Background. Serum uric acid (SUA) was closely related to body metabolism. This study aimed to investigate the relationship between the adult weight-adjusted waist index (WWI) and SUA. Methods. In the ...National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020, 6494 eligible participants aged ≥20 were included. The multivariate logistic regression model was used to test the correlation between WWI and SUA. At the same time, subgroup analysis was carried out by using multivariate logistic regression according to age, sex, and race. Then, the fitting smooth curve was applied to solve the association between WWI and SUA. Finally, the recursive algorithm was used to calculate the inflection point in the nonlinear relationship, and the two-stage piecewise linear regression model was used to analyze the relationship between WWI and SUA on both sides of the inflection point. Results. In all the 6494 participants, through the fully adjusted model, this study found that there was a positive correlation between WWI and SUA (β = 5.64; 95% CI: 2.62 and 8.66). In addition, this positive correlation still had certain statistical significance in the subgroup analysis stratified by sex, age, and race. Our research team found a significant positive correlation between the WWI and SUA in females, but the correlation was not significant in males. We also found a small inverted U-shaped curve between the WWI and SUA in men when we stratified the sex subgroups. The small inflection point was determined to be 11.5 cm/√ kg. In racial subgroup analysis, we also found a U-shaped relationship between the WWI and SUA in non-Hispanic White and other race/ethnicity (the inflection point was 11.08 cm/√ kg and 12.14 cm/√ kg, respectively). Conclusion. This study showed that the WWI was a newly developed and new predictor of centripetal obesity independent of body weight and there was a positive correlation between the WWI and SUA.
In most deep learning-based brain tumor segmentation methods, training the deep network requires annotated tumor areas. However, accurate tumor annotation puts high demands on medical personnel. The ...aim of this study is to train a deep network for segmentation by using ellipse box areas surrounding the tumors. In the proposed method, the deep network is trained by using a large number of unannotated tumor images with foreground (FG) and background (BG) ellipse box areas surrounding the tumor and background, and a small number of patients (<20) with annotated tumors. The training is conducted by initial training on two ellipse boxes on unannotated MRIs, followed by refined training on a small number of annotated MRIs. We use a multi-stream U-Net for conducting our experiments, which is an extension of the conventional U-Net. This enables the use of complementary information from multi-modality (e.g., T1, T1ce, T2, and FLAIR) MRIs. To test the feasibility of the proposed approach, experiments and evaluation were conducted on two datasets for glioma segmentation. Segmentation performance on the test sets is then compared with those used on the same network but trained entirely by annotated MRIs. Our experiments show that the proposed method has obtained good tumor segmentation results on the test sets, wherein the dice score on tumor areas is (0.8407, 0.9104), and segmentation accuracy on tumor areas is (83.88%, 88.47%) for the MICCAI BraTS’17 and US datasets, respectively. Comparing the segmented results by using the network trained by all annotated tumors, the drop in the segmentation performance from the proposed approach is (0.0594, 0.0159) in the dice score, and (8.78%, 2.61%) in segmented tumor accuracy for MICCAI and US test sets, which is relatively small. Our case studies have demonstrated that training the network for segmentation by using ellipse box areas in place of all annotated tumors is feasible, and can be considered as an alternative, which is a trade-off between saving medical experts’ time annotating tumors and a small drop in segmentation performance.
