Adj R2 Research Articles

Estimation of Marine Macroalgal Biomass Using a Coverage Analysis

This study was conducted to assess the feasibility of biomass estimation by non-destructive sampling, determine whether the results derived from various types of marine macroalgae are reliable, and a newly proposed method. A quantitative survey was conducted on marine macroalgae communities distributed in the subtidal zone in 67 coastal regions in Korea. Regression analyses were conducted on 11,642 fresh weight datasets covering of 135 species of marine macroalgae. The linear function was FW = 17.721C (adj r2 = 0.745, p < 0.001) and the power function was FW = 4.48C1.251 (adj r2 = 0.891, p < 0.001). Our analysis accounted for the fact that there were three vertically distributed layers of a marine macroalgal assemblages with various shapes (i.e., the Ecklonia complex, the Sargassum and Undaria complex, and the understory complex). For the Ecklonia complex, the linear function was FW = 27.360C (adj r2 = 0.886, p < 0.001) and the power function was FW = 9.626C1.223 (adj r2 = 0.909, p < 0.001). For the Sargassum and Undaria complex, the linear function was FW = 18.389C (adj r2 = 0.916, p < 0.001) and the power function was FW = 6.567C1.255 (adj r2 = 0.942, p < 0.001). For the understory complex, the linear function was FW = 10.419C (adj r2 = 0.737, p < 0.001) and the power function was FW = 4.377C1.182 (adj r2 = 0.871, p < 0.001). Our findings demonstrated that the proposed method can accurately estimate the primary productivity of a wide range of coastal ecosystems based on remote sensing and non-destructive surveys of small-scale marine macroalgal communities.

Box-Behnken design optimization of sulfate reduction from natural water by electrocoagulation process

The purpose of this work is to investigate sulfate removal from aqueous solutions by electrocoagulation (EC). The influence of electrolysis time, initial pH, and current density was carried out. The interaction of the several effects on removal efficiency was also studied. The Box-Behnken experimental design (BBD) in Response Surface Methodology (RSM) was applied in the development of statistical analysis, modeling, and interpretation of the resultant treatment data of sulfate removal by EC. The optimum conditions for highest removal ratio of sulfate from aqueous solution were: current density of 10 mA/cm2, initial pH equal 5 and electrolysis time of 60 min. Sulfate removal efficiency reach a maximum value of 98.76% and the predicted value is 100%. According to ANOVA results, the correlation coefficient (R2) value of 98% proved that experimental data and model predictions agreed well. The R2 adj and R2 pred were also in a reasonable agreement (98% and 95% respectively). The mathematical model that describes the EC process was determined and proved that all variable had linear and quadratic significant effect on sulfate removal efficiency. The optimum conditions founded using BBD conducted to 60 and 90% of sulfate removal respectively from seawater and brackish water.

Optimization of biomass production from Chlorella vulgaris by response surface methodology and study of the fatty acid profile for biodiesel production: A green approach

This study was aimed to utilize Box Behnken Design (BBD) of the response surface methodology, for identifying optimum levels of particular variables for increased biomass production in Chlorella vulgaris. A second-order polynomial model produced satisfactory results in biomass yield (P < 0.0001). The amount of biomass predicted in Response Surface Methodology was 11.165 mg/ml at optimized conditions pH-8.07, temperature-39.5 °C, sodium bicarbonate-0.007 mg/ml and urea-0.005 mg/ml. Results of the predicted and the actual response were differing with residuals >2.34% and R2-98.32 and Adj R2 90.83 for biomass and were found to be in reasonable agreement with the better reliability model. Chlorella vulgaris was cultivated in modified artificial sea nutrient medium (III), supplemented with CO2 under optimized conditions and the lipid was extracted by Soxhlet extractor and the GC-MS analysis of the lipid revealed 35 compounds and the lipid after transesterification process revealed 30 compounds following 20 compounds of crude glycerol. Transesterification of the lipid produced 86.115% of biodiesel compounds and 92.015% of crude glycerol when compared to the Soxhlet extractor, which produced 53.56% of biodiesel compounds.

