bluuebunny/crossref_metadata_2025_split huggingface dataset:
ANALISIS PEMILIHAN MEDIA PROMOSI DIGITAL BERDASARKAN PERILAKU KONSUMEN MENGGUNAKAN APRIORI
Authors: Hendy M.Taufiq Sauma , Budiman Saiful Nur , Yuana Haris 
Published: November 2022

Associatian Rule merupakan metode data mining untuk menentukan asosiasi berbasis aturan dan menentukan korelasi antar variabel dalam suatu kumpulan data. Pada penelitian ini penggunaan metode association rule dipilih karena bertujuan untuk mengetahui penerapan algoritma apriori pada penelitian analisis dan juga mengetahui hasil pengujian dari pemilihan media promosi digital berdasarkan perilaku pembelian pelanggan. Dengan demikian melalui penelitian ini, pelaku UKM bisa mengetahui media digital yang paling tepat untuk mempromosikan produk kepada pelanggan yang sekarang lebih menyukai berbelanja secara online. Hasil penelitian menunjukkan bahwa 2 kombinasi itemset media yang cocok digunakan sebagai media promosi yang efektif, dimana media yang memiliki asosiasi terkuat adalah yaitu Instagram dan influenser. Kuatnya ikatan antar media yang meyakinkan dan dapat dijadikan acuan karena ketepatan kombinasi itemset yang saling berkorelasi dan validitas yang dihasilkan. Menetapkan nilai support minimal 0,3 dan confidence minimal 0,8 untuk menghitung metode association rule, terlihat bahwa komponen (D,H) yang mewakili Instagram dan influencer memiliki nilai support sebesar 0,388889 dan nilai confidence sebesar 0,807692.Kemudian untuk hasil pengujian didapatkan hasil lift ratio lebih besar dari 1 yaitu sebesar 1,615385 yang menunjukkan adanya sinergi antara Instagram dengan influencer. Dengan demikian, para UKM dapat menjadikan hasil penelitian ini sebagai alat bisnis digital melalui Instagram dan influencer untuk meningkatkan penjualan produknya.
Detection of Brucella S2 vaccine strain by a loop-mediated isothermal amplification (LAMP) method
Authors: Mu Jiaming , Li Qi , Yan Xu , Mao Xiaowei , Shi Yaqin , Qin Yun , Liu Chunxia , Wang Wenlong 
Published: November 2022

IntroductionBrucellosis is a highly prevalent zoonotic disease caused byBrucellaspp.Brucella suisS2 vaccination is an effective strategy to prevent animal brucellosis. However, S2 induces antibodies against the smooth lipopolysaccharide,making it challenging to distinguish field infected from vaccinated livestock. Early and accurate diagnosis is essential for infection control and prevention. In this study, we aimed to develop a quick and accurate assay to distinguish theBrucellaS2vaccine strain from closely relatedB. abortusandB. melitensis.MethodsWhole-genome sequencing ofB. suis S2was performed, and the sequence was compared with that of the genomes ofB. abortusandB. melitensis. One specific gene,GL_0002189, was selected as a marker to differentiate theBrucellaS2vaccine strain fromB. abortusandB. melitensis. A loop-mediated isothermal amplification (LAMP) assay was developed, based on theGL_0002189gene, and then assessed for target specificity, lower limit of detection, and repeatability.ResultsOur results revealed that there was no cross-reaction with other strains, and the LAMP assay displayed high sensitivity for detecting S2 with a minimum detection limit of 18.9×103 copies/µL DNA input, it is nearly 100 times higher than conventional PCR technology. Concordance between the LAMP assay and a conventional polymerase chain reaction method was assessed using 54 blood samples collected from sheep with suspected brucellosis. Total concordance between the two assays was 92.6%, without a significant difference (p &gt; 0.05) in the test results.ConclusionThis is the first report of a LAMP assay for the detection of theB. suisS2vaccine strain. Our approach can be helpful for the control and eradication of brucellosis, and its simplicity in requiring no specialized equipment or personnel makes it useful for implementation in resource-limited settings as well as for field use.
Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study
Authors: Liu XiaoHuan , Zhang Weiyue , Zhang Qiao , Chen Long , Zeng TianShu , Zhang JiaoYue , Min Jie , Tian ShengHua , Zhang Hao , Huang Hantao , Wang Ping , Hu Xiang , Chen LuLu 
Published: November 2022

