Genetic background and intraoperative haemodynamic instability in patients with pheochromocytoma and paraganglioma: a multicenter retrospective study.

BACKGROUND: Perioperative management to maintain intraoperative haemodynamic stability is crucial during surgical treatment of pheochromocytomas and paragangliomas (PPGLs). Although approximately 70% of PPGLs carry pathogenic variants (PVs) in susceptibility genes, whether intraoperative haemodynamic instability (IHI) is associated with genetic background remains unclear. This study aimed to analyse IHI in patients with PPGL due to PVs in different genes. MATERIALS AND METHODS: This retrospective study recruited 756 patients with abdominal PPGL from two tertiary care centres. Clinical information including sex, age, catecholamine-associated signs and symptoms (CAS), tumour location and size, biochemistry, and perioperative characteristics were collected. Genetic mutations were investigated using next-generation sequencing. RESULTS: Among the 671 patients included in the analysis, 61.8% (415/671) had IHI. IHI was significantly associated with genetic background in patients with PPGL. Most (80.9%, 89/110) patients with PPGL due to PVs in HRAS suffered IHI. In contrast, only half (31/62) of patients with PPGL due to PVs in VHL had IHI. In the multivariate regression analysis, compared to those with negative genetic testing results, patients with PPGL due to PVs in HRAS (OR 3.82, 95% CI 2.187-6.679, P<0.001), the other cluster 2 genes (OR 1.95, 95% CI 1.287-2. 569, P< 0.05), and cluster 1 genes other than VHL (OR 2.35, 95% CI 1.338-4.111, P<0.05) were independent risk factors for IHI, while PVs in VHL was not independent risk factor (OR 1.09, 95% CI 0.605-1.953, P>=0.05). In addition, age at diagnosis of primary tumour, presenting of CAS, and tumour size were identified as independent factors for IHI. The nomogram illustrated that genetic background as sharing the largest contribution to IHI, followed by tumour size, age, and presenting of CAS. CONCLUSION: IHI is associated with the genetic background in patients with PPGL. The perioperative management of patients with PPGL can be personalized according to their genetic backgrounds, tumour size, age, and presenting of CAS.

Development of Axially Chiral Pyridylidene Amine Ligands and their Application in Pd-Catalyzed Enantioselective Allylic Substitution.

A series of novel axially chiral pyridylidene amine (PYE) ligands has been developed, and their catalytic capability has been demonstrated in various highly efficient and enantioselective Pd-catalyzed asymmetric allylic substitutions. A density-functional theory (DFT) study explains the preferential enantiocontrol in the key transition states of the axially chiral PYE ligand-promoted Pd-catalyzed allylic alkylation.

Endocrine cancer trends 1990-2021: global disparities and health inequalities.

This study provides a comprehensive analysis of global, continental, and national trends in the prevalence and mortality of prostate cancer (PC), breast cancer (BC), and thyroid cancer (TC). Utilizing 2021 Global Burden of Diseases (GBD2021) data, prevalence and death rates for 2021 were examined, with temporal trends from 1990 to 2021 analyzed via Joinpoint regression. Annual percentage change (APC) and average APC (AAPC) were calculated with 95% confidence intervals (CI). Distributive inequalities were quantified using the slope index of inequality and concentration index. In 2021, PC, BC, and TC showed higher global age-standardized prevalence rates (ASPR) in Europe and America compared to Africa and Asia, while higher age-standardized death rates (ASDR) for PC and BC were noted in Africa. Over the study period, significant global increases in ASPR were observed for PC (AAPC = 0.78, 95% CI: 0.67 to 0.89), BC (AAPC = 0.31, 95% CI: 0.24 to 0.37), and TC (AAPC = 1.42, 95% CI: 1.31 to 1.52). Conversely, ASDR significantly decreased for PC (AAPC = -0.83, 95% CI: -0.92 to -0.74), BC (AAPC = -0.48, 95% CI: -0.56 to -0.39), and TC (AAPC = -0.23, 95% CI: -0.29 to -0.17). Variations were observed across continents and time periods, affecting 204 countries and territories. higher social development index (SDI) levels were associated with a more pronounced burden of these cancers. The findings highlight significant global heterogeneity in prevalence, death rates, and temporal trends of endocrine cancers, with important implications for epidemiology and public health policies.

New perspective for pathomechanism and clinical applications of animal toxins: Programmed cell death.