Partner Related Motives and Strategic Alliance Formation: Evidence from Small and Medium Enterprises in Kenya

This study investigates the effect of partner-related motives on firm performance, and the study targeted manufacturing SMEs based in Kenya. The partner-related motives were operationalized as the social factors of reputation-based motives, historical-based motives, and institutional-based motives, while firm performance is operationalized as sales growth and net profit. The target population for the study consisted of 74 SMEs based in Nairobi City County with existing strategic alliances. The study adopted descriptive and explanatory research designs and collected data from company CEOs or senior managers. The survey data was analyzed using descriptive and inferential statistics. The survey findings showed that partner-related motives have been adopted and practiced by manufacturing SMEs to a high extent (M=3.68; S.D.=0.83). The study findings indicate that partner related motives have a significant effect on performance of manufacturing SMEs (Adj R2=0.525, β=0.444, p&lt;0.05). Accordingly, manufacturing SMEs in Kenya are motivated to form strategic alliances by reputation-based motives and institutional-based motives, with the same motives having a positive effect on SME performance. In contrast, historical-based motives have no significant effect on SME performance. Therefore, the study concluded that reputation-based motives push manufacturing SMEs in Kenya to engage in strategic alliances while, historical-based motives and institution-based motives pull manufacturing SMEs in Kenya to form strategic alliances with other firms. The study recommended that top managers in the manufacturing SMEs need to adopt a vigorous diagnostic process to identify and define their partner-related motives. The study observes that such a move will enable the manufacturing SMEs to identify the most suitable alliance partner(s) who can offer complementary resources to improve performance.

Hot spots and anomalies of CO2 over eastern Amazonia, Brazil: A time series from 2015 to 2018

The easternmost Amazon, located in the Maranhão State, in Brazil, has suffered massive deforestation in recent years, which has devastated almost 80% of the original vegetation. We aim to characterize hot spots, hot moments, atmospheric carbon dioxide anomalies (Xco2, ppm), and their interactions with climate and vegetation indices in eastern Amazon, using data from NASA's Orbiting Carbon Observatory-2 (OCO-2). The study covered the period from January 2015 to December 2018. The data were subjected to regression, correlation, and temporal analysis, identifying the spatial distribution of hot/cold moments and hot/cold spots. In addition, anomalies were calculated to identify potential CO2 sources and sinks. Temporal changes indicate atmospheric Xco2 in the range from 362.2 to 403.4 ppm. Higher Xco2 values (hot moments) were concentrated between May and September, with some peaks in December. The lowest values (cold moments) were concentrated from November to April. SIF 771 W m−2 sr−1 μm−1 explained the temporal changes of Xco2 in 58% (R2 adj = 0.58; p < 0.001) and precipitation in 27% (R2 adj = 0.27; p ≤ 0.001). Spatial hot spots with 90% confidence were more representative in 2016. The maximum and minimum Xco2 (ppm) anomalies were 6.19 ppm (source) and −6.29 ppm (sink), respectively. We conclude that the hot moments of Xco2 in the eastern Amazon rainforest are concentrated in the dry season of the year. Xco2 spatial hot spots and anomalies are concentrated in the southern region and close to protected areas of the Amazon rainforest.

The Association of Visibility and Adenocarcinoma Lung Cancer in Southern Taiwan

Background/Aim Studies on association between lung cancer and long-term exposure to air pollution are limited due to the unavailability of air pollution data. The study aims to assess association of visibility, a proxy indicator of long-term air pollution exposure, with adenocarcinoma lung cancer. Methods Our study area is in southern Taiwan, an industrial area with 2.7 million people in 5.7 thousand km². Annual lung cancer incidence data with the ICD-O-3 codes from C34.0-C34.9 were obtained from Taiwan Cancer Registry (TCR) from 1997 to 2018. Age-adjusted incidence of lung cancers were standardized by the WHO 2000 world standard population. Hourly atmospheric visibility data from 1961 to 2022 were obtained from Taiwan Central Weather Bureau. 30-years moving averages were then calculated from 1967 onward to represent long-term visibility in the study area. Linear regression models were employed to estimate associations of 30-years averaging visibility annual age-adjusted lung cancers incidence for both adenocarcinoma and non-adenocarcinoma from 1997 to 2018. Results From 1997 to 2018, southern Taiwan&amp;#x27;s adenocarcinoma lung cancer incidence increased from 8.93 to 25.81 per 100,000 population, while non-adenocarcinoma incidence decreased from 14.61 to 10.41 per 100,000 population. The 30-years averaged visibility in the study area declined from 14.90 km to 7.65 km in the same period. Reducing visibility is significantly associated adenocarcinoma lung cancer, with a 2.43% (95% confidence interval [CI]: 2.77-2.11, adjusted R2 value: 0.92) increase in incidence by 1 km decrease in visibility during this period. Such associations exist for both females and males with increasing incidence of 2.57% (95% CI: 2.92-2.22, adj R2: 0.92) and 2.32% (95% CI: 2.69-1.95, adj R2: 0.89) by 1 km visibility reduction, respectively. By contrast, visibility reduction was not associated with increased in non-adenocarcinoma incidence. Conclusions Long-term visibility reduction is associated with increase in adenocarcinoma lung cancer incidence but not with non-adnocarcinoma.

