The fidelity of transcription in human cells.

To determine the error rate of transcription in human cells, we analyzed the transcriptome of H1 human embryonic stem cells with a circle-sequencing approach that allows for high-fidelity sequencing of the transcriptome. These experiments identified approximately 100,000 errors distributed over every major RNA species in human cells. Our results indicate that different RNA species display different error rates, suggesting that human cells prioritize the fidelity of some RNAs over others. Cross-referencing the errors that we detected with various genetic and epigenetic features of the human genome revealed that the in vivo error rate in human cells changes along the length of a transcript and is further modified by genetic context, repetitive elements, epigenetic markers, and the speed of transcription. Our experiments further suggest that BRCA1, a DNA repair protein implicated in breast cancer, has a previously unknown role in the suppression of transcription errors. Finally, we analyzed the distribution of transcription errors in multiple tissues of a new mouse model and found that they occur preferentially in neurons, compared to other cell types. These observations lend additional weight to the idea that transcription errors play a key role in the progression of various neurological disorders, including Alzheimer's disease.

Recent Progress on Phase Engineering of Nanomaterials.

As a key structural parameter, phase depicts the arrangement of atoms in materials. Normally, a nanomaterial exists in its thermodynamically stable crystal phase. With the development of nanotechnology, nanomaterials with unconventional crystal phases, which rarely exist in their bulk counterparts, or amorphous phase have been prepared using carefully controlled reaction conditions. Together these methods are beginning to enable phase engineering of nanomaterials (PEN), i.e., the synthesis of nanomaterials with unconventional phases and the transformation between different phases, to obtain desired properties and functions. This Review summarizes the research progress in the field of PEN. First, we present representative strategies for the direct synthesis of unconventional phases and modulation of phase transformation in diverse kinds of nanomaterials. We cover the synthesis of nanomaterials ranging from metal nanostructures such as Au, Ag, Cu, Pd, and Ru, and their alloys; metal oxides, borides, and carbides; to transition metal dichalcogenides (TMDs) and 2D layered materials. We review synthesis and growth methods ranging from wet-chemical reduction and seed-mediated epitaxial growth to chemical vapor deposition (CVD), high pressure phase transformation, and electron and ion-beam irradiation. After that, we summarize the significant influence of phase on the various properties of unconventional-phase nanomaterials. We also discuss the potential applications of the developed unconventional-phase nanomaterials in different areas including catalysis, electrochemical energy storage (batteries and supercapacitors), solar cells, optoelectronics, and sensing. Finally, we discuss existing challenges and future research directions in PEN.

Facet-Controlled Synthesis of Unconventional-Phase Metal Alloys for Highly Efficient Hydrogen Oxidation.

Facet control and phase engineering of metal nanomaterials are both important strategies to regulate their physicochemical properties and improve their applications. However, it is still a challenge to tune the exposed facets of metal nanomaterials with unconventional crystal phases, hindering the exploration of the facet effects on their properties and functions. In this work, by using Pd nanoparticles with unconventional hexagonal close-packed (hcp, 2H type) phase, referred to as 2H-Pd, as seeds, a selective epitaxial growth method is developed to tune the predominant growth directions of secondary materials on 2H-Pd, forming Pd@NiRh nanoplates (NPLs) and nanorods (NRs) with 2H phase, referred to as 2H-Pd@2H-NiRh NPLs and NRs, respectively. The 2H-Pd@2H-NiRh NRs expose more (100)h and (101)h facets on the 2H-NiRh shells compared to the 2H-Pd@2H-NiRh NPLs. Impressively, when used as electrocatalysts toward hydrogen oxidation reaction (HOR), the 2H-Pd@2H-NiRh NRs show superior activity compared to the NiRh alloy with conventional face-centered cubic (fcc) phase (fcc-NiRh) and the 2H-Pd@2H-NiRh NPLs, revealing the crucial role of facet control in enhancing the catalytic performance of unconventional-phase metal nanomaterials. Density functional theory (DFT) calculations further unravel that the excellent HOR activity of 2H-Pd@2H-NiRh NRs can be attributed to the more exposed (100)h and (101)h facets on the 2H-NiRh shells, which possess high electron transfer efficiency, optimized H* binding energy, enhanced OH* binding energy, and a low energy barrier for the rate-determining step during the HOR process.

