Miracle-dz/UniFAR-FTUs huggingface dataset:
The KRAS-Mutant Consensus Molecular Subtype 3 Reveals an Immunosuppressive Tumor Microenvironment in Colorectal Cancer

Simple Summary The poor prognosis outcome of patients with KRAS mutations (KRASmut) was correlated with an immunosuppressive tumor microenvironment (TME). At the gene expression level and pathway analysis, KRASmut tumor activates TGFβ signaling to reduced proinflammatory and cytokine gene signatures. Spatial profiling in the TME region of KRASmut, classified as consensus molecular subtype 3 (CMS3), showed an up-regulation of genes CD40, CTLA4, ARG1, STAT3, IDO, and CD274, associated with immunosuppression in TME. Abstract Colorectal cancers (CRC) with KRAS mutations (KRASmut) are frequently included in consensus molecular subtype 3 (CMS3) with profound metabolic deregulation. We explored the transcriptomic impact of KRASmut, focusing on the tumor microenvironment (TME) and pathways beyond metabolic deregulation. The status of KRASmut in patients with CRC was investigated and overall survival (OS) was compared with wild-type KRAS (KRASwt). Next, we identified CMS, and further investigated differentially expressed genes (DEG) of KRASmut and distinctive pathways. Lastly, we used spatially resolved gene expression profiling to define the effect of KRASmut in the TME regions of CMS3-classified CRC tissues. CRC patients with KRASmut were mainly enriched in CMS3. Their specific enrichments of immune gene signatures in immunosuppressive TME were associated with worse OS. Activation of TGFβ signaling by KRASmut was related to reduced pro-inflammatory and cytokine gene signatures, leading to suppression of immune infiltration. Digital spatial profiling in TME regions of KRASmut CMS3-classified tissues suggested up-regulated genes, CD40, CTLA4, ARG1, STAT3, IDO, and CD274, that could be characteristic of immune suppression in TME. This study may help to depict the complex transcriptomic profile of KRASmut in immunosuppressive TME. Future studies and clinical trials in CRC patients with KRASmut should consider these transcriptional landscapes.
Association between School Achievement and Tobacco Susceptibility among US Adolescents: Ethnic Differences

Background: Although risky behaviors such as educational problems and tobacco use tend to co-occur, these associations may vary across diverse ethnic groups, in part because ethnic minorities tend to reside in worse neighborhoods and tend to attend worse schools than Non-Latino White adolescents. Aim: To compare the association between baseline school achievement (student grades) and subsequent tobacco use susceptibility (openness to smoke in future) by ethnicity, we compared African American, Latino, and Non-Latino White adolescents in the US over a four-year period. Methods: This longitudinal study followed 3636 adolescents who were never smokers at baseline for a period of four years. Baseline and four-year data of the Population Assessment of Tobacco and Health (PATH) study were used for this analysis. All participants were 12 to 17 years old at baseline and were either Non-Latino White (Majority), African American (Minority), or Latino (Minority). The outcome was a tobacco use susceptibility score at wave 4 which was defined as openness to use tobacco in the future, measured at year four. The predictor was school achievement at wave 1, measured as grades from F to A+. The moderator was ethnicity (African American, Latino, Non-Latino White), and covariates were age, gender, parental education, and family structure. Results: Our linear regressions in the pooled sample showed an inverse association between baseline school achievement and subsequent tobacco use susceptibility four years later. However, this inverse association was weaker for ethnic minorities than for Non-Latino White adolescents, as documented by interaction effects between ethnic minority status and baseline school grades. Conclusion: Higher educational success better correlates with lower tobacco use susceptibility of non-Latino White than African American and Latino adolescents, which may reflect some tobacco use susceptibility of Latino and African American adolescents with highly educated parents. Future research should investigate how social context such as high-risk school environment, neighborhood risk, peer risk, and other mechanisms increase behavioral risk of educationally successful African American and Latino adolescents.
Relationship between MoM and T-matrix approach: TM case in 2-D conducting scattering problems

