bluuebunny/crossref_metadata_2025 huggingface dataset:
Myasthenia Gravis: utilising cross-platform quantitative content analysis to uncover and validate unmet needs
Authors: Legg David , Meisel Andreas , Stein Maike , Gerischer Lea , Herdick Meret , Krüger Daniela , Mergenthaler Philipp , Masanneck Lars , Lehnerer Sophie
Published: September 2024

Background

Recent years have seen a rapid growth in the number of online health communities targeted at patients with long-term conditions. Myasthenia Gravis (MG) is a rare neurological disease for which such communities have not been analysed before. The aim of this study was to better understand the needs of the MG population through the collation and categorisation of questions that users of MG social media were asking fellow users on these platforms.

Methodology

Systematic observation of four MG Facebook groups was conducted over a 2-month period. Groups were selected for analysis based on the following systematic criteria: Language (English), Membership (≥ 5,000 members), group activity (≥ 2 posts per week), target audience (general MG population) and researcher engagement with group administrators. The study protocol was reviewed by the institutional review board of the Charité—Universitätsmedizin Berlin (EA2/106/22). During the observation period, data were extracted from individual posts featuring questions made across each group using a systematic and objective coding scheme. All data points were coded directly from the source and collated into an SPSS database (IBM SPSS V.27, SPSS). Absolute and relative frequencies were calculated for categorical variables and proportions were compared across groups to validate the credibility and relevance of different requests.

Results

Of the 2,062 posts observed (N = 2,062), 1,392 featured questions (n = 1,392). Questions were asked by 787 unique users: 531 were identified as one-time users (67%) and 256 were identified as repeat users (33%). Six hundred and fifty six users were classified as presumed diagnosed (83%), 61 as seeking diagnosis (8%), 69 as family and/or friends (9%) and as other (<0%). Eight unique categories of questions were observed including MG treatment (31%), Symptoms (19%), Living with MG (12%), Diagnosis (10%), non-MG medication (11%), Tests (8%), Location (4%) and Other (4%).

Conclusion

Members of the MG population make active use of online health communities to seek and discuss practical information concerning various aspects of the disease, its diagnosis and care. The openness and willingness of the sample population to share sensitive medical information shows a high need for information not entirely catered to by the medical profession.
The mechanism and potential therapeutic target of piezo channels in pain
Authors: Xu Yi , Wang Yuheng , Mei Shuchong , Hu Jialing , Wu Lidong , Xu Luyang , Bao Lijie , Fang Xiaowei
Published: September 2024

Pain is a common symptom of many clinical diseases; it adversely affects patients’ physical and mental health, reduces their quality of life, and heavily burdens patients and society. Pain treatment is one of the most difficult problems today. There is an urgent need to explore the potential factors involved in the pathogenesis of pain to improve its diagnosis and treatment rate. Piezo1/2, a newly identified mechanosensitive ion channel opens in response to mechanical stimuli and plays a critical role in regulating pain-related diseases. Inhibition or downregulation of Piezo1/2 alleviates disease-induced pain. Therefore, in this study, we comprehensively discussed the biology of this gene, focusing on its potential relevance in pain-related diseases, and explored the pharmacological effects of drugs using this gene for the treatment of pain.
Unraveling the pathogenic mechanism of a novel filamin a frameshift variant in periventricular nodular heterotopia
Authors: Xue Chunran , Wang Yishu , Peng Jing , Feng Sisi , Guan Yangtai , Hao Yong
Published: September 2024

Background

Periventricular nodular heterotopia (PVNH) is a neuronal migration disorder caused by the inability of neurons to move to the cortex. Patients with PVNH often experience epilepsy due to ectopic neuronal discharges. Most cases of PVNH are associated with variations in filamin A (FLNA), which encodes an actin-binding protein. However, the underlying pathological mechanisms remain unclear.

Methods

Next-generation sequencing was performed to detect variants in the patient with PVNH, and the findings were confirmed using Sanger sequencing. Iterative threading assembly refinement was used to predict the structures of the variant proteins, and the search tool for the retrieval of interacting genes/proteins database was used to determine the interactions between FLNA and motility-related proteins. An induced pluripotent stem cell (iPSC) line was generated as a disease model by reprogramming human peripheral blood mononuclear cells. The FLNA expression in iPSCs was assessed using western blot and quantitative real-time polymerase chain reaction (qRT-PCR). Immunofluorescence analysis was performed to determine the arrangement of F-actin.

Results

A novel FLNA frameshift variant (NM_001456.3: c.1466delG, p. G489Afs*9) was identified in a patient with PVNH and epilepsy. Bioinformatic analysis indicated that this variation was likely to impair FLNA function. Western blot and qRT-PCR analysis of iPSCs derived from the patient’s peripheral blood mononuclear cells revealed the absence of FLNA protein and mRNA. Immunofluorescence analysis suggested an irregular arrangement and disorganization of F-actin compared to that observed in healthy donors.

