CeO2/Co heterostructure encapsulated in hollow necklace-like carbon fiber as an advanced host material for high-performance lithium-sulfur batteries.

The shuttle effect of lithium polysulfides (LiPSs) and the sluggish reaction kinetics of LiPSs conversion pose serious challenges to the commercial feasibility of lithium-sulfur (Li-S) batteries. To address these obstacles, herein, we construct CeO2/Co heterostructures in hollow necklace-like carbon fibers (CeO2/Co-CNFs) as the cathode host material for Li-S batteries. The specific surface area of fibers is significantly enhanced by using a template, thereby promoting the utilization efficiency of sulfur. Meanwhile, CeO2/Co-CNFs show strong conductivity, effective adsorption to LiPSs, and robust catalytic activity for LiPSs conversion. As a result, the Li-S battery with CeO2/Co-CNFs displays 961 mAh g-1 at 0.2 C, with an 86 % capacity retention rate after 100 cycles. At 2.0 C current density, the composite cathode maintains an initial discharge capacity of 782 mAh g-1, with a mere 0.044 % capacity loss per cycle. Furthermore, in situations with limited electrolytes, high sulfur loading, and high areal mass loading, the composite cathode can provide a high areal capacity of 6.2 mg cm-2 over 100 cycles. This work provides a useful approach for investigating high-performance Li-S battery cathodes.

Construction and validation of nomogram model for predicting the risk of ventricular arrhythmia after emergency PCI in patients with acute myocardial infarction.

OBJECTIVE: To make predictions about the risk of MVA (Malignant Ventricular Arrhythmia) after primary PCI (Percutaneous Coronary Intervention) in patients with AMI (Acute Myocardial Infarction) through constructing and validating the Nomogram model. METHODS: 311 AMI patients who suffered from emergency PCI in Hefei Second People's Hospital from January 2020 to May 2023 were selected as the training set; 253 patients suffering from the same symptom in Hefei First People's Hospital during the same period were selected as the validation set. Risk factors were further screened by means of multivariate logistic and stepwise regression. The nomogram model was constructed, and then validated by using C-index, ROC curve, decision curve and calibration curve. RESULTS: Multivariate logistic analysis revealed that urea, systolic pressure, hypertension, Killip class II-IV, as well as LVEF (Left Ventricular Ejection Fraction) were all unrelated hazards for MVA after emergency PCI for AMI (P<0.05); a risk prediction nomogram model was constructed. The C-index was calculated to evaluate the predictive ability of the model. Result showed that the index of the training and the validation set was 0.783 (95% CI: 0.726-0.84) and 0.717 (95% CI: 0.65-0.784) respectively, which suggested that the model discriminated well. Meanwhile, other tools including ROC curve, calibration curve and decision curve also proved that this nomogram plays an effective role in forecasting the risk for MVA after PCI in AMI patients. CONCLUSIONS: The study successfully built the nomogram model and made predictions for the development of MVA after PCI in AMI patients.

Analysis for Causes of Corneal Melt After the Boston Keratoprosthesis Type I: The Chinese People's Liberation Army General Hospital Experience.

PURPOSE: The purpose of this study was to evaluate the long-term incidence, risk factors, and the management of corneal melt following Boston type I keratoprosthesis (B-KPro I) implantation. METHODS: This is a retrospective observational case series. Data were collected regarding demographics, preoperative characteristics, incidence, and outcomes of corneal melt in 102 patients who underwent B-KPro I in the Chinese PLA General Hospital between 2011 and 2018, with a follow-up period ranging from 4 to 11 years. RESULTS: Chemical burn was the most common indication for B-KPro I (n = 56; 53.8%), followed by ocular trauma (n = 26; 25.0%). During the follow-up period (107 ± 25.7 months), corneal melt occurred in 60 cases among 37 eyes (35.6%), with an incidence of 20.2% at 1 year after surgery. Fourteen cases presented with recurrent corneal melt. Patients with multiple corneal allograft failures had a higher risk of corneal melt. Thermal burns, compared with alkali burns, significantly elevated the odds ratio (OR) of corneal melt (OR, 5.11; 95% confidence interval, 1.05-24.86; P = 0.043). CONCLUSIONS: Corneal melt significantly reduced the retention time of KPro (P < 0.01), and its coexistence with other complications further shortened the retention time. A specific pattern of corneal melt occurrence was identified, with a peak incidence at 1 year postoperatively. Our findings suggest variations in the risk of corneal melt among different indications, with thermal burns carrying the highest OR. Moreover, each previous failed keratoplasty doubled the risk of corneal melt after B-KPro I.

