bluuebunny/crossref_metadata_2025 huggingface dataset:
Liquid-phase exfoliated 2D materials for lithium-ion battery anode: current status and future direction
Authors: Li Ziyu , Liu Xuefeng , Xu Ke , Xie Qiao , Li Yage , Zhang Haijun , Zhang Shaowei , Lei Wen
Published: August 2024

With the increasing need for energy and the swift advancement of the electric vehicle industry, the field of energy storage has garnered significant attention. Especially, lithium-ion batteries (LIBs) serve as crucial energy storage devices and have received particular attention. As an emerging class of electrode materials, two-dimensional (2D) materials have become promising candidates for solving the challenges of LIBs owing to their high theoretical capacity, high specific surface area, high ionic conductivity, and long cycle life. The research progress on 2D materials, especially those prepared through liquid-phase exfoliation (LPE), has shown great potential in improving the performance of LIBs. LPE is a powerful and efficient method for preparing 2D materials with various sizes and properties, which is suitable for practical applications. Given these, this paper underscores the great potential of 2D materials prepared via LPE as anode materials for LIBs. Meanwhile, the existence of challenges that need to be overcome in relation to the scalability of the LPE method and the use of 2D materials in practical applications are also proposed.
Effect of tempering process on the mechanical properties and corrosion resistance of E690 marine steel
Authors: Liu Zhimin , Fu Kuijun , Xu Zhen , Wang Jiaji , Zhao Ming , Wang Dong
Published: August 2024

To accurately replicate actual production and save production costs, this study examines the influence of the tempering process on the structure, mechanical properties, and corrosion resistance of E690 marine steel. Various techniques were employed to evaluate its properties, behavior, and performance, including metallurgical microscopy, scanning electron microscopy, transmission electron microscopy, electron backscatter diffraction, impact experiments, tensile tests, and electrochemical corrosion tests. The results indicate that as the tempering temperature increases, the tempering degree of the tempered martensite structure improves, the martensite strip coarsens, the size of the precipitated carbide increases, and the proportion of large-angle grain boundaries decreases. Consequently, the tensile strength and yield strength initially increase and then decrease, while the impact toughness and elongation gradually improve. At a tempering temperature of 600 °C, the steel exhibits the best overall mechanical properties, with a tensile strength of 729 MPa, yield strength of 649 MPa, and elongation of 18%. Furthermore, at a tempering temperature of 550 °C, the test steel shows an optimal corrosion resistance, with a corrosion rate of 0.03233 mm y−1 and an open-circuit potential of −0.36 V.
Study on plasma expansion model of primary discharge on spacecraft solar array
Authors: WEI 尉 Dejie 德杰 , (武建文) Jianwen WU , ZHU 朱 Liying 立颖
Published: August 2024

In the space plasma environment, primary discharge may occur on the solar array and evolve into a destructive sustained arc, which threatens the safe operation of the spacecraft. Based on the plasma expansion fluid theory, a new multicomponent plasma expansion model is proposed in this study, which takes into account the effects of ion species, ion number, initial discharge current, and Low Earth Orbit (LEO) plasma environment. The expansion simulation of single-component and multicomponent ions is carried out respectively, and the variations of plasma number density, expansion distance, and speed during the expansion process are obtained. Compared with the experimental results, the evolution of propagation distance and speed is closed and the error is within a reasonable range, which verifies the validity and rationality of the model. The propagation characteristics of the primary discharge on the solar array surface and the influence of the initial value on the maximum propagation distance and the propagation current peaks are investigated. This study can provide important theoretical support for the propagation and evolution of the primary discharge and the key behavior of the transition to secondary discharge on spacecraft solar array.
A short-term wind speed prediction method based on the IDBO-BPNN
Authors: Wang Lingzhi , Li Cheng , Li Chenyang , Zhao Ling
Published: August 2024

Wind energy is known for its uncertainty and volatility, necessitating accurate wind speed prediction for stable wind farm operations. To enhance wind speed prediction accuracy, this study proposes a BP neural network (BPNN) short-term wind speed prediction model based on the Improved Dung Beetle Optimization (IDBO) algorithm. Addressing the issue of local optimization and reduced accuracy in the BPNN optimized by the Dung Beetle Optimization (DBO) algorithm, the circle chaotic mapping is utilized for population initialization to achieve a more uniform initial distribution. The improved sine-cosine algorithm, triangle wandering strategy, and adaptive weight coefficient are then employed to optimize dung beetle positions, balancing global exploration and local development capabilities and improving the algorithm’s search performance. Finally, the improved DBO algorithm optimizes the weights and thresholds of the BPNN, and the IDBO-BPNN prediction model was constructed. Simulation experiments were conducted based on wind speed data from a wind farm in Ohio, USA. The IDBO-BPNN model was compared with other prediction models, and error evaluation indexes were introduced to evaluate the experimental results. The findings demonstrate that the suggested model yields the most accurate predictions and achieves the optimal error evaluation indexes. MAE, MSE, RMSE, NSE and R2 of dataset 1 are 0.42247, 0.28775, 0.53642, 88.8785%, 89.161%, those of dataset 2 are 0.28283, 0.14952, 0.38668, 85.7383%, 86.577%, and those of dataset 3 are 0.45406, 0.39268, 0.62664, 84.3859%, 84.931%. In particular, compared with BPNN model, the five evaluation indexes of the IDBO-BPNN model promoted by 41.53%, 57.38%, 34.71%, 24.91%, and 11.44%, respectively in dataset 3. Therefore, that the proposed IDBO-BPNN model exhibits higher accuracy in short-term wind speed prediction, indicating its feasibility and superiority in the realm of wind energy.
Effect of process variables on microhardness and surface roughness in SPIF of beryllium copper
Authors: Verma Nikesh , Kumar Vikas
Published: August 2024

