Tag: nevin manimala

Sci Total Environ. 2021 Aug 21;801:149797. doi: 10.1016/j.scitotenv.2021.149797. Online ahead of print.

ABSTRACT

Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatially and temporally. The problem becomes more complex as drought occurrence is dependent on a multitude of factors ranging from hydro-meteorological to climatic variables. A paradigm shift happened in this field when it was found that the inclusion of climatic variables in the data-driven prediction model improves the accuracy. However, this understanding has been primarily using statistical metrics used to measure the model accuracy. The present work tries to explore this finding using an explainable artificial intelligence (XAI) model. The explainable deep learning model development and comparative analysis were performed using known understandings drawn from physical-based models. The work also tries to explore how the model achieves specific results at different spatio-temporal intervals, enabling us to understand the local interactions among the predictors for different drought conditions and drought periods. The drought index used in the study is Standard Precipitation Index (SPI) at 12 month scales applied for five different regions in New South Wales, Australia, with the explainable algorithm being SHapley Additive exPlanations (SHAP). The conclusions drawn from SHAP plots depict the importance of climatic variables at a monthly scale and varying ranges of annual scale. We observe that the results obtained from SHAP align with the physical model interpretations, thus suggesting the need to add climatic variables as predictors in the prediction model.

PMID:34467917 | DOI:10.1016/j.scitotenv.2021.149797

Eur J Obstet Gynecol Reprod Biol. 2021 Aug 9;265:74-79. doi: 10.1016/j.ejogrb.2021.08.010. Online ahead of print.

ABSTRACT

OBJECTIVE: Uterine smooth muscle tumors of uncertain malignant potential (STUMP) is a heterogeneous group of tumors with histological and biological diversity that cannot be defined as a benign leiomyoma or malignant leiomyosarcoma. The study aims to investigate the diagnostic methods, treatment management and prognosis of STUMP patients in a 13-year period.

STUDY DESIGN: We retrospectively reviewed the clinicopathologic information of 31 STUMP patients in Peking University People’s Hospital. Statistical analyses were conducted to compare the difference of clinical characteristics between the women in myomectomy group and those in hysterectomy group.

RESULTS: The most common clinical presentation was menstrual disorder. The tumors were mainly manifested as hypoechoic, non-cystic nodules with low blood flow signal by pelvic doppler ultrasonography. Most tumors carried Ki-67 index ranging from 10% to 30%. Immunohistochemical markers such as ER, PR, p16 and Desmin was positively expressed in tumors. At the first operation, 21 cases underwent myomectomy and 10 cases underwent hysterectomy. The patients in myomectomy group were younger than those in hysterectomy group. In the follow-up period, two cases experienced a relapse in the form of STUMP within 36 months. One case died of cardiovascular accident while the other cases were alive. Six of 21 women in myomectomy group desired pregnancy and two healthy live births were recorded.

CONCLUSION: The diagnosis of STUMP primarily depends on histopathologic features. Fertility-sparing surgery may be a treatment selection for patients with fertility desire. Patients with STUMP, especially in the case of myomectomy, should be informed of recurrence risk and monitored closely.

PMID:34467879 | DOI:10.1016/j.ejogrb.2021.08.010

Sci Total Environ. 2021 Aug 18;801:149693. doi: 10.1016/j.scitotenv.2021.149693. Online ahead of print.

ABSTRACT

Appropriate produced water (PW) management is critical for oil and gas industry. Understanding PW quantity and quality trends for one well or all similar wells in one region would significantly assist operators, regulators, and water treatment/disposal companies in optimizing PW management. In this research, historical PW quantity and quality data in the New Mexico portion (NM) of the Permian Basin from 1995 to 2019 was collected, pre-processed, and analyzed to understand the distribution, trend and characteristics of PW production for potential beneficial use. Various machine learning algorithms were applied to predict PW quantity for different types of oil and gas wells. Both linear and non-linear regression approaches were used to conduct the analysis. The prediction results from five-fold cross-validation showed that the Random Forest Regression model reported high prediction accuracy. The AutoRegressive Integrated Moving Average model showed good results for predicting PW volume in time series. The water quality analysis results showed that the PW samples from the Delaware and Artesia Formations (mostly from conventional wells) had the highest and the lowest average total dissolved solids concentrations of 194,535 mg/L and 100,036 mg/L, respectively. This study is the first research that comprehensively analyzed and predicted PW quantity and quality in the NM-Permian Basin. The results can be used to develop a geospatial metrics analysis or facilitate system modeling to identify the potential opportunities and challenges of PW management alternatives within and outside oil and gas industry. The machine learning techniques developed in this study are generic and can be applied to other basins to predict PW quantity and quality.

