bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptation and feasibility of WHO PM+ for adolescents living with HIV in KwaZulu-Natal Province, South Africa: an implementation feasibility study protocol
Authors: Wambua Grace Nduku , Stein Alan , Seedat Soraya , Sijbrandij Marit , Baisley Kathy , Shahmanesh Maryam , Seeley Janet , Ngwenya Nothando
Published: July 2024

Introduction

Adolescents living with HIV (ALHIV) are an extremely vulnerable population, with the burden of mental health problems carefully documented together with the constraints for receiving timely and adequate management of the problems, especially in rural settings. Problem Management Plus (PM+) is a scalable psychological intervention for individuals impaired by distress in communities exposed to adversity. Initially developed for adult populations, few studies have assessed its potential to address adolescent distress. This study aims to co-adapt PM+ with an adherence component (PM+Adherence) for ALHIV and to evaluate its acceptability and feasibility in rural Kwa-Zulu Natal Province, South Africa.

Methods and analysis

We will use a mixed-methods approach over three phases. The first phase will include a realist synthesis and collection of formative data from up to 60 ALHIV, caregivers and healthcare providers to inform the adaptation of WHO PM+, including the components of an adherence module. During the second phase, we will undertake the cultural adaptation of the PM+Adherence intervention. The third phase will involve a hybrid type 3 implementation strategy among ALHIV aged 16–19 years (n=50) to implement and evaluate the feasibility of the culturally co-adapted PM+Adherence. The feasibility indicators to be evaluated include reach, adoption, attrition, implementation and acceptability of the adapted intervention, which will be assessed qualitatively and quantitatively. In addition, we will assess preliminary effectiveness using an intention-to-treat approach on HIV-related indicators and mental health outcomes at baseline, end intervention, 2-month follow-up during the 6-month implementation.

Discussion

We expect that the PM+Adherence will be acceptable and can feasibly be delivered by lay counsellors in resource-limited rural KwaZulu-Natal.

Ethics and dissemination

Ethical clearance has been obtained from the University of KwaZulu-Natal Biomedical Research Ethics Committee, (BREC/00005743/2023). Dissemination plans include presentations at scientific conferences, peer-reviewed publications and community level.
Assessment of local sensitivity in incomplete retinal pigment epithelium and outer retinal atrophy (iRORA) lesions in intermediate age-related macular degeneration (iAMD)
Authors: Ameln Julius , Saßmannshausen Marlene , von der Emde Leon , Carmichael-Martins Alessandra , Holz Frank G , Ach Thomas , Harmening Wolf M
Published: July 2024

Objective

Lesions of incomplete retinal pigment epithelium and outer retinal atrophy (iRORA) are associated with disease progression in intermediate age-related macular degeneration (AMD). However, the corresponding functional impact of these precursor lesions is unknown and needs to be established.

Methods and analysis

We present a cross-sectional study of four patients with intermediate AMD employing clinical-grade MAIA (stimulus size: 0.43°, ~125 µm) and adaptive optics scanning light ophthalmoscope (AOSLO, stimulus size 0.07°, ~20 µm) based microperimetry (MP) to assess the specific impact of iRORA lesions on retinal sensitivity.

Results

AOSLO imaging showed overall reduced photoreceptor reflectivity and patches of hyporeflective regions at drusen with interspersed hyperreflective foci in iRORA regions. MAIA-MP yielded an average retinal sensitivity loss of -7.3 ±3.1 dB at iRORA lesions compared to the in-eye control. With AOSLO-MP, the corresponding sensitivity loss was -20.1 ±4.8 dB.

Conclusion

We demonstrated that iRORA lesions are associated with a severe impairment in retinal sensitivity. Larger cohort studies will be necessary to validate our findings.
Effect of tooth surface wear on dynamic characteristics of spur gear transmission system
Authors: Zhao Juan , Cheng Hongchuan , Lu Kaiwen , Liu Songnian , Yang Zhou
Published: July 2024

The meshing stiffness and system dynamic characteristics caused by gear wear fault are studied. Firstly, potential energy method was used to model and solve the meshing stiffness of gears and the effect of wear on the meshing stiffness and static transfer error was analyzed. A 6-dof spur gear dynamics model was established considering various nonlinear factors, and the dynamic responses of the spur gear system under various wear degrees were analyzed by using time domain, spectrum, phase plane, and Poincare mapping. Finally, the visual test platform of the gear box is built, and the wear condition and dynamic response of the gear box under different wear cycles are analyzed. Results show that the meshing stiffness of gear decreases due to wear, and the meshing stiffness of double tooth decreases more than that of single tooth. In addition, the static transmission errors caused by wear changes periodically with meshing frequency. Wear causes the vibration response of gear system to become complex gradually, and the nonlinear of the system is enhanced, which changes from single period motion to quasi period motion. Results can provide theoretical support for gear wear reduction, life extension, vibration reduction, and noise reduction and lubrication improvement.
Experimental evaluation of a small-sized continuum robot for grasping tasks
Authors: Mehrkish Ali , Janabi-Sharifi Farrokh
Published: July 2024

