bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of oral metformin on gut microbiota characteristics and metabolite fractions in normal-weight type 2 diabetic mellitus patients
Authors: Niu Xiaohong , Wang Ying , Huang Linqing , Guo Pengna , Zhang Shi , Sun Yan , Jin Miaomiao 
Published: August 2024

Background and aimsTo analyze the effect of oral metformin on changes in gut microbiota characteristics and metabolite composition in normal weight type 2 diabetic patients.MethodsT2DM patients in the cross-sectional study were given metformin for 12 weeks. Patients with unmedicated T2DM were used as a control group to observe the metrics of T2DM patients treated with metformin regimen. 16S rDNA high-throughput gene sequencing of fecal gut microbiota of the study subjects was performed by llumina NovaSeq6000 platform. Targeted macro-metabolomics was performed on 14 cases of each of the gut microbiota metabolites of the study subjects using UPLC-MS/MS technology. Correlations between the characteristics of the gut microbiota and its metabolites, basic human parameters, glycolipid metabolism indicators, and inflammatory factors were analyzed using spearman analysis.ResultsGlycolipid metabolism indexes and inflammatory factors were higher in normal-weight T2DM patients than in the healthy population (P&lt;0.05), but body weight, BMI, waist circumference, and inflammatory factor concentrations were lower in normal-weight T2DM patients than in obese T2DM patients (P&lt;0.05). Treatment with metformin in T2DM patients improved glycolipid metabolism, but the recovery of glycolipid metabolism was more pronounced in obese T2DM patients. None of the differences in α-diversity indexes were statistically significant (P&gt;0.05), and the differences in β-diversity were statistically significant (P &lt;0.05). Community diversity and species richness recovered after metformin intervention compared to before, and were closer to the healthy population. We found that Anaerostipes/Xylose/Ribulose/Xylulose may play an important role in the treatment of normal-weight T2DM with metformin by improving glycemic lipids and reducing inflammation. And Metformin may play a role in obese T2DM through Romboutsia, medium-chain fatty acids (octanoic acid, decanoic acid, and dodecanoic acid).ConclusionGut microbial dysbiosis and metabolic disorders were closely related to glucose-lipid metabolism and systemic inflammatory response in normal-weight T2DM patients. Metformin treatment improved glucose metabolism levels, systemic inflammation levels in T2DM patients, closer to the state of healthy population. This effect may be mediated by influencing the gut microbiota and microbial host co-metabolites, mainly associated with Anaerostipes and xylose/Ribulose/Xylulose. Metformin may exert its effects through different pathways in normal-weight versus obese T2DM patients.
Plasma metabolites as potential markers and targets to prevent and treat urolithiasis: a Mendelian randomization study
Authors: Zhu Wuhui , Li Huan , Zhang Ming , Ji Bing , Liu Zongtao 
Published: August 2024

BackgroundStudies on the relationships between diseases of the urinary system and human plasma proteomes have identified several potential biomarkers. However, none of these studies have elucidated the causal relationships between plasma proteins and urolithiasis.ObjectiveThe objective of the study was to investigate the potential risks of plasma metabolites in urolithiasis using a two-sample Mendelian randomization (MR) study.MethodsA total of 1,400 metabolites were identified in the most comprehensive genome-wide association study (GWAS) of plasma metabolomics in a European population to date, and single-nucleotide polymorphisms (SNPs) were used as the instrumental variables for the plasma metabolites. The European GWAS data for urinary calculi included 482,123 case samples and 6,223 control samples (ebi-a-GCST90018935). The associations between the plasma metabolites and risk of urolithiasis were evaluated by inverse variance weighting (IVW) and supplemented by sensitivity analyses of the MR-Egger and MR-PRESSO tests.ResultsFor the first time, we found a causal relationship between two plasma metabolites (p &lt; 1.03 × 10−4) and urolithiasis (p &lt; 0.05). The chemical 4-hydroxychlorothalonil, which is an intermediate product of the pesticide hydroxychlorothalonil, could promote urolithiasis (odds ratio (OR) = 1.12) as a risk factor. Moreover, 1-stearoyl-2-arachidonoyl-GPC, which is an important component of phospholipid metabolism in the human body, can inhibit urolithiasis (OR = 0.94).Conclusions Our results suggest that blood metabolites can be used as blood markers and drug targets in the prevention, diagnosis, and treatment of urolithiasis; furthermore, our results can provide a basis for policy makers to formulate prevention and treatment policies for urolithiasis.
Enhancing pediatric attention-deficit hyperactivity disorder treatment: exploring the gut microbiota effects of French maritime pine bark extract and methylphenidate intervention
Authors: Weyns Anne-Sophie , Ahannach Sarah , Van Rillaer Tim , De Bruyne Tess , Lebeer Sarah , Hermans Nina 
Published: August 2024