Antimicrobial therapy based on self-assembling peptides.

The emergence of drug-resistant microorganisms has threatened global health, and microbial infections have severely limited the use of medical materials. For example, the attachment and colonization of pathogenic bacteria to medical implant materials can lead to wound infections, inflammation and complications, as well as implant failure, shortening their lifespan and even resulting in patient death. In the era of antibiotic resistance, antimicrobial drug discovery needs to prioritize unconventional therapies that act on new targets or adopt new mechanisms. In this regard, supramolecular antimicrobial peptides have emerged as attractive therapeutic platforms, both as bactericides for combination antibiotics and as delivery vehicles. By taking advantage of their programmable intermolecular and intramolecular interactions, peptides can be modified to form higher-order structures (including nanofibers and nanoparticles) with unique functionality. This paper begins with an analysis of the relationship between peptide self-assembly and antimicrobial activity, describes in detail the research and development of various self-assembled antimicrobial peptides in recent years, and finally explores different combinatorial strategies for self-assembling antimicrobial peptides.

Identification of candidate genes for adult plant stripe rust resistance transferred from Aegilops ventricosa 2NvS into wheat via fine mapping and transcriptome analysis.

KEY MESSAGE: An adult plant gene for resistance to stripe rust was narrowed down to the proximal one-third of the 2NvS segment translocated from Aegilops ventricosa to wheat chromosome arm 2AS, and based on the gene expression analysis, two candidate genes were identified showing a stronger response at the adult plant stage compared to the seedling stage. The 2NvS translocation from Aegilops ventricosa, known for its resistance to various diseases, has been pivotal in global wheat breeding for more than three decades. Here, we identified an adult plant resistance (APR) gene in the 2NvS segment in wheat line K13-868. Through fine mapping in a segregating near-isogenic line (NIL) derived population of 6389 plants, the candidate region for the APR gene was narrowed down to between 19.36 Mb and 33 Mb in the Jagger reference genome. Transcriptome analysis in NILs strongly suggested that this APR gene conferred resistance to stripe rust by triggering plant innate immune responses. Based on the gene expression analysis, two disease resistance-associated genes within the candidate region, TraesJAG2A03G00588940 and TraesJAG2A03G00590140, exhibited a stronger response to Puccinia striiformis f. sp. tritici (Pst) infection at the adult plant stage than at the seedling stage, indicating that they could be potential candidates for the resistance gene. Additionally, we developed a co-dominant InDel marker, InDel_31.05, for detecting this APR gene. Applying this marker showed that over one-half of the wheat varieties approved in 2021 and 2022 in Sichuan province, China, carry this gene. Agronomic trait evaluation of NILs indicated that the 2NvS segment effectively mitigated the negative effects of stripe rust on yield without affecting other important agronomic traits. This study provided valuable insights for cloning and breeding through the utilization of the APR gene present in the 2NvS segment.

Thermal Conductivity and Sintering Mechanism of Aluminum/Diamond Composites Prepared by DC-Assisted Fast Hot-Pressing Sintering.

A novel DC-assisted fast hot-pressing (FHP) powder sintering technique was utilized to prepare Al/Diamond composites. Three series of orthogonal experiments were designed and conducted to explore the effects of sintering temperature, sintering pressure, and holding time on the thermal conductivity (TC) and sintering mechanism of an Al-50Diamond composite. Improper sintering temperatures dramatically degraded the TC, as relatively low temperatures (≤520 °C) led to the retention of a large number of pores, while higher temperatures (≥600 °C) caused unavoidable debonding cracks. Excessive pressure (≥100 MPa) induced lattice distortion and the accumulation of dislocations, whereas a prolonged holding time (≥20 min) would most likely cause the Al phase to aggregate into clusters due to surface tension. The optimal process parameters for the preparation of Al-50diamond composites by the FHP method were 560 °C-80 MPa-10 min, corresponding to a density and TC of 3.09 g cm-3 and 527.8 W m-1 K-1, respectively. Structural defects such as pores, dislocations, debonding cracks, and agglomerations within the composite strongly enhance the interfacial thermal resistance (ITR), thereby deteriorating TC performance. Considering the ITR of the binary solid-phase composite, the Hasselman-Johnson model can more accurately predict the TC of Al-50diamond composites for FHP technology under an optimal process with a 3.4% error rate (509.6 W m-1 K-1 to 527.8 W m-1 K-1). The theoretical thermal conductivity of the binary composites estimated by data modeling (Hasselman-Johnson Model, etc.) matches well with the actual thermal conductivity of the sintered samples using the FHP method.

