Miracle-dz/UniFAR-FTUs huggingface dataset:
A Case Report of Occult Weak ‘A’ Subgroup: An Important Message for Renal Transplant Physicians

Accurate ABO grouping is the cornerstone of a successful ABO-compatible organ transplant. While conventional methods identify blood groups accurately in most cases, rare and weak blood groups could occasionally be misread/missed. Weak A subgroups such as A3, Ax, Aend, Am, Ay, and Ael are often mistyped as group O. We present one interesting case of ‘weak A’ subgroup in a renal transplant donor, who was wrongly typed as ‘O’ Rh D positive by conventional grouping techniques. It was a near miss as the donor was almost selected for transplant for the patient with blood group B positive.
Metabolic and immune response to high-fat diet in healthy urban Indonesian males with family history of type 2 diabetes mellitus

Objectives Non-diabetic first-degree relatives (FDR) of type 2 diabetes mellitus (T2DM) patients have been reported to have relatively higher insulin resistance and inflammatory markers compared to population without family history of T2DM. We investigated whether healthy FDR T2DM of Indonesian males living in urban area are more susceptible to the adverse effects of high-fat diet (HFD) than non-FDR subjects. Methods Twentyseven normoglycemic and normotensive FDR males and 28 ageand- body-mass-index-(BMI)-matched healthy non-FDR males underwent a 5-days HFD challenge. Dietary intake before and after HFD were collected by 24-hours food recall. Metabolic profiles and plasma cytokine levels were assessed before and after the HFD intervention. Results Within similar BMI profile between groups, FDR subjects showed significantly bigger waist circumference (p=0.001) and higher triglyceride (p=0,03) than those of non-FDR. Despite similar HOMA-IR and IL-6 responses to 5-days HFD, significant increase of plasma TNF-α/IL-10 ratio found in FDR subjects, while in contrary, TNF-α/IL-10 ratio significantly decreased in non-FDR group (p<0.001), resulting an OR of 7.1 (95% CI 2.2-23.4) for FDR to develop elevated plasma TNF-α/IL-10 ratio in response to HFD. The tendency was as high as 24.8 (95% CI 2.3-262.6) in FDR subjects with BMI ≥25 compared to the corresponding non-FDR subjects. Conclusions High-fat diet induced insulin resistance and increase of IL-6 plasma in healthy adult Indonesian males. Immune response polarization favouring proinflammatory environment was predominantly occurred in FDR subjects when compared to those of non- FDR subjects. Alteration of lipid accumulation was highly likely contributed to greater HFD-inflammation effects on FDR than non-FDR subjects.
The Intersection of Stress, Health, and Health Care Opportunities for Appalachian Transgender and Nonbinary People: An Interpretative Phenomenological Analysis

Transgender or nonbinary (TNB) individuals in the United States South experience higher rates of physical and mental health disparities when compared to their cisgender counterparts. Societal, interpersonal, and individual stigmas contribute to these disparities by increasing the levels of stress in the TNB population, which is a primary factor in higher morbidity and mortality. However, there is a paucity of research examining the impact of these stigmas on health through the lived experiences of TNB people living in Appalachia. An interpretive phenomenological analysis (IPA) research design was used to collect and analyze semi-structured interviews with TNB individuals living in Appalachia. Transcribed interviews were analyzed repeatedly by two analysts to identify emergent themes which focused on understanding an individual's lived experiences through interpretation. Ten participants from four Appalachian states within three Appalachian sub-regions participated in this study. Three shared healthcare themes were identified: experiences of stigma related to gender, the impact of stigma on personal wellbeing and perception of health, and the need for affirming TNB healthcare services. Respondents noted that chronic stress factors such as continual and compounding experiences of stigma and discrimination, stemming from religion or lack of affirming providers, negatively impacted their health. TNB individuals living in Appalachia experience chronic societal, interpersonal, and individual stressors that negatively impact their health. By addressing the stigmas, public health leaders, policymakers, and providers can improve access to health care and the health and quality of life of Appalachian TNB people.
Long‐distance gene flow in Acacia senegal: Hope for disturbed and fragmented populations

