities, in later-life health are present across the region, and that the magnitude of social gradients in mortality is overall larger in high-income countries as compared to middle-income countries.