Cardiac Multi-Frequency Vibration Signal Sensor Module and Feature Extraction Method Based on Vibration Modeling.

Cardiovascular diseases pose a long-term risk to human health. This study focuses on the rich-spectrum mechanical vibrations generated during cardiac activity. By combining Fourier series theory, we propose a multi-frequency vibration model for the heart, decomposing cardiac vibration into frequency bands and establishing a systematic interpretation for detecting multi-frequency cardiac vibrations. Based on this, we develop a small multi-frequency vibration sensor module based on flexible polyvinylidene fluoride (PVDF) films, which is capable of synchronously collecting ultra-low-frequency seismocardiography (ULF-SCG), seismocardiography (SCG), and phonocardiography (PCG) signals with high sensitivity. Comparative experiments validate the sensor's performance and we further develop an algorithm framework for feature extraction based on 1D-CNN models, achieving continuous recognition of multiple vibration features. Testing shows that the recognition coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) of the 8 features are 0.95, 2.18 ms, and 4.89 ms, respectively, with an average prediction speed of 60.18 us/point, meeting the re-quirements for online monitoring while ensuring accuracy in extracting multiple feature points. Finally, integrating the vibration model, sensor, and feature extraction algorithm, we propose a dynamic monitoring system for multi-frequency cardiac vibration, which can be applied to portable monitoring devices for daily dynamic cardiac monitoring, providing a new approach for the early diagnosis and prevention of cardiovascular diseases.

Genome-wide QTL mapping for agronomic traits in the winter wheat cultivar Pindong 34 based on 90K SNP array.

Introduction: Agronomic traits are key components of wheat yield. Exploitation of the major underlying quantitative trait loci (QTLs) can improve the yield potential in wheat breeding. Methods: In this study, we constructed a recombinant inbred line (RIL) population from Mingxian 169 (MX169) and Pindong 34 (PD34) to determine the QTLs for grain length (GL), grain width (GW), grain length-to-width ratio (LWR), plant height (PH), spike length (SL), grain number per spike (GNS), and the thousand grain weight (TGW) across four environments using wheat 90K SNP array. Results: A QTL associated with TGW, i.e., QTGWpd.swust-6BS, was identified on chromosome 6B, which explained approximately 14.1%-16.2% of the phenotypic variation. In addition, eight QTLs associated with GL were detected across six chromosomes in four different test environments. These were QGLpd.swust-1BL, QGLpd.swust-2BL, QGLpd.swust-3BL.1, QGLpd.swust-3BL.2, QGLpd.swust-5DL, QGLpd.swust-6AL, QGLpd.swust-6DL.1, and QGLpd.swust-6DL.2. They accounted for 9.0%-21.3% of the phenotypic variation. Two QTLs, namely, QGWpd.swust-3BS and QGWpd.swust-6DL, were detected for GW on chromosomes 3B and 6D, respectively. These QTLs explained 12.8%-14.6% and 10.8%-15.2% of the phenotypic variation, respectively. In addition, two QTLs, i.e., QLWRpd.swust-7AS.1 and QLWRpd.swust-7AS.2, were detected on chromosome 7A for the grain LWR, which explained 10.9%-11.6% and 11.6%-11.2% of the phenotypic variation, respectively. Another QTL, named QGNSpd-swust-6DS, was discovered on chromosome 6D, which determines the GNS and which accounted for 11.4%-13.8% of the phenotypic variation. Furthermore, five QTLs associated with PH were mapped on chromosomes 2D, 3A, 5A, 6B, and 7B. These QTLs were QPHpd.swust-2DL, QPHpd.swust-3AL, QPHpd.swust-5AL, QPHpd.swust-6BL, and QPHpd.swust-7BS, which accounted for 11.3%-19.3% of the phenotypic variation. Lastly, a QTL named QSLpd.swust-3AL, conferring SL, was detected on chromosome 3A and explained 16.1%-17.6% of the phenotypic variation. All of these QTLs were defined within the physical interval of the Chinese spring reference genome. Discussion: The findings of this study have significant implications for the development of fine genetic maps, for genomic breeding, and for marker-assisted selection to enhance wheat grain yield.