The T-matrix of arbitrary shaped conducting cylinders is obtained in case of TM wave polarization. The electric field integral equation (EFIE) is solved by the method of moments (MoM), in which different orders of first-kind Bessel functions are used as incident waves one by one and radiation of surface discrete currents, resulted from MoM, is aggregated in a main coordinates system by employing the addition theorem of cylindrical harmonics. An explicit relationship between the impedance matrix in MoM and T-matrix of the cylinder is derived and verified by several calculation results.
INFLUENCE OF FUEL PROPERTIES ON THE DIESEL INJECTION PROCESS IN NONVAPORIZING CONDITIONS

This paper presents an experimental investigation of the influence of fuel density, viscosity, and surface tension on the diesel injection process (spray development and droplet size distribution) in non-vaporizing conditions. The spray development was captured in a pressurized vessel with a high-speed camera in order to obtain the penetration length and the spray angle. The droplet size distributions were measured by laser diffraction. A fuel matrix of eight fuels was designed including independent variations of fuel density, viscosity, and surface tension. Experimental conditions, such as injection pressure and air density, were varied according to current diesel engine conditions. The analysis focuses mainly on the quasi-stationary phase of the injection event. Results indicate that viscosity and to a lesser extent fuel density affect the spray characteristics. Increasing fuel density and viscosity by, respectively, 100 kg/m3 and 6.5 mm2/s induces longer spray tip penetration (up to 7%) with a narrower spray angle (drop of up to 3 deg) in quasi-stationary conditions. An increase in the Sauter mean diameter (up to 23% or 3 µm) was also observed. An increase in surface tension from 18 to 30 mN/m did not induce any significant modifications in the droplet size or in the spray development. Correlations, some of which are based on existing ones, are proposed to estimate the spray cone angle, the spray tip penetration, the SMD (Sauter mean diameter) and the drop size distribution considering the experimental conditions and the fuel properties.
Learning with Degree-Based Subgraph Estimation

Networks and their topologies are critical to nearly every aspect of modern life, with social networks governing human interactions and computer networks governing global information-flow. Network behavior is inherently structural, and thus modeling data from networks benefits from explicitly modeling structure. This thesis covers methods for and analysis of machine learning from network data while explicitly modeling one important measure of structure: degree. Central to this work is a procedure for exact maximum likelihood estimation of a distribution over graph structure, where the distribution factorizes into edge-likelihoods for each pair of nodes and degree-likelihoods for each node. This thesis provides a novel method for exact estimation of the maximum likelihood edge structure under the distribution. The algorithm solves the optimization by constructing an augmented graph containing, in addition to the original nodes, auxiliary nodes whose edges encode the degree potentials. The exact solution is then recoverable by finding the maximum weight b-matching on the augmented graph, a well-studied combinatorial optimization. To solve the combinatorial optimization, this thesis focuses in particular on a belief propagation-based approach to finding the optimal b-matching and provides a novel proof of convergence for belief propagation on the loopy graphical model representing the b-matching objective. Additionally, this thesis describes new algorithmic techniques to improve the scalability of the b-matching solver. In addition to various applications of node degree in machine learning, including classification and collaborative filtering, this thesis proposes a learning algorithm for learning the parameters of the distribution from network data consisting of node attributes and network connectivity, using strategies similar to maximum-margin structured prediction. The main methods and results in this thesis represent a deep exploration of exact degree-based estimation for machine learning from network data, and furthermore lead to various extensions and applications of the main idea described within.
Multifunctional doxorubicin/superparamagnetic iron oxide-encapsulated Pluronic F127 micelles used for chemotherapy/magnetic resonance imaging