This study explores catheters, small-sized continuum robots (CRs), in medical procedures, utilizing a recently developed comprehensive classification system known as the “CR-based taxonomy”. This work specializes the proposed taxonomy for small-sized CRs with medical applications through semi-structured interviews with researchers in this field. Subsequently, it provides a comprehensive analysis of grasp taxonomy, encompassing aspects such as grasp stability, grasp adaptability, and the inherent characteristics of manipulated objects and tasks. This analysis is conducted within the context of the “CR-based taxonomy” to assess its feasibility in a practical scenario involving a small-sized CR. Based on this analysis, fixed-tip grasp, hook grasp, and power form closure grasp (PFG) with a grasp stability of 18 have the highest stability, while platform/pull/push grasp and expandable grasp have the lowest stability. Moreover, PFG and precision multi-contact grasp have superior adaptability compared to other grasp families. Also, the planar payload of selected grasp families is much higher than the spatial payload of those families; however, the grasp size remains equal for both dimensions. This endeavor lays the groundwork for more in-depth investigations into catheter applications and offers valuable guidance to medical device developers in the creation of enhanced medical instruments.
Cosmology from string T-duality and zero-point length
Authors: Luciano G. G. , Sheykhi A.
Published: July 2024

Inspired by string T-duality and taking into account the zero-point length correction, $$l_0$$

l
0

, to the gravitational potential, we construct modified Friedmann equations by applying the first law of thermodynamics on the apparent horizon of the Friedmann–Robertson–Walker (FRW) Universe. The cosmological viability of this extended scenario is investigated by studying influences on the evolution of the early Universe and performing cosmographic analysis. Furthermore, we explore the inflationary paradigm under the slow-roll condition. By testing the model against observational data, the zero-point length is constrained around the Planck scale, in compliance with the original assumption from string T-duality. We also study the growth of density perturbations in the linear regime. It is shown that the zero-point length stands out as an alternative characterization for the broken-power-law spectrum, providing a better fit for the experimental measurements than the simple power-law potential. Finally, we focus on implications for the primordial gravitational wave (PGW) spectrum. Should the zero-point length be running over energy scales, as is the case for all parameters and coupling constants in quantum gravity under renormalization group considerations, deviations from general relativity (GR) might be potentially tested through upcoming PGW observatories.
A new cubic trigonometric Nu-Spline with shape control parameter and its applications
Authors: Munir Ayesha , Samreen Shamaila , Ghaffar Abdul , Inc Mustafa , Sarfraz Muhammad
Published: July 2024

This study introduces a novel Cubic Trigonometric Nu-Spline (CTNS) with a shape parameter tailored for curve designing, ensuring geometric continuity of order 2. The CTNS possesses fundamental geometric properties such as convex hull, partition of unity, affine invariance, and variation diminishing, which are thoroughly discussed herein. Notably, our spline technique is enriched with Nu-Spline constraints, offering compelling local and global shape control capabilities. These capabilities encompass point tension, interval, or global tensions, enhancing versatility across various shape impacts. Beyond its curve designing prowess, the proposed technique exhibits commendable precision in estimating control points. Furthermore, its utility extends to diverse fields including electronics, medical image interpolation, manipulator path planning, and discrete time signal processing. Through numerical experimentation, we demonstrate the simplicity of implementing the CTNS algorithm alongside its superior accuracy compared to existing techniques.
Application of Big Data and Quantum Computing in the Secure Federated Internet of Things
Authors: Xu Lingyue , Jiang Guosong , He Bowen
Published: July 2024

Federated Internet of Things (IoT) presents both unprecedented opportunities and challenges in security and data management. This study explores the integration of big data analytics and Quantum Computing as potential solutions to address security concerns within the Federated IoT ecosystem. The study examines the implications of leveraging big data analytics to process and analyze the massive volume of data generated by IoT devices. Advanced analytics techniques, including machine learning and anomaly detection algorithms, are employed to enhance the detection and mitigation of security threats such as unauthorized access, data breaches and malicious attacks. Furthermore, the study investigates the role of Quantum Computing infrastructure in providing scalable and reliable resources for securely storing, processing and transmitting IoT data. By offloading computational tasks to quantum-based platforms, the aim is to alleviate the burden on edge devices while ensuring robust security measures are in place to safeguard sensitive information. A comprehensive review of existing literature and case studies identifies key challenges and opportunities in implementing big data and Quantum Computing solutions within the Federated IoT environment. The study also proposes potential frameworks and methodologies for integrating these technologies effectively, considering factors such as data privacy, scalability and interoperability. Overall, this research aims to advance secure IoT systems by leveraging big data analytics and cloud computing. By addressing security concerns proactively and adopting innovative approaches, the goal is to create a more resilient and trustworthy Federated IoT ecosystem, benefiting society at large.
Subclinical Coronary Artery Disease in Patients with Idiopathic Inflammatory Myopathy: An Evaluation by CT Coronary Angiography
Authors: Luk Lucas , Hui Peter Kei Tat , Tang Iris , Wong Victor Tak Lung , Pang Steve , Lao Virginia Weng Nga , So Ho
Published: July 2024

