Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the tumor immune microenvironment for precision immunotherapy

The complexity of the cellular and acellular players within the tumor microenvironment (TME) allows for significant variation in TME constitution and role in anticancer treatment response. Spatial alterations in populations of tumor cells and adjacent non‐malignant cells, including endothelial cells, fibroblasts and tissue‐infiltrating immune cells, often have a major role in determining disease progression and treatment response in cancer. Many current standard systemic antineoplastic treatments target the cancer cells and could be further refined to directly target commonly dysregulated cell populations of the TME. Recent developments in immuno‐oncology and bioengineering have created an attractive potential to model these complexities at the level of the individual patient. These developments, along with the increasing momentum in precision medicine research and application, have catalysed exciting new discoveries in understanding drug–TME interactions, target identification, and improved efficacy of therapies. While rapid progress has been made, there are still many challenges to overcome in the development of accurate in vitro, in vivo and ex vivo models incorporating the cellular interactions that take place in the TME. In this review, we describe how advances in immuno‐oncology and patient‐derived models, such as patient‐derived organoids and explant cultures, have enhanced the landscape of personalised immunotherapy prediction and treatment of solid organ malignancies. We describe and compare different immunological targets and perspectives on two‐dimensional and three‐dimensional modelling approaches that may be used to better rationalise immunotherapy use, ultimately providing a knowledge base for the integration of the autologous TME into these predictive models.
Permian Magnetostratigraphy and End of the Kiaman Reverse Polarity Superchron From the Southeast Karoo Basin, South Africa

Paleomagnetic results for a ∼2,353‐m‐thick magnetostratigraphic section for undeformed middle to late Permian rocks in the southeast of the Karoo Basin of South Africa are reported. Predominantly pseudo‐single‐domain or single‐domain titanomagnetite (with possible minor contributions by pyrrhotite and multi‐domain magnetite) were identified as remanence carriers of a dual polarity magnetization interpreted as the record of the Permian geomagnetic field during the Kiaman Reverse Polarity Superchron and subsequent Illawarra mixed polarity interval. The timing of remanence acquisition is further constrained by the effect of Jurassic‐aged dolerite intrusions, which either partially or wholly overprint the Permian remanence in their immediate vicinity. A paleopole at 62.0°S; 64.3°E and dp/dm = 4.9°/5.8° is calculated from the bedding‐corrected primary remanence (when corrected for inclination shallowing at f = 0.6 the paleopole is located at 53.2°S; 46.9°E and dp/dm = 5.9°/6.3°). This is comparable to other Permian paleopoles from the southwest section of the Karoo Basin. The end of the Kiaman Reverse Polarity Superchron can be correlated between the E‐W extremes of the basin to reveal a diachronous boundary between the Ecca and the Beaufort groups, with diachronicity calibrated to 1.1 million years for the first time.
Lessons from an Expert Teacher of Immigrant Youth: A Portrait of Social Justice Teaching

ABSTRACT With approximately 40 million foreign-born people in the United States, US classrooms are witnessing an intense concentration of newcomer students and a persistent achievement gap between immigrant students and their English-speaking, US-born peers. Yet, some teachers are consistently successful with “those” children typically marginalized by schools. In this article, we describe, analyze, and theorize the practice of a master teacher who has spent over 20 years working with newcomer immigrant youth in the United States. Daphne invites her students to co-create the curriculum with her around their pressing questions, driven by her strong belief that her students are full of capacity, woke to the world around them, and thinking deeply about issues that affect them. Daphne’s practice demonstrates the power of critical pedagogy, funds of knowledge, and learning communities when they are enacted consistently as an ongoing and regular practice. Her students become agentic learners who thrive in ways we would wish for all students.
Preparation of Joint Faulting Data for the Local Calibration of AASHTO Pavement Mechanistic–Empirical Design in Louisiana