Impact of Long COVID on Health-Related Quality of Life Among Patients After Acute COVID-19 Infection: A Cross-Sectional Study.

Concerns have been raised globally regarding the long-term effects of the novel coronavirus disease 2019 (COVID-19). This study aimed to investigate the impact of long COVID on the health of patients recovering from acute COVID-19 in China. We conducted a cross-sectional questionnaire survey from 1 February to 9 March 2023. Propensity score matching (PSM) was used to understand the differences in health utility values between individuals with and without long COVID. Factors associated with health-related quality of life (HRQoL) were determined using a multiple linear regression model. A chi-square test was used to compare differences between the 2 groups for each dimension of the EuroQoL-5 Dimension-5 Level (EQ-5D-5L) scale. In total, 307 participants were included in the analysis, of which 40.39% exhibited at least 1 persistent symptom. The common symptoms of long COVID were fatigue/weakness, coughing, memory decline, poor concentration, and phlegm in the throat. Most patients with long COVID reported mild effects from their symptoms. After propensity score matching, the long-COVID group had lower health utility scores than the non-long-COVID group (0.94 vs 0.97). In the multivariable linear regression analysis, persistent symptoms and low annual household income were associated with lower health utility values (P < .05). Anxiety/depression and pain/discomfort were the major problems experienced by the participants with long COVID. Long-COVID symptoms following acute COVID-19 infection have a serious impact on health-related quality of life. Therefore, it is necessary to implement interventions to improve patient health after the recovery from acute COVID-19.

Accurate prediction of solvent flux in sub-1-nm slit-pore nanosheet membranes.

Nanosheet-based membranes have shown enormous potential for energy-efficient molecular transport and separation applications, but designing these membranes for specific separations remains a great challenge due to the lack of good understanding of fluid transport mechanisms in complex nanochannels. We synthesized reduced MXene/graphene hetero-channel membranes with sub-1-nm pores for experimental measurements and theoretical modeling of their structures and fluid transport rates. Our experiments showed that upon complete rejection of salt and organic dyes, these membranes with subnanometer channels exhibit remarkably high solvent fluxes, and their solvent transport behavior is very different from their homo-structured counterparts. We proposed a subcontinuum flow model that enables accurate prediction of solvent flux in sub-1-nm slit-pore membranes by building a direct relationship between the solvent molecule-channel wall interaction and flux from the confined physical properties of a liquid and the structural parameters of the membranes. This work provides a basis for the rational design of nanosheet-based membranes for advanced separation and emerging nanofluidics.

Milk-derived Lactobacillus with high production of short-chain fatty acids relieves antibiotic-induced diarrhea in mice.

Antibiotic-associated diarrhea (AAD) is a common side effect during antibiotic treatment, and this has warranted research into alternative protocols. In this study, we investigated the potential therapeutic effects of three cohorts, Lactobacillus plantarum KLDS 1.0386, Lactobacillus acidophilus KLDS 1.0901 and a mixed strain of both, on intestinal inflammation, the intestinal mucosal barrier, and microbial community in mice with ampicillin-induced diarrhea. The results showed that Lactobacillus inhibited the activation of the TLR4/NF-κB signaling pathway, decreased the expression of pro-inflammatory cytokines, increased the expression of anti-inflammatory cytokines in the murine intestine, and alleviated the intestinal barrier damage and inflammation induced by ampicillin. In addition, Lactobacillus ameliorates intestinal epithelial barrier damage by increasing the expression of tight junction proteins and aquaporins. After Lactobacillus treatment, the diversity of gut microbiota increased significantly, and the composition and function of gut microbiota gradually recovered. In the gut microbiota, Bacteroidetes and Escherichia Shigella related to the synthesis of short-chain fatty acids (SCFAs) were significantly affected by ampicillin, while Lactobacillus regulates the cascade of the microbial-SCFA signaling pathway, which greatly promoted the generation of SCFAs. Collectively, Lactobacillus showed better results in treating AAD, especially in mixed strains.