Shared Decision-Making in Pancreatic Surgery.

The objective of this study is to determine the factors influencing pancreatic surgery patients' perceptions of the shared decision-making process (SDM). Decision-making in pancreatic surgery is complicated by the risk of morbidity and mortality and risk of early recurrence of disease. Improvement in SDM has the potential to improve the receipt of goal- and value-concordant care. This cross-sectional survey included patients who underwent pancreatic surgery. The following components were studied in relation to SDM: modified satisfaction with decision scale (SWD), modified decisional regret scale (DRS), quality of physician and patient interaction, and the impact of quality of life (FACT-Hep). Correlations were computed using Pearson's correlation score and a regression model. The survey completion rate was 72.2% (of 40/55) and the majority (72.5%) of patients underwent pancreaticoduodenectomy. There were significant positive relationships between the SDM measure and (DRS, SWD; r = 0.70, P < 0.001) and responses to questions regarding how well the patient's actual recovery matched their expectations before treatment (r = 0.62, P < 0.001). The quality of the physician-patient relationship correlated with how well recovery matched expectations (r = 0.53, P = 0.002). SDM measure scores were significant predictors of the decision evaluation measure (R2(adj) = 0.48, P < 0.001), FACT-Hep (R2(adj) = 0.15, P < 0.001), and recovery expectations measure (R2(adj) = 0.37, P < 0.001). Improved SDM in pancreatic surgery is associated with more realistic recovery expectations, decreased decisional regret, and improved quality of life.

Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?

BackgroundPatients undergoing chemoradiation and immune checkpoint inhibitor (ICI) therapy for locally advanced non-small cell lung cancer (NSCLC) experience pulmonary toxicity at higher rates than historical reports. Identifying biomarkers beyond conventional clinical factors and radiation dosimetry is especially relevant in the modern cancer immunotherapy era. We investigated the role of novel functional lung radiomics, relative to functional lung dosimetry and clinical characteristics, for pneumonitis risk stratification in locally advanced NSCLC.MethodsPatients with locally advanced NSCLC were prospectively enrolled on the FLARE-RT trial (NCT02773238). All received concurrent chemoradiation using functional lung avoidance planning, while approximately half received consolidation durvalumab ICI. Within tumour-subtracted lung regions, 110 radiomics features (size, shape, intensity, texture) were extracted on pre-treatment [99mTc]MAA SPECT/CT perfusion images using fixed-bin-width discretization. The performance of functional lung radiomics for pneumonitis (CTCAE v4 grade 2 or higher) risk stratification was benchmarked against previously reported lung dosimetric parameters and clinical risk factors. Multivariate least absolute shrinkage and selection operator Cox models of time-varying pneumonitis risk were constructed, and prediction performance was evaluated using optimism-adjusted concordance index (c-index) with 95% confidence interval reporting throughout.ResultsThirty-nine patients were included in the study and pneumonitis occurred in 16/39 (41%) patients. Among clinical characteristics and anatomic/functional lung dosimetry variables, only the presence of baseline chronic obstructive pulmonary disease (COPD) was significantly associated with the development of pneumonitis (HR 4.59 [1.69–12.49]) and served as the primary prediction benchmark model (c-index 0.69 [0.59–0.80]). Discrimination of time-varying pneumonitis risk was numerically higher when combining COPD with perfused lung radiomics size (c-index 0.77 [0.65–0.88]) or shape feature classes (c-index 0.79 [0.66–0.91]) but did not reach statistical significance compared to benchmark models (p > 0.26). COPD was associated with perfused lung radiomics size features, including patients with larger lung volumes (AUC 0.75 [0.59–0.91]). Perfused lung radiomic texture features were correlated with lung volume (adj R2 = 0.84–1.00), representing surrogates rather than independent predictors of pneumonitis risk.ConclusionsIn patients undergoing chemoradiation with functional lung avoidance therapy and optional consolidative immune checkpoint inhibitor therapy for locally advanced NSCLC, the strongest predictor of pneumonitis was the presence of baseline chronic obstructive pulmonary disease. Results from this novel functional lung radiomics exploratory study can inform future validation studies to refine pneumonitis risk models following combinations of radiation and immunotherapy. Our results support functional lung radiomics as surrogates of COPD for non-invasive monitoring during and after treatment. Further study of clinical, dosimetric, and radiomic feature combinations for radiation and immune-mediated pneumonitis risk stratification in a larger patient population is warranted.

