Nevin Manimala

Environ Sci Pollut Res Int. 2022 Sep 22. doi: 10.1007/s11356-022-23055-z. Online ahead of print.

ABSTRACT

The abundant release of toxic heavy metals into wastewater has been a serious threat to human health, aquatic environments, plants, and animals; thus, it is critical to purify wastewater of these pollutants through a proper treatment process. A novel hydrogel compound was synthesized using partially hydrolyzed polyacrylamide (PHPAm) and functionalized Fe₃O₄-coated magnetic nanoparticles (PHPAm/Fe₃O₄@SiO₂-SH) that is efficient in removal of mercury and lead from wastewater. This new magnetic nanoadsorbent is characterized using scanning electron microscope, Fourier-transform infrared, thermogravimetric analysis, vibrating sample magnetometer, and energy-dispersive X-ray analysis. The central composite design under response surface methodology (CCD-RSM) was applied in designing the experiments to optimize the main parameters affecting the adsorption capacity: initial concentration (77.50 mg L^-1), pH (6.11 and 6.48), adsorbent dosage (25 mg), and contact time (115 and 106 min) for both Hg²⁺ and Pb²⁺ adsorption, respectively. Quadratic models were used for variable predictions and analysis of variance was applied to evaluate the statistical parameters and investigate the interactions of the variables. The high determination coefficient (R² 0.99) for both metals indicates a good correlation between actual and predicted response values. Additionally, thermodynamic modeling showed an endothermic and exothermic for Hg²⁺ and Pb²⁺, respectively, and also the spontaneous nature of both metals’ adsorption process within the temperature range of 288-318 K. Mercury and lead kinetic studies were in agreement with pseudo-second-order modeling, and the equilibrium results revealed that the Langmuir isotherm best fit the experimental data with maximum adsorption capacities of 256.41 and 227.27 (mg g^-1) for Hg²⁺ and Pb²⁺, respectively. Overall, PHPAm/Fe₃O₄@SiO₂-SH is thought to have highly promising potential for investigating heavy metals in wastewater treatment, and will make important contributions to similar studies that may be conducted in the future.

PMID:36136188 | DOI:10.1007/s11356-022-23055-z

Environ Sci Pollut Res Int. 2022 Sep 22. doi: 10.1007/s11356-022-23129-y. Online ahead of print.

ABSTRACT

Nitrate pollution of groundwater has become a global concern as it can affect drinking water quality and human health. In this paper, an extensive hydrochemical investigation was performed to assess the spatial distribution, source identification, and health risk of groundwater nitrate pollution in the Subei Lake basin. The prevalent pollutant, nitrate (NO₃^–), was identified based on descriptive statistical method and box plots, and most of the other parameters of groundwater samples met water standards and can be used for drinking purpose. The results showed that nearly 23.53% of groundwater samples displays the NO₃^– concentrations higher than the limit of 50 mg/L recommended by the World Health Organization, and the highest nitrate content (199 mg/L) is mainly distributed around the Mukai Lake. Piper triangle diagram demonstrated that the dominated anions of hydrochemical types exhibit a gradual evolving trend from HCO₃^– to SO₄^2- and Cl^– with increasing nitrate concentration. The correspondence analysis suggested that agricultural activities are identified as the most possible source of nitrate contamination, while the higher content of other parameters in individual groundwater samples may be controlled by natural factors. The impacts of pollutant NO₃^– on human health were quantified using human health risk assessment method, and results showed that the order of non-carcinogenic health risk values through drinking water intake is Infants>Children>Adult males>Adult females, and 65%, 53%, 41%, and 35% of samples exceed the acceptable risk level (hazard quotient=1), respectively. The main findings obtained from this study can provide valuable insight on drinking water safety and groundwater pollution prevention.

PMID:36136183 | DOI:10.1007/s11356-022-23129-y

Maxillofac Plast Reconstr Surg. 2022 Sep 22;44(1):30. doi: 10.1186/s40902-022-00354-6.