Biosynthesis of CuTe Nanorods with Large Molar Extinction Coefficients for NIR-II Photoacoustic Imaging.

Photoacoustic imaging (PAI) in the second near-infrared region (NIR-II), due to deeper tissue penetration and a lower background interference, has attracted widespread concern. However, the development of NIR-II nanoprobes with a large molar extinction coefficient and a high photothermal conversion efficiency (PCE) for PAI and photothermal therapy (PTT) is still a big challenge. In this work, the NIR-II CuTe nanorods (NRs) with large molar extinction coefficients ((1.31 ± 0.01) × 108 cm-1·M-1 at 808 nm, (7.00 ± 0.38) × 107 cm-1·M-1 at 1064 nm) and high PCEs (70% at 808 nm, 48% at 1064 nm) were synthesized by living Staphylococcus aureus (S. aureus) cells as biosynthesis factories. Due to the strong light-absorbing and high photothermal conversion ability, the in vitro PA signals of CuTe NRs were about 6 times that of indocyanine green (ICG) in both NIR-I and NIR-II. In addition, CuTe NRs could effectively inhibit tumor growth through PTT. This work provides a new strategy for developing NIR-II probes with large molar extinction coefficients and high PCEs for NIR-II PAI and PTT.

Biosynthesis of NIR-II Ag2Se Quantum Dots with Bacterial Catalase for Photoacoustic Imaging and Alleviating-Hypoxia Photothermal Therapy.

Developing the second near-infrared (NIR-II) photoacoustic (PA) agent is of great interest in bioimaging. Ag2Se quantum dots (QDs) are one kind of potential probe for applications in NIR-II photoacoustic imaging (PAI). However, the surfaces with excess anions of Ag2Se QDs, which increase the probability of nonradiative transitions of excitons benefiting PA imaging, are not conducive to binding electron donor ligands for potential biolabeling and imaging. In this study, Staphylococcus aureus (S. aureus) cells are driven for the biosynthesis of Ag2Se QDs with catalase (CAT). Biosynthesized Ag2Se (bio-Ag2Se-CAT) QDs are produced in Se-enriched environment of S. aureus and have a high Se-rich surface. The photothermal conversion efficiency of bio-Ag2Se-CAT QDs at 808 and 1064 nm is calculated as 75.3% and 51.7%, respectively. Additionally, the PA signal responsiveness of bio-Ag2Se-CAT QDs is ≈10 times that of the commercial PA contrast agent indocyanine green. In particular, the bacterial CAT is naturally attached to bio-Ag2Se-CAT QDs surface, which can effectively relieve tumor hypoxia. The bio-Ag2Se-CAT QDs can relieve heat-initiated oxidative stress while undergoing effective photothermal therapy (PTT). Such biosynthesis method of NIR-II bio-Ag2Se-CAT QDs opens a new avenue for developing multifunctional nanomaterials, showing great promise for PAI, hypoxia alleviation, and PTT.

Ligand-Assisted Phase Engineering of Nanomaterials.

