Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometric changes in the nucleoids of Deinococcus radiodurans reveal involvement of new proteins in recovery from ionizing radiation

The extremophile Deinococcus radiodurans maintains a highly-organized and condensed nucleoid as its default state, possibly contributing to high tolerance of ionizing radiation (IR). Previous studies of the D. radiodurans nucleoid were limited by reliance on manual image annotation and qualitative metrics. Here, we introduce a high-throughput approach to quantify the geometric properties of cells and nucleoids, using confocal microscopy, digital reconstructions of cells, and computational modeling. We utilize this novel approach to investigate the dynamic process of nucleoid condensation in response to IR stress. Our quantitative analysis reveals that at the population level, exposure to IR induced nucleoid compaction and decreased size of D. radiodurans cells. Morphological analysis and clustering identified six distinct sub-populations across all tested experimental conditions. Results indicate that exposure to IR induces fractional redistributions of cells across sub-populations to exhibit morphologies that associate with greater nucleoid condensation, and decreased abundance of sub-populations associated with cell division. Nucleoid associated proteins (NAPs) may link nucleoid compaction and stress tolerance, but their roles in regulating compaction in D. radiodurans is unknown. Imaging of genomic mutants of known and suspected NAPs that contribute to nucleoid condensation found that deletion of nucleic acid binding proteins, not previously described as NAPs, can remodel the nucleoid by driving condensation or decondensation in the absence of stress and that IR increases the abundance of these morphological states. Thus, our integrated analysis introduces a new methodology for studying environmental influences on bacterial nucleoids and provides an opportunity to further investigate potential regulators of nucleoid condensation. Importance D. radiodurans, an extremophile known for its stress tolerance, constitutively maintains a highly-condensed nucleoid. Qualitative studies have described nucleoid behavior under a variety of conditions. However, a lack of quantitative data regarding nucleoid organization and dynamics have limited our understanding of regulatory mechanisms controlling nucleoid organization in D. radiodurans. Here, we introduce a quantitative approach that enables high-throughput quantitative measurements of subcellular spatial characteristics in bacterial cells. Applying this to wild-type or single-protein-deficient populations of D. radiodurans subjected to ionizing radiation, we identified significant stress-responsive changes in cell shape, nucleoid organization, and morphology. These findings highlight this methodology’s adaptability and capacity for quantitatively analyzing the cellular response to stressors for screening cellular proteins involved in bacterial nucleoid organization.
ComboPath: An ML system for predicting drug combination effects with superior model specification

Drug combinations have been shown to be an effective strategy for cancer therapy, but identifying beneficial combinations through experiments is labor-intensive and expensive [Mokhtari et al., 2017]. Machine learning (ML) systems that can propose novel and effective drug combinations have the potential to dramatically improve the efficiency of combinatoric drug design. However, the biophysical parameters of drug combinations are degenerate, making it difficult to identify the ground truth of drug interactions even given experimental data of the highest quality available. Existing ML models are highly underspecified to meet this challenge, leaving them vulnerable to producing parameters that are not biophysically realistic and harming generalization. We have developed a new ML model, “ComboPath”, aimed at a novel ML task: to predict interpretable cellular dose response surface of a two-drug combination based on each drugs’ interactions with their known protein targets. ComboPath incorporates a biophysically-motivated intermediate parameterization with prior information used to improve model specification. This is the first ML model to nominate beneficial drug combinations while simultaneously reconstructing the dose response surface, providing insight on both the potential of a drug combination and its optimal dosing for therapeutic development. We show that our models were able to accurately reconstruct 2D dose response surfaces across held out combination samples from the largest available combinatoric screening dataset while substantially improving model specification for key biophysical parameters.
Strategy for unlimited cycles of scarless oligonucleotide directed gene editing in Chlamydomonas reinhardtii

CRISPR/Cas9 gene editing in the model green alga Chlamydomonas reinhardtii relies on the use of selective marker genes to enrich for non-selectable target mutations. This becomes challenging when many sequential modifications are required in a single cell line, as useful markers are limited. Here we demonstrate a cyclical selection process which only requires a single marker gene to identify an almost infinite sequential series of CRISPR-based target gene modifications. The NIA1 (Nit1, NR; nitrate reductase) gene was this selectable marker. In the forward stage of the cycle, a stop codon was engineered into the NIA1 gene at the CRISPR target location. Cells retaining the wild type NIA1 gene were killed by chlorate, while NIA1 knockout mutants survived. In the reverse phase of the cycle, the stop codon engineered into the NIA1 gene during the forward phase was edited back to the wild type sequence. Using nitrate as the sole nitrogen source, here only the reverted wild type cells survived. By using CRISPR to specifically deactivate and reactivate the NIA1 gene, a marker system was established that flipped back and forth between chlorate- and auxotrophic (nitrate) based selection. This provided a scarless cyclical marker system that enabled an indefinite series of CRISPR edits in other, non-selectable genes. Here, we demonstrate that this ‘Sequential CRISPR via Recycling Endogenous Auxotrophic Markers (SCREAM)’ technology enables an essentially limitless series of genetic modifications to be introduced to a single cell lineage of C. reinhardtii in a fast and efficient manner to complete complex genetic engineering.
Elucidating Resistance Mechanisms in Staphylococcus epidermidis: A High-Performing MALDI-TOF MS-Based Proteomic Approach for Predictive Modeling