ABSTRACT

PURPOSE: Surgical removal of intra-bony calcific benign lesions is technically challenging regarding its accessibility, proximity to vital structures, and deteriorating effect on the remaining bony structures.

METHODS: Computer-guided buccal cortical plate separation was performed for ten patients using patient-specific osteotomy locating guides and pre-bent plates. The guide was designed to outline the osteotomy, the buccal cortical plate was separated, the lesion was removed, and finally, the pre-bent plates were used to fix the separated cortex.

RESULTS: Surgical procedures were uneventful for all patients, operation time was 39.5 ± 13.01 min, postoperative pain decreased within the follow-up time intervals, and there was a statistical significant difference between the time intervals (P value < 0.001). Edema and trismus were acceptable. One case showed nerve affection which resolved after 4 weeks.

CONCLUSION: Computer-guided buccal cortical plate separation for removal of intra-bony calcified benign lesions provides a promising approach, especially for inexperienced surgeons.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05329974 . Registered on 6 April 2022-retrospectively registered.

PMID:36136180 | DOI:10.1186/s40902-022-00354-6

Environ Monit Assess. 2022 Sep 22;194(11):818. doi: 10.1007/s10661-022-10490-1.

ABSTRACT

The potential contamination levels and human health risk of heavy metals in sediment of the Turnasuyu Stream in Ordu, Turkey, were evaluated comprehensively by taking seasonal samples from three different locations. The order of the mean heavy metals (HMs) concentrations (mg/kg) were as follows: Fe > Al > Mn > Pb > Zn > Cu > Co > Cr > Ni > Cd > As. All HM levels, except Cd and Pb, were in the minimum enrichment range as assessed by the sediment enrichment factor (EF). Similar low contamination levels for all HM, except Pb and Cd, were also observed when the contamination factor (CF) and geo-accumulation index (I_geo) were taken into account. The low risk of the study area has also been confirmed by the ecological risk index (E_rⁱ) values. The probable human health risk assessment has been performed, and the lifetime cancer risk (LCR) values for adults were found as negligible with values below 10^-6. In addition, the hazard index (HI) and total hazard index (THI) results were both higher in children than in adults. The Pearson correlation coefficient (PCC) revealed the highest correlation between Cd and Pb (0.85). When the ecological indexes and statistical results are evaluated together, it is thought that the presence of HMs in the sediment may be due to lithological reasons as well as anthropogenic activities such as quarrying, municipal, agricultural, and domestic discharges in the region. Mitigation measures should be taken in accordance with the standards within the river basin to prevent the potential risks of pollution.

PMID:36136175 | DOI:10.1007/s10661-022-10490-1

Discov Oncol. 2022 Sep 22;13(1):90. doi: 10.1007/s12672-022-00558-2.

ABSTRACT

BACKGROUND: Nectin-4 contributes to tumor proliferation, lymphangiogenesis and angiogenesis in malignant tumors and is an emerging target in tumor therapy. In renal cell carcinoma (RCC) VEGF-directed tyrosine kinase inhibitors and checkpoint inhibitors are currently treatments of choice. Enfortumab vedotin-ejf (EV) is an antibody drug conjugate that targets Nectin-4. The aim of our study was to investigate the expression of Nectin-4 in a large cohort of papillary RCC specimens.

PATIENTS AND METHODS: Specimens were derived from the PANZAR consortium (Erlangen, Heidelberg, Herne, Homburg, Mainz, Mannheim, Marburg, Muenster, LMU Munich, TU Munich, and Regensburg). Clinical data and tissue samples from n = 190 and n = 107 patients with type 1 and 2 pRCC, respectively, were available. Expression of Nectin-4 was determined by immunohistochemistry (IHC).

RESULTS: In total, Nectin-4 staining was moderately or strongly positive in of 92 (48.4%) of type 1 and 39 (36.4%) type 2 of pRCC cases. No associations between Nectin-4 expression and age at diagnosis, gender, grading, and TNM stage was found. 5 year overall survival rate was not statistically different in patients with Nectin-4 negative versus Nectin-4 positive tumors for the overall cohort and the pRCC type 2 subgroup, but higher in patient with Nectin-4 positive pRCC type 1 tumors compared to Nectin-4 negative tumors (81.3% vs. 67.8%, p = 0.042).