Various animal toxins pose a significant threat to human safety, necessitating urgent attention to their treatment and research. The clinical potential of programmed cell death (PCD) is widely regarded as a target for envenomation, given its crucial role in regulating physiological and pathophysiological processes. Current research on animal toxins examines their specific components in pathomechanisms and injuries, as well as their clinical applications. This review explores the relationship between various toxins and several types of PCD, such as apoptosis, necroptosis, autophagy, ferroptosis, and pyroptosis, to provide a reference for future understanding of the pathophysiology of toxins and the development of their potential clinical value.

Elucidating the interaction of rhizosphere microorganisms and environmental factors influencing the quality of Polygonatum kingianum Coll. et Hemsl.

Polygonatum kingianum Collett & Hemsl., is one of the most important traditional Chinese medicines in China. The purpose of this study is to investigate the relationship between herb quality and microbial-soil variables, while also examining the composition and structure of the rhizosphere microbial community in Polygonatum kingianum, the ultimate goal is to provide a scientific approach to enhancing the quality of P. kingianum. Illumina NovaSeq technology unlocks comprehensive genetic variation and biological functionality through high-throughput sequencing. And in this study it was used to analyze the rhizosphere microbial communities in the soils of five P. kingianum planting areas. Conventional techniques were used to measure the organic elements, pH, and organic matter content. The active ingredient content of P. kingianum was identified by High Performance Liquid Chromatography (HPLC) and Colorimetry. A total of 12,715 bacterial and 5487 fungal Operational Taxonomic Units (OTU) were obtained and taxonomically categorized into 81 and 7 different phyla. Proteobacteria, Bacteroidetes, and Acidobacteriae were the dominant bacterial phyla Ascomycota and Basidiomycota were the dominat fungal phyla. The key predictors for bacterial community structure included hydrolysable nitrogen and available potassium, while for altering fungal community structure, soil organic carbon content (OCC), total nitrogen content (TNC), and total potassium content (TPOC) were the main influencing factors. Bryobacter and Candidatus Solibacter may indirectly increase the polysaccharide content of P. kingianum, and can be developed as potential Plant Growth Promoting Rhizobacteria (PGPR). This study has confirmed the differences in the soil and microorganisms of different origins of P. kingianum, and their close association with its active ingredients. And it also broadens the idea of studying the link between plants and microorganisms.

Altered sleep onset transition in depression: Evidence from EEG activity and EEG functional connectivity analyses.

OBJECTIVE: Sleep disorders constitute a principal diagnostic criterion for depression, potentially reflecting the abnormal persistence of brain activity during the sleep onset (SO) transition. Here, we sought to explore the differences in the dynamic changes in the EEG activity and the EEG functional connectivity (FC) during the SO transition in depressed patients. METHODS: Overnight polysomnography recordings were obtained from thirty-two depressed patients and thirty-three healthy controls. The multiscale permutation entropy (MSPE) and EEG relative power were extracted to characterize EEG activity, and weighted phase lag index (WPLI) was calculated to characterize EEG FC. RESULTS: The intergroup differences in EEG activity of relative power and MSPE were reversed near SO, which attributed to slower rates of change among depressed patients. Regarding the characteristics of the EEG FC network, depressed patients exhibited significantly higher inter-hemispheric and interregional WPLI values in both delta and alpha bands throughout the SO transition, concomitant with different dynamic properties in the delta band FC. During the process after SO, patients exhibited increased inter-hemispheric long-range links, whereas controls showed more intra-hemispheric ones. Finally, we found significant correlations in the dynamic changes between different EEG measures. CONCLUSIONS: Our research revealed that the abnormal changes during the SO transition in depressed patients were manifested in both homeostatic and dynamic aspects, which were reflected in EEG FC and EEG activity, respectively. SIGNIFICANCE: These findings may elucidate the mechanism underlying sleep disorders in depression from the perspective of neural activity.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors.

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

Coherence-controlled chaotic soliton bunch.

