bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sleep, light exposure at night, and psychological wellbeing during pregnancy
Authors: Ng Choon Ming , Kaur Satvinder , Kok Ee Yin , Chew Wan Ling , Takahashi Masaki , Shibata Shigenobu 
Published: September 2023

Abstract
Background
Psychological wellbeing during pregnancy is imperative for optimal maternal outcomes. The present study aimed to determine the association between sleep quality, light exposure at night, and psychological wellbeing in the 2nd and 3rd trimesters of pregnancy.

Methods
This prospective study was conducted in 9 randomly selected government maternity clinics in Kuala Lumpur, Malaysia. Healthy women aged 20–48 years old with single pregnancy were recruited using convenience sampling (n = 169). Sleep quality, light exposure at night, and psychological wellbeing were self-reported using the Pittsburgh Sleep Quality Index (PSQI), Harvard Light Exposure Assessment (H-LEA), and Depression, Anxiety, and Stress Scale (DASS-21) in the 2nd trimester and followed-up at the 3rd trimester.

Results
During the 2nd and 3rd trimesters of pregnancy, mild to severe symptoms of stress (10.7 and 11.3%), anxiety (42 and 44.3%), and depression (9.6 and 16.6%) were observed among the participants. Adjusted multiple linear regression revealed that poor sleep quality and higher light exposure at night were attributed to greater stress and depression symptoms in the 3rd trimester. Higher lux level exposed from 10 pm to < 1 am was associated with increased stress (β = 0.212, p = 0.037) and depression (β = 0.228, p = 0.024). Only poor sleep quality was observed to adversely affect anxiety (β = 0.243, p = 0.002) and depression levels (β = 0.259, p = 0.001) in the 2nd trimester.

Conclusions
Present study provided preliminary findings on the association between sleep quality, light at night, and psychological wellbeing of pregnant women. As a recommendation, future research could investigate whether public health interventions aimed at decreasing artificial light at night can benefit sleep quality and the psychological health of pregnant women.
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic
Authors: Qasrawi Radwan , Hoteit Maha , Tayyem Reema , Bookari Khlood , Al Sabbah Haleama , Kamel Iman , Dashti Somaia , Allehdan Sabika , Bawadi Hiba , Waly Mostafa , Ibrahim Mohammed O. ,   The Regional CORONA COOKING Survey Group, De Backer Charlotte , Teunissen Lauranna , Van Royen Kathleen , Cuykx Isabelle , Decorte Paulien , Ouvrein Gaëlle , Poels Karolien , Vandebosch Heidi , Maldoy Katrien , Pabian Sara , Matthys Christophe , Smits Tim , Vrinten Jules , DeSmet Ann , Teughels Nelleke , Geuens Maggie , Vermeir Iris , Proesmans Viktor , Hudders Liselot , Al-Mannai Mariam , Alalwan Tariq , Naim Elissa , Mansour Rania , Yazbeck Nour , Agha Hazem , Seir Rania Abu , Arrish Jamila , Fallata Ghadir , Alhumaidan Omar , Alakeel Shihana , AlBuayjan Norah , Alkhunein Sarah , Binobaydan Budur , Alshaya Aeshah , Aldhaheri Ayesha , Polo Stephanny Vicuna , Al-Halawa Diala Abu 
Published: September 2023

AbstractBackgroundA direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to predict food insecurity across ten Arab countries in the Gulf and Mediterranean regions. A total of 13,443 participants were extracted from the international Corona Cooking Survey conducted by 38 different countries during the COVID -19 pandemic.ResultsThe findings indicate that Jordanian, Palestinian, Lebanese, and Saudi Arabian respondents reported the highest rates of food insecurity in the region (15.4%, 13.7%, 13.7% and 11.3% respectively). On the other hand, Oman and Bahrain reported the lowest rates (5.4% and 5.5% respectively). Our model obtained accuracy levels of 70%-82% in all algorithms. Gradient Boosting and Random Forest techniques had the highest performance levels in predicting food insecurity (82% and 80% respectively). Place of residence, age, financial instability, difficulties in accessing food, and depression were found to be the most relevant features associated with food insecurity.ConclusionsThe ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally.
Dynamicity, emerging patterns, and spatiotemporal trends of scientific production on the use of activated carbon in oral health: a scientometric study
Authors: Mayta-Tovalino Frank , Espinoza-Carhuancho Fran , Alvitez-Temoche Daniel , Mauricio-Vilchez Cesar , Munive-Degregori Arnaldo , Barja-Ore John , Pacheco-Mendoza Josmel 
Published: September 2023