Conclusion

Our findings indicate that the frameshift variant of FLNA (NM_001456.3: c.1466delG, p. G489Afs*9) impairs the arrangement and organization of F-actin, potentially influencing cell migration and causing PVNH.
Weakly supervised localization model for plant disease based on Siamese networks
Authors: Chen Jiyang , Guo Jianwen , Zhang Hewei , Liang Zhixiang , Wang Shuai
Published: September 2024

Problems

Plant diseases significantly impact crop growth and yield. The variability and unpredictability of symptoms postinfection increase the complexity of image-based disease detection methods, leading to a higher false alarm rate.

Aim

To address this challenge, we have developed an efficient, weakly supervised agricultural disease localization model using Siamese neural networks.

Methods

This model innovatively employs a Siamese network structure with a weight-sharing mechanism to effectively capture the visual differences in plants affected by diseases. Combined with our proprietary Agricultural Disease Precise Localization Class Activation Mapping algorithm (ADPL-CAM), the model can accurately identify areas affected by diseases, achieving effective localization of plant diseases.

Results and conclusion

The results showed that ADPL-CAM performed the best on all network architectures. On ResNet50, ADPL-CAM’s top-1 accuracy was 3.96% higher than GradCAM and 2.77% higher than SmoothCAM; the average Intersection over Union (IoU) is 27.09% higher than GradCAM and 19.63% higher than SmoothCAM. Under the SPDNet architecture, ADPL-CAM achieves a top-1 accuracy of 54.29% and an average IoU of 67.5%, outperforming other CAM methods in all metrics. It can accurately and promptly identify and locate diseased leaves in crops.
Development and validation of the Arabic children’s strong communication scale: a pilot study
Authors: Alhamami Munassir , Alduais Ahmed , Alasmari Muhammad , Qasem Fawaz
Published: September 2024

Background

The assessment of communication skills in Arabic-speaking children has been challenged by a lack of culturally and linguistically appropriate tools. The Arabic children’s strong communication scale (ACSCS) was developed in response to this need, adapting the children’s communication checklist-2 (CCC-2) to better suit the Arabic context.

Aims

This study aimed to validate the ACSCS and establish its utility in measuring communication strengths among Arabic-speaking children.

Methods

A total of 102 participants completed the questionnaire, which included relatives, teachers, and speech therapists of children aged 4–16. Twenty-two items were developed that targeted children communication strengths. The items were based on a theoretical framework that encompassed language proficiency, social communication, and behavioral aspects. Exploratory factor analysis (EFA) and confirmatory composite analysis (CCA) were employed to validate the structure of the ACSCS. The scale’s reliability was tested using Cronbach’s alpha and composite reliability, while its validity was assessed through convergent and discriminant validity measures.

Results

The EFA and CCA confirmed a clear distinction of communication strengths. Reliability analyses indicated high internal consistency for the ACSCS. Discriminant validity was established, showing that the ACSCS accurately measures distinct facets of communication skills.

Conclusion

The ACSCS is a valid and reliable instrument for assessing communication skills in Arabic-speaking children, reflecting strengths across various domains.

Implications

The scale has significant implications for educational and clinical settings, providing a culturally sensitive tool for practitioners and researchers to assess and support the communication development of Arabic-speaking children.
Embedding positive psychology into curriculum to promote posttraumatic growth, psychological flexibility, and socio-emotional competencies in higher education
Authors: Chim Kathleen , Lai JoJo T. C. , Chan Benjamin Tak Yuen
Published: September 2024

Background

The benefits of positive psychology interventions (PPIs) have become increasingly popular. While there is an emerging evidence base on the effectiveness of applying positive psychology in curriculum as preventive, early mental health intervention for higher education students, little is known about the content and pedagogy in these promising courses.

Objective

This article describes (a) the rationale for and development of a positive psychology course embedded into the curriculum that aims to foster posttraumatic growth, psychological flexibility, and socio-emotional competencies for higher education students; and (b) a mixed-method non-randomised pre-post study to evaluate the effectiveness of the positive psychology course in achieving positive participant outcomes.

Methods

Higher education students from different disciplines will be enrolled to a general education course, “Positive Psychology and Personal Growth”, where they will learn progressive topics and complete summative assessments related to key areas in positive psychology. In addition to lectures, participants will engage in constructivist-based experiential activities that are guided by research on PPIs, life-design interventions and constructivist learning principles. The primary outcome is posttraumatic growth, and the secondary outcomes are psychological flexibility, and socio-emotional competencies.

Expected results

We hypothesised that after the curriculum-embedded PPI, participants will have significantly higher levels of posttraumatic growth, psychological flexibility, and socio-emotional competencies. Results derived from the questionnaire survey will be supported by corroborating evidence identified from qualitative analysis of participants' summative assessments and follow-up semi-structured interviews on their perceptions of the present course.

