bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging quantum‐inspired chimp optimization and deep neural networks for enhanced profit forecasting in financial accounting systems
Authors: Zhang Lin , Alsubai Shtwai , Alqahtani Abdullah , Alanazi Abed , Abualigah Laith
Published: February 2024

Deep learning and metaheuristic algorithms have recently increased in various sciences, including financial accounting information systems (FAISs). However, the existence of large datasets has dramatically increased the complexity of these hybrid networks, so to address this shortcoming, this paper aims to develop a quantum‐behaved chimp optimization algorithm (QCHOA) and deep neural network (DNN) for the prediction of the profit based on FAISs. Considering that there is no suitable dataset for the challenge, a novel dataset is developed utilizing the 15 features from the Chinese market dataset to compare more. This work designs QCHOA and five DNN‐based predictors to forecast profit. These algorithms include the universal learning CHOA (ULCHOA), the niching CHOA (NCHOA) as the two best‐modified versions of CHOA, the quantum‐behaved whale optimization algorithm (QWOA), and the quantum‐behaved grey wolf optimizer (QGWO) as the two best quantum‐behaved optimizers as well as classic CHOA. The most effective deep learning‐based predictors for forecasting the profit, ranked from highest to lowest, are DNN‐QCHOA, DNN‐NCHOA, DNN‐QWOA, DNN‐QGWO, DNN‐ULCHOA, DNN‐CHOA, and classic DNN, with corresponding ranking scores of 42, 36, 30, 24, 18, 12, and 6. As a final suggestion for profit prediction, the DNN‐CHOA is shown to be the most accurate model.
Association between pulp and periapical disease with type 2 diabetes: A bidirectional Mendelian randomization
Authors: Wang Yuqiang , Zhu Jiakang , Tang Ying , Huang Cui
Published: February 2024

Aim

This current Mendelian randomization (MR) study aims to comprehensively explore the potential bidirectional link between pulp and periapical disease (PAP) with type 2 diabetes mellitus (T2DM).

Methodology

Summary level data of European‐based population genome‐wide association studies (GWASs) were employed to undertake this MR study. With the selection of single nucleotide polymorphisms (SNPs) as the instrumental variable, the radial inverse‐variance weighted (radial IVW) method with modified second‐order weights was applied as the primary method. Additionally, a range of sensitivity analyses were conducted to investigate pleiotropy. Results from different sources of outcome were pooled by meta‐analysis with the fixed model.

Results

The results of this MR analysis did not suggest a significant impact of pulp and periapical disease on type 2 diabetes (combined OR = 1.04, 95% CI: 1.00–1.07, p = .033) and vice versa (OR = 1.04, 95% CI: 0.96–1.14, p = .329). No significant pleiotropy was detected in the final model after the removal of outliers, demonstrating the reliability of the results in our primary analysis.

Conclusions

With the limitations inherent in the present MR study, there is no significant evidence in either direction to suggest a causal association between pulp and periapical disease and type 2 diabetes mellitus.
Demographics, clinical characteristics, and treatment patterns among keloid patients: United States Electronic Health Records (EHR) Database Study
Authors: Olopoenia Abisola , Yamaguchi Yuji , Peeva Elena , Berman Brian , Jagun Oladayo , George Prethibha
Published: February 2024

Introduction

There is limited epidemiologic evidence on keloids using real‐world data, especially in the United States (US) across race and ethnicity.

Methods

We conducted a retrospective cohort study using Cerner Real‐World Data, between 2015 and 2021, to describe the demographic and clinical characteristics of US adults with keloids. Keloids were identified using a combination of ICD‐10 and (Systemized Nomenclature of Medicine‐Clinical Terms [SNOMED] codes). Demographics (including race and ethnicity), clinical characteristics, treatment patterns, and healthcare utilization were compared across keloid and non‐keloid populations.

Results

Among 5,457 keloid patients identified in the study, the majority were female (61.8%) with a mean age of 34.2 years and of non‐Hispanic Black, Hispanic, and Asian descent (P < 0.001). Relative to non‐keloid cohorts, patients with keloids had significantly higher rates of integumentary, cardiorespiratory, general, auditory, and ocular surgeries and burns (all P < 0.05). Patients with keloids were also more likely to have comorbidities like obesity, hypertension, hyperlipidemia, and diabetes (P < 0.05) when compared to those with no keloids. A large proportion of keloids were untreated; among those treated, the most common keloid treatments were medication therapy (51.5%) and surgical excision (10.6%). Non‐Hispanic Black and Hispanic keloid patients were significantly more likely to receive medication therapy and surgical excision (P < 0.001) compared to keloid patients of other races or ethnicities.

