Explore the vast range of titles available.

Since the detection of phosphine in the wastewater treatment plants in 1988, more and more investigations revealed that phosphine is closely related to ecological activities on a global scale. Here, we present perspectives on the whole dynamic cycles of phosphorus, particularly in terms of phosphine and its interactions with natural ecosystems, as well as the impacts from human activities. It may conclude that the phosphine-driving cycles of phosphorus depend on the coordination of human activities with natural ecosystems. Most importantly, the extensive recovery of phosphorus in numerous urban wastewater treatment plants may seriously obstruct its global cycles to catch up with the ecological needs in natural ecosystems. Phosphine gas plays an important role in the biogeochemical phosphorus cycle. Phosphorus might be one of the important elements participating in the global climate change together with carbon and nitrogen.

The unique properties of nanomaterials offer vast opportunities to advance sustainable processes. Incidental nanoparticles (INPs) represent a significant part of nanomaterials, yet their potential for sustainable applications remains largely untapped. Herein, we developed a simple strategy to harness INPs to upgrade the waste-to-resource paradigm, significantly reducing the energy consumption and greenhouse gas emissions. Using the recycling of fly ash from municipal solid waste incineration (MSWI) as a proof of concept, we reveal that incidental iron oxide nanoclusters confined inside the residual carbon trigger Fenton-like catalysis by contacting H 2 O 2 at circumneutral pH (5.0–7.0). This approach efficiently detoxifies the adsorbed dioxins under ambient conditions, which otherwise relies on energy-intensive thermal methods in the developed recovery paradigms. Collective evidence underlines that the uniform distribution of iron oxide nanoclusters within dioxin-enriched nanopores enhances the collision between the generated active oxidants and dioxins, resulting in a substantially higher detoxification efficiency than the Fe(II)-induced bulk Fenton reaction. Efficient and cost-effective detoxification of MSWI fly ash at 278‒288 K at pilot scale, combined with the satisfactory removal of adsorbed chemicals in other solid wastes unlocks the great potential of incidental nanoparticles in upgrading the process of solid waste utilization and other sustainable applications. Detoxification of dioxins is critical for fly ash upcycling but has long been relying on energy-intensive methods. Here, the authors report a simple yet effective paradigm that leverages the Fenton-like activity of the incidental iron oxide nanoclusters to detoxify fly ash under ambient conditions.

Objectives Quantifying radiation burden is essential for justification, optimization, and personalization of CT procedures and can be characterized by a variety of risk surrogates inducing different radiological risk reflections. This study compared how twelve such metrics can characterize risk across patient populations. Methods This study included 1394 CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogates were considered: volume computed tomography dose index (CTDI vol ), dose-length product (DLP), size-specific dose estimate (SSDE), DLP-based effective dose (ED k ), dose to a defining organ (OD D ), effective dose and risk index based on organ doses (ED OD , RI), and risk index for a 20-year-old patient (RI rp ). The last three metrics were also calculated for a reference ICRP-110 model (OD D,0 , ED 0 , and RI 0 ). Lastly, motivated by the ICRP, an adjusted-effective dose was calculated as E D r = RI R I rp × E D OD . A linear regression was applied to assess each metric’s dependency on RI. The results were characterized in terms of risk sensitivity index (RSI) and risk differentiability index (RDI). Results The analysis reported significant differences between the metrics with ED r showing the best concordance with RI in terms of RSI and RDI. Across all metrics and protocols, RSI ranged between 0.37 (SSDE) and 1.29 (RI 0 ); RDI ranged between 0.39 (ED k ) and 0.01 (ED r ) cancers × 10 3 patients × 100 mGy. Conclusion Different risk surrogates lead to different population risk characterizations. ED r exhibited a close characterization of population risk, also showing the best differentiability. Care should be exercised in drawing risk predictions from unrepresentative risk metrics applied to a population. Key Points • Radiation risk characterization in CT populations is strongly affected by the surrogate used to describe it. • Different risk surrogates can lead to different characterization of population risk. • Healthcare professionals should exercise care in ascribing an implicit risk to factors that do not closely reflect risk.

