Approaches for Enhancing Wastewater Treatment of Photocatalytic Fuel Cells: A Review.

Environmental pollution and energy crises have garnered global attention. The substantial discharge of organic waste into water bodies has led to profound environmental contamination. Photocatalytic fuel cells (PFCs) enabling the simultaneous removal of refractory contaminants and recovery of the chemical energy contained in organic pollutants provides a potential strategy to solve environmental issues and the energy crisis. This review will discuss the fundamentals, working principle, and configuration development of PFCs and photocatalytic microbial fuel cells (PMFCs). We particularly focus on the strategies for improving the wastewater treatment performance of PFCs/PMFCs in terms of coupled advanced oxidation processes, the rational design of high-efficiency electrodes, and the strengthening of the mass transfer process. The significant potential of PFCs/PMFCs in various fields is further discussed in detail. This review is intended to provide some guidance for the better implementation and widespread adoption of PFC wastewater treatment technologies.

Construction and regulation of high active sites in montmorillonite composite catalyst for the removal of ofloxacin via persulfate activation.

In this study, ionic liquids (ILs) were used as organic modifiers by introducing montmorillonite nanolayers containing potential C and N active sites between the montmorillonite nanolayers. Organically modified montmorillonite (ILs-Mt-p) was further prepared by high-temperature pyrolysis under N2 and used for the removal of ofloxacin (OFL) by activated peroxymonosulfate (PMS). Combined with XPS and other characterization analyses, it was found that the catalyst materials prepared from different organic modifiers had similar surface functional groups and graphitized structures, but contained differences in the types and numbers of C and N active sites. The catalyst (3CPC-Mt-p) obtained after pyrolysis of montmorillonite modified with cetylpyridinium chloride (CPC) had optimal catalytic performance, in which graphitic C, graphitic N, and carbonyl group (C[bond, double bond]O) could synergistically promote the activation of PMS by electron transfer, and 77.3 % of OFL could be removed within 60 min. The effects of OFL concentration, initial pH, and anions on the effects of OFL removal by the 3CPC-Mt-p/PMS system were further investigated. Satisfactory degradation results were obtained over a wide pH range. Cl- promoted the system to degrade OFL, while the presence of SO42-, H2PO4- and HA showed some inhibition, but overall the 3CPC-Mt-p catalysts had a strong anti-interference ability, showing good application prospects. The quenching experiments and EPR tests showed that O2-- and 1O2 in the 3CPC-Mt-p/PMS system were the main reactive oxygen species for the degradation of OFL, and •OH was also involved in the reaction. This study provides ideas for the construction and modulation of active sites in mineral materials such as montmorillonite and broadens the application of montmorillonite composite catalysts in advanced oxidation processes for the treatment of antibiotic wastewater.

Size-Dependent Catalysis in Fenton-like Chemistry: From Nanoparticles to Single Atoms.

State-of-the-art Fenton-like reactions are crucial in advanced oxidation processes (AOPs) for water purification. This review explores the latest advancements in heterogeneous metal-based catalysts within AOPs, covering nanoparticles (NPs), single-atom catalysts (SACs), and ultra-small atom clusters. A distinct connection between the physical properties of these catalysts, such as size, degree of unsaturation, electronic structure, and oxidation state, and their impacts on catalytic behavior and efficacy in Fenton-like reactions. In-depth comparative analysis of metal NPs and SACs is conducted focusing on how particle size variations and metal-support interactions affect oxidation species and pathways. The review highlights the cutting-edge characterization techniques and theoretical calculations, indispensable for deciphering the complex electronic and structural characteristics of active sites in downsized metal particles. Additionally, the review underscores innovative strategies for immobilizing these catalysts onto membrane surfaces, offering a solution to the inherent challenges of powdered catalysts. Recent advances in pilot-scale or engineering applications of Fenton-like-based devices are also summarized for the first time. The paper concludes by charting new research directions, emphasizing advanced catalyst design, precise identification of reactive oxygen species, and in-depth mechanistic studies. These efforts aim to enhance the application potential of nanotechnology-based AOPs in real-world wastewater treatment.

