Miracle-dz/UniFAR-FTUs huggingface dataset:
Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice

Mycobacterium tuberculosis, the bacillus that causes tuberculosis (TB), infects 2 billion people across the globe, and results in 8-9 million new TB cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. We investigated the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using clinical indicators of disease, granuloma histopathological features, and immune response traits identified five new loci on mouse chromosomes 1, 2, 4, 16 and three previously identified loci on chromosomes 3 and 17. Quantitative trait loci (QTLs) on chromosomes 1, 16, and 17, associated with multiple correlated traits and had similar patterns of allele effects, suggesting these QTLs contain important genetic regulators of responses to M. tuberculosis. To narrow the list of candidate genes in QTLs, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks, generating functional scores. The scores were then used to rank candidates for each mapped trait in each locus, resulting in 11 candidates: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Importantly, all 11 candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling. Further, all candidates contain single nucleotide polymorphisms (SNPs), and some but not all SNPs were predicted to have deleterious consequences on protein functions. Multiple methods were used for validation including (i) a statistical method that showed Diversity Outbred mice carrying PWH/PhJ alleles on chromosome 17 QTL have shorter survival; (ii) quantification of S100A8 protein levels, confirming predicted allele effects; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and new functionally relevant gene candidates that may be major regulators of granuloma necrosis and acute inflammation in pulmonary TB.
Automated workflow for the cell cycle analysis of non-adherent and adherent cells using a machine learning approach

Understanding the details of the cell cycle at the level of individual cells is critical for both cellular biology and cancer research. While existing methods using specific fluorescent markers have advanced our ability to study the cell cycle in cells that adhere to surfaces, there is a clear gap when it comes to non-adherent cells. In this study, we combine a specialized surface to improve cell attachment, the genetically-encoded FUCCI(CA)2 sensor, an automated image processing and analysis pipeline, and a custom machine-learning algorithm. This combined approach allowed us to precisely measure the duration of different cell cycle phases in non-adherent, as well as adherent cells. Our method provided detailed information from hundreds of cells under different experimental conditions in a fully automated manner. We validated this approach in two different acute myeloid leukemia cell lines, NB4 and Kasumi-1, which have unique and distinct cell cycle characteristics. We also measured how drugs that influence cell cycle properties affect the duration of each phase in the cell cycles of these cell lines. Importantly, our cell cycle analysis system is freely available and has also been validated for use with adherent cells. In summary, this article introduces a comprehensive, automated method for studying the cell cycle in both non-adherent and adherent cells, offering a valuable tool for cellular biology, cancer research and drug development.
Role of the metallo-reductase FADING and vacuolinos in anthocyanin degradation in flowers and fruits

Anthocyanins are vacuolar pigments that confer red-violet colors to plant tissues. Pigmentation patterns result from spatio-temporally regulated anthocyanin synthesis and degradation. Mutational inactivation of a conserved MYB-bHLH-WDrepeat-WRKY transcriptional complex (MBWW) causes degradation of anthocyanins and ‘fading’ of flower color via a pathway that involves FADING (FA). Here we show that FA encodes a vacuolar membrane Fe-reductase-oxidase that promotes anthocyanin degradation. In wild type petals anthocyanins in the central vacuole (CV) are stable, because FA-GFP is upheld in small vacuoles (vacuolinos) and kept away from the CV, indicating that vacuolinos act as gatekeepers in protein trafficking. In cells lacking vacuolinos, including mbww- mutant petals, FA-GFP reaches the CV and triggers anthocyanin degradation. Virus-induced gene silencing (VIGS) of an FA-homolog in pepper fruits prevented the “fading” of anthocyanins during fruit maturation. These findings provide new insights to breed ornamental and food crops with increased anthocyanin-content and enhanced nutritional value of edible parts.
Knowledge Graph Embeddings: Open Challenges and Opportunities

While Knowledge Graphs (KGs) have long been used as valuable sources of structured knowledge, in recent years, KG embeddings have become a popular way of deriving numeric vector representations from them, for instance, to support knowledge graph completion and similarity search. This study surveys advances as well as open challenges and opportunities in this area. For instance, the most prominent embedding models focus primarily on structural information. However, there has been notable progress in incorporating further aspects, such as semantics, multi-modal, temporal, and multilingual features. Most embedding techniques are assessed using human-curated benchmark datasets for the task of link prediction, neglecting other important real-world KG applications. Many approaches assume a static knowledge graph and are unable to account for dynamic changes. Additionally, KG embeddings may encode data biases and lack interpretability. Overall, this study provides an overview of promising research avenues to learn improved KG embeddings that can address a more diverse range of use cases.
Ψ k Scientiﬁc Highlight Of The Month