CONCLUSION: Nectin-4 could not be confirmed as a prognostic marker in pRCC in general. Due to its high abundance on pRCC specimens Nectin-4 is an interesting target for therapeutical approaches e.g. with EV. Clinical trials are warranted to elucidate its role in the pRCC treatment landscape.

PMID:36136143 | DOI:10.1007/s12672-022-00558-2

Ann Hematol. 2022 Sep 22. doi: 10.1007/s00277-022-04984-8. Online ahead of print.

ABSTRACT

Despite widespread concern about energy imbalance due to tumor and chemotherapy-related side effects, little is known about detailed variations in energy input, metabolic rate, and physical activity. This study explored changes in energy balance components and serum biomarkers of patients with hematologic malignancies undergoing chemotherapy. Our prospective study included 40 patients with hematologic malignancies hospitalized for chemotherapy. We measured energy balance components, physical function, and serum biomarkers at baseline and weekly after chemotherapy for 3 weeks. Significant weight loss, representing negative energy balance, occurred at 2 (p = 0.002) and 3 weeks (p < 0.001) post-chemotherapy. Statistically reduced oral intake was observed at 3 weeks post-chemotherapy (p = 0.040), and resting energy expenditure statistically decreased according to Harris-Benedict equation, but not to Penn State University equation. Physical function according to DEMMI score decreased significantly at 3 weeks post-chemotherapy (p = 0.002). Serum biomarker analysis demonstrated significant changes in albumin, total protein, CXCL13, and GDF15, with exception of leptin. Although conventional serum biomarkers (total protein and albumin) did not reach pathological states despite their statistical differences, subgroup analysis showed CXCL13 in weight loss group and GDF15 in reduced oral intake group were significantly changed. Over half of patients (65.0%, n = 26) suffered from energy imbalance associated with weight loss and reduced oral intake during chemotherapy. Serial laboratory results suggested that novel biomarkers (CXCL13, GDF15) could be correlated with cachexic state and reduced food intake. Monitoring clinical and serum biomarkers associated with energy balance together can help identify needs for nutritional support in patients with hematologic malignancies undergoing chemotherapy.

PMID:36136099 | DOI:10.1007/s00277-022-04984-8

Biom J. 2022 Sep 22. doi: 10.1002/bimj.202200035. Online ahead of print.

ABSTRACT

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.

PMID:36136044 | DOI:10.1002/bimj.202200035

Mol Pharm. 2022 Sep 22. doi: 10.1021/acs.molpharmaceut.2c00573. Online ahead of print.

ABSTRACT

A pair of popular thermodynamic models for pharmaceutical applications, namely, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and the conductor-like screening model for real solvents (COSMO-RS) are thoroughly benchmarked for their performance in predicting the solubility of active pharmaceutical ingredients (APIs) in pure solvents. The ultimate goal is to provide an illustration of what to expect from these progressive frameworks when applied to the thermodynamic solubility of APIs based on activity coefficients in a purely predictive regime without specific experimental solubility data (the fusion properties of pure APIs were taken from experiments). While this kind of prediction represents the typical modus operandi of the first-principles-aided COSMO-RS, PC-SAFT is a relatively highly parametrized model that relies on experimental data, against which its pure-substance and binary interaction parameters (k_ij) are fitted. Therefore, to make this benchmark as fair as possible, we omitted any binary parameters of PC-SAFT (i.e., k_ij = 0 in all cases) and preferred pure-substance parameter sets for APIs not trained to experimental solubility data. This computational approach, together with a detailed assessment of the obtained solubility predictions against a large experimental data set, revealed that COSMO-RS convincingly outperformed PC-SAFT both qualitatively (i.e., COSMO-RS was better in solvent ranking) and quantitatively, even though the former is independent of both substance- and mixture-specific experimental data. Regarding quantitative comparison, COSMO-RS outperformed PC-SAFT for 9 of the 10 APIs and for 63% of the API-solvent systems, with root-mean-square deviations of the predicted data from the entire experimental data set being 0.82 and 1.44 log units, respectively. The results were further analyzed to expand the picture of the performance of both models with respect to the individual APIs and solvents. Interestingly, in many cases, both models were found to qualitatively incorrectly predict the direction of deviations from ideality. Furthermore, we examined how the solubility predictions from both models are sensitive to different API parametrizations.

