bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robustness Of Radiomics To Variations In Segmentation Methods In Multimodal Brain MRI
Authors: Poirot Maarten Gijsbert , Caan Matthan , Ruhe Henricus Gerardus , Bjørnerud Atle , Groote Inge , Reneman Liesbeth , Marquering Henk 
Published: March 2022

Abstract
Background: Radiomics in neuroimaging uses fully automatic segmentation to delineate the anatomical areas for which radiomic features are computed. However, differences among these segmentation methods affect radiomic features to an unknown extent.Method: A scan-rescan dataset (n=46) of T1-weighted and diffusion tensor images was used. Subjects were split into a sleep-deprivation and a control group. Scans were segmented using four segmentation methods from which radiomic features were computed. First, we measured segmentation agreement using the Dice-coefficient. Second, robustness and reproducibility of radiomic features were measured using the intraclass correlation coefficient (ICC). Last, difference in predictive power was assessed using the Friedman-test on performance in a radiomics-based sleep deprivation classification application.Results: Segmentation agreement was generally high (interquartile range=0.77-0.90) and median feature robustness to segmentation method variation was higher (ICC>0.7) than scan-rescan reproducibility (ICC 0.3-0.8). However, classification performance differed significantly among segmentation methods (p<0.001) ranging from 77% to 84%. Accuracy was higher for more recent deep learning-based segmentation methods.Conclusion: Despite high agreement among segmentation methods, subtle differences significantly affected radiomic features and their predictive power. Consequently, the effect of differences in segmentation methods should be taken into account when designing and evaluating radiomics-based research methods.
Implementation Rate and Effects of Multidisciplinary Team Meetings on Decision Making about Radiotherapy : An Observational Study at a Single Japanese Institution
Authors: Ichikawa Mayumi , Uematsu Ken , Yano Natsuko , Yamada Masayoshi , Ono Takashi , Kawashiro Shohei , Akamatsu Hiroko , Hagiwara Yasuhito , Sato Hiraku , Nemoto Kenji 
Published: March 2022

Abstract
Background: Cancer treatment requires a multidisciplinary approach. Therefore, multidisciplinary team meetings (MDTMs) have been widely used to determine the direction of treatment. However, no standard provisions exist for conducting MDTMs, and recommendations discussed in MDTMs are sometimes not implemented. ​This study analyzed the indications for radiotherapy discussed and recommended at MDTMs, identified the rate of radiotherapy recommendations for patients that were not implemented, and clarified the reasons at a single academic center in Japan.Methods: This was a cross-sectional study that analyzed the minutes and electronic medical records of cases discussed at MDTMs held between April 2012-March 2017 at Yamagata University Hospital. We categorized how radiotherapy was initially presented at MDTMs, determined the rate of radiotherapy recommendations made through MDTMs, analyzed whether treatment recommendations were subsequently implemented, and examined the causes of non-implementation. We performed a statistical analysis to assess some clinical factors (sex, age, number of multidisciplinary team meetings, and classification of planned treatment) associated with the non-implementation of radiotherapy recommendations from MDTMs.Results: A total of 1,813 cases were discussed at MDTMs, of which 71% (1,293 cases) were presented with treatment plans, including radiotherapy. Further, 66% (1,205 cases) were recommended for radiotherapy through the MDTMs. Recommendations from MDTMs were not implemented in 7% (142 cases). The most typical reason for non-implementation was the clinician’s opinion (30%), followed by patient preferences (27%) and disease progression (20%). Change in cancer stage and improvement in symptoms were 12% and 4%, respectively. These ratios were similar each year. We could not find the factors associated with the non-implementation of radiotherapy recommendations from MDTMs.Conclusions: MDTMs had a significant effect on the recommendation of radiotherapy for each patient with a tumor. The primary reason for the non-implementation of decisions made at MDTMs was the opinion of clinicians and the patient’s preference. These results were similar to previous studies. We need to establish a monitoring system where patients themselves can decide the treatments based on their choices while using the recommendations from MDTMs.
Antibiotic resistance pattern and molecular detection of ESBL-associated genes in E. coli from surface and wastewater of Islamabad capital territory, Pakistan
Authors: Ahsan Aitezaz , Rehman Tariq Atta Ur , Irshad Hamid , Shahzad Muhammad Armaghan , Siddique Abubakar , Jamil Asma , Ali Adnan 
Published: March 2022

