bluuebunny/crossref_metadata_2025_split huggingface dataset:
Description of Neoseiulus hexaporus sp. nov. and a redescription of Neoseiulus mumai (Acari: Mesostigmata: Phytoseiidae) from Florida citrus groves
Authors: Döker Ismail , Demard Emilie P , Bolton Samuel J , Qureshi Jawwad A 
Published: June 2023

Abstract
Predatory mites are effective natural enemies of small arthropods, including pest mites and insects, which provide biological control of several crop pests worldwide. The family Phytoseiidae (Acari: Mesostigmata) is a diverse group of predators found in cultivated crops and other habitats containing natural vegetation. Although some phytoseiid species are commercialized and widely used in biological control programs, the determination of natural populations and identification of the species is a vital first step in understanding their interactions with the crop, environment, and pests. The citrus crop is a diverse agroecosystem colonized by a variety of pests including mites and warrants an understanding of the complex of predators. We collected predatory mites from multiple citrus groves in Florida, to find and identify species for biological control in citrus crops. The examination of the specimens involved the use of Olympus CX-41 microscope, and drawings were prepared with the help of the attached camera Lucida. Any needed corrections were made using tracing paper, rapidograph pen, and Adobe Photoshop version CS6. Neoseiulus hexaporussp. nov. is described and illustrated as a new species based on its distinct morphology compared with previously described species in paspalivorus group. We also provide a complementary redescription of Neoseiulus mumai (Denmark), including an important diagnostic character of leg chaetotaxy which had led to the description of a new species, Neoseiulus kikuyu Ma, Fan & Zhang. We also provide new illustrations of N. mumai to facilitate its diagnosis.
A dilemma for Nicolausian discounting
Authors: Cibinel Pietro 
Published: June 2023

Abstract
Orthodox decision theory is fanatical in the way it treats small probabilities of enormous value, if unbounded utility functions are allowed. Some have suggested a fix, Nicolausian discounting, according to which outcomes with small enough probabilities should be ignored when making decisions. However, there are lotteries involving only small-probability outcomes, none of which should intuitively be ignored. So the Nicolausian discounter needs a procedure for distinguishing the problematic cases of small-probability outcomes from the unproblematic ones. In this paper, I present a dilemma for Nicolausian discounting: the view must be coupled either with a procedure that delivers fanatical verdicts of its own, as bad as those of orthodox decision theory, or with one that entails intransitive cyclic preferences.
Cognitive Reserve Moderates the Effects of Fatigue and Depressive Symptoms in Multiple Sclerosis
Authors: Bradson Megan L , Cadden Margaret H , Riegler Kaitlin E , Thomas Garrett A , Randolph John J , Arnett Peter A 
Published: June 2023

Abstract
To investigate cognitive reserve as a possible moderator in the relationship between fatigue and depressive symptoms in persons with multiple sclerosis (PwMS). Fifty-three PwMS (37 female; mean age, 52.66; mean education, 14.81) completed comprehensive neuropsychological testing and psychosocial questionnaires assessing the perceived effects of fatigue (Fatigue Impact Scale) and depressive symptoms (Beck Depression Inventory-Fast Screen). Cognitive reserve (CR) was operationalized as Fixed CR and Malleable CR. Fixed CR was quantified as the standardized mean of years of education and a vocabulary-based estimate of premorbid intelligence. Malleable CR was quantified as the standardized mean of cognitive exertion, exercise, and socializing items from the Cognitive Health Questionnaire. Regressions on depressive symptoms examining fatigue, both conceptualizations of CR, and their interactions were explored. A Bonferroni correction was used; results were considered significant at an alpha level of p &lt; .01. The interactions between fatigue and both conceptualizations of CR were significant, p = .005 (Fixed CR); p = .004 (Malleable CR). Simple effects tests revealed that fatigue only predicted depressive symptoms in PwMS with low Fixed CR or low Malleable CR (p’s &lt; .001), and not in those with high Fixed or high Malleable CR (p &gt; .01). Cognitive reserve moderated the relationship between fatigue and depressive symptoms in PwMS. Specifically, fatigue does not appear to influence depression in PwMS with high cognitive reserve. Having higher cognitive reserve (either Fixed or Malleable) may reduce the likelihood that fatigue will lead to depressive symptoms in MS.
Moral Gaslighting
Authors: Manne Kate 
Published: June 2023