Discussion

The current study will fill in a gap in existing intervention research and practise in curriculum-embedded PPIs and promote research transparency and pedagogical advancement. The intervention provides guidance and recommendations for educators to consider embedding positive psychology into the formal curriculum as cost-effective, low-intensity, structured, and sustainable educational interventions for higher education students.
The transnational mental health burden of Haiti’s alleged collapse: preliminary findings from The Haitian Well-Being Study
Authors: Blanc Judite , Carrenard Niara J. , Auguste Evan , Luma Sherryn , Francois Laura , Bigdeli Tim , Jean-Louis Girardin , Duthely Lunthita
Published: September 2024

Background

Transnational drug trafficking, political unrest, gang violence, and paramilitarism, which are pervasive in Haiti, have resulted in a mental health crisis for the broader Haitian community. This study explores the mental well-being of Haitians in Haiti and the United States by identifying barriers and facilitators to mental health through the lived experiences of men and women.

Method

Four Focus group discussions conducted in April and November 2023 engaged 28 participants (20 women and eight men) aged between 23 and 60 years from locations in Haiti (Port-au-Prince, Cite Soleil, Cayes, Cap-Haitien, Saint-Marc) and the United States. Discussions revolved around the definition of mental health, stressors, coping mechanisms, risk and protective factors, and barriers to mental health care.

Results

Six principal themes emerged: 1- Chronic Traumatic Stress: continued violence, political instability, unemployment, lack of social support, adverse childhood experiences, family separation, and forced displacement were significant sources of stress. 2- Increased Health Burden: Participants reported experiencing chronic physical and psychological symptoms [i.e., hypertension, anxiety, depression, sleep issues, substance abuse, suicidal ideations, characteristics of post-traumatic stress disorder (PTSD)], which were attributed to Haiti’s social, political, and infrastructure collapse. 3- Risk Factors: limited access to mental health services, pervasive hopelessness, scarcity of opportunities, and stigma were identified as significant risks. 4- Future Uncertainty: widespread concerns regarding the future predominated. 5- Multigenerational Concerns: Significant anxiety concerning the mental health and development of children, as well as the functionality of mental health practitioners, was noted. 6- Coping and Protective Factors: Effective coping strategies include mental stimulation, peer support, managing digital consumption, engaging in leisurely activities, such as listening to music, and faith/spirituality.

Conclusion

The study’s findings underscore the sociopolitical and economic crisis in Haiti, which has resulted in violence and a dismantle of political, educational, financial, and health infrastructures. These factors were identified as the primary source of chronic distress, contributing to widespread mental health issues, adverse physical symptoms, and disruption in daily life. The implications for practice, healing, research & policy are discussed.
How the acceleration phase influences energy flow and the resulting joint moments of the throwing shoulder in the deceleration phase of the javelin throw
Authors: Köhler Hans-Peter , Schödlbauer Maximilian , Witt Maren
Published: September 2024

Introduction

The throwing motion in the javelin throw applies high loads to the musculoskeletal system of the shoulder, both in the acceleration and deceleration phases. While the loads occurring during the acceleration phase and their relationship to kinematics and energy flow have been relatively well investigated, there is a lack of studies focusing the deceleration phase. Therefore, the aim of this study is to investigate how the throwing arm is brought to rest, which resultant joint torques are placed on the shoulder and how they are influenced by the kinematics of the acceleration phase.

Methods

The throwing movement of 10 javelin throwers were recorded using a 12-infrared camera system recording at 300 Hz and 16 markers placed on the body. Joint kinematics, kinetics and energy flow were calculated between the touchdown of the rear leg and the timepoint of maximum internal rotation after release +0.1 s. Elastic net regularization regression was used to predict the joint loads in the deceleration phase using the kinematics and energy flow of the acceleration phase.

Results

The results show that a significant amount of energy is transferred back to the proximal segments, while a smaller amount of energy is absorbed. Furthermore, relationships between the kinematics and the energy flow in the acceleration phase and the loads placed on the shoulder joint in the deceleration phase, based on the elastic net regularized regression, could be established.

Discussion

The results indicate that the loads of the deceleration phase placed on the shoulder can be influenced by the kinematics of the acceleration phase. For example, an additional upper body forward tilt can help to increase the braking distance of the arm and thus contribute to a reduced joint load. Furthermore, the energy flow of the acceleration phase can be linked to joint stress. However, as previously demonstrated the generation of mechanical energy at the shoulder seems to have a negative effect on shoulder loading while the transfer can help optimize the stress. The results therefore show initial potential for optimizing movement, to reduce strain and improve injury prevention in the deceleration phase.
Concussion management and concussion recovery in Gaelic games: a qualitative analysis
Authors: Daly Ed , Ryan Lisa
Published: September 2024

Background

The purpose of this qualitative research study was to interview current and retired Gaelic games athletes to understand the current landscape of concussion recovery in Gaelic sports from the athlete perspective.

Methods

A grounded theory methodology was employed to explore the experiences of a cohort of Gaelic games athletes (n = 22) regarding recovery from concussion, the levels of concussion awareness in Gaelic sports and their opinions on current concussion identification protocols. The study's data were gathered through semi-structured interviews.

Results

Two major themes were identified, (1) Male and female athletes experience a range of acute and chronic symptoms post-SRC and (2) Gaelic sports athletes are expected to demonstrate constant allegiance and commitment to the GAA. These themes were further divided into categories and subcategories.