500병상 미만 병원 간호사의 직무스트레스 영향요인

The study is focused on identifying effect of working environment on job stress for the nurses affiliated in hospitals with less than 500 beds. The research design was descriptive study. The data was collected using a structured self-report questionnaire via online survey. The data was collected and analyzed from 348 subjects. To identify the effect on job stress, following sub-domains of nurse work environment was analyzed using multiple regression: competency of nursing manager, safety management system, support system, personal characteristics, job-related characteristics and hospital-related characteristics. The result shows job position, number of beds, competency of nursing manager, support system are significant (F=18.540, p=&lt;.001), Adj R2 = .431). For the job position factor, job stress of staff nurse was showed higher than that of nursing manager. For the hospital size factor, job stress of the nurses who work in hospital with 100~300 beds and 300~500 beds was showed higher than that of the nurses who work in hospital with less than 100 beds. For the work environment factor, job stress of nurses decreased as the nurses perceive positively about competency of nursing manager and support system. It is expected to be used as fundamental information on nurse job stress and human resource management for hospitals with less than 500 beds.

A Generalizable Approach to Predicting Performance on USMLE Step 2 CK.

IntroductionThe elimination of the USMLE Step 1 three-digit score has created a deficit in standardized performance metrics for undergraduate medical educators and residency program directors. It is likely that there will be greater emphasis on USMLE Step 2 CK, an exam found to be associated with later clinical performance in residents and physicians. Because many previous models relied on Step 1 scores to predict student performance on Step 2 CK, we developed a model using other metrics.Materials and MethodsAssessment data for 228 students in three cohorts (classes of 2018, 2019, and 2020) were collected, including the Medical College Admission Test (MCAT), NBME Customized Assessment Service (CAS) exams and NBME Subject exams. A linear regression model was conducted to predict Step 2 CK scores at five time-points: at the end of years one and two and at three trimester intervals in year three. An additional cohort (class of 2021) was used to validate the model.ResultsSignificant models were found at 5 time-points in the curriculum and increased in predictability as students progressed: end of year 1 (adj R2 = 0.29), end of year 2 (adj R2 = 0.34), clerkship trimester 1 (adj R2 = 0.52), clerkship trimester 2 (adj R2 = 0.58), clerkship trimester 3 (adj R2 = 0.62). Including Step 1 scores did not significantly improve the final model. Using metrics from the class of 2021, the model predicted Step 2 CK performance within a mean square error (MSE) of 8.3 points (SD = 6.8) at the end of year 1 increasing predictability incrementally to within a mean of 5.4 points (SD = 4.1) by the end of year 3.ConclusionThis model is highly generalizable and enables medical educators to predict student performance on Step 2 CK in the absence of Step 1 quantitative data as early as the end of the first year of medical education with increasingly stronger predictions as students progressed through the clerkship year.

Energy and exergy analysis of three leaved yam starch drying in a tray dryer: parametric, modelling and optimization studies