Abstract
Philosophers have turned their attention to gaslighting only recently, and have made considerable progress in analysing its characteristic aims and harms. I am less convinced, however, that we have fully understood its nature. I will argue in this paper that philosophers and others interested in the phenomenon have largely overlooked a phenomenon I call moral gaslighting, in which someone is made to feel morally defective—for example, cruelly unforgiving or overly suspicious—for harbouring some mental state to which she is entitled. If I am right about this possibility, and that it deserves to be called gaslighting, then gaslighting is a far more prevalent and everyday phenomenon than has previously been credited. And it can also be a purely structural phenomenon, as well as an interpersonal one, which remains a controversial possibility in the current literature.
Art as a Shelter from Science
Authors: Nguyen C Thi 
Published: June 2023

Abstract
In our life with science, we trust experts; we form judgements by inference from past evidence. We conduct ourselves very differently in the aesthetic domain. We avoid deferring to aesthetic experts. We form our judgements through direct perception of particulars rather than through inference. Why the difference? I suggest that we avoid aesthetic testimony and aesthetic inference, not because they’re unusable, but because we have adopted social norms to avoid them. Aesthetic appreciation turns out to be something like a game. We have laid down certain rules and restrictions in order to shape a kind of activity we cherish. And aesthetic properties turn out to be a kind of social construct. Much like the goal of a game, they are constituted in part by our obedience to certain rules. The norms of aesthetic life are different from those of science because our purposes are different. We engage in science to get the right answers; we engage in aesthetic appreciation to be absorbed in the activity of the sensuous perception of particulars. Our aesthetic practices are a constructed shelter from science; they restore to us a small domain where we may once again engage in our own sensuous perception of particulars.
Family and Marriage: Institutions and the Need for Social Goods
Authors: Munoz-Dardé Véronique , Martin M G F 
Published: June 2023

Abstract
Institutions, if unjust, ought to be reformed or even abolished. This radical Rawlsian thought leads to the question of whether the family ought to be abolished, given its negative impact on the very possibility of delivering equality of life chances. In this article, we address questions regarding the justice of the family, and of marriage, and reflect on rights, equality, and the provision of social goods by institutions. There is a temptation to justify our social institutions in terms which highlight their universal accessibility and benefits. But we may best understand the claim of some of our most important institutions where we recognize that they are forms of social good which may legitimately benefit some without having to benefit all. Their abolition is unjustified where there is sufficient value in them given our collective needs that it is unreasonable for some to refuse the means to maintain and promote these goods.
Attitudes and the Normativity of Fittingness
Authors: McHugh Conor 
Published: June 2023

Abstract
What is the structure of normative reality? According to X First, normativity has a monistic foundationalist structure: there is a unique normatively basic property in terms of which all the other normative properties are analysed. The main aim of this paper is to defend the view that fittingness—the property that an attitude has when it gets things right with respect to its object, as when you admire the admirable or desire the desirable—is first, or perhaps joint first. I will focus in particular on the questions whether and why fittingness is normative.
MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis
Authors: Cai Guoxin , Zhao Wenyi , Zhou Zhan , Gu Xun 
Published: June 2023