BackgroundOpportunely screening for diabetes is crucial to reduce its related morbidity, mortality, and socioeconomic burden. Machine learning (ML) has excellent capability to maximize predictive accuracy. We aim to develop ML-augmented models for diabetes screening in community and primary care settings.Methods8425 participants were involved from a population-based study in Hubei, China since 2011. The dataset was split into a development set and a testing set. Seven different ML algorithms were compared to generate predictive models. Non-laboratory features were employed in the ML model for community settings, and laboratory test features were further introduced in the ML+lab models for primary care. The area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (auPR), and the average detection costs per participant of these models were compared with their counterparts based on the New China Diabetes Risk Score (NCDRS) currently recommended for diabetes screening.ResultsThe AUC and auPR of the ML model were 0·697and 0·303 in the testing set, seemingly outperforming those of NCDRS by 10·99% and 64·67%, respectively. The average detection cost of the ML model was 12·81% lower than that of NCDRS with the same sensitivity (0·72). Moreover, the average detection cost of the ML+FPG model is the lowest among the ML+lab models and less than that of the ML model and NCDRS+FPG model.ConclusionThe ML model and the ML+FPG model achieved higher predictive accuracy and lower detection costs than their counterpart based on NCDRS. Thus, the ML-augmented algorithm is potential to be employed for diabetes screening in community and primary care settings.
Circulating tumor DNA profile and its clinical significance in patients with hormone receptor-positive and HER2-negative mBC
Authors: Tang Yu , Li Jing , Liu Binliang , Ran Jialu , Hu Zhe-Yu , Ouyang Quchang 
Published: November 2022

BackgroundAfter early-line (first- and second-line) endocrine therapy, hormone-receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancers (mBCs) become resistant to endocrine therapy. Genetic alterations may underlie resistance to endocrine therapies. This study aims to investigate the circulating tumor DNA (ctDNA) alterations and the clinical implication in hormone-receptor-positive, HER2-negative metastatic breast cancer patients with multiline endocrine therapy failure.MethodsThis registered study (NCT05079074, ClinicalTrials.gov) enrolled 104 patients with hormone-receptor-positive, HER2-negative metastatic breast cancer who progressed after the early-line endocrine therapy. ctDNA alterations were analyzed by next generation sequencing (NGS). ctDNA alterations were ranked and clustered by using R ‘ComplexHeatmap’ and ‘hclust’ function. ctDNA-guided therapy was administrated. Progression-free survival (PFS) was assessed COX regression analysis, and Kaplan-Meier curves were plotted.FindingsThe top ctDNA altered genes were TP53 (39%), PIK3CA (38%), BRCA1/2 (13%), ESR1 (12%), FGFR (11%), ERBB2 (11%), and GATA3 (9%). Among these genes, TP53, PIK3CA helix domain mutation (PIK3CA-HD), FGFR, ESR1 and GATA3 were related to endocrine therapy resistance. The genetic landscapes changed and tumor mutation burden increased in both TP53-altered and PIK3CA-altered patients. Both BRCA1/2 and ERBB2 alterations correlated with TP53 alterations (P=0.02 and P=0.04, respectively). However, while 93% BRCA1/2 alterations concentrated in PIK3CA-wildtype patients, 82% ERBB2 alterations concentrated in PIK3CA-altered patients. Kaplan–Meier curves showed that patients who received druggable ctDNA alteration-guided treatment (DDAT) had significantly longer PFS than those who received physician-chosen therapy, with median PFS of 6.1 months versus 4.6 months (hazard ratio = 0.53, 95% CI: 0.34-0.85, Logrank P = 0.006).ConclusionMultiple genetic alterations were important reasons for the failure of endocrine therapy for HR-positive and HER2-negative mBC. Targeting these genes might restore the treatment sensitivity and benefit survival.
Diagnosis of giant cell arteritis by temporal artery biopsy is associated with biopsy length
Authors: Ruediger Carlee , Ninan Jem , Dyer Kathryn , Lyne Suellen , Tieu Joanna , Black Rachel J. , Dodd Thomas , Lester Susan , Hill Catherine L. 
Published: November 2022