Fenton-like activity and pathway modulation via single-atom sites and pollutants comediates the electron transfer process.

The studies on the origin of versatile oxidation pathways toward targeted pollutants in the single-atom catalysts (SACs)/peroxymonosulfate (PMS) systems were always associated with the coordination structures rather than the perspective of pollutant characteristics, and the analysis of mechanism commonality is lacking. In this work, a variety of single-atom catalysts (M-SACs, M: Fe, Co, and Cu) were fabricated via a pyrolysis process using lignin as the complexation agent and substrate precursor. Sixteen kinds of commonly detected pollutants in various references were selected, and their lnkobs values in M-SACs/PMS systems correlated well (R2 = 0.832 to 0.883) with their electrophilic indexes (reflecting the electron accepting/donating ability of the pollutants) as well as the energy gap (R2 = 0.801 to 0.840) between the pollutants and M-SACs/PMS complexes. Both the electron transfer process (ETP) and radical pathways can be significantly enhanced in the M-SACs/PMS systems, while radical oxidation was overwhelmed by the ETP oxidation toward the pollutants with lower electrophilic indexes. In contrast, pollutants with higher electrophilic indexes represented the weaker electron-donating capacity to the M-SACs/PMS complexes, which resulted in the weaker ETP oxidation accompanied with noticeable radical oxidation. In addition, the ETP oxidation in different M-SACs/PMS systems can be regulated via the energy gaps between the M-SACs/PMS complexes and pollutants. As a result, the Fenton-like activities in the M-SACs/PMS systems could be well modulated by the reaction pathways, which were determined by both electrophilic indexes of pollutants and single-atom sites. This work provided a strategy to establish PMS-based AOP systems with tunable oxidation capacities and pathways for high-efficiency organic decontamination.

Achieving synergistic improvement in dielectric and energy storage properties at high-temperature of all-organic composites via physical electrostatic effect.

In response to the increasing demand for miniaturization and lightweight equipment, as well as the challenges of application in harsh environments, there is an urgent need to explore the new generation of high-temperature-resistant film capacitors with excellent energy storage properties. In this study, we report an all-organic composite system based on two polymers with similar densities and high glass transition temperatures, achieving a synergistic effect of dielectric constant and breakdown strength. The preparation of the composite is simple, overcoming the challenge of dispersing nanoparticles in traditional organic-inorganic systems. The high polarity of polyethersulfone can modulate the polarization properties of the composites and, through a physical electrostatic effect, inhibit dipole relaxation, further reducing the current density of the composite dielectric at high temperatures, resulting in a significant improvement in insulating properties. The 9 : 1 composite dielectric at 150 °C demonstrates an energy storage density of up to 6.4 J cm-3 and an efficiency of 82.7%. This study offers a promising candidate material and development direction for the next-generation energy storage capacitors with broad application prospects.

Transcription factors-related molecular subtypes and risk prognostic model: exploring the immunogenicity landscape and potential drug targets in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients. METHODS: RNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs. RESULTS: According to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p < 0.001). Moreover, the area under the ROC curve (AUC) values of the 1-year, 2-year and 3-year survival rates were 0.792, 0.71 and 0.695, respectively. The risk model was validated in the ICGC database. Notably, trametinib sensitivity was highly correlated with the expression of core TFs, and molecular docking predicted the possible binding sites of trametinib with these TFs. More importantly, the expression of core TFs was downregulated under trametinib treatment. CONCLUSIONS: A prognostic signature with 9 TFs performed well in predicting the survival rate and chemotherapy/immunotherapy effect of HCC patients. Trimetinib has potential application value in HCC by targeting TFs.

Apoptosis-related prognostic biomarkers and potential targets for acute kidney injury based on machine learning algorithm and in vivo experiments.