PMID:36136040 | DOI:10.1021/acs.molpharmaceut.2c00573

Milbank Q. 2022 Sep 22. doi: 10.1111/1468-0009.12582. Online ahead of print.

ABSTRACT

Policy Points Social determinants of health are an important predictor of future health care costs. Medicaid must partner with other sectors to address the underlying causes of its beneficiaries’ poor health and high health care spending.

CONTEXT: Social determinants of health are an important predictor of future health care costs but little is known about their impact on Medicaid spending. This study analyzes the role of social determinants of health (SDH) in predicting future health care costs for adult Medicaid beneficiaries with similar past morbidity burdens and past costs.

METHODS: We enrolled into a prospective cohort study 8,892 adult Medicaid beneficiaries who presented for treatment at an emergency department or clinic affiliated with two hospitals in Washington, DC, between September 2017 and December 31, 2018. We used SDH information measured at enrollment to categorize our participants into four social risk classes of increasing severity. We used Medicaid claims for a 2-year period; 12 months pre- and post-study enrollment to measure past and future morbidity burden according to the Adjusted Clinical Groups system. We also used the Medicaid claims data to characterize total annual Medicaid costs one year prior to and one year after study enrollment.

RESULTS: The 8,892 participants were primarily female (66%) and Black (91%). For persons with similar past morbidity burdens and past costs (p < 0.01), the future morbidity burden was significantly higher in the upper two social risk classes (1.15 and 2.04, respectively) compared with the lowest one. Mean future health care spending was significantly higher in the upper social risk classes compared with the lowest one ($2,713, $11,010, and $17,710, respectively) and remained significantly higher for the two highest social risk classes ($1,426 and $3,581, respectively), given past morbidity burden and past costs (p < 0.01). When we controlled for future morbidity burden (measured concurrently with future costs), social risk class was no longer a significant predictor of future health care costs.

CONCLUSIONS: SDH are statistically significant predictors of future morbidity burden and future costs controlling for past morbidity burden and past costs. Further research is needed to determine whether current payment systems adequately account for differences in the care needs of highly medically and socially complex patients.

PMID:36134645 | DOI:10.1111/1468-0009.12582

Integr Environ Assess Manag. 2022 Sep 22. doi: 10.1002/ieam.4688. Online ahead of print.

ABSTRACT

Pesticide surface water monitoring data have rarely been used as the only quantitative measure of exposure because the available monitoring data for most pesticides has not been considered robust enough for direct use in pesticide exposure assessments due to infrequent sampling. The cost of daily sample collection and analysis prohibits high sampling frequency for most monitoring programs. In this context, a common question raised in assessments is how likely peak concentrations (i.e., annual maximums) may be missed if sampling intervals are greater than daily. The US Geological Survey developed the statistical model ‘seasonal wave with streamflow adjustment and extended capability’ (SEAWAVE-QEX) to address the need to estimate infrequently occurring pesticide concentrations, such as annual maximum daily concentrations, for sites with non-daily monitoring data. This study compares the results of two post-processing methods and evaluates the capability of SEAWAVE-QEX to estimate annual maximum concentrations of three commonly used herbicides and one metabolite in a catchment in Belgium. The study concludes that the appropriateness of using SEAWAVE-QEX to estimate annual maximum concentrations is dependent on pesticide characteristics and usage and that the model can be particularly sensitive to non-flow correlated exposure events (e.g., point source contributions or drift). This article is protected by copyright. All rights reserved. © 2022 SETAC.

PMID:36134644 | DOI:10.1002/ieam.4688