Abstract Even though pollen and seed dispersals are some of the important factors that determine tree species survival across landscapes, gene dispersal data of important tropical dryland tree species such as Acacia senegal that are undergoing various population disturbances remain scarce. Understanding patterns of gene dispersal in these ecosystems is important for conservation, landscape restoration and tree improvement. We investigated pollen and seed mediated gene flow in two A. senegal populations of contrasting state (less disturbed and heavily undisturbed) using nine microsatellites and 128 genotyping‐by‐sequencing single nucleotide polymorphism (SNPs) multilocus genotypes of two growth stages (juvenile and adult trees) and their spatial locations. We performed parentage assignments using likelihood approach and undertook spatial genetic structure (SGS) analyses for the two growth stages through correlation among kinship coefficients and geographical distances between pair of individuals. The SNPs showed higher resolving power and assignment rates than microsatellites; however, a combination of the two marker‐types improved the assignment rate and provided robust parentage assessments. We found evidence of long‐distance (up to 210 m) pollination events for both populations; however, the majority of seed dispersal was found closer to the putative maternal parent. On average, parentage analysis showed high amounts of pollen (40%) and seed (20%) immigration in both populations. Significant positive SGS was found only for the adult cohorts in the less disturbed population for distance classes 20 and 40 m, indicating historical short‐distance seed dispersals. Our results suggest long‐distance gene flow within the species and we recommend conservation of remnant and isolated populations or individual trees to promote genetic connectivity.
In vitro and in silico studies for the identification of anti-cancer and antibacterial peptides from camel milk protein hydrolysates

Today, breast cancer and infectious diseases are very worrying that led to a widespread effort by researchers to discover natural remedies with no side effects to fight them. In the present study, we isolated camel milk protein fractions, casein and whey proteins, and hydrolyzed them using pepsin, trypsin, and both enzymes. Screening of peptides with anti-breast cancer and antibacterial activity against pathogens was performed. Peptides derived from whey protein fraction with the use of both enzymes showed very good activity against MCF-7 breast cancer with cell viability of 7.13%. The separate use of trypsin and pepsin to digest whey protein fraction yielded peptides with high antibacterial activity against S. aureus (inhibition zone of 4.17 ± 0.30 and 4.23 ± 0.32 cm, respectively) and E. coli (inhibition zone of 4.03 ± 0.15 and 4.03 ± 0.05 cm, respectively). Notably, in order to identify the effective peptides in camel milk, its protein sequences were retrieved and enzymatically digested in silico. Peptides that showed both anticancer and antibacterial properties and the highest stability in intestinal conditions were selected for the next step. Molecular interaction analysis was performed on specific receptors associated with breast cancer and/or antibacterial activity using molecular docking. The results showed that P3 (WNHIKRYF) and P5 (WSVGH) peptides had low binding energy and inhibition constant so that they specifically occupied active sites of protein targets. Our results introduced two peptide-drug candidates and new natural food additive that can be delivered to further animal and clinical trials.
Methods used to evaluate usability of mobile clinical decision support systems for healthcare emergencies: a systematic review and qualitative synthesis