This Psi-k Scientiﬁc Highlight is a reformatted preprint version of E. Caldeweyher and J. G. Brandenburg 2018 J. Phys.: Condens. Matter 30 213001 and is reproduced with permission by the Institute of Physics. Abstract Kohn-Sham density functional theory (DFT) is routinely used for the fast electronic structure computation of large systems and will most likely continue to be the method of choice for the generation of reliable geometries in the foreseeable future. Here, we present a hierarchy of simpliﬁed DFT methods designed for consistent structures and non-covalent interactions of large systems with particular focus on molecular crystals. The covered methods are a minimal basis set Hartree-Fock (HF-3c), a small basis set screened exchange hybrid functional (HSE-3c), and a generalized gradient approximated functional evaluated in a medium-sized basis set (B97-3c), all augmented with semi-classical correction potentials. We give an overview on the methods design, a comprehensive evaluation on established benchmark sets for geometries and lattice energies of molecular crystals, and highlight some realistic applications on large organic crystals with several hundreds of atoms in the primitive unit cell.
Enhancing Photostability of Complex Lead Halides through Modification with Antibacterial Drug Octenidine

The high power-conversion efficiencies of hybrid perovskite solar cells encourage many researchers. However, their limited photostability represents a serious obstacle to the commercialization of this promising technology. Herein, we present an efficient method for improving the intrinsic photostability of a series of commonly used perovskite material formulations such as MAPbI3, FAPbI3, Cs0.12FA0. 88PbI3, and Cs0.10MA0. 15FA0.75PbI3 through modification with octenidine dihydroiodide (OctI2), which is a widely used antibacterial drug with two substituted pyridyl groups and two cationic centers in its molecular framework. The most impressive stabilizing effects were observed in the case of FAPbI3 and Cs0.12FA0. 88PbI3 absorbers that were manifested in significant suppression or even blocking of the undesirable perovskite films’ recrystallization and other decomposition pathways upon continuous 110 mW/cm2 light exposure. The achieved material photostability—within 9000 h for the Oct(FA)n−1PbnI3n+1 (n = 40–400) and 20,000 h for Oct(Cs0.12FA0.88)n−1PbnI3n+1 (where n = 40–400) formulations—matches the highest values ever reported for complex lead halides. It is important to note that the stabilizing effect is maintained when OctI2 is used only as a perovskite surface-modifying agent. Using a two-cation perovskite composition as an example, we showed that the performances of the solar cells based on the developed Oct(Cs0.12FA0.88)399Pb400I1201 absorber material are comparable to that of the reference devices based on the unmodified perovskite composition. These findings indicate a great potential of the proposed approach in the design of new highly photostable and efficient light absorbers. We believe that the results of this study will also help to establish important guidelines for the rational material design to improve the operational stability of perovskite solar cells.
ad-Immobilization of whole cells of Lactococcus lactis containing high levels of a hyperthermostable β-galactosidase enzyme in chitosan beads for efficient galacto-oligosaccharide production

Galacto-oligosaccharides (GOS) are prebiotic food ingredients that are proposed to stimulate the growth of beneficial gut microorganisms, particularly bifido-bacteria. Previously, we developed a method for efficient GOS production using whole cells of Lactococcus lactis containing high levels of a hyper-thermostable β-galactosidase enzyme from Sulfolobus solfataricus . In this study, a recombinant DNA removal and whole-cell enzyme immobilization process was developed to produce GOS from lactose before removal of the immobilized whole-cell enzyme, which could be reused for subsequent applications. Chitosan was found to be a superior immobilization material compared with alginate, as it retained its bead structure during the high temperature (90°C) used here for GOS production. Prior to immobilization, the recombinant DNA was degraded in the whole cells using UV treatment, resulting in an immobilized whole-cell enzyme that was free of recombinant DNA and with minimum effect on the efficiency of the enzyme. The optimum pH and temperature for GOS synthesis using the chitosan beads was pH = 5.5 and 90°C. The highest GOS production using the chitosan beads occurred with 40% initial lactose resulting in 150 g/L of GOS (tri-oligosaccharides and tetra-oligosaccharides) in addition to di-oligosaccharide GOS products that were not quantified. Notably, the highest lactose conversion rate was found using lower starting lactose concentrations, with more than 60% conversion into tri-oligosaccharides and tetra-oligosaccharides. The immobilized enzyme retained ~50% activity after 2 cycles of GOS production. In conclusion, the chitosan-immobilized whole-cell enzyme can be used for efficient GOS production that is free of the whole-cell enzyme as well as detectable recombinant DNA.
Symmetry of upper eyelid after unilateral blepharoptosis repair with minimally invasive conjoint fascial sheath suspension technique.