Abstract
The goal of this study was to determine how surface and wastewater contribute to the contamination of the environment with an extended-spectrum β-lactamase-producing Escherichia coli (ESBL E. coli). Water samples (n = 32) were collected from eight different locations of Islamabad and processed for microbiological and molecular analyses of E. coli and ESBL E. coli. Antimicrobial susceptibility testing was carried out to determine the resistance pattern of the isolates. A total of 21 water samples were contaminated with E. coli and 15 isolates were identified as ESBL producers harboring blaTEM (40%) and blaCTX-M (33.33%) genes. Interestingly, all the ESBL E. coli isolates showed the least resistance against second-generation Cephalosporins compared to other generations. Moreover, the study showed that the aquatic environment is harboring multidrug-resistant E. coli; therefore, it may act as a source of transmission to humans. The recovery of ESBL E. coli isolates resistant to higher generation Cephalosporins, Monobactam, and Carbapenems from water samples indicated an alarming situation. Thus, there is an urgent need to treat water efficiently for microbial decontamination to minimize the transmission of antimicrobial-resistant (AMR) bacteria.
Heterotrimeric G Protein α-Subunits - Structures, Peptide-Derived Inhibitors, and Mechanisms
Authors: Voss Jan H. , Müller Christa E. 
Published: March 2022

Abstract:G protein-coupled receptors are the largest protein family in the human body and represent the most important class of drug targets. They receive extracellular signals and transduce them into the cytosol. The guanine nucleotide-binding Gα proteins represent the main relays by which GPCRs induce intracellular effects. More than 800 different GPCRs interact with 16 Gα proteins belonging to 4 families, Gαi, Gαs, Gαq, and Gα12/13. The direct inhibition of Gα protein subunits rather than the modulation of GPCR subtypes has been proposed as a novel strategy for the treatment of complex diseases, including inflammation and cancer. This mini-review presents an introduction to G protein structure and function and describes achievements in the development of peptidic and peptide-derived Gα protein inhibitors. They have become indispensable pharmacological tools, and some of them exhibit significant potential as future drugs.
Bioactive Compounds from Plants and their Immune Potential against
Corona Virus
Authors: Tingirikari Jagan Mohan Rao , Musini Anjaneyulu 
Published: March 2022

Background:
Corona virus is a contagious single-strand RNA virus affecting majorly
the lungs causing severe acute respiratory disease. The viral pandemic has affected the world
economy and posed new challenges to the scientific community. Due to high mutation rate, a lot of
variants are occurring and persons who are vaccinated are also getting affected. In addition, vaccination
trials for children aged below 18 are still going on. Moreover, the cost, shelf-life, success
rate, no booster dose required, and the long-term complications associated with the vaccine are yet
to be studied. Preservation and transportation of vaccines are another big challenge.

Objective:
Despite vaccination, the best alternative is to boost our immune system by administration
of bioactive compounds which are safe and effective. Bioactive compounds have been found
to be effective against several viral infections.

Methods:
Literature review has been performed using recently published research and review articles
pertaining to the role of plant-derived bioactive compounds in regulating COVID-19 infection.

Result:
The current review will describe the role and mechanism of bioactive compounds derived
from natural sources in disease management and boosting the immune system against COVID-19.