Engineering conservation during the drying process is paramount as it will help in the preservation and cost minimization of food products during processing to avoid spoilage and maximize their utilization in society. Unlike other yam species, three-leaved yam starch (TLYS) contains phytonutrients for the treatment of ailments such as diabetes and rheumatism. This work examined the energy and exergy of TLYS drying. The starch was extracted from the tuber and dried while the temperature, time, air velocity, and sample thickness were varied. TLYS proximate and SEM analysis revealed a significant amount of starch. Energy analysis revealed that energy utilization (EU) and energy utilization ratio (EUR) increased as the temperature rose and decreased as drying time increased; energy efficiency (EE) increased steadily and then reduced as drying time increased. Exergy analysis revealed that drying temperature increased exergetic efficiency and loss; drying time increased exergetic efficiency from 30 min to 4 h. The highest exergy loss was observed when the sample was dried for 4 h and the thickness is 17 mm; as the thickness decreased to 12.75 mm, the exergy loss decreased from 2.471392 J/s to 1.459247 J/s; the highest exergy efficiency of 2.471392 J/s was observed at the thickness of 4.25 mm, and the sustainability index increased as the sample thickness increased and decreased as the drying air temperature decreased. Response surface methodology (RSM) was utilized to model and optimize the effect of the process’s inherent operating factors (temperature, time, and air velocity) and maximize the process’s energy and exergy efficiency. The (Analysis of Variance) ANOVA revealed a second-order polynomial model with an R2 (0.9911), Adj R2 (0.9797) and Pred R2 (0.8577) for energy efficiency and R2 (0.9824), Adj R2 (0.9598), and Pred R2 (0.7184) for exergy efficiency, indicating a significant correlation between observed and predicted values. At a temperature of 60 °C, a time of 3 h, and an air velocity of 1.5 m/s, the optimal energy efficiency of 75.09 % and exergy efficiency of 99.221% were obtained with desirability of 0.997. The findings of this study can be used to improve the design and development of driers for TLYS preservation.

Alliance Motives among Manufacturing SMES: Evidence from an Emerging Economy

This study was designed to investigate the effect of environmental-based motives on firm performance. The study targeted manufacturing Small and Medium Enterprises based in Kenya whose performance has been negatively affected by high industry competition, low technology uptake, and industry regulation. The study was geared towards establishing the environmental-based motives pushing and pulling manufacturing Small and Medium Enterprises toward strategic alliance formation. To this end, the study was set to investigate whether compliance with government regulation, the need to grow market share, and the need to increase customer base motivates manufacturing Small and Medium Enterprises in Kenya to form strategic alliances. The target population for the study consisted of 74 SMEs and the study adopted descriptive and explanatory research designs and collected data from company CEOs or senior managers. Descriptive and inferential statistics were used to analyze the survey data. The study findings indicated that environmental-based motives have a positive and significant effect on the performance of manufacturing Small and Medium Enterprises in Kenya (Adj R2 = 0.484). Based on these findings, the study concluded that environmental-based motives of compliance with the government regulation, market share, and customer base motivate manufacturing Small and Medium Enterprises to form strategic alliances and that these motives have a positive and significant effect on firm performance. The study contributed to the general body of knowledge by bridging the contextual and empirical gaps identified after the literature review. The study recommends that top management teams in the manufacturing industry should map environmental-based motives and align such motives to specific aspects of their value chain activities.

Influence of Principals’ Teaching Staff Development on Students’ Academic Performance in Kisumu County, Kenya

Transformational leadership was operationalized as setting direction, staff development, building collaborative cultures, staffing the program, and academic performance as the KCSE mean score of a school for the period 2014 – 2018. The study arose from the fact that, high school principals are working hard yet the academic performance of public secondary schools in Kisumu County has remained generally poor. Between 2014 and 2018, only 26.9% of students from Kisumu County scored at least C+, and the average mean score in KCSE for the period was only 4.23, below 7.0, the cut out entry. At least 65% of the candidates from Kisumu County did not proceed to university education during the period. Several educational stakeholders had linked school leadership to the poor academic performance, but without empirical evidence. The study specifically investigated the influence of teaching staff development on the students’ academic performance in public secondary schools in Kisumu County. The study adopted a cross sectional survey research design. The target population consisted of 204 principals, 2,196 teachers, and 13,213 Form Three students. In sampling, Krejcie and Morgan table was used to find 152 principals, 333 teachers and 378 students, from 152 schools. Data was collected using questionnaires, interviews, observation and document analysis, and analyzed using simple linear, simple correlation, and stepwise regression with dummy variables, at .05 level of significance. The study tested specific hypothesis that staff development by principals do not have a significant influence on academic performance. The study found 7 significant associations at α = .01, (ϒSDR*DVP = .594, p = .000; ϒSDR*BCC = .476, p = .000; ϒDVP*BCC = .719, p = .000; ϒ =.416, p =.000; ϒ = .685, p =.000; ϒDVP*ACP = .239, p =.000; ϒBCC*ACP = .212, p = .000) and one significant association at α = .05, ϒSDR*ACP =.203, p = .012. The study found that staff development (good) [F (2,149) = 4.027), p = .020, R2 adj = .039, t (149) = 2.604, p = .010]. The study recommends that the ministry of education should empower principals with resources that will enable them to empower their teaching staff by training them on various needs that may arise in the society from time to time, and since the society is dynamic continuous provision of resources by the ministry would be ideal.

