bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coordinated emission reduction strategy of water pollution and carbon emissions in the South-to-North Water Diversion Project based on a differential game model
Authors: Chen Junfei , Cheng Yusong , Yang Wentong 
Published: May 2024

ABSTRACTThis study investigates the green development of the South-to-North Water Diversion Project (SNWDP) by exploring the synergistic reduction of water pollution and carbon emissions. Firstly, a differential game model is constructed to reduce pollution and carbon in the water supply chain. Secondly, the emission reduction strategies of water source and receiving areas under centralized and decentralized decision models are compared and analyzed and a cost-sharing contract is designed to coordinate the supply chain. Finally, numerical analysis is used to compare and analyze the important parameters to draw conclusions. The results show that: (1) Collaboration between water source and receiving areas influences emission reduction efforts, with the highest achieved under the centralized model. (2) The cost-sharing contract improves efforts and addresses ‘free-riding’ in the decentralized model. (3) The SNWDP can achieve a win-win situation in terms of both environmental and economic benefits by promoting the synergy of pollution reduction and carbon reduction.
Hallmarks of Periodontitis
Authors: Gasmi Benahmed Asma , Gasmi Amin , Noor Sadaf , Semenova Yuliya , Emadali Alireza , Dadar Maryam , Shanaida Yurii , Avdeev Oleksandr , Bjørklund Geir 
Published: May 2024

Abstract:
Periodontitis is a complex polymicrobial disease of the oral cavity that affects
tooth-supporting tissues. It is caused by multiple factors, such as pathogenic bacteria, genetic
predisposition, and host immune response factors. The pathogenesis of periodontal
disease involves the complex interrelations among bacterial toxins, several populations
of cells, and host cell-secreted inflammatory mediators. Generally, periodontitis is characterized
by the formation of intricate and varied biofilms of microbes on the tooth surface,
commonly known as dental plaque. Activation of defense cells is characterized by
releasing inflammatory mediators, such as proteases, acidic metabolites, cytokines, interleukins,
and chemokines, which destroy tissue and ultimately cause bone resorption.
The individual periodontal condition has a significant impact on systemic homeostasis,
and its disruption can cause the development of some metabolic disorders. This review
article summarizes the latest studies on the pathogenesis of periodontitis and describes
the role of inflammatory mediators and genetic polymorphism in individuals, as well as
relationships with some metabolic conditions. The information is collected from
PubMed, Scopus, ScienceDirect, SpringerLink, and clinicaltrials.gov.
Non-Cystic Fibrosis-Related Bronchiectasis in Children: Are Bacteria Always to Blame?
Authors: Virgili Fabrizio , La Regina Domenico , Nenna Raffaella , Mancino Enrica , Matera Luigi , Spatuzzo Mattia , Iovine Elio , Midulla Fabio 
Published: May 2024

Background:
Bronchiectases are structural alterations characterized by the dilation of
bronchial walls due to inflammation, resulting in a loss of elasticity and muscle function. They are
more common in adults than children and have various etiologies (such as chronic infections, particularly
in developing countries, or immunodeficiencies in industrialized nations), with up to
40% being idiopathic.

Case presentation:
We reported the case of a nine-year-old child who, following two lower respiratory
tract infections (a severe H1N1 influenza pneumonia and a milder episode caused by M.
pneumoniae), developed bronchiectasis without underlying predisposing conditions.

Discussion:
Bronchiectasis is a morphological alteration of the bronchi, which can develop subsequently
to lung infections and may remain clinically silent even for a long time. The most common
associated symptoms include productive cough, persistent rales, therapy-resistant “asthma,”
and recurrent lung infections. High-Resolution CT (HRCT) scans are the gold standard for their diagnosis,
while their management requires a comprehensive approach, including pharmacological
and psychosocial measures. It is always advisable to investigate the underlying etiology to eventually
establish a causal treatment.

