Category: Nevin Manimala

Sci Total Environ. 2022 Apr 8:155131. doi: 10.1016/j.scitotenv.2022.155131. Online ahead of print.

ABSTRACT

Naturally occurring, geogenic manganese (Mn) and iron (Fe) are frequently found dissolved in groundwater at concentrations that make the water difficult to use (deposits, unpleasant taste) or, in the case of Mn, a potential health hazard. Over 6000 groundwater measurements of Mn and Fe in Southeast Asia and Bangladesh were assembled and statistically examined with other physicochemical parameters. The machine learning methods random forest and generalized boosted regression modeling were used with spatially continuous environmental parameters (climate, geology, soil, topography) to model and map the probability of groundwater Mn > 400 μg/L and Fe > 0.3 mg/L for Southeast Asia and Bangladesh. The modeling indicated that drier climatic conditions are associated with a tendency of elevated Mn concentrations, whereas high Fe concentrations tend to be found in a more humid climate with elevated levels of soil organic carbon. The spatial distribution of Mn > 400 μg/L and Fe > 0.3 mg/L was compared and contrasted with that of the critical geogenic contaminant arsenic (As), confirming that high Fe concentrations are often associated with high As concentrations, whereas areas of high concentrations of Mn and As are frequently found adjacent to each other. The probability maps draw attention to areas prone to elevated, concentrations of geogenic Mn and Fe in groundwater and can help direct efforts to mitigate their negative effects. The greatest Mn hazard is found in densely populated northwest Bangladesh and the Mekong, Red and Ma River Deltas of Cambodia and Vietnam. Widespread elevated Fe concentrations and their associated negative effects on water infrastructure pose challenges to water supply. The Mn and Fe prediction maps demonstrate the value of machine learning for the geospatial prediction modeling and mapping of groundwater contaminants, as well as the potential for further constituents to be targeted by this novel approach.

PMID:35405246 | DOI:10.1016/j.scitotenv.2022.155131

Rom J Intern Med. 2022 Apr 11. doi: 10.2478/rjim-2022-0005. Online ahead of print.

ABSTRACT

Background: Improved prognosis and delay of clinical complications in Diabetes mellitus can be ensured by early screening and regular monitoring after diagnosis. This requires venipuncture at regular intervals of time causing anxiety and discomfort to the patient. Hence, development of a painless, non-invasive procedure is desirable for which saliva is a potential tool. Also, this would provide an easy and cost-effective means for large scale screening and epidemiological intervention. Aim: To measure fasting plasma glucose (FPG) and compare and correlate with salivary glucose levels in normal and diabetic individuals. Also, the correlation between glycated hemoglobin (HbA1c) and salivary glucose is studied in the diabetics and controls. Methods: Blood and salivary glucose was estimated by GOD-POD method and glycated hemoglobin by HPLC. Statistical analysis was done on SPSS 16. Mean, Standard deviation, independent t test, ANOVA (f test), Pearson’s correlation coefficient along with regression analysis was carried out and comparison was done between the control and diabetic groups and the different subgroups within the diabetic group. Results:A significant difference between the salivary glucose levels in subjects indicating that a deranged glycemic status is reflected in saliva. Also, salivary glucose increases in proportion to an increase in the FPG and HbA1C of the diabetics. The regression coefficient was calculated and a formula was derived for prediction of FPG and HbA1c using salivary glucose. Conclusion: Saliva can be used as a screening tool for diabetes. Standardization of the technique and setting up a reference range will also make it useful in diagnosing diabetes mellitus.

PMID:35405049 | DOI:10.2478/rjim-2022-0005

Horm Mol Biol Clin Investig. 2022 Apr 11. doi: 10.1515/hmbci-2021-0074. Online ahead of print.

ABSTRACT

OBJECTIVES: Vitamin D is an important regulator of the immune system, and it has been shown that deficiency of vitamin D is significant environmental factor in some immune-mediated diseases such as Multiple Sclerosis (MS). In this study, we have compared serum 25 hydroxyvitamin (OH) D levels in Relapsing-Remitting Multiple Sclerosis (RRMS), clinically isolated syndrome (CIS), and control groups.

METHODS: Forty patients with CIS and 60 patients who have been diagnosed RRMS between age 18-45, respectively, and followed up at Pamukkale University Faculty of Medicine, Department of Neurology, and 60 healthy individuals have been included in this study. Serum 25(OH) vitamin D, calcium, phosphorus, alkaline phosphatase, parathormone, insulin, and fasting blood glucose levels were studied for all three groups.