Conclusions

This study provided real‐world insights into the keloid population in the US. Our findings emphasize the high burden of keloids and its substantial impact on ethnic minorities. Given high keloid recurrence rates and limited standardized treatments for keloids, further research into keloids is crucial to the development of keloid‐specific therapeutic options.
Maximum Likelihood Estimation of Multivariate Regime Switching Student‐t Copula Models
Authors: Cortese Federico P. , Pennoni Fulvia , Bartolucci Francesco
Published: February 2024

We propose a multivariate regime switching model based on a Student‐
copula function with parameters controlling the strength of correlation between variables and that are governed by a latent Markov process. To estimate model parameters by maximum likelihood, we consider a two‐step procedure carried out through the Expectation–Maximisation algorithm. To address the main computational burden related to the estimation of the matrix of dependence parameters and the number of degrees of freedom of the Student‐
copula, we show a novel use of the Lagrange multipliers, which simplifies the estimation process. The simulation study shows that the estimators have good finite sample properties and the estimation procedure is computationally efficient. An application concerning log‐returns of five cryptocurrencies shows that the model permits identifying bull and bear market periods based on the intensity of the correlations between crypto assets.
Overcoming local anesthesia failure during routine dental treatments in children
Authors: Yagudaev Michael , Yarom Noam , Ashkenazi Malka
Published: February 2024

Background

Local anesthesia (LA) during routine dental treatment in children fails in 5%–35% of first attempts. No data, however, are available on the success rates of subsequent attempts.

Aim

To evaluate the effectiveness of primary, secondary, and tertiary LA attempts (P‐LA, S‐LA, and T‐LA, respectively) for anesthetizing molars during routine dental treatments in children.

Design

We retrospectively analyzed dental records of all children (2–18 years) who had been administered LA for the treatment of primary or permanent molars by a single paediatric dentist, between 2011 and 2022. All LAs were delivered using a computer‐controlled local anesthetic delivery (CCLAD) system.

Results

The failure rate of P‐LA in 1312 molars was 13% and correlated with age (p < .001), type of tooth (p < .001), type of treatment (p < .001), and treated arch (p < .001). The effectiveness of S‐LA for buccal infiltration, intrasulcular, inferior alveolar nerve block, greater palatine nerve block (GPNB), posterior superior alveolar nerve block (PSANB), or a combination of the last two was 50%, 87.2%, 66.7%, 63.6%, 33.3%, and 100%, respectively, and was not significantly associated with age or the type of tooth, treatment, or P‐LA.

Conclusion

The optimal choice of S‐LA for anesthetizing maxillary molars was a combination of PSANB and GPNB, whereas for mandibular molars, it was IS‐CCLAD system.
The union default: Free‐riding solutions
Authors: Harcourt Mark , Gall Gregor , Wilson Margaret
Published: February 2024

A union default would empower unions to extend membership and representation to nonunion employers but still allow workers to opt‐out and, thereby, free‐ride. Though most workers would retain membership, free‐riding could still undermine a default. First, propensity to maintain membership is likely to vary, leaving some sectors with too few members for viable, effective representation. Second, public goods research suggests free‐riding increases over time when already extant. Third, expectations of widespread future free‐riding could discourage workers from recruiting the minimum number of workers necessary to attain the default. We test two solutions—all employees being required to pay union fees or employers paying union fees—to these challenges, examining effects on intention to retain membership and support for a default. We find both have positive impacts upon reducing free‐riding.
Extending coverage to migrant workers to advance universal social protection
Authors: Kazi‐Aoul Samia , van Panhuys Clara , Brener Mariano , Ruggia‐Frick Raúl
Published: February 2024

Migration is a complex phenomenon that has significant implications for migrant workers’ access to social protection and for social security systems in both origin and destination countries. As the number of migrants continues to rise worldwide, policy makers face a multitude of challenges in adapting social protection programmes to meet the needs of an increasingly diverse population. This article explores the relationship between migration and social protection, highlighting key issues and trends that have emerged in recent years. It examines the impact of migration on social security systems in both sending and receiving countries and reports on the ways in which migration patterns can create both opportunities and challenges for these systems. The article provides an overview of social protection measures and gaps in selected countries and considers the need for policy makers to take account of the unique needs and circumstances of migrant populations. The article also explores the role of international cooperation in addressing the social protection challenges and opportunities posed by migration. It considers some of the emerging trends and innovations to support the governance of social protection schemes that may help to address some of the legal and practical challenges faced by migrant workers and social security institutions. The article highlights the importance of understanding the complex relationship between migration and social protection to develop policies and programmes that are responsive to the needs of all members of society, regardless of their country of origin or immigration status. It also underlines the importance of quality administration and good governance for the effective implementation of social protection measures. In support of the 2030 Sustainable Development Goals agenda, a call is made for continued dialogue and collaboration among policy makers and stakeholders to ensure that social security systems are equitable, effective, inclusive, and sustainable in an increasingly globalized world.
Extending social protection to migrant workers in the region of the Cooperation Council for the Arab States of the Gulf (GCC): An analysis of enablers and barriers
Authors: Lowe Christina , Hagen‐Zanker Jessica , Mazzilli Caterina , Khater Lea Bou , Pellerano Luca , Hunt Abigail
Published: February 2024

