GIS-based assessment of groundwater vulnerability to heavy metal contamination via water quality pollution indices in urban Aligarh, India

The study presents an assessment of groundwater vulnerability due to heavy-metal contamination using Heavy Metal Pollution and Contamination Index of Urban Aligarh. Globally, hazardous compounds in industrially contaminated sites are pressing and high-priority issue. A detailed risk assessment was carried out to determine the potential health hazards linked to locations that were recently polluted. A total of 17 groundwater samples were taken from hand-pump and 20 industrial drainage samples were collected from selected areas of Aligarh. The concentration of heavy-metals in the collected samples analyzed were shown on maps using ArcGIS software and interpreted for Heavy Metal Pollution Index (HPIx) and Contamination Index (CDx). These analyzed values were subsequently compared with the permissible limits established by the agencies like EPA, WHO, and BIS. The mean concentration of heavy-metals in groundwater of different locations was observed as follows particular sequence: Ni (1.40), Cu (0.58), Zn (0.06), Fe (0.08), Mn (0.04), Cr (0.001), Pb (0.00025) mg/l. Additionally in industrial effluent, Cr (18.3), Ni (13.34), Mn (1.16), Cu (1.99), Pb (1.2), Fe (6.3), Zn (0.51) mg/l. According to HPIx, the analysis reveals 64.7%, of visited areas belonged to have safe groundwater. Conversely, a smaller proportion, 35.3%, was found falling into heavy metal-polluted group. HIGHLIGHTS The study provides a comprehensive assessment of heavy metal contamination.; GIS-driven vulnerability mapping is conducted in the study.; The study includes an evaluation of real-world impact.; The study systematically validates scientific indices for accuracy and reliability.; The study investigates health effects resulting from heavy metal contamination.; A comprehensive analysis of drinking water quality.

Air pollution tolerance, anticipated performance, and metal accumulation indices of four evergreen tree species in Dhaka, Bangladesh

Trees in urban forests are able to better air quality by removing particulate matter (PM) from the atmosphere through the accumulation of particles on their leaf surfaces. When exposed to air pollutants, the physiology, morphology, and biochemistry of a plant may be affected, which will result in alterations to that plant’s function and growth. In this study, we assessed, for the first time, the tolerance or sensitivity of four evergreen trees (Ficus benghalensis, Ficus religiosa, Mangifera indica, and Polyalthia longifolia) towards air pollution by employing several indices. The trees, which are commonly grown along the roadside in Dhaka, Bangladesh, were evaluated by using the air pollution tolerance index (APTI), the anticipated performance index (API), and the metal accumulation index (MAI). The deposition of four heavy metals (Cd, Cr, Pb, and Ni) on the leaves of four aforementioned tree species was studied employing ICP-MS, and subsequently, a predictive foliar MAI was created. APTI values of the studied plants varied from 10.31 to 12.51 implying that they were either intermediately tolerant or sensitive. A significantly strong positive correlation was obtained between APTI and relative water content (RWC) (r = 0.864; p < 0.001) and between APTI and ascorbic acid content (AAC) (r = 0.748; p < 0.01). The API revealed M. indica as a good performer, which maintained the highest score (68.75%) among the tree species irrespective of different sites. The Pb concentrations were anomalously high in the atmosphere of Dhaka, suggesting its anthropogenic origin. A significant (r = 0.722; p < 0.01) relationship was found between Cd and Pb indicating their common origin. Among the species, F. benghalensis had the highest MAI value (13.60). The MAI value was found to have a significant association with pH, AAC, and total chlorophyll content. Based on APTI, API, and MAI values, the most suitable plant species for urban forest development was identified to be M. indica followed by F. benghalensis and F. religiosa

Estrogen Induces c-myc Transcription by Binding to Upstream ERE Element in Promoter

Estrogen Receptor &alpha;(ER&alpha;) is reported to regulate the expression of many target genes by binding to specific estrogen response elements (EREs) in their promoters. c-myc is known to be over-expressed in most of the human carcinomas due to dysregulated transcription, translation, or protein stability. Estrogen (E) can induce the c-myc expression by binding to an upstream enhancer element in its promoter. This suggests that elevated estradiol (E2), a potent form of estrogen, levels could induce the expression of c-myc in breast cancer (BC). The expression of c-myc and estradiol were induced at Stage III and Stage IV of breast cancer. c-myc and estradiol expression was also associated with the established risk factors of breast cancer, such as BMI. Age at the time of the disease was alsocorrelated with the relative expression of c-myc and estradiol (p &lt; 0.0007 and p &lt; 0.000001). The correlation coefficient (R = 0.462) shows a positive relationship between estradiol bound ER, ER, and c-myc. Docking energy &minus;229 kJ/mol suggests the binding affinity of estradiol bound ER binding to 500 bp upstream of proximal promotor of c-myc at three distinct positions. The data presented in this study proposed that the expression of c-myc and estradiol are directly correlated in breast cancer. The prognostic utility of an induced level of c-myc associated with the normal status of the c-myc gene and estradiol for patients with metastatic carcinoma should be explored further

Making prescriptions "talk" to stroke and heart attack survivors to improve adherence: Results of a randomized clinical trial (The Talking Rx Study).

BACKGROUND:We developed and tested the effectiveness of a tailored health information technology driven intervention: "Talking Prescriptions" (Talking Rx) to improve medication adherence in a resource challenged environment. METHODS:We conducted a parallel, randomized, controlled, assessor-blinded trial at the Aga Khan University (AKU), Karachi, Pakistan. Adults with diagnosis of cerebrovascular accident (CVA) or coronary artery disease (CAD) diagnosed least one month before enrollment, on anti-platelets and statins, with access to a mobile phone were enrolled. The intervention group received a) Daily Interactive Voice Response (IVR) call services regarding specific statin and antiplatelet b) Daily tailored medication reminders for statin and antiplatelet and c) Weekly lifestyle modification messages for a period of 3 months. We assessed Medication adherence to statin and antiplatelets by a validated version of the 8-item Morisky Medication Adherence scale 8 (MMAS-8) at 3 months by a blinded assessment officer. Analysis was conducted by intention-to-treat principle (ITT). RESULTS:Between April 2015 and December 2015, 197 participants (99 in intervention and 98 in the usual care group) enrolled in the Talking Rx Study. The dropout rate was 9.6%. Baseline group characteristics were similar. At baseline, the mean MMAS-8 was 6.68 (SD = 1.28) in the intervention group and 6.77 (SD = 1.36) in usual care group. At end of follow-up, the mean MMAS-8 increased to 7.41(0.78) in the intervention group compared with 7.38 (0.99) in usual care group with mean difference of 0.03 (S.D 0.13) (95% C.I [-0.23, 0.29]), which was not statistically significant. (P-Value = 0.40) CVA patients showed a relatively greater magnitude of adherence via the MMAS-8 at the end of follow up where the mean MMAS-8 increased to 7.29 (S.D 0.82) in the intervention group as compared to 7.07(S.D 1.24) in usual care group with mean difference of 0.22 (SD = 0.22) 95% C.I (-0.20, 0.65) with (P-value = 0.15). Around 84% of those on intervention arm used the service, calling at least 3 times and listening to their prescriptions for an average of 8 minutes. No user was excluded due to technologic reasons. CONCLUSION:The use of a phone based medication adherence program was feasible in LMIC settings with high volume clinics and low patient literacy. In this early study, with limited follow up, the program did not achieve any statistically significant differences in adherence behavior as self-reported by the MMAS-8 Scale. TRIAL REGISTRATION:Clinical Trials.gov NCT02354040

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population