Pre-eclampsia is a complex multi-system pregnancy disorder with limited treatment options. Therefore, we aimed to screen for metabolites that have causal associations with preeclampsia and to predict target-mediated side effects based on Mendelian randomization (MR) analysis. A two-sample MR analysis was firstly conducted to systematically assess causal associations of blood metabolites with pre-eclampsia, by using metabolites related large-scale genome-wide association studies (GWASs) involving 147,827 European participants, as well as GWASs summary data about pre-eclampsia from the FinnGen consortium R8 release data that included 182,035 Finnish adult female subjects (5922 cases and 176,113 controls). Subsequently, a phenome-wide MR (Phe-MR) analysis was applied to assess the potential on-target side effects associated with hypothetical interventions that reduced the burden of pre-eclampsia by targeting identified metabolites. Four metabolites were identified as potential causal mediators for pre-eclampsia by using the inverse-variance weighted method, including cholesterol in large HDL (L-HDL-C) [odds ratio (OR): 0.88; 95% confidence interval (95% CI): 0.83-0.93; P = 2.14 × 10 ), cholesteryl esters in large HDL (L-HDL-CE) (OR: 0.88; 95% CI: 0.83-0.94; P = 5.93 × 10 ), free cholesterol in very large HDL (XL-HDL-FC) (OR: 0.88; 95% CI: 0.82-0.94; P = 1.10 × 10 ) and free cholesterol in large HDL (L-HDL-FC) (OR: 0.89; 95% CI: 0.84-0.95; P = 1.45 × 10 ). Phe-MR analysis showed that targeting L-HDL-CE had beneficial effects on the risk of 24 diseases from seven disease chapters. Based on this systematic MR analysis, L-HDL-C, L-HDL-CE, XL-HDL-FC, and L-HDL-FC were inversely associated with the risk of pre-eclampsia. Interestingly, L-HDL-CE may be a promising drug target for preventing pre-eclampsia with no predicted detrimental side effects. The study consists of a two-stage design that conducts MR at both stages. First, we assessed the causality for the associations between 194 blood metabolites and the risk of pre-eclampsia. Second, we investigated a broad spectrum of side effects associated with the targeting identified metabolites in 693 non-preeclampsia diseases. Our results suggested that Cholesteryl esters in large HDL may serve as a promising drug target for the prevention or treatment of pre-eclampsia with no predicted detrimental side effects.

A variety of patient populations receive allergen immunotherapy (AIT), but clinicians still lack an effective electronic platform to manage them. We designed a platform based on the framework of value set extraction standardization, integration, and structurization. Average medication scoring (AMS) and other electronic medical records were developed and stored on a MySQL database. Data storage is hosted on cloud servers, linked to a mobile application, Bluetooth lung function monitoring, and a dedicated website that acts as a front-end. Since 2015, 23,847 patients in 48 hospitals with AIT prescriptions were included. Of these patients, the median age was 15 (interquartile range, 10-27) years. Allergic rhinitis was the most common disorder and accounted for 9753 (40.9%) of the cases. Five hundred and thirty-three basic data elements and six independent modules were constructed for the platform to facilitate the physicians in establishing SCIT projects, symptom scores, AMS, lung function tests, and follow-up appointments. One hundred and twelve drugs including 10 dosage forms were identified from an internal list of the dataset. The unit score was calculated based on the action mechanism of the medicine. The AMS formula has six parameters: total dose, frequency, period, unit score, unit dose, and follow-up days. A lower AMS suggests a better treatment efficacy. The program presented our experience in developing, pilot testing, and evaluating an electronic AIT platform, and future research would indicate whether the template could be made more time efficient in clinical practice.

A Correction to this paper has been published: https://doi.org/10.1007/s00330-021-07903-z