Beryllium copper is gaining the popularity among material research community owing to its excellent properties like high strength-to-weight ratio, corrosion resistance, and high electrical conductivity. This work aims to enhance the performance of ‘Single Point Incremental Forming (SPIF)’ of Beryllium copper using desirability function analysis (DFA). Feed rate (FEED), Step size (SS), wall angle (WA), and tool rotation speed (TRPM) are the four vital input parameters that have been chosen. This research investigates the effects of variations in these four factors on the truncated cone’s surface roughness and microhardness. After testing different levels of these parameters, the optimal setting using desirability function analysis was 0.4 mm step size, 200 mm min−1 feed rate, 47° wall angle, and a tool rotation speed of 1500 rpm with desirability of 70.7%. Further, measured data was subjected to Analysis of Variance (ANOVA) tests to determine the significance of all parameters on the responses. Results of the ANOVA analysis showed that the step size and tool rotation speed had the most profound impact on surface roughness and micro-hardness respectively. Feed rate and wall angle were the least significant parameters in affecting the surface roughness and micro-hardness respectively. The confirmation experiments validated fine-tuning with predicted and experimental values.
The CCT chaperonin and actin modulate the ER and RNA-binding protein condensation during oogenesis and maintain translational repression of maternal mRNA and oocyte quality
Authors: Elaswad Mohamed T. , Gao Mingze , Tice Victoria E. , Bright Cora G. , Thomas Grace M. , Munderloh Chloe , Trombley Nicholas J. , Haddad Christya N. , Johnson Ulysses G. , Cichon Ashley N. , Schisa Jennifer A.
Published: August 2024

The regulation of maternal mRNAs is essential for proper oogenesis, the production of viable gametes, and to avoid birth defects and infertility. Many oogenic RNA-binding proteins have been identified with roles in mRNA metabolism, some of which localize to dynamic ribonucleoprotein granules and others that appear dispersed. Here, we use a combination of in vitro condensation assays and the in vivo Caenorhabditis elegans oogenesis model to characterize the properties of the conserved KH-domain MEX-3 protein and to identify novel regulators of MEX-3 and three other translational regulators. We demonstrate that MEX-3 undergoes phase separation and appears to have intrinsic gel-like properties in vitro. We also identify novel roles for the chaperonin-containing tailless complex polypeptide 1 (CCT) chaperonin and actin in preventing ectopic RNA-binding protein condensates in maturing oocytes that appear to be independent of MEX-3 folding. The CCT chaperonin and actin also oppose the expansion of endoplasmic reticulum sheets that may promote ectopic condensation of RNA-binding proteins. These novel regulators of condensation are also required for the translational repression of maternal mRNA which is essential for oocyte quality and fertility. The identification of this regulatory network may also have implications for understanding the role of hMex3 phase transitions in cancer.
Material me
Authors: Gerrans Philip
Published: August 2024

Self awareness is at heart a form of bodily awareness. But self awareness is not identical to bodily awareness. Pain is a good example. Pain is not experienced as a simple signal of bodily damage. Rather the experience of pain is an emergent product of sensorimotor, interoceptive, emotional and higher cognitive processing integrated to deal with a signal of damage or threat. This explains patterns of overlapping activity between neural substrates of self awareness, affect, and interoceptive/nociceptive experience. Self awareness arise in the process of integration which is why as Wittgenstein among others observed pain is intimately and insistently experienced as “mine”. Rather the insula cortex serves as a crucial relay station in the integration of interoception, sensorimotor regulation, cognition and control. The feeling that I am the subject of bodily and affective experience is an emergent result of patterned activity across a distributed system . This processing is anchored by the avatar: a representation of the entity that regulates the system and feels the consequences.
Alienation and identification in addiction
Authors: Gerrans Philip
Published: August 2024

Addiction is often explained as a loss of self-control . It is also explained as a form of brain disease. Neural adaptation accounts split the difference, arguing that addiction results from ‘hijack’ by addictive targets of mechanisms of reward prediction, habit formation, decision-making, and cognitive control. The idea that addiction is ultimately a problem of self modelling integrates the ‘brain disease’ and self control accounts. It explains the role of the insula (a hub of self modelling) in addiction and some cases of disruption of addiction following a lesion to the anterior insula cortex. Deactivation of the anterior insula can disrupt addiction by alienating the subject from her addictive tendencies. This account is consistent with neural evidence but also incorporates personal and social aspects of addiction that are opaque to neural-level explanation. The self modelling account is consistent with accounts that argue that an important aspect of addiction consists in inability to with a non-addicted future self.
Current Evidence and Recommendations for Further Research
Authors: Manuel Jennifer I , Nizza Megan R , Herman Daniel B , Conover Sarah A , Esquivel Laura I , Yuan Yeqing , Susser Ezra S
Published: August 2024