With the rapid development of the mining industry, the pollution of heavy metal(loid)s in soils near copper (Cu) mining sites is a significant concern worldwide. However, the pollution status and ...probabilistic health risks of heavy metal(loid)s of soils associated with Cu mines, have rarely been studied on a global scale. In this study, eight heavy metal(loid) concentrations in soil samples taken near 102 Cu mining sites worldwide were obtained through a literature review. Based on this database, the heavy metal(loid) pollution and ecological risk in soils near Cu mines were evaluated. Most of the study sites exceeded the moderately to heavily polluted levels of Cu and Cd; compared to other regions, higher pollution levels were observed at sites in Oman, China, Australia, and the United Kingdom. Soil pollution by Cd, Pb, and Zn at agricultural sites was higher than that in non-agricultural sites. In addition, these heavy metal(loid)s produced a high ecological risk to soils around Cu mining sites in which the contribution of Cd, Cu, and As reached up to 46.5%, 21.7%, and 18.4%, respectively. The mean hazard indices of the eight heavy metal(loid)s were 0.209 and 0.979 for adults and children, respectively. The Monte Carlo simulation further predicted that 1.40% and 29.9% of non-carcinogenic risk values for adults and children, respectively, exceeded the safe level of 1.0. Moreover, 84.5% and 91.0% of the total cancer risk values for adults and children, respectively, exceeded the threshold of 1E-04. Arsenic was the main contributor to non-carcinogenic risk, while Cu had the highest exceedance of carcinogenic risk. Our findings indicate that the control of Cu, Cd, and As should be prioritized because of their high incidence and significant risks in soils near Cu mines. These results provide valuable inputs for policymakers in designing effective strategies for reducing the exposure of heavy metal(loid)s in this area worldwide.
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•Global investigation of heavy metal(loid)s in soils near Cu mining sites was conducted.•Pollution posed by Cu and Cd of these examined sites is serious.•Health risks posed by As and Cu should merit more attention.•Cu, Cd, and As were identified as priority control pollutants for soil management.
Plant growth-promoting bacteria (PGPB) offer a promising solution for mitigating heavy metals (HMs) stress in crops, yet the mechanisms underlying the way they operate in the soil-plant system are ...not fully understood. We therefore conducted a meta-analysis with 2037 observations to quantitatively evaluate the effects and determinants of PGPB inoculation on crop growth and HMs accumulation in contaminated soils. We found that inoculation increased shoot and root biomass of all five crops (rice, maize, wheat, soybean, and sorghum) and decreased metal accumulation in rice and wheat shoots together with wheat roots. Key factors driving inoculation efficiency included soil organic matter (SOM) and the addition of exogenous fertilizers (N, P, and K). The phylum Proteobacteria was identified as the keystone taxa in effectively alleviating HMs stress in crops. More antioxidant enzyme activity, photosynthetic pigment, and nutrient absorption were induced by it. Overall, using PGPB inoculation improved the growth performance of all five crops, significantly increasing crop biomass in shoots, roots, and grains by 33 %, 35 %, and 20 %, respectively, while concurrently significantly decreasing heavy metal accumulation by 16 %, 9 %, and 37 %, respectively. These results are vital to grasping the benefits of PGPB and its future application in enhancing crop resistance to HMs.
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•The overall effects and determinants of PGPB inoculation on the crop growth and HMs accumulation were meta-analyzed.•Inoculation with PGPB reduced HMs bioavailability in contaminated soil by 10.5 %.•Soil organic matter (SOM) and exogenous fertilizers (N, P, K) were important overall drivers of PGPB inoculation efficiency.•The phylum Proteobacteria was considered to be the most effective keystone taxa in reducing the heavy metal stress in crop shoots and roots.
To better understand the reasons for reduced hospital admissions to a hospital general medicine service during COVID-19 lockdowns.
A statistical model for admission rates to the General Medicine ...Service at Wellington Hospital, Aotearoa New Zealand, since 2015 was constructed. This model was used to estimate changes in admission rates for transmissible and non-transmissible diagnoses during and following COVID-19 lockdowns for total admissions and various sub-groups.
For the 2020 lockdown (n=734 admissions), the overall rate ratio of admissions was 0.71 compared to the pre-lockdown rate. Non-transmissible diagnoses, which constitute 87% of admissions, had an admission rate ratio of 0.77. Transmissible diagnoses, constituting 13% of admissions, had an admission rate ratio of 0.44. Reductions in admissions did not exacerbate existing ethnic disparities in access to health services. The lag in recovery of admission rates was more pronounced for transmissible than non-transmissible diagnoses. The 2021 lockdown (n=105 admissions) followed this pattern, but was of shorter duration with small numbers, and therefore measures were frequently not statistically significant.
The biggest relative reduction in hospital admission was due to a reduction in transmissible illness admissions, likely due to COVID-related public health measures. However, the biggest reduction in absolute terms was in non-transmissible illnesses, where hospital avoidance may be associated with increased morbidity or mortality.