Polymeric micelles are frequently used to transport and deliver drugs throughout the body because they protect against degradation. Research on functional polymeric micelles for biomedical applications has generally shown that micelles have beneficial properties, such as specific functionality, enhanced specific tumor targeting, and stabilized nanostructures. The particular aim of this study was to synthesize and characterize multifunctional polymeric micelles for use in controlled drug delivery systems and biomedical imaging. In this study, a theranostic agent, doxorubicin/superparamagnetic iron oxide (SPIO)-encapsulated Pluronic F127 (F127) micelles, was developed for dual chemotherapy/magnetic resonance imaging (MRI) purposes, and the structure and composition of the micellar SPIO were characterized by transmission electron microscopy and magnetic measurements. Our results revealed that the micellar SPIO with a diameter of around 100 nm led to a significant advantage in terms of T2 relaxation as compar.
Deep Submillimeter Images of NGC 891—Cold Dust at Larger Galactic Radii

We present images in the 450 and 850 μm continuum of the edge-on galaxy NGC 891. These measurements, carried out with the recently commissioned Submillimeter Common-User Bolometer Array, provide the deepest images yet of a nearby galaxy in the submillimeter wave band. We detect dust emission from 2/3 of the optical disk and confirm the presence of dust chimneys escaping from the main absorption layer up to z-heights of nearly 2 kpc. A comparison between the submillimeter surface brightness along the major axis with that corresponding to the IRAS 60 and 100 μm filters implies that large amounts of cold dust (~15 K) are present in the disk (in fact, an order of magnitude more grain material than the warm dust detected by IRAS). These cold grains predominate at larger galactic radii.
Circulating miR-122-5p, miR-92a-3p, and miR-18a-5p as Potential Biomarkers in Human Liver Transplantation Follow-Up

The requirement of blood-circulating sensitive biomarkers for monitoring liver transplant (LT) is currently a necessary step aiming at the reduction of standard invasive protocols, such as liver biopsy. In this respect, the main objective of this study is to assess circulating microRNA (c-miR) changes in recipients’ blood before and after LT and to correlate their blood levels with gold standard biomarkers and with outcomes such as rejection or complications after graft. An miR profile was initially performed; then, the most deregulated miRs were validated by RT-qPCR in 14 recipients pre- and post-LT and compared to a control group of 24 nontransplanted healthy subjects. MiR-122-5p, miR-92a-3p, miR-18a-5p, and miR-30c-5p, identified in the validation phase, were also analyzed considering an additional 19 serum samples collected from LT recipients and focusing on different follow-up (FU) times. The results showed significant, FU-related changes in c-miRs. In particular, miR-122-5p, miR-92a-3p, and miR-18a-5p revealed the same trend after transplantation and an increase in their level was found in patients with complications, independently from FU times. Conversely, the variations in the standard haemato-biochemical parameters for liver function assessment were not significant in the same FU period, confirming the importance of c-miRs as potential noninvasive biomarkers for monitoring patients’ outcomes.
Evidence for specularly reflected ions upstream from the quasi‐parallel bow shock

Ion velocity distributions in the form of bunches of gyrating particles traveling along helical paths have been observed moving sunward immediately upstream from quasi-parallel parts of the earth's bow shock using Los Alamos/Garching instruments on ISEE-1 and -2. These distributions have characteristics which indicate that they are produced by the nearly specular reflection at the shock of a portion of the incident solar wind ions. In particular, the guiding center motion and the gyrospeeds of the gyrating ions are quantitatively consistent with simple geometrical considerations for specular reflection. These considerations reveal that specularly reflected ions can escape upstream for θBn 45° (where θBn is the angle between the upstream magnetic field, B, and the local shock normal nˆ). These upstream gyrating ions are an important signature of one of the processes by which solar wind streaming energy is dissipated into other forms of energy at the shock.
Nonutility of procalcitonin for diagnosing bacterial pneumonia in patients with severe COVID-19