Abstract
A phenotype may be associated with multiple genes that interact with each other in the form of a gene module or network. How to identify these relationships is one important aspect of comparative transcriptomics. However, it is still a challenge to align gene modules associated with different phenotypes. Although several studies attempted to address this issue in different aspects, a general framework is still needed. In this study, we introduce Module Alignment of TranscripTomE (MATTE), a novel approach to analyze transcriptomics data and identify differences in a modular manner. MATTE assumes that gene interactions modulate a phenotype and models phenotype differences as gene location changes. Specifically, we first represented genes by a relative differential expression to reduce the influence of noise in omics data. Meanwhile, clustering and aligning are combined to depict gene differences in a modular way robustly. The results show that MATTE outperformed state-of-the-art methods in identifying differentially expressed genes under noise in gene expression. In particular, MATTE could also deal with single-cell ribonucleic acid-seq data to extract the best cell-type marker genes compared to other methods. Additionally, we demonstrate how MATTE supports the discovery of biologically significant genes and modules, and facilitates downstream analyses to gain insight into breast cancer. The source code of MATTE and case analysis are available at https://github.com/zjupgx/MATTE.
A Bayesian approach to estimate MHC-peptide binding threshold
Authors: Liu Ran , Hu Ye-Fan , Huang Jian-Dong , Fan Xiaodan 
Published: June 2023

AbstractMajor histocompatibility complex (MHC)-peptide binding is a critical step in enabling a peptide to serve as an antigen for T-cell recognition. Accurate prediction of this binding can facilitate various applications in immunotherapy. While many existing methods offer good predictive power for the binding affinity of a peptide to a specific MHC, few models attempt to infer the binding threshold that distinguishes binding sequences. These models often rely on experience-based ad hoc criteria, such as 500 or 1000nM. However, different MHCs may have different binding thresholds. As such, there is a need for an automatic, data-driven method to determine an accurate binding threshold. In this study, we proposed a Bayesian model that jointly infers core locations (binding sites), the binding affinity and the binding threshold. Our model provided the posterior distribution of the binding threshold, enabling accurate determination of an appropriate threshold for each MHC. To evaluate the performance of our method under different scenarios, we conducted simulation studies with varying dominant levels of motif distributions and proportions of random sequences. These simulation studies showed desirable estimation accuracy and robustness of our model. Additionally, when applied to real data, our results outperformed commonly used thresholds.
TIMER is a Siamese neural network-based framework for identifying both general and species-specific bacterial promoters
Authors: Zhu Yan , Li Fuyi , Guo Xudong , Wang Xiaoyu , Coin Lachlan J M , Webb Geoffrey I , Song Jiangning , Jia Cangzhi 
Published: June 2023

Abstract

Background
Promoters are DNA regions that initiate the transcription of specific genes near the transcription start sites. In bacteria, promoters are recognized by RNA polymerases and associated sigma factors. Effective promoter recognition is essential for synthesizing the gene-encoded products by bacteria to grow and adapt to different environmental conditions. A variety of machine learning-based predictors for bacterial promoters have been developed; however, most of them were designed specifically for a particular species. To date, only a few predictors are available for identifying general bacterial promoters with limited predictive performance.

Results
In this study, we developed TIMER, a Siamese neural network-based approach for identifying both general and species-specific bacterial promoters. Specifically, TIMER uses DNA sequences as the input and employs three Siamese neural networks with the attention layers to train and optimize the models for a total of 13 species-specific and general bacterial promoters. Extensive 10-fold cross-validation and independent tests demonstrated that TIMER achieves a competitive performance and outperforms several existing methods on both general and species-specific promoter prediction. As an implementation of the proposed method, the web server of TIMER is publicly accessible at http://web.unimelb-bioinfortools.cloud.edu.au/TIMER/.
Machine learning modeling of RNA structures: methods, challenges and future perspectives
Authors: Wu Kevin E , Zou James Y , Chang Howard 
Published: June 2023

Abstract
The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules’ secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.
MTM: a multi-task learning framework to predict individualized tissue gene expression profiles
Authors: He Guangyi , Chen Maiyue , Bian Yingnan , Yang Ence 
Published: June 2023

Abstract

Motivation
Transcriptional profiles of diverse tissues provide significant insights in both fundamental and translational researches, while transcriptome information is not always available for tissues that require invasive biopsies. Alternatively, predicting tissue expression profiles from more accessible “surrogate” samples, especially blood transcriptome, has become a promising strategy when invasive procedures are not practical. However, existing approaches ignore tissue-shared intrinsic relevance, inevitably limiting predictive performance.