Idiopathic inflammatory myopathy (IIM) poses elevated risk of cardiovascular event and mortality, similar to other autoimmune rheumatic diseases. We conducted a cross-sectional study to examine the prevalence and risk factor of subclinical coronary artery disease (CAD) in patients with IIM, using CT coronary angiogram (CTCA). The prevalence of obstructive CAD and CAD in IIM (13.3% and 66.7%, respectively) were significantly higher than age and sex-matched controls (0% and 30%, respectively, both [Formula: see text]). Diabetes mellitus and calcium calcification score [Formula: see text] units were found to be the independent predictors of obstructive CAD. Screening of high-risk patients with aggressive treatment of cardiovascular risk factors should be considered in managing IIM patients.
Decoupling Deep Learning for Enhanced Image Recognition Interpretability
Authors: Peng Yitao , He Lianghua , Hu Die , Liu Yihang , Yang Longzhen , Shang Shaohua
Published: July 2024

The quest for enhancing the interpretability of neural networks has become a prominent focus in recent research endeavors. Prototype-based neural networks have emerged as a promising avenue for imbuing models with interpretability by gauging the similarity between image components and category prototypes to inform decision-making. However, these networks face challenges as they share similarity activations during both the inference and explanation processes, creating a tradeoff between accuracy and interpretability. To address this issue and ensure that a network achieves high accuracy and robust interpretability in the classification process, this article introduces a groundbreaking prototype-based neural network termed the “Decoupling Prototypical Network” (DProtoNet). This novel architecture comprises encoder, inference, and interpretation modules. In the encoder module, we introduce decoupling feature masks to facilitate the generation of feature vectors and prototypes, enhancing the generalization capabilities of the model. The inference module leverages these feature vectors and prototypes to make predictions based on similarity comparisons, thereby preserving an interpretable inference structure. Meanwhile, the interpretation module advances the field by presenting a novel approach: a “multiple dynamic masks decoder” that replaces conventional upsampling similarity activations. This decoder operates by perturbing images with mask vectors of varying sizes and learning saliency maps through consistent activation. This methodology offers a precise and innovative means of interpreting prototype-based networks. DProtoNet effectively separates the inference and explanation components within prototype-based networks. By eliminating the constraints imposed by shared similarity activations during the inference and explanation phases, our approach concurrently elevates accuracy and interpretability. Experimental evaluations on diverse public natural datasets, including CUB-200-2011, Stanford Cars, and medical datasets like RSNA and iChallenge-PM, corroborate the substantial enhancements achieved by our method compared to previous state-of-the-art approaches. Furthermore, ablation studies are conducted to provide additional evidence of the effectiveness of our proposed components.
Leveraging Hybrid Adaptive Sine Cosine Algorithm with Deep Learning for Arabic Poem Meter Detection
Authors: Al-shathry Najla , Al-onazi Badria , Hassan Abdulkhaleq Q A , Alotaibi Shoayee , Alotaibi Saud , Alotaibi Faiz , Elbes Mohammed , Alnfiai Mrim
Published: July 2024

Poetry is a significant aspect of any language. Many cultures and the history of nations are recognized in poems. Compared to prose, each poem has a rhythmic structure that is quite different. The language has its set of lyrical structures for poems, known as meters. Detecting the meters of Arabic poems is a complicated and lengthy procedure. The text must be encrypted using the Arudi method to classify the poem's meter, which requires complex rule-based transformation before another set of rules classifies the meters. Applying deep learning (DL) to meter classification in Arabic poems includes constructing a neural network to discern rhythmic patterns inherent in various meters. The model can extract essential features, like word lengths or syllable patterns, by tokenizing and preprocessing text datasets. Architectures such as Long Short-Term Memory Networks (LSTM) or Recurrent Neural Networks (RNNs) are fitting solutions to capture temporal relations in poetic verses. This research introduces a Hybrid Meta-heuristics with Deep Learning for the Arabic Poem Meter Detection and Classification (HMDL-APMDC) model. The main intention of the HMDL-APMDC system is to recognize various kinds of meters in Arabic poems. The HMDL-APMDC technique primarily preprocesses the input dataset to make it compatible with the classification process. Besides, the HMDL-APMDC technique applies Convolution and Attention with a Bi-directional Gated Recurrent Unit (CAT-BiGRU) for the automated recognition of meter classes. Furthermore, the adaptive sine-s-cosine particle swarm optimization (ASCA-PSO) algorithm is applied to optimize the hyperparameter tuning of the CAT-BiGRU model, enhancing the meter detection results. A detailed simulation analysis is made to highlight the improved performance of the HMDL-APMDC technique. The empirical outcomes stated that the HMDL-APMDC technique had a superior outcome of 98.53% over recent models under the MetRec dataset.
Digging into Depth and Color Spaces: A Mapping Constraint Network for Depth Super-Resolution
Authors: Sun Baoli , Guo Yanjun , Yan Tiantian , Ye Xinchen , Wang Zhihui , Li Haojie , Wang Zhiyong
Published: July 2024