Abstract Objective The aim of this study was to determine the methods and metrics used to evaluate the usability of mobile application Clinical Decision Support Systems (CDSSs) used in healthcare emergencies. Secondary aims were to describe the characteristics and usability of evaluated CDSSs. Materials and Methods A systematic literature review was conducted using Pubmed/Medline, Embase, Scopus, and IEEE Xplore databases. Quantitative data were descriptively analyzed, and qualitative data were described and synthesized using inductive thematic analysis. Results Twenty-three studies were included in the analysis. The usability metrics most frequently evaluated were efficiency and usefulness, followed by user errors, satisfaction, learnability, effectiveness, and memorability. Methods used to assess usability included questionnaires in 20 (87%) studies, user trials in 17 (74%), interviews in 6 (26%), and heuristic evaluations in 3 (13%). Most CDSS inputs consisted of manual input (18, 78%) rather than automatic input (2, 9%). Most CDSS outputs comprised a recommendation (18, 78%), with a minority advising a specific treatment (6, 26%), or a score, risk level or likelihood of diagnosis (6, 26%). Interviews and heuristic evaluations identified more usability-related barriers and facilitators to adoption than did questionnaires and user testing studies. Discussion A wide range of metrics and methods are used to evaluate the usability of mobile CDSS in medical emergencies. Input of information into CDSS was predominantly manual, impeding usability. Studies employing both qualitative and quantitative methods to evaluate usability yielded more thorough results. Conclusion When planning CDSS projects, developers should consider multiple methods to comprehensively evaluate usability.
Molecular dynamics simulations of thermal transport in isotopically modulated semiconductor nanostructures

In this paper, we investigate the effect of isotopic modulation on the thermal conductivity of semiconductor nanostructures. The isotope doping is of particular interest for the application of semiconductors as thermoelectric materials as it leaves the electronic properties practically unaffected while the phononic transport is retarded. This approach could increase the figure of merit of thermoelectric generators by decreasing the thermal conductivity of semiconductors. We use non‐equilibrium molecular dynamics simulations to examine thermal transport in isotopically engineered semiconductors. The temperature profiles along the sample region deduced from the simulations allow the extraction of thermal conductivities. The reliability of the MD‐predicted thermal conductivities is studied by analyzing the influence of the input parameters on the results. The first set of samples are isotopically modified silicon samples. The influence of temperature, isotopic composition, and ordering of isotopic defects on the thermal conductivity of silicon is studied. The second material system under investigation is silicon germanium alloys. The influence of isotopic modulation on the thermal conductivity of Si–Ge alloys is examined for varying chemical composition. The thermal conductivities predicted by MD are compared to results derived from the solution of the Boltzmann transport equation in the relaxation time approach.
Autologous natural killer cells as a promising immunotherapy for locally advanced colon adenocarcinoma: Three years follow‐up of resectable case

Over the last decade, a new modality of immunotherapy has been announced, with the expectation of better long‐term clinical outcomes and disease‐free survival after the definitive surgical treatment of colon cancer. Natural killer (NK) cells as part of cellular therapy in immunotherapy have the potential effect as an adjuvant therapy for locally advanced and metastasized colorectal adenocarcinoma. We would evaluate the clinical outcome of autologous NK cell therapy for resectable colon cancer.
A potential posttranscriptional regulator for p60‐katanin: miR‐124‐3p

Katanin is a microtubule severing protein belonging to the ATPase family and consists of two subunits; p60‐katanin synthesized by the KATNA1 gene and p80‐katanin synthesized by the KATNB1 gene. Microtubule severing is one of the mechanisms that allow the reorganization of microtubules depending on cellular needs. While this reorganization of microtubules is associated with mitosis in dividing cells, it primarily takes part in the formation of structures such as axons and dendrites in nondividing mature neurons. Therefore, it is extremely important in neuronal branching. p60 and p80 katanin subunits coexist in the cell. While p60‐katanin is responsible for cutting microtubules with its ATPase function, p80‐katanin is responsible for the regulation of p60‐katanin and its localization in the centrosome. Although katanin has vital functions in the cell, there are no known posttranscriptional regulators of it. MicroRNAs (miRNAs) are a group of small noncoding ribonucleotides that have been found to have important roles in regulating gene expression posttranscriptionally. Despite being important in gene regulation, so far no microRNA has been experimentally associated with katanin regulation. In this study, the effects of miR‐124‐3p, which we detected as a result of bioinformatics analysis to have the potential to bind to the p60 katanin mRNA, were investigated. For this aim, in this study, SH‐SY5Y neuroblastoma cells were transfected with pre‐miR‐124‐3p mimics and pre‐mir miRNA precursor as a negative control, and the effect of this transfection on p60‐katanin expression was measured at both RNA and protein levels by quantitative real‐time PCR (qRT‐PCR) and western blotting, respectively. The results of this study showed for the first time that miR‐124‐3p, which was predicted to bind p60‐katanin mRNA by bioinformatic analysis, may regulate the expression of the KATNA1 gene. The data obtained within the scope of this study will make important contributions in order to better understand the regulation of the expression of p60‐katanin which as well will have an incontrovertible impact on the understanding of the importance of cytoskeletal reorganization in both mitotic and postmitotic cells.
Tomographic reconstruction of sound velocity distribution

