bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis, Antimicrobial, Antioxidant Evaluation, and DFT Estimation of
some New Cyclohexenone Derivatives Derived from Benzyloxy Chalcones
Authors: Noori Abdullah Media 
Published: January 2023

Background::
New cyclohexenone derivatives candidates were designed to discover
their antioxidant and antibacterial activity potentials, respectively.

Methods:
Aldehydes with the diverse functional group were prepared from 4-hydroxy benzaldehyde
and benzyl bromide and converted to chalcones by reaction with 4-substituted benzophenones
and 2-acetyl naphthalene. When chalcone derivatives were subjected to ethyl acetoacetate, it produced
new cyclohexenone derivatives through NaOH- catalyzed addition-ring closure reaction. The
new compound structures were strengthened by their spectral information. The new compounds are
examined for in vitro antifungal and antibacterial actions through broth microdilution technique,
and they exhibited potential responses against various bacteria and fungi.

Results:
As a result, composites with (-F) group as a substituent on para position were established
to be the forceful derivatives against S. aureus, E. coli organism, and C. albicans since this compound
could inhibit the microbial and Fungai growth at lower concentrations compared to the
standards (Ciprofloxacin HCl, and Fluconazole).

Conclusion:
DPPH radical scavenging experiments were used to evaluate proton donating antioxidant effects; it was exposed that compound 7c has the most significant antioxidant activity, while less than the standard ascorbic acid. Finally, HOMO-LUMO was calculated, which represents the quantum mechanical calculations of energies and conducted by the theory of density functional (DFT) method based on the level of (B3LYP) with 6-31G (d, p) basis set.
Differential Effects of Laxatives on Barium Sulfate Coating and Image
Quality in Double-Contrast Barium Enema
Authors: Lai Cheng-Shih , Tsai Hong-Ming , Ting Chien-Yi , Wang Bow 
Published: January 2023

Background:
Diagnostic accuracy of double-contrast barium enema (DCBE) depends upon the barium sulfate coating efficiency in the colon.

Objective:
To evaluate effects of three laxatives on barium sulfate coating efficiency in the large intestine, sigmoid colon, and hepatic flexure in DCBE.

Methods:
This retrospective study included patients receiving DCBE after pre-procedure cleansing with Dulcolax® with castor oil (DC), Klean-Prep® (KP), or Fleet®. Patients’ DCBE images were reviewed.

Results:
Among 373 cases of DCBE, 151 received DC, 147 received KP, and 75 received Fleet. For DCBE, the optimal extent of barium sulfate residue coated on the wall of the large intestine is less than one-fourth of bowel wall width; the DC group had a higher percentage of less than one-fourth of bowel wall than that of the KP or Fleet group (both p < 0.0167). DC, KP and Fleet have comparable barium sulfate coating efficiency in the sigmoid colon. However, in the hepatic flexure, the DC group had a higher percentage of barium sulfate coating without interruption than that of the KP or Fleet groups (both p < 0.0167).

Conclusion:
DC has a better barium sulfate coating efficiency in the hepatic flexure compared with KP and Fleet.
Research Progress on Amide Proton Transfer Imaging in
Preoperative and Postoperative Glioma Assessment
Authors: Lin Fan , Zhang Han-wen 
Published: January 2023

Abstract:
Amide proton transfer (APT) imaging is a technique that reflects the level of amide proton
transport of hydrogen ions in water to peptides and proteins within the tumour by using magnetic resonance
imaging without contrast administration. This technique can more accurately reflect the protein
level, pH value, and other relevant information within the tumour. Currently, APT is widely used in
glioma research. In this paper, we briefly describe the research progress on this technique.
Quantitative Analysis for Chinese and US-listed Pharmaceutical
Companies by the LightGBM Algorithm
Authors: Zheng Wenwen , Li Junjun , Wang Yu , Ye Zhuyifan , Zhong Hao , Kot Hung Wan , Ouyang Defang , Chan Ging 
Published: January 2023

Aim:
This article aims to quantitatively analyze the growth trend of listed pharmaceutical
companies in the US and China by a machine learning algorithm.