The emergence of Staphylococcus epidermidis as a significant nosocomial pathogen necessitates advancements in more efficient antimicrobial resistance (AMR) profiling. However, existing culture-based antimicrobial susceptibility testing (AST) methods can take up to 96 hours, while holistic PCR assays can cost thousands of dollars. This study combines machine learning with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to develop predictive models for various antibiotics using a comprehensive dataset containing thousands of S. epidermidis isolates. Optimized machine learning models utilized feature selection and achieved high AUROC scores ranging from 0.80 to 0.95 while maintaining AUPRC scores up to 0.96 for balanced datasets. Shapley Additive exPlanations (SHAP) were employed to analyze relevant features and assess the significance of corresponding protein biomarkers while also verifying that predictive power was derived from the detection of proteins rather than noise. AMR prediction models were validated externally to evaluate model performance outside the original data collection site. The findings in this study demonstrate that combining machine learning with AMR profiling yields significant and relevant results, indicating that such an approach is a promising solution for rapid and cost-effective treatments for nosocomial infections. Models created to predict AMR can also aid in biomarker discovery. The workflow used in the present study is potentially applicable to other microbial pathogens in the future.
It’s all in the timing: Delayed feedback in autism may weaken predictive mechanisms during contour integration

Humans rely on predictive mechanisms during visual processing to efficiently resolve incomplete or ambiguous sensory signals. While initial low-level sensory data are conveyed by feedforward connections, feedback connections are believed to shape sensory processing through conveyance of statistical predictions based on prior exposure to stimulus configurations. Individuals with autism spectrum disorder (ASD) show biases in stimulus processing toward parts rather than wholes, suggesting their sensory processing may be less shaped by statistical predictions acquired through prior exposure to global stimulus properties. Investigations of illusory contour (IC) processing in neurotypical (NT) adults have established a well-tested marker of contour integration characterized by a robust modulation of the visually evoked potential (VEP) – the IC-effect – that occurs over lateral occipital scalp during the timeframe of the N1 component. Converging evidence strongly supports the notion that this IC-effect indexes a signal with significant feedback contributions. Using high-density VEPs, we compared the IC-effect in 6–17-year-old children with ASD (n=32) or NT development (n=53). Both groups of children generated an IC-effect that was equivalent in amplitude. However, the IC-effect notably onset 21ms later in ASD, even though timing of initial VEP afference was identical across groups. This suggests that feedforward information predominated during perceptual processing for 15% longer in ASD compared to NT children. This delay in the feedback dependent IC-effect, in the context of known developmental differences between feedforward and feedback fibers, suggests a potential pathophysiological mechanism of visual processing in ASD, whereby ongoing stimulus processing is less shaped by statistical prediction mechanisms. SIGNIFICANCE STATEMENT Children with autism often present with an atypical visual perceptual style that emphasizes parts or details over the whole. Using electroencephalography (EEG), this study identifies delays in the visual feedback from higher order sensory brain areas to primary sensory regions. Because this type of visual feedback is thought to carry information about prior sensory experiences, individuals with autism may have difficulty efficiently using prior experience and predictions to help make sense of incoming new visual information. This provides empirical neural evidence to support theories of disrupted sensory perception mechanisms in autism.
A Comprehensive Approach to Characterize Navigation Instruments for Magnetic Guidance in Biological Systems

The non-invasive spatiotemporal control of cellular functions, organization of tissues, and even the behavior of small animals has become paramount for advanced therapies. As magnetic fields do not interact with biological matter, their application is not only suitable for in vitro experiments but also for in vivo applications, even in deep tissues. Particularly, the remote manipulation of paramagnetic entities through magnetic instruments has emerged as a promising approach across various biological contexts. Despite similarities in basic experimental concepts, variations in the properties and descriptions of those magnetic instruments among the authors and studies resulted in a lack of reproducibility and comparability. Therefore, this article addresses the question of how to standardize the characterization of magnetic instruments. Our emphasis lies on the ability of magnetic systems to control the movement of paramagnetic objects such as ferro- or superparamagnetic particles, within organisms. This movement is achieved by exerting a force on magnetic particles by exposing them to a locally varying magnetic field. While it is well-known that the exerted force depends on the spatial variation (i.e. the gradient) of the magnetic field, the magnitude of the field is equally important. However, this second factor is often neglected in the literature. Therefore, we conduct a comprehensive analysis and discussion of both factors. Furthermore, we propose a novel descriptor, termed"effective gradient", which combines both dependencies. To illustrate, we characterize different magnet systems by calculating and comparing the different quantities and relating them to two experiments with different superparamagnetic nanoparticles.
Human induced pluripotent stem cell-derived cardiomyocytes to study inflammation-induced diastolic dysfunction