This chapter reviews the current state of evidence on Critical Time Intervention (CTI), methodological strengths and challenges, and recommendations for future research. The authors discuss the effectiveness of CTI and its adaptations by summarizing the evidence derived from experimental and quasi-experimental studies of its impact conducted in the United States, Brazil, Canada, the Netherlands, and the United Kingdom and Europe. The review suggests that CTI has shown a consistent positive impact on reducing homelessness and enhancing service engagement across diverse populations and settings, while impacts in other domains are uneven. The chapter concludes with a discussion of the methodological challenges of the existing evidence and several recommendations for future research. These include factors associated with effective program implementation and the need to understand for whom and under what conditions CTI is most effective.
Good Judgment
Authors: Zinkin Melissa
Published: August 2024

This chapter explains why for Kant aesthetic judgment is the pure form of all judgment, including rational judgment. It is because our capacity for making aesthetic judgments is the same as our capacity for coming up with a concept and thereby comprehending something. Although many commentators have compared Kant’s discussion of judgments of taste in the third Critique to his discussion of the generation of concepts, none has argued that reason is the source of both of these forms of mental activity. To see this, we must adjust our understanding not only of aesthetic judgment in Kant’s philosophy, but also of human reason. We will have to see that human reason is the faculty of deep judgment and that it has an aesthetic—and an artistic—component.
Depth and Moral Worth
Authors: Zinkin Melissa
Published: August 2024

This chapter continues to set the stage for a discussion of moral worth in Kant by addressing two recent accounts of what Kant means by acting from the motive of duty. Julia Markovits and Nomy Arpaly each argue that their view is an improvement on Kant. This chapter argues that they misunderstand Kant, in part, because they think that for Kant acting for the sake of duty is meant only to avoid moral “contingency” and not to avoid moral “precariousness” as well. In order to clarify Kant’s position and defend it, the chapter shows how he would respond to Markovits and Arpaly, and, further, how he would resolve a disagreement between them about whether or not depth of concern contributes to the moral worth of an action. For Kant, the moral worth of an action does indeed involve a depth of moral feeling.
The “Third Thing”
Authors: Zinkin Melissa
Published: August 2024

This chapter argues that in Groundwork III, where Kant emphasizes that the free will is a kind of causality in accordance with immutable laws, the kind of causality that he has in mind is a teleological causality. To be autonomous is not just for me to be the efficient cause of my own action as opposed to having my action be determined by something external to my own reason. Instead, Kant’s “richer and more fruitful” idea of autonomy indicates that I am obligated to act on those maxims that I have self-legislated for the sake of myself, understood as a member of the intelligible world. What causes me to do what is right is the awareness that by doing so I am realizing my own necessary end. Accompanying such autonomous actions is what I call a feeling of “self-rightness.”
Cold War maladies
Authors: Clark Heather
Published: August 2024

This chapter looks into Sylvia Plath’s life, particularly her breakdown and the writing of her novel The Bell Jar. After struggling for several weeks with insomnia and depression, Plath began cutting herself; she was treated with a series of disastrous outpatient shock treatments at Valley Head Hospital in Carlisle, Massachusetts. Terrified of more shock treatments and fearful of a future trapped inside a mental hospital, Plath decided to end her life while she still possessed free will and was remembered as a success rather than a mental patient. Despite her suicide attempt and missing the academic year, Plath was still the star student in the English department at Smith College. This chapter cites numerous details from Plath’s own life that would inspire scenes in The Bell Jar, and outlines the novel’s major themes.
Inverse probability weighting to estimate impacts of hypothetical occupational limits on radon exposure to reduce lung cancer
Authors: Keil Alexander P , Li Yi , Lan Qing , Bertke Stephen , Daniels Robert D , Edwards Jessie K , Kelly-Reif Kaitlin
Published: August 2024

Radon is a known cause of lung cancer. Protective standards for radon exposure are derived largely from studies of working populations that are prone to healthy worker survivor bias. This bias can lead to underprotection of workers and is a key barrier to understanding health effects of many exposures. We apply inverse probability weighting to study a set of hypothetical exposure limits among 4137 male, White and American Indian radon-exposed uranium miners in the Colorado Plateau followed from 1950 to 2005. We estimate cumulative risk of lung cancer through age 90 under hypothetical occupational limits. We estimate that earlier implementation of the current US Mining Safety and Health Administration annual standard of 4 working level months (implemented here as a monthly exposure limit) could have reduced lung cancer mortality from 16 of 100 workers to 6 of 100 workers (95% confidence interval, 3/100, 8/100), in contrast with previous estimates of 10 of 100 workers. Our estimate is similar to that among contemporaneous occupational cohorts. Inverse probability weighting is a simple and computationally efficient way address healthy worker survivor bias to contrast health effects of exposure limits and estimate the number of excess health outcomes under exposure limits at work.
INTREPPPID—an orthologue-informed quintuplet network for cross-species prediction of protein–protein interaction
Authors: Szymborski Joseph , Emad Amin
Published: August 2024