IntroductionThe pathogenesis of Attention-Deficit Hyperactivity Disorder (ADHD) is thought to be multifactorial, with a potential role for the bidirectional communication between the gut microbiome and brain development and function. Since the “golden-standard” medication therapy with methylphenidate (MPH) is linked to multiple adverse effects, there is a need for alternative treatment options such as dietary polyphenols. These secondary plant metabolites exert antioxidant and anti-inflammatory effects, but much less is known about their impact on the gut microbiota. Since polyphenols are believed to modulate gut microbial composition, interventions might be advantageous in ADHD therapy. Therefore, intervention studies with polyphenols in ADHD therapy investigating the gut microbial composition are highly relevant.MethodsBesides the primary research questions addressed previously, this study explored a potential prebiotic effect of the polyphenol-rich French Maritime Pine Bark Extract (PBE) compared to MPH and a placebo in pediatric ADHD patients by studying their impact on the gut microbiota via amplicon sequencing of the full length 16S rRNA gene ribosomal subunit (V1-V9).ResultsOne interesting finding was the high relative abundance of Bifidobacteria among all patients in our study cohort. Moreover, our study has identified that treatment (placebo, MPH and PBE) explains 3.94% of the variation in distribution of microbial taxa (adjusted p-value of 0.011).DiscussionOur small sample size (placebo: n = 10; PBE: n = 13 and MPH: n = 14) did not allow to observe clear prebiotic effects in the patients treated with PBE. Notwithstanding this limitation, subtle changes were noticeable and some limited compositional changes could be observed.Clinical Trial Registrationdoi: 10.1186/S13063-017-1879-6
A real-world pharmacovigilance study of KRAS G12C mutation inhibitors based on the food and drug administration adverse event reporting system
Authors: Wu Lisha , Xu Maosheng , Li Xueqin , Aierken Dilinuer , Yu Jinxiu , Qin Tao 
Published: August 2024

IntroductionSotorasib and adagrasib have been widely used for the non-small cell lung cancer (NSCLC) patients harboring Kirsten rat sarcoma viral oncogene homolog (KRAS) G12C mutation. It's necessary to assess their safety profiles in the real-world population.MethodsA retrospective pharmacovigilance was conducted to examine adverse events (AEs) associated with sotorasib and adagrasib therapies using the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Disproportionality analysis was performed employing Venn analysis and four data-mining algorithms, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS).ResultsThe most commonly reported system organ classes (SOCs) for both adagrasib and sororasib were general, gastrointestinal, and investigations disorders. Notably, sotorasib exhibited significant signals for neoplasms and hepatobiliary disorders in four algorithms. Specifically, AEs related to neoplasms were predominantly associated with lung malignancies, all of which were consistent with the therapeutic indications of KRAS G12C mutation inhibitor. A total of 19 common AEs were identified in sotorasib and adagrasib, spanning gastrointestinal, general, hepatobiliary, investigations, metabolism, musculoskeletal, neoplasms, and respiratory disorders. 4 severe AEs (SAEs) were identified in sotorasib, with 3 SAEs displaying significant signals in four algorithms, including drug-induced liver injury, pancreatitis, and hepatic failure. In adagrasib, only 2 SAEs were detected, with renal failure showing significant signals in four algorithms.ConclusionThis study offers a comprehensive evaluation of the major safety signals associated with sotorasib and adagrasib, providing valuable information for clinicians regarding drug selection and safety considerations, thereby facilitating the design of future prospective safety studies.
Predicting the efficiency of chidamide in patients with angioimmunoblastic T-cell lymphoma using machine learning algorithm
Authors: Zhang Chunlan , Xu Juan , Gu Mingyu , Tang Yun , Tang Wenjiao , Wang Jie , Liu Qinyu , Yang Yunfan , Zhong Xushu , Xu Caigang 
Published: August 2024