AIM To investigate the symmetry of upper eyelid in patients with unilateral mild and moderate blepharoptosis who underwent unilateral minimally invasive combined fascia sheath (CFS) suspension. METHODS A retrospective study of patients who underwent unilateral minimally invasive CFS suspension surgery between January 2018 and December 2021. Inclusion criteria included unilateral mild and moderate ptosis, good levator muscle function (>9 mm) and follow-up of at least 6mo. Pre- and post-operative symmetry was graded subjectively for marginal reflex distance 1 (MRD1), tarsal platform show (TPS) and eyebrow fat span (BFS). A t-test was used to evaluate MRD1, TPS and BFS asymmetry by calculating delta values. The Bézier curve tool of the Image J software was used to extract the upper eyelid contours, where the symmetry was measured by the percentage of overlapping curvatures (POC). RESULTS Totally 105 patients (105 eyelids) were included (mild group, n=84; moderate group, n=21). Postoperatively, all patients increased MRD1 and decreased TPS in the ptotic eye while maintaining unchanged BFS. The asymmetric delta value for MRD1 was measured to be 1.48±0.86 preoperatively, and it decreased to 0.58±0.67 postoperatively in all cases (P=0.0004). In patients with mild ptosis, the asymmetry value of TPS fell significantly from 1.15±0.62 to 0.68±0.38 (P=0.0187). The symmetry of the upper eyelid contour increased in all subgroups of patients, with a POC of 59.39%±13.45% preoperatively and POC of 78.29%±13.80% postoperatively. CONCLUSION Minimally invasive CFS suspension is proved to be an effective means of improving the symmetry of unilateral ptosis in terms of MRD1 (all subgroups), POC (all subgroups) and TPS (only mild group), whereas BFS is unaffected.
OBM Integrative and Complementary Medicine

This paper reviews key theories underlying the interpersonal process in Compassion Focused Therapy (CFT) and links these to purported mechanisms of action in CFT. The paper goes on to provide a concrete practice example of an exampled dialogue between a clinician and client and narrates the interpersonal processes and mechanisms of action in an attempt to elucidate how interpersonal processes can be leveraged to facilitate therapeutic change. In so doing, this paper seeks to advance scholarship on precise mechanisms of change in psychotherapy, especially interpersonal processes in psychotherapy. Furthermore this paper seeks to provide a useful account of how interpersonal theory can be enacted in a clinical interaction.
review: A perspective on the future of genomic selection in dairy cattle

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of “single-step” methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.
A theory of counterfactuals

Will reading habit influence your life? Many say yes. Reading theory of counterfactuals is a good habit; you can develop this habit to be such interesting way. Yeah, reading habit will not only make you have any favourite activity. It will be one of guidance of your life. When reading has become a habit, you will not make it as disturbing activities or as boring activity. You can gain many benefits and importances of reading.
Heuristic-Aided Compressed Distance Databases

Answering point-to-point distance queries is important in many applications, including games, robotics and vehicle routing in operations research. Searching in a graph to answer distance queries on demand can often be too slow. An alternative strategy, taken in methods such as Transit and Hub Labels, is to pre-compute information that can help compute distances much faster. To be practical, such methods need to generate much less preprocessed data than a naive all-pairs distance table. We present Heuristic-Aid Compressed Distance Databases (HCDs), pre-computed data structures based on the observation that heuristic distance estimations can sometimes coincide with true distances. Compared to a naive all-pairs distance table, we report compression factors of two to three orders of magnitude in a wide range of maps, reducing the memory usage to a reasonable size. Compared to compressed path databases, our approach generally generates smaller databases, and answers query distances faster.
Rational Design of Flexible Mechanical Force Sensors for Healthcare and Diagnosis

Over the past decade, there has been a significant surge in interest in flexible mechanical force sensing devices and systems. Tremendous efforts have been devoted to the development of flexible mechanical force sensors for daily healthcare and medical diagnosis, driven by the increasing demand for wearable/portable devices in long-term healthcare and precision medicine. In this review, we summarize recent advances in diverse categories of flexible mechanical force sensors, covering piezoresistive, capacitive, piezoelectric, triboelectric, magnetoelastic, and other force sensors. This review focuses on their working principles, design strategies and applications in healthcare and diagnosis, with an emphasis on the interplay among the sensor architecture, performance, and application scenario. Finally, we provide perspectives on the remaining challenges and opportunities in this field, with particular discussions on problem-driven force sensor designs, as well as developments of novel sensor architectures and intelligent mechanical force sensing systems.
A type VII secretion system in Group B Streptococcus mediates cytotoxicity and 1 virulence 2