Conclusion

Based on the experiences of the cohort of Gaelic sports athletes, there exists a wide variation of SRC symptomology in the acute, and chronic (post-concussion syndrome) phases. In many cases, there are reports of long-term side effects associated with the perceived mismanagement or misdiagnosis of SRC in Gaelic sports. Gaelic sports athletes require a more robust SRC management system to support and manage SRC in the acute, chronic and long-term phases.
Long-Term Exposure to Particulate Matter and Mortality: An Update of the WHO Global Air Quality Guidelines Systematic Review and Meta-Analysis
Authors: Orellano Pablo , Kasdagli Maria-Iosifina , Pérez Velasco Román , Samoli Evangelia
Published: September 2024

Objectives

For the development of the 2021 global air quality guidelines, the World Health Organization (WHO) commissioned a series of systematic reviews and meta-analyses to assess the association between exposure to air pollution and all-cause and cause-specific mortality. One of these reviews, which we aim to update, focused on the effects of long-term exposure to PM2.5 and PM10 on all-cause and cause-specific mortality.

Methods

The protocol for this study was registered in PROSPERO (CRD42023425327). We searched the PubMed and Embase databases for studies published between September 2018 and May 2023. Study-specific effects were pooled using random-effects models.

Results

We included 106 studies in the meta-analysis, 46 studies from the previous review and 60 from this update. All exposure-outcome pairs analysed showed positive and significant associations, except for PM10 and cerebrovascular mortality. The certainty of the evidence was rated as high for the majority of exposure-outcome pairs.

Conclusion

We included a large number of new cohorts, and provided new concentration-response functions that will inform WHO advice on the use of this information for air pollution health risk assessments.
Research on Topic Mining and Evolution Trends of Functional Agriculture Based on the BERTopic Model
Authors: Lin Qiao , Xin Zhulin , Peng Shuang , Zhao Ruixue , Nie Yingli , Chen Youtao , Yin Xuebin , Xian Guojian , Zhang Qiang
Published: September 2024

Based on the BERTopic model, this study analyzes 15,744 scientific papers in the field of functional agriculture from 1995 to 2024 to uncover core themes and evolutionary trends in global functional agriculture, and particularly focuses on revealing the developmental trajectory in China. The results indicate that global functional agriculture research is characterized by diverse themes and intensive study, forming a multi-topic cross-network centered on plant chemical extraction and agricultural soil research, with a focus on food nutrition, human health, and environmental protection. By contrast, China’s functional agriculture research demonstrates a more focused and in-depth approach, concentrating on functional food development and agricultural environmental protection themes, with notable growth trends in areas such as selenium-enriched products and resistant starch. Combined with China’s agricultural development environment, this study makes the following suggestions for the development of functional agriculture in China: (1) Promoting interdisciplinary cooperation between functional agriculture and other technologies. (2) Developing agricultural products with Chinese characteristics and forming Chinese functional agricultural product brands. (3) Utilizing smart farming technology to boost functional agriculture.
Influence and Mechanism of Fertilization and Irrigation of Heavy Metal Accumulation in Salinized Soils
Authors: Yu Dandan , Miao Qingfeng , Shi Haibin , Feng Zhuangzhuang , Feng Weiying , Li Zhen , Gonçalves José Manuel
Published: September 2024

The impact of fertilization and irrigation on heavy metal accumulation in saline–alkali soil and its underlying mechanisms are critical issues given the constraints that soil salinization places on agricultural development and crop quality. This study addressed these issues by investigating the effects of adjusting organic fertilizer types, proportions, and irrigation volumes on the physicochemical properties of lightly to moderately saline–alkali soils and analyzing the interaction mechanisms between microorganisms and heavy metals. The results indicate that the rational application of organic fertilizers combined with supplemental irrigation can mitigate soil salinity accumulation and water deficits, and reduce the soil pH, thereby enhancing soil oxidation, promoting nitrogen transformation and increasing nitrate–nitrogen levels. As the proportion of organic fertilizers increased, heavy metal residues, enrichment, and risk indices in the crop grains also increased. Compared to no irrigation, supplemental irrigation of 22 mm during the grain-filling stage increased soil surface Cd content, Zn content, and the potential ecological risk index (HRI) by 10.2%, 3.1%, and 8%, respectively, while simultaneously reducing the heavy metal content in grains by 12–13.5% and decreasing heavy metal enrichment. Principal component analysis revealed the primary factors influencing Cu and Zn residues and Cd accumulation in the crop grains. Soil salinity was significantly negatively correlated with soil pH, organic matter, total nitrogen, and ammonium nitrogen, whereas soil organic matter, total nitrogen, ammonium nitrogen, soil pH, oxidation–reduction potential, soluble nitrogen, and microbial biomass nitrogen were positively correlated. The accumulation and residues of Zn and Cu in the soil were more closely correlated with the soil properties compared to those of Cd. Specifically, Zn accumulation on the soil surface was primarily related to aliphatic organic functional groups, followed by soil salinity. Residual Zn in the crop grains was primarily associated with soil oxidation–reduction properties, followed by soil moisture content. The accumulation of Cu on the soil surface was mainly correlated with the microbial biomass carbon (MBC), whereas the residual Cu in the crop grains was primarily linked to the soil moisture content. These findings provide theoretical insights for improving saline–alkali soils and managing heavy metal contamination, with implications for sustainable agriculture and environmental protection.
RETRACTED: Babu et al. Estimating the Crop Acreage of Menthol Mint Crop from Remote Sensing Satellite Imagery Using ANN. Agronomy 2023, 13, 951
Authors: Babu Jampani Satish , Ch Smitha Chowdary , Bhattacharyya Debnath , Byun Yungcheol
Published: September 2024