BackgroundChidamide is subtype-selective histone deacetylase (HDAC) inhibitor that showed promising result in clinical trials to improve prognosis of angioimmunoblastic T-cell lymphoma (AITL) patients. However, in real world settings, contradictory reports existed as to whether chidamide improve overall survival (OS). Therefore, we aimed to develop an interpretable machine learning (Machine learning)–based model to predict the 2-year overall survival of AITL patients based on chidamide usage and baseline features.MethodsA total of 183 patients with AITL were randomly divided into training set and testing set. We used 5 ML algorithms to build predictive models. Recursive feature elimination (RFE) method was used to filter for the most important features. The ML models were interpreted and the relevance of the selected features was determined using the Shapley additive explanations (SHAP) method and the local interpretable model–agnostic explanationalgorithm.ResultsA total of 183 patients with newly diagnosed AITL from 2012 to 2022 from 3 centers in China were enrolled in our study. Seventy-one patients were dead within 2 years after diagnosis. Five ML algorithms were built based on chidamide usage and 16 baseline features to predict 2-year OS. Catboost model presented to be the best predictive model. After RFE screening, 12 variables demonstrated the best performance (AUC = 0.8651). Using chidamide ranked third among all the variables that correlated with 2-year OS.ConclusionThis study demonstrated that the Catboost model with 12 variables could effectively predict the 2-year OS of AITL patients. Combining chidamide in the treatment therapy was positively correlated with longer OS of AITL patients.
QTL-Seq identified a genomic region on chromosome 1 for soil-salinity tolerance in F2 progeny of Thai salt-tolerant rice donor line “Jao Khao”
Authors: Khunsanit Prasit , Jitsamai Navarit , Thongsima Nattana , Chadchawan Supachitra , Pongpanich Monnat , Henry Isabelle M. , Comai Luca , Suriya-Arunroj Duangjai , Budjun Itsarapong , Buaboocha Teerapong 
Published: August 2024

IntroductionOwing to advances in high-throughput genome sequencing, QTL-Seq mapping of salt tolerance traits is a major platform for identifying soil-salinity tolerance QTLs to accelerate marker-assisted selection for salt-tolerant rice varieties. We performed QTL-BSA-Seq in the seedling stage of rice from a genetic cross of the extreme salt-sensitive variety, IR29, and “Jao Khao” (JK), a Thai salt-tolerant variety.MethodsA total of 462 F2 progeny grown in soil and treated with 160 mM NaCl were used as the QTL mapping population. Two high- and low-bulk sets, based on cell membrane stability (CMS) and tiller number at the recovery stage (TN), were equally sampled. The genomes of each pool were sequenced, and statistical significance of QTL was calculated using QTLseq and G prime (G′) analysis, which is based on calculating the allele frequency differences or Δ(SNP index).ResultsBoth methods detected the overlapping interval region, wherein CMS-bulk was mapped at two loci in the 38.41–38.85 Mb region with 336 SNPs on chromosome 1 (qCMS1) and the 26.13–26.80 Mb region with 1,011 SNPs on chromosome 3 (qCMS3); the Δ(SNP index) peaks were −0.2709 and 0.3127, respectively. TN-bulk was mapped at only one locus in the overlapping 38.26–38.95 Mb region on chromosome 1 with 575 SNPs (qTN1) and a Δ(SNP index) peak of −0.3544. These identified QTLs in two different genetic backgrounds of segregating populations derived from JK were validated. The results confirmed the colocalization of the qCMS1 and qTN1 traits on chromosome 1. Based on the CMS trait, qCMS1/qTN1 stably expressed 6%–18% of the phenotypic variance in the two validation populations, while qCMS1/qTN1 accounted for 16%–20% of the phenotypic variance in one validation population based on the TN trait.ConclusionThe findings confirm that the CMS and TN traits are tightly linked to the long arm of chromosome 1 rather than to chromosome 3. The validated qCMS-TN1 QTL can be used for gene/QTL pyramiding in marker-assisted selection to expedite breeding for salt resistance in rice at the seedling stage.
Examining bystander intervention for peer depression and sociodemographic correlates among university students in Singapore
Authors: Lim Benedict Wei Zhi , Koh Yen Sin , Shahwan Shazana , Goh Chong Min Janrius , Samari Ellaisha , Ong Wei Jie , Kwok Kian Woon , Chong Siow-Ann , Subramaniam Mythily 
Published: August 2024