Scene depth super-resolution (DSR) poses an inherently ill-posed problem due to the extremely large space of one-to-many mapping functions from a given low-resolution (LR) depth map, which possesses limited depth information, to multiple plausible high-resolution (HR) depth maps. This characteristic renders the task highly challenging, as identifying an optimal solution becomes significantly intricate amidst this multitude of potential mappings. While simplistic constraints have been proposed to address the DSR task, the relationship between LR and HR depth maps and the color image has not been thoroughly investigated. In this paper, we introduce a novel mapping constraint network (MCNet) that incorporates additional constraints derived from both LR depth maps and color images. This integration aims to optimize the space of mapping functions and enhance the performance of DSR. Specifically, alongside the primary DSR network (DSRNet) dedicated to learning LR-to-HR mapping, we have developed an auxiliary degradation network (ADNet) that operates in reverse, generating the LR depth map from the reconstructed HR depth map to obtain depth features in LR space. To enhance the learning process of DSRNet in LR-to-HR mapping, we introduce two mapping constraints in LR space: (1) the cycle-consistent constraint, which offers additional supervision by establishing a closed loop between LR-to-HR and HR-to-LR mappings, and (2) the region-level contrastive constraint, aimed at reinforcing region-specific HR representations by explicitly modeling the consistency between LR and HR spaces. To leverage the color image effectively, we introduce a feature screening module to adaptively fuse color features at different layers, which can simultaneously maintain strong structural context and suppress texture distraction through subspace generation and image projection. Comprehensive experimental results across synthetic and real-world benchmark datasets unequivocally demonstrate the superiority of our proposed method over state-of-the-art DSR methods. Our MCNet achieves an average MAD reduction of 3.7% and 7.5% over state-of-the-art DSR method for ×8 and ×16 cases on Milddleburry dataset, respectively, without incurring additional costs during inference.
Left-Right Asymmetry in Invertebrates: From Molecules to Organisms
Authors: Kuroda Reiko
Published: July 2024

Although most animals appear symmetric externally, they exhibit chirality within their body cavity, i.e., in terms of asymmetric organ position, directional organ looping, and lateralized organ function. Left-right (LR) asymmetry is determined genetically by intricate molecular interactions that occur during development. Key genes have been elucidated in several species. There are common mechanisms in vertebrates and invertebrates, but some appear to exhibit unique mechanisms. This review focuses on LR asymmetry formation in invertebrates, particularly Drosophila, ascidians, and mollusks. It aims to understand the role of the genes that are key to creating LR asymmetry and how chirality information is converted/transmitted across the hierarchies from molecules to cells and from cells to tissues.
Recombination Rate Variation in Social Insects: An Adaptive Perspective
Authors: DeLory Timothy J. , Romiguier Jonathan , Rueppell Olav , Kapheim Karen M.
Published: July 2024

Social insects have the highest rates of meiotic recombination among Metazoa, but there is considerable variation within the Hymenoptera. We synthesize the literature to investigate several hypotheses for these elevated recombination rates. We reexamine the long-standing Red Queen hypothesis, considering how social aspects of immunity could lead to increases in recombination. We examine the possibility of positive feedback between gene duplication and recombination rate in the context of caste specialization. We introduce a novel hypothesis that recombination rate may be driven up by direct selection on recombination activity in response to increases in lifespan. Finally, we find that the role of population size in recombination rate evolution remains opaque, despite the long-standing popularity of this hypothesis. Moreover, our review emphasizes how the varied life histories of social insect species provide an effective framework for advancing a broader understanding of adaptively driven variation in recombination rates.
Neutron Skins: Weak Elastic Scattering and Neutron Stars
Authors: Mammei Juliette M. , Horowitz Charles J. , Piekarewicz Jorge , Reed Brendan T. , Sfienti Concettina
Published: July 2024

The recently completed PREX-2 campaign measured the density distribution of neutrons in the lead nucleus as a function of momentum transfer (the form factor), confirmed a relatively large extent of the neutrons beyond the protons in the nucleus (the neutron skin), and provided a precise determination of the density of protons and neutrons at the center of a heavy nucleus. In turn, the measured form factor can be related to various nuclear and neutron star properties. The NICER X-ray telescope has inferred the masses and radii of some X-ray pulsars (neutron stars), although complications arise when determining these quantities independently. Further improvements in NICER have enabled simultaneous mass–radius determinations that had not previously been possible. During the next decade, measurements in astrophysics, gravitational-wave astronomy, and nuclear physics are expected to provide a wealth of more precise data. In this review, we present an overview of the current state of neutron skin measurements and offer insights into prospects for the future.
Novel Liquid Argon Time-Projection Chamber Readouts
Authors: Asaadi Jonathan , Dwyer Daniel A. , Russell Brooke
Published: July 2024