This article explores factors influencing the extension of social protection to migrant workers in the region of the Cooperation Council for the Arab States of the Gulf (GCC). While there are some indications of new momentum for reforms, we find that reforms to address gaps in legal social protection coverage have historically been hindered by the very design of the migration system, including the assumed short‐term migration time frame and over reliance on employer‐sponsored provisions, as well as the political economy in the region, which translates into a segmented labour market and associated social protection entitlements for national and migrant workers, and limited channels for migrant worker representation. Despite some new mechanisms being developed, labour dispute and judicial systems are often ineffective in protecting workers and their families when benefits are not paid. Bureaucratic, financial, language, documentation and geographic barriers constitute further obstacles to migrant workers’ access to social protection in practice. The article closes with key policy implications, including measures for: developing comprehensive legal provisions in line with international standards and principles as well as the commitments to leave no one behind and to ensure social protection for all in the United Nations 2030 Agenda for Sustainable Development; addressing practical barriers, power imbalances and outreach, monitoring and enforcement gaps; and strengthening dialogue and collaboration between all actors, including GCC and country of origin governments, employers, workers, and wider stakeholders advocating for migrant workers’ rights.
Social protection for refugees and migrants: Examining access to benefits and labour market interventions
Authors: Seyfert Karin , Alonso Héctor
Published: February 2024

The article discusses the current practices for providing social protection to refugees and migrants, focusing primarily on low‐ and middle‐income (LMICs) destination countries. It examines formal providers of social protection, including state institutions, development agencies and humanitarian organizations. In recent years, there has been an increase in funding from multilateral donors, especially in the context of the COVID–19 pandemic, leading to the establishment of national assistance programmes in LMICs that also encompass refugees and to a lesser extent migrant workers. International agencies play a crucial role in providing humanitarian cash assistance to refugees, given their status under international protection under the 1951 Refugee Convention and related protocols. Access to social insurance remains tied to formal employment. Social insurance entitlements for migrants are often restricted and refugees are typically excluded from formal employment in LMICs. Regarding labour market interventions, refugees and migrants are often excluded from national programmes, with migrants’ residence permits being often tied to employment. For refugees, international agencies take a prominent role in providing livelihood programmes aimed at enhancing income‐generating opportunities, economic inclusion and financial independence. However, the effectiveness of these interventions remains unclear, lacking rigorous evidence, and often being short‐term with limited coverage.
Commentary: A nurturing care perspective on bundling interventions – a reflection on Jeong et al. (2023)
Authors: Black Maureen M. , Kowalski Alysse J.
Published: February 2024

Bundling multiple interventions have been implemented and evaluated in response to global recognition that young children benefit from the multiple components of nurturing care. Engaging Fathers for Effective Child Nutrition and Development in Tanzania Study evaluated the impact of adding a parenting intervention to a nutrition program and involving fathers on children's development. The study found that the bundled nutrition‐parenting intervention improved children's short‐term cognitive and receptive language scores over the nutrition only intervention, with no difference between involving mother–father couples versus mothers only. This study adds to recommendations for future multiple component interventions, including to investigate the mechanisms driving interventions, to address the potential for both benefits and harms, to involve household and community caregivers, and to incorporate implementation research to transition evidence‐based programs to scale. Expanding nurturing care through multiple component interventions has the potential to promote equity by ensuring that all children have opportunities for healthy growth and development.
Advances in life‐history knowledge for 35 seahorse species from community science
Authors: Camins Elsa , Stanton Lily M. , Correia Miguel , Foster Sarah J. , Koldewey Heather J. , Vincent Amanada C. J.
Published: February 2024

Marine community science presents an important route to gather valuable scientific information while also influencing local management and policy, thus contributing to marine conservation efforts. Because seahorses are cryptic but charismatic species, they are good candidates for engaging diverse people to help overcome the many gaps in biological knowledge. We have synthesized information contributed to the community science project iSeahorse from October 2013 to April 2022 for 35 of 46 known seahorse species. We then compared the obtained results with information in existing IUCN Red List assessments, executed from 2014 to 2017, to explore the potential of iSeahorse in expanding seahorse knowledge. Our results show updated geographic ranges for 7 seahorse species, new habitats described for 24 species, observations outside the previously recorded depth range for 14 species, and new information on sex ratio for 15 species and on pregnancy seasonality for 11 species. As one example of the power of iSeahorse, contributed observations on Coleman's pygmy seahorse (Hippocampus colemani) indicated that its geographic range is thousands of square kilometers larger, its habitat more diverse, and its depth range shallower than previously known. It is clear that iSeahorse is expanding knowledge on seahorses to a level that will help improve IUCN Red List assessments. The power of community science for marine conservation in general needs to be fully explored.
Patient portal messages to support an age‐friendly health system for persons with dementia
Authors: Gleason Kelly T. , Powell Danielle , DeGennaro Athena P. , Wu Mingche M. J. , Zhang Talan , Wolff Jennifer L.
Published: February 2024

Background

Patient portal secure messaging can support age‐friendly dementia care, yet little is known about care partner use of the portal and how message concerns relate to age‐friendly issues.