An overwhelming majority of protein–protein interaction (PPI) studies are conducted in a select few model organisms largely due to constraints in time and cost of the associated ‘wet lab’ experiments. In silico PPI inference methods are ideal tools to overcome these limitations, but often struggle with cross-species predictions. We present INTREPPPID, a method that incorporates orthology data using a new ‘quintuplet’ neural network, which is constructed with five parallel encoders with shared parameters. INTREPPPID incorporates both a PPI classification task and an orthologous locality task. The latter learns embeddings of orthologues that have small Euclidean distances between them and large distances between embeddings of all other proteins. INTREPPPID outperforms all other leading PPI inference methods tested on both the intraspecies and cross-species tasks using strict evaluation datasets. We show that INTREPPPID’s orthologous locality loss increases performance because of the biological relevance of the orthologue data and not due to some other specious aspect of the architecture. Finally, we introduce PPI.bio and PPI Origami, a web server interface for INTREPPPID and a software tool for creating strict evaluation datasets, respectively. Together, these two initiatives aim to make both the use and development of PPI inference tools more accessible to the community.
Canalizing kernel for cell fate determination
Authors: Kim Namhee , Lee Jonghoon , Kim Jongwan , Kim Yunseong , Cho Kwang-Hyun
Published: August 2024

The tendency for cell fate to be robust to most perturbations, yet sensitive to certain perturbations raises intriguing questions about the existence of a key path within the underlying molecular network that critically determines distinct cell fates. Reprogramming and trans-differentiation clearly show examples of cell fate change by regulating only a few or even a single molecular switch. However, it is still unknown how to identify such a switch, called a master regulator, and how cell fate is determined by its regulation. Here, we present CAESAR, a computational framework that can systematically identify master regulators and unravel the resulting canalizing kernel, a key substructure of interconnected feedbacks that is critical for cell fate determination. We demonstrate that CAESAR can successfully predict reprogramming factors for de-differentiation into mouse embryonic stem cells and trans-differentiation of hematopoietic stem cells, while unveiling the underlying essential mechanism through the canalizing kernel. CAESAR provides a system-level understanding of how complex molecular networks determine cell fates.
TME-NET: an interpretable deep neural network for predicting pan-cancer immune checkpoint inhibitor responses
Authors: Ding Xiaobao , Zhang Lin , Fan Ming , Li Lihua
Published: August 2024

Immunotherapy with immune checkpoint inhibitors (ICIs) is increasingly used to treat various tumor types. Determining patient responses to ICIs presents a significant clinical challenge. Although components of the tumor microenvironment (TME) are used to predict patient outcomes, comprehensive assessments of the TME are frequently overlooked. Using a top-down approach, the TME was divided into five layers—outcome, immune role, cell, cellular component, and gene. Using this structure, a neural network called TME-NET was developed to predict responses to ICIs. Model parameter weights and cell ablation studies were used to investigate the influence of TME components. The model was developed and evaluated using a pan-cancer cohort of 948 patients across four cancer types, with Area Under the Curve (AUC) and accuracy as performance metrics. Results show that TME-NET surpasses established models such as support vector machine and k-nearest neighbors in AUC and accuracy. Visualization of model parameter weights showed that at the cellular layer, Th1 cells enhance immune responses, whereas myeloid-derived suppressor cells and M2 macrophages show strong immunosuppressive effects. Cell ablation studies further confirmed the impact of these cells. At the gene layer, the transcription factors STAT4 in Th1 cells and IRF4 in M2 macrophages significantly affect TME dynamics. Additionally, the cytokine-encoding genes IFNG from Th1 cells and ARG1 from M2 macrophages are crucial for modulating immune responses within the TME. Survival data from immunotherapy cohorts confirmed the prognostic ability of these markers, with p-values <0.01. In summary, TME-NET performs well in predicting immunotherapy responses and offers interpretable insights into the immunotherapy process. It can be customized at https://immbal.shinyapps.io/TME-NET.
Generation of a high confidence set of domain–domain interface types to guide protein complex structure predictions by AlphaFold
Authors: Geist Johanna Lena , Lee Chop Yan , Strom Joelle Morgan , de Jesús Naveja José , Luck Katja
Published: August 2024

Motivation

While the release of AlphaFold (AF) represented a breakthrough for the prediction of protein complex structures, its sensitivity, especially when using full length protein sequences, still remains limited. Modeling success rates might increase if AF predictions were guided by likely interacting protein fragments. This approach requires available sets of highly confident protein–protein interface types. Computational resources, such as 3did, infer interacting globular domain types from observed contacts in protein structures. Assessing the accuracy of these predicted interface types is difficult because we lack hand-curated reference sets of verified domain–domain interface (DDI) types.