Type VII secretion systems (T7SS) have been identified in Actinobacteria and Firmicutes and 28 have been shown to secrete effector proteins with functions in virulence, host toxicity, or 29 interbacterial killing in a few genera. Bioinformatic analysis indicates that Group B streptococcal 30 (GBS) isolates encode four distinct subtypes of T7SS machinery, three of which encode 31 adjacent putative T7SS effectors with WXG and LXG motifs. However, the function of T7SS in 32 GBS pathogenesis is not known. Here we show that the most abundant GBS T7SS subtype is 33 important for virulence and cytotoxicity in brain endothelium and that these phenotypes are 34 dependent on the WXG100 effector EsxA. We further show that the WXG motif is required for 35 cytotoxicity in brain endothelium and that EsxA is a pore-forming protein. This work reveals the 36 importance of a T7SS in host–GBS interactions and has implications for the functions of T7SS 37 effectors in other Gram-positive bacteria. in GBS. We show by genomic analysis of available whole that the GBS T7SS can be divided into at least four subtypes based on the C-terminus of EssC. The GBS T7SS subtype I is the most prevalent, representing >50% of all isolates analyzed. Using a representative subtype I GBS strain, CJB111, we show that deletion 90 of the ATPase-encoding gene, essC, mitigates virulence and GBS-induced inflammation in the brain, as well as cell death in brain endothelial cells and that these phenotypes are dependent on the T7SS canonical substrate EsxA. We further show that the EsxA WXG motif is required for cytotoxicity in brain endothelium and that EsxA is a pore-forming protein. Our study provides the first experimental evidence indicating the T7SS promotes GBS pathogenesis and is the first demonstrate a role for a non-mycobacterial EsxA homolog in pore formation.
How Does Workplace Bullying Effect on Organizational Commitment and Job Performance? Mediating Effect of Job Stress in Hotels and Travel Agents.

Bullying is one of the most prominent terms recently circulated among people and on social media. This term is not modern; rather, it is as old as man, as it is one of the negative behaviours that some people follow. The phenomenon of bullying is present at all levels of life, and is not limited to one side without the other. It appears in the work environment as in life in general, where some employees are exposed to different forms of occupational bullying. Many researchers have examined the phenomenon of bullying in the work environment. Due to its significant impact on employees and their performance, and therefore on work and performance of tasks. So, the study relied on adopting a quantitative research with deductive approach and using mono method quantitative (field survey) over a structured questionnaire form filled by 578 employees from travel agents and hotels in Egypt. Statistical analyses were accomplished by using Statistical Package for Social Sciences (SPSS version 23) and IBM Amos ver. 25. The findings of this study achieved that workplace bullying effect on organizational commitment, job performance. The study recommends the following:
KalmanHD: Robust On-Device Time Series Forecasting with Hyperdimensional Computing

Time series forecasting is shifting towards Edge AI, where models are trained and executed on edge devices instead of in the cloud. However, training forecasting models at the edge faces two challenges concurrently: (1) dealing with streaming data containing abundant noise, which can lead to degradation in model predictions, and (2) coping with limited on-device resources. Traditional approaches focus on simple statistical methods like ARIMA or neural networks, which are either not robust to sensor noise or not efficient for edge deployment, or both. In this paper, we propose a novel, robust, and lightweight method named KalmanHD for on-device time series forecasting using Hyperdimensional Computing (HDC). KalmanHD integrates Kalman Filter (KF) with HDC, resulting in a new regression method that combines the robustness of KF towards sensor noise and the efficiency of HDC. KalmanHD first encodes the past values into a high-dimensional vector representation, then applies the Expectation-Maximization (EM) approach as in KF to iteratively update the model based on the incoming samples. KalmanHD inherently considers the variability of each sample and thereby enhances robustness. We further accelerate KalmanHD by substituting the expensive matrix multiplication with efficient binary operations between the covariance and the encoded values. Our results show that KalmanHD achieves MAE comparable to the state-of-the-art noise-optimized NN-based methods while running $3.6-8.6\times$ faster on typical edge platforms. The source code is available at https://github.com/DarthIV02/Ka1manHD
Multi-Mode Interference Reflector for Integrated Photonics

1-port and 2-port InAs-QD MMIR lasers are designed, fabricated, and characterized. MMIRs laser have lower threshold current densities compared to cleaved-cleaved FP lasers with the same cavity length, up to 40% less. They are promising for use in optoelectronic-integrated circuits.