Methods

We conducted a two‐part observational study. We first assessed the feasibility of automating care partner identification from patient portal messages by developing and testing a natural language processing (NLP) rule‐based classification system from portal messages of 1973 unique patients 65 and older. Second, two independent reviewers manually coded a randomly selected sample of portal messages for 987 persons with dementia to identify the frequency of expressed needs from the 4M domains of an Age‐Friendly Health System (medications, mentation, mobility, and what matters).

Results

A total of 267 (13.53%) of 1973 messages sent from older adults' portal accounts were identified through manual coding as sent by a nonpatient author. The NLP model performance to identify nonpatient authors demonstrated an AUC of 0.90. Most messages sent from the accounts of persons with dementia contained content relevant to the 4Ms (60%, 601/987), with the breakdown as follows: medications—36% (357/987), mobility—10% (101/987), mentation—16% (153/987), and what matters (aligning care with specific health goals and care preferences)—21%, 207/987.

Conclusions

Patient portal messaging offers an avenue to identify care partners and meet the informational needs of persons with dementia and their care partners.
Child and family characteristics in multisystemic therapy for child abuse and neglect (MST‐CAN): Are there associations with treatment outcome?
Authors: Buderer Corinna , Kirsch Tom , Pérez Tania , Swenson Cynthia Cupit , Fürstenau Ute , Rhiner Bruno , Schmid Marc
Published: February 2024

Evidence‐based indication for targeted interventions is a central approach in the field of child welfare and psychotherapy. This study explored the characteristics of children and families referred to Multisystemic Therapy for Child Abuse and Neglect (MST‐CAN) in Switzerland and their associations with treatment outcomes. We sought to identify subgroups of children and families referred to MST‐CAN and understand their specific needs and alignment with the program. We identified five distinct subgroups of children: (a) those characterized by clinically significant “social withdrawal” and “anxiety/depression,” (b) with multiple clinically significant emotional and behavioral problems, (c) with predominantly externalizing problems, (d) with no pathological findings at all, with parents who were less stressed and had fewer mental health problems, and (e) with mainly internalizing problems and parents whose mental health problems deteriorated during treatment. Investigating the fit of children and families referred to treatment programs can enhance the understanding of their healthcare needs and enable more individualized interventions.
Deep learning‐based skin care product recommendation: A focus on cosmetic ingredient analysis and facial skin conditions
Authors: Lee Jinhee , Yoon Huisu , Kim Semin , Lee Chanhyeok , Lee Jongha , Yoo Sangwook
Published: February 2024

Background

Recommendations for cosmetics are gaining popularity, but they are not being made with consideration of the analysis of cosmetic ingredients, which customers consider important when selecting cosmetics.

Aims

This article aims to propose a method for estimating the efficacy of cosmetics based on their ingredients and introduces a system that recommends personalized products for consumers, combined with AI skin analysis.

Methods

We constructed a deep neural network architecture to analyze sequentially arranged cosmetic ingredients in the product and incorporated skin analysis models to get the precise skin status of users from frontal face images. Our recommendation system makes decisions based on the results optimized for the individual.

Results

Our cosmetic recommendation system has shown its effectiveness through reliable evaluation metrics, and numerous examples have demonstrated its ability to make reasonable recommendations for various skin problems.

Conclusion

The result shows that deep learning methods can be used to predict the effects of products based on their cosmetic ingredients and are available for use in personalized cosmetic recommendations.
Baiting whiteness: Ziwe Fumudoh's satirical repetition
Authors: Wood Katelyn Hale
Published: February 2024

Analyzing the comedy of Ziwe Fumudoh, this paper examines how repeated comedic bits can challenge white audiences' disingenuous anti‐racism, satirize toxic white womanhood in the U.S., and script what is possible when white feminists demonstrate sincere attempts at cross‐racial connection. Each artifact from Ziwe's comedy—an interview with chef Alison Roman, a musical sketch titled “Lisa Called the Cops,” and an interview with activist Gloria Steinem—carve out productive modes of confrontation. Ziwe satirizes the ridiculousness of white performative allyship and toxic white womanhood, and demonstrates the push and pull between hope and hopelessness of structural progress in the U.S.
Hybridization and gene expression: Beyond differentially expressed genes
Authors: Runemark Anna , Moore Emily C. , Larson Erica L.
Published: February 2024

Gene expression has a key role in reproductive isolation, and studies of hybrid gene expression have identified mechanisms causing hybrid sterility. Here, we review the evidence for altered gene expression following hybridization and outline the mechanisms shown to contribute to altered gene expression in hybrids. Transgressive gene expression, transcending that of both parental species, is pervasive in early generation sterile hybrids, but also frequently observed in viable, fertile hybrids. We highlight studies showing that hybridization can result in transgressive gene expression, also in established hybrid lineages or species. Such extreme patterns of gene expression in stabilized hybrid taxa suggest that altered hybrid gene expression may result in hybridization‐derived evolutionary novelty. We also conclude that while patterns of misexpression in hybrids are well documented, the understanding of the mechanisms causing misexpression is lagging. We argue that jointly assessing differences in cell composition and cell‐specific changes in gene expression in hybrids, in addition to assessing changes in chromatin and methylation, will significantly advance our understanding of the basis of altered gene expression. Moreover, uncovering to what extent evolution of gene expression results in altered expression for individual genes, or entire networks of genes, will advance our understanding of how selection moulds gene expression. Finally, we argue that jointly studying the dual roles of altered hybrid gene expression, serving both as a mechanism for reproductive isolation and as a substrate for hybrid ecological adaptation, will lead to significant advances in our understanding of the evolution of gene expression.
Functional traits of fossil plants
Authors: McElwain Jennifer C. , Matthaeus William J. , Barbosa Catarina , Chondrogiannis Christos , O' Dea Katie , Jackson Bea , Knetge Antonietta B. , Kwasniewska Kamila , Nair Richard , White Joseph D. , Wilson Jonathan P. , Montañez Isabel P. , Buckley Yvonne M. , Belcher Claire M. , Nogué Sandra
Published: February 2024