Acute kidney injury (AKI) is a common critical illness in hospitalized patients, characterized by a rapid decline in kidney function over a short period, which can seriously endanger the patient's life. Currently, there is a lack of precise and universal AKI diagnostic biomarkers in clinical practice. In this study, weighted gene coexpression network analysis (WGCNA), differential expression analysis, univariate and multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and immune cell infiltration were performed to identify apoptosis-related biomarkers that can be used for AKI diagnosis. Three core apoptosis-related genes (ARGs), CBFB, EGF and COL1A1, were identified as AKI biomarkers. More importantly, an apoptosis-related signature containing three hub ARGs was validated as a diagnostic model. The hub genes exhibited good correlations with glomerular filtration rate (GFR) and serum creatinine (SCr) in the Nephroseq kidney disease database. Additionally, CIBERSORT immune infiltration analysis indicated that these core ARGs may affect immune cell recruitment and infiltration in AKI patients. Subsequently, we investigated the alteration of the expression levels of three core ARGs in AKI samples using single-cell RNA sequencing analysis and analyzed the cell types that mainly expressed these ARGs. More importantly, the expression of core ARGs was validated in folic acid- and cisplatin-induced AKI mouse models. In summary, our study identified three diagnostic biomarkers for AKI, explored the roles of ARGs in AKI progression and provided new ideas for the clinical diagnosis and treatment of AKI.

Advances in Polymer Dielectrics with High Energy Storage Performance by Designing Electric Charge Trap Structures.

Dielectric capacitors have been developed for nearly a century, and all-polymer film capacitors are currently the most popular. Much effort has been devoted to studying polymer dielectric capacitors and improving their capacitive performance, but their high conductivity and capacitance losses under high electric fields or elevated temperatures are still significant challenges. Although many review articles have reported various strategies to address these problems, to the best of current knowledge, no review article has summarized the recent progress in the high-energy storage performance of polymer-based dielectric films with electric charge trap structures. Therefore, this paper first reviews the charge trap characterization methods for polymeric dielectrics and discusses their strengths and weaknesses. The research progress on the design of charge trap structures in polymer dielectric films, including molecular chain optimization, organic doping, blending modification, inorganic doping, multilayered structures, and the mechanisms of the charge trap-induced enhancement of the capacitive performance of polymers are systematically reviewed. Finally, a summary and outlook on the fundamental theory of charge trap regulation, performance characterization, numerical calculations, and engineering applications are presented. This review provides a valuable reference for improving the insulation and energy storage performance of dielectric capacitive films.

Enhanced degradation of micropollutants by visible light photocatalysts with strong oxygen activation ability.

Visible light photocatalysis is widely considered a sustainable approach to break down micropollutants without chemical addition. To promote the output of photogenerated carriers under visible light, a Z-scheme plasmonic photocatalyst Bi-CeO2/Ag0/BiO2 was designed and fabricated to activate dissolved oxygen in water for micropollutant degradation. The doped Bi not only improved the separation of electron-hole, but also narrowed the band gap of CeO2 to enhance its absorption of visible light. Notably, metallic silver (Ag0) works as an electronic transmission vehicle from Bi-CeO2 to BiO2 in a Z-scheme mechanism. Likewise, the surface plasmon resonance effect of Ag0 also enhanced the absorption of visible light. Furthermore, the Bi doping induced abundant surface oxygen vacancies on CeO2 for enhanced capability and selectivity towards O2 adsorption and activation, which favored the generation of O2•- by photogenerated electrons to degrade sulfamethoxazole, enrofloxacin, and bisphenol A. Theoretical calculation results also confirmed the O2•--driven degradation pathway for sulfamethoxazole. Therefore, the Z-scheme Bi-CeO2/Ag0/BiO2 not only extends the photocatalytic reactivity of CeO2-based catalysts to the visible light range, but also provides a chemical-free method to effectively degrade micropollutants.

Association of childhood adversities with psychosocial difficulties among Chinese children and adolescents.