AimsTemporal artery biopsy (TAB) is a widely used method for establishing a diagnosis of Giant Cell Arteritis (GCA). The optimal TAB length for accurate histological GCA diagnosis has been suggested as 15 mm post-fixation (15–20 mm pre-fixation). The aim of this study was to determine the relationship between a histological GCA diagnosis and optimal TAB length in the South Australian (SA) population.Materials and methodsPre-fixation TAB length (mm) was reported in 825/859 of all samples submitted to SA Pathology between 2014 and 2020 from people aged 50 and over. When more than one biopsy was taken, the longest length was recorded. Analyses of both TAB length and TAB positive proportions were performed by multivariable linear and logistic regression analysis, including covariates sex, age, and calendar year.ResultsThe median age of participants was 72 (IQR 65, 79) years, 549 (66%) were female. The TAB positive proportion was 172/825 (21%) with a median biopsy length of 14 mm (IQR 9, 18). Biopsy length (mm) was shorter in females (p = 0.001), increased with age (p = 0.006), and a small positive linear trend with calendar year was observed (p = 0.015). The TAB positive proportion was related to older age (slope/decade: 6, 95% CI 3.6, 8.3, p &lt; 0.001) and to TAB length (slope/mm 0.6, 95% CI 0.2, 0.9, p = 0.002), but not sex or calendar year. Comparison of models with TAB length cut-points at 5, 10, 15, 20 mm in terms of diagnostic yield, receiver operating characteristics and Akaike Information Criteria confirmed ≥ 15 mm as an appropriate, recommended TAB length. However, only 383 (46%) of the biopsies in our study met this criteria. The diagnostic yield at this cut-point was estimated as 25% which equates to an expected additional 30 histologically diagnosed GCA patients.ConclusionThis study confirms that TAB biopsy length is a determinant of a histological diagnosis of temporal arteritis, and confirms that a TAB length ≥ 15 mm is optimal. Approximately half the biopsies in this study were shorter than this optimal length, which has likely led to under-diagnosis of biopsy-proven GCA in SA. Further work is needed to ensure appropriate TAB biopsy length.
Development and external validation of a radiomics combined with clinical nomogram for preoperative prediction prognosis of resectable pancreatic ductal adenocarcinoma patients
Authors: Wang Fangqing , Zhao Yuxuan , Xu Jianwei , Shao Sai , Yu Dexin 
Published: November 2022

PurposeTo develop and externally validate a prognosis nomogram based on contrast-enhanced computed tomography (CECT) combined clinical for preoperative prognosis prediction of patients with pancreatic ductal adenocarcinoma (PDAC).Methods184 patients from Center A with histopathologically confirmed PDAC who underwent CECT were included and allocated to training cohort (n=111) and internal validation cohort (n=28). The radiomic score (Rad - score) for predicting overall survival (OS) was constructed by using the least absolute shrinkage and selection operator (LASSO). Univariate and multivariable Cox regression analysis was used to construct clinic-pathologic features. Finally, a radiomics nomogram incorporating the Rad - score and clinical features was established. External validation was performed using Center B dataset (n = 45). The validation of nomogram was evaluated by calibration curve, Harrell’s concordance index (C-index) and decision curve analysis (DCA). The Kaplan-Meier (K-M) method was used for OS analysis.ResultsUnivariate and multivariate analysis indicated that Rad – score, preoperative CA 19-9 and postoperative American Joint Committee on Cancer (AJCC) TNM stage were significant prognostic factors. The nomogram based on Rad - score and preoperative CA19-9 was found to exhibit excellent prediction ability: in the training cohort, C-index was superior to that of the preoperative CA19-9 (0.713 vs 0.616, P&lt; 0.001) and AJCC TNM stage (0.713 vs 0.614, P&lt; 0.001); the C-index was also had good performance in the validation cohort compared with CA19-9 (internal validation cohort: 0.694 vs 0.555, P&lt; 0.001; external validation cohort: 0.684 vs 0.607, P&lt; 0.001) and AJCC TNM stage (internal validation cohort: 0.694 vs 0.563, P&lt; 0.001; external validation cohort: 0.684 vs 0.596, P&lt; 0.001). The calibration plot and DCA showed excellent predictive accuracy in the validation cohort.ConclusionWe established a well-designed nomogram to accurately predict OS of PDAC preoperatively. The nomogram showed a satisfactory prediction effect and was worthy of further evaluation in the future.
Comparative efficacy and safety of prophylactic norepinephrine and phenylephrine in spinal anesthesia for cesarean section: A systematic review and meta-analysis with trial sequential analysis
Authors: Liu Peng , He Hong , Zhang Shan-Shan , Liang Yun , Gao Zi-Jun , Yuan Hui , Dong Bu-Huai 
Published: November 2022