IntroductionThe Advancing Research To Eliminate Mental Illness Stigma (ARTEMIS) study evaluated the impact of an intervention developed and implemented in Singapore on attitudes towards depression in university students. We aimed to assess the likelihood of university students intervening when their peers suffer from depression, before and after the ARTEMIS intervention.Methods390 students were recruited from a university in Singapore. The ARTEMIS intervention comprised a lecture by a trained mental health professional, a sharing session by a person with lived experience of depression, and a question-and-answer segment with a panel. The Bystander Intervention Scale for Depression (BISD) was administered at baseline, post-intervention, and 3-month follow-up. BISD assessed four factors: acceptance of responsibility to intervene, knowledge on how to intervene, awareness of depression among peers, and vigilance towards possible symptoms of depression. Linear mixed models were conducted to investigate associations. Sociodemographic correlates were also examined.ResultsA favourable shift in all factors was observed at post-intervention, which weakened at 3-month follow-up. Having past experience in the mental health field (β=1.50) and older age (β=0.18) were significantly associated with knowledge on how to intervene. Having social contact with mental illness (SCMI) and past experience in the mental health field (PEMHF) were significantly associated with awareness of depression among peers (SCMI β=0.89, PEMHF β=0.43) and vigilance towards possible symptoms of depression (SCMI β=0.39, PEMHF β=0.61).DiscussionThe short-term results of the intervention appeared promising across all BISD factors; however, these results were not sustained after 3 months. Future research should include the impact of ‘booster’ interventions over time. Sociodemographic factors that were identified to be significant correlates should also be considered when planning for future interventions.
Exploring infectious disease spread as a function of seasonal and pandemic-induced changes in human mobility
Authors: Cai Ruiqing , Spencer Zach , Ruktanonchai Nick 
Published: August 2024

IntroductionCommunity-level changes in population mobility can dramatically change the trajectory of any directly-transmitted infectious disease, by modifying where and between whom contact occurs. This was highlighted throughout the COVID-19 pandemic, where community response and nonpharmaceutical interventions changed the trajectory of SARS-CoV-2 spread, sometimes in unpredictable ways. Population-level changes in mobility also occur seasonally and during other significant events, such as hurricanes or earthquakes. To effectively predict the spread of future emerging directly-transmitted diseases, we should better understand how the spatial spread of infectious disease changes seasonally, and when communities are actively responding to local disease outbreaks and travel restrictions.MethodsHere, we use population mobility data from Virginia spanning Aug 2019-March 2023 to simulate the spread of a hypothetical directly-transmitted disease under the population mobility patterns from various months. By comparing the spread of disease based on where the outbreak begins and the mobility patterns used, we determine the highest-risk areas and periods, and elucidate how seasonal and pandemic-era mobility patterns could change the trajectory of disease transmission.Results and discussionThrough this analysis, we determine that while urban areas were at highest risk pre-pandemic, the heterogeneous nature of community response induced by SARS-CoV-2 cases meant that when outbreaks were occurring across Virginia, rural areas became relatively higher risk. Further, the months of September and January led to counties with large student populations to become particularly at risk, as population flows in and out of these counties were greatly increased with students returning to school.
PENGARUH UKURAN PERUSAHAAN, OPINI AUDIT DAN PERGANTIAN AUDITOR TERHADAP KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN
Authors: Witantri Witantri , Wilestari Median 
Published: August 2024

The study aims to examine the effect of Company Size, Audit Opinion, and Auditor Turnover on the timeliness of financial reporting. The population in this study is the consumer cylclicals sector companies listed on the Indonesia Stock Exchange for the period 2020-2022. The sampling method used was a purposive sampling method in order to obtain 87 companies. The total data processed in this study were 261 data. The type of data used is secondary data in the form of annual financial reports for companies in the consumer cyclicals sector listed on the Indonesia Stock Exchange for the period 2020-2022. The data analysis method used in this study is logistic regression with the help of SPSS software version 24. The results of the study prove that all variables of Company Size, Audit Opinion, and Auditor Turnover together positively influence the timeliness of financial reporting. Then the result of the study partially proves that Company Size has no significant effect on the timeliness of financial reporting, then Audit opinion and Auditor Turnover has a significant positive effect on the timeliness of financial reporting.
PREDIKSI CURAH HUJAN PERBULAN DI KOTA YOGYAKARTA PERIODE 2015-2019 MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DAN KALMAN FILTER (Studi Kasus : Data Curah Hujan Tahun 2015-2019)
Authors: Selamat Irene Kristija , Setyawan Yudi 
Published: August 2024

