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Green, efficient, and cost-effective soil leaching technologies have emerged as an innovative strategy for remediating heavy metal-contaminated soils. In this study, we proposed NH4HSO4 and KHSO4 as novel eluents for removing heavy metals from contaminated soils and investigated the effects of various factors, including leaching temperature, liquid to solid ratio (L/S), time, and molar concentration ratio, on their efficacy. We also examined the mineral contents and structural properties of the contaminated soil before and after leaching using the novel eluents via scanning electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction spectroscopy, and Fourier transform infrared spectroscopy. The results indicated that the leaching rates of Zn, Pb, and Cd using NH4HSO4 and KHSO4 (25 °C, 360 min, L/S = 20, and 0.075 mol/L) were 86.17%, 45.97%, and 79.92% and 89.12%, 46.185%, and 84.32%, respectively. Furthermore, these eluents improved the quality of the treated soil by slightly increasing its N and K contents without altering its structure. The leaching rates of Zn in the exchangeable and acid-soluble, reducible, and oxidizable forms by KHSO4 were best fitted by the Avrami–Erofeev equation, diffusion via the product layer, and the new shrinking core model, respectively. The heavy metal proportion in the oxidizable and residual fraction increased after leaching. Based on these findings, NH4HSO4 and KHSO4 show promise as effective agents for the rapid, efficient, cost effective, and sustainable remediation of heavy metal-polluted soils. [ABSTRACT FROM AUTHOR]

Background: Granulomatous mastitis (GM) is a benign, chronic, inflammatory disease lacking clear treatment guidelines. The purpose of this American Society of Breast Surgeons (ASBrS) prospective, multisite registry was to characterize the presentation of GM and identify treatment strategies associated with symptom resolution and optimal cosmesis. Methods: ASBrS members entered data into a registry on patient demographics, treatment, symptoms, and cosmesis over a 1-year period. Initial symptoms were graded as mild, moderate, or severe. The Chi-square test and logistic regression were used to identify factors related to symptom improvement and cosmesis. Results: Overall, 112 patients with a mean age of 36 years were included. More patients were Hispanic (49.1%) and from the Southwest (41.1%), and management included observation (4.5%), medical (70.5%), surgical (5.4%), or combination treatment (19.6%). Immunosuppression was used in 83 patients (74.1%), including 43 patients who received intralesional steroid injections. Patients with severe symptoms were more likely to undergo surgical intervention compared with those with mild or moderate symptoms (21.4% vs. 0% and 7.5%, respectively; p = 0.004). Within 1 year, 85 patients (75.9%) experienced symptom improvement and/or resolution at a median of 3 months. Receipt of immunosuppressive therapy was predictive of improvement or resolution at 1 month (odds ratio 4.22; p = 0.045). One-year physician-assessed cosmesis was excellent or good for 20/35 patients (57.1%) and was not associated with type of treatment or symptom severity. Conclusion: Although GM can have a protracted course, the majority of patients in this registry resolved within 1 year, with good cosmetic result. Treatment with immunosuppression appears to be most beneficial, and a symptom-based algorithm may be helpful to guide treatment. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, wastewater surveillance of the SARS CoV-2 virus has been demonstrated to be effective for population surveillance at the county level down to the building level. At the University of California, San Diego, daily high-resolution wastewater surveillance conducted at the building level is being used to identify potential undiagnosed infections and trigger notification of residents and responsive testing, but the optimal determinants for notifications are unknown. To fill this gap, we propose a pipeline for data processing and identifying features of a series of wastewater test results that can predict the presence of COVID-19 in residences associated with the test sites. Using time series of wastewater results and individual testing results during periods of routine asymptomatic testing among UCSD students from 11/2020 to 11/2021, we develop hierarchical classification/decision tree models to select the most informative wastewater features (patterns of results) which predict individual infections. We find that the best predictor of positive individual level tests in residence buildings is whether or not the wastewater samples were positive in at least 3 of the past 7 days. We also demonstrate that the tree models outperform a wide range of other statistical and machine models in predicting the individual COVID-19 infections while preserving interpretability. Results of this study have been used to refine campus-wide guidelines and email notification systems to alert residents of potential infections. [ABSTRACT FROM AUTHOR]