This study investigated the effects of biochars pyrolyzed at different temperatures on plant germination and growth and attempted to determine the mechanisms underlying those effects. The ...experimental results showed that phytotoxicity of biochar pyrolyzed at 500 or 800 °C was significantly higher than that of biochar pyrolyzed at 200 °C, especially at high dosages (200.0 and 300.0 g/L). However, concentrations of heavy metals and polycyclic aromatic hydrocarbon (PAHs) in biochar pyrolyzed at 500 and 800 °C were lower than those in biochar pyrolyzed at 200 °C. The inhibitory effect of aqueous biochar extract on seed germination was significantly weaker than that of biochar. Electron paramagnetic resonance (EPR) signal intensity was enhanced with increasing pyrolysis temperature, which indicates the existence of a greater number of free radicals. Furthermore, •OH and •O2− were the primary reactive oxygen species in the biochar system. It can be concluded that the phytotoxicity of biochar pyrolyzed at high temperatures (>500 °C) enables to attributing free radical-induced oxidative damage, whereas that of biochar produced at low temperatures (200 °C) results in the presence of conventional contaminants (such as heavy metals and PAHs). The information obtained in this study provides a more comprehensive understanding of the potential risk of free radicals in plant system biochar.
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•High-dose biochar has a significant negative impact on the germination rate, shoot length and root length of seeds.•The phytotoxicity of 500 °C and 800 °C biochar is significantly higher than that of 200 °C biochar.•Inhibitory effect of biochar water extract on seed germination is obviously weaker than that of biochar.•The intensity of EPR signal increases with the increase of pyrolysis temperature.•Phytotoxicity of 500 °C and 800 °C biochar was due to the oxidative damage by free radicals.
Quinclorac (3,7-dichloroquinoline-8-carboxylic acid, QNC) is a highly selective auxin herbicide that is typically applied to paddy rice fields. Its residue is a serious problem in crop rotations. In ...this study, Oryza sativa L. seedlings was used as a model plant to explore its biochemical response to abiotic stress caused by QNC and nZVI coexposure, as well as the interactions between QNC and nZVI treatments. Exposure to 5 and 10 mg/L QNC reduced the fresh biomass by 26.6% and 33.9%, respectively, compared to the control. The presence of 50 and 250 mg/L nZVI alleviated the QNC toxicity, but the nZVI toxicity was aggravated by the coexist of QNC. Root length was enhanced upon exposure to low or medium doses of both QNC and nZVI, whereas root length was inhibited under high-dose coexposure. Both nZVI and QNC, either alone or in combination, significantly inhibited the biosynthesis of chlorophyll, and the inhibition rate increased with elevated nZVI and QNC concentration. It was indicated that nZVI or QNC can affect the plant photosynthesis, and there was a significant interaction between the two treatments. Effects of QNC on the antioxidant response of Oryza sativa L. differed in the shoots and roots; generally, the introduction of 50 and 250 mg/L nZVI alleviated the oxidative stress (POD in shoots, SOD and MDA in roots) induced by QNC. However, 750 mg/kg nZVI seriously damaged Oryza sativa L. seedlings, which likely resulted from active iron deficiency. QNC could be removed from the culture solution by nZVI; as a result, nZVI suppressed QNC uptake by 20%–30%.
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•Compared to control, the total fresh weight of rice was decreased by treated with QNC or nZVI alone.•Root length was enhanced at low or medium doses of QNC and nZVI, but inhibited at high doses.•The introduction of nZVI significantly alleviated the oxidative stress induced by QNC.•750 mg/kg of nZVI caused serious suppression and damage of rice due to active iron deficiency.•The presence of nZVI suppressed the uptake of QNC in rice seedlings by 20–30%.
To identify the radiological features and clinical biomarkers that could predict the occult metastasis (OM) of pancreatic ductal adenocarcinoma (PDAC).
This retrospective study included PDAC patients ...who were radiologically diagnosed resectable (R) or borderline resectable (BR) and underwent surgical exploration from January 2018 to December 2021. Depending on whether distant metastases were found during the exploration, patients were divided into OM and non-OM groups. Univariate and multivariable logistic regression analyses were performed to determine the radiological and clinical predictive factors for occult metastasis. Model performance was determined by discrimination and calibration.