A minuscule fraction of the Earth's paleobiological diversity is preserved in the geological record as fossils. What plant remnants have withstood taphonomic filtering, fragmentation, and alteration in their journey to become part of the fossil record provide unique information on how plants functioned in paleo‐ecosystems through their traits. Plant traits are measurable morphological, anatomical, physiological, biochemical, or phenological characteristics that potentially affect their environment and fitness. Here, we review the rich literature of paleobotany, through the lens of contemporary trait‐based ecology, to evaluate which well‐established extant plant traits hold the greatest promise for application to fossils. In particular, we focus on fossil plant functional traits, those measurable properties of leaf, stem, reproductive, or whole plant fossils that offer insights into the functioning of the plant when alive. The limitations of a trait‐based approach in paleobotany are considerable. However, in our critical assessment of over 30 extant traits we present an initial, semi‐quantitative ranking of 26 paleo‐functional traits based on taphonomic and methodological criteria on the potential of those traits to impact Earth system processes, and for that impact to be quantifiable. We demonstrate how valuable inferences on paleo‐ecosystem processes (pollination biology, herbivory), past nutrient cycles, paleobiogeography, paleo‐demography (life history), and Earth system history can be derived through the application of paleo‐functional traits to fossil plants.
Inflammation‐mediated metabolic regulation in adipose tissue
Authors: Xu Shujie , Lu Feng , Gao Jianhua , Yuan Yi
Published: February 2024

Chronic inflammation of adipose tissue is a prominent characteristic of many metabolic diseases. Lipid metabolism in adipose tissue is consistently dysregulated during inflammation, which is characterized by substantial infiltration by proinflammatory cells and high cytokine concentrations. Adipose tissue inflammation is caused by a variety of endogenous factors, such as mitochondrial dysfunction, reactive oxygen species (ROS) production, endoplasmic reticulum (ER) stress, cellular senescence, ceramides biosynthesis and mediators of lipopolysaccharides (LPS) signaling. Additionally, the gut microbiota also plays a crucial role in regulating adipose tissue inflammation. Essentially, adipose tissue inflammation arises from an imbalance in adipocyte metabolism and the regulation of immune cells. Specific inflammatory signals, including nuclear factor‐κB (NF‐κB) signaling, inflammasome signaling and inflammation‐mediated autophagy, have been shown to be involved in the metabolic regulation. The pathogenesis of metabolic diseases characterized by chronic inflammation (obesity, insulin resistance, atherosclerosis and nonalcoholic fatty liver disease [NAFLD]) and recent research regarding potential therapeutic targets for these conditions are also discussed in this review.
Feasibility of spheno‐occipital synchondrosis fusion stages as an indicator for the assessment of maxillomandibular growth: A mixed longitudinal study
Authors: Geng Jing , Zhao Guangpu , Gu Yan
Published: February 2024

Objectives

This study aimed to assess the relative growth rates (RGRs) of the maxilla and mandible at varying fusion stages of the spheno‐occipital synchondrosis (SOS), thereby elucidating the potential of SOS stages in predicting maxillomandibular growth.

Materials and Methods

A total of 320 subjects (171 boys and 149 girls), aged 6 to 18 years, were retrospectively included. Each subject had a minimum of two longitudinal cone‐beam computed tomography (CBCT) images, with no more than one interval of SOS fusion stage change between the two scans. Subjects were categorized based on their SOS fusion stages and genders. The RGRs of the maxilla and mandible at various SOS fusion stages were measured and compared using longitudinal CBCT images.

Results

Significant statistical differences were observed in maxillomandibular RGRs across various SOS fusion stages. In girls, the sagittal growth of the maxilla remained stable and active until SOS 3, subsequently exhibited deceleration in SOS 4–5 (compared to SOS 3–4, P < .05) and continued to decrease in SOS 5–6. Whereas in boys, the sagittal growth of the maxilla remained stable until SOS 4, and a deceleration trend emerged starting from SOS 5 to 6 (P < .01 compared to SOS 4–5). Mandibular growth patterns in both genders exhibited a progression of increasing‐accelerating‐decelerating rates from SOS 2 to 6. The highest RGRs for total mandibular length were observed in SOS 3–4 and SOS 4–5.