Background:
In the last two decades, the global pharmaceutical industry has faced the dilemma of
low research & development (R&D) success rate. The US is the world's largest pharmaceutical
market, while China is the largest emerging market.

Objective:
To collect data from the database and apply machine learning to build the model.

Method:
LightGBM algorithm was used to build the model and identify the factor important to
the performance of pharmaceutical companies.

Results:
The prediction accuracy for US companies was 80.3%, while it was 64.9% for
Chinese companies. The feature importance shows that the net profit growth rate and debt liability
ratio are significant in financial indicators. The results indicated that the US may continue to
dominate the global pharmaceutical industry, while several Chinese pharmaceutical companies
rose sharply after 2015 with the narrowing gap between the Chinese and US pharmaceutical industries.

Conclusion:
In summary, our research quantitatively analyzed the growth trend of listed pharmaceutical
companies in the US and China by a machine learning algorithm, which provide a novel
perspective for the global pharmaceutical industry. According to the R&D capability and profitability,
141 US-listed and 129 China-listed pharmaceutical companies were divided into four levels
to evaluate the growth trend of pharmaceutical firms.
Effects of Sheng-Mai Injection on Diabetes Mellitus: A Systematic Review
and Meta-analysis
Authors: Yang Maoyi , Hu Zhipeng , Yue Rensong 
Published: January 2023

Background:
Diabetes mellitus (DM) is a metabolic disorder characterized by progressive
β cell dysfunction. Sheng-Mai Injection (SMI), a Traditional Chinese medicine preparation,
is widely used for DM and its related complications.

Objective:
This meta-analysis aimed to summarize the applications of SMI in DM and related
complications.

Methods:
Eight databases were searched, and meta-analyses were performed.

Results:
Fifteen studies, including 1273 participants, were included. All studies and participants
included were from China. Pooled effects showed that SMI might reduce glycated hemoglobin
(MD -0.46%; 95% CI -0.89 to -0.03; P < 0.01), fasting blood glucose (MD -0.83 mmol/L; 95%
CI -1.30 to -0.36; P < 0.01), two-hour postprandial glucose (MD -1.27 mmol/L; 95% CI -1.96 to
-0.58; P < 0.01), 24-hour urinary protein (MD -0.28 mg; 95% CI -0.51 to -0.06; P = 0.01), blood
urea nitrogen (MD -1.31 mg; 95% CI -2.08 to -0.54; P < 0.05), Scr (MD -2.60; 95% CI -3.43 to
-1.77; P < 0.05), ulnar nerve motor nerve conduction velocity (MNCV) (MD 1.45; 95% CI 0.03
to 2.87; P < 0.05), and tibial nerve sensory nerve conduction velocity (SNCV) (MD 1.84; 95%
CI 0.1 to 3.58; P < 0.05). There was no evidence of an effect on common peroneal nervous
MNCV and SNCV, tibial nerve MNCV, median nerve MNCV, and SNCV. Adverse effects included
less frequent gastrointestinal reactions, elevated transaminase, leucopenia, fever, and rash.

Conclusion:
Combination use of SMI based on conventional hypoglycemic treatment can significantly
improve HbA1c, FBG, and 2hPG in DM and reduce 24-hour urinary protein, Scr, and
BUN in DM patients. SMI was found to have no effect on the neurological function of diabetic
peripheral neuropathy.
Research Trends in Abrasive Water Jet Machining Using Numerical Simulation
Tools: A Bibliometric Review
Authors: Bongale Anupkumar M. , Doreswamy Deepak , Abdallah Zahra , Bhat Subraya Krishna 
Published: January 2023

Background:
Abrasive water jet (AWJ) machining process is one of the most sought-after machining technologies for the processing of advanced hard-to-cut materials. It involves parameters, such as abrasive size, shape, density, pressure, standoff distance (SOD), abrasive concentration, feed rate, etc., which govern the quality of machining. It is very crucial to understand the influence of these parameters on the quality attributes.