A total of 502 patients (median age, 64 years; interquartile range, 57-70 years; 294 men) were enrolled, among which 68 (13.5%) patients were found with distant metastases, with 45 liver-only, 19 peritoneal-only, four patients had both liver and peritoneal metastases. Rim enhancement and peripancreatic fat stranding were more frequent in the OM group than in the non-OM group. Tumor size (p = 0.028), tumor resectability (p = 0.031), rim enhancement (p < 0.001), peripancreatic fat stranding (p < 0.001) and level of CA125 (p = 0.021) were independent predictors of occult metastasis according to the multivariable analyses, and the areas under the curve (AUCs) of these characteristics were 0.703, 0.594, 0.638, 0.655, 0.631, respectively. The combined model showed the highest AUC of 0.823.
Rim enhancement, peripancreatic fat stranding, tumor size, tumor resectability and level of CA125 are risk factors for OM of PDAC. The combined model of radiological and clinical features may help the preoperative prediction of OM in PDAC.
Cotton is one of the most important economic crops in the world, and it is a major source of fiber in the textile industry. Strigolactones (SLs) are a class of carotenoid-derived plant hormones ...involved in many processes of plant growth and development, although the functions of SL in fiber development remain largely unknown. Here, we found that the endogenous SLs were significantly higher in fibers at 20 days post-anthesis (DPA). Exogenous SLs significantly increased fiber length and cell wall thickness. Furthermore, we cloned three key SL biosynthetic genes, namely GhD27, GhMAX3, and GhMAX4, which were highly expressed in fibers, and subcellular localization analyses revealed that GhD27, GhMAX3, and GhMAX4 were localized in the chloroplast. The exogenous expression of GhD27, GhMAX3, and GhMAX4 complemented the physiological phenotypes of d27, max3, and max4 mutations in Arabidopsis, respectively. Knockdown of GhD27, GhMAX3, and GhMAX4 in cotton resulted in increased numbers of axillary buds and leaves, reduced fiber length, and significantly reduced fiber thickness. These findings revealed that SLs participate in plant growth, fiber elongation, and secondary cell wall formation in cotton. These results provide new and effective genetic resources for improving cotton fiber yield and plant architecture.
Over one-third of the population of Havelock North, New Zealand, approximately 5500 people, were estimated to have been affected by campylobacteriosis in a large waterborne outbreak. Cases reported ...through the notifiable disease surveillance system (notified case reports) are inevitably delayed by several days, resulting in slowed outbreak recognition and delayed control measures. Early outbreak detection and magnitude prediction are critical to outbreak control. It is therefore important to consider alternative surveillance data sources and evaluate their potential for recognizing outbreaks at the earliest possible time.
The first objective of this study is to compare and validate the selection of alternative data sources (general practice consultations, consumer helpline, Google Trends, Twitter microblogs, and school absenteeism) for their temporal predictive strength for Campylobacter cases during the Havelock North outbreak. The second objective is to examine spatiotemporal clustering of data from alternative sources to assess the size and geographic extent of the outbreak and to support efforts to attribute its source.
We combined measures derived from alternative data sources during the 2016 Havelock North campylobacteriosis outbreak with notified case report counts to predict suspected daily Campylobacter case counts up to 5 days before cases reported in the disease surveillance system. Spatiotemporal clustering of the data was analyzed using Local Moran's I statistics to investigate the extent of the outbreak in both space and time within the affected area.
Models that combined consumer helpline data with autoregressive notified case counts had the best out-of-sample predictive accuracy for 1 and 2 days ahead of notified case reports. Models using Google Trends and Twitter typically performed the best 3 and 4 days before case notifications. Spatiotemporal clusters showed spikes in school absenteeism and consumer helpline inquiries that preceded the notified cases in the city primarily affected by the outbreak.
Alternative data sources can provide earlier indications of a large gastroenteritis outbreak compared with conventional case notifications. Spatiotemporal analysis can assist in refining the geographical focus of an outbreak and can potentially support public health source attribution efforts. Further work is required to assess the location of such surveillance data sources and methods in routine public health practice.
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