ConspectusThe synthesis of monodisperse colloidal nanomaterials with well-defined structures is important for both fundamental research and practical application. To achieve it, wet-chemical methods with the usage of various ligands have been extensively explored to finely control the structure of nanomaterials. During the synthesis, ligands cap the surface and thus modulate the size, shape, and stability of nanomaterials in solvents. Besides these widely investigated roles of ligands, it has been recently discovered that ligands can affect the phase of nanomaterials, i.e., their atomic arrangement, providing an effective strategy to realize the phase engineering of nanomaterials (PEN) by selecting appropriate ligands. Nanomaterials normally exist in the phases that are thermodynamically stable in their bulk states. Previous studies have shown that under high temperature or high pressure, nanomaterials can exist in unconventional phases which are unattainable in the bulks. Importantly, nanomaterials with unconventional phases exhibit unique properties and functions different from conventional-phase ones. Consequently, it is feasible to utilize the PEN to tune the physicochemical properties and application performance of nanomaterials. During wet-chemical synthesis, ligands binding to the surface of nanomaterials can modify their surface energy, which could significantly affect the Gibbs free energy of nanomaterials and thus determine the stability of different phases, making it possible to obtain nanomaterials with unconventional phases at mild reaction conditions. For instance, a series of Au nanomaterials with unconventional hexagonal phases have been prepared with the assistance of oleylamine. Therefore, the rational design and selection of different ligands and deep understanding of their effect on the phase of nanomaterials would significantly accelerate the development of PEN and the discovery of novel functional nanomaterials for diverse applications.In this Account, we briefly summarize the recent progress in ligand-assisted PEN, elaborating the important roles of different ligands in the direct synthesis of nanomaterials with unconventional crystal phases and amorphous phase as well as the phase transformation of nanomaterials. We first introduce the background of this research topic, highlighting the concept of PEN and why ligands can modulate the phase of nanomaterials. Then we discuss the usage of four kinds of ligands, i.e., amines, fatty acids, sulfur-containing ligands, and phosphorus-containing ligands, in phase engineering of different nanomaterials, especially metal, metal chalcogenide, and metal oxide nanomaterials. Finally, we provide our personal views of the challenges and future promising research directions in this exciting field.

Combined Effect of Hydrophilic Pore and the Type of Protons on Proton Conductivity in Porous Metal-Organic Frameworks: A Feasible Approach to Achieve a Super Proton Conductor under Hydrated Conditions.

There has been a steady growth of interest in proton-conductive metal-organic frameworks (MOFs) due to their potential utility in proton-exchange membrane fuel cells. To attain a super proton conductivity (>1 × 10-2 S cm-1) in a MOF-based proton conductor is a key step toward practical application. Currently, most studies are focused on enhancing the proton conductivity of porous MOFs by controlling a single factor, such as the type of protons or hydrophilic pore or hydrogen bond. However, a limited contribution from a single factor cannot afford to remarkably increase the proton conductivity of the MOF and form a super proton conductor. Herein, we constructed two distinct porous MOFs, {(H3O+)4[Cu12(ci)12(OH)4(H2O)12]·3H2O·9DMF} (Cu-ci-3D, H2ci = 1H-indazole-5-carboxylic acid, DMF = N,N'-dimethylformamide) and {[Co(Hppca)2]·2HN(CH3)2·CH3OH·2H2O} (Co-ppca-2D, H2ppca = 5-(pyridin-3-yl)-1H-pyrazole-3-carboxylic acid), to tune their proton conductivities at high relative humidity (RH) using the combined effect of hydrophilic pore and the type of protons, ultimately achieving super proton conduction. Excitingly, Cu-ci-3D indeed harvests a super proton conductivity of 1.37 × 10-2 S cm-1 at 353 K and ∼97% RH, superior to some previously reported MOF-based proton conductors. The results present a unique perspective for developing high-performance MOF-based proton conductors and understanding their structure-performance relationships.

Facile Synthesis and Characterization of Fluorescent Polystyrene Nanospheres for Homogeneous Light-Initiated Chemiluminescence Immunoassay.