Heart failure with preserved ejection fraction (HFpEF) is commonly found in persons living with HIV (PLWH) even when antiretroviral therapy (ART) suppresses HIV viremia. However, studying this condition has been challenging because an appropriate animal model is not available. In this paper, we study the relaxation function of human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CMs) in culture to simulate HFpEF and to assess whether various drugs have an effect. We show that treatment of hiPSC-CMs with inflammatory cytokines (such as interferon-γ or TNF-α) impair their relaxation and that SGLT2 inhibitors, clinically proven as effective for HFpEF, reverse this effect. Additionally, treatment with mitochondrial antioxidants (like mito-Tempo) and certain antiretrovirals resulted in the reversal of the effects of these cytokines on cardiomyocyte relaxation. Finally, incubation of hiPSC-CMs with serum from HIV patients with and without diastolic dysfunction (DD) did not alter their relaxation, indicating that short exposure to the serum of these patients is not sufficient to induce DD in vitro. Together, our results indicate that hiPSC-CMs can be used as a model to study molecular mechanisms of inflammation-mediated abnormal cardiomyocyte relaxation and screen for potential new interventions.
Assessing the Student's Attitudes Towards Sustainable Agriculture

Students are the agriculturist of tomorrow; therefore policies aimed at developing sustainable agriculture should address the needs of this group. To discover their attitudes towards sustainable agriculture, a survey among 100 agricultural students was conducted. Questionnaire was used to examine student attitudes regarding sustainable agriculture. Finding is shown that students' attitudes towards sustainable agriculture are positive, especially in cognitive aspect. In conclusion, to enhance student attitudes towards sustainable behavior in agriculture context, it is important that curriculum develops for familiar student with sustainable agriculture practices and concepts such as: integrated pest management, low-input agriculture, rotational grazing, ecological agriculture, waste management, organic farming and alternative agriculture as to meet the needs of students preparing to enter the work force of the 21st century food and fiber system.
2023 Asymptotic soliton-like and asymptotic peakon-like solutions of the modiﬁed Camassa-Holm equation with variable coeﬃcients and singular perturbation

The paper deals with the construction of the asymptotic soliton-like and the asymptotic peakon-like solutions to the modiﬁed Camassa-Holm equation with variable coeﬃ-cicents and a singular perturbation. This equation is a generalization of the well known modiﬁed Camassa-Holm equation which is integrable system and in addition to the soliton solutions the equation has the peakon solutions. The novelty of the ideas of this paper lies in the development of a technique for constructing asymptotic peakon-like solutions. In the paper a general scheme of ﬁnding asymptotic approximation of any order is presented and accuracy of the asymptotic approximation is found. The obtained results are illustrated by examples both the soliton-like and the peakon-like solutions. For the examples the main and the ﬁrst terms of the soliton-like and peakon-like solutions are found. Moreover, for diﬀerent values of a small parameter the graphs that demonstrate kind of the solutions are presented. The considered examples demonstrate that for an adequate description of the wave process it is enough obtain the main and the ﬁrst terms of correspond asymptotic solutions. The results also conﬁrm that the proposed technique can be used for constructing asymptotic wave-like solutions of other equations.
Sexually dimorphic behavioral responses to prenatal dioxin Sexually dimorphic behavioral responses to prenatal dioxin exposure exposure

11 and another schedule requiring a pause of at least 10 sec between responses (DRL 10-sec). TCDD evoked a sexually dimorphic response pattern. Generally, TCDD-exposed males responded at lower rates than control males. In contrast, exposed females responded at higher rates than controls. Each response measure from the mult-FR DRL schedule yielded a male–female difference score. We used the differences in response rate to calculate benchmark doses based on the relative displacement from modeled zero-dose performance of the effective dose at 1% (ED 01 ) and 10% (ED 10 ), as determined by a second-order polynomial fit to the dose–effect function. For the male–female difference in FR rate of responding, the mean ED 10 was 2.77 ng/kg with a 95% lower bound of 1.81 ng/kg. The corresponding ED 01 was 0.27 ng/kg with a 95% lower bound of 0.18 ng/kg. For the male–female difference in DRL rate, the mean ED 10 was 2.97 ng/kg with a 95% lower bound of 2.02 ng/kg. The corresponding ED 01 was 0.30 ng/kg with a 95% lower bound of 0.20 ng/kg. These values fall close to, but below, current estimates of human body burdens of 13 ng/kg, based on TCDD toxic equivalents.
BRAF Genetic Testing to Select Melanoma or Glioma Patients for Targeted Therapy Effective : August 1 , 2018