Results

To improve protein complex modeling of DDIs by AF, we manually inspected 80 randomly selected DDI types from the 3did resource to generate a first reference set of DDI types. Identified cases of DDI type nonapproval (40%) primarily resulted from inaccurate Pfam domain matches, crystal contacts, and synthetic protein constructs. Using logistic regression, we predicted a subset of 2411 out of 5724 considered DDI types in 3did to be of high confidence, which we subsequently applied to 53 000 human–protein interactions to predict DDIs followed by AF modeling. We obtained highly confident AF models for 604 out of 1129 predicted DDIs. Of note, for 47% of them no confident AF structural model could be obtained using full length protein sequences.

Availability and implementation

Code is available at https://github.com/KatjaLuckLab/DDI_manuscript.
A comparative study on the transcultural (re-)reception of The Untamed and its queerness with Chinese characteristics
Authors: Qiao Peng , Hu Yuqi
Published: August 2024

Drawing on Stanley Fish’s concept of interpretive communities, this article explores the various transcultural interpretations of queer opacity, a Chinese variant of queerness within dan’gai web series. This study reveals that while viewers employ a shared interpretive strategy of queer reading to identify queer opacity, the effect of queer interpretation is contingent upon the queer interpretive subcommunities’ familiarity with Chinese culture. Moreover, different cultures possess sub-strategies of queer reading: visibility reading is often practiced in the global northwest to initiate visibility politics in society, while opacity reading is used in the global southeast in an unconfrontational manner within fictional worlds. By examining a layered interpretive phenomenon that involves transcultural reaction videos towards the Chinese dan’gai web series The Untamed (TU), alongside the danmu from Chinese viewers on these videos, this study contributes to scholarship on transcultural queerness through the lenses of queer opacity and transcultural reader reception.
Predicting psoriasis severity using machine learning: a systematic review
Authors: McMullen Eric P , Al Naser Yousif A , Maazi Mahan , Grewal Rajan S , Abdel Hafeez Dana , Folino Tia R , Vender Ronald B
Published: August 2024

Background

In dermatology, the applications of machine learning (ML), an artificial intelligence (AI) subset that enables machines to learn from experience, have progressed past the diagnosis and classification of skin lesions. A lack of systematic reviews exists to explore the role of ML in predicting the severity of psoriasis.

Objectives

To identify and summarize the existing literature on predicting psoriasis severity using ML algorithms and to identify gaps in ­current clinical applications of these tools.

Methods

OVID Embase, OVID MEDLINE, ACM Digital Library, Scopus and IEEE Xplore were searched from inception to August 2024.

Results

In total, 30 articles met our inclusion criteria and were included in this review. One article used serum biomarkers, while the remaining 29 used image-based models. The most common severity assessment score employed by these ML models was the Psoriasis Area and Severity Index score, followed by body surface area, with 15 and 5 articles, respectively.

Conclusions

The small size and heterogeneity of the existing body of literature are the primary limitations of this review. Progress in assessing skin lesion severity through ML in dermatology has advanced, but prospective clinical applications remain limited. ML and AI promise to improve psoriasis management, especially in nonimage-based applications requiring further exploration. Large-scale prospective trials using diverse image datasets are necessary to evaluate and predict the clinical value of these predictive AI models.
Efficacy of salmon GnRHa, Ovaprim® and hCG for hormonal stimulation of spermiation in the Fowler’s toad (Anaxyrus fowleri)
Authors: Saylor Erin M , Kouba Andrew J , Boudreau Melanie R , Songsasen Nucharin , Kouba Carrie K
Published: August 2024

Ex situ amphibian populations can experience reproductive dysfunction due to the absence of environmental cues that trigger reproductive events. Assisted reproductive technologies (ART) for amphibians, specifically exogenous hormone regimens, can circumvent these external signals to induce gametogenesis and gamete release. Currently, the use of the mammalian reproductive hormones gonadotropin-releasing hormone (GnRH) and human chorionic gonadotropin (hCG) are used in a species-specific manner to stimulate amphibian breeding. Hormones or hormone mixtures that are effective in all breeding scenarios would provide the best option for conservation practitioners and some commercial products are already in use for breeding other ectotherms. Ovaprim®, which contains salmon GnRH analogue (sGnRHa) and the dopamine antagonist domperidone (DOM), is effective in fish aquaculture and may be effective for amphibians. To test this hypothesis, we treated Fowler’s toads (Anaxyrus fowleri) with either sGnRHa alone, a high or low dose of Ovaprim® or hCG. We then compared spermiation response, sperm quantity and quality parameters, and changes in animal mass over time within each treatment. We found administration of Ovaprim® resulted in more males producing sperm with better motility compared to administration of sGnRHa alone. In addition, the Ovaprim® and sGnRHa treatments resulted in lower response rates, lower sperm motilities, more abnormal sperm, and higher aggregations of sperm compared to the hCG treatment. Furthermore, Ovaprim®-treated males gained significant mass, suggesting an anti-diuretic effect of DOM. Together, these results show that neither Ovaprim® nor sGnRHa, at the concentrations tested, are likely suitable replacements for hCG in ex situ bufonid breeding programmes and that hormone mixtures developed for fish may have limited transferability to new world toad species.
RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice
Authors: Kumar Deepesh , Venkadesan SureshKumar , Prabha Ratna , Begam Shbana , Dutta Bipratip , Mishra Dwijesh C , Chaturvedi K K , Jha Girish Kumar , Solanke Amolkumar U , Sevanthi Amitha Mithra
Published: August 2024