PMID:34467907 | DOI:10.1016/j.scitotenv.2021.149693

Pediatr Dent. 2021 Jul 15;43(4):276-281.

ABSTRACT

Purpose: Childhood caries is a highly prevalent disease that is intricately connected to diet and other social and behavioral factors. While it has been established that breastfeeding confers many health benefits for children, previous research found no consensus on the relationship between breastfeeding and caries. The purpose of this study was to examine the relationship between early childhood caries (ECC) and the length of time breastfeeding using the National Health and Nutrition Examination Survey (NHANES). Methods: Four cycles of NHANES (2011 to 2018) were analyzed, including 3,234 children ages two to five years. The association between breastfeeding duration and incidence of ECC and severe earlychildhood caries (S-ECC) was evaluated using logistic regression, adjusting for age, ethnicity, education, income, last dental visit, and sugar-sweetened beverages. Results: In the study population, 16.9 percent had ECC and 12.2 percent had S-ECC. Breastfeeding six months to one year, one to two years, or over two years was not associated with higher odds of ECC or S-ECC than breastfeeding for zero to six months after adjusting for covariates. Conclusions: There was no statistically significant relationship between breastfeeding and early childhood caries, and breastfeeding duration was not associated with increased caries risk. More research from well-controlled analytical studies is needed to establish or refute a relationship between breastfeeding and ECC.

PMID:34467843

Pediatr Dent. 2021 Jul 15;43(4):290-295.

ABSTRACT

Purpose: The purpose of this study was to evaluate the treatment outcomes of multisurface caries in primary molars treated with intracoronal restorations versus stainless steel crowns (SSCs) through a retrospective split-mouth study. Methods: Dental records were screened for patients who had treatment of one primary molar with a multisurface restoration and one primary molar with an SSC. Teeth were followed until a loss to follow-up, exfoliation, or failure. Results: A total of 988 primary molars were evaluated, with a mean follow-up time of 22 months. The survival probabilities for: SSCs were 95.5 percent at one year of service and 92.8 percent at two years of service; and for intracoronal restorations were 92.0 percent at one year of service and 80.0 percent at two years of service. Overall survival analysis showed SSCs to be significantly more successful than restorations (P<0.001), particularly in children treated at ages four years and younger (P<0.001). No statistically significant difference (P=0.10) was found for children treated at ages five years and older. Conclusions: Stainless steel crowns have a higher survival probability versus restorations for multisurface caries. In children ages four years and younger, more aggressive treatment of multi-surface caries with SSCs should be considered, as conservative treatment leads to an increased need for retreatment.

PMID:34467846

J Environ Manage. 2021 Aug 28;299:113594. doi: 10.1016/j.jenvman.2021.113594. Online ahead of print.