Homogeneous light-initiated chemiluminescence technology (LICA) is widely used in clinical diagnostics due to the advantages of high sensitivity, minimal reagent usage, and no need for washing. Luminescent microspheres receive singlet oxygen emitted by photosensitive microspheres to generate optical signals. Therefore,1O2-initiated luminescent nanospheres are crucial, but there are few reports on the preparation of 1O2-initiated luminescent nanospheres. Herein, monodisperse luminescent Eu/C-28@PS (Eps) nanospheres were prepared and optimized using chelate Eu (TTA)3phen and 4-(2-phenyl-5,6-dihydro1,4-oxathiin-3-yl)-N, N-ditetradecylbenzenamine (C-28) as probe dye via THF/water swelling-shrinking procedure. Various swelling parameters were studied to obtain the swelling conditions that produce the minimum particle size and narrow size distribution, which shows good results in uniform particle size distribution (~ 250 nm, a PDI of 0.03), surface carboxylate content (1.18 mmol/g), and BSA loading capability (129.8 mg/g) in the case of 20 mg total probe dosage and 2 h of incubation at 40 °C using 14% THF/water mixture as a co-solvent system. The composition of the entrapped probe has a gain effect on the 1O2-initiated fluorescent signal and the optimal ratio of Eu (TTA)3phen: C-28 (1:1) was obtained on a commercial analyzer using IgG and anti-human IgG as models in PBS buffer. These results indicate that monodisperse luminescent Eps nanospheres are suitable as light-initiated chemiluminescence sensors and have great application potential in early detection, screening tests, and prognostic evaluation of patients.

AlphaLISA-Based Immunoassay for Detection of Troponin T in Serum of Patients with Acute Myocardial Infarction.

Survival and prognosis of patients with acute myocardial infarction (AMI) are highly dependent on rapid and accurate diagnosis of myocardial damage. Troponin T is the primary diagnostic biomarker and is widely used in clinical practice. Amplified luminescent proximity homogeneous assay (AlphaLISA) may provide a solution to rapidly detect a small amount of analyte through molecular interactions between special luminescent donor beads and acceptor bead. Here, a double-antibody sandwich assay was introduced into AlphaLISA for rapid detection for early diagnosis of AMI and disease staging evaluation. The performance of the assay was evaluated. The study found that the cTnT assay has a linear range of 48.66 to 20,000 ng/L with a limit of detection of 48.66 ng/L. In addition, the assay showed no cross-reactivity with other classic biomarkers of myocardial infarction and was highly reproducible with intra- and inter-batch coefficients of variation of less than 10%, notably, only 3 min was taken, which is particularly suitable for clinical diagnosis. These results suggest that our method can be conveniently applied in the clinic to determine the severity of the patient's condition.

Establishment of trypsinogen-2 Amplification Luminescent Proximity Homogeneous Assay and its Application in Acute Pancreatitis.

We aim to develop an amplified luminescence proximity homogeneous assay (AlphaLISA) for quantification of trypsinogen-2 levels in human serum for the diagnosis of acute pancreatitis. Based on new amplified luminescence proximity homogeneity assay (AlphaLISA) method, carboxyl-modified donor and acceptor beads were coupled to capture and detection antibodies. A double antibody sandwich immunoassay was used to detect the concentration of trypsinogen-2 in serum. The method had good linearity (> 0.998). The intra - analysis precision was between 1.54% and 2.20% (< 10%), the inter-analysis precision was between 3.17% and 6.94% (< 15%), and the recovery was between 96.23% and 103.45%. The cross-reactivity of carbohydrate antigen 242 (CA242) and T-cell immunoglobulin mucin-3 (Tim-3) were 0.09% and 0.93%, respectively. The detection time only needed 15 min. The results of trypsinogen-2-AlphaLISA and time-resolved fluorescence immunoassay were consistent (ρ = 0.9019). In addition, serum trypsinogen-2 concentration in patients with acute pancreatitis [239.23 (17.83-807.58) ng/mL] was significantly higher than that in healthy controls [20.54 (12.10-39.73) ng/mL]. When the cut-off value was 35.38ng/mL, the sensitivity and specificity were 91.8% and 96.67%, and the positive detection rate was 91.80%. We have successfully established a trypsinogen-2-AlphaLISA method, which can promote the timely diagnosis of acute pancreatitis.

Multiparametric MRI-based fusion radiomics for predicting telomerase reverse transcriptase (TERT) promoter mutations and progression-free survival in glioblastoma: a multicentre study.