Characterization and biodegradation of ibuprofen by Bacillus siamensis strain DSI-1 isolated from wastewater

Nonsteroidal anti-inflammatory drugs (NSAIDs) are the emerging class of xenobiotics that were detected in various environmental sources. The monocyclic compound Ibuprofen acts as an emerging micro-pollutant and this has been widely used in the form a pain reliever drug. Microbes have the potential to use this compound as bon and nitrogen source. Hence, this study was conducted in the batch culture with the relevant concentration of Ibuprofen. The active microbial culture was collected from wastewater and this was used to isolate the true degrader of IBU by the addition of IBU during the enrichment process. Therefore, the enrichment culture technique was performed to isolate true Ibuprofen degrading bacterial strain. Haldane’s growth kinetics model was used in order to study the kinetic behaviour of strain. The isolate DSI-1 has been characterized by microscopy, biochemical tests and molecular analysis by using 16S rRNA sequencing. Based on these characterization methods, the isolate DSI-1 was reported as Bacillus siamensis strain DSI-1 (with GenBank accession number MT039503). This strain has degraded the Ibuprofen (up to concentration of 15 mg/L) which was added to wastewater in scale-up bioreactor (5L) study conducted in the present work. Through the batch culture study, it was observed that 20 mg/L of IBU was degraded in 24 h and the maximum specific growth rate (μmax) observed was 0.21/h. The saturation constant (Ks) and inhibition constant (Ki) observed for ibuprofen degradation were 17 ± 5%, and 315 ± 5% mg/L, respectively, with correlation coefficient (R2) of 0.9827. The mathematical modelling was used with the help of Design-Expert® software for the optimization of various physical parameters by experimental design. The correlation coefficient (R2) observed for IBU degradation was 0.8897, Adj R2 (0.7794), and predicted R2 (0.4736). The optimum conditions reported of IBU degradation were temperature (30 °C), pH (7.0), IBU (3.5 mg/L), and agitation speed (165 rpm). This research exemplifies the involvement of bacteria with efficient removal of the relative concentration of Ibuprofen from wastewater. Therefore, the results of this study have indicated the potential for the isolated IBU degrading Bacillus siamensis strain DSI-1 and this strain can be further deployed for bioremediation program by in-situ degradation.

Using the Theory of Planned Behavior to assess community pharmacists’ intention to prescribe using the Formulary and Protocol Compendia

BackgroundOregon pharmacists can autonomously prescribe hormonal contraception, naloxone, and various medications and devices from a Formulary and Protocol Compendia (FPC). Prescribing using the FPC has seen limited uptake. Objectives(1) Assess Oregon community pharmacists' intention to prescribe using the FPC; (2) Determine the impact that attitudes, subjective norms (SN), perceived behavioral control (PBC), perceived obligation, and past prescribing behavior have on pharmacists' intention to prescribe; (3) Examine the relationship between beliefs and pharmacists’ attitudes, subjective norms, and perceived behavioral control. MethodsThis study was conducted as a cross sectional survey, which was developed based on the results of a previously conducted research project. A modified version of the Theory of Planned Behavior (TPB) was the study framework. All Oregon community pharmacists with a public email address were invited to participate. The questionnaire collected information on TPB constructs as well as demographic and practice information. TPB constructs were measured directly (intention, attitudes, SN, PBC, perceived obligation, and past prescribing behavior) and indirectly (attitudes, SN, and PBC). Descriptive statistics were used for all items. Multiple linear regression was used to assess Objectives 2 and 3. ResultsThere were 175 useable responses included in the analysis of the estimated 1015 community pharmacists that received the survey invitation (17%). Respondents had 16.5 ± 13.3 years in practice, 60% held a PharmD degree, and 69% had prescribed in some manner before. Mean intention to prescribe using the FPC was 5.0 ± 1.5 (7-point scale with 7 indicating higher intention). Attitudes, SN, PBC, and PO were significant predictors of intention to prescribe, while past prescribing behavior was not (Adj R2 = 0.741, p < .0001). Attitudes were explained by beliefs about increasing patient access (p = .0179). PBC was explained by beliefs about having policies and procedures in place (p = .004) and feeling comfortable prescribing (p = .008). ConclusionsOregon community pharmacists have a positive intention to prescribe using the FPC, but actual uptake remains low. Efforts to increase uptake should focus on the beliefs that contribute most strongly to pharmacist intention.

