Organic fragments newly released from heat-treated peat soils create synergies with dissolved organic carbon to enhance Cr(VI) removal.

Surface fires occur naturally or anthropogenically and can raise the temperature at the soil surface up to 600 °C. The heat derived from the surface fire can be subsequently transferred into CO2-enriched subsoils. As a result, the chemical compositions of soil organic matter (SOM) may be altered in fire-impacted anaerobic environments, indirectly influencing the redox transformations of pollutants, such as Cr(VI). In this study, a peat soil was heated up to 600 °C with limited air flow to simulate the effects of heat on the SOM during surface fire events. Then, Cr(VI) removal, including reduction and sorption, by the heat-treated peat soils was determined in relation to changes in the soil organic components. The results showed that the amount of O-containing functional groups, -CH2/-CH3 units of aliphatic groups, and dissolved organic carbon (DOC) in the SOM gradually decreased with an increase in the heating temperature. The removal of 0.1932 mM Cr(VI) did not exhibit a consistent decline along with the changes in these soil components. The heating temperatures of 200 and 250 °C were the thresholds that led to the decomposition of temperature-sensitive soil organic components such as lignin and other labile SOM. Such newly released organic fragments synergized lignin-like substances and carboxyl groups, resulting in up to 99% removal of the initially added Cr(VI). As the heating temperatures were increased from 300 to 600 °C, Cr(VI) reduction decreased from 66% to 20%. The black carbon-like materials and/or aromatic-containing moieties were the major components responsible for Cr(VI) reduction in 600°C-treated peat soils.

Accumulation and bio-oxidation of arsenite mediated by thermoacidophilic Cyanidiales: innate potential biomaterials toward arsenic remediation.

Addressing geogenic and anthropogenic arsenic (As) pollution is critical for environmental health. This study explored arsenite [As(III)] removal using Cyanidiales, particularly Cyanidium caldarium (Cc) and Galdieria partita (Gp), under acidic to neutral pH, and determined As(III) detoxification mechanisms in relation to As speciation and protein secondary structure in Cyanidiales. Regarding As(III) sorption amounts, Cc outperformed Gp, reaching 83.2 mg g-1 of removal at pH 5.0. Wherein, 23.5 % of sorbed As on Cc presented as arsenate [As(V)] complexation with polysaccharides, alongside other predominant species including As(III)-cysteine (41.2 %) and As(III)-polysaccharides (35.3 %) complexes. This suggested that As(III) was directly transported into cells, rather than As(V). Coupled with the formation of As(III)-cysteine complexes within cells, these mechanisms may be key to efficiently accumulating As(III) in Cyanidiales during the 6-h incubation. These results highlight the potential of Cyanidiales for sustainable As(III) remediation and provide new insights into managing As(III) toxicity.

Prediction of Mandibular Advancement Device Response Using CPAP Pressure in Different Polysomnographic Phenotypes.

Objective: Both continuous positive airway pressure (CPAP) pressure and polysomnographic phenotypes have been associated with mandibular advancement device (MAD) treatment response, but the precise relationship has not been fully elucidated. We hypothesized that utilizing CPAP pressure would predict the MAD response in treatment-naïve patients with moderate-severe obstructive sleep apnea (OSA), and the MAD response would be associated with two polysomnographic phenotypes, including sleep stage dependency and positional dependency. Methods: OSA treatment-naïve patients with an apnea-hypopnea index (AHI) ≥15/h who declined CPAP treatment and received MAD treatment for 3-6 months were enrolled. The MAD treatment response was defined as 1) residual AHI under MAD (AHIMAD) <5/h and 2) AHIMAD <10/h. Logistic regression was applied to identify the association between CPAP pressure and MAD treatment responders. The predictability of the MAD responder status utilizing CPAP pressure was assessed with the area under the receiver operating characteristic (AUROC). Results: A total of 128 enrolled patients (AHI ≥30/h in 74.2%) were recruited, of whom 119 patients and 80 patients were included for analysis of sleep stage and positional dependency, respectively. REM-predominant OSA had lower AHI than stage-independent OSA, while the supine-predominant phenotype had lower anthropometrics than the nonpositional-dependent phenotype. The response rates for AHIMAD <5/h and AHIMAD <10/h were 25.8% and 48.4%, respectively. Lower anthropometrics, baseline AHI, and supine predominance were associated with the responder status, while CPAP pressure was an independent predictor. The AUROCs for the prediction of AHIMAD <5/h and AHIMAD <10/h responders were 0.635 and 0.664, respectively. Utilizing a CPAP level >14 cmH2O as the cutoff to predict criterion 1 and 2 nonresponders, the sensitivity was 93.9% and 95.2%, respectively. Conclusion: In treatment-naïve patients with moderate-severe OSA, the supine-predominant phenotype and lower CPAP pressure were associated with the MAD response, while the sleep stage dependency phenotype was not. Utilization of a CPAP level >14 cmH2O could be a sensitive measure to identify nonresponders.