Conclusion:
In addition to vaccination, the administration of plant-derived bioactive compounds
will help in regulating viral infection and boosting the immune response during COVID-19 infection.
Knowledge, Awareness, and Practice of Gingival Veneer Prosthesis Among Dental Students, Interns, and Practitioners in the Riyadh Region: A Cross-Sectional Questionnaire-Based Survey
Authors: Altaleb Abdul Qader Mohammed , Albader Rayan Abdullah , Alfahad Muhannad Abdulaziz , AlGhizzi Mohammad Ghizzi Mohammad , Aldhuwayhi Sami , Mustafa Mohammed Ziauddeen , Thakare Amar Ashok , Naqvi Zuber Ahamed 
Published: March 2022

Background:The treatment modality of using gingival veneer prosthesis for anterior gingival recession is not widely known even in the dental fraternity. This survey has been conducted considering its essential nature and absence of data on its awareness in the Riyadh region.Aims:The aim of the study was to assess the knowledge, awareness, and practice of gingival veneer prosthesis among dental students, interns, and practitioners in the Riyadh region.Materials and Methods:A descriptive cross-sectional electronic survey was conducted on dental students, interns, and practitioners of both genders in Saudi Arabia, using a convenient sampling method. The final questionnaire consisted of 12 questions. The percentage of various responses, with reference to the demographics, and statistical significance, were tested by independent sample t-test and p-value <0.05. The responses/data of 446 participants were tabulated and processed in SPSS (version 21.0).Results:The preferred treatment option for an anterior gingival recession proposed by prosthodontists was prosthetic correction (p<0.05), and for other groups, it was periodontal surgery (p<0.05). 66% of general practitioners’ group and 56% of dental students and interns’ group, respectively, were not sure about the ideal treatment option for Miller’s class III & IV gingival defects, while 70% of general practitioners’ group and 65% of the students and interns’ group, respectively, were not sure about the ideal treatment option for the management of gingival tissue loss between implants,.Conclusion:There is a significant lack of knowledge on using gingival veneer prosthesis as a treatment option for anterior gingival defects among general dental practitioners, interns, and dental students (p˂0.05).
Relations Between BMI Trajectories and Habitual Physical Activity Measured by a Smartwatch in the Electronic Cohort of the Framingham Heart Study: Cohort Study
Authors: Hammond Michael M , Zhang Yuankai , Pathiravasan Chathurangi H. , Lin Honghuang , Sardana Mayank , Trinquart Ludovic , Benjamin Emelia J , Borrelli Belinda , Manders Emily S , Fusco Kelsey , Kornej Jelena , Spartano Nicole L , Kheterpal Vik , Nowak Christopher , McManus David D , Liu Chunyu , Murabito Joanne M 
Published: March 2022

Background
The prevalence of obesity is rising. Most previous studies that examined the relations between BMI and physical activity (PA) measured BMI at a single timepoint. The association between BMI trajectories and habitual PA remains unclear.

Objective
This study assesses the relations between BMI trajectories and habitual step-based PA among participants enrolled in the electronic cohort of the Framingham Heart Study (eFHS).

Methods
We used a semiparametric group-based modeling to identify BMI trajectories from eFHS participants who attended research examinations at the Framingham Research Center over 14 years. Daily steps were recorded from the smartwatch provided at examination 3. We excluded participants with <30 days or <5 hours of smartwatch wear data. We used generalized linear models to examine the association between BMI trajectories and daily step counts.

Results
We identified 3 trajectory groups for the 837 eFHS participants (mean age 53 years; 57.8% [484/837] female). Group 1 included 292 participants whose BMI was stable (slope 0.005; P=.75), group 2 included 468 participants whose BMI increased slightly (slope 0.123; P<.001), and group 3 included 77 participants whose BMI increased greatly (slope 0.318; P<.001). The median follow-up period for step count was 516 days. Adjusting for age, sex, wear time, and cohort, participants in groups 2 and 3 took 422 (95% CI –823 to –21) and 1437 (95% CI –2084 to –790) fewer average daily steps, compared with participants in group 1. After adjusting for metabolic and social risk factors, group 2 took 382 (95% CI –773 to 10) and group 3 took 1120 (95% CI –1766 to –475) fewer steps, compared with group 1.

Conclusions
In this community-based eFHS, participants whose BMI trajectory increased greatly over time took significantly fewer steps, compared with participants with stable BMI trajectories. Our findings suggest that greater weight gain may correlate with lower levels of step-based physical activity.
Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review
Authors: Yang Xinyu , Mu Dongmei , Peng Hao , Li Hua , Wang Ying , Wang Ping , Wang Yue , Han Siqi 
Published: March 2022

Background
With the accumulation of electronic health records and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of artificial intelligence based on electronic health records in cancer care.