PURPOSE: This study evaluated the performance of multiparametric magnetic resonance imaging (MRI)-based fusion radiomics models (MMFRs) to predict telomerase reverse transcriptase (TERT) promoter mutation status and progression-free survival (PFS) in glioblastoma patients. METHODS: We retrospectively analysed 208 glioblastoma patients from two hospitals. Quantitative imaging features were extracted from each patient's T1-weighted, T1-weighted contrast-enhanced, and T2-weighted preoperative images. Using a coarse-to-fine feature selection strategy, four radiomics signature models were constructed based on the three MRI sequences and their combination for TERT promoter mutation status and PFS; model performance was subsequently evaluated. Subgroup analyses were performed by the radiomics signature of TERT promoter mutation status and PFS to distinguish patients who could benefit from prolonged temozolomide chemotherapy cycles. RESULTS: TERT promoter mutation status was best predicted by MMFR, with an area under the curve (AUC) of 0.816 and 0.812 for the training and internal validation sets, respectively. The external test set also achieved stable and optimal prediction results (AUC, 0.823). MMFR better predicted patient PFS compared with the single-sequence radiomics signature in the test set (C-index, 0.643 vs 0.561 vs 0.620 vs 0.628). Subgroup analyses showed that more than six cycles of postoperative temozolomide chemotherapy were associated with improved PFS for patients in class 2 (high TERT promoter mutation and high survival rates; HR, 0.222; 95% CI, 0.054 - 0.923; p = 0.025). CONCLUSION: MMFR is an effective method to predict TERT promoter mutations and PFS in patients with glioblastoma. Moreover, subgroup analysis could differentiate patients who may benefit from prolonged TMZ chemotherapy cycles.

Fractionation of metals in soil for strawberry cultivation: Effect on metal migration in food chain and application in risk assessment.

Although trace metals in strawberry production system have attracted growing attention, little is known about metal fractionation in soil for strawberry cultivation. We hypothesized that the metal fractions in soil influenced by strawberry production had significant effect on food chain transport of metals and their risk in soil. Here, samples of strawberries and soil were gathered in the Yangtze River Delta, China to verify the hypothesis. Results showed that the acid-soluble Cr, Cd, and Ni in soil for strawberry cultivation were 21.5%-88.3% higher than those in open field soil, which enhanced uptake and bioaccessible levels of these metals in strawberries. Overall, the ecological, mobility, and health risks of Pb, Zn, Ni, and Cu in soil were at a low level. However, the ecological risk of bioavailable Cd, mobility risk of Cd, and cancer risk of bioavailable Cr in over 70% of the soil samples were at moderate, high, and acceptable levels, respectively. Since the increased acid-soluble Cr and Ni in soil were related to soil acidification induced by strawberry production, nitrogen fertilizer application should be optimized to prevent soil acidification and reduce transfer of Cr and Ni. Additionally, as Cd and organic matter accumulated in soil, the acid-soluble Cd and the ecological and mobility risks of Cd in soil were enhanced. To decrease transfer and risk of Cd in soil, organic fertilizer application should be optimized to mitigate Cd accumulation, alter organic matter composition, and subsequently promote the transformation of bioavailable Cd into residual Cd in soil.

Joint effects of heat-humidity compound events on drowning mortality in Southern China.

BACKGROUND: Several previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality. METHODS: The drowning mortality data and meteorological data during the five hottest months (May to September) were collected from 46 cities in Southern China (2013-2018 in Guangdong, Hunan and Zhejiang provinces). Distributed lag non-linear model was first conducted to examine the association between heat-humidity compound events and drowning mortality at city level. Then, meta-analysis was employed to pool the city-specific exposure-response associations. Finally, we analysed the additive interaction of heat and humidity on drowning mortality. RESULTS: Compared with wet-non-hot days, dry-hot days had greater effects (excess rate (ER)=32.34%, 95% CI: 24.64 to 40.50) on drowning mortality than wet-hot days (ER=14.38%, 95%CI: 6.80 to 22.50). During dry-hot days, males (ER=42.40%, 95% CI: 31.92 to 53.72), adolescents aged 0-14 years (ER=45.00%, 95% CI: 21.98 to 72.35) and urban city (ER=36.91%, 95% CI: 23.87 to 51.32) showed higher drowning mortality risk than their counterparts. For wet-hot days, males, adolescents and urban city had higher ERs than their counterparts. Attributable fraction (AF) of drowning attributed to dry-hot days was 23.83% (95% CI: 21.67 to 26.99) which was significantly higher than that for wet-hot days (11.32%, 95% CI: 9.64 to 13.48%). We also observed that high temperature and low humidity had an additive interaction on drowning mortality. CONCLUSION: We found that dry-hot days had greater drowning mortality risk and burden than wet-hot days, and high temperature and low humidity might have synergy on drowning mortality.