Background: Phenylephrine is the first-line drug used to maintain blood pressure in cesarean delivery. However, it poses a high risk of bradycardia and depression of cardiac activity in pregnant women. Consequently, norepinephrine has gained popularity over the recent years, as an alternative to Phenylephrine because it is thought that prophylactic use of vasopressors may reduce the incidence of hypotension after spinal anesthesia. This systematic review compared the efficacy of both treatments.Methods: We searched the following databases; CNKI, PubMed, Embase, Web of science, clinicaltrials.gov, Medline and Cochrane Library, for randomized controlled trials comparing the prophylactic efficacy of norepinephrine and phenylephrine on elective cesarean delivery under spinal anesthesia. The search period was from inception to July 2022, and the primary outcome indicator was incidence of bradycardia. Statistical analysis was conducted on Rev manager 5.4, and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework was used to evaluate the quality of evidence from each main finding.Results: A total of 12 papers were included in the analysis. The incidence of bradycardia (RR = 0.37, 95% CI: 0.28 to 0.49, p &lt; 0.00001) and reactive hypertension (RR = 0.58, 95% CI 0.40 to 0.83, p = 0.003) was significantly lower in the norepinephrine (NE) group compared with the phenylephrine (PE) category. In contrast, there were no statistical differences in the umbilical cord blood gas analysis pH values between the groups (arterial: MD = 0.00, 95% CI −0.00 to 0.01, p = 0.22, vein: MD = 0.01, 95% CI −0.00 to 0.02, p = 0.06). The incidence of hypotension, nausea, and vomiting did not differ significantly between the NE and PE groups (hypotension: 23% vs. 18%; nausea: 14% vs. 18%; vomiting: 5% vs. 7%, respectively).Conclusion: Prophylactic use of norepinephrine is safe and effective in maintaining maternal hemodynamics without causing adverse events to either the pregnant woman or fetus.Systematic Review Registration: website https://www.crd.york.ac.uk/prospero/, identifier CRD42022347095
A risk model developed based on necroptosis to assess progression for ischemic cardiomyopathy and identify possible therapeutic drugs
Authors: Lu Yang , Wang Dashuai , Zhu Yaoxi , Du Yimei , Zhang Jinying , Yang Han 
Published: November 2022

Object: Ischemic cardiomyopathy (ICM), with high morbidity and mortality, is the most common cause of heart failure. Cardiovascular remodeling secondary to chronic myocardial ischemia is the main cause of its progression. A recently identified type of programmed cell death called necroptosis is crucial in the development of various cardiovascular diseases. However, the function role of necroptosis in cardiac remodeling of ICM has not been elucidated. Our study aimed to screen for genes associated with necroptosis and construct a risk score to assess the progression and evaluate the prognosis of ICM patients, and further to search for potentially therapeutic drugs.Methods: The gene expression profiling was obtained from the GEO database. LASSO regression analysis was used to construct necroptosis-related gene signatures associated with ICM progression and prognosis. TF-gene and miRNA-gene networks were constructed to identify the regulatory targets of potential necroptosis-related signature genes. Pathway alterations in patients with high necroptosis-related score (NRS) were analyzed by GO, KEGG, GSEA analysis, and immune cell infiltration was estimated by ImmuCellAI analysis. CMap analysis was performed to screen potential small molecule compounds targeting patients with high NRS. Independent risk analyses were performed using nomograms.Results: Six necroptosis-related signature genes (STAT4, TNFSF10, CHMP5, CHMP18, JAK1, and CFLAR) were used to define the NRS, with areas under the ROC curves of 0.833, 0.765, and 0.75 for training test, test set, and validation set, respectively. Transcription factors FOXC1 and hsa-miR-124-3p miRNA may be regulators of signature genes. Patients with higher NRS have pathway enriched in fibrosis and metabolism and elevated nTreg cells. AZD-7762 may be an effective drug to improve the prognosis of patients with high NRS. A feature-based nomogram was constructed from which patients could derive clinical benefit.Conclusion: Our results reveal 6 necroptosis gene signatures that can evaluate the progression and prognosis of ICM with high clinical value, and identify potential targets that could help improve cardiovascular remodeling.
Community pharmacists’ views and experiences toward over-the-counter medicines misuse and abuse in Saudi Arabia: A qualitative study
Authors: Algarni Mohammad , Jalal Zahraa , Hadi Muhammad Abdul , Alghamdi Saleh 
Published: November 2022