Objective:
Due to the complex nature of the process that involves complex process parameters, the accurate prediction of response by experimental methods is difficult. In this scenario, numerical methods are helpful in understanding the mechanisms of material removal. Thus, a comprehensive summary of these research trends is needed.

Methods:
In this article, a bibliometric analysis is carried out on scientific publications pertaining to AWJ machining (AWJM) using numerical simulation tools. Citation and bibliographic coupling analyses have been carried out to identify the current research trends, the important journals, authors, institutions, and countries engaged in research on AWJM using numerical simulation.

Results:
The analysis revealed Shandong University to have the maximum number of affiliated researchers working in this area. The International Journal of Machine Tools and Manufacture was the leading journal based on CiteScore, SJR rank and SNIP ranks, and the largest volume of articles was published by this journal. The critical topics of research and international collaborative opportunities were identified through the analysis of keywords, Sankey and network diagrams.

Conclusion:
The present article would be valuable for academia and industry, aiding them in updating their knowledge on the latest developments in AWJM.
Factors Associated With Telemedicine Use Among Patients With Rheumatic and Musculoskeletal Disease: Secondary Analysis of Data From a German Nationwide Survey
Authors: Muehlensiepen Felix , Petit Pascal , Knitza Johannes , Welcker Martin , Vuillerme Nicolas 
Published: January 2023

Background
Previous studies have demonstrated telemedicine (TM) to be an effective tool to complement rheumatology care and address workforce shortage. With the outbreak of the COVID-19 pandemic, TM experienced a massive upswing. A previous study revealed that physicians’ willingness to use TM and actual use of TM are closely connected to their knowledge of TM. However, it remains unclear which factors are associated with patients’ motivation to use TM.

Objective
This study aims to identify the factors that determine patients’ willingness to try TM (TM try) and their wish that their rheumatologists offer TM services (TM wish).

Methods
We conducted a secondary analysis of data from a German nationwide cross-sectional survey among patients with rheumatic and musculoskeletal disease (RMD). Bayesian univariate and multivariate logistic regression analyses were applied to the data to determine which factors were associated with TM try and TM wish. The predictor variables (covariates) studied individually included sociodemographic factors (eg, age and sex) and health characteristics (eg, disease type and health status). All the variables positively or negatively associated with TM try or TM wish in the univariate analyses were then considered for the Bayesian model averaging analysis after a selection based on the variance inflation factor (≤2.5). All the analyses were stratified by sex.

Results
Of the total 102 variables, 59 (57.8%) and 45 (44.1%) variables were found to be positively or negatively associated (region of practical equivalence ≤5%) with TM try and TM wish, respectively. A total of 16 and 8 determinant factors were identified for TM try and TM wish, respectively. Wishing that TM services were offered by rheumatologists, having internet access at home, residing 5 to 10 km away from the general practitioner’s office, owning an electronic device, and being aged 40 to 60 years were among the factors positively associated with TM try and TM wish. By contrast, not yet being diagnosed with an RMD, having no prior knowledge of TM, having a bad health status, living in a rural area, not documenting one’s health status, not owning an electronic device, and being aged 60 to 80 years were negatively associated with TM try and TM wish.

Conclusions
Our results suggest that health status, knowledge, age, and access to technical equipment and infrastructure influence the motivation of patients with RMD to use telehealth services. In particular, older patients with RMD living in rural areas, who could likely benefit from using TM, are currently not motivated to use TM and seem to need additional TM support.
Association Between the Severity of Depressive Symptoms and Human-Smartphone Interactions: Longitudinal Study
Authors: Yang Xiao , Knights Jonathan , Bangieva Victoria , Kambhampati Vinayak 
Published: January 2023

Background
Various behavioral sensing research studies have found that depressive symptoms are associated with human-smartphone interaction behaviors, including lack of diversity in unique physical locations, entropy of time spent in each location, sleep disruption, session duration, and typing speed. These behavioral measures are often tested against the total score of depressive symptoms, and the recommended practice to disaggregate within- and between-person effects in longitudinal data is often neglected.