ABSTRACT Background Patients hospitalized with COVID-19 are at significant risk for superimposed bacterial pneumonia. However, diagnosing superinfection is challenging due to its clinical resemblance to severe COVID-19. We therefore evaluated whether the immune biomarker, procalcitonin, could facilitate the diagnosis of bacterial superinfection. Methods We retrospectively identified 185 patients hospitalized with severe COVID-19 who underwent lower respiratory culture; 85 had evidence of bacterial superinfection. Receiver operating characteristic curve and area under the curve (AUC) analyses were performed to assess the utility of procalcitonin for diagnosing superinfection. Results This approach demonstrated that procalcitonin measured at the time of culture was incapable of distinguishing patients with bacterial infection (AUC, 0.52). The AUC not affected by exposure to antibiotics, treatment with immunomodulatory agents, or timing of procalcitonin measurement. Conclusion Static measurement of procalcitonin does not aid in the diagnosis of superinfection in severe COVID-19.
White Matter Microstructure Reflects Individual Differences in Music Reward Sensitivity

People show considerable variability in the degree of pleasure they experience from music. These individual differences in music reward sensitivity are driven by variability in functional connectivity between the nucleus accumbens (NAcc), a key structure of the reward system, and the right superior temporal gyrus (STG). However, it is unknown whether a neuroanatomical basis exists for this variability. We used diffusion tensor imaging and probabilistic tractography to study the relationship between music reward sensitivity and white matter microstructure connecting these two regions via the orbitofrontal cortex (OFC) in 38 healthy human participants (24 females and 14 males). We found that right axial diffusivity (AD) in the STG–OFC connectivity inversely correlated with music reward sensitivity. Additionally, right mean diffusivity and left AD in the NAcc-OFC tract also showed an inverse correlation. Further, AD in this tract also correlated with previously acquired BOLD activity during music listening, but not for a control monetary reward task in the NAcc. Finally, we used mediation analysis to show that AD in the NAcc–OFC tract explains the influence of NAcc activation during a music task on music reward sensitivity. Overall, our results provide further support for the idea that the exchange of information among perceptual, integrative, and reward systems is important for musical pleasure, and that individual differences in the structure of the relevant anatomical connectivity influences the degree to which people are able to derive such pleasure. SIGNIFICANCE STATEMENT Music is one of the most important sources of pleasure for many people, but at the same time there are important individual differences in the sensitivity to musical reward. Previous studies have revealed the critical involvement of the functional connectivity between perceptual and subcortical brain areas in the enjoyment of music. However, it is unknown whether individual differences in music sensitivity might arise from variability in the structural connectivity among these areas. Here we show that structural connectivity between supratemporal and orbitofrontal cortices, and between orbitofrontal and nucleus accumbens, predict individual differences in sensibility to music reward. These results provide evidence for the critical involvement of the interaction between the subcortical reward system and higher-order cortical areas in music-induced pleasure.
Between Abnormal “Otherness” to Groundbreaking “Uniqueness”: The Family-Construction Process of the GLBT Family

ABSTRACT The GLBT family is a new postmodern phenomenon demonstrating the accomplishments of marginal groups seeking acceptance within mainstream society. The article is based on a qualitative phenomenological study conducted in Israel during 2012, providing a theoretical model combining a vast number of GLBT parenting options ranging from surrogacy, sperm donation, adoption, and co-parenting. The research consisted of 50 personal interviews that concentrated on the family experiences of couples of gay men and lesbian woman who opted to bring a child into their families. Analysis of the data points to a process of empowerment where societal norms in respect to gender, parenting, and family are deconstructed and then reconstructed. The theoretical model conceptualizes three parenting challenges that highlight the respondent’s family experience: “Otherness,” belonging, and self-actualization. Research shows that every period of family life addresses a different segment, where one of the three challenges becomes the dominant experience.
Multiple-image super-resolution of cryo-electron micrographs based on deep internal learning