Background: Community pharmacists are uniquely positioned to identify and address the issue of misuse and abuse of over-the-counter (OTC) medicines. To date, no study has explored the Saudi community pharmacists’ views and experiences regarding aspects of OTC medicines’ misuse and abuse.Objective: To explore the views and experiences of the Saudi community pharmacists towards OTC medicines misuse and abuse. Furthermore, we aimed to identify frequently misused and abused medicines, the reasons and contributing factors, the role of pharmacists, and potential risk-mitigating strategies.Methods: Semi-structured interviews were conducted with a convenient sample of sixteen community pharmacists recruited from community pharmacies across the AL-Baha region, Saudi Arabia. Interviews were conducted using a pilot-tested interview guide in the Arabic language. All interviews were audio-recorded, transcribed verbatim, translated from Arabic into English, and then thematically analysed.Results: Analysis of interviews generated five main themes, including the commonly misused and abused OTC medicines, reasons and factors contributing to misuse and abuse of OTC medicines, pharmacists’ interventions to manage misuse and abuse, challenges and barriers to pharmacists’ interventions in misuse and abuse issues; and potential strategies to reduce the risk of OTC medicines misuse and abuse and improve pharmacists’ practice. Sedative antihistamines, cough products containing dextromethorphan, codeine-based analgesics, and non-codeine-based analgesics were commonly misused and abused OTC medicines. Managing ongoing medical conditions was the main reason for misusing OTC analgesics while recreational use and inducing sleep were the common reasons for abuse. Several factors contributing to misuse and abuse were reported, including unprofessional advice sought from other people, lack of awareness about medicines, and commercial advertisement of OTC products. Community pharmacists identified misuse and abuse among customers by judging their behaviours and attitudes and using structured questioning techniques. Counselling customers on the appropriate use of medicines, providing safe alternatives, and refusing to sell products were among the commonly used actions of pharmacists to address misuse/abuse. Pharmacists proposed several strategies to reduce the risk of OTC medicines misuse/abuse but believed that rescheduling OTC medicines with abuse potential to prescription-only medicine was the best option.Conclusion: Community pharmacists believed that the misuse and abuse of OTC medicines amongst pharmacy customers was common. A multidimensional strategy consisting of upskilling community pharmacists, a comprehensive review of OTC medicines sale regulations, and patient education to limit the risks of OTC medicines misuse/abuse is required.
Data assimilation on mechanistic models of glucose metabolism predicts glycemic states in adolescents following bariatric surgery
Authors: Richter Lauren R. , Albert Benjamin I. , Zhang Linying , Ostropolets Anna , Zitsman Jeffrey L. , Fennoy Ilene , Albers David J. , Hripcsak George 
Published: November 2022

Type 2 diabetes mellitus is a complex and under-treated disorder closely intertwined with obesity. Adolescents with severe obesity and type 2 diabetes have a more aggressive disease compared to adults, with a rapid decline in pancreatic β cell function and increased incidence of comorbidities. Given the relative paucity of pharmacotherapies, bariatric surgery has become increasingly used as a therapeutic option. However, subsets of this population have sub-optimal outcomes with either inadequate weight loss or little improvement in disease. Predicting which patients will benefit from surgery is a difficult task and detailed physiological characteristics of patients who do not respond to treatment are generally unknown. Identifying physiological predictors of surgical response therefore has the potential to reveal both novel phenotypes of disease as well as therapeutic targets. We leverage data assimilation paired with mechanistic models of glucose metabolism to estimate pre-operative physiological states of bariatric surgery patients, thereby identifying latent phenotypes of impaired glucose metabolism. Specifically, maximal insulin secretion capacity, σ, and insulin sensitivity, SI, differentiate aberrations in glucose metabolism underlying an individual’s disease. Using multivariable logistic regression, we combine clinical data with data assimilation to predict post-operative glycemic outcomes at 12 months. Models using data assimilation sans insulin had comparable performance to models using oral glucose tolerance test glucose and insulin. Our best performing models used data assimilation and had an area under the receiver operating characteristic curve of 0.77 (95% confidence interval 0.7665, 0.7734) and mean average precision of 0.6258 (0.6206, 0.6311). We show that data assimilation extracts knowledge from mechanistic models of glucose metabolism to infer future glycemic states from limited clinical data. This method can provide a pathway to predict long-term, post-surgical glycemic states by estimating the contributions of insulin resistance and limitations of insulin secretion to pre-operative glucose metabolism.