The association between long-term exposure to ambient formaldehyde and respiratory mortality risk: A national study in China.

INTRODUCTION: While ambient formaldehyde (HCHO) concentrations are increasing worldwide, there was limited research on its health effects. OBJECTIVES: To assess the association of long-term exposure to ambient HCHO with the risk of respiratory (RESP) mortality and the associated mortality burden in China. METHODS: Annual and seasonal RESP death and tropospheric HCHO vertical columns data were collected in 466 counties/districts across China during 2013-2016. A difference-in-differences approach combined with a generalized linear mixed-effects regression model was employed to assess the exposure-response association between long-term ambient HCHO exposure and RESP mortality risk. Additionally, we computed the attributable fraction (AF) to gauge the proportion of RESP mortality attributable to HCHO exposure. RESULTS: This analysis encompassed 560,929 RESP deaths. The annual mean ambient HCHO concentration across selected counties/districts was 8.02×1015 ± 2.22×1015 molec.cm-2 during 2013-2016. Each 1.00×1015 molec.cm-2 increase in ambient HCHO was associated with a 1.61 % increase [excess risk (ER), 95 % confidence interval (CI): 1.20 %, 2.03 %] in the RESP mortality risk. The AF of RESP mortality attributable to HCHO was 12.16 % (95 %CI:9.33 %, 14.88 %), resulting in an annual average of 125,422 (95 %CI:96,404, 153,410) attributable deaths in China. Stratified analyses suggested stronger associations in individuals aged ≥65 years old (ER=1.87 %, 95 %CI:1.43 %, 2.32 %), in cold seasons (ER=1.00 %, 95 %CI:0.56 %, 1.44 %), in urban areas (ER=1.65 %, 95 %CI:1.15 %, 2.16 %), and in chronic obstructive pulmonary disease patients (ER=1.95 %, 95 %CI:1.42 %, 2.48 %). CONCLUSIONS: This study suggested that long-term HCHO exposure may significantly increase the risk of RESP mortality, leading to a substantial mortality burden. Targeted measures should be implemented to control ambient HCHO pollution promptly.

Projecting future minimum mortality temperature in China.

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030-2039), 2060 s (2060-2069), and 2090 s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

Sandwich Therapy with Radionuclide Combined with Intralesional Injections Based on Differences in the Spatial Structure Components of Keloids.

BACKGROUND: Complications such as ulceration, depigmentation, and recurrence limit the use of intralesional injections and brachytherapy in keloid treatment. We designed a modified "sandwich" therapy based on the spatial distribution of keloid components to reduce the incidence of these complications. METHODS: First, we analyzed the spatial distribution pattern of scar tissue through single-cell sequencing analysis, ultrasound, and pathology. Subsequently, a "sandwich" therapy combining radionuclide and intralesional injections was designed based on the pattern found in the previous stage. Finally, 40 patients with keloid scars at 41 sites were included in the clinical trial. RESULTS: Single-cell sequencing identified two significant cellularly highly expressed genes and enriched pathways in the keloid vascular wall that primarily play essential roles in angiogenesis and promoting collagen synthesis, thereby promoting scar growth. Color ultrasound showed that there were hierarchical differences in the blood supply of the keloid, and further H&E, CD34, and eNOS staining showed that there were hierarchical differences in the spatial structure of blood vessels, fibroblasts, and collagen in the keloid. In clinical studies, the complication rate of "sandwich" therapy is lower than that of conventional treatment. CONCLUSION: The distribution of blood vessels and collagen in keloid scars is characterized by spatial variability. The "sandwich" therapy of radionuclide combined with intralesional injections is a modified type of precisely targeted therapy designed based on this variability; it has fewer complications and good clinical efficacy and is worthy of popularization. LEVEL OF EVIDENCE II: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