Abstract
Background
The use of activated carbon (AC) in oral hygiene products has gained significant interest; however, its potential benefits for oral health remain uncertain. This study aimed to conduct a scientometric analysis to examine the dynamicity, emerging patterns, and trends over time in scientific production concerning the use of AC in oral health.

Methods
The Web of Science database was searched for articles published between 2005 and 2022. Various bibliometric indicators, including the H-index, annual growth, Lotka’s law, Bradford’s law, and Sankey diagram, were used for data analysis. Overlay maps, timezone visualization, and three field plots were used to evaluate visualization patterns, time–temporal relationships, and trends. Information retrieval process was performed on March 11, 2023.

Results
The analysis revealed that only six studies constituted the top references with the highest number of citations in recent years, with Brooks’ 2017 study demonstrating the most significant increase in citation. The dual-map overlay demonstrated a close citation relationship between cluster 4 (Molecular Biology Immunology) and the areas of Environmental, Toxicology, and Nutrition. The visualization graph of publication patterns indicated the journals that accumulated the highest number of citations during the study period.

Conclusion
This scientometric study provides valuable insights into the use of AC in oral health and its impact on the field of dentistry. It determines the most productive journals, authors, and countries with the greatest influence. AC effectively removes pollutants and is gaining interest for use in dental effluent treatment. Thus, it may be a viable option for professionals.
The efficacy of oxytocin gel in postmenopausal women with vaginal atrophy: an updated systematic review and meta-analysis
Authors: Farahat Ramadan Abdelmoez , Salamah Hazem Mohamed , Mahmoud Abdelrahman , Hamouda Esraa , Hashemy Mahmoud , Hamouda Heba , Samir Ali , Chenfouh Imane , Marey Ahmed , Awad Dina M. , Farag Elsayed , Abd-Elgawad Mohamed , Eldesouky Elsayed 
Published: September 2023

Abstract
Background
Genitourinary syndrome of menopause (GSM) is a common and disturbing issue in the postmenopausal period. Unlike vasomotor symptoms, it has a progressive trend. Our study aims to evaluate the efficacy and safety of oxytocin gel versus placebo gel in postmenopausal women with GSM.

Methods
A systematic review and meta-analysis synthesizing randomized controlled trials (RCTs) from Web of Science, SCOPUS, PubMed, and Cochrane Central Register of Controlled Trials databases on January 18, 2023. Keywords such as “oxytocin,“ “intravaginal,“ “vaginal,“ “atrophic,“ and “atrophy” were used. We used Review Manager (RevMan) version 5.4 in our analysis. We used the risk ratio (RR) for dichotomous outcomes and the mean difference (MD) for continuous outcomes; both were presented with the corresponding 95% confidence interval (CI) and were calculated with the Mantel-Haenszel or inverse variance statistical method. Cochrane’s Q test and the I2 statistic were used as measures of statistical inconsistency and heterogeneity. The Cochrane Risk of Bias Tool for RCTs was used for the quality assessment of the included studies.

Results
Seven studies with 631 patients were included. Regarding the maturation index, there was a statistically insignificant increase in the oxytocin arm (MD = 12.34, 95% CI (-12.52-37.19), P = 0.33). Clinically assessed vaginal atrophy showed a statistically significant reduction in the oxytocin group (RR = 0.32, 95% CI (0.23 − 0.10), P < 0.00001). For dyspareunia, vaginal pH, and histological evaluation of vaginal atrophy, there was a statistically insignificant difference between the two groups (RR = 1.02, 95% CI (0.82–1.27), P = 0.84), (MD = -0.74, 95% CI (-1.58-0.10), P = 0.08), and (MD = -0.38, 95% CI (-0.82-0.06), P = 0.09), respectively. There was no significant difference in the safety profile between the two groups as measured by endometrial thickness (MD = 0.00, 95% CI (-0.23-0.23), P = 0.99).