Objective
The aim of this study was to conduct a review to introduce the current state and limitations of artificial intelligence based on electronic health records of patients with cancer and to summarize the performance of artificial intelligence in mining electronic health records and its impact on cancer care.

Methods
Three databases were systematically searched to retrieve potentially relevant papers published from January 2009 to October 2020. Four principal reviewers assessed the quality of the papers and reviewed them for eligibility based on the inclusion criteria in the extracted data. The summary measures used in this analysis were the number and frequency of occurrence of the themes.

Results
Of the 1034 papers considered, 148 papers met the inclusion criteria. Cancer care, especially cancers of female organs and digestive organs, could benefit from artificial intelligence based on electronic health records through cancer emergencies and prognostic estimates, cancer diagnosis and prediction, tumor stage detection, cancer case detection, and treatment pattern recognition. The models can always achieve an area under the curve of 0.7. Ensemble methods and deep learning are on the rise. In addition, electronic medical records in the existing studies are mainly in English and from private institutional databases.

Conclusions
Artificial intelligence based on electronic health records performed well and could be useful for cancer care. Improving the performance of artificial intelligence can help patients receive more scientific-based and accurate treatments. There is a need for the development of new methods and electronic health record data sharing and for increased passion and support from cancer specialists.
Associations Between the Digital Clock Drawing Test and Brain Volume: Large Community-Based Prospective Cohort (Framingham Heart Study)
Authors: Yuan Jing , Au Rhoda , Karjadi Cody , Ang Ting Fang , Devine Sherral , Auerbach Sanford , DeCarli Charles , Libon David J , Mez Jesse , Lin Honghuang 
Published: March 2022

Background
The digital Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies.

Objective
We aimed to investigate the association between dCDT features and brain volume.

Methods
This study included participants from the Framingham Heart Study who had both a dCDT and magnetic resonance imaging (MRI) scan, and were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those whose cognition was intact.

Results
A total of 1656 participants were included in this study (mean age 61 years, SD 13 years; 50.9% women), with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value <.05/18). Eleven dCDT composite scores were associated with cerebral white matter volume, but only 1 dCDT composite score was associated with cerebral gray matter volume. None of the dCDT composite scores was associated with hippocampal volume or WMH volume. The classification model for differentiating MCI and normal cognition participants, which incorporated age, sex, education, MRI measures, and dCDT composite scores, showed an area under the curve of 0.897.

Conclusions
dCDT composite scores were significantly associated with multiple brain MRI measures in a large community-based cohort. The dCDT has the potential to be used as a cognitive assessment tool in the clinical diagnosis of MCI.
Using Twitter to Examine Stigma Against People With Dementia During COVID-19: Infodemiology Study
Authors: Bacsu Juanita-Dawne , Fraser Sarah , Chasteen Alison L , Cammer Allison , Grewal Karl S , Bechard Lauren E , Bethell Jennifer , Green Shoshana , McGilton Katherine S , Morgan Debra , O’Rourke Hannah M , Poole Lisa , Spiteri Raymond J , O'Connell Megan E 
Published: March 2022