Liquid argon time-projection chambers (LArTPCs) have become a prominent tool for experiments in particle physics. Recent years have yielded significant advances in the techniques used to capture the signals generated by these cryogenic detectors. This article summarizes these novel developments for detection of ionization electrons and scintillation photons in LArTPCs. New methods to capture ionization signals address the challenges of scaling traditional techniques to the large scales necessary for future experiments. Pixelated readouts improve signal fidelity and expand the applicability of LArTPCs to higher-rate environments. Methods that leverage amplification in argon enable measurements in the keV regime and below. Techniques to enhance collection of argon scintillation photons improve calorimetry and expand the physics program for very large detectors. Future efforts aim to demonstrate systems for the combined detection of both electrons and photons.
Exotic Hadrons at LHCb
Authors: Johnson Daniel , Polyakov Ivan , Skwarnicki Tomasz , Wang Mengzhen
Published: July 2024

It has been 5 years since the data sample from the LHCb detector, the first experiment optimized for heavy-flavor physics studies at a hadronic collider, was completed. These data led to many major discoveries in exotic hadron spectroscopy, which we review in this article. We supplement the experimental results with a selection of phenomenological interpretations. As the upgraded LHCb detector is expected to collect a larger data sample starting in 2024, we also discuss the potential of the LHCb program in exotic hadron physics for the near future and beyond.
α- or β-Adrenergic blockade does not affect transplanted islet cell responses to hypoglycemia in type 1 diabetes
Authors: Rickels Michael R. , Bellin Melena D. , Stefanovski Darko , Peleckis Amy J. , Dalton-Bakes Cornelia , Markmann Eileen , Nguyen Huong-Lan , Townsend Raymond R. , Hering Bernhard J. , Naji Ali
Published: July 2024

Whether adrenergic input to islets is necessary for glucose homeostasis in humans is debated. Here, the adrenergic contribution to intrahepatically transplanted islet cell responses to hypoglycemia in individuals with type 1 diabetes was investigated through α- or β-adrenergic receptor blockade during hyperinsulinemic euglycemic-hypoglycemic clamps. Neither α- nor β-adrenergic blockage affected the suppression of endogenous insulin or activation of glucagon secretion, suggesting that sympathetic reinnervation of islet grafts is not required for posttransplant defense against hypoglycemia.
ECM Microenvironment in Vascular Homeostasis: New Targets for Atherosclerosis
Authors: Zhang Lu , Feng Qianqian , Kong Wei
Published: July 2024

Alterations in vascular extracellular matrix (ECM) components, interactions, and mechanical properties influence both the formation and stability of atherosclerotic plaques. This review discusses the contribution of the ECM microenvironment in vascular homeostasis and remodeling in atherosclerosis, highlighting Cartilage oligomeric matrix protein (COMP) and its degrading enzyme ADAMTS7 as examples, and proposes potential avenues for future research aimed at identifying novel therapeutic targets for atherosclerosis based on the ECM microenvironment.
Spatiotemporal and Species‐Crossing Transmission Dynamics of Subclade 2.3.4.4b H5Nx HPAIVs
Authors: Li Minghui , Tian Jingman , Bai Xiaoli , Song Xingdong , Zhao Zhiguo , Shi Jianzhong , Deng Guohua , Zeng Xianying , Tian Guobin , Kong Huihui , Liu Jinxiong , Li Chengjun , Li Yanbing
Published: July 2024

Subclade 2.3.4.4b H5Nx highly pathogenic avian influenza (HPAI) viruses, emerged in 2013 with multiple subtypes of H5N8, H5N1, and H5N6, had unprecedently caused a global epizootic by H5N1 since 2021, which had devasted multiple species of wild birds, poultry, and wild mammals (terrestrial and marine) with a high mortality, causing severe ecological damage. The infected wild mammals may become new “mixers” for influenza viruses, posing the potential transmission to human. Frequent outbreaks of subclade 2.3.4.4b H5Nx viruses among wild birds and poultry had exposed major gaps in our knowledge on their evolution, spatiotemporal diffusion, and species‐crossing transmission. Here, we integrated the phylogenetic and epidemiological data of subclade 2.3.4.4b H5Nx viruses in public database and used Bayesian phylodynamic analysis to reveal the pattern of the global large‐scale transmission. Phylogenic analysis demonstrated that the HA gene of these viruses diverged into two dominant clusters around 2015 and 2016. The Bayesian phylodynamic analysis illustrated that the viruses presented spatiotemporally complex transmission network with geographical and host relative expansion and recombination with different subtypes of NA segment. Spatially, the Russian Federation (Siberia) was identified as the primary hub for virus transmission, which was further facilitated by the establishment of strong epidemiological linkages between West Europe and broader regions, such as North America. As for hosts, wild Anseriformes were the primary species for the virus spillover, contributing to the spatial expansion and rapid diffusion globally of subclade 2.3.4.4b viruses. We investigated the phylogeny of subclade 2.3.4.4b H5Nx viruses and the spatiotemporal pattern of transmission with initial location and the primary host, which could provide comprehensive insights for subclade 2.3.4.4b H5Nx viruses. Due to the wild birds involved the widespread of subclade 2.3.4.4b H5Nx viruses, the epizootics in poultry are inevitable, so we highly recommend to apply the policy of culling plus with vaccination to protect the poultry industry and potentially protect the public health.
LsAc ∗‐MJ: A Low‐Resource Consumption Reinforcement Learning Model for Mahjong Game
Authors: Li Xiali , Wang Zhaoqi , Liu Bo , Dai Junxue
Published: July 2024