The Agronomy Editorial Office retracts the article entitled “Estimating the Crop Acreage of Menthol Mint Crop from Remote Sensing Satellite Imagery Using ANN” [...]
Trypsin Inhibitor of Ricinus communis L. (Euphorbiaceae) in the Control of Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae)
Authors: Ramos Vinicius O. , Alves Dejane S. , Carvalho Geraldo A. , Santos Custódio D. , Cavalheiro Alberto J. , Oliveira Júlia A. C. , Marques Tamara R. , Simão Anderson A. , Saczk Adelir A.
Published: September 2024

The fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), is a polyphagous insect of various agricultural crops. The methods used for its control have led to the selection of resistant insect populations, which justifies the search for new alternatives for the management of this insect. Accordingly, in the present study, trypsin inhibitors present in the leaf extract of Ricinus communis (Euphorbiaceae) were investigated for their activity against S. frugiperda. Chemometric optimization methods were developed for the extraction, purification, identification, and structural characterization of the inhibitors. In addition, the effect of R. communis extract on S. frugiperda development was evaluated. Inhibitor extraction was chemometrically optimized, yielding an extract with an antitryptic activity of 94,837.14 mUIT g−1. The R. communis extract was purified and found to contain two compounds (adenosine and ricinine) exhibiting trypsin inhibitor activity. However, after purification, only ricinine inhibited S. frugiperda trypsin in vitro (103.21 mUIT mg−1). The extract was added to the diet of S. frugiperda larvae, resulting in reduced digestion, increased protein in the feces (control = 12,571 μg protein/mg feces; 1818.2 g mL−1 = 16,867 μg protein/mg feces), and insect mortality. At the highest concentration, the treatment led to an LT50 of 15.9 days and a cumulative survival rate of 18.5%. Based on the results of this study, it is possible that ricinine binds to the catalytic site of trypsin, causing the mortality of S. frugiperda larvae.
Impacts of Various Straw-Returning Techniques on the Chemical Characteristics and Bacterial Diversity of Soil
Authors: Hou Wenfeng , Wang Dong , Li Yanan , Li Qi , Liu Shuxia , Wang Chengyu
Published: September 2024

Straw returning enhances soil fertility and increases corn yield, but the impact on soil fertility varies with different incorporation methods. To explore the optimal straw-returning method, this study, based on a long-term field experiment, investigated the following different corn-straw-returning methods: deep plowing and straw returning (B), rotary tillage and straw returning (RT), crushing and mixing straw returning (TM), pulverized cover straw returning (C), high-stubble-retention straw returning (LHS), strip cover (S), and flat no-tillage without straw returning (CK). High-throughput sequencing technology was employed to analyze the soil bacterial community composition and structural changes under different straw-returning methods. The study further explored the relationships between the soil bacterial community and nutrient content. The results indicated that different straw-returning methods altered the composition and structure of the soil bacterial community. The TM treatment significantly increased the richness and diversity of the soil bacterial communities. Shredding and covering (C and TM) effectively improved the soil nutrient content and bacterial community structure. In the C treatment, the abundance of Blastococcus, Nocardioides, and Microvirga increased the most, by 241.02%, 77.79%, and 355.08%, respectively, compared with CK. In the TM treatment, Pseudarthrobacter showed the highest abundance, increasing by 343.30%. The genes involved in soil carbon hydrolysis (pulA), nitrification (hao), organic nitrogen degradation and synthesis (gudB), and the nitrogen limitation response (glnR) significantly decreased by 56.21%, 78.75%, 66.46%, and 67.40%, respectively, in the C treatment. The genes involved in soil carbon hydrolysis (IMA), carbon fixation (pccB-A), methane metabolism (moxF), nitrate reduction in soil (nirD), organic nitrogen degradation and synthesis (gdh, ureAB, ureE), and phosphate absorption (glpT) significantly increased by 93.37%, 92.68%, 95.00%, 23.42%, 35.40%, 114.21%, 59.14%, and 75.86%, respectively, in the C treatment. The nitrate reduction gene (nrfA) significantly increased by 80.27% in the TM treatment. Therefore, we concluded that straw primarily stimulates the activity of bacterial communities and regulates the bacterial community by changing the relative abundance of the soil microorganisms and functional genes, thereby improving the soil nutrient content. This study considered pulverized cover straw returning and crushing and mixing straw returning to be the most reasonable methods.
Comparison of Deep Learning Models for Multi-Crop Leaf Disease Detection with Enhanced Vegetative Feature Isolation and Definition of a New Hybrid Architecture
Authors: Saleem Sajjad , Sharif Muhammad Irfan , Sharif Muhammad Imran , Sajid Muhammad Zaheer , Marinello Francesco
Published: September 2024