Accelerometers are widely used for tracking human movement and provide minute-level (or even 30 Hz level) physical activity (PA) records for detailed analysis. Instead of using day-level summary statistics to assess these densely sampled inputs, we implement functional principal component analysis (FPCA) approaches to study the temporal patterns of PA data from 245 overweight/obese women at three visits over a 1-year period. We apply longitudinal FPCA to decompose PA inputs, incorporating subject-specific variability, and then test the association between these patterns and obesity-related health outcomes by multiple mixed effect regression models. With the proposed methods, the longitudinal patterns in both densely sampled inputs and scalar outcomes are investigated and connected. The results show that the health outcomes are strongly associated with PA variation, in both subject and visit-level. In addition, we reveal that timing of PA during the day can impact changes in outcomes, a finding that would not be possible with day-level PA summaries. Thus, our findings imply that the use of longitudinal FPCA can elucidate temporal patterns of multiple levels of PA inputs. Furthermore, the exploration of the relationship between PA patterns and health outcomes can be useful for establishing weight-loss guidelines. [ABSTRACT FROM AUTHOR]

Pepsinogen I (PGI) can reflect the morphology and function of the gastric mucosa. Accordingly, the large-scale community health screening of PGI can dramatically increase the early diagnosis rate of gastric cancer. However, PGI testing can only be carried out in comprehensive hospitals and health examination centers. To ameliorate this issue, a point-of-care chemiluminescent immunoassay for PGI was developed in a fully automated miniaturized instrument. This instrument was especially developed for health check-ups in the grassroots communities; its volume of which is only 0.18 m3. Critically, the entire detection process for a single sample only requires 20 min, and the samples can be loaded continuously, making the method suitable for high-throughput analysis. The assay displayed an excellent detection limit of 0.048 ng/mL with a broad detection range of 0–200 ng/mL. Furthermore, this assay exhibited high sensitivity and specificity, had low intra- and inter-assay coefficients of variation (<10%), and was not affected after storage at 37 °C for 7 days. The assay was used to detect PGI in 95 clinical serum samples, and the results were highly correlated with those that were clinically tested (correlation coefficient, R2 = 0.998). Hence, the method established in this work has great application value and can be broadly applied for the large-scale screening of gastric cancer in resource-limited areas. [ABSTRACT FROM AUTHOR]

This investigation was made to examine how the conditions of hydrothermal synthesis influence the crystal structure of xonotlite and its morphology. For synthesis, we used acid residues after extracting the alumina from circulating fluidized bed fly ash as raw material, as far as we know, that no one used before. Staring with Ca/Si = 1, hydrothermal temperatures were between 180 and 260 °C. The samples were characterized in terms of mineralogical composition (XRD), morphological analysis (SEM), and thermal gravimetric and differential thermal analyses. During the 72 h synthesis at 240 °C, well formed xonotlite fibers of 10-15 μm long were obtained. Under the same conditions, but at 200 °C, the obtained xonotlite was poorly formed. The results indicated that the residue could be used to prepare pure xonotlite. Different hydrothermal temperatures and holding times have a great impact on crystallinity and morphology of xonotlite. [ABSTRACT FROM AUTHOR]

The extraction of alumina from coal fly ash (CFA) is a good way to enhance its value-added utilization. The presence of inert matter with a high degree of polymerization, such as mullite and other aluminosilicates, greatly restricts the reactivity of CFA. Thus, the CFA needs to be activated before use. Thermal activation by calcination with added sodium hydrogen sulfate (NaHSO4) was carried out in this study. The calcination products were characterized by means of X-ray diffraction, thermal gravimetric and differential scanning calorimetric analysis, and scanning electron microscopy to assess the effects of the additive, calcining temperature, and calcining time on the products. The results indicated that NaHSO4 facilitated the decomposition of the polymeric phases and significantly improved the alumina extraction. Alumina in CFA was transformed into soluble Na3Al(SO4)3. When CFA was mixed with sodium hydrogen sulfate at a NaHSO4/Al2O3 molar ratio of 6, the alumina extraction reached 90 % at 500 °C after 2 h. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: [ABSTRACT FROM AUTHOR]