Investigation of the Associations between Diet Quality and Health-Related Quality of Life in a Sample of Swedish Adolescents.

Most adolescents do not consume a high-quality diet, while self-reported mental health problems within this group are increasing. This study aimed to investigate the association between diet quality and health-related quality of life, and to explore the differences in diet quality and health-related quality of life between gender and parental education status. In this cross-sectional study, a detailed web-based recall method was implemented to determine dietary intake, which was analysed using the newly developed Swedish Healthy Eating Index for Adolescents 2015 (SHEIA15) and the Riksmaten Adolescents Diet Diversity Score (RADDS), to determine diet quality. The KIDSCREEN-10 questionnaire was used to measure health-related quality of life, and parental education was self-reported through questionnaires. Parental education was divided into two groups: ≤12 years or >12 years. The study included 1139 adolescents from grade 7 (13–14 years old), 51% were girls. The results showed that girls had higher scores for healthy eating and diet diversity but lower scores for health-related quality of life. A positive association was found between diet diversity and health-related quality of life (Adj R2 = 0.072, p = 0.001), between vegetable/fruit consumption and health-related quality of life (Adj R2 = 0.071, p = 0.002), and between healthy eating and diet diversity (Adj R2 = 0.214, p < 0.001). No association was found between healthy eating and health-related quality of life for all participants. The mean scores for healthy eating and diet diversity were significantly higher in the higher education parental group. In conclusion, higher diet diversity and increased fruit and vegetable consumption could be a strategy to improve health-related quality of life among adolescents. There is a need to promote better diet quality, especially in households of low parental education. In addition, there is a further need to investigate the potential benefits of improved diet quality on mental health and overall well-being.

Pengaruh LDR, BOPO, NPL dan Mobile Banking terhadap Profitabilitas

This study aims to analyze the effect of the Loan to Deposit Ratio (LDR), Operating Costs of Operating Income (BOPO), Non Performing Loans (NPL), and Mobile Banking (MB) on Profitability (ROA) at PT Bank Tabungan Negara (Persero) Tbk from 2011 to 2020. The multiple Linear Regression Analysis Model is used to determine the magnitude of the relationship between the independent variable and the dependent variable while testing the hypothesis by using a t-test (partial) and f-test (simultaneous). Based on the results of the study from 2011 to 2020, it was concluded that the t-test (partial) showed that LDR had an insignificant positive effect on profitability. BOPO has a negative and significant effect on profitability. NPL and MB show that the two independent variables have no significant negative effect on profitability. With the f test (simultaneous) the significance of the effect of the independent variables, LDR, BOPO, NPL, and MB on the dependent variable Profitability can be concluded simultaneously has a significant positive effect on Profitability. The coefficient of determination adj R2 is 97.1%, this indicates that there is a very strong correlation where the independent variables LDR, BOPO, NPL, and MB greatly affect profitability, while 2.9% of other variables are outside the model of this study.

Salicylic acid derivatives as potential α-glucosidase inhibitors: drug design, molecular docking and pharmacokinetic studies

BackgroundDiabetes mellitus (DM) is one of the most defying health risk in the twenty-first century promoting a high rate of morbidity and mortality that could possibly increase if no intervention is in place. However, drugs for curing DM are available but are associated with adverse side effect necessitating the pursuit for a safe antidiabetic drugs. The present study was conducted in order to develop a QSAR model that would be used to predict the activities of salicylic acid derivatives, as well as to determine the binding interactions of the compounds with α-glucosidase using molecular docking studies.ResultsModel one was selected and reported as the best model based on its fitness with the following validation keys: R2(trng set) = 0.968, R2(adj) = 0.957, Q2(cv) = 0.932, LOF = 0.085 and R2(test set) = 0.864. Five potent analogues were designed using the ligand-based method with their predicted activities been calculated and found to be higher compared to the lead compound. Furthermore, binding interactions of the designed analogues within the active site of α-glucosidase (pdb id:3L4V) illustrate a good binding affinities than kotalanol and acarbose. However, the ADMET and drug-likeness properties predicted the design analogues to be pharmacologically and orally safe by not having more than one violation of Lipinski’s (Ro5) criteria.ConclusionsThe present findings therefore showed that the salicylic acid derivatives could serve as α-glucosidase inhibitors. The compounds can be studied further for a hunts of promising drug candidates against diabetes mellitus.