Conclusion

Spheno‐occipital synchondrosis fusion stages can serve as a valid indicator of maxillomandibular growth maturation.
Drying and fragmentation drive the dynamics of resources, consumers and ecosystem functions across aquatic‐terrestrial habitats in a river network
Authors: Sarremejane Romain , Silverthorn Teresa , Arbaretaz Angélique , Truchy Amélie , Barthélémy Nans , López‐Rojo Naiara , Foulquier Arnaud , Simon Laurent , Pella Hervé , Singer Gabriel , Datry Thibault
Published: February 2024

Rivers form meta‐ecosystems, in which disturbance and connectivity control biodiversity, ecosystem functioning and their interactions across the river network, but also across connected instream and riparian ecosystems. This aquatic–terrestrial linkage is modified by drying, a disturbance that also naturally fragments river networks and thereby modifies organism dispersal and organic matter (OM) transfers across the river network. However, little evidence of the effects of drying on river network‐scale OM cycling exists. Here, we assessed the effects of fragmentation by drying at the river meta‐ecosystem scale by monitoring leaf resource stocks, invertebrate communities and decomposition rates, across three seasons and 20 sites, in the instream and riparian habitats of a river network naturally fragmented by drying. Although instream leaf resource quantity and quality increased, leaf‐shredder invertebrate richness and abundance decreased with flow intermittence. Decomposition was, however, mainly driven by network‐scale fragmentation and connectivity. Shredder richness and invertebrate‐driven decomposition both peaked at sites with intermediate amounts of intermittent reaches upstream, suggesting that upstream drying can promote the biodiversity and functioning of downstream ecosystems. Shredder richness, however, had a negative effect on decomposition in perennial sites, likely due to interspecific competition. Leaf quantity, invertebrate communities and invertebrate‐driven decomposition became more similar between instream and riparian habitats as drying frequency increased, likely due to homogenization of environmental conditions between both habitats as the river dried. Our study demonstrates the paramount effects of drying on the dynamics of resources, communities and ecosystem functioning in rivers and presents evidence of one of the first network‐scale examples of the co‐drivers of ecosystem functions across terrestrial–aquatic boundaries.
The transcriptional landscape of Populus pattern/effector‐triggered immunity and how PagWRKY18 involved in it
Authors: Chen Sisi , Tan Shuxian , Jin Zhelun , Wu Jiadong , Zhao Yiyang , Xu Weijie , Liu Sijia , Li Yue , Huang Huahong , Bao Fei , Xie Jianbo
Published: February 2024

Plants trigger a robust immune response by activating massive transcriptome reprogramming through crosstalk between PTI and ETI. However, how PTI and ETI contribute to the quantitative or/and qualitative output of immunity and how they work together when both are being activated were unclear. In this study, we performed a comprehensive overview of pathogen‐triggered transcriptomic reprogramming by analyzing temporal changes in the transcriptome up to 144 h after Colletotrichum gloeosporioides inoculated in Populus. Moreover, we constructed a hierarchical gene regulatory network of PagWRKY18 and its potential target genes to explore the underlying regulatory mechanisms of PagWRKY18 that are not yet clear. Interestingly, we confirmed that PagWRKY18 protein can directly bind the W‐box elements in the promoter of a transmembrane leucine‐rich repeat receptor‐like kinase, PagSOBIR1 gene, to trigger PTI. At the same time, PagWRKY18 functions in disease tolerance by modulation of ROS homeostasis and induction of cell death via directly targeting PagGSTU7 and PagPR4 respectively. Furthermore, PagPR4 can interact with PagWRKY18 to inhibit the expression of PagPR4 genes, forming a negative feedback loop. Taken together, these results suggest that PagWRKY18 may be involved in regulating crosstalk between PTI and ETI to activate a robust immune response and maintain intracellular homeostasis.
Drought: A context‐dependent damper and aggravator of plant diseases
Authors: Choudhary Aanchal , Senthil‐Kumar Muthappa
Published: February 2024

Drought dynamically influences the interactions between plants and pathogens, thereby affecting disease outbreaks. Understanding the intricate mechanistic aspects of the multiscale interactions among plants, pathogens, and the environment—known as the disease triangle—is paramount for enhancing the climate resilience of crop plants. In this review, we systematically compile and comprehensively analyse current knowledge on the influence of drought on the severity of plant diseases. We emphasise that studying these stresses in isolation is not sufficient to predict how plants respond to combined stress from both drought and pathogens. The impact of drought and pathogens on plants is complex and multifaceted, encompassing the activation of antagonistic signalling cascades in response to stress factors. The nature, intensity, and temporality of drought and pathogen stress occurrence significantly influence the outcome of diseases. We delineate the drought‐sensitive nodes of plant immunity and highlight the emerging points of crosstalk between drought and defence signalling under combined stress. The limited mechanistic understanding of these interactions is acknowledged as a key research gap in this area. The information synthesised herein will be crucial for crafting strategies for the accurate prediction and mitigation of future crop disease risks, particularly in the context of a changing climate.
Periodontitis and rheumatoid arthritis—Global efforts to untangle two complex diseases
Authors: Lopez‐Oliva Isabel , Malcolm Jennifer , Culshaw Shauna
Published: February 2024