Agricultural productivity is one of the critical factors towards ensuring food security across the globe. However, some of the main crops, such as potato, tomato, and mango, are usually infested by leaf diseases, which considerably lower yield and quality. The traditional practice of diagnosing disease through visual inspection is labor-intensive, time-consuming, and can lead to numerous errors. To address these challenges, this study evokes the AgirLeafNet model, a deep learning-based solution with a hybrid of NASNetMobile for feature extraction and Few-Shot Learning (FSL) for classification. The Excess Green Index (ExG) is a novel approach that is a specified vegetation index that can further the ability of the model to distinguish and detect vegetative properties even in scenarios with minimal labeled data, demonstrating the tremendous potential for this application. AgirLeafNet demonstrates outstanding accuracy, with 100% accuracy for potato detection, 92% for tomato, and 99.8% for mango leaves, producing incredibly accurate results compared to the models already in use, as described in the literature. By demonstrating the viability of a deep learning/IoT system architecture, this study goes beyond the current state of multi-crop disease detection. It provides practical, effective, and efficient deep-learning solutions for sustainable agricultural production systems. The innovation of the model emphasizes its multi-crop capability, precision in results, and the suggested use of ExG to generate additional robust disease detection methods for new findings. The AgirLeafNet model is setting an entirely new standard for future research endeavors.
Leveraging Convolutional Neural Networks for Disease Detection in Vegetables: A Comprehensive Review
Authors: Mahmood ur Rehman Muhammad , Liu Jizhan , Nijabat Aneela , Faheem Muhammad , Wang Wenyuan , Zhao Shengyi
Published: September 2024

Timely and accurate detection of diseases in vegetables is crucial for effective management and mitigation strategies before they take a harmful turn. In recent years, convolutional neural networks (CNNs) have emerged as powerful tools for automated disease detection in crops due to their ability to learn intricate patterns from large-scale image datasets and make predictions of samples that are given. The use of CNN algorithms for disease detection in important vegetable crops like potatoes, tomatoes, peppers, cucumbers, bitter gourd, carrot, cabbage, and cauliflower is critically examined in this review paper. This review examines the most recent state-of-the-art techniques, datasets, and difficulties related to these crops’ CNN-based disease detection systems. Firstly, we present a summary of CNN architecture and its applicability to classify tasks based on images. Subsequently, we explore CNN applications in the identification of diseases in vegetable crops, emphasizing relevant research, datasets, and performance measures. Also, the benefits and drawbacks of CNN-based methods, covering problems with computational complexity, model generalization, and dataset size, are discussed. This review concludes by highlighting the revolutionary potential of CNN algorithms in transforming crop disease diagnosis and management strategies. Finally, this study provides insights into the current limitations regarding the usage of computer algorithms in the field of vegetable disease detection.
Knowledge Mapping Analysis of Karst Rocky Desertification Vegetation Restoration in Southwest China: A Study Based on Web of Science Literature
Authors: Lu Xiaxia , Sheng Maoyin , Luo Mengxia
Published: September 2024

Karst rocky desertification (KRD) is a serious ecological and environmental issue, hindering the sustainable socio-economic development of the karst area. To scientifically control this issue, lots of studies on KRD vegetation restoration have been conducted in the past few decades. In the present study, a systematic review of the research progress and future trends in KRD vegetation restoration was conducted. The results showed the following: (1) Studies on KRD vegetation restoration began in the 1990s and could be divided into the four following stages: germination (1993–2002), initial development (2003–2010), steady growth (2011–2016), and rapid growth (2017–2023); (2) research hot topics included theoretical implications, vegetation restoration strategies and technologies, ecological responses to the KRD vegetation restoration, and the coupling of vegetation restoration with landscape resource enhancement; (3) the research frontiers were as follows: the classification and restoration effectiveness of KRD vegetation types, the impacts of KRD vegetation restoration on soil microorganisms and soil erosion, the influences of ecological engineering and land use on KRD vegetation restoration, and the relationships between KRD vegetation restorations and karst ecosystem structural functions. Finally, research prospects were proposed from the research methods, perspectives, content, and shortcomings. This study provided valuable references for in-depth research in the field of KRD vegetation restoration.
Australian University Students’ Experience of Animal-Assisted Education: An Exploratory Study
Authors: Hill Jessica , Waldby Lucy , Quinlan Teresa , Fleming Jennifer , Hoyle Melanie , Driscoll Carlie
Published: September 2024