The Predictor Roles of Spiritual Well-Being, Healthcare Professionals' Support and Shock Anxiety in Implantable Cardioverter-Defibrillator Device Acceptance.

BackgroundAcceptance of the implantable cardioverter-defibrillator (ICD) device may be affected by a variety of factors. This study aimed to investigate the predictor roles of spiritual well-being, healthcare professionals’ support and shock anxiety in accepting ICD.MethodsThis cross-sectional study was conducted on 100 patients with ICD. The data were collected by the Florida Patient Acceptance Scale, Florida Shock Anxiety Scale, Spiritual Well-Being Scale and Healthcare Professionals’ Support Questionnaire.ResultsThe mean (SD) scores of patient acceptance, shock anxiety, spiritual well-being and healthcare professionals’ support were 65.4 (13.56), 21.93 (8.95), 88.92 (11.78) and 76.41 (10.54), respectively. The results revealed higher acceptance among the participants with lower shock anxiety levels (r = −0.51, P < 0.001), higher mean scores of spiritual well-being (r = 0.33, P = 0.001) and higher healthcare professionals’ support (r = 0.40, P < 0.01). Additionally, the results of linear regression indicated that spiritual well-being, healthcare professionals’ support and shock anxiety predicted 36% of the patient acceptance variance (R = 0.61, R2 = 0.38, adj R2 = 0.36) and shock anxiety and healthcare professionals’ support were the predictors of patient acceptance.ConclusionThe study results indicated that the patients’ mean score of acceptance was relatively high. In addition, the mean scores of shock anxiety, spiritual well-being and healthcare professionals’ support were low, moderate and relatively high, respectively. Conducting healthcare professionals’ support interventions, spiritual therapy and reducing shock anxiety can help patients accept ICDs.

Development of the PortionSize App for Real-Time Dietary Feedback

ObjectivesWe developed the PortionSizeTM app (PS app) to provide participants, in real time, an estimate of dietary intake and assistance with following dietary plans and managing body weight. The app provides templates superimposed on user’s food images to provide feedback on energy intake (kcal), macronutrients, and food groups. The current pilot study aimed to test the validity of the PS app in a lab-based setting and identify areas for improvement. MethodsDuring a lab visit, adults (4 male, 11 female), aged 18–65, BMI 18.5–45 kg/m2, majority (93%) White, were trained and used the PS app to assess dietary intake of foods provided, which were also covertly weighed. Participants (n = 14) provided qualitative feedback on PS app usability. Bland-Altman analysis was performed to determine if bias was introduced by increasing energy per food item. Qualitative methods were used to evaluate open-ended responses on PS app desirability. ResultsAcross all 69 food items, mean (± SD) energy between PS (162 ± 167 kcal) estimates and weighed food (143 ± 126 kcal) were not statistically different (P = 0.10). The Bland-Altman plot indicated agreement in energy intake between PS estimates and weighed values for lower energy foods, and the PS app overestimated energy intake for higher energy foods (Adj R2 = 0.20, P = < 0.001). Beverages (soda and tea), condiments (salad dressing and butter), and specific foods items (apples, chicken, pizza, carrots, and cookies) had the largest error (>30% difference in kcal between PS estimated and weighed foods). These foods have previously been identified as problematic in food intake estimation research. The most frequently mentioned difficulties with the PS app were the food search (7/14), food list options (4/14), and difficulties with PS templates (6/14). Consequently, improvements to the PS app included a new feature for estimating weight of packaged food, new methods for volume estimation of beverages, an updated method for manually entering foods not captured in real-time, an improved food search, updates to the PS food database, and changes to app training instructions. ConclusionsThis pilot study demonstrates promise for the PS app to measure average energy intake. Areas of further app development were identified and actioned and are undergoing additional validity testing. Funding SourcesR01DK124558, T32 DK64584, P30 DK072476, U54 GM104940.