PLEASE NOTE: Contracts exclude from coverage, among other things, services or procedures that are considered investigational or cosmetic. Providers may bill members for services or procedures that are considered investigational or cosmetic. Providers are encouraged to inform members before rendering such services that the members are likely to be financially responsible for the cost of these services.
Genetic analysis of the IBM2Syn10-DH maize population for response to low and high nitrogen input

48 Introduction 49 Materials & Methods 52 Plant material 52 Experimental design and field management 52 Phenotypic measurements 54 Statistical analysis 55 QTL analysis 56 Results 58 Phenotypic results 58 Variance components 60 Phenotypic correlation 60 Genotypic results 62 Discussion 66 Phenotypic analysis 66 Genotypic analysis 69 References 75 Figures 81 Tables 94 Appendix 117 CHAPTER 4: GENERAL CONCLUSIONS 125 References 128
A CLINICAL SCORE FOR DIAGNOSIS OF PROBABLE DENGUE IN CHILDREN IN AN ENDEMIC AREA, THAILAND

Dengue is one of the most important mosquito-borne diseases in tropical and subtropical regions of the world. Laboratory diagnosis is often expensive or unavailable in some endemic areas, making clinical diagnosis important for case management. In order to develop and validate the Mahidol dengue clinical score (MDCS), a predictive of dengue among children who present with acute febrile illness without localizing signs in a dengue endemic area, data on clinical and laboratory findings in a cohort study of children with acute febrile illness without localizing signs identified prospectively were analyzed and compared between those with and without laboratory-confirmed dengue. MDCS was then developed using independent clinical risk factors associated with dengue. The validity of MDCS w as further evaluated by comparison to WHO dengue diagnostic criteria. In children who had acute febrile illness without localizing signs, MDCS-A version comprising of mucosal bleeding, facial flush, absence of rhinorrhea, posi - tive tourniquet test, leucopenia, and thrombocytopenia had a diagnostic value comparable to WHO 1997 criteria, while MDCS-B version that excludes data on leukopenia and thrombocytopenia, making it more feasible in laboratory-limited settings, had a diagnostic value comparable to WHO 2009 criteria. Thus, MDCS can be used as a screening diagnostic tool for dengue infection in children in a dengue endemic area.
Exploiting IFTTT and Usage Control Obligations for Smart Home Security and Management

In this paper we present an application of the Usage Control paradigm to a Smart Home infrastructure, based on a model extension and structured use of obligations. In the proposed extended model obligations are exploited to enforce two diﬀer-ent access revocation time, namely revoke and suspend. This increases the policy expressiveness and enable to optimize the resource usage. Furthermore, obligations are exploited to send commands via IFTTT to diﬀerent interconnected Smart Home devices, to impose safety-relevant behaviors, or to act on policy attributes to implement a self-healing paradigm for revoked sessions. The paper is motivated by a parental control use case where deep learning is used in combination with Usage Control to regulate dynamically viewing rights of a Smart TV and interactions with interconnected devices. Accuracy and performance experiments show the eﬀectiveness and feasibility of the proposed work.
Treatment of Comorbid Mental Disorder and Sexual Offending: A Critical Analysis

Aim/Background: Elevated rates of serious mental illness (schizophrenia, bipolar disorder, major depression) are found among sexual offenders. However, information about effective treatment to prevent recidivism among these mentally disordered sex offenders is sparse. Methods: Therefore, a critical analysis of extant literature was completed. Results: Studies often conflated serious mental illness with intellectually disability, personality disorders, and substance use disorders, making findings difficult to interpret. Conclusion: The literature indicates that when treating mentally disordered sexual offenders, the symptoms of mental illness should first be controlled, and comorbid substance use disorders treated. Treatment in a group setting using a CBT-based model was most commonly reported, with only some individual therapy described. Staff support to prevent burnout is also recommended.
The IOC international harmful algal bloom program history and science impacts

Harmful algal blooms (HABs) have become an important subdiscipline within oceanography. Heightened attention to this topic as well as significant research advances reflect the global nature of the problem and the development of strong national and international programs for HAB research and management. The planning, communication, coordination, and capacity-building activities of the Intergovernmental Oceanographic Commission (IOC) have been a key factor in this growth. Here, we highlight selected advances in science and management capacity for HABs and document the impressive growth of the field in the context of activities supported directly or indirectly by IOC. As we look to the future, the field has significant momentum and stability. Nevertheless, it will require scientific guidance and coordination going forward. With an appropriate commitment of resources from member states, the IOC HAB program can continue to be a major factor in the sustained growth of this important scientific discipline and its delivery of improved observation and management systems.