High-performance electrosorption of lanthanum ion by Mn3O4-loaded phosphorus-doped porous carbon electrodes via capacitive deionization.

Transition-metal-oxide@heteroatom doped porous carbon composites have attracted considerable research interest because of their large theoretical adsorption capacity, excellent electrical conductivity and well-developed pore structure. Herein, Mn3O4-loaded phosphorus-doped porous carbon composites (Mn3O4@PC-900) were designed and fabricated for the electrosorption of La3+ in aqueous solutions. Due to the synergistic effect between Mn3O4 and PC-900, and the active sites provided by Mn-O-Mn, C/PO, C-P-O and Mn-OH, Mn3O4@PC-900 exhibits high electrosorption performance. The electrosorption value of Mn3O4@PC-900 was 45.34% higher than that of PC-900, reaching 93.02 mg g-1. Moreover, the adsorption selectivity reached 87.93% and 89.27% in La3+/Ca2+ and La3+/Na+ coexistence system, respectively. After 15 adsorption-desorption cycles, its adsorption capacity and retention rate were 50.34 mg g-1 and 54.12%, respectively. The electrosorption process is that La3+ first accesses the pores of Mn3O4@PC-900 to generate an electric double layer (EDL), and then undergoes further Faradaic reaction with Mn3O4 and phosphorus-containing functional groups through intercalation, surface adsorption and complexation. This work is hoped to offer a new idea for exploring transition-metal-oxide @ heteroatom doped porous carbon composites for separation and recovery of rare earth elements (REEs) by capacitive deionization.

Identification of illicit discharges in sewer networks by an SWMM-Bayesian coupled approach.

Illicit discharges into sewer systems are a widespread concern within China's urban drainage management. They can result in unforeseen environmental contamination and deterioration in the performance of wastewater treatment plants. Consequently, pinpointing the origin of unauthorized discharges in the sewer network is crucial. This study aims to evaluate an integrative method that employs numerical modeling and statistical analysis to determine the locations and characteristics of illicit discharges. The Storm Water Management Model (SWMM) was employed to track water quality variations within the sewer network and examine the concentration profiles of exogenous pollutants under a range of scenarios. The identification technique employed Bayesian inference fused with the Markov chain Monte Carlo sampling method, enabling the estimation of probability distributions for the position of the suspected source, the discharge magnitude, and the commencement of the event. Specifically, the cases involving continuous release and multiple sources were examined. For single-point source identification, where all three parameters are unknown, concentration profiles from two monitoring sites in the path of pollutant transport and dispersion are necessary and sufficient to characterize the pollution source. For the identification of multiple sources, the proposed SWMM-Bayesian strategy with improved sampling is applied, which significantly improves the accuracy.

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant features in sewer flow modelling and investigated the importance of the relevant features. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events.

A dynamic one-dimensional model for simulating unsteady air-water stratified flow in sewer pipes.

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme. The dynamic airflow model amalgamates energy and momentum equations, circumventing laborious pressure iteration computations. This model utilizes friction coefficients at interfaces to enhance the description of the momentum exchange in the airflow and provide a logical explanation for air pressure. A systematic analysis indicates that this model can be easily adapted to include complex boundary conditions, facilitating its use for modeling airflow in real sewer networks. Furthermore, this research uncovers a direct correlation between the air-to-water flow rate ratio and the filling ratio under natural ventilation conditions, and an empirical formula encapsulating this relationship is derived. This finding offers insights for practical engineering applications.