University students experience poorer mental health outcomes when compared to the general population. Poor mental health has been associated with reduced wellbeing and low academic performance, resulting in higher rates of withdrawal. Animal-assisted education is an intervention found to result in a reduction in anxiety and an increased learning engagement among primary and secondary students. However, minimal research has been conducted regarding the inclusion of therapy dogs in the learning environments of students in tertiary education. This study explored the influence of animal-assisted education on the experience of university students. A total of 56 university students engaged with animal-assisted education over a 13-week period and completed an online survey comprised of open- and closed-response questions. The findings showed that all perceived benefits of the therapy dog, including improved mood and reduction of anxiety, increased motivation and engagement in learning activities, as well as an improved social engagement with peers and the educator. Preliminary findings demonstrated that the inclusion of animal-assisted education into the teaching of university students may assist in supporting their mental health and overall learning experience. Research is needed to explore the most effective ways to incorporate animal-assisted education into university settings for both students and therapy dogs.
Morphophysiological Assessment of the Cervix during the Reproductive Cycle and Early Pregnancy in Does Using Computed Tomography and Oxytocin Receptor Immunohistochemistry
Authors: Kanthawat Supapit , Srisuwatanasagul Kongkiat , Thatsanabunjong Fueangrat , Chaivoravitsakul Nardtiwa , Panyaboriban Saritvich , Srisuwatanasagul Sayamon
Published: September 2024

This study aimed to elucidate the morphophysiology and oxytocin receptor (OXTR) expression in the cervix of doe goats during various reproductive stages to enhance reproductive management strategies. A total of 40 cervical samples were categorized into follicular (n = 15), luteal (n = 10), and early pregnancy (n = 15) stages. Utilizing advanced imaging based on functional and morphological markers, the study employed computed tomography (CT) scans, histochemical staining (Masson trichrome and alcian blue), immunohistochemistry, Western blotting, and quantitative PCR (qPCR) to assess structural changes in the cervix and in OXTR expression during the estrous cycle and early pregnancy. CT scans revealed consistent cervical folds and a significant reduction in cervical width during pregnancy, suggesting structural adaptations for gestational integrity. Histochemical analyses indicated a well-organized collagen network and presence of mucins, essential for cervical function and integrity. Immunohistochemistry and Western blotting demonstrated elevated OXTR protein levels during the follicular stage, which were markedly reduced during pregnancy, indicating a role in facilitating cervical relaxation and sperm transport during estrus and maintaining cervical closure during gestation. qPCR analysis showed stable OXTR mRNA levels during follicular and luteal stages with a slight, non-significant increase during pregnancy, pointing towards posttranscriptional regulatory mechanisms. In conclusion, this study demonstrates that cervical morphology and OXTR expression in doe goats undergo significant changes across reproductive stages, with elevated OXTR protein levels during the follicular phase and notable reductions in cervical width and OXTR protein levels during pregnancy, indicating structural and functional adaptations for both reproductive processes and gestational integrity.
A Novel Bifidobacterium longum Subsp. longum T1 Strain from Cow’s Milk: Homeostatic and Antibacterial Activity against ESBL-Producing Escherichia coli
Authors: Machulin Andrey V. , Abramov Vyacheslav M. , Kosarev Igor V. , Deryusheva Evgenia I. , Priputnevich Tatiana V. , Panin Alexander N. , Manoyan Ashot M. , Chikileva Irina O. , Abashina Tatiana N. , Blumenkrants Dmitriy A. , Ivanova Olga E. , Papazyan Tigran T. , Nikonov Ilia N. , Suzina Nataliya E. , Melnikov Vyacheslav G. , Khlebnikov Valentin S. , Sakulin Vadim K. , Samoilenko Vladimir A. , Gordeev Alexey B. , Sukhikh Gennady T. , Uversky Vladimir N. , Karlyshev Andrey V.
Published: September 2024

Background/Objectives: The global emergence of antibiotic-resistant zooanthroponotic Escherichia coli strains, producing extended-spectrum beta-lactamases (ESBL-E) and persisting in the intestines of farm animals, has now led to the development of a pandemic of extra-intestinal infectious diseases in humans. The search for innovative probiotic microorganisms that eliminate ESBL-E from the intestines of humans and animals is relevant. Previously, we received three isolates of bifidobacteria: from milk of a calved cow (BLLT1), feces of a newborn calf (BLLT2) and feces of a three-year-old child who received fresh milk from this calved cow (BLLT3). Our goal was to evaluate the genetic identity of BLLT1, BLLT2, BLLT3 isolates using genomic DNA fingerprinting (GDF), to study the tolerance, adhesion, homeostatic and antibacterial activity of BLLT1 against ESBL-E. Methods: We used a complex of microbiological, molecular biological, and immunological methods, including next generation sequencing (NGS). Results: GDF showed that DNA fragments of BLLT2 and BLLT3 isolates were identical in number and size to DNA fragments of BLLT1. These data show for the first time the possibility of natural horizontal transmission of BLLT1 through with the milk of a calved cow into the intestines of a calf and the intestines of a child. BLLT1 was resistant to gastric and intestinal stresses and exhibited high adhesive activity to calf, pig, chicken, and human enterocytes. This indicates the unique ability of BLLT1 to inhabit the intestines of animals and humans. We are the first to show that BLLT1 has antibacterial activity against ESBL-E strains that persist in humans and animals. BLLT1 produced 145 ± 8 mM of acetic acid, which reduced the pH of the nutrient medium from 6.8 to 5.2. This had an antibacterial effect on ESBL-E. The genome of BLLT1 contains ABC-type carbohydrate transporter gene clusters responsible for the synthesis of acetic acid with its antibacterial activity against ESBL-E. BLLT1 inhibited TLR4 mRNA expression induced by ESBL-E in HT-29 enterocytes, and protected the enterocyte monolayers used in this study as a bio-model of the intestinal barrier. BLLT1 increased intestinal alkaline phosphatase (IAP) as one of the main molecular factors providing intestinal homeostasis. Conclusions: BLLT1 shows promise for the creation of innovative functional nutritional products for humans and feed additives for farm animals that will reduce the spread of ESBL-E strains in the food chain.
Differential Nitric Oxide Responses in Primary Cultured Keratinocytes and Fibroblasts to Visible and Near-Infrared Light
Authors: Barolet Augustin C. , Magne Brice , Barolet Daniel , Germain Lucie
Published: September 2024