Controlling the coherence of chaotic soliton bunch holds the promise to explore novel light-matter interactions and manipulate dynamic events such as rogue waves. However, the coherence control of chaotic soliton bunch remains challenging, as there is a lack of dynamic equilibrium mechanism for stochastic soliton interactions. Here, we develop a strategy to effectively control the coherence of chaotic soliton bunch in a laser. We show that by introducing a lumped fourth-order-dispersion (FOD), the soliton oscillating tails can be formed and generate the potential barriers among the chaotic solitons. The repulsive force between neighboring solitons enabled by the potential barriers gives rise to an alleviation of the soliton fusion/annihilation from stochastic interactions, endowing the capability to control the coherence in chaotic soliton bunch. We envision that this result provides a promising test-bed for a variety of dynamical complexity science and brings new insights into the nonlinear behavior of chaotic laser sources.

Multi-parameter MRI-Based Machine Learning Model to Evaluate the Efficacy of STA-MCA Bypass Surgery for Moyamoya Disease: A Pilot Study.

Superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery represents the primary treatment for Moyamoya disease (MMD), with its efficacy contingent upon collateral vessel development. This study aimed to develop and validate a machine learning (ML) model for the non-invasive assessment of STA-MCA bypass surgery efficacy in MMD. This study enrolled 118 MMD patients undergoing STA-MCA bypass surgery. Clinical features were screened to construct a clinical model. MRI features were extracted from the middle cerebral artery supply area using 3D Slicer and employed to build five ML models using logistic regression algorithm. The combined model was developed by integrating the radiomics score (Rad-score) with the clinical features. Model performance validation was conducted using ROC curves. Platelet count (PLT) was identified as a significant clinical feature for constructing the clinical model. A total of 3404 features (851 × 4) were extracted, and 15 optimal features were selected from each MRI sequence as predictive factors. Multivariable logistic regression identified PLT and Rad-score as independent parameters used for constructing the combined model. In the testing set, the AUC of the T1WI ML model [0.84 (95% CI, 0.70-0.97)] was higher than that of the clinical model [0.66 (95% CI, 0.46-0.86)] and the combined model [0.80 (95% CI, 0.66-0.95)]. The T1WI ML model can be used to assess the postoperative efficacy of STA-MCA bypass surgery for MMD.

Advances in artificial intelligence for meibomian gland evaluation: A comprehensive review.

Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to evaporative dry eye, significantly impacting visual quality. With a global prevalence estimated at 35.8 %, it presents substantial challenges for clinicians. Conventional manual evaluation techniques for MGD face limitations characterized by inefficiencies, high subjectivity, limited big data processing capabilities, and a dearth of quantitative analytical tools. With rapidly advancing artificial intelligence (AI) techniques revolutionizing ophthalmology, studies are now leveraging sophisticated AI methodologies--including computer vision, unsupervised learning, and supervised learning--to facilitate comprehensive analyses of meibomian gland (MG) evaluations. These evaluations employ various techniques, including slit lamp examination, infrared imaging, confocal microscopy, and optical coherence tomography. This paradigm shift promises enhanced accuracy and consistency in disease evaluation and severity classification. While AI has achieved preliminary strides in meibomian gland evaluation, ongoing advancements in system development and clinical validation are imperative. We review the evolution of MG evaluation, juxtapose AI-driven methods with traditional approaches, elucidate the specific roles of diverse AI technologies, and explore their practical applications using various evaluation techniques. Moreover, we delve into critical considerations for the clinical deployment of AI technologies and envisages future prospects, providing novel insights into MG evaluation and fostering technological and clinical progress in this arena.

CRLNet: A Multimodal Peach Detection Network Based on Cooperative Asymptotic Enhancement and the Fusion of Granularity Refinement.

Accurate peach detection is essential for automated agronomic management, such as mechanical peach harvesting. However, ubiquitous occlusion makes identifying peaches from complex backgrounds extremely challenging. In addition, it is difficult to capture fine-grained peach features from a single RGB image, which can suffer from light and noise in scenarios with dense small target clusters and extreme light. To solve these problems, this study proposes a multimodal detector, called CRLNet, based on RGB and depth images. First, YOLOv9 was extended to design a backbone network that can extract RGB and depth features in parallel from an image. Second, to address the problem of information fusion bias, the Rough-Fine Hybrid Attention Fusion Module (RFAM) was designed to combine the advantageous information of different modes while suppressing the hollow noise at the edge of the peach. Finally, a Transformer-based Local-Global Joint Enhancement Module (LGEM) was developed to jointly enhance the local and global features of peaches using information from different modalities in order to enhance the percentage of information about the target peaches and remove the interference of redundant background information. CRLNet was trained on the Peach dataset and evaluated against other state-of-the-art methods; the model achieved an mAP50 of 97.1%. In addition, CRLNet also achieved an mAP50 of 92.4% in generalized experiments, validating its strong generalization capability. These results provide valuable insights for peach and other outdoor fruit multimodal detection.