An approach based on limited-angle transmission tomography for reconstruction of the sound velocity distribution in the breast is proposed. The imaging setup allows acoustic data acquisition for simultaneous B-mode image formation and the tomographic sound velocity reconstruction. The time-of-flight data are acquired by a linear array positioned at the top of the compressed breast that both transmits and receives, and a metal plate is placed at the bottom as a reflector. In order to improve the sound velocity estimation accuracy, a reconstruction algorithm based on a convex programming formulation has been developed. Simulations for both imaging and time-of-flight data based on a 5-MHz linear array were performed. Effects of wave propagation such as refraction and diffraction were included in the generated data. Results show that the proposed approach is both feasible and accurate. The approach can be used to complement conventional B-mode imaging to enhance the detection of breast cancer.
Improved facial expression recognition using graph signal processing

A novel method of facial expression recognition using graph signal processing (GSP) is proposed. Here the dimensionality of the feature vector of the facial expression based on the histogram of oriented gradients and discrete wavelet transform is reduced using the GSP and then applied to a classifier. The proposed scheme is compared with the existing methods on the JAFFE dataset in terms of the accuracy and the length of the feature vector. It is seen from the simulation results that the proposed scheme provides better accuracy than the existing methods.
A Data Mining Approach to Highlight Relations Between Functional Modules

We propose a data-mining approach to work on large graphs with set of labels associated to vertices. This type of data fits well with biological datasets, for example, a protein/protein interaction graph where each protein is labeled with the biological situations in which the corresponding gene is over-expressed. Previous works on this type of dataset focus on finding functional modules, i.e., set of strongly interacting proteins over-expressed in the same biological situations. Our main originality considering previous work on this type of dataset consists in finding collections of functional modules. We introduce the problem of extracting Maximal Homogeneous Clique Set (MHCS) which are set of cliques (i.e., complete subgraph) satisfying constraints on the number of labels shared by all the vertices and on the number of separated cliques having a minimal size. This pattern definition may highlight relations between densely connected subgraphs, for example it may exhibit genes being at the bridge of different functional modules. It might also shows up groups of proteins for which we have no evidences of interaction and where their coding genes are all over-expressed in the same biological situations. This kind of patterns might suggests investigations for potential interactions. Clearly, a naive enumeration of all MHCS in a dataset is intractable in practice, it is thus necessary to develop an efficient algorithm taking into account constraints properties. Using monotonic and anti-monotonic constraints properties, we were able to propose a complete algorithm, and we experimentally shown that it scales well on graphs with hundreds thousand vertices. We also performed experiments on a biological dataset built upon STRING, a protein/protein interactions database and SQUAT, a binarized gene expression database containing results from SAGE experiments. On this dataset we looked for MHCSs formed by at least 2 separated cliques having 3 genes, and where all genes are over-expressed in 3 common biological situations. Using those parameters we found groups of genes that are functionally unrelated except for a transcription factor (CRX) activating genes related to eye development and vision that fall in different functional categories.
Understanding discrete capillary-wave turbulence using a quasi-resonant kinetic equation