Understanding the impact of oral health on rheumatoid arthritis (RA) will inform how best to manage patients with both periodontitis and RA. This review seeks to provide an update on interventional and mechanistic investigations, including a brief summary of European Research programs investigating the link between periodontitis and RA. Recent clinical studies are described that evaluate how the treatment of one disease impacts on the other, as are studies in both humans and animal models that have sought to identify the potential mechanisms linking the two diseases.
Temporal dynamics of autonomic nervous system responses under cognitive‐emotional workload in obsessive‐compulsive disorder
Authors: Portnova Galina , Khayrullina Guzal , Martynova Olga
Published: February 2024

Dysregulation of the autonomic nervous system (ANS) is commonly observed in various mental disorders, particularly when individuals engage in prolonged cognitive‐emotional tasks that require ANS adjustment to workload. Although the understanding of the temporal dynamics of sympathetic and parasympathetic tones in obsessive‐compulsive disorder (OCD) is limited, analyzing ANS reactions to cognitive‐emotional workload could provide valuable insights into one of the underlying causes of OCD. This study investigated the temporal dynamics of heart rate (HR) and pupil area (PA) while participants with OCD and healthy volunteers solved antisaccade tasks, with affective pictures serving as central fixation stimuli. The data of 31 individuals with OCD and 30 healthy volunteers were included in the study, comprising three separate blocks, each lasting approximately 8 min. The results revealed an increase in sympathetic tone in the OCD group, with the most noticeable rise occurring during the middle part of each block, particularly during the presentation of negative stimuli. Healthy volunteers demonstrated adaptive temporal dynamics of HR and PA from the first block to the last block of tasks, whereas individuals with OCD exhibited fewer changes over time, suggesting a reduced adaptation of the ANS sympathetic tone to cognitive‐emotional workload in OCD.
Suicide Crisis Syndrome: A systematic review
Authors: Melzer Laura , Forkmann Thomas , Teismann Tobias
Published: February 2024

Background

The objective of this systematic review is to describe the scientific evidence for the Suicide Crisis Syndrome (SCS), a presuicidal cognitive and affective state consisting of five symptomatic dimensions: entrapment, affective disturbance, loss of cognitive control, hyperarousal, and social withdrawal. The aim of this article is to summarize the emerging literature on the SCS and to assess the extent to which a uniform syndrome can be assumed.

Methods

A systematic literature search was conducted in three different databases (PubMed, PsycInfo, and Google Scholar) using the search terms “Suicide Crisis Inventory,” “Suicide Crisis Syndrome,” “Narrative Crisis Model of Suicide,” and “Suicide Trigger State.”

Results

In total, 37 articles from 2010 to 2022 were identified by search criteria. Twenty‐one articles published between 2017 and 2022 were included in the systematic review. All but three studies were conducted in the United States and examined clinical samples of adult high‐risk psychiatric in‐ and outpatients. Sample sizes ranged from N = 170 to 4846. The findings confirm the unidimensional structure of the proposed disorder and support the predictive validity for short‐term suicidal behavior above and beyond suicidal ideation.

Conclusion

Despite the promising predictive validity of the SCS, a precise prediction of future suicidal behavior remains difficult.
The MpNAC72/MpERF105‐MpMYB10b module regulates anthocyanin biosynthesis in Malus ‘Profusion’ leaves infected with Gymnosporangium yamadae
Authors: Wang Yu , An Hong , Yang Yue , Yi Cheng , Duan Ying , Wang Qian , Guo Yannan , Yao Lina , Chen Mingkun , Meng Jiaxin , Wei Jun , Hu Chenyang , Li Houhua
Published: February 2024

Apple rust is a serious fungal disease affecting Malus plants worldwide. Infection with the rust pathogen Gymnosporangium yamadae induces the accumulation of anthocyanins in Malus to resist rust disease. However, the mechanism of anthocyanin biosynthesis regulation in Malus against apple rust is still unclear. Here, we show that MpERF105 and MpNAC72 are key regulators of anthocyanin biosynthesis via the ethylene‐dependent pathway in M. ‘Profusion’ leaves under rust disease stress. Exogenous ethephon treatment promoted high expression of MpERF105 and MpNAC72 and anthocyanin accumulation in G. yamadae‐infected M. ‘Profusion’ leaves. Overexpression of MpERF105 increased the total anthocyanin content of Malus plant material and acted by positively regulating its target gene, MpMYB10b. MpNAC72 physically interacted with MpERF105 in vitro and in planta, and the two form a protein complex. Coexpression of the two leads to higher transcript levels of MpMYB10b and higher anthocyanin accumulation. In addition, overexpression of MpERF105 or MpNAC72 enhanced the resistance of M. ‘Profusion’ leaves to apple rust. In conclusion, our results elucidate the mechanism by which MpERF105 and MpNAC72 are induced by ethylene in G. yamadae‐infected M. ‘Profusion’ leaves and promote anthocyanin accumulation by mediating the positive regulation of MpMYB10b expression.
Remittances and inequality: A meta‐analytic investigation
Authors: Anwar Amar , Mang Colin F. , Plaza Sonia
Published: February 2024