BackgroundDuring the pandemic, there has been significant social media attention focused on the increased COVID-19 risks and impacts for people with dementia and their care partners. However, these messages can perpetuate misconceptions, false information, and stigma.ObjectiveThis study used Twitter data to understand stigma against people with dementia propagated during the COVID-19 pandemic.MethodsWe collected 1743 stigma-related tweets using the GetOldTweets application in Python from February 15 to September 7, 2020. Thematic analysis was used to analyze the tweets.ResultsBased on our analysis, 4 main themes were identified: (1) ageism and devaluing the lives of people with dementia, (2) misinformation and false beliefs about dementia and COVID-19, (3) dementia used as an insult for political ridicule, and (4) challenging stigma against dementia. Social media has been used to spread stigma, but it can also be used to challenge negative beliefs, stereotypes, and false information.ConclusionsDementia education and awareness campaigns are urgently needed on social media to address COVID-19-related stigma. When stigmatizing discourse on dementia is widely shared and consumed amongst the public, it has public health implications. How we talk about dementia shapes how policymakers, clinicians, and the public value the lives of people with dementia. Stigma perpetuates misinformation, pejorative language, and patronizing attitudes that can lead to discriminatory actions, such as the limited provision of lifesaving supports and health services for people with dementia during the pandemic. COVID-19 policies and public health messages should focus on precautions and preventive measures rather than labeling specific population groups.
Penegakan Hukum Pidana terhadap Pelaku Vandalisme pada Rambu Lalu Lintas
Authors: Kadek Putra Dwi Payana  , Anak Agung Sagung Laksmi Dewi  , I Made Minggu Widyantara  
Published: March 2022

Vandalism has quite a negative impact on human life such as disrupting the function of public facilities, for example, vandalism in the form of graffiti on traffic signs which in addition to damaging the function of traffic signs can also endanger road users. Therefore, it is necessary to enforce the law on the crime of vandalism in order to provide a deterrent effect by giving sanctions to the perpetrators of vandalism. The purpose of this study is to determine the legal arrangements against vandalism perpetrators on traffic signs and to discuss criminal sanctions that can be imposed on perpetrators of vandalism on traffic signs. The research method that the author uses is normative legal research. The sources of legal material in this study consist of secondary, primary and tertiary legal sources used in this study. These materials are collected by means of recording techniques, file systems, and document studies which will be analyzed systematically. in Article 275 paragraph (2) of Law Number 22 of 2009 concerning Road Traffic and Transportation. The author suggests to the government to immediately make a specific law, and the public to immediately report it to the authorities if there are acts of vandalism
PENGARUH LEVERAGE, RETURN ON ASSET (ROA) DAN INTENSITAS MODAL TERHADAP PENGHINDARAN PAJAK DENGAN TRANSPARANSI SEBAGAI VARIABEL MODERASI PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA
Authors: Arimurti Trias , Astriani Devi , Sabaruddin  
Published: March 2022

Penelitian ini untuk menguji dan menganalisis pengaruh leverage, return on asset (ROA dan intensitas modal terhadap penghindaran pajak dengan transparansi sebagai variabel moderasi. Data yang digunakan dalam penelitian ini adalah data sekunder yang bersumber dari data laporan keuangan perusahaan di Bursa Efek Indonesia. Populasi dalam penelitian ini adalah seluruh perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia. Teknik sampling yang digunakan purposive sampling dengan kriteria yang disesuaikan dengan kebutuhan dalam penelitian. Dari kriteria yang ditentukan sebanyak 37 perusahaan didapat sebanyak 37 perusahaan sebagai sampel. Metode analisis data menggunakan regresi data panel dengan alat analisis Eviews 10 dan Moderating Regression Analysis (MRA). Hasil penelitian menunjukkan bahwa pertama, Leverage tidak berpengaruh positif terhadap penghindaran pajak. Hal ini menunjukkan bahwa utang semakin tinggi jumlah pendanaan dari utang oleh pihak ketiga yang digunakan perusahaan dan semakin tinggi pula biaya bunga yang timbul dari utang tersebut, sehingga akan memberikan pengaruh berkurangnya beban pajak perusahaan tidak menjadikan perusahaan melakukan pembiayaan dengan utang dalam jumlah yang besar. Kedua, ROA berpengaruh positif terhadap penghindaran pajak. Hal ini menunjukkan semakin tinggi profitabilitas perusahaan, maka semakin baik pula perencanaan pajak perusahaan karena dapat menghasilkan optimalisasi pajak dan kecenderungan perusahaan untuk melakukan penghindaran pajak menjadi semakin menurun. Ketiga, intensitas modal. Hal ini menunjukkan bahwa beban penyusutan yang berasal dari aktiva tetap perusahaan tidak cukup berpengaruh terhadap pengurangan pajak perusahaan.