This article proposes a novel Mahjong game model, LsAc ∗‐MJ, designed to address challenges posed by data scarcity, difficulty in leveraging contextual information, and the computational resource‐intensive nature of self‐play zero‐shot learning. The model is applied to Japanese Mahjong for experiments. LsAc ∗‐MJ employs long short‐term memory (LSTM) neural networks, utilizing hidden nodes to store and propagate contextual historical information, thereby enhancing decision accuracy. Additionally, the paper introduces an optimized Advantage Actor‐Critic (A2C) algorithm incorporating an experience replay mechanism to enhance the model’s decision‐making capabilities and mitigate convergence difficulties arising from strong data correlations. Furthermore, the paper presents a two‐stage training approach for self‐play deep reinforcement learning models guided by expert knowledge, thereby improving training efficiency. Extensive ablation experiments and performance comparisons demonstrate that, in contrast to other typical deep reinforcement learning models on the RLcard platform, the LsAc ∗‐MJ model consumes lower computational and time resources, has higher training efficiency, faster average decision time, higher win‐rate, and stronger decision‐making ability.
Identification of ATP-Competitive Human CMG Helicase Inhibitors for Cancer Intervention that Disrupt CMG-Replisome Function
Authors: Xiang Shengyan , Craig Kendall C. , Luo Xingju , Welch Darcy L. , Ferreira Renan B. , Lawrence Harshani R. , Lawrence Nicholas J. , Reed Damon R. , Alexandrow Mark G.
Published: July 2024

The human CMG helicase (Cdc45-MCM-GINS) is a novel target for anticancer therapy. Tumor-specific weaknesses in the CMG are caused by oncogene-driven changes that adversely affect CMG function, and CMG activity is required for recovery from replicative stresses such as chemotherapy. Herein, we developed an orthogonal biochemical screening approach and identified CMG inhibitors (CMGi) that inhibit ATPase and helicase activities in an ATP-competitive manner at low micromolar concentrations. Structure–activity information, in silico docking, and testing with synthetic chemical compounds indicate that CMGi require specific chemical elements and occupy ATP-binding sites and channels within minichromosome maintenance (MCM) subunits leading to the ATP clefts, which are likely used for ATP/ADP ingress or egress. CMGi are therefore MCM complex inhibitors (MCMi). Biologic testing shows that CMGi/MCMi inhibit cell growth and DNA replication using multiple molecular mechanisms distinct from other chemotherapy agents. CMGi/MCMi block helicase assembly steps that require ATP binding/hydrolysis by the MCM complex, specifically MCM ring assembly on DNA and GINS recruitment to DNA-loaded MCM hexamers. During the S-phase, inhibition of MCM ATP binding/hydrolysis by CMGi/MCMi causes a “reverse allosteric” dissociation of Cdc45/GINS from the CMG that destabilizes replisome components Ctf4, Mcm10, and DNA polymerase-α, -δ, and -ε, resulting in DNA damage. CMGi/MCMi display selective toxicity toward multiple solid tumor cell types with K-Ras mutations, targeting the CMG and inducing DNA damage, Parp cleavage, and loss of viability. This new class of CMGi/MCMi provides a basis for small chemical development of CMG helicase-targeted anticancer compounds with distinct mechanisms of action.
Supplementary Data from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: July 2024

Numbers at risk for the association between low and high hypoxia in COAD and READ tumors (associated with the Kaplan-Meier curve shown in Figure 1D).
Figure 2 from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: July 2024

Hypoxia score associated with significant differences in microbial populations in colorectal cancer. A, Volcano plot of microbes from ORIEN and TCGA tumors showing strain differences when tumors are stratified by high vs. low hypoxia scores (tertiles). B, Fold change of microbes that show hypoxic enrichment in both ORIEN and TCGA datasets. XRT, X-ray therapy.
Figure 1 from The Tumor Microbiome Reacts to Hypoxia and Can Influence Response to Radiation Treatment in Colorectal Cancer
Authors: Benej Martin , Hoyd Rebecca , Kreamer McKenzie , Wheeler Caroline E. , Grencewicz Dennis J. , Choueiry Fouad , Chan Carlos H.F. , Zakharia Yousef , Ma Qin , Dodd Rebecca D. , Ulrich Cornelia M. , Hardikar Sheetal , Churchman Michelle L. , Tarhini Ahmad A. , Robinson Lary A. , Singer Eric A. , Ikeguchi Alexandra P. , McCarter Martin D. , Tinoco Gabriel , Husain Marium , Jin Ning , Tan Aik C. , Osman Afaf E.G. , Eljilany Islam , Riedlinger Gregory , Schneider Bryan P. , Benejova Katarina , Kery Martin , Papandreou Ioanna , Zhu Jiangjiang , Denko Nicholas , Spakowicz Daniel
Published: July 2024