Conclusion:
This study aims to emphasize that not only bacteria but also viral infections and their
associated inflammatory impact on lung tissue can contribute to the development of bronchiectasis.
This study aims to implement current knowledge regarding non-cystic fibrosis-related
bronchiectasis and to underscore the significance of post-acute instrumental reassessment in lower
respiratory tract infections, especially when severe.
A Computational Study of Phenothiazine Derivatives as Acetylcholinesterase Inhibitors Targeting Alzheimer’s Disease
Authors: V. Prema , A. Meena , N. Ramalakshmi 
Published: May 2024

Background:
Alzheimer’s disease is a neurodegenerative disorder that affects learning,
memory and behavioral turbulence in elderly patients. Acetylcholinesterase (AChE) inhibitors act
as anti-Alzheimer’s agents. Phenothiazine derivatives are considered momentous anti-Alzheimer’s
agents because of their AChE inhibitory activity. The elevated levels and increased expression of
this protein have been associated with Alzheimer's disease. Coumarin-fused phenothiazines have
emerged as significant anti-Alzheimer's agents due to their notable receptor inhibitory activity.

Objective:
Some unique phenothiazine analogs were designed, and computational studies were
conducted to explore their inhibitory activity against the AChE enzyme (PDB id: 4EY7) by using
the Schrodinger suite-2019-4.

Methods:
Docking studies were conducted by using the Glide module; binding free energies were
calculated by means of the Prime MM-GBSA module, and Molecular dynamics (MD) simulation
was performed by using the Desmond module of the Schrodinger suite. Glide scores were used to
find out the binding affinity of the ligands with the target 4EY7.

Results:
The compounds exhibited enhanced hydrophobic interactions and formed hydrogen bonds,
effectively impeding Acetylcholinesterase. The Glide scores for the compounds ranged from -13.4237
to -8.43439, surpassing the standard (Donepezil) with a score of -16.9898. Interestingly, a positive
value was obtained for the MM-GBSA binding of the potent inhibitor. To gain insights into the dynamic
behavior of the protein A8, molecular dynamics (MD) simulations were employed.

Conclusion:
Based on the results, the study concludes that phenothiazine derivatives show promise
as acetylcholinesterase inhibitors. Compounds with notable Glide scores are poised to exhibit significant
anti-Alzheimer's activity, suggesting their potential therapeutic efficacy. Further in vitro
and in vivo investigations are warranted to validate and explore the therapeutic potentials of these
compounds.
Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review
Authors: Sweeney Colm , Ennis Edel , Mulvenna Maurice D , Bond Raymond , O'Neill Siobhan 
Published: May 2024

Background
Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and understanding in the fields of mental health and suicide prevention.

Objective
This systematic review aimed to determine how machine learning and data analysis can be applied to text-based digital media data to understand mental health and aid suicide prevention.

Methods
A systematic review of research papers from the following major electronic databases was conducted: Web of Science, MEDLINE, Embase (via MEDLINE), and PsycINFO (via MEDLINE). The database search was supplemented by a hand search using Google Scholar.

Results
Overall, 19 studies were included, with five major themes as to how data analysis and machine learning techniques could be applied: (1) as predictors of personal mental health, (2) to understand how personal mental health and suicidal behavior are communicated, (3) to detect mental disorders and suicidal risk, (4) to identify help seeking for mental health difficulties, and (5) to determine the efficacy of interventions to support mental well-being.

Conclusions
Our findings show that data analysis and machine learning can be used to gain valuable insights, such as the following: web-based conversations relating to depression vary among different ethnic groups, teenagers engage in a web-based conversation about suicide more often than adults, and people seeking support in web-based mental health communities feel better after receiving online support. Digital tools and mental health apps are being used successfully to manage mental health, particularly through the COVID-19 epidemic, during which analysis has revealed that there was increased anxiety and depression, and web-based communities played a part in reducing isolation during the pandemic. Predictive analytics were also shown to have potential, and virtual reality shows promising results in the delivery of preventive or curative care. Future research efforts could center on optimizing algorithms to enhance the potential of text-based digital media analysis in mental health and suicide prevention. In addressing depression, a crucial step involves identifying the factors that contribute to happiness and using machine learning to forecast these sources of happiness. This could extend to understanding how various activities result in improved happiness across different socioeconomic groups. Using insights gathered from such data analysis and machine learning, there is an opportunity to craft digital interventions, such as chatbots, designed to provide support and address mental health challenges and suicide prevention.
Machine Learning–Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study
Authors: Kim Hyejun , Son Yejun , Lee Hojae , Kang Jiseung , Hammoodi Ahmed , Choi Yujin , Kim Hyeon Jin , Lee Hayeon , Fond Guillaume , Boyer Laurent , Kwon Rosie , Woo Selin , Yon Dong Keon 
Published: May 2024

Background
Suicide is the second-leading cause of death among adolescents and is associated with clusters of suicides. Despite numerous studies on this preventable cause of death, the focus has primarily been on single nations and traditional statistical methods.