Comparative Field Evaluation and Transcriptome Analysis Reveals that Chromosome Doubling Enhances Sheath Blight Resistance in Rice.

Rice sheath blight, caused by Rhizoctonia solani Kihn (R. solani), poses a significant threat to rice production and quality. Autotetraploid rice, developed through chromosome doubling of diploid rice, holds great potential for enhancing biological and yield traits. However, its resistance to sheath blight in the field has remained unclear. In this study, the field resistance of 35 autotetraploid genotypes and corresponding diploids was evaluated across three environments from 2020 to 2021. The booting stage was optimal for inoculating period based on the inoculation and analysis of R. solani at five rice growth stages. We found autotetraploids generally exhibited lower disease scores than diploids, indicating enhanced resistance after chromosome doubling. Among the 35 genotypes, 16 (45.71%) displayed increased resistance, 2 (5.71%) showed decreased resistance, and 17 (48.57%) displayed unstable resistance in different sowing dates. All combinations of the genotype, environment and ploidy, including the genotype-environment-ploidy interaction, contributed significantly to field resistance. Chromosome doubling increased sheath blight resistance in most genotypes, but was also dependent on the genotype-environment interaction. To elucidate the enhanced resistance mechanism, RNA-seq revealed autotetraploid recruited more down-regulated differentially expressed genes (DEGs), additionally, more resistance-related DEGs, were down-regulated at 24 h post inoculation in autotetraploid versus diploid. The ubiquinone/terpenoid quinone and diterpenoid biosynthesis pathways may play key roles in ploidy-specific resistance mechanisms. In summary, our findings shed light on the understanding of sheath blight resistance mechanisms in autotetraploid rice.

Petal-Shaped Graphene Porous Films with Enhanced Absorption-Dominated Electromagnetic Shielding Performance and Mechanical Properties.

The absorption-dominated graphene porous materials, considered ideal for mitigating electromagnetic pollution, encounter challenges related to intricate structural design. Herein, petal-like graphene porous films with dendritic-like and honeycomb-like pores are prepared by controlling the phase inversion process. The theoretical simulation and experimental results show that PVP K30 modified on the graphene surface via van der Waals interactions promotes graphene to be uniformly enriched on the pore walls. Benefiting from the regulation of graphene distribution and the construction of honeycomb pore structure, when 15 wt % graphene is added, the porous film exhibits absorption-dominated electromagnetic shielding performance, compared with the absence of PVP K30 modification. The total electromagnetic shielding effectiveness is 24.1 dB, an increase of 170%; the electromagnetic reflection coefficient reduces to 2.82 dB; The thermal conductivity reaches 1.1 W/(m K), representing a 104% increase. In addition, the porous film exhibits improved mechanical properties, the tensile strength increases to 6.9 MPa, and the elongation at break increases by 131%. The method adopted in this paper to control the enrichment of graphene in the pore walls during the preparation of honeycomb porous films by the phase inversion method can avoid the agglomeration of graphene and improve the overall performance of the porous graphene porous films.

Construction of Zn-Cu bimetallic metal-organic frameworks for carbon dioxide capture.

Bimetallic metal-organic frameworks (MOFs) have shown more impressive performance in gas adsorption compared with monometallic MOFs. Herein, a Cu-Zn bimetallic metal-organic framework (Zn/Cu-BTC) was synthesized via a one-pot method, and its structure, thermal stability and CO2 adsorption property were investigated and compared with those of corresponding monometallic Cu-BTC and Zn-BTC. The results showed that Zn/Cu-BTC has a specific ortho-octahedral crystal morphology with a unique X-ray diffraction peak, the atomic ratio of Zn to Cu is about 1 : 5, and it remained stable at a temperature up to 490 K. In Zn/Cu-BTC, Cu2+ played a role in increasing the specific surface area and porosity of the MOF and improving the gas adsorption performance. The CO2 adsorption of Zn/Cu-BTC is lower than that of Cu-BTC but much higher than that of Zn-BTC, and CO2 adsorption heat was 30.52 kJ mol-1, which indicated physical adsorption. In addition, Zn/Cu-BTC had higher CO2/N2 adsorption selectivity compared with Zn-BTC and Cu-BTC, with a maximum value of 17. This study can be a reference for the research on improving the adsorption selectivity of gases by constructing bimetallic MOFs.