Results
We propose a unified deep learning-based multi-task learning framework, multi-tissue transcriptome mapping (MTM), enabling the prediction of individualized expression profiles from any available tissue of an individual. By jointly leveraging individualized cross-tissue information from reference samples through multi-task learning, MTM achieves superior sample-level and gene-level performance on unseen individuals. With the high prediction accuracy and the ability to preserve individualized biological variations, MTM could facilitate both fundamental and clinical biomedical research.

Availability and implementation
MTM’s code and documentation are available upon publication on GitHub (https://github.com/yangence/MTM).
Reconstructor: a COBRApy compatible tool for automated genome-scale metabolic network reconstruction with parsimonious flux-based gap-filling
Authors: Jenior Matthew L , Glass Emma M , Papin Jason A 
Published: June 2023

Abstract

Motivation
Genome-scale metabolic network reconstructions (GENREs) are valuable for understanding cellular metabolism in silico. Several tools exist for automatic GENRE generation. However, these tools frequently (i) do not readily integrate with some of the widely-used suites of packaged methods available for network analysis, (ii) lack effective network curation tools, (iii) are not sufficiently user-friendly, and (iv) often produce low-quality draft reconstructions.

Results
Here, we present Reconstructor, a user-friendly, COBRApy-compatible tool that produces high-quality draft reconstructions with reaction and metabolite naming conventions that are consistent with the ModelSEED biochemistry database and includes a gap-filling technique based on the principles of parsimony. Reconstructor can generate SBML GENREs from three input types: annotated protein .fasta sequences (Type 1 input), a BLASTp output (Type 2), or an existing SBML GENRE that can be further gap-filled (Type 3). While Reconstructor can be used to create GENREs of any species, we demonstrate the utility of Reconstructor with bacterial reconstructions. We demonstrate how Reconstructor readily generates high-quality GENRES that capture strain, species, and higher taxonomic differences in functional metabolism of bacteria and are useful for further biological discovery.

Availability and implementation
The Reconstructor Python package is freely available for download. Complete installation and usage instructions and benchmarking data are available at http://github.com/emmamglass/reconstructor.
Generation of a novel Stra8-driven Cre recombinase strain for use in pre-meiotic germ cells in mice
Authors: Ahmed Avery A , Salas Ernesto , Lanza Denise G , Heaney Jason D , Pangas Stephanie A 
Published: June 2023

Abstract
The development of oocytes occurs over a broad time frame, starting at the earliest stages of embryogenesis and continuing into adulthood. Conditional knockout technologies such as the Cre/loxP recombination system are useful for analyzing oocyte development at specific stages, but not every time frame has appropriate Cre drivers, for instance, during oocyte meiotic initiation through early prophase I in the embryo. Here, we generated a novel knockin mouse line that produces a bicistronic transcript from the endogenous Stra8 locus that includes a “self-cleaving” 2A peptide upstream of cre. This allows for high efficiency cleavage and production of both proteins individually and results in expression of cre in both male and female gonads at the biologically relevant stage. Fluorescent reporter analysis confirms that this line recapitulates endogenous Stra8 expression in both sexes and does not affect fertility of heterozygous nor homozygous mice. This line, named Stra8P2Acre, adds to the repertoire of germ-cell specific cre driver lines and, importantly, allows for deletion of target genes during key embryonic oocyte developmental stages, including early events in meiosis.
Summary Sentence Generation of a novel cre recombinase knockin to the Stra8 locus allows production of Stra8 and cre without affecting fertility.
Hyperthermic Intrathoracic Chemotherapy (HITOC) Improves Malignant Pleural Mesothelioma Control Through a Tumor Specific Cytotoxic Immune Response
Authors: Cavin S , Hao Y , Gkasti A , Chriqui L E , Marie D , Abdelnour E , Gonzalez M , Krueger T , Dyson P J , Peters S , Meylan E , Perentes J Y 
Published: June 2023

Abstract

Background
The management of malignant pleural mesothelioma (MPM) remains challenging with poor patient survival. Local therapies such as hyperthermic intrathoracic cisplatin (HITOC) have shown good tumor control in selected patients. HITOC was shown to increase MPM drug exposure while limiting systemic side effects but alternative mechanisms for HITOC are still lacking.