RESULTS: A statistically significant difference was determined in the comparison of three groups for mean 25(OH) vitamin D levels. In the intergroup comparison of mean 25(OH) vitamin D; mean 25(OH) vitamin D level was determined to be statistically significantly lower in both RRMS and CIS groups compared to control group (p<0.05).

CONCLUSIONS: Since vitamin D deficiency poses a problem from the early stage of disease spectrum in both CIS patients and MS patients, 25(OH) vitamin D level should be routinely controlled, and replacement should be administered upon any deficiency state.

PMID:35405046 | DOI:10.1515/hmbci-2021-0074

Ecology. 2022 Apr 11:e3718. doi: 10.1002/ecy.3718. Online ahead of print.

ABSTRACT

Monitoring technologies now provide real-time animal location information which opens the possibility of forecasting systems to fuse these data with movement models to predict future trajectories. State space modelling approaches are well established for retrospective location estimation and behavioural inference through state and parameter estimation. Here, we use a state space model within a comprehensive data assimilative framework for probabilistic animal movement forecasting. Real-time location information is combined with stochastic movement model predictions to provide forecasts of future animal locations and trajectories, as well as estimation of key behavioural parameters. Implementation uses ensemble-based sequential Monte Carlo methods (a particle filter). We first apply the framework to an idealized case using a non-dimensional animal movement model based on a continuous-time random walk process. A set of numerical forecasting experiments demonstrate the workflow and key features, such as the online estimation of behavioural parameters using state augmentation, the use of potential functions for habitat preference, as well as the role of observation error and sampling frequency on forecast skill. For a realistic demonstration, we adapt the framework to short-term forecasting of the endangered Southern Resident Killer Whale (SRKW) in the Salish Sea using visual sighting information wherein the potential function reflects historical habitat utilization of SRKW. We successfully estimate whale locations up to 2.5 hours in advance with a moderate prediction error ($< 5$ km), providing reasonable lead-in time to mitigate vessel-whale interactions. It is argued that this forecasting framework can be used to synthesize diverse data types, improve animal movement models and behavioural understanding, and has the potential to become an important new direction for movement ecology.

PMID:35405019 | DOI:10.1002/ecy.3718

Oper Dent. 2022 Apr 11. doi: 10.2341/20-156-L. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the effect of different surface treatments on the shear bond strength (SBS) of lithium silicate (LS) and lithium disilicate (LD) ceramics, after thermocycling.

METHODS AND MATERIALS: For SBS test, 72 ceramic blocks (18×14×2 mm) were made (24 blocks from each ceramic material): VITA Suprinity (LSS), Celtra Duo (LSC), and Lithium disilicate (LD). The blocks were polished with sandpaper of increasing grit (#280, #400, #800, and #1200) and embedded in chemically activated acrylic resin. Afterwards, they were randomly divided into 12 groups (6 blocks per group) according to: “Ceramic” (LD, LSC, and LSS) and “Surface treatment” (HFS: hydrofluoric acid + silane; MEP: Monobond Etch & Prime/Ivoclar). From each treated surface ceramic block, four dual-curing resin cement cylinders (RelyX U200, 3M Oral Care) were prepared using a Tygon tube (Ø=3 mm and h=2 mm) and light cured for 40 seconds (1000 mW/cm2) (N=288/n=24). All specimens were submitted to thermocycling (10,000 cycles, 5°C and 55°C, 30 seconds) and then to SBS test at a crosshead speed of 1 mm/min using a 50-kgf load cell. Forty-five additional blocks were made for roughness and SEM analysis. Failure mode was also performed. The data (MPa) were statistically analyzed by oneway analysis of variance (ANOVA), Tukey test (5%), and Weibull analysis. The Ra was analyzed by Kruskal-Wallis and Dunn Test (5%). The other variables were analyzed qualitatively.

RESULTS: ANOVA revealed that “surface treatment” was significant for all ceramic materials (p<0.05). The LD-HFS (18.66±3.49), LSC-HFS (16.81±2.62), and LSS-HFS (16.33±3.08) groups had significantly higher SBS than the LD-MEP (7.00±4.2), LSC-MEP (14.12±3.51), and LSS-MEP (13.87±2.52) groups. Complete adhesive failures at the cement- dentin interface were more frequent. Weibull modulus was superior for the LD-HFS (6.22), LSC-HFS (8.8), and LSS-HFS (7.4) groups.

CONCLUSION: HF followed by silanization is the most suitable surface treatment for the cementation of LS and LD glass ceramics.

PMID:35405015 | DOI:10.2341/20-156-L

Oper Dent. 2022 Apr 11. doi: 10.2341/20-007-C. Online ahead of print.