The Effects of Dietary n-3 Highly Unsaturated Fatty Acids on Growth, Antioxidant Capacity, Immunity, and Oxylipin Profiles in Acipenser dabryanus.

Currently, the effects of dietary levels of n-3 highly unsaturated fatty acids (HUFAs) on the growth performance, antioxidant capacity, immunity, and serum oxylipin profiles of female F2-generation Yangtze sturgeon remain unknown. A total of 75 Yangtze sturgeons, an endangered freshwater fish species, with an average body weight of 3.60 ± 0.83 kg, were randomly allocated to 15 concrete pools, with each dietary group represented by 5 fish per pool. The fish were fed five different experimental diets containing various levels of n-3 HUFAs (0.5%, 1.0%, 1.5%, 2.0%, and 2.4%). After a feeding period of 5 months, no significant differences in the growth performances of the fish were observed among the five dietary groups (p > 0.05). However, we did note that the serum levels of low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), and total cholesterol (TCHO) exhibited a marked increase in the fish that consumed higher dietary n-3 HUFA levels (p < 0.05). Conversely, alkaline phosphatase (ALP) activities showed a notable decrease as dietary n-3 HUFA levels increased (p < 0.05). Serum antioxidant indices, such as the activity levels of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px), were significantly higher in the 2.4% HUFA group compared to the 0.5% HUFA group. Additionally, muscle antioxidant indices, including total antioxidant capacity (T-AOC), catalase (CAT), and SOD activity, exhibited notable increases as dietary n-3 HUFA levels increased (p < 0.05). Furthermore, there was a decrease in malondialdehyde (MDA) levels as dietary n-3 HUFA levels increased (p < 0.05). In relation to immune indices, only serum immunoglobulin M (IgM) and muscle complement 3 (C3) were found to be influenced by dietary n-3 HUFA levels (p < 0.05). A total of 80 oxylipins were quantified, and our subsequent K-means cluster analysis resulted in the classification of 62 oxylipins into 10 subclasses. Among the different n-3 HUFA diets, a total of 14 differential oxylipins were identified in the sera. These findings demonstrate that dietary supplementation with n-3 HUFAs exceeding a 1.0% level can enhance antioxidant capacity and regulate serum lipid metabolism, potentially through modulation of oxylipins derived from ARA, DHA, and EPA. These insights provide novel perspectives on the mechanisms underlying these observations.

Small-molecule targeting PKM2 provides a molecular basis of lactylation-dependent fibroblast-like synoviocytes proliferation inhibition against rheumatoid arthritis.

Fibroblast-like synoviocytes (FLS) play an important role in rheumatoid arthritis (RA)-related swelling and bone damage. Therefore, novel targets for RA therapy in FLS are urgently discovered for improving pathologic phenomenon, especially joint damage and dyskinesia. Here, we suggested that pyruvate kinase M2 (PKM2) in FLS represented a pharmacological target for RA treatment by antimalarial drug artemisinin (ART). We demonstrated that ART selectively inhibited human RA-FLS and rat collagen-induced arthritis (CIA)-FLS proliferation and migration without observed toxic effects. In particular, the identification of targets revealed that PKM2 played a crucial role as a primary regulator of the cell cycle, leading to the heightened proliferation of RA-FLS. ART exhibited a direct interaction with PKM2, resulting in an allosteric modulation that enhances the lactylation modification of PKM2. This interaction further promoted the binding of p300, ultimately preventing the nuclear translocation of PKM2 and inducing cell cycle arrest at the S phase. In vivo, ART obviously suppressed RA-mediated synovial hyperplasia, bone damage and inflammatory response to further improve motor behavior in CIA-rats. Taken together, these findings indicate that directing interventions towards PKM2 in FLS could offer a hopeful avenue for pharmaceutical treatments of RA through the regulation of cell cycle via PKM2 lactylation.

Lymph node dissection in small-sized pulmonary metastasectomy: Impact on the long-term survival.