Louisiana utilized performance data from the pavement management system (PMS) to evaluate and calibrate the AASHTO Pavement Mechanistic–Empirical (ME) Design. Analysis of the PMS faulting data revealed that there were no records between 0 and 0.2 in. (5 mm); others over 0.2 in. (5 mm) appeared to be much greater than would be expected based on engineering experience. Therefore, several tasks were completed to validate the PMS faulting data and prepare them for local calibration. This paper presents details of the problem, approach, results, and lessons learned. First, faulting data from the PMS and Long-Term Pavement Performance database were analyzed to have an overview of the common range of joint faulting. To validate the PMS faulting data, 43 representative projects across Louisiana were selected for further analysis. Longitudinal profiles were collected with high-speed profilers and analyzed with the AASHTO R36 automated faulting measurement (AFM) algorithms. Manual measurements were also conducted during site visits. The comparison of faulting from different methods showed that the PMS data extremely overestimated faulting compared with the AFM estimation or the manual measurement. Results from the AFM algorithm were much closer (in the same magnitude) to the manual measurements. Therefore, faulting data from the AFM algorithm were used, and the faulting model was successfully calibrated. It is recommended to evaluate PMS faulting data carefully before applying them to calibrate the AASHTO Pavement ME Design software. Automated faulting measurement based on high-speed profiles is a feasible approach.
Entrepreneurial Humility and Learning from Serious Games

Serious games can create a fruitful environment for learning and development but participating in such games for learning in organizations imposes some challenges. The purpose of this article is to show having which element of entrepreneurial humility could play a significant role in relation with learning from serious games. In this study, 7 experts were chosen based on a questionnaire attempt to evaluate and prioritize entrepreneurial humility criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The respondents view ‘social openness’ as the most important criterion. The results of this study help organizations’ managers, decision-makers, and practitioners decide where to focus their attention during the implementation stage, in order to increase effectiveness of a talent development portfolio especially serious games.
Working Around Technologies—Invisible Professionalism?

This study discusses how professionalism and work ethics influence how health care professionals work around new technologies. When people avoid using technologies, they are not necessarily ceasing to engage in their work activities. The workaround strategies presented here are rather practical expressions of professionals’ active encounter with the complexity of work situations, and can therefore be important signs of professional ethical judgement. Drawing on science and technology studies and the concept of invisible work, the study discusses workaround situations that arise in health care work in Denmark. The aim and contribution of the study is twofold. First, it attempts to revitalise the discussion on technology workaround strategies as responsible professionalism. Second, it will direct attention to and contribute to an understanding of how the normativity embedded in technological development in the health care sector is central to the work of health care professionals.
PENGARUH KEPERCAYAAN, KEMUDAHAN DAN KUALITAS INFORMASI TERHADAP KEPUTUSAN PEMBELIAN ONLINE DI SITUS ONLINE FASHION ZALORA.CO.ID

Perkembangan teknologi di Indonesia semakin berkembang dapat dilihat dari bbanyaknya inovasi yang dibuat oleh masyarakat khususnya dalam memanfaatkan fasilitas internet. Internet memiliki peran peting dalam mendukung perkembangan e-commerce dalam melakukan transaksi secara online. Banyak nya toko belanja online yang bermunculan membuat masyarakat menjadi lebih sering melakukan keputusan pembelian terhadap suatu produk, dan belanja online sendiri dinilai jauh lebih mudah dan efektif. Dalam keputusan pembelian ada beberapa faktor yang mendukung yaitu Kepercayaan, Kemudahan dan Kualitas informasi dengan ketiga faktor tersebut seseorang mampu mengambil keputusan untuk membeli produk tersebut atau tidak. Penelitian ini merupakan penelitian deskriptif kausal dengan menggunakan metode pendekatan kuantitatif. Populasi pada penelitian ini adalah konsumen Zalora.co.id namun tidak diketahui secara pasti berapa jumlah pelanggan Zalora.co.i, sehingga teknik pengambilan sampel yang di gunakan adalah Nonprobability sampling dengan teknik analisis convinece sampling dengan sampel sebanyak 400 responden dengan menggunakan skala liker 5 poin. Metode pengumpulan data dilakukan dengan melakukan penyebaran kuesioner secara online. pengolahan data dilakukan dengan teknik analisis regresi berganda dengan uji hipotesis secara simultan dan parsial Hasil analisis menunjukan bahwa konsumen memiliki tanggapan cukup baik terhadap kepercayaan, kemudahan, kualitas informasi dan keputusan pembelian. Secara simultan Kepercayaan, kemudahaan dan kualitas informasi berpengaruh signifikan sebesar 70,6%. Secara parsial menunjukan bahwa kepercayaan, kemudahan dan kualitas informasi berpengaruh signifikan terhadap keputusan pembelian
3D shape instantiation for intra-operative navigation from a single 2D projection