NO is a crucial signaling molecule involved in skin health, the immune response, and the protection against environmental stressors. This study explores how different wavelengths of light, namely blue (455 nm), red (660 nm), and near infrared (NIR, 850 nm), affect nitric oxide (NO) production in skin cells. Primary keratinocytes and fibroblasts from three donors were exposed to these wavelengths, and NO production was quantified using a DAF-FM fluorescent probe. The results demonstrated that all three wavelengths stimulated NO release, with blue light showing the most pronounced effect. Specifically, blue light induced a 1.7-fold increase in NO in keratinocytes compared to red and NIR light and a 2.3-fold increase in fibroblasts compared to red light. Notably, fibroblasts exposed to NIR light produced 1.5 times more NO than those exposed to red light, while keratinocytes consistently responded more robustly across all wavelengths. In conclusion, blue light significantly boosts NO production in both keratinocytes and fibroblasts, making it the most effective wavelength. Red and NIR light, while less potent, also promote NO production and could serve as complementary therapeutic options, particularly for minimizing potential photoaging effects.
Functional Characterization of the Ciliate Stylonychia lemnae Serotonin N-Acetyltransferase, a Pivotal Enzyme in Melatonin Biosynthesis and Its Overexpression Leads to Peroxidizing Herbicide Tolerance in Rice
Authors: Lee Kyungjin , Back Kyoungwhan
Published: September 2024

Serotonin N-acetyltransferase (SNAT) is a pivotal enzyme for melatonin biosynthesis in all living organisms. It catalyzes the conversion of serotonin to N-acetylserotonin (NAS) or 5-methoxytrypytamine (5-MT) to melatonin. In contrast to animal- and plant-specific SNAT genes, a novel clade of archaeal SNAT genes has recently been reported. In this study, we identified homologues of archaeal SNAT genes in ciliates and dinoflagellates, but no animal- or plant-specific SNAT homologues. Archaeal SNAT homologue from the ciliate Stylonychia lemnae was annotated as a putative N-acetyltransferase. To determine whether the putative S. lemnae SNAT (SlSNAT) exhibits SNAT enzyme activity, we chemically synthesized and expressed the full-length SlSNAT coding sequence (CDS) in Escherichia coli, from which the recombinant SlSNAT protein was purified by Ni2+ affinity column chromatography. The recombinant SlSNAT exhibited SNAT enzyme activity toward serotonin (Km = 776 µM) and 5-MT (Km = 246 µM) as substrates. Furthermore, SlSNAT-overexpressing (SlSNAT-OE) transgenic rice plants showed higher levels of melatonin synthesis than wild-type controls. The SlSNAT-OE rice plants exhibited delayed leaf senescence and tolerance against treatment with the reactive oxygen species (ROS)-inducing herbicide butafenacil by decreasing hydrogen peroxide (H2O2) and malondialdehyde (MDA) levels, suggesting that melatonin alleviates ROS production in vivo.
Sequence-Information Recognition Method Based on Integrated mDTW
Authors: Sun Boliang , Chen Chao
Published: September 2024

In the fields of machine learning and artificial intelligence, the processing of time-series data has been a continuous concern and a significant algorithm for intelligent applications. Traditional deep-learning-based methods seem to have reached performance ceilings in certain specific areas, such as online character recognition. This paper proposes an algorithmic framework to break this deadlock by classifying time-series data by evaluating the similarities among handwriting samples using multidimensional Dynamic Time Warping (mDTW) distances. A simplified hierarchical clustering algorithm is employed as a classifier for character recognition. Moreover, this work achieves joint modeling with current mainstream temporal models, enabling the mDTW model to integrate modeling results from methods like RNN or Transformer, therefore further enhancing the accuracy of related algorithms. A series of experiments were conducted on a public database, and the results indicate that our method overcomes the bottleneck of current deep-learning-based methods in the field of online handwriting character recognition. More importantly, compared to deep -learning-based methods, the proposed method has a simpler structure and higher interpretability. Experimental results demonstrate that our proposed method outperforms existing state-of-the-art models in handwriting character recognition, achieving a top-1 accuracy of 98.5% and a top-3 accuracy of 99.3%, thus confirming its effectiveness in overcoming the limitations of traditional deep-learning models in temporal sequence processing.