MicroRNAs are key players involved in stress responses in plants and reports are available on the role of miRNAs in drought stress response in rice. This work reports the development of a database, RiceMetaSys: Drought-miR, based on the meta-analysis of publicly available sRNA datasets. From 28 drought stress-specific sRNA datasets, we identified 216 drought-responsive miRNAs (DRMs). The major features of the database include genotype-, tissue- and miRNA ID-specific search options and comparison of genotypes to identify common miRNAs. Co-localization of the DRMs with the known quantitative trait loci (QTLs), i.e., meta-QTL regions governing drought tolerance in rice pertaining to different drought adaptive traits, narrowed down this to 37 promising DRMs. To identify the high confidence target genes of DRMs under drought stress, degradome datasets and web resource on drought-responsive genes (RiceMetaSys: DRG) were used. Out of the 216 unique DRMs, only 193 had targets with high stringent parameters. Out of the 1081 target genes identified by Degradome datasets, 730 showed differential expression under drought stress in at least one accession. To retrieve complete information on the target genes, the database has been linked with RiceMetaSys: DRG. Further, we updated the RiceMetaSys: DRGv1 developed earlier with the addition of DRGs identified from RNA-seq datasets from five rice genotypes. We also identified 759 putative novel miRNAs and their target genes employing stringent criteria. Novel miRNA search has all the search options of known miRNAs and additionally, it gives information on their in silico validation features. Simple sequence repeat markers for both the miRNAs and their target genes have also been designed and made available in the database. Network analysis of the target genes identified 60 hub genes which primarily act through abscisic acid pathway and jasmonic acid pathway. Co-localization of the hub genes with the meta-QTL regions governing drought tolerance narrowed down this to 16 most promising DRGs.

Database URL: http://14.139.229.201/RiceMetaSys_miRNA

Updated database of RiceMetaSys URL: http://14.139.229.201/RiceMetaSysA/Drought/
Left ventricular diastolic dysfunction in non-myocardial disorders
Authors: Smiseth Otto A , Wang Tom Kai Ming , Klein Allan L , Nagueh Sherif F
Published: August 2024

This article reviews and discusses non-myocardial disorders that represent diagnostic challenges when evaluating patients for suspected heart failure with preserved left ventricular ejection fraction. This includes pre-capillary pulmonary hypertension, which is important to differentiate from post-capillary hypertension caused by left-sided heart disease. The impact of electrical disorders on LV diastolic function is also reviewed, and includes a discussion of left bundle branch, which has both a direct effect on LV diastolic function, as well as a long-term effect due to remodelling. Furthermore, evaluation of diastolic function in patients with atrial fibrillation is discussed. Pericardial diseases are reviewed as well as effects of a normal pericardium on diastolic function in failing hearts. Finally, the article reviews how valvular diseases impact LV diastolic function.
A case report of Ebstein’s anomaly–Gerbode defect dyad: is there room for another anomaly in the same patient?
Authors: Onea Horea-Laurentiu , Lazar Florin-Leontin , Teodoru Minodora , Stoia Oana , Olinic Dan-Mircea
Published: August 2024

Background

Ebstein’s anomaly is a rare congenital heart disease characterized by apical displacement of the septal and posterior tricuspid valve leaflets. It is commonly associated with other defects such as patent foramen ovale or accessory atrioventricular pathways.

Case summary

We describe a case of an Ebstein anomaly diagnosed in an adult in his 50s in association with a septal defect between the left ventricle and right atrium (Gerbode defect). The diagnosis was confirmed on magnetic resonance imaging. A third anomaly was noted on coronary angiography, consisting of an aberrant origin of the right coronary artery from the left sinus of Valsalva. The patient was paucisymptomatic until he developed typical atrial flutter. Catheter ablation was employed after first arrhythmia recurrence and the patient is to date in good clinical condition.

Conclusion

The association of Ebstein’s anomaly–Gerbode defect is extremely rare, and to our knowledge, this is the first case that presents in addition an anomalous coronary artery. Both structural defects were without haemodynamic significance, and there was no proof of myocardial ischaemia. As the case illustrates, congenital disorders, even when in conjunction, can have a silent clinical course and multimodality imaging is sometimes necessary for a complete and final diagnosis.
PRAP study—partial versus radical adrenalectomy in hereditary pheochromocytomas
Authors: Xu Kai , Langenhuijsen Johan F , Viëtor Charlotte L , Feelders Richard A , van Ginhoven Tessa M , Elhassan Yasir S , Bioletto Fabio , Parasiliti-Caprino Mirko , Zandee Wouter T , Kruijff Schelto , Backman Samuel , Åkerström Tobias , Pamporaki Christina , Bechmann Nicole , Lussey-Lepoutre Charlotte , Canu Letizia , Steenaard Rebecca V , Driessens Natacha , Velema Marieke , Dreijerink Koen M A , Engelsman Anton F , Timmers Henri J L M , de Laat Joanne M
Published: August 2024

Objective

Hereditary pheochromocytoma (hPCC) commonly develops bilaterally, causing adrenal insufficiency when standard treatment, radical adrenalectomy (RA), is performed. Partial adrenalectomy (PA) aims to preserve adrenal function, but with higher recurrence rates. This study compares outcomes of PA versus RA in hPCC.