Objective
This study aims to develop a predictive model for adolescent suicidal thinking using multinational data sets and machine learning (ML).

Methods
We used data from the Korea Youth Risk Behavior Web-based Survey with 566,875 adolescents aged between 13 and 18 years and conducted external validation using the Youth Risk Behavior Survey with 103,874 adolescents and Norway’s University National General Survey with 19,574 adolescents. Several tree-based ML models were developed, and feature importance and Shapley additive explanations values were analyzed to identify risk factors for adolescent suicidal thinking.

Results
When trained on the Korea Youth Risk Behavior Web-based Survey data from South Korea with a 95% CI, the XGBoost model reported an area under the receiver operating characteristic (AUROC) curve of 90.06% (95% CI 89.97-90.16), displaying superior performance compared to other models. For external validation using the Youth Risk Behavior Survey data from the United States and the University National General Survey from Norway, the XGBoost model achieved AUROCs of 83.09% and 81.27%, respectively. Across all data sets, XGBoost consistently outperformed the other models with the highest AUROC score, and was selected as the optimal model. In terms of predictors of suicidal thinking, feelings of sadness and despair were the most influential, accounting for 57.4% of the impact, followed by stress status at 19.8%. This was followed by age (5.7%), household income (4%), academic achievement (3.4%), sex (2.1%), and others, which contributed less than 2% each.

Conclusions
This study used ML by integrating diverse data sets from 3 countries to address adolescent suicide. The findings highlight the important role of emotional health indicators in predicting suicidal thinking among adolescents. Specifically, sadness and despair were identified as the most significant predictors, followed by stressful conditions and age. These findings emphasize the critical need for early diagnosis and prevention of mental health issues during adolescence.
The biology teacher profile of junior and senior high school and the use of learning models in Ternate Indonesia
Authors: Madjid Ilham , Duran Corebima Aloysius , Suwono Hadi , Mahanal Susriyati 
Published: May 2024

The implementation of instructional models in the classroom significantly impacts students’ learning abilities and achievements. The adoption of a teacher-centered learning approach might lead to reduced student engagement in the learning process, consequently influencing their ability to acquire life skills. The current study aimed to determine the educational attainment, teaching experience, utilization of learning media and application of learning models by junior and senior high school biology teachers in Ternate, Indonesia. This study employed a qualitative research method that utilized survey questionnaires. The respondents were 25 biology teachers of junior high school and 30 biology teachers of senior high school. The research findings showed that (1) 84% of the junior high school biology teachers have the undergraduate education and 16% of them have the master education; 69.77% of those of the senior high school have the undergraduate education and 30.23% of them have the master education. (2) Both the junior and the senior high school biology teachers have over 15 years of teaching experience. (3) Among the junior high school biology teachers, the use of student worksheet is only 20%, and the use of learning media is 14%; Among the senior high school biology teachers, the use of student worksheet is 36.66% and the use of learning media is 23.33%. (4) The uses of conventional learning and the use of cooperative learnings among junior high school biology teachers are 83% and 17%, respectively; where as among those of senior high school are 73.34% and 26.66%, respectively. In conclusion, the educational qualifications of junior and senior high school biology teachers in Ternate have satisfied the necessary criteria for teaching. However, the teachers have not been able to enhance the quality of education in the city. This highlights the importance of developing innovative learning models to improve the learning abilities and achievements.
DIARRHEA CAUSING ENTEROBACTERIACEAE AND THEIR ANTIBIOTIC RESISTANCE PATTERNS AMONG DIARRHEA PATIENTS FROM SANA’A CITY, YEMEN
Authors: AbdulMughni Gamil Taher Ahmed , Al-Moyed Khaled Abdulkarim , Al-gunaid Eshrak Adulmalik , Al-Shami Huda Zaid , Al-Haidary Naif Mohammed , Al-Madhaji Anowar  Gasem , Al-Shamahy Hassan Abdulwahab 
Published: May 2024