BACKGROUND: Adverse childhood experiences (ACEs) have been well recognized as risk factors for various adverse outcomes. However, the impacts of ACEs on psychological wellbeing among Chinese children and adolescents are unknown. METHODS: In total, 27 414 participants (6592 Grade 4-6 and 20 822 Grade 7-12 students) were included and information on ACEs and various psychosocial outcomes was collected. We identified subgroups with distinct psychosocial statuses using cluster analysis and logistic regression was applied to measure the associations of ACEs [individual, cumulative numbers by categories or co-occurring patterns identified by using multiple correspondence analysis (MCA)] with item- and cluster-specific psychosocial difficulties. RESULTS: Three and four cluster-based psychosocial statuses were identified for Grade 4-6 and Grade 7-12 students, respectively, indicating that psychosocial difficulties among younger students were mainly presented as changes in relationships/behaviours, whereas older students were more likely featured by deviations in multiple domains including psychiatric symptoms and suicidality. Strongest associations were found for threat-related ACEs (e.g. bullying experiences) with item- or cluster-based psychosocial difficulties (e.g. for cluster-based difficulties, the highest odds ratios = 1.72-2.08 for verbal bullying in Grade 4-6 students and 6.30-12.81 for cyberbullying in Grade 7-12 students). Analyses on cumulative numbers of ACEs and MCA-based ACE patterns revealed similar risk patterns. Additionally, exposure patterns predominated by poor external environment showed significant associations with psychosocial difficulties among Grade 7-12 students but not Grade 4-6 students. CONCLUSIONS: Chinese adolescents faced different psychosocial difficulties that varied by age, all of which were associated with ACEs, particularly threat-related ACEs. Such findings prompt the development of early interventions for those key ACEs to prevent psychosocial adversities among children and adolescents.

Immunogenic landscape and risk score prediction based on unfolded protein response (UPR)-related molecular subtypes in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is the most common type of cancer and causes a significant number of cancer-related deaths worldwide. The molecular mechanisms underlying the development of HCC are complex, and the heterogeneity of HCC has led to a lack of effective prognostic indicators and drug targets for clinical treatment of HCC. Previous studies have indicated that the unfolded protein response (UPR), a fundamental pathway for maintaining endoplasmic reticulum homeostasis, is involved in the formation of malignant characteristics such as tumor cell invasiveness and treatment resistance. The aims of our study are to identify new prognostic indicators and provide drug treatment targets for HCC in clinical treatment based on UPR-related genes (URGs). Methods: Gene expression profiles and clinical information were downloaded from the TCGA, ICGC and GEO databases. Consensus cluster analysis was performed to classify the molecular subtypes of URGs in HCC patients. Univariate Cox regression and machine learning LASSO algorithm were used to establish a risk prognosis model. Kaplan-Meier and ROC analyses were used to evaluate the clinical prognosis of URGs. TIMER and XCell algorithms were applied to analyze the relationships between URGs and immune cell infiltration. Real time-PCR was performed to analyze the effect of sorafenib on the expression levels of four URGs. Results: Most URGs were upregulated in HCC samples. According to the expression pattern of URGs, HCC patients were divided into two independent clusters. Cluster 1 had a higher expression level, worse prognosis, and higher expression of immunosuppressive factors than cluster 2. Patients in cluster 1 were more prone to immune escape during immunotherapy, and were more sensitive to chemotherapeutic drugs. Four key UPR genes (ATF4, GOSR2, PDIA6 and SRPRB) were established in the prognostic model and HCC patients with high risk score had a worse clinical prognosis. Additionally, patients with high expression of four URGs are more sensitive to sorafenib. Moreover, ATF4 was upregulated, while GOSR2, PDIA6 and SRPRB were downregulated in sorafenib-treated HCC cells. Conclusion: The UPR-related prognostic signature containing four URGs exhibits high potential application value and performs well in the evaluation of effects of chemotherapy/immunotherapy and clinical prognosis.

Adverse health consequences of undiagnosed hearing loss at middle age: A prospective cohort study with the UK Biobank.