INTRODUCTION: Pulmonary metastasectomy has been clarified in improving long-term survival in most primary malignancies with pulmonary metastasis, while the role of additional lymph node dissection remained controversial. We aimed to investigate the prognosis of lymph node involvement and identify the role of lymph node dissection during pulmonary metastasectomy in a real-world cohort. METHODS: We identified patients diagnosed with pulmonary metastases with ≤3 cm in size and received pulmonary metastasectomy between 2004 and 2017 in the Surveillance, Epidemiology, and End Results database. We compared the survival via Kaplan-Meier analysis and propensity score matching method, and the multivariable analysis was conducted by cox regression analysis. RESULTS: A total of 3452 patients were included, of which 2268(65.7%) received lymph node dissection, and the incidence of node-positive was 11.3%(256/2268). In total, the median overall survival was 62.8 months(interquartile range, 28.6-118.9 months), and the lymph node involvement was referred to an impaired survival compared to node-negative diseases(5-year overall survival rate, 58.0% versus 38.6%), with comparable survival between N1 and N2 diseases(P = 0.774). Lymph node dissection was associated with improved survival(HR = 0.80; 95%CI, 0.71-0.90; P < 0.001), and the survival benefits remained regardless of age, sex, the number of metastases, and surgical procedures, even in those with node-negative diseases. At least eight LNDs might lead to a significant improvement in survival, and additional survival benefits might be limited with additional dissected lymph nodes. CONCLUSIONS: Lymph node involvement was associated with impaired survival, and lymph node dissection during pulmonary metastasectomy could improve long-term survival and more accurate staging.

Silver Surface-Assisted Dehydrobrominative Cross-Coupling between Identical Aryl Bromides.

Cross-coupling reactions represent an indispensable tool in chemical synthesis. An intriguing challenge in this field is to achieve selective cross-coupling between two precursors with similar reactivity or, to the limit, the identical molecules. Here we report an unexpected dehydrobrominative cross-coupling between 1,3,5-tris(2-bromophenyl)benzene molecules on silver surfaces. Using scanning tunneling microscopy, we examine the reaction process at the single-molecular level, quantify the selectivity of the dehydrobrominative cross-coupling, and reveal the modulation of selectivity by substrate lattice-related catalytic activity or molecular assembly effect. Theoretical calculations indicate that the dehydrobrominative cross-coupling proceeds via regioselective C-H bond activation of debrominated TBPB and subsequent highly selective C-C coupling of the radical-based intermediates. The reaction kinetics plays an important role in the selectivity for the cross-coupling. This work not only expands the toolbox for chemical synthesis but also provides important mechanistic insights into the selectivity of coupling reactions on the surface.

Wind Aggregation Enhanced Triboelectric-Electromagnetic Hybrid Generator with Slit Effect.

It is of great significance to establish a low-cost, high-efficiency, self-powered micrometeorological monitoring system for agriculture, animal husbandry, and transportation. However, each additional detection element in the meteorological monitoring system increases the power consumption of the whole system by about 0.7 W. As a renewable energy technology, a triboelectric nanogenerator has the advantages of low price and self-powered sensing. To reduce the power consumption of the micrometeorological monitoring system, this work introduces an innovative solution: the wind-gathering enhanced triboelectric-electromagnetic hybrid generator (WGE-TEHG). Coupling the thin-film vibrating triboelectric nanogenerator (TENG) and electromagnetic generator (EMG), the TENG is used to monitor wind direction and the EMG is used to monitor wind speed and provide energy needed by the system. In particular, the TENG can be used as a self-powered sensor to reduce the power consumption of the sensing system. Besides, the TENG is used to produce slit effect to enhance the output performance of EMG. The experimental results show that the WGE-TEHG can build a self-powered natural environment micrometeorological sensing system. It can monitor the wind direction, wind speed, temperature, and relative humidity. This research has great application value for the self-powered sensing implementation of a hybrid TENG and EMG.

Deciphering carbon emissions in urban sewer networks: Bridging urban sewer networks with city-wide environmental dynamics.