Methods

Patients with hPCC due to pathogenic variants in RET, VHL, NF1, MAX, and TMEM127 from 12 European centers (1974–2023) were studied retrospectively. Stratified analysis based on surgery type and initial presentation was conducted. The main outcomes included recurrence, adrenal insufficiency, metastasis, and mortality.

Results

The study included 256 patients (223 RA, 33 PA). Ipsilateral recurrence rates were 9/223 (4%) after RA versus 5/33 (15%) after PA (P = 0.02). Metastasis and mortality did not differ between groups. Overall, 103 patients (40%) underwent bilateral adrenalectomy either synchronously or metachronously (75 RA, 28 PA). Of these, 46% developed adrenal insufficiency after PA.

In total, 191 patients presented with initial unilateral disease, of whom 50 (26%) developed metachronous contralateral disease, most commonly in RET, VHL, and MAX. In patients with metachronous bilateral disease, adrenal insufficiency developed in 3/4 (75%) when PA was performed as the first operation followed by RA, compared to 1/7 (14%) when PA was performed as the second operation after prior RA (P = 0.09).

Conclusion

In patients with hPCC undergoing PA, local recurrence rates are higher than after RA, but metastasis and disease-specific mortality are similar. Therefore, PA seems a safe method to preserve adrenal function in patients with hPCC, in cases of both synchronous and metachronous bilateral disease, when performed as a second operation.
Coping with extreme heat: current exposure and implications for the future
Authors: Weitz Charles A
Published: August 2024

A preview of how effective behavioral, biological and technological responses might be in the future, when outdoor conditions will be at least 2°C hotter than current levels, is available today from studies of individuals already living in extreme heat. In areas where high temperatures are common—particularly those in the hot and humid tropics—several studies report that indoor temperatures in low-income housing can be significantly hotter than those outdoors. A case study indicates that daily indoor heat indexes in almost all the 123 slum dwellings monitored in Kolkata during the summer were above 41°C (106°F) for at least an hour. Economic constraints make it unlikely that technological fixes, such as air conditioners, will remedy conditions like these—now or in the future. People without access to air conditioning will have to rely on behavioral adjustments and/or biological/physiological acclimatization. One important unknown is whether individuals who have lived their entire lives in hot environments without air conditioning possess natural levels of acclimatization greater than those indicated by controlled laboratory studies. Answering questions about the future will require more studies of heat conditions experienced by individuals, more information on indoor versus outdoor heat conditions, and a greater understanding of the behavioral and biological adjustments made by people living today in extremely hot conditions.
T and Z, partial seed coat patterning genes in common bean, provide insight into the structure and protein interactions of a plant MBW complex
Authors: McClean Phillip E , Roy Jayanta , Colbert Christopher L , Osborne Caroline , Lee Rian , Miklas Phillip N , Osorno Juan M
Published: August 2024

Flavonoids are secondary metabolites associated with plant seed coat and flower color. These compounds provide health benefits to humans as anti-inflammatory and antioxidant compounds. The expression of the late biosynthetic genes in the flavonoid pathway is controlled by a ternary MBW protein complex consisting of interfacing MYB, beta-helix–loop–helix (bHLH), and WD40 Repeat (WDR) proteins. P, the master regulator gene of the flavonoid expression in common bean (Phaseolus vulgaris L.), was recently determined to encode a bHLH protein. The T and Z genes control the distribution of color in bean seeds and flowers and have historically been considered regulators of the flavonoid gene expression. T and Z candidates were identified using reverse genetics based on genetic mapping, phylogenetic analysis, and mutant analysis. Domain and AlphaFold2 structure analyses determined that T encodes a seven-bladed β-propeller WDR protein, while Z encodes a R2R3 MYB protein. Deletions and SNPs in T and Z mutants, respectively, altered the 3D structure of these proteins. Modeling of the Z MYB/P bHLH/T WDR MBW complex identified interfacing sequence domains and motifs in all three genes that are conserved in dicots. One Z MYB motif is a possible beta-molecular recognition feature (β-MoRF) that only appears in a structured state when Z MYB is modeled as a component of a MBW complex. Complexes containing mutant T and Z proteins changed the interaction of members of the complex in ways that would alter their role in regulating the expression of genes in the flavonoid pathway.
Neurogenesis in Caenorhabditis elegans
Authors: Poole Richard J , Flames Nuria , Cochella Luisa
Published: August 2024