This article provides a comprehensive meta‐analysis that addresses an important gap in the literature by examining the relationship between remittances and inequality in recipient countries. While numerous empirical studies have explored this relationship, there has been no prior attempt to systematically and rigorously synthesise the evidence. This study employs advanced meta‐analysis techniques, such as Bayesian model averaging, to analyse 578 estimates reported in 45 studies. The overall finding is that the effect of remittances on inequality is negative but economically small. However, significant regional variations exist, with remittances contributing to increased inequality in South Asia, while having a substantial inequality‐reducing effect in East Asia, Eastern Europe and Latin America. In the Middle East and North Africa and Sub‐Saharan Africa, only marginal economic impact is found. We recommend that future studies should control for educational attainment, income level and institutional quality to improve the accuracy of their estimates.
Comparison of bias adjustment in meta-analysis using data-based and opinion-based methods
Authors: Stone Jennifer C. , Furuya-Kanamori Luis , Aromataris Edoardo , Barker Timothy H. , Doi Suhail A.R.
Published: February 2024

Introduction:

Several methods exist for bias adjustment of meta-analysis results, but there has been no comprehensive comparison with unadjusted methods. We compare 6 bias-adjustment methods with 2 unadjusted methods to examine how these different methods perform.

Methods:

We re-analyzed a meta-analysis that included 10 randomized controlled trials. Two data-based methods (Welton’s data-based approach and Doi’s quality effects model) and 4 opinion-informed methods (opinion-based approach, opinion-based distributions combined statistically with data-based distributions, numerical opinions informed by data-based distributions, and opinions obtained by selecting areas from data-based distributions) were used to incorporate methodological quality information into the meta-analytical estimates. The results of these 6 methods were compared with 2 unadjusted models: the DerSimonian-Laird random effects model and Doi’s inverse variance heterogeneity model.

Results:

The 4 opinion-based methods returned the random effects model estimates with wider uncertainty. The data-based and quality effects methods returned different results and aligned with the inverse variance heterogeneity method with some minor downward bias adjustment.

Conclusion:

Opinion-based methods seem to only add uncertainty rather than bias adjust.
A Hybrid Perspective of Vision-Based Methods for Estimating Structural Displacements Based on Mask Region-Based Convolutional Neural Networks
Authors: Xu Chuanchang , Lai Cass Wai Gwan , Wang Yangchun , Hou Jiale , Shao Zhufeng , Cai Enjian , Yang Xingjian
Published: February 2024

Vision-based methods have shown great potential in vibration-based structural health monitoring (SHM), which can be classified as target-based and target-free methods. However, target-based methods cannot achieve subpixel accuracy, and target-free methods are sensitive to environmental effects. To this end, this paper proposed a hybrid perspective of vision-based methods for estimating structural displacements, based on Mask region-based convolutional neural networks (Mask R-CNNs). In proposed methods, Mask R-CNN is used to first locate the target region and then target-free vision-based methods are used to estimate structural displacements from the located target. The performances of proposed methods were validated in a shaking table test of a cold formed steel (CFS) wall system. It can be seen that Mask R-CNN can significantly improve the accuracy of feature point matching results of the target-free method. The comparisons of estimated structural displacements using proposed methods are conducted and detailed into accuracy, stability, and computational burden, to guide the selection of the proper proposed method for the specific problem in vibration-based SHM. Proposed methods can also achieve even 1/15 pixel-level accuracy. Moreover, different image denoising methods in different lighting conditions are compared.
Gas Path Fault Diagnosis of Turboshaft Engine Based on Novel Transfer Learning Methods
Authors: Zhao Yong-Ping , Jin Hui-Jie , Liu Hao
Published: February 2024

Data-driven fault diagnosis method is widely used in the field of engine health management, which uses engine sensor data as input and engine faulty components as output for component-level fault diagnosis of the engine. The application premise of the general data-driven fault diagnosis method is that all data come from the same working conditions, that is, they belong to the same distribution. However, this assumption is not valid in the actual engine fault diagnosis, because the engine state will change with the increase of running time. In the meantime, collecting engine data is usually expensive, time-consuming, and laborious. To solve these problems, extreme learning machine (ELM)-based two transfer learning methods for fault diagnosis of turboshaft engines are proposed in this paper. One is joint solving ELM (JSELM), which regards the information of the target domain and source domain as similar and different parts, respectively, and knowledge is extracted from them at the same time. The other is model transfer-based ELM (MTELM), which uses the idea of pretraining. First, a general ELM classifier is trained with the source domain data and then fine-tuned with the target domain data. Both methods have a good real-time performance as the traditional ELM. When there are a few data in the target domain, they achieve much better classification accuracy than traditional ELM. Finally, experiments are carried out with turboshaft engine simulation data. The results show that both methods are effective, especially MTELM, which has better classification accuracy.