ABSTRACT

AIM: To evaluate and compare the effects of both manual and ultrasonic scaling on surface roughness of four different base materials, used for elevating dentin/cementum gingival margins of proximal cavities.

METHODS AND MATERIALS: Eighty human upper molars with compound Class II mesial cavities, with gingival margins 1 mm below the cemento-enamel junction (CEJ), were divided into four different groups according to the type of the base material used; resin-modified glass ionomer (RMGI), glass hybrid (HV-GIC), flowable bulk-fill resin composite (Bulk Flow) and bioactive ionic resin (Activa). This was followed by completing the restorations with the same resin composite. All materials were used according to the manufacturers’ instructions. All groups were further subdivided into two subgroups according to the scaling technique: manual (hand) or ultrasonic. All restorative and scaling procedures were performed after fixation of specimens with acrylic beside neighboring teeth to simulate natural contact. The mean surface roughness (Ra, μm) of all specimens was measured quantitatively and qualitatively by a three-dimensional (3D) surface analyzer system at two stages; (1) after thermal cycling for 5000 cycles without scaling and (2) after scaling. Data were statistically analyzed using analysis of variance (ANOVA), Tukey post hoc tests, and paired sample t-tests (at α=0.05).

RESULTS: For baseline readings, the Bulk Flow group had the lowest Ra values, while HV-GIC group had the highest. RMGI and Activa groups had no statistical significant difference between their Ra values (p>0.05). For post scaling readings, hand scaling had significantly lower Ra values than ultrasonic scaling in all the material groups (p<0.05), except in the Bulk Flow group, where both scaling methods were not significantly different from each other (p>0.05).

CONCLUSION: Bulk Flow had the smoothest surfaces when cured against a matrix band compared with the other tested base materials. When hand and ultrasonic scaling methods were compared, the latter technique had more detrimental effect on the surface texture of the four tested base materials.

PMID:35405002 | DOI:10.2341/20-007-C

Oper Dent. 2022 Apr 11. doi: 10.2341/20-215-C. Online ahead of print.

ABSTRACT

OBJECTIVES: This double-blind, randomized clinical trial evaluated the influence of dentin moisture on postoperative sensitivity (POS), as well as, on clinical performance in posterior bulk-fill composite restorations, using a universal adhesive, until 12 months after clinical service.

METHODS AND MATERIALS: In accordance with a split-mouth design, 45 patients received posterior restorations, restored with a bulk-fill resin composite (Filtek Bulk Fill, 3M Oral Care) and a universal adhesive used in etch-and-rinse mode (SBU; Single Bond Universal Adhesive), which were applied on dry or moist dentin, with a cavity depth of at least 3 mm. Three operators placed 90 Class I/Class II restorations. Patients were evaluated for spontaneous and stimulated POS in the baseline, and after 48 hours, 7 days, and at 6 and 12 months. In addition, secondary parameters (marginal discoloration, marginal adaptation, fracture, and recurrent caries) were evaluated by World Dental Federation (FDI) criteria after 7 days and at 6 and 12 months. Statistical analyzes were performed using the Chi-square, Fisher exact, Friedman, Kruskall-Wallis, and Mann-Whitney tests (α=0.05).

RESULTS: No significant spontaneous and stimulated POS was observed when SBU was applied in dry and moist dentin (p>0.05). A significant and higher risk of spontaneous POS (20.0%; 95%CI 10.9-33.82 for dry dentin and 22.22%; 95%CI 12.54-36.27 for moist dentin) occurred up to 48 hours after restoration placement for the dry and moist dentin groups (p<0.02). However, the POS intensity was mild up to 48 hours with no significant difference between dry and moist dentin groups (p>0.79). When secondary parameters were evaluated, no significant differences between the groups were observed.

CONCLUSION: Dentin moisture did not influence POS in posterior bulk-fill composite restorations when associated with a universal adhesive applied in etch-and-rinse mode.

PMID:35405005 | DOI:10.2341/20-215-C

PLoS One. 2022 Apr 11;17(4):e0265507. doi: 10.1371/journal.pone.0265507. eCollection 2022.

ABSTRACT

BACKGROUND: Inappropriate polypharmacy has been linked with adverse outcomes in older, multimorbid adults. OPERAM is a European cluster-randomized trial aimed at testing the effect of a structured pharmacotherapy optimization intervention on preventable drug-related hospital admissions in multimorbid adults with polypharmacy aged 70 years or older. Clinical results of the trial showed a pattern of reduced drug-related hospital admissions, but without statistical significance. In this study we assessed the cost-effectiveness of the pharmacotherapy optimisation intervention.