Hypoxia exists in colorectal cancer and predicts poor patient outcomes after X-ray therapy. A, Hypoxia expression signature scores for the ORIEN dataset across tumor sites showing a wide distribution for COAD and READ samples. The median values are indicated with a black circle. Abbreviated cancer names are lung squamous cell carcinoma (LUSC), skin cutaneous melanoma (SKCM), small cell lung cancer (SCLC), lung adenocarcinoma (LUAD), sarcoma (SARC), pancreatic adenocarcinoma (PAAD), other colorectal cancers (Other CR), and thyroid carcinoma (THCA). B, A comparison of the Buffa score histogram of ORIEN with TCGA colorectal cancer datasets shows a similar mode in both but with a wider distribution for ORIEN. Tertiles used to designate “high” and “low” hypoxia are marked with dashed lines. C, Comparison of Buffa scores in normal adjacent and normal GTEx data compared with colon and rectal cancers (TCGA). D, For ORIEN patients receiving radiotherapy, a Kaplan–Meier curve stratifying the patient population into upper and lower hypoxia tertiles shows that hypoxic tumors have a worse patient outcome. E, Cox proportional hazard P values calculated by stratifying the hypoxia scores at every percentile (x-axis). The larger area above the horizontal dotted line indicates the strong separation of survival at a range of threshold values and is therefore more robust than single threshold analyses for small sample sizes. The total area of the Buffa hypoxia score was slightly larger than the others (inset).
Revised typification of Ctenanthe and Stromanthe (Marantaceae)
Authors: LUNA NAÉDJA KALIÉRE MARQUES , GOMES-SILVA FRANCIONE , PESSOA EDLLEY MAX , FELIX LEONARDO PESSOA
Published: July 2024

N/A
Future Change in the Contribution of Riming and Depositional Growth to the Surface Solid Precipitation in Hokkaido, Japan
Authors: Sato Yousuke , Kamada Moeka , Hashimoto Akihiro , Inatsu Masaru
Published: July 2024

This study examined future changes in the microphysical properties of surface solid precipitation over Hokkaido, Japan. A process-tracking model that predicts the mass of the hydrometeors generated by each cloud microphysical process was implemented in a meteorological model. This implementation aimed to analyze the mass fraction of hydrometeors resulting from depositional growth and the riming process to the total mass of surface solid precipitation. Results from pseudo–global warming experiments suggest two potential future changes in the characteristics of surface solid precipitation over Hokkaido. First, the rimed particles are expected to increase and be dominant over the west and northwest coast of Hokkaido, where heavy snowfall occurs primarily due to the lake effect. Second, the mass fraction from depositional growth under relatively higher temperatures is expected to increase. This increase is anticipated to be dominant over the eastern part and mountainous area of Hokkaido. Additionally, the fraction of liquid precipitation to total precipitation is expected to increase in the future. These results suggest that the microphysical properties of solid precipitation in Hokkaido are expected to be similar to those observed in the current climate over Hokuriku, the central part of Japan even in warmer climate conditions.

Significance Statement

This study examines potential future changes in the growth processes contributing to surface precipitation particles in Hokkaido, Japan. The surface solid precipitation particles in the western and eastern regions of Hokkaido are mainly generated through depositional growth that occurs within the temperature ranges −36° to −20°C and −20° to −10°C, respectively. A future shift is anticipated, with riming becoming the primary process. This shift suggests that snowfall particles will be heavier than those in the current climate, which would increase the snow-removal workload. The change in precipitation characteristics could influence adaptation and mitigation strategies for climate change in cold regions.
Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink
Authors: Davoudi Pourya , Do Duy Ngoc , Rathgeber Bruce , Colombo Stefanie , Sargolzaei Mehdi , Plastow Graham , Wang Zhiquan , Miar Younes
Published: July 2024

The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for mink.
A dual RNA-seq analyses revealed dynamic arms race during the invasion of walnut by Colletotrichum gloeosporioides
Authors: Li Xichen , Dong Yuhui , Yu Haiyi , Zhao Jing , Yang Fei , Song Weichen , Wang Changxi , Liu Jianning , Liang Qiang , Wang Yicheng , Yang Ke Qiang , Fang Hongcheng
Published: July 2024

Background

Walnut anthracnose caused by Colletotrichum gloeosporioides seriously endangers the yield and quality of walnut, and has now become a catastrophic disease in the walnut industry. Therefore, understanding both pathogen invasion mechanisms and host response processes is crucial to defense against C. gloeosporioides infection.