Characteristics of three organic fertilizers and their influence on the mobility of cadmium and arsenic in a soil-rice (Oryza sativa L.) system.

The properties of different organic fertilizers and their potential for stabilizing toxic metals(loids) in soil have not been fully investigated. This study characterized and evaluated three organic fertilizers from different raw materials. The mushroom residue organic fertilizer (MO) had higher C, H, and O contents and more functional groups (-OH, C-H, and C = O). Its application significantly increased pH (1.00 ~ 1.32 units), organic matter (OM) content (26.58 ~ 69.11%), and cation exchange capacity (CEC) (31.52 ~ 39.91%) of soil. MO treatments can simultaneously reduce the bioavailable TCLP-Cd and TCLP-As in soil, solving the difficulties of remediating the combined Cd and As pollution. MO treatments inhibited the migration of Cd and As from soil to plant, promoting plant growth. Redundancy analysis (RDA) revealed that metal(loid) variations in plants were related to soil properties (40.09%) and TCLP-Cd/As (44.74%). Furthermore, the toxic metals(loids) risk assessment for all organic fertilizers was at safe levels. This study provided a valuable reference for choosing organic fertilizers and presented a novel option for the "producing while remediating" of farmlands with low pollution.

Differentiation of tuberculous and brucellar spondylitis using conventional MRI-based deep learning algorithms.

PURPOSE: To investigate the feasibility of deep learning (DL) based on conventional MRI to differentiate tuberculous spondylitis (TS) from brucellar spondylitis (BS). METHODS: A total of 383 patients with TS (n = 182) or BS (n = 201) were enrolled from April 2013 to May 2023 and randomly divided into training (n = 307) and validation (n = 76) sets. Sagittal T1WI, T2WI, and fat-suppressed (FS) T2WI images were used to construct single-sequence DL models and combined models based on VGG19, VGG16, ResNet18, and DenseNet121 network. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. The AUC of DL models was compared with that of two radiologists with different levels of experience. RESULTS: The AUCs based on VGG19, ResNet18, VGG16, and DenseNet121 ranged from 0.885 to 0.973, 0.873 to 0.944, 0.882 to 0.929, and 0.801 to 0.933, respectively, and VGG19 models performed better. The diagnostic efficiency of combined models outperformed single-sequence DL models. The combined model of T1WI, T2WI, and FS T2WI based on VGG19 achieved optimal performance, with an AUC of 0.973. In addition, the performance of all combined models based on T1WI, T2WI, and FS T2WI was better than that of two radiologists (P<0.05). CONCLUSION: The DL models have potential guiding value in the diagnosis of TS and BS based on conventional MRI and provide a certain reference for clinical work.

Gut microorganisms of Locusta migratoria in various life stages and its possible influence on cellulose digestibility.

Locusta migratoria is an important phytophagous pest, and its gut microbial communities play an important role in cellulose degradation. In this study, the gut microbial and cellulose digestibility dynamics of Locusta migratoria were jointly analyzed using high-throughput sequencing and anthrone colorimetry. The results showed that the gut microbial diversity and cellulose digestibility across life stages were dynamically changing. The species richness of gut bacteria was significantly higher in eggs than in larvae and imago, the species richness and cellulose digestibility of gut bacteria were significantly higher in early larvae (first and second instars) than in late larvae (third to fifth instars), and the diversity of gut bacteria and cellulose digestibility were significantly higher in imago than in late larvae. There is a correlation between the dynamics of gut bacterial communities and cellulose digestibility. Enterobacter, Lactococcus, and Pseudomonas are the most abundant genera throughout all life stages. Six strains of highly efficient cellulolytic bacteria were screened, which were dominant gut bacteria. Carboxymethyl cellulase activity (CMCA) and filter paper activity (FPA) experiments revealed that Pseudomonas had the highest cellulase enzyme activity. This study provides a new way for the screening of cellulolytic bacteria and lays the foundation for developing insects with significant biomass into cellulose-degrading bioreactors. IMPORTANCE: Cellulose is the most abundant and cheapest renewable resource in nature, but its degradation is difficult, so finding efficient cellulose degradation methods is an urgent challenge. Locusta migratoria is a large group of agricultural pests, and the large number of microorganisms that inhabit their intestinal tracts play an important role in cellulose degradation. We analyzed the dynamics of Locusta migratoria gut microbial communities and cellulose digestibility using a combination of high-throughput sequencing technology and anthrone colorimetry. The results revealed that the gut microbial diversity and cellulose digestibility were dynamically changed at different life stages. In addition, we explored the intestinal bacterial community of Locusta migratoria across life stages and its correlation with cellulose digestibility. The dominant bacterial genera at different life stages of Locusta migratoria were uncovered and their carboxymethyl cellulase activity (CMCA) and filter paper activity (FPA) were determined. This study provides a new avenue for screening cellulolytic bacteria and lays the foundation for developing insects with significant biomass into cellulose-degrading bioreactors.