Objective
We aimed to understand depression as a multidimensional process and explore the association between specific dimensions and behavioral measures computed from passively sensed human-smartphone interactions. We also aimed to highlight the nonergodicity in psychological processes and the importance of disaggregating within- and between-person effects in the analysis.

Methods
Data used in this study were collected by Mindstrong Health, a telehealth provider that focuses on individuals with serious mental illness. Depressive symptoms were measured by the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) Self-Rated Level 1 Cross-Cutting Symptom Measure-Adult Survey every 60 days for a year. Participants’ interactions with their smartphones were passively recorded, and 5 behavioral measures were developed and were expected to be associated with depressive symptoms according to either theoretical proposition or previous empirical evidence. Multilevel modeling was used to explore the longitudinal relations between the severity of depressive symptoms and these behavioral measures. Furthermore, within- and between-person effects were disaggregated to accommodate the nonergodicity commonly found in psychological processes.

Results
This study included 982 records of DSM Level 1 depressive symptom measurements and corresponding human-smartphone interaction data from 142 participants (age range 29-77 years; mean age 55.1 years, SD 10.8 years; 96 female participants). Loss of interest in pleasurable activities was associated with app count (γ10=−0.14; P=.01; within-person effect). Depressed mood was associated with typing time interval (γ05=0.88; P=.047; within-person effect) and session duration (γ05=−0.37; P=.03; between-person effect).

Conclusions
This study contributes new evidence for associations between human-smartphone interaction behaviors and the severity of depressive symptoms from a dimensional perspective, and it highlights the importance of considering the nonergodicity of psychological processes and analyzing the within- and between-person effects separately.
Combining Experience Sampling and Mobile Sensing for Digital Phenotyping With m-Path Sense: Performance Study
Authors: Niemeijer Koen , Mestdagh Merijn , Verdonck Stijn , Meers Kristof , Kuppens Peter 
Published: January 2023

Background
The experience sampling methodology (ESM) has long been considered as the gold standard for gathering data in everyday life. In contrast, current smartphone technology enables us to acquire data that are much richer, more continuous, and unobtrusive than is possible via ESM. Although data obtained from smartphones, known as mobile sensing, can provide useful information, its stand-alone usefulness is limited when not combined with other sources of information such as data from ESM studies. Currently, there are few mobile apps available that allow researchers to combine the simultaneous collection of ESM and mobile sensing data. Furthermore, such apps focus mostly on passive data collection with only limited functionality for ESM data collection.

Objective
In this paper, we presented and evaluated the performance of m-Path Sense, a novel, full-fledged, and secure ESM platform with background mobile sensing capabilities.

Methods
To create an app with both ESM and mobile sensing capabilities, we combined m-Path, a versatile and user-friendly platform for ESM, with the Copenhagen Research Platform Mobile Sensing framework, a reactive cross-platform framework for digital phenotyping. We also developed an R package, named mpathsenser, which extracts raw data to an SQLite database and allows the user to link and inspect data from both sources. We conducted a 3-week pilot study in which we delivered ESM questionnaires while collecting mobile sensing data to evaluate the app’s sampling reliability and perceived user experience. As m-Path is already widely used, the ease of use of the ESM system was not investigated.