Unlike traditional open surgery where surgeons can see the operation area clearly, in robot-assisted Minimally Invasive Surgery (MIS), a surgeon’s view of the region of interest is usually limited. Currently, 2D images from fluoroscopy, Magnetic Resonance Imaging (MRI), endoscopy or ultrasound are used for intra-operative guidance as real-time 3D volumetric acquisition is not always possible due to the acquisition speed or exposure constraints. 3D reconstruction, however, is key to navigation in complex in vivo geometries and can help resolve this issue. Novel 3D shape instantiation schemes are developed in this thesis, which can reconstruct the high-resolution 3D shape of a target from limited 2D views, especially a single 2D projection or slice. To achieve a complete and automatic 3D shape instantiation pipeline, segmentation schemes based on deep learning are also investigated. These include normalization schemes for training U-Nets and network architecture design of Atrous Convolutional Neural Networks (ACNNs). For U-Net normalization, four popular normalization methods are reviewed, then Instance-Layer Normalization (ILN) is proposed. It uses a sigmoid function to linearly weight the feature map after instance normalization and layer normalization, and cascades group normalization after the weighted feature map. Detailed validation results potentially demonstrate the practical advantages of the proposed ILN for effective and robust segmentation of different anatomies. For network architecture design in training Deep Convolutional Neural Networks (DCNNs), the newly proposed ACNN is compared to traditional U-Net where max-pooling and deconvolutional layers are essential. Only convolutional layers are used in the proposed ACNN with different atrous rates and it has been shown that the method is able to provide a fullycovered receptive field with a minimum number of atrous convolutional layers. ACNN enhances the robustness and generalizability of the analysis scheme by cascading multiple atrous blocks. Validation results have shown the proposed
Gaussian Alignments in Statistical Translation

Machine translation software has been under development almost since the birth of the electronic computer. Current state-of-the-art methods use statistical techniques to learn how to translate from one natural language to another from a corpus of handtranslated text. The success of these techniques comes from two factors: a simple statistical model and vast training data sets. The standard agenda for improving such models is to enable it to model greater complexity; however, it is a byword within the machine learning community that added complexity must be supported with more training data. Given that current models already require huge amounts of data, our agenda is instead to simplify current models before adding extensions. We present one such simplification, which results in fewer than 10% as many alignment model parameters and produces results competitive with the original model. An unexpected benefit of this technique is that it naturally gives a measure for how difficult it is to translate from one language to another given a data set. Next, we present one suggestion for adding complexity to model new behavior. Thesis Supervisor: Michael J. Collins Title: Assosciate Professor
regionalism in public management reforms: the case

Although comparative research on new public management reforms has identified variable pathways of change between countries, less is known about variations within countries where there has been significant political and administrative decentralisation to regional tiers of government. In this paper we address this concern, focusing on public hospital management reforms in the Italian Servizio Sanitario Nazionale (SSN) as an illustrative case. Drawing on a range of publicly available administrative data sources we find that there is a significant regional dimension, with more autonomous regional governments with right- wing political majorities being more likely to adopt corporate style management practices at hospital level.
EHD2 overexpression promotes tumorigenesis and metastasis in triple-negative breast cancer by regulating store-operated calcium entry