Conclusions
Although oxytocin has been proposed as a viable alternative to estrogen in the treatment of GSM, our findings show the opposite. Larger, high-quality RCTs are needed to confirm or refute our results.

Trial registration
PROSPERO registration number CRD42022334357.
Temporal trends in chronic complications of diabetes by sex in community-based people with type 2 diabetes: the Fremantle Diabetes Study
Authors: Davis Wendy A. , Davis Timothy M. E. 
Published: September 2023

Abstract
Background
Whether recent reductions in cardiovascular disease (CVD) events and mortality in type 2 diabetes apply equally to both sexes is largely unknown. The aim of this study was to characterize temporal changes in CVD events and related outcomes in community-based male and female Australian adults with type 2 diabetes or without known diabetes.

Methods
Participants from the longitudinal observational Fremantle Diabetes Study Phases I (FDS1; n = 1291 recruited 1993–1996) and II (FDS2; n = 1509 recruited 2008–2011) and four age-, sex- and postcode-matched individuals without diabetes (FDS1 n = 5159; FDS2 n = 6036) were followed for first myocardial infarction, stroke, heart failure hospitalization, lower extremity amputation, CVD death and all-cause mortality. Five-year incidence rates (IRs) for males versus females in FDS1 and FDS2 were calculated, and IR ratios (IRRs) derived.

Results
The FD1 and FDS2 participants were of mean age 64.0 and 65.4 years, respectively, and 48.7% and 51.8% were males. For type 2 diabetes, IRRs for all endpoints were 11–62% lower in FDS2 than FDS1 for both sexes. For participants without diabetes, IRRs were 8–56% lower in FDS2 versus FDS1 apart from stroke in females (non-significantly 41% higher). IRRs for males versus females across FDS phases were not significantly different for participants with type 2 diabetes or those without diabetes (P-values for male * FDS2 interaction ≥ 0.0.083 adjusted for age). For risk factors in participants with type 2 diabetes, greater improvements between FDS1 and FDS2 in smoking rates in males were offset by a greater reduction in systolic blood pressure in females.

Conclusions
The incidence of chronic complications in Australians with type 2 diabetes and without diabetes has fallen similarly in both sexes over recent decades, consistent with comparably improved overall CVD risk factor management.
A3DyDB: exploring structural aggregation propensities in the yeast proteome
Authors: Garcia-Pardo Javier , Badaczewska-Dawid Aleksandra E. , Pintado-Grima Carlos , Iglesias Valentín , Kuriata Aleksander , Kmiecik Sebastian , Ventura Salvador 
Published: September 2023

Abstract
Background
The budding yeast Saccharomyces cerevisiae (S. cerevisiae) is a well-established model system for studying protein aggregation due to the conservation of essential cellular structures and pathways found across eukaryotes. However, limited structural knowledge of its proteome has prevented a deeper understanding of yeast functionalities, interactions, and aggregation.

Results
In this study, we introduce the A3D yeast database (A3DyDB), which offers an extensive catalog of aggregation propensity predictions for the S. cerevisiae proteome. We used Aggrescan 3D (A3D) and the newly released protein models from AlphaFold2 (AF2) to compute the structure-based aggregation predictions for 6039 yeast proteins. The A3D algorithm exploits the information from 3D protein structures to calculate their intrinsic aggregation propensities. To facilitate simple and intuitive data analysis, A3DyDB provides a user-friendly interface for querying, browsing, and visualizing information on aggregation predictions from yeast protein structures. The A3DyDB also allows for the evaluation of the influence of natural or engineered mutations on protein stability and solubility. The A3DyDB is freely available at http://biocomp.chem.uw.edu.pl/A3D2/yeast.