Background and aims: The rise of antibiotic-resistant strains of the bacteria causing diarrhea remains a major worldwide health concern, especially in children under five. The purpose of this surveillance study was to ascertain the prevalence and antibiotic susceptibility profile of Enterobacteriaceae, which cause diarrhea.
Materials and Methods: The National Center for Public Health Laboratories (NCPHL) in Sana'a city was the site of this cross-sectional investigation. Patient stool samples exhibiting diarrhea were gathered and cultivated using standard differential/selective medium. Standard biochemical assays and serological investigations were employed to identify the isolates. With the aid of Kirby-Bauer disk diffusion, the antibiogram was identified.
Results: Enterobacteriaceae isolates were obtained from 972 stool samples collected; 15.3% (149/972) were diarrheagenic Enterobacteriaceae bacteria, including E. coli, Salmonella, and Shigella. There were 8.3% (81/972) Salmonella spp., 5.7% (56/972) Shigella spp., and 1.2% (12/972) E. coli. E. coli strains were grouped, with the most prominent being serogroups O153 (3, 2%) and O25 (2, 1.4%). Fifty-six (37.6%) Shigella species were identified as Shigella boydii type 2 and Shigella bodii type 17, which were the most common Shigella isolated (11, 8.1%, and 16, 10.7%, respectively). We detected high resistance of Salmonella isolates to tetracycline (29/81, 35.8%) but relatively low resistance to ciprofloxacin (7/81, 8.6%) and ceftriaxone (5/81, 6.3%).
Conclusion: The many Enterobacteriaceae linked to instances of diarrhea in Sana'a, Yemen, were demonstrated in this study, along with the necessity of differential diagnosis for improved treatment results. Salmonella, Shigella, and Escherichia coli have all been linked to episodes of diarrhea in Sana'a city. To stop Yemen's antimicrobial resistance from spreading, regular antimicrobial susceptibility testing, efficient monitoring, and national surveillance of AMR bacteria should be put into place.

Peer Review History:
Received 3 February 2024; Revised 12 March 2024; Accepted 20 April; Available online 15 May 2024
Academic Editor: Dr. Gehan Fawzy Abdel Raoof Kandeel, Pharmacognosy Department, National Research Centre, Dokki, 12622, Giza, Egypt, gehankandeel9@yahoo.com
Average Peer review marks at initial stage: 6.0/10
Average Peer review marks at publication stage: 7.5/10
Reviewers:
Dr. George Zhu, Tehran University of Medical Sciences, Tehran, Iran, sansan4240732@163.com
Dr. Esther Marguerite Chase DJANGA, Faculty of Medicine and Biomedical Sciences. Department of Public Health. University of Yaoundé I, Cameroon. e.djanga@yahoo.com
THE PREVALENCE AND ASSOCIATED FACTORS OF STAPHYLOCOCCUS AUREUS COLONIZATION IN THE ORAL CAVITY OF ADULTS
Authors: Ali Nagi Ibraheem Abduh , Howilah Ahmed Abdullah , Al-Sanabani Nesreen Fadel , AL-Haddad Khaled A , Al-Shamahy Hassan Abdulwahab , Madar Ebtihal Mohamed , Al-Ghaffari Khaled Mohammed 
Published: May 2024

Background and aims: Long-term carriers of S. aureus are thought to make up between 21% and 30% of the human population. The bacteria are present in the mouth mucous membrane, the lower reproductive tract of females, the nose, and the typical skin microbiota. S. aureus can cause a wide range of ailments, from mild skin infections like cellulitis, boils, carbuncles, folliculitis, abscesses and scalded skin syndrome. Finding the prevalence of S. aureus in the oral cavities of adult dental patients as well as any possible contributing factors was the aim of this study.
Methods: One hundred patients—fifty-nine with natural teeth and fifty with prosthetics—who attended dental clinics run by the Sana'a University Faculty of Dentistry participated in a cross-sectional study. The buccal mucous membranes of both groups were sampled, and the swabs were cultured on both selective medium (Mannitol salt agar) and medium supplemented with 5% blood. After that, all cultured plates were incubated at 37°C with oxygen for 48 hours, after which the bacterial growth was identified using conventional techniques.
Results: Compared to female patients (41%), male patients had an oral colonization rate of S. aureus of 58.9%; for the younger age group (24–34 years), it was 70% with OR=3.7 (p=0.003). There was a significant link (odds ratio = 4.9) between detachable prostheses, prosthesis wearers with more than six years of experience (OR=17, p<0.001), and smokers who regularly lit up (OR=7.3, p= 0.03). Furthermore, a significant association was discovered between the practice of consistently ingesting large amounts of sugar (OR=5.7, p=0.01) and the growth of S. aureus in the oral cavity.
Conclusion Healthy persons had a high frequency of Staphylococcus aureus in their oral cavities, and the infection was linked to certain behaviors such as smoking, chewing Qat, using prostheses, and patients who were younger in age. Also, the study emphasizes how crucial it is to practice proper oral hygiene because Staphylococcus aureus can primarily cause possible systemic infections through the mouth cavity.