OBJECTIVES: Hearing impairment is common in the middle-aged population but remains largely undiagnosed and untreated. The knowledge about to what extent and how hearing impairment matters for health is currently lacking. Thus, we aimed to comprehensively examine the adverse health consequences as well as the comorbidity patterns of undiagnosed hearing loss. STUDY DESIGN: Based on the prospective cohort of the UK Biobank, we included 14,620 individuals (median age 61 years) with audiometry-determined (i.e., speech-in-noise test) objective hearing loss and 38,479 individuals with subjective hearing loss (i.e., tested negative but with self-reported hearing problems; median age 58 years) at recruitment (2006-2010), together with 29,240 and 38,479 matched unexposed individuals respectively. MAIN OUTCOME MEASURES: Cox regression was used to determine the associations of both hearing-loss exposures with the risk of 499 medical conditions and 14 cause-specific deaths, adjusting for ethnicity, annual household income, smoking and alcohol intake, exposure to working noise, and BMI. Comorbidity patterns following both exposures were visualized by comorbidity modules (i.e., sets of connected diseases) identified in the comorbidity network analyses. RESULTS: During a median follow-up of 9 years, 28 medical conditions and mortality related to nervous system disease showed significant associations with prior objective hearing loss. Subsequently, the comorbidity network identified four comorbidity modules (i.e., neurodegenerative, respiratory, psychiatric, and cardiometabolic diseases), with the most pronounced association noted for the module related to neurodegenerative diseases (meta-hazard ratio [HR] = 2.00, 95%confidence interval [CI] 1.67-2.39). For subjective hearing loss, we found 57 associated medical conditions, which were partitioned into four modules (i.e., diseases related to the digestive, psychiatric, inflammatory, and cardiometabolic systems), with meta-HRs varying from 1.17 to 1.25. CONCLUSIONS: Undiagnosed hearing loss captured by screening could identify individuals with at greater risk of multiple adverse health consequences, highlighting the importance of screening for speech-in-noise hearing impairment in the middle-aged population, for potential early diagnosis and intervention.

Complete defluorination of perfluorooctanoic acid (PFOA) by ultrasonic pyrolysis towards zero fluoro-pollution.

Advanced oxidation/reduction of PFAS is challenged and concerned by the formation of toxic, short-chain intermediates during water treatments. In this study, we investigated the complete defluorination of PFOA by ultrasound/persulfate (US/PS) with harmless end-products of CO2, H2O, and F‒ ions. We observed 100% defluorination after 4 h of US treatment alone with a power input of 900 W. PS addition, however, suppressed defluorination. We demonstrated by kinetics-fitted Langmuir-type adsorption modeling, the added PS increased competition with PFOA for adsorption sites on the bubble-water interface where radical oxidation and pyrolysis may occur. Providing sulfate (SO4•-) and hydroxyl (•OH) radicals by means other than US did not defluorinate PFOA, indicating that pyrolysis likely contributes to the high defluorination performance. Bond dissociation energies for CC and CF were independent of pressure but decreased at elevated temperatures within cavitation bubbles (i.e., 5000 K) favoring the pyrolysis reactions. Furthermore, bond length calculations indicated that PFOA cleavage only begins to occur at temperatures in excess of those generated at the bubble interface (i.e., >1500 K) at the femtosecond level. This suggests that PFOA vaporizes or injects by nanodrops upon attachment to the cavitation bubble, enters the bubble, and is then cleaved within the bubble by pyrolysis. Our research in low-frequency ultrasonic horn system challenges the previous founding that defluorination of PFOA initiates and occurs at the bubble-water interface. We describe here that supplementing US-based processes with complementary treatments may have undesired effects on the efficacy of US. The mechanistic insights will further promote the implementation of US technology for PFAS treatment in achieving the zero fluoro-pollution goal.