Animals rely on their nervous systems to process sensory inputs, integrate these with internal signals, and produce behavioral outputs. This is enabled by the highly specialized morphologies and functions of neurons. Neuronal cells share multiple structural and physiological features, but they also come in a large diversity of types or classes that give the nervous system its broad range of functions and plasticity. This diversity, first recognized over a century ago, spurred classification efforts based on morphology, function, and molecular criteria. Caenorhabditis elegans, with its precisely mapped nervous system at the anatomical level, an extensive molecular description of most of its neurons, and its genetic amenability, has been a prime model for understanding how neurons develop and diversify at a mechanistic level. Here, we review the gene regulatory mechanisms driving neurogenesis and the diversification of neuron classes and subclasses in C. elegans. We discuss our current understanding of the specification of neuronal progenitors and their differentiation in terms of the transcription factors involved and ensuing changes in gene expression and chromatin landscape. The central theme that has emerged is that the identity of a neuron is defined by modules of gene batteries that are under control of parallel yet interconnected regulatory mechanisms. We focus on how, to achieve these terminal identities, cells integrate information along their developmental lineages. Moreover, we discuss how neurons are diversified postembryonically in a time-, genetic sex-, and activity-dependent manner. Finally, we discuss how the understanding of neuronal development can provide insights into the evolution of neuronal diversity.
The genetic architecture of polygenic local adaptation and its role in shaping barriers to gene flow
Authors: Zwaenepoel Arthur , Sachdeva Himani , Fraïsse Christelle
Published: August 2024

We consider how the genetic architecture underlying locally adaptive traits determines the strength of a barrier to gene flow in a mainland-island model. Assuming a general life cycle, we derive an expression for the effective migration rate when local adaptation is due to genetic variation at many loci under directional selection on the island, allowing for arbitrary fitness and dominance effects across loci. We show how the effective migration rate can be combined with classical single-locus diffusion theory to accurately predict multilocus differentiation between the mainland and island at migration–selection–drift equilibrium and determine the migration rate beyond which local adaptation collapses, while accounting for genetic drift and weak linkage. Using our efficient numerical tools, we then present a detailed study of the effects of dominance on barriers to gene flow, showing that when total selection is sufficiently strong, more recessive local adaptation generates stronger barriers to gene flow. We then study how heterogeneous genetic architectures of local adaptation affect barriers to gene flow, characterizing adaptive differentiation at migration–selection balance for different distributions of fitness effects. We find that a more heterogeneous genetic architecture generally yields a stronger genome-wide barrier to gene flow and that the detailed genetic architecture underlying locally adaptive traits can have an important effect on observable differentiation when divergence is not too large. Lastly, we study the limits of our approach as loci become more tightly linked, showing that our predictions remain accurate over a large biologically relevant domain.
TooManyCellsInteractive: A visualization tool for dynamic exploration of single-cell data
Authors: Klamann Conor , Lau Christie J , Ruiz-Ramírez Javier , Schwartz Gregory W
Published: August 2024

Background

As single-cell sequencing technologies continue to advance, the growing volume and complexity of the ensuing data present new analytical challenges. Large cellular populations from single-cell atlases are more difficult to visualize and require extensive processing to identify biologically relevant subpopulations. Managing these workflows is also laborious for technical users and unintuitive for nontechnical users.

Results

We present TooManyCellsInteractive (TMCI), a browser-based JavaScript application for interactive exploration of cell populations. TMCI provides an intuitive interface to visualize and manipulate a radial tree representation of hierarchical cell subpopulations and allows users to easily overlay, filter, and compare biological features at multiple resolutions. Here we describe the software architecture and demonstrate how we used TMCI in a pan-cancer analysis to identify unique survival pathways among drug-tolerant persister cells.

Conclusions

TMCI will facilitate exploration and visualization of large-scale sequencing data in a user-friendly way. TMCI is freely available at https://github.com/schwartzlab-methods/too-many-cells-interactive. An example tree from data within this article is available at https://tmci.schwartzlab.ca/.
RNAVirHost: a machine learning–based method for predicting hosts of RNA viruses through viral genomes
Authors: Chen Guowei , Jiang Jingzhe , Sun Yanni
Published: August 2024

Background

The high-throughput sequencing technologies have revolutionized the identification of novel RNA viruses. Given that viruses are infectious agents, identifying hosts of these new viruses carries significant implications for public health and provides valuable insights into the dynamics of the microbiome. However, determining the hosts of these newly discovered viruses is not always straightforward, especially in the case of viruses detected in environmental samples. Even for host-associated samples, it is not always correct to assign the sample origin as the host of the identified viruses. The process of assigning hosts to RNA viruses remains challenging due to their high mutation rates and vast diversity.

Results

In this study, we introduce RNAVirHost, a machine learning–based tool that predicts the hosts of RNA viruses solely based on viral genomes. RNAVirHost is a hierarchical classification framework that predicts hosts at different taxonomic levels. We demonstrate the superior accuracy of RNAVirHost in predicting hosts of RNA viruses through comprehensive comparisons with various state-of-the-art techniques. When applying to viruses from novel genera, RNAVirHost achieved the highest accuracy of 84.3%, outperforming the alignment-based strategy by 12.1%.

Conclusions

The application of machine learning models has proven beneficial in predicting hosts of RNA viruses. By integrating genomic traits and sequence homologies, RNAVirHost provides a cost-effective and efficient strategy for host prediction. We believe that RNAVirHost can greatly assist in RNA virus analyses and contribute to pandemic surveillance.