Peer Review History:
Received 3 February 2024; Revised 10 March 2024; Accepted 23 April; Available online 15 May 2024
Academic Editor: Dr. Marwa A. A. Fayed, University of Sadat City, Egypt, maafayed@gmail.com
Average Peer review marks at initial stage: 6.0/10
Average Peer review marks at publication stage: 7.5/10
Reviewers:
Dr. George Zhu, Tehran University of Medical Sciences, Tehran, Iran, sansan4240732@163.com
Dr. Mohsen Ali Al-Hamzi, Thamar University, Factuality of Dentistry, Yemen. mohsenalhamzi@gmail.com
ANTIOXIDANT, ANTI-INFLAMMATORY, ANTIDIABETIC, ANTHELMINTHIC, AND THROMBOLYTIC ACTIVITY OF THE METHANOL EXTRACT OF CITRULLUS LANATUS PEEL
Authors: Nahar Nazmun , Fatema Ummul Khair , Sharma Partha Protim , Bhuiya Abdul Motaleb , Begum Taslima , Azahar Nur Fauwizah , Rahman Mohammad Nasrin Abdul , Sulaiman Wan Mohd Azizi Bin Wan , Azad Abul Kalam 
Published: May 2024

Background: The present study aimed for in vitro evaluation of Citrullus lanatus Peel (CLP) methanol extract for antioxidative, anti-inflammatory, antidiabetic, anthelmintic, and thrombolytic activity.
Method: CLP was extracted with methanol and tested for in vitro antioxidative (DPPH and H2O2 scavenging method), thrombolytic, anthelmintic, antidiabetic, and anti-inflammatory properties (human red blood cell membrane stabilization method, α-amylase inhibitory effect by using Iodine-Starch method.
Results: The percentage yield was 7% and phytochemical profile showed the presence of steroid, tannins, saponins, flavonoids, glycoside and reducing sugar. In DPPH scavenging assay, 88.7% was at 1000 g/ml, whereas 34% to 48.9% (IC50 27.65 µg/ml) in H2O2 and from 61.8% to 95.2% (IC50 value: 07 µg/ml) in ASCOR. In in vitro anti-inflammatory activity, the maximum protection percentage was observed 58% and 44%. Consecutively, in anti-diabetic activity, IC50 values of 1137.64 μg/ml whereas reference (Acarbose) exhibited IC50 at 671.71 μg/ml. On the other hand, the inhibitory effect of Acarbose showed 57% and 98% respectively at 2000 μg/ml. In earthworms, it considered as very potential for the helminthic infection and helminthiasis. A significant clot lysis activity of 44% was noticed when the clots were treated with 100 µl of CLP extract (10 mg/ml) in in-vitro thrombolytic activity assay.
Conclusions: The findings of this study revealed that the peel possessed the antioxidant, anti-inflammatory, antidiabetic, anthelminthic and thrombolytic activities. These findings will be motivated to do further research on molecular level to finds into more depth which is considered as the limitation of this study.

Peer Review History:
Received 3 February 2024; Revised 12 March 2024; Accepted 20 April; Available online 15 May 2024
Academic Editor: Dr. A.A. Mgbahurike, University of Port Harcourt, Nigeria, amaka_mgbahurike@yahoo.com
Average Peer review marks at initial stage: 6.0/10
Average Peer review marks at publication stage: 7.5/10
Reviewers:
Dr. Gehan Fawzy Abdel Raoof Kandeel, Pharmacognosy Department, National Research Centre, Dokki, 12622, Giza, Egypt, gehankandeel9@yahoo.com
Dr. Francis Adou Yapo, Felix Houphouet Boigny, University of Abidjan, Ivory Coast, fyapo@yahoo.fr