With nearly all cancer deaths a result of metastasis, elucidating novel pro-metastatic cellular adaptations could provide new therapeutic targets. Here, we show that overexpression of the EPS15-Homology Domain-containing 2 (EHD2) protein in a large subset of breast cancers (BCs), especially the triple-negative (TNBC) and HER2+ subtypes, correlates with shorter patient survival. The mRNAs for EHD2 and Caveolin-1/2, structural components of caveolae, show co-overexpression across breast tumors, predicting shorter survival in basal-like BC. EHD2 shRNA knockdown and CRISPR-Cas9 knockout of EHD2, together with mouse EHD2 rescue, in TNBC cell line models demonstrate a major positive role of EHD2 in promoting tumorigenesis and metastasis. Mechanistically, we link these roles of EHD2 to store-operated calcium entry (SOCE), with EHD2-dependent stabilization of plasma membrane caveolae ensuring high cell surface expression of the SOCE-linked calcium channel Orai1. The novel EHD2-SOCE oncogenic axis represents a potential therapeutic target in EHD2 and CAV1/2-overexpressing BC.
Ribosomal RNA operons define a central functional compartment in the Streptomyces chromosome

Streptomyces are prolific producers of specialized metabolites with applications in medicine and agriculture. These bacteria possess a large linear chromosome genetically compartmentalized: core genes are grouped in the central part, while terminal regions are populated by poorly conserved genes and define the chromosomal arms. In exponentially growing cells, chromosome conformation capture unveiled sharp boundaries formed by ribosomal RNA (rrn) operons that segment the chromosome into multiple domains. The first and last rrn operons delimit the highly expressed central compartment and the rather transcriptionally silent terminal compartments. Here we further explore the link between the genetic distribution of rrn operons and Streptomyces genomic compartmentalization. A large panel of genomes of species representative of the genus diversity revealed that rrn operons and core genes form a central skeleton, the former being identifiable from their core gene environment. We implemented a new nomenclature for Streptomyces genomes and trace their rrn-based evolutionary history. Remarkably, rrn operons are close to pericentric inversions. Moreover, the central compartment delimited by rrn operons has a very dense, nearly invariant core gene content. Finally, this compartment harbors genes with the highest expression levels, regardless of gene persistence and distance to the origin of replication. Our results highlight that rrn operons define the structural boundaries of a central functional compartment prone to transcription in Streptomyces.
MYB and ELF3 differentially modulate labor-inducing gene expression in myometrial cells

Spontaneous uterine contractions are initiated when smooth muscle cells (SMCs) within the uterine muscle, or myometrium, transition from a functionally dormant to an actively contractile phenotype at the end of the pregnancy period. We know that this process is accompanied by gestational time point-specific differences in the SMC transcriptome, which can be modulated by the activator protein 1 (AP-1), nuclear factor kappa beta (NF-κβ), estrogen receptor (ER), and progesterone receptor (PR) transcription factors. Less is known, however, about the additional proteins that might assist these factors in conferring the transcriptional changes observed at labor onset. Here, we present functional evidence for the roles of two proteins previously understudied in the SMC context—MYB and ELF3—which can contribute to the regulation of labor-driving gene transcription. We show that the MYB and ELF3 genes exhibit elevated transcript expression levels in mouse and human myometrial tissues during spontaneous term labor. The expression of both genes was also significantly increased in mouse myometrium during preterm labor induced by the progesterone antagonist mifepristone (RU486), but not during infection-simulating preterm labor induced by intrauterine infusion of lipopolysaccharide (LPS). Furthermore, both MYB and ELF3 proteins affect labor-driving gene promoter activity, although in surprisingly opposing ways: Gja1 and Fos promoter activation increases in the presence of MYB and decreases in the presence of ELF3. Collectively, our study adds to the current understanding of the transcription factor network that defines the transcriptomes of SMCs during late gestation and implicates two new players in the control of labor timing.
The role of histone acetyltransferases Gcn5 and Esa1 in recruiting the RSC complex and maintaining nucleosome-depleted regions genome-wide in Saccharomyces cerevisiae