Conclusion
The A3DyDB addresses a gap in yeast resources by facilitating the exploration of correlations between structural aggregation propensity and diverse protein properties at the proteome level. We anticipate that this comprehensive database will become a standard tool in the modeling of protein aggregation and its implications in budding yeast.
Evaluation of the solar-powered Silver Bullet 2.1 (Lumin 8) light trap for sampling malaria vectors in western Kenya
Authors: Mbare Oscar , Njoroge Margaret Mendi , Ong’wen Fedinand , Bukhari Tullu , Fillinger Ulrike 
Published: September 2023

Abstract
Background
Centers for Disease Control and Prevention (CDC) light traps are widely used for sampling mosquitoes. However, this trap, manufactured in the USA, poses challenges for use in sub-Saharan Africa due to procurement costs and shipping time. Traps that are equally efficient than the CDC light trap, but which are amenable for use in remote African settings and made in Africa, are desirable to improve local vector surveillance. This study evaluated a novel solar-powered light trap made in South Africa (Silver Bullet trap; SB), for its efficiency in malaria vector sampling in western Kenya.

Methods
Large cage (173.7 m3) experiments and field evaluations were conducted to compare the CDC-incandescent light trap (CDC-iLT), CDC-UV fluorescent tube light trap (CDC-UV), SB with white diodes (SB-White) and SB with UV diodes (SB-UV) for sampling Anopheles mosquitoes. Field assessments were done indoors and outdoors following a Latin square design. The wavelengths and absolute spectral irradiance of traps were compared using spectrometry.

Results
The odds of catching a released Anopheles in the large cage experiments with the SB-UV under ambient conditions in the presence of a CDC-iLT in the same system was three times higher than what would have been expected when the two traps were equally attractive (odds ratio (OR) 3.2, 95% confidence interval CI 2.8–3.7, P < 0.01)). However, when the white light diode was used in the SB trap, it could not compete with the CDC-iLT (OR 0.56, 95% CI 0.48–0.66, p < 0.01) when the two traps were provided as choices in a closed system. In the field, the CDC and Silver Bullet traps were equally effective in mosquito sampling. Irrespective of manufacturer, traps emitting UV light performed better than white or incandescent light for indoor sampling, collecting two times more Anopheles funestus sensu lato (s.l.) (RR 2.5; 95% CI 1.7–3.8) and Anopheles gambiae s.l. (RR 2.5; 95% 1.7–3.6). Outdoor collections were lower than indoor collections and similar for all light sources and traps.

Conclusions
The solar-powered SB trap compared well with the CDC trap in the field and presents a promising new surveillance device especially when charging on mains electricity is challenging in remote settings.
Empowering health geography research with location-based social media data: innovative food word expansion and energy density prediction via word embedding and machine learning
Authors: Wang Jue , Kim Gyoorie , Chang Kevin Chen-Chuan 
Published: September 2023

Abstract
Background
The exponential growth of location-based social media (LBSM) data has ushered in novel prospects for investigating the urban food environment in health geography research. However, previous studies have primarily relied on word dictionaries with a limited number of food words and employed common-sense categorizations to determine the healthiness of those words. To enhance the analysis of the urban food environment using LBSM data, it is crucial to develop a more comprehensive list of food-related words. Within the context, this study delves into the exploration of expanding food-related words along with their associated energy densities.

Methods
This study addresses the aforementioned research gap by introducing a novel methodology for expanding the food-related word dictionary and predicting energy densities. Seed words are generated from official and crowdsourced food composition databases, and new food words are discovered by clustering food words within the word embedding space using the Gaussian mixture model. Machine learning models are employed to predict the energy density classifications of these food words based on their feature vectors. To ensure a thorough exploration of the prediction problem, ten widely used machine learning models are evaluated.

Results
The approach successfully expands the food-related word dictionary and accurately predicts food energy density (reaching 91.62%.). Through a comparison of the newly expanded dictionary with the initial seed words and an analysis of Yelp reviews in the city of Toronto, we observe significant improvements in identifying food words and gaining a deeper understanding of the food environment.