Endovascular treatment of aorta-iliac arterial pseudoaneurysm caused by Brucella.

We aimed to analyze the feasibility of endovascular treatment for brucellosis-related aorta-iliac artery pseudoaneurysm. We did a statistical analysis that among the 11 cases, the thoracic aorta was involved in 3 cases, the abdominal aorta was involved in 6 cases, and the iliac artery was involved in 2 cases. Five patients had a history of contact with cattle and sheep, 3 had a history of drinking raw milk, 10 patients had a fever before the operation, and 11 patients had positive serum agglutination test. Blood culture was positive in 2 patients. All patients were given anti-brucellosis treatment immediately after diagnosis. One died of aortic rupture 5 days after emergency endovascular gastrointestinal bleeding. Endovascular-covered stent implantation and active anti-brucellosis therapy were used to treat 10 patients. The follow-up period was 8 years without aortic complications or death for all patients. We think early diagnosis and a combination of anti-brucellosis drugs and endovascular therapy may be the first choice for treating the pseudoaneurysm caused by Brucella.

The role of electrocatalytic materials for developing post-lithium metal||sulfur batteries.

The exploration of post-Lithium (Li) metals, such as Sodium (Na), Potassium (K), Magnesium (Mg), Calcium (Ca), Aluminum (Al), and Zinc (Zn), for electrochemical energy storage has been driven by the limited availability of Li and the higher theoretical specific energies compared to the state-of-the-art Li-ion batteries. Post-Li metal||S batteries have emerged as a promising system for practical applications. Yet, the insufficient understanding of quantitative cell parameters and the mechanisms of sulfur electrocatalytic conversion hinder the advancement of these battery technologies. This perspective offers a comprehensive analysis of electrode parameters, including S mass loading, S content, electrolyte/S ratio, and negative/positive electrode capacity ratio, in establishing the specific energy (Wh kg-1) of post-Li metal||S batteries. Additionally, we critically evaluate the progress in investigating electrochemical sulfur conversion via homogeneous and heterogeneous electrocatalytic approaches in both non-aqueous Na/K/Mg/Ca/Al||S and aqueous Zn||S batteries. Lastly, we provide a critical outlook on potential research directions for designing practical post-Li metal||S batteries.

Carbon performance analysis of upgraded wastewater treatment plants in key control areas of the Ziya River Basin in China.

Wastewater treatment plants (WWTPs) are one of the largest sources of greenhouse gas (GHG) emissions, and they are also one of the largest energy consumption industries in urban systems. With the progression of upgrading and standard-rising, WWTPs both directly and indirectly increase carbon emissions from the increased investments in facilities and usages in electricity as well as chemical agents. Here, we collected operational data from 15 WWTPs in the key control areas of the Ziya River Basin in North China and accounted for the changes in carbon performance at different technical upgrade methods. Results showed that the average carbon emission performance increased by 0.487 kg CO2/m3 after the upgrade. Carbon emissions from electricity consumption, chemical usage, biochemical process and sludge treatment accounted for 42%, 17%, 24%, and 17% of the total improvement in carbon emission performance, respectively. Reducing energy consumption, regulating chemical use and sludge comprehensive utilization are the key to carbon emission reduction. It further proposes that the development of wastewater treatment discharge standards should fully consider the comprehensive utilization of water quality classification. Regions with favorable natural conditions should make full use of their advantages by adopting economically feasible, low-energy-consuming technologies such as constructed wetlands, which offer carbon sequestration and landscaping benefits. This study provides guidance on the selection of technological pathways for pollution reduction and carbon mitigation in the wastewater treatment industry and on achieving sustainable water resource utilization.