Results

Here, we investigated the mechanisms of interaction between walnut fruits (anthracnose-resistant F26 fruit bracts and anthracnose-susceptible F423 fruit bracts) and C. gloeosporioides at three infection time points (24hpi, 48hpi, and 72hpi) using a high-resolution time series dual transcriptomic analysis, characterizing the arms race between walnut and C. gloeosporioides. A total of 20,780 and 6670 differentially expressed genes (DEGs) were identified in walnut and C. gloeosporioides against 24hpi, respectively. Generous DEGs in walnut exhibited opposite expression patterns between F26 and F423, which indicated that different resistant materials exhibited different transcriptional responses to C. gloeosporioides during the infection process. KEGG functional enrichment analysis indicated that F26 displayed a broader response to C. gloeosporioides than F423. Meanwhile, the functional analysis of the C. gloeosporioides transcriptome was conducted and found that PHI, SignalP, CAZy, TCDB genes, the Fungal Zn (2)-Cys (6) binuclear cluster domain (PF00172.19) and the Cytochrome P450 (PF00067.23) were largely prominent in F26 fruit. These results suggested that C. gloeosporioides secreted some type of effector proteins in walnut fruit and appeared a different behavior based on the developmental stage of the walnut.

Conclusions

Our present results shed light on the arms race process by which C. gloeosporioides attacked host and walnut against pathogen infection, laying the foundation for the green prevention of walnut anthracnose.
Effects of tea infusion on selenium uptake in grapevine
Authors: Wang Jin , Xiao Yunying , Zhang Dilian , Dai Zhen , Huang Kewen , Wang Xun , Lv Xiulan , Lin Lijin
Published: July 2024

Increased selenium (Se) content in fruits can supply Se in human body, but the effects of teas on the Se uptake in fruit trees are unknown. The effects of infusions of four teas (green, black, dark, and white) on the Se uptake of grapevine were studied to promote the Se uptake in fruit trees in this study. However, only black tea infusion increased the biomass, photosynthetic pigment content, superoxide dismutase (SOD) activity, peroxidase (POD) activity, and soluble protein content of grapevine. Except for white tea infusion, other tea infusions also increased the catalase (CAT) activity of grapevine. Furthermore, the tea infusions increased the activities of adenosine triphosphate sulfurase (ATPS) and adenosine 5’-phosphosulfate reductase (APR), and decreased the activities of serine acetyltransferase (SAT) and selenocysteine methyltransferase (SMT). Only the dark and white tea infusions increased the shoot total Se content by 86.53% and 23.32%, respectively (compared with the control), and also increased the shoot inorganic Se content and shoot organic Se content. Notably, four tea infusions decreased the organic Se proportion and increased the inorganic Se proportion in grapevine. Correlation and grey relational analyses showed that the root total Se content, ATPS activity, and ARP activity were closely associated with the shoot total Se content. The principal component and cluster analyses also showed that the ATPS activity, APR activity, root total Se content, and shoot total Se content were classified into one category. These findings show that black tea infusion can promote grapevine growth, while dark and white tea infusions can promote the Se uptake in grapevine.
An evaluation of sample size requirements for developing risk prediction models with binary outcomes
Authors: Pavlou Menelaos , Ambler Gareth , Qu Chen , Seaman Shaun R. , White Ian R. , Omar Rumana Z.
Published: July 2024

Background

Risk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise model performance when the model is applied to new patients. For binary outcomes, the calibration slope (CS) and the mean absolute prediction error (MAPE) are two key measures on which sample size calculations for the development of risk models have been based. CS quantifies the degree of model overfitting while MAPE assesses the accuracy of individual predictions.

Methods

Recently, two formulae were proposed to calculate the sample size required, given anticipated features of the development data such as the outcome prevalence and c-statistic, to ensure that the expectation of the CS and MAPE (over repeated samples) in models fitted using MLE will meet prespecified target values. In this article, we use a simulation study to evaluate the performance of these formulae.

Results

We found that both formulae work reasonably well when the anticipated model strength is not too high (c-statistic < 0.8), regardless of the outcome prevalence. However, for higher model strengths the CS formula underestimates the sample size substantially. For example, for c-statistic = 0.85 and 0.9, the sample size needed to be increased by at least 50% and 100%, respectively, to meet the target expected CS. On the other hand, the MAPE formula tends to overestimate the sample size for high model strengths. These conclusions were more pronounced for higher prevalence than for lower prevalence. Similar results were drawn when the outcome was time to event with censoring. Given these findings, we propose a simulation-based approach, implemented in the new R package ‘samplesizedev’, to correctly estimate the sample size even for high model strengths. The software can also calculate the variability in CS and MAPE, thus allowing for assessment of model stability.

Conclusions

The calibration and MAPE formulae suggest sample sizes that are generally appropriate for use when the model strength is not too high. However, they tend to be biased for higher model strengths, which are not uncommon in clinical risk prediction studies. On those occasions, our proposed adjustments to the sample size calculations will be relevant.