Experimental and numerical studies have shown that, with sufficient nonlinearity, the theoretical capillary-wave power-law spectrum derived from the kinetic equation (KE) of weak turbulence theory can be realized. This is despite the fact that the KE is derived assuming an infinite domain with continuous wavenumber, while experiments and numerical simulations are conducted in realistic finite domains with discrete wavenumbers for which the KE theoretically allows no energy transfer. To understand this, we first analyse results from direct simulations of the primitive Euler equations to elucidate the role of nonlinear resonance broadening (NRB) in discrete turbulence. We define a quantitative measure of the NRB, explaining its dependence on the nonlinearity level and its effect on the properties of the obtained stationary power-law spectra. This inspires us to develop a new quasi-resonant kinetic equation (QKE) for discrete turbulence, which incorporates the mechanism of NRB, governed by a single parameter $\unicode[STIX]{x1D705}$ expressing the ratio of NRB and wavenumber discreteness. At $\unicode[STIX]{x1D705}=\unicode[STIX]{x1D705}_{0}\approx 0.02$ , the QKE recovers simultaneously the spectral slope $\unicode[STIX]{x1D6FC}_{0}=-17/4$ and the Kolmogorov constant $C_{0}=6.97$ (corrected from the original derivation) of the theoretical continuous spectrum, which physically represents the upper bound of energy cascade capacity for the discrete turbulence. For $\unicode[STIX]{x1D705}<\unicode[STIX]{x1D705}_{0}$ , the obtained spectra represent those corresponding to a finite domain with insufficient nonlinearity, resulting in a steeper spectral slope $\unicode[STIX]{x1D6FC}<\unicode[STIX]{x1D6FC}_{0}$ and reduced capacity of energy cascade $C>C_{0}$ . The physical insights from the QKE are corroborated by direct simulation results of the Euler equations.
Hardware architecture and optimisation of FPP particle PHD filter for multi‐target tracking in cyber‐physical systems

To meet the rapidly growing demand of localisation and tracking information of mobile agents in cyber-physical systems, in this paper, we propose a fully pipelined and parallel (FPP) hardware architecture of particle probability hypothesis density (PHD) filter for multi-target tracking on the multi-cores processor hardware platforms, where an improved resampling algorithm is designed. We formulate the demand of minimising the processing delay in this architecture as an optimisation problem, which can be efficiently solved by transforming it to a group of mixed non-linear integer programming problems. Delay analysis shows that the proposed FPP particle PHD filter achieves significant improvement of real-time performance, and simulation results demonstrate that tracking performance remains at the same level as traditional particle PHD filters.
Unique Genomic Alterations and Microbial Profiles Identified in Patients With Gastric Cancer of African, European, and Asian Ancestry

Objective: Here, we characterize differences in the genetic and microbial profiles of GC in patients of African (AFR), European, and Asian ancestry. Background: Gastric cancer (GC) is a heterogeneous disease with clinicopathologic variations due to a complex interplay of environmental and biological factors, which may affect disparities in oncologic outcomes. Methods: We identified 1042 patients with GC with next-generation sequencing data from an institutional Integrated Mutation Profiling of Actionable Cancer Targets assay and the Cancer Genomic Atlas group. Genetic ancestry was inferred from markers captured by the Integrated Mutation Profiling of Actionable Cancer Targets and the Cancer Genomic Atlas whole exome sequencing panels. Tumor microbial profiles were inferred from sequencing data using a validated microbiome bioinformatics pipeline. Genomic alterations and microbial profiles were compared among patients with GC of different ancestries. Results: We assessed 8023 genomic alterations. The most frequently altered genes were TP53, ARID1A, KRAS, ERBB2, and CDH1. Patients of AFR ancestry had a significantly higher rate of CCNE1 alterations and a lower rate of KRAS alterations (P < 0.05), and patients of East Asian ancestry had a significantly lower rate of PI3K pathway alterations (P < 0.05) compared with other ancestries. Microbial diversity and enrichment did not differ significantly across ancestry groups (P > 0.05). Conclusions: Distinct patterns of genomic alterations and variations in microbial profiles were identified in patients with GC of AFR, European, and Asian ancestry. Our findings of variation in the prevalence of clinically actionable tumor alterations among ancestry groups suggest that precision medicine can mitigate oncologic disparities.