A novel risk score model based on pyroptosis-related genes for predicting survival and immunogenic landscape in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer worldwide, with high incidence and mortality. Pyroptosis, a form of inflammatory-regulated cell death, is closely associated with oncogenesis. METHODS: Expression profiles of HCC were downloaded from the TCGA database and validated using the ICGC and GEO databases. Consensus clustering analysis was used to determine distinct clusters. The pyroptosis-related genes (PRGs) included in the pyroptosis-related signature were selected by univariate Cox regression and LASSO regression analysis. Kaplan-Meier and receiver operating characteristic (ROC) analyses were performed to estimate the prognostic potential of the model. The characteristics of infiltration of immune cells between different groups of HCC were explored. RESULTS: Two independent clusters were identified according to PRG expression. Cluster 2 showed upregulated expression, poor prognosis, increased immune cell infiltration and worse immunotherapy response than cluster 1. A prognostic risk signature consisting of five genes (GSDME, NOD1, PLCG1, NLRP6 and NLRC4) was identified. In the high-risk score group, HCC patients showed decreased survival rates. In particular, multiple clinicopathological characteristics and immune cell infiltration were significantly associated with the risk score. Notably, the 5 PRGs in the risk score have been implicated in carcinogenesis, immunological pathways and drug sensitivity. CONCLUSIONS: A prognostic signature comprising five PRGs can be used as a potential prognostic factor for HCC. The PRG-related signature provides an in-depth understanding of the association between pyroptosis and chemotherapy or immunotherapy for HCC patients.

Prediction of Suicidal Behaviors in the Middle-aged Population: Machine Learning Analyses of UK Biobank.

BACKGROUND: Suicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. OBJECTIVE: We aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. METHODS: Based on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. RESULTS: Individuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low (<1st) genetic susceptibilities groups, respectively. CONCLUSIONS: We established applicable machine learning-based models for predicting both the short- and long-term risk of suicidality with high accuracy across populations of varying genetic risk for suicide, highlighting a cost-effective method of identifying individuals with a high risk of suicidality.

Mortality among twin individuals exposed to loss of a co-twin.

BACKGROUND: Although the death of a child, sibling or spouse has been associated with elevated risk of mortality, less is known about the survival of twin siblings exposed to a co-twin loss. METHODS: In a Swedish population-based sibling-matched cohort, we compared the mortality of 5548 twin individuals who lost their co-twin between 1932 and 2011 with that of 27 740 age-matched and sex-matched twin individuals without such a loss and 6772 full siblings of these exposed twin individuals. Cox regression models were used to estimate the hazard ratios (HRs) of all-cause and cause-specific mortality. RESULTS: We found increased risk of all-cause mortality among twin individuals exposed to a co-twin loss compared with matched unexposed twin individuals (HR = 1.30, 95% CI: 1.18-1.43) and their full siblings (HR = 1.10, 95% CI: 0.96-1.27) after adjusting for multiple covariates. The all-cause mortality risk was greater for loss of a co-twin due to unnatural deaths (HR = 1.54, 95% CI: 1.17-2.03) than natural deaths (HR = 1.26, 95% CI: 1.14-1.40). For cause-specific mortality, co-twin loss was associated with a higher risk of unnatural deaths both among twin individuals who lost their co-twin due to unnatural deaths (HR = 1.98, 95% CI: 1.27-3.10) and those whose loss was due to natural deaths (HR = 1.48, 95% CI: 1.07-2.06). The risk elevations were generally stronger for loss of a monozygotic co-twin than loss of a dizygotic co-twin. CONCLUSION: Loss of a co-twin, especially a monozygotic co-twin, was associated with increased mortality, particularly of unnatural causes, among the surviving twin individuals. The excess mortality is likely attributable to both shared disease susceptibility within the twin pair and the adverse health sequelae of bereavement.

Single atom Mn anchored on N-doped porous carbon derived from spirulina for catalyzed peroxymonosulfate to degradation of emerging organic pollutants.

Highly efficient single atom catalysts are critical to substantially promote for peroxymonosulfate (PMS) activation to organic pollutant degradation, but it remains a challenge at present. Herein, single atom Mn anchored on N-doped porous carbon (SA-Mn-NSC) was synthesized by ball milling of Mn-doped carbon nitride and spirulina biochar to dominantly activate PMS. The precursor of carbon nitride and spirulina possessed a strong coordinating capability for Mn(II), facilitating the formation of highly dispersed nitrogen-coordinated Mn sites (Mn-N4). The SA-Mn-NSC catalyst exhibited high activity and stability in the heterogeneous activation of PMS to degrade a wide range of pollutants within 10 min, showing an outstanding degradation rate constant of 0.31 min-1 in enrofloxacin (ENR) degradation. The high surface density of Mn-N4 sites and abundant interconnected meso-macro pores were highly favorable for activating PMS to produce 1O2 and high-valent manganese (Mn(IV)) for pollutant degradation. This work offers a new pathway of using a low-cost and easily accessible single-atom catalysts (SACs) and could inspire more catalytic oxidation strategies.