As urbanization accelerates, understanding and managing carbon emissions from urban sewer networks have become crucial for sustainable urban water cycles. This review examines the factors influencing greenhouse gas (GHG) emissions within urban sewage systems, analyzing the complex effects between water quality, hydrodynamics, and sewer infrastructure on GHG production and emission processes. It reveals significant spatiotemporal heterogeneity in GHG emissions, particularly under long-term scenarios where flow rates and temperatures exhibit strong impacts and correlations. Given the presence of fugitive and dissolved potential GHGs, standardized monitoring and accounting methods are deemed essential. Advanced modeling techniques emerge as crucial tools for large-scale carbon emission prediction and management. The review identifies that traditional definitions and computational frameworks for carbon emission boundaries fail to fully consider the inherent heterogeneity of sewers and the dynamic changes and impacts of multi-source pollution within the sewer system during the urban water cycle. This includes irregular fugitive emissions, the influence of stormwater systems, climate change, geographical features, sewer design, and the impacts of food waste and antibiotics. Key strategies for emission management are discussed, focusing on the need for careful consideration of approaches that might inadvertently increase global emissions, such as ventilation, chemical treatments, and water management practices. The review advocates for an overarching strategy that encompasses a holistic view of carbon emissions, stressing the importance of refined emission boundary definitions, novel accounting practices, and comprehensive management schemes in line with the water treatment sector's move towards carbon neutrality. It champions the adoption of interdisciplinary, technologically advanced solutions to mitigate pollution and reduce carbon emissions, emphasizing the importance of integrating cross-scale issues and other environmentally friendly measures in future research directions.

Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction.

PURPOSE: To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). METHODS AND MATERIALS: A total of 114 brain metastases (BMs) from 82 patients were evaluated, including 26 BMs that developed biopsy-confirmed local failure post-SRS. The SRS spatial dose distribution (Dmap) of each BM was registered to the planning contrast-enhanced T1 (T1-CE) magnetic resonance imaging (MRI). Axial slices of the Dmap, T1-CE, and planning target volume (PTV) segmentation (PTVseg) intersecting the BM center were extracted within a fixed field of view determined by the 60% isodose volume in Dmap. A spherical projection was implemented to transform planar image content onto a spherical surface using multiple projection centers, and the resultant T1-CE/Dmap/PTVseg projections were stacked as a 3-channel variable. Four Visual Geometry Group (VGG-19) deep encoders were used in an ensemble design, with each submodel using a different spherical projection formula as input for BM outcome prediction. In each submodel, clinical features after positional encoding were fused with VGG-19 deep features to generate logit results. The ensemble's outcome was synthesized from the 4 submodel results via logistic regression. In total, 10 model versions with random validation sample assignments were trained to study model robustness. Performance was compared with (1) a single VGG-19 encoder, (2) an ensemble with a T1-CE MRI as the sole image input after projections, and (3) an ensemble with the same image input design without clinical feature inclusion. RESULTS: The ensemble model achieved an excellent area under the receiver operating characteristic curve (AUCROC: 0.89 ± 0.02) with high sensitivity (0.82 ± 0.05), specificity (0.84 ± 0.11), and accuracy (0.84 ± 0.08) results. This outperformed the MRI-only VGG-19 encoder (sensitivity: 0.35 ± 0.01, AUCROC: 0.64 ± 0.08), the MRI-only deep ensemble (sensitivity: 0.60 ± 0.09, AUCROC: 0.68 ± 0.06), and the 3-channel ensemble without clinical feature fusion (sensitivity: 0.78 ± 0.08, AUCROC: 0.84 ± 0.03). CONCLUSIONS: Facilitated by the spherical image projection method, a deep ensemble model incorporating Dmap and clinical variables demonstrated excellent performance in predicting BM post-SRS local failure. Our novel approach could improve other radiation therapy outcome models and warrants further evaluation.

Analytical Gradient Using Cluster-in-Molecule RI-MP2 Method for the Geometry Optimizations of Large Systems.

We present an efficient analytical energy gradient algorithm for the cluster-in-molecule resolution-of-identity second-order Møller-Plesset perturbation (CIM-RI-MP2) method based on the Lagrange multiplier method. Our algorithm independently constructs the Lagrangian formalism within each cluster, avoiding the solution of the coupled-perturbed Hartree-Fock (CPHF) equation for the whole system. Due to this feature, the computational cost of the CIM-RI-MP2 gradients is much lower than that of other local MP2 algorithms. Benchmark calculations of several molecules containing up to 312 atoms demonstrate the general applicability of our CIM-RI-MP2 gradient algorithm. The optimized structure of a 244-atom molecule using the CIM-RI-MP2 method with the cc-pVDZ basis set is in good agreement with the corresponding crystal structure. A single-point gradient calculation conducted for a molecular cage containing 972 atoms and 9612 basis functions takes 48 h on 25 nodes, utilizing a total of 600 CPU cores. The present CIM-RI-MP2 gradient program is applicable for obtaining the optimized geometries of large systems with hundreds of atoms.