Conclusions
This study proposes a novel method to expand food-related vocabulary and predict the food energy density based on machine learning and word embedding. This method makes a valuable contribution to building a more comprehensive list of food words that can be used in geography and public health studies by mining geotagged social media data.
Periostin drives extracellular matrix degradation, stemness, and chemoresistance by activating the MAPK/ERK signaling pathway in triple–negative breast cancer cells
Authors: Wu Jinna , Li Jia , Xu Huiya , Qiu Ni , Huang Xiaojia , Li Hongsheng 
Published: September 2023

Abstract
Background
Adipose tissue, which is mainly composed of adipocytes, is a crucial component of the tumor microenvironment, particularly in breast cancer. Adipocytes surround breast cancer cells and may participate in cell‒cell interactions in the breast microenvironment. However, little is currently known about how adipocytes influence the biological behavior of the surrounding breast cancer cells. Hence, this study sought to investigate the role and underlying mechanisms of periostin in triple–negative breast cancer (TNBC) cells cocultured with adipogenic conditioned medium (ACM) and palmitic acid (PA).

Methods
Human TNBC cell lines (MDA‒MB‒231 and SUM159PT) were treated with ACM and PA, then the expression of periostin, matrix metalloproteinases (MMPs) and stemness–related molecules were assessed by Western blotting and RT‒qPCR. The cellular viability was assessed using CCK‒8 assay. Plasmid transfection, RNA sequencing, and pathway inhibitor were used to explore the specific mechanisms of periostin.

Results
ACM and PA elevated the expression of both MMPs and stemness–related molecules in TNBCs. MMPs can promote tumor cell infiltration and migration by degrading the extracellular matrix, and stemness expression increases the development of tumor chemoresistance. Additionally, ACM and PA increased periostin expression, while inhibiting periostin disrupted the involvement of ACM and PA in promoting extracellular matrix degradation, stemness, and chemoresistance in TNBCs. Furthermore, this study found that periostin promoted TNBC progression by activating the MAPK/ERK signaling pathway and that inhibition of MAPK/ERK signaling reduced the phenotype caused by periostin upregulation in TNBCs treated with ACM or PA. Finally, the present results showed that the high expression of POSTN, which encodes periostin, was substantially related to worse survival in TNBC patients.

Conclusions
The results of the study elucidated for the first time how periostin is the key protein secreted in TNBCs in response to the adipocyte–regulated tumor microenvironment, while periostin–neutralizing antibodies may serve as potential therapeutic agents in relation to TNBC progression.
Targeted co-delivery of curcumin and erlotinib by MoS2 nanosheets for the combination of synergetic chemotherapy and photothermal therapy of lung cancer
Authors: Chen Zhihuai , Wei Xinqi , Zheng Yunru , Zhang Zongwei , Gu Wang , Liao Wenjun , Zhang Hua , Wang Xiaoying , Liu Jian , Li Hua , Xu Wei 
Published: September 2023

Abstract
Background
Curcumin (Cur), a bioactive component of Chinese traditional medicine, has demonstrated inhibitory properties against cancer cell proliferation while synergistically enhancing the anticancer efficacy of erlotinib (Er). However, the individual limitations of both drugs, including poor aqueous solubility, lack of targeting ability, short half-life, etc., and their distinct pharmacokinetic profiles mitigate or eliminate their combined antitumor potential.

Results
In this study, we developed a molybdenum disulfide (MoS2)-based delivery system, functionalized with polyethylene glycol (PEG) and biotin, and co-loaded with Cur and Er, to achieve efficient cancer therapy. The MoS2-PEG-Biotin-Cur/Er system effectively converted near-infrared (NIR) light into heat, thereby inducing direct photothermal ablation of cancer cells and promoting controlled release of Cur and Er. Biotin-mediated tumor targeting facilitated the selective accumulation of MoS2-PEG-Biotin-Cur/Er at the tumor site, thus enhancing the synergistic antitumor effects of Cur and Er. Remarkably, MoS2-PEG-Biotin-Cur/Er achieved the combination of synergistic chemotherapy and photothermal therapy (PTT) upon NIR irradiation, effectively suppressing lung cancer cell proliferation and inhabiting tumor growth in vivo.

Conclusions
The as-synthesized MoS2-PEG-Biotin-Cur/Er, featuring high targeting ability, NIR light-responsive drug release, and the integration of synergistic chemotherapy and PTT, may provide a promising strategy for the treatment of lung cancer in clinical practice.

Graphical Abstract