Chromatin remodelers are essential for the maintenance of chromatin structure and gene regulation. In this study, we examined the role of histone acetyltransferases (HATs) Gcn5 and Esa1 in regulating RSC and histone occupancies and their effects on transcription genome-wide. We identified contrasting roles of HATs in modulating RSC occupancies in promoters and ORFs. In HAT mutants, RSC accumulated in nucleosome depleted regions (NDRs) with “fragile nucleosomes (FNs)” more than those with stable -1 nucleosomes. Moreover, the accumulation was more significant in the Esa1 mutant than in the Gcn5 mutant. However, RSC NDR accumulation was not observed in cells lacking H3 or H4 tails. Furthermore, we observed marked increases in histone occupancies in NDRs in the HAT mutants genome-wide. Overall, these data suggest that FNs use hypoacetylated tails to recruit RSC to NDRs, and subsequent acetylation of the tails promote histone eviction. In contrast to the promoters, RSC occupancies were significantly reduced in transcribed ORFs in the HAT mutants. Additionally, the HAT mutants showed reduced TBP and Pol II binding at promoters. Thus, our data implicate HATs and RSC in maintaining NDRs, regulating chromatin structure, and promoting transcription.
Updated Variant Curation Expert Panel Criteria and Pathogenicity Classifications for 251 Variants for RYR1-related Malignant Hyperthermia Susceptibility

The ClinGen malignant hyperthermia susceptibility (MHS) variant curation expert panel specified the ACMG/AMP criteria for RYR1-related MHS and a pilot analysis of 84 variants was published. We have now classified an additional 251 variants for RYR1-related MHS according to current ClinGen standards and updated the criteria where necessary. Criterion PS4 was modified such that individuals with multiple RYR1 variants classified as pathogenic (P), likely pathogenic (LP) or variant of uncertain significance (VUS) were not considered as providing evidence for pathogenicity. Critera PS1 and PM5 were revised to consider LP variants at the same amino acid residue as providing evidence for pathogenicity at reduced strength. Finally, PM1 was revised such that if PS1 or PM5 are used PM1, if applicable, should be downgraded to supporting. Of the 251 RYR1 variants, 42 were classified as P/LP, 16 as B/LB, and 193 as VUS. The primary driver of 176 VUS classifications was insufficient evidence supporting pathogenicity, rather than evidence against pathogenicity. Functional data supporting PS3/BS3 was identified for only 13 variants. Based on the posterior probabilities of pathogenicity and variant frequencies in gnomAD, we estimated the prevalence of individuals with RYR1-related MHS pathogenic variants to be between 1/300 and 1/1,075, considerably higher than current estimates. We have updated ACMG/AMP criteria for RYR1-related MHS and classified 251 variants. We suggest that prioritization of functional studies is needed to resolve the large number of VUS classifications and allow for appropriate risk assessment. RYR1-related MHS pathogenic variants are likely to be more common than currently appreciated.
Time-kill kinetics reveal heterogeneous tolerance to disinfectants

Disinfection is an important strategy to limit the spread of infections. Failure of disinfection may facilitate evolution of resistance against disinfectants and antibiotics through the processes of cross-resistance and co-resistance. The best possible outcome of disinfection minimizes the number of surviving bacteria and the chance for resistance evolution. Resistance describes the ability to grow in previously inhibitory concentrations of an antimicrobial, whereas tolerance is associated with enhanced survival of lethal doses. Individual bacteria from the same population can display considerable heterogeneity in their ability to survive treatment (i.e. tolerance) with antimicrobials, which can result in unexpected treatment failure. Here, we investigated how phenotypic heterogeneity affects the ability of E. coli to survive treatment with six different substances commonly used as active substances in disinfectants, preservatives and antiseptics. A mathematical model which assumes that phenotypic heterogeneity underlies the observed disinfection kinetics was used to infer whether time-kill kinetics were caused by a tolerant subpopulation. The analysis identified bimodal kill kinetics for benzalkonium chloride (BAC), didecyldimethylammonium chloride (DDAC), and isopropanol (Iso). In contrast, kill kinetics by chlorhexidine (CHX), glutaraldehyde (GTA), and hydrogen peroxide (H2O2) were best explained by unimodal kill kinetics underpinned by a broad distribution of tolerance times for CHX as opposed to a narrow distribution of tolerance times for GTA and H2O2. These findings have implications for the risk of disinfection failure, with potential consequences for the evolution of antimicrobial resistance and tolerance.