Association between periodontal disease and osteoporosis in postmenopausal women: a protocol for systematic review and meta-analysis.

INTRODUCTION: Periodontal disease and osteoporosis are common chronic diseases, especially for the postmenopausal women. Several original studies explore the association, but there still controversial. Therefore, we will conduct this systematic review and meta-analysis to assess the association between periodontal disease and osteoporosis in postmenopausal women. METHODS AND ANALYSIS: This study adheres to the Preferred Reporting Items for Systematic Reviews and Meta-analyses for Protocols. We will systematically search Medline/PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science and Scopus from inception to August 2021 to collect all relevant publications, with no restrictions on publication date or languages. Study selection, data extraction and risk of bias assessment will be conducted independently by two trained reviewers independently. The Cochrane's tool for assessing risk of bias, Newcastle-Ottawa Scale and Agency for Healthcare Research and Quality will be used for the risk of bias assessment. OR, HR and risk ratio with 95% CI were considered as the effect size for dichotomous outcomes, weighted mean difference with 95% CI were calculated as the effect size for continuous outcomes. Random-effects models will be used. Heterogeneity between studies will be assessed via the forest plot and I². Publication bias will detected by funnel plots, Begg's test and Egger's test. The subgroup analyses and sensitivity ananlyses will also be used to explore and interpret the heterogeneity. ETHICS AND DISSEMINATION: This study does not require ethical approval. We will disseminate our findings by publishing results in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42021225746.

Termite Pest Identification Method Based on Deep Convolution Neural Networks.

Several species of drywood termites, subterranean termites, and fungus-growing termites cause extensive economic losses annually worldwide. Because no universal method is available for controlling all termites, correct species identification is crucial for termite management. Despite deep neural network technologies' promising performance in pest recognition, a method for automatic termite recognition remains lacking. To develop an automated deep learning classifier for termite image recognition suitable for mobile applications, we used smartphones to acquire 18,000 original images each of four termite pest species: Kalotermitidae: Cryptotermes domesticus (Haviland); Rhinotermitidae: Coptotermes formosanus Shiraki and Reticulitermes flaviceps (Oshima); and Termitidae: Odontotermes formosanus (Shiraki). Each original image included multiple individuals, and we applied five image segmentation techniques for capturing individual termites. We used 24,000 individual-termite images (4 species × 2 castes × 3 groups × 1,000 images) for model development and testing. We implemented a termite classification system by using a deep learning-based model, MobileNetV2. Our models achieved high accuracy scores of 0.947, 0.946, and 0.929 for identifying soldiers, workers, and both castes, respectively, which is not significantly different from human expert performance. We further applied image augmentation techniques, including geometrical transformations and intensity transformations, to individual-termite images. The results revealed that the same classification accuracy can be achieved by using 1,000 augmented images derived from only 200 individual-termite images, thus facilitating further model development on the basis of many fewer original images. Our image-based identification system can enable the selection of termite control tools for pest management professionals or homeowners.

Efficacy and safety of pilocarpine for radiation-induced xerostomia in patients with head and neck cancer: A systematic review and meta-analysis.

BACKGROUND: Pilocarpine has been used widely in the treatment of dry mouth and glaucoma. In this review, the authors assessed the efficacy and safety of pilocarpine for patients with head and neck cancer who have radiation-induced xerostomia. TYPES OF STUDIES REVIEWED: The authors conducted a systematic search including meta-analyses and randomized controlled trials in the following databases: MEDLINE, Embase, Cochrane Library, and Science Citation Index Expanded. The primary outcome was the severity of xerostomia (measured using visual analog scale [VAS] scores). Adverse events were other outcomes of interest. The authors performed meta-analyses where appropriate. The authors used the Cochrane Collaboration's tool for assessing risk of bias to assess the quality of the study. RESULTS: The authors identified 6 studies (including 752 patients in total). The results of a meta-analysis of 3 articles showed that pilocarpine was associated with a 12-point increase in VAS score (mean difference, 12.00; 95% confidence interval [CI], 1.93-22.08; P = .02) and higher rates of adverse events compared with placebo in terms of sweating (odds ratio [OR], 3.71; 95% CI, 2.34-5.86; P < .00001). There were no differences in rhinitis (OR, 1.21; 95% CI, 0.68-2.16; P = .52) and nausea (OR, 1.44; 95% CI, 0.83-2.49; P = .19). CONCLUSIONS AND PRACTICAL IMPLICATIONS: On the basis of the best available evidence, the results of this meta-analysis provide evidence that pilocarpine offers statistically significant clinical benefits for the symptomatic treatment of radiation-induced xerostomia in patients with head and neck cancer. However, the authors of this systematic review found the best available evidence in the meta-analysis in 3 studies, 1 of which showed no effect. The authors of this systematic review suggest that these patients take 5 milligrams of pilocarpine 3 times daily, and that there is need for further study.