ABSTRACT

Nowadays, releasing the Emerging Pollutants (EPs) in the nature is one of the main reasons for many health and environmental disasters. Amoxicillin as an antibiotic is one of the EPs and categorized as the Endocrine Disrupting Compounds (EDCs) in hazardous materials. Accumulation of amoxicillin in the soil bulk increases the cancer risk, drug resistances and other epidemiological diseases. Hence, the soil bioremediation of antibiotics can be a solution for this problem which is more environmental-friendly system. This study technically creates a bio-engine setup in soil bulk for remediation of amoxicillin based on Aspergillus Flavus (AF) activities and Removal Percentage (RP) of amoxicillin with Aflatoxin B1 Generation (AG) controls. The main novelty is to propose a hybrid computational intelligence approach to do optimization for mechanical and biological aspects and to predict the behavior of bio-engine’s effective mechanical and biological features in an intelligent way. The optimization model is formulated by the Central Composite Design (CCD) which is set by the Response Surface Methodology (RSM). The prediction model is formulated by the Random Forest (RF), Adaptive Neuro Fuzzy Inference System (ANFIS) and Random Tree (RT) algorithms. According to the experimental practices from real soil samples in different times and places, concentration of amoxicillin and Aflatoxin B1 are set equal to 25 mg/L (ppm) and 15 μg/L (ppb). Likewise, the outcomes of experiments in CCD-RSM computations are evaluated by curve fitting comparisons between linear, 2FI, quadratic and cubic polynomial equations with considering to regression coefficient and predicted regression coefficient values, ANOVA and optimization by sequential differentiation. Based on the results of CCD-RSM, the RP performance in the optimum conditions is measured around 86% and in 25 days after runtime, the RP and AG are balanced in the safe mode. The proposed hybrid model achieves the 0.99 accuracy. The applicability of the research is done using real field evaluations from drug industrial park in Mashhad city in Iran. Finally, a broad analysis is done and managerial insights are concluded. The main findings of the present research are: (I) with application of bioremediation from fungus activities, amoxicillin amounts can be control in soil resources with minimum AG, (II) ANFIS model has the best accuracy for smart monitoring of amoxicillin bioremediation in soil environments and (III) based on the statistical assessments Aeration Intensity and AF/Biological Waste ratio are most effective on the amoxicillin removal percentage.

PMID:34467868 | DOI:10.1016/j.jenvman.2021.113594

Pediatr Dent. 2021 Jul 15;43(4):270-275.

ABSTRACT

Purpose: The purpose of this study was to evaluate the prevalence, severity, and distribution of molar incisor hypomineralization (MIH) and its association with socioeconomic characteristics among eight-year-old students from public schools in Petrópolis, Rio de Janeiro, Brazil. Methods: This cross-sectional study evaluated 450 eight-year-old Brazilian children. A questionnaire was used to assess socioeconomic factors (family income, maternal education, and person per household). MIH was diagnosed based on European Academy of Paediatric Dentistry criteria. The severity of MIH was evaluated at patient and tooth levels. The examinations were conducted in school environments. Descriptive analysis, chi-square, Fisher’s exact, and Kruskal-Wallis tests were performed. Results: The prevalence of MIH was 28.7 percent. The average of affected molars and incisors was 2.25 (standard deviation [SD] equals 1.03) and 0.84 (1.22 SD). The maxillary molars were the most affected, but mandibular molars showed greater severity. The majority of MIH-children had white-creamy opacities (51.9 percent). There was no association between MIH and socioeconomic factors. MIH was more prevalent in boys (P=0.025). The number of incisors with MIH rose with the increasing number of affected molars (P=0.02). A significant association between severity and the mean number of affected molars was observed (P=0.004). Conclusions: The prevalence of molar incisor hypomineralization was 28.7 percent. MIH severity at the individual level was significantly associated with the number of affected teeth and the occurrence of affected incisors.

PMID:34467841

Urol Oncol. 2021 Aug 28:S1078-1439(21)00366-5. doi: 10.1016/j.urolonc.2021.08.007. Online ahead of print.

ABSTRACT

PURPOSE: Robust prediction of progression on active surveillance (AS) for prostate cancer can allow for risk-adapted protocols. To date, models predicting progression on AS have invariably used traditional statistical approaches. We sought to evaluate whether a machine learning (ML) approach could improve prediction of progression on AS.

PATIENTS AND METHODS: We performed a retrospective cohort study of patients diagnosed with very-low or low-risk prostate cancer between 1997 and 2016 and managed with AS at our institution. In the training set, we trained a traditional logistic regression (T-LR) classifier, and alternate ML classifiers (support vector machine, random forest, a fully connected artificial neural network, and ML-LR) to predict grade-progression. We evaluated model performance in the test set. The primary performance metric was the F1 score.

RESULTS: Our cohort included 790 patients. With a median follow-up of 6.29 years, 234 developed grade-progression. In descending order, the F1 scores were: support vector machine 0.586 (95% CI 0.579 – 0.591), ML-LR 0.522 (95% CI 0.513 – 0.526), artificial neural network 0.392 (95% CI 0.379 – 0.396), random forest 0.376 (95% CI 0.364 – 0.380), and T-LR 0.182 (95% CI 0.151 – 0.185). All alternate ML models had a significantly higher F1 score than the T-LR model (all p <0.001).