Aims
We hypothesized that HITOC induces an immune response directed against MPM which decreases cancer related mortality.

Methods
A perfusion circuit was downsized to administer cisplatin in the thoracic cavity of MPM bearing mice at normo (37°C, ITOC) or hyperthermic (39°C, HITOC) conditions for 30 minutes. Tumor platinum content and distribution were determined by inductively coupled plasma mass spectrometry (ICP-MS) and by laser ablation ICP-MS respectively. The impact of (H)ITOC on the MPM immune microenvironment was questioned using flow cytometry and immunohistochemistry. Tumor growth and survival was assessed in immunocompetent and T-cell deficient mice. Finally, the combination of HITOC with anti-CTLA-4 and anti-PD-1 antibodies was evaluated in immunocompetent animals.

Results
MPM tumor control and mouse survival were significantly improved by HITOC compared to controls (ITOC, saline 37 and 39°C). This correlated with higher tumor platinum content that was mainly located at the surface of tumors. Furthermore, HITOC enhanced MPM infiltration by cytotoxic T-cells and decreased the level of protumor (M2-like) macrophages at day 7. The beneficial impact of HITOC on tumor control and mice survival was lost in immunocompromised animals. Interestingly, HITOC significantly induced PD-1 and CTLA-4 immune checkpoint molecules expression and administration of dual immune checkpoint blockade after HITOC increased of almost two fold the median survival of the animals.

Conclusions
HITOC improves MPM control through a T lymphocyte immune mediated response. The potentiation of the immune checkpoint blockade response by HITOC opens new perspectives for the combination of immune checkpoint inhibitors with HITOC in clinic.
Maternal Obesity Increases the Risk for Hepatocellular Carcinoma in a Toxic Liver Cancer Model Through the Gut Microbiome
Authors: Moeckli B , Delaune V , Gilbert B , Rodrigues Ribeiro J , Peloso A , Oldani G , El Hajji S , Slits F , Gex Q , Lacotte S , Toso C 
Published: June 2023

Abstract

Background
The obesity pandemic leads to rising obesity rate in women of reproductive age with emerging evidence that maternal obesity has a negative impact on the long-term health of offspring. Additionally, obesity is an independent risk factor for malignancies and particularly hepatocellular carcinoma (HCC).

Aims
The aim of our study is to investigate the impact of maternal obesity on the risk for HCC in the offspring and identify potential mechanisms of transmission.

Methods
Female mice were fed either a high fat (HFD) or a normal diet (ND) before mating. Offspring received ND throughout life. We studied the liver histology and tumor load in a short-term transgenic (12 weeks) or a toxin induced long-term (36 weeks) HCC mouse model. To normalize the gut microbiome, we co-housed offspring of HFD and ND mothers after weaning. The composition of the gut microbiota was assessed through 16S rRNA sequencing.

Results
Maternal obesity induced a distinguishable shift in the microbial composition towards decreased microbial diversity (2.56 vs. 2.92, p=0.0089), increased proportions of Firmicutes and decreased abundance of Bacteroidota. At 40 weeks female HFD offspring developed steatosis (9.43 vs 3.09%, p=0.0023) and a higher number of inflammatory infiltrates (4.8 vs 1.0, p=0.018) compared to ND offspring. A higher proportion of female HFD offspring developed liver tumors after DEN induction (79.8 vs 37.5%, p=0.0084) with a higher total tumor volume at 36 weeks (234 vs 3 µm3, p=0.0041). An effect that we did not observe in the short-term transgenic model. Gut microbiome composition was corrected through co-housing offspring and co-housing normalized the tumor number and volume to the level of ND offspring.

Conclusions
Maternal obesity increases the susceptibility to develop HCC in offspring. The transmission of an altered gut microbiome appears to play an important role in this increased long-term risk profile.