Abstract Single-particle cryo-electron microscopy (cryo-EM) is a powerful imaging modality capable of visualizing proteins and macromolecular complexes at near-atomic resolution. The low electron-doses used to prevent radiation damage to the biological samples, however, result in images where the power of the noise is 100 times greater than the power of the signal. To overcome these low signal-to-noise ratios (SNRs), hundreds of thousands of particle projections are averaged to determine the three-dimensional structure of the molecule of interest. The sampling requirements of high-resolution imaging impose limitations on the pixel sizes that can be used for acquisition, limiting the size of the field of view and requiring data collection sessions of several days to accumulate sufficient numbers of particles. Meanwhile, recent image super-resolution (SR) techniques based on neural networks have shown state-of-the-art performance on natural images. Building on these advances, here, we present a multiple-image SR algorithm based on deep internal learning designed specifically to work under low-SNR conditions. Our approach leverages the internal image statistics of cryo-EM movies and does not require training on ground-truth data. When applied to single-particle datasets of apoferritin and T20S proteasome, we show that the resolution of the 3D structure obtained from SR micrographs can surpass the limits imposed by the imaging system. Our results indicate that the combination of low magnification imaging with in silico image SR has the potential to accelerate cryo-EM data collection by virtue of including more particles in each exposure and doing so without sacrificing resolution.
Comparison and Evaluation of GHG Emissions during Simulated Thermophilic Composting of Different Municipal and Agricultural Feedstocks

Composting is widely used to recycle a variety of different organic wastes. In this study, dairy manure, chicken litter, biosolids, yard trimmings and food waste were selected as representative municipal and agricultural feedstocks and composted in simulated thermophilic composting reactors to compare and evaluate the GHG emissions. The results showed that the highest cumulative emissions of CO2, CH4 and N2O were observed during yard trimmings composting (659.14 g CO2 kg−1 DM), food waste composting (3308.85 mg CH4 kg−1 DM) and chicken litter composting (1203.92 mg N2O kg−1 DM), respectively. The majority of the carbon was lost in the form of CO2. The highest carbon loss by CO2 and CH4 emissions and the highest nitrogen loss by N2O emission occurred in dairy manure (41.41%), food waste (0.55%) and chicken litter composting (3.13%), respectively. The total GHG emission equivalent was highest during food waste composting (365.28 kg CO2-eq ton−1 DM) which generated the highest CH4 emission and second highest N2O emissions, followed by chicken litter composting (341.27 kg CO2-eq ton−1 DM), which had the highest N2O emissions. The results indicated that accounting for GHG emissions from composting processes when it is being considered as a sustainable waste management practice was of great importance.
What’s in the laundromat? Mapping and characterising offshore-owned residential property in London

The UK, particularly London, is a global hub for money laundering, a significant portion of which takes place through residential property. However, understanding the distribution and characteristics of offshore residential property in the UK is a challenge. This paper attempts to remedy that situation by enhancing a publicly available dataset of UK property owned by offshore companies. We create a data-processing pipeline which draws on several datasets and on machine learning techniques to create a parsed set of addresses classified into six use classes. The enhanced dataset contains 138,000 properties – 44,000 more than the original dataset. The majority are residential (95k), with a disproportionate number of those in London (42k). The average offshore residential property in London is worth 1.33 million GBP, and collectively this amounts to approximately 56 billion GBP. We perform an in-depth analysis of offshore residential property in London, comparing the price, distribution and entropy/concentration with Airbnb property, low-use/empty property and conventional residential property. We estimate that the total number of offshore, low-use and Airbnb properties in London is between 144,000 and 164,000, collectively worth between 145–174 billion GBP. Furthermore, offshore residential property is more expensive and has higher entropy/concentration than all other property types. In addition, we identify two different types of offshore property – nested and individual – which have different price and distribution characteristics. Finally, we release the enhanced offshore property dataset, the complete low-use London dataset and the pipeline for creating the enhanced dataset to encourage further research into this topic.