Results
Data from m-Path Sense were submitted by 104 participants, totaling 69.51 GB (430.43 GB after decompression) or approximately 37.50 files or 31.10 MB per participant per day. After binning accelerometer and gyroscope data to 1 value per second using summary statistics, the entire SQLite database contained 84,299,462 observations and was 18.30 GB in size. The reliability of sampling frequency in the pilot study was satisfactory for most sensors, based on the absolute number of collected observations. However, the relative coverage rate—the ratio between the actual and expected number of measurements—was below its target value. This could mostly be ascribed to gaps in the data caused by the operating system pushing away apps running in the background, which is a well-known issue in mobile sensing. Finally, some participants reported mild battery drain, which was not considered problematic for the assessed participants’ perceived user experience.

Conclusions
To better study behavior in everyday life, we developed m-Path Sense, a fusion of both m-Path for ESM and Copenhagen Research Platform Mobile Sensing. Although reliable passive data collection with mobile phones remains challenging, it is a promising approach toward digital phenotyping when combined with ESM.
Real-world comparison between weekly versus biweekly dosing of cetuximab for metastatic colorectal cancer
Authors: Aggarwal Himani , Han Yimei , Sheffield Kristin M , Cui Zhanglin Lin 
Published: January 2023

Aim:
This real-world study aims to compare overall survival (OS) associated with biweekly (Q2W) versus weekly (Q1W) cetuximab dosing regimens for metastatic colorectal cancer (mCRC) treatment in the US.
Methods:
Adult patients with
KRAS
wild-type mCRC who received cetuximab ± chemotherapy from 2013 to 2019 were selected using Flatiron Health's electronic health records database. Propensity score matching was used to balance Q2W and Q1W cohorts on baseline patient characteristics. The Kaplan–Meier method was used for survival analyses. Several sensitivity analyses were conducted to assess the robustness of findings from the main analysis.
Results:
Of 1075 patients in the study, 60.7% received cetuximab Q1W and 39.3% Q2W. Median OS (95% confidence interval) in months was 17.2 (15.3, 18.8) for Q2W versus 14.3 (12.8, 16.0) for Q1W; p = 0.246. Similar OS between the dosing cohorts was observed in sensitivity analyses.
Conclusion:
Weekly and biweekly cetuximab had comparable effectiveness in this real-world study.
Proteomic Predictors of Incident Diabetes: Results From the Atherosclerosis Risk in Communities (ARIC) Study
Authors: Rooney Mary R. , Chen Jingsha , Echouffo-Tcheugui Justin B. , Walker Keenan A. , Schlosser Pascal , Surapaneni Aditya , Tang Olive , Chen Jinyu , Ballantyne Christie M. , Boerwinkle Eric , Ndumele Chiadi E. , Demmer Ryan T. , Pankow James S. , Lutsey Pamela L. , Wagenknecht Lynne E. , Liang Yujian , Sim Xueling , van Dam Rob , Tai E. Shyong , Grams Morgan E. , Selvin Elizabeth , Coresh Josef 
Published: January 2023

OBJECTIVEThe plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis.RESEARCH DESIGN AND METHODSIn 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47–70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments.RESULTSThere were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P &lt; 10−5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P &lt; 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk.CONCLUSIONSWe identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.
Deciphering the Greek Temple: Verification with Software Tools of the Solar Design of the Parthenon in Athens and the Temple of Zeus in Olympia
Authors: Uson Ezequiel 
Published: January 2023

In Greek temples, compositional order and Pythagorean geometry were used to achieve regularity, proportion and beauty, combining exact magnitudes between the parts and the whole. It is also known that all the temples were oriented with great precision. However, the diverse reasons for their construction makes their astronomical orientation more difficult to interpret. In this research, the Parthenon in Athens (447-436 BC) and the Temple of Zeus in Olympia (470-456 BC) were analysed with solar simulation software. Comparing the results obtained, it is verified that both temples were designed and oriented following a plan: to facilitate the symbolic use of sunlight for the veneration of the goddess Athena and the god Zeus on the dates of the celebration of certain religious rituals. Verification was performed using a process that allows its extrapolation to similar analyses of any other Greek temple.