METHODS: We performed a pre-planned within-trial cost-effectiveness analysis (CEA) of the OPERAM intervention, from a healthcare system perspective. All data were collected within the trial apart from unit costs. QALYs were computed by applying the crosswalk German valuation algorithm to EQ-5D-5L-based quality of life data. Considering the clustered structure of the data and between-country heterogeneity, we applied Generalized Structural Equation Models (GSEMs) on a multiple imputed sample to estimate costs and QALYs. We also performed analyses by country and subgroup analyses by patient and morbidity characteristics.

RESULTS: Trial-wide, the intervention was numerically dominant, with a potential cost-saving of CHF 3’588 (95% confidence interval (CI): -7’716; 540) and gain of 0.025 QALYs (CI: -0.002; 0.052) per patient. Robustness analyses confirmed the validity of the GSEM model. Subgroup analyses suggested stronger effects in people at higher risk.

CONCLUSION: We observed a pattern towards dominance, potentially resulting from an accumulation of multiple small positive intervention effects. Our methodological approaches may inform other CEAs of multi-country, cluster-randomized trials facing presence of missing values and heterogeneity between centres/countries.

PMID:35404990 | DOI:10.1371/journal.pone.0265507

PLoS One. 2022 Apr 11;17(4):e0266078. doi: 10.1371/journal.pone.0266078. eCollection 2022.

ABSTRACT

INTRODUCTION: HIV prevalence and sexual risk have been estimated very high for transgender people. However, the limited sampling and data collection methods used in current research on transgender people potentially led to overrepresentation and generalisation of people at risk for HIV. Current HIV prevalence estimates in transgender populations are generalised from studies mainly focusing on transgender women engaging in sex work. Moreover, studies focusing on non-binary people, who identify with a broad range of identities beyond the traditional male and female gender identities, are scarce.

OBJECTIVES: To estimate the HIV prevalence rate in the Flemish and Brussels (Belgium) transgender population, including transgender women, transgender men and non-binary people, and to identify the associated risk factors.

METHODS: In this community-based cross-sectional study, self-identified transgender and non-binary (TGNB) people will be recruited through a two-stage time-location sampling approach. First, community settings in which TGNB people gather will be mapped to develop an accurate sampling frame. Secondly, a multistage sampling design is applied involving a stratification based on setting type (healthcare facilities vs outreach events), a selection of clusters by systematic sampling and a simple random selection of TGNB people within each cluster. Participants will complete an electronic self-reported survey to measure sociological, sexual and drug-using behaviors (risk factors) and oral fluid aliquots will be collected and tested for HIV antibodies. Logistic regression models will be used to evaluate risk factors independently associated with HIV infection. The presented study is registered at ClinicalTrials.gov (NCT04930614).

DISCUSSION: This study will be the first to investigate the HIV prevalence rates and associated risk behaviors in an accurate representation of the TGNB population in a Western European country. The findings will globally serve as a knowledge base for identifying subgroups at risk for becoming infected with HIV within TGNB people and to set up targeted prevention programs.

PMID:35404977 | DOI:10.1371/journal.pone.0266078

PLoS One. 2022 Apr 11;17(4):e0265071. doi: 10.1371/journal.pone.0265071. eCollection 2022.

ABSTRACT

In Ethiopia, soil degradation is one of the major causes of low and declining agricultural productivity. As a result of this challenge, the country has been battling to adopt conservation practices. The main objective of this study was to assess farmers’ adoption decisions of soil and water conservation (SWC) practices. For the survey, 304 farmers were selected from farming communities in Lege-Lafto Watershed, South Wollo,Ethiopia. Information were gathered using a household survey, and through focus group discussions, key informant interviews, and field observation. A binary logistic regression model and descriptive statistics were used to analyze the data. The results indicated that about 64% of the farmers adopted soil and water conservation practices in the study area. The findings depicted that soil bund, stone bund, stone-faced soil bund, loose stone and brush-wood check dams, hillside terrace, and bund stabilized with vegetation are practiced in the watershed. The analysis result revealed adoption of soil and water conservation practices is significantly and positively influenced by the perception of farmers on erosion problems and SWC practices, family labour, educational level, and membership in local institutions. However, distance from residence to the nearest market and farmland, off-farm activities, and the ratio of cultivable land to family size influenced the adoption of SWC practices negatively. Therefore, improving farmers’ educational status, and strengthening local institutions are vital for sustainable land management practices in the country.

PMID:35404967 | DOI:10.1371/journal.pone.0265071