The change in the liver volume after direct intrahepatic portocaval shunt in patients with Budd-Chiari syndrome with diffuse hepatic vein occlusion.

PURPOSE: To evaluate the changes in the liver volume and function after direct intrahepatic portocaval shunt (DIPS) in patients with Budd-Chiari syndrome (BCS) with diffuse hepatic vein (HV) occlusion. METHODS: The clinical data of 29 patients with BCS who underwent DIPS for intractable ascites caused by diffuse hepatic vein occlusion in the Affiliated Hospital of Xuzhou Medical University were analysed retrospectively; the patients included 8 males and 21 females, with an average age of 33.3 ± 6.3 years. The patients underwent abdominal CT scanning and liver function examinations before DIPS, and 1 week, 3 months, 6 months and 12 months after DIPS. The changes of the liver volume and liver function before and after DIPS were compared. RESULTS: All 29 patients underwent DIPS successfully. 28 patients survived during the follow-up of 12-33 months, with a median follow-up of 16 months. The patients' liver function were significantly improved at 3, 6 and 12 months after the operation compared to before the operation (P < 0.05). The liver volumes measured before the operation and 1 week, 3 months, 6 months and 12 months after the operation were 2124.586 ± 420.889 cm3, 1926.263 ± 372.268 cm3, 1480.592 ± 183.061 cm3, 1461.904 ± 153.027 cm3 and 1469.286 ± 148.549 cm3, respectively. Compared with the preoperative liver volume, the liver volume had decreased significantly at 1 week, 3 months, 6 months and 12 months after the operation (P < 0.05). However, there was no significant difference in the liver volumes at 6 and 12 months after the operation (P = 0.35). CONCLUSIONS: Direct intrahepatic portocaval shunt has achieved satisfactory clinical results in the treatment of BCS with diffuse hepatic vein occlusion. The congestive hepatomegaly was gradually reduced after the operation. The liver volume (which was defined as the clinical efficacy in this study) remained stable after 6 months.

Development and Validation of a Novel Ferroptosis-Related Gene Signature for Prognosis and Immunotherapy in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a cancer that is sensitive to ferroptosis, and immunotherapy has emerged as a promising treatment for HCC patients. However, the prognostic potential of ferroptosis-related genes (FRGs) and the effect of ferroptosis on the tumor immune microenvironment in HCC remain largely obscure. Here, we analyzed the expression pattern of FRGs using the TCGA, ICGC and GEO databases. The expression of most FRGs was upregulated in HCC tissues compared with normal liver tissues. Three independent clusters were determined by consensus clustering analysis based on FRG expression in HCC. Cluster 3 exhibited higher expression, unfavorable prognosis, and higher histological tumor stage and grade than clusters 1 and 2. CIBERSORT analysis indicated different infiltrating levels of various immune cells among the three clusters. Moreover, most immune checkpoint genes were highly expressed in cluster 3. Univariate Cox regression and LASSO regression analyses were performed to develop a five FRG-based prognostic risk model using the TCGA and ICGC datasets. Kaplan-Meier analysis and ROC curves were performed to verify the prognostic potential of the risk model. A nomogram containing independent prognostic factors was further developed. Compared with low-risk patients, high-risk HCC patients exhibited worse overall survival (OS). In addition, this risk model was significantly correlated with the infiltrating levels of six major types of immune cells in HCC. Finally, the relationships between the five FRGs and drug sensitivity were investigated. The present study suggests that the five FRGs could elucidate the molecular mechanisms of HCC and lead to a new direction for the improvement of predictive, preventive, and personalized medicine for HCC.