CONCLUSION: In our study, ML methods significantly outperformed T-LR in predicting progression on AS for prostate cancer. While our specific models require further validation, we anticipate that a ML approach will help produce robust prediction models that will facilitate individualized risk-stratification in prostate cancer AS.

PMID:34465541 | DOI:10.1016/j.urolonc.2021.08.007

Semergen. 2021 Aug 29:S1138-3593(21)00226-4. doi: 10.1016/j.semerg.2021.07.010. Online ahead of print.

ABSTRACT

OBJECTIVES: To evaluate the adequacy of vitamin D treatment based on clinic evidence in a Primary Care Center as well as to analyze some characteristics of the prescriptions made.

MATERIALS AND METHODS: Descriptive cross-sectional study. Primary Care. Patients above 14 years old with vitamin D prescription. Main variable was the therapeutic adequacy with vitamin D compounds (adequacy was considered when there was a clinical indication for treatment and blood vitamin D levels below 20ng/ml). Other clinical variables were collected. Frequency and association measures were used for statistical analysis. Level of statistical significance was considered <0.05.

RESULTS: 430 patients, 346 women (80.5%, 95% CI=77-84). Record of vitamin D values in 216 (50.2%, 95% CI=45-55). Screening/treatment indications in 219 patients (50.9%, 95% CI=46-56), of those in 150 patients vitamin D values were recorded (68.5%, 95% CI=62-75), average (±SD) was 21.22±12ng/ml, deficiency criteria in 86 (57.3%, 95% CI=51-64), insufficiency in 37 (24.7%, 95% CI=19-30) and sufficiency in 27 (18%, 95% CI=13-23). 86 patients (20%, 95% CI=16-24) had treatment indications plus vitamin D deficiency with no differences between genders.

CONCLUSIONS: Only 20% of the patients had treatment indications plus vitamin D deficiency. Female predominance. Just over half had indications for screening of serological vitamin D values and/or indications for treatment with vitamin D compounds.

PMID:34465546 | DOI:10.1016/j.semerg.2021.07.010

Cytotherapy. 2021 Aug 28:S1465-3249(21)00745-3. doi: 10.1016/j.jcyt.2021.07.010. Online ahead of print.

ABSTRACT

BACKGROUND AIMS: The high genetic diversity of HLA across populations significantly confines the effectiveness of a donor or umbilical cord blood search for allogeneic hematopoietic stem cell transplantation (HSCT). This study aims to probe the HLA immunogenetic profile of the population of Crete, a Greek region with specific geographic and historical characteristics, and to investigate potential patterns in HLA distribution following comparison with the Deutsche Knochenmarkspenderdatei (DKMS) donor registry. It also aims to highlight the importance of regional public cord blood banks (PCBBs) in fulfilling HSCT needs, especially in countries with significant genetic diversity.

METHODS: A cohort of 1835 samples representative of the Cretan population was typed for HLA class I (HLA-A, HLA-B, HLA-C) and class II (HLA-DRB1, HLA-DQB1, HLA-DPB1) loci by high-resolution second field next-generation sequencing. Data were compared with the respective HLA profiles of 12 DKMS populations (n = 20 032). Advanced statistical and bioinformatics methods were employed to assess specific intra- and inter-population genetic indexes associated with the regional and geographic distribution of HLA alleles and haplotypes.

RESULTS: A considerable HLA allelic and haplotypic diversity was identified among the Cretan samples and between the latter and the pooled DKMS cohort. Even though the HLA allele and haplotype frequency distribution was similar to regions of close geographic proximity to Crete, a clinal distribution pattern from the northern to southern regions was identified. Significant differences were also observed between Crete and the Greek population of DKMS.

CONCLUSIONS: This study provides an in-depth characterization of the HLA immunogenetic profile in Crete and reveals the importance of demographic history in HLA heterogeneity and donor selection. The novel HLA allele and haplotype frequency comparative data between the Cretan and other European populations signify the importance of regional PCBBs in prioritizing HLA diversity to efficiently promote the HSCT program at the national level and beyond.

PMID:34465516 | DOI:10.1016/j.jcyt.2021.07.010