IntroductionHepatitis B virus (HBV) has recently been reported to impair both sperm and oocyte function, potentially increasing infertility and birth defects risks, although primarily recognised as a concern for mother-to-child transmission. Population-based evidence regarding the association between paternal preconception HBV infection and preterm birth (PTB) risk is absent.MethodsThis retrospective cohort study was conducted based on the National Free Preconception Checkups Project between 22 April 2010 and 31 December 2020 in China. Paternal preconception HBV infection statuses were divided into three groups: uninfected, past exposure and immunity, and current infection. Inverse probability weighting (IPW) via propensity models was used to adjust for imbalance by different groups of paternal preconception HBV infection status. Log-binomial regression models were employed to estimate the relative risk ratios (RRs) of PTB associated with paternal preconception HBV infection.Results7 395 829 couples were included, with a PTB incidence of 5.65%. Compared with HBV-uninfected males, those with prior HBV exposure had a 5% increased PTB risk in offspring (RR 1.05, 95% CI 1.04 to 1.07), and those infected with HBV currently showed a 10% increased PTB risk (RR 1.10, 95% CI 1.09 to 1.12). No significant association was observed when both partners had the same HBV immunity prior to pregnancy (RR 1.01, 95% CI 0.99 to 1.03). Moreover, an interaction effect between maternal and paternal preconception HBV infection was observed (Pfor interaction=0.003), with couples both currently infected with HBV showing the highest PTB risk (RR 1.16, 95% CI 1.11 to 1.20). Consistent results were obtained across all PTB subtypes.ConclusionsBoth paternal current HBV infection and prior exposure were identified to be associated with increased PTB risks independently. Moreover, the interaction impact of HBV infections between couples on PTB risks should also be considered. These findings provide new evidence for the paternal risk factors of PTB, highlighting the importance of comprehensive HBV screening and immunity management for both parents before conception to reduce PTB risks.

This work presents an effective approach for manganese-doped Al2O3 ceramic membrane (Mn-doped membrane) fouling control by in-situ confined H2O2 cleaning in wastewater treatment. An Mn-doped membrane with 0.7 atomic percent Mn doping in the membrane layer was used in a membrane bioreactor with the aim to improve the catalytic activity toward oxidation of foulants by H2O2. Backwashing with 1 mM H2O2 solution at a flux of 120 L/m2/h (LMH) for 1 min was determined to be the optimal mode for in-situ H2O2 cleaning, with confined H2O2 decomposition inside the membrane. The Mn-doped membrane with in-situ H2O2 cleaning demonstrated much better fouling mitigation efficiency than a pristine Al2O3 ceramic membrane (pristine membrane). With in-situ H2O2 cleaning, the transmembrane pressure increase (ΔTMP) of the Mn-doped membrane was 22.2 kPa after 24-h filtration, which was 40.5% lower than that of the pristine membrane (37.3 kPa). The enhanced fouling mitigation was attributed to Mn doping, in the Mn-doped membrane layer, that improved the membrane surface properties and confined the catalytic oxidation of foulants by H2O2 inside the membrane. Mn3+/Mn4+ redox couples in the Mn-doped membrane catalyzed H2O2 decomposition continuously to generate reactive oxygen species (ROS) (i.e., HO• and O21), which were likely to be confined in membrane pores and efficiently degraded organic foulants.

Lumbar degenerative disc diseases constitute a major contributor to lower back pain. In pursuit of an enhanced understanding of lumbar degenerative pathology and the development of more effective treatment modalities, the application of precise measurement techniques for lumbar segment kinematics is imperative. This study aims to pioneer a novel automated lumbar spine orientation estimation method using deep learning techniques, to facilitate the automatic 2D–3D pre‐registration of the lumbar spine during physiological movements, to enhance the efficiency of image registration and the accuracy of spinal segment kinematic measurements. A total of 12 asymptomatic volunteers were enrolled and captured in 2 oblique views with 7 different postures. Images were used for deep learning model development training and evaluation. The model was composed of a segmentation module using Mask R‐CNN and an estimation module using ResNet50 architecture with a Squeeze‐and‐Excitation module. The cosine value of the angle between the prediction vector and the vector of ground truth was used to quantify the model performance. Data from another two prospective recruited asymptomatic volunteers were used to compare the time cost between model‐assisted registration and manual registration without a model. The cosine values of vector deviation angles at three axes in the cartesian coordinate system were 0.9667 ± 0.004, 0.9593 ± 0.0047 and 0.9828 ± 0.0025, respectively. The value of the angular deviation between the intermediate vector obtained by utilising the three direction vectors and ground truth was 10.7103 ± 0.7466. Results show the consistency and reliability of the model's predictions across different experiments and axes and demonstrate that our approach significantly reduces the registration time (3.47 ± 0.90 min vs. 8.10 ± 1.60 min, p < 0.001), enhances the efficiency, and expands its broader utilisation of clinical research about kinematic measurements.