Curah hujan sangat menarik untuk dikaji sebab curah hujan merupakan salah satu faktor terbesar yang mempengaruhi iklim suatu wilayah dan mempengaruhi berbagai sektor kehidupan manusia. Penelitian ini bertujuan untuk mengetahui hasil prediksi curah hujan perbulan di Kota Yogyakarta periode 2015-2019 yang dianalisis menggunakan metode Autoregressive Integrated Moving Average (ARIMA) untuk mendapatkan hasil peramalan yang diharapkan dapat memberikan tingkat akurasi yang tinggi dan metode Kalman Filter yang merupakan sebuah model bagian dari state space (ruang keadaan) yang dapat diterapkan dalam model peramalan. Model ini menggunakan teknik rekursif untuk mengintegrasikan data pengamatan terbaru ke model untuk mengoreksi prediksi sebelumnya dan melakukan prediksi selanjutnya dan salah satu model runtun waktu yang digunakan dalam menentukan prediksi selanjutnya. Model ini bekerja secara rekursif untuk meminimalkan ketidaktepatan dalam peramalan. Kedua metode tersebut digunakan untuk memprediksi curah hujan (mm) perbulan di Kota Yogyakarta periode 2015-2019. Hasil penelitian menunjukkan bahwa model yang terbentuk adalah model ARIMA (1, 0, 1) dan model ARIMA (1,0,2). Setelah dilakukan perhitungan menggunakan metode ARIMA dan Kalman Filter, menggunakan nilai MSE, model yang terbaik adalah model ARIMA (1,0,1) menggunakan metode Kalman Filter karna memiliki nilai MSE terkecil yaitu sebesar 6,722873 dibanding metode ARIMA. Hal ini membuktikan bahwa prediksi menggunakan metode Kalman Filter baik dibandingkan metode ARIMA.
RETROSPECTIVE ANALYSIS OF THE MOSCOW CENTRAL CIRCLE RECONSTRUCTION PROJECT
Authors: Тарасова А.Ю. 
Published: August 2024

В условиях ограниченности ресурсов проекты комплексного развития территорий становятся все более актуальными. В частности, вопрос создания многофункциональных зон города Москвы носит стратегический характер, так как содействует созданию новых рабочих мест, активному развитию городских территорий, создавая тем самым дополнительные «точки притяжения» населения. В связи с этим высокая значимость отводится проекту по реконструкции Московского центрального кольца (МЦК) как катализатору развития социальной инфраструктуры. Статья посвящена оценке успешности проекта реконструкции. В рамках проводимого анализа в статье рассматриваются традиционные критерии, связанные с классическим проектным треугольником: его бюджетные, временные параметрыи содержание работ. Кроме того, анализируются дополнительные критерии: соответствие, устойчивость, социальный эффект и экономическая эффективность. Далее систематизированы реализовавшиеся риски и их влияние на результат проекта. Автором поднимается вопрос достижения заданных целей и установленных требований к продукту проекта. На основание проведенного анализа дается общая оценка успешности проекта. На основе анализа публикаций в статье также высказываются предположения о возможных направлениях работ с проектом по реконструкции МЦК в ближайшем будущем.
In limited resources conditions, projects for the integrated territories’ development are becoming more and more relevant. In particular, the issue of creating multifunctional zones in Moscow is of a strategic nature, as it contributes to the new workplaces’ creation, the active urban areas development, thereby creating additional "points of attraction" for the population. In this regard, high importance is given to the Moscow Central Circle reconstruction project as a catalyst for the social infrastructure development. The article is devoted to assessing the reconstruction project’s success. As part of the analysis, the article examines traditional criteria associated with the classic project triangle: its budget, time parameters and work content. In addition, other criteria are analyzed: compliance, sustainability, social impact and economic efficiency. Next, the realized risks and their impact on the project outcome are systematized. The author raises the issue of achieving the specified goals and established requirements for the project product. Based on the analysis, an overall assessment of the project success is given. The article also makes assumptions about possible areas of work with the MCC reconstruction project in the near future.