Optimizing the placement of medical wastewater outlets in sewer systems to reduce chemical consumption at wastewater treatment plants.

The severely low influent chemical oxygen demand (COD) concentration at wastewater treatment plants (WWTPs) has become a critical issue. A key factor is the excessive biodegradation of organic matter by microbial communities within sewer systems. Intense disinfection commonly adopted for medical wastewater leads to abundant residual chlorine entering sewers, likely causing significant changes in microbial communities and sewage quality in sewers, yet our understanding is limited. Through long-term sewer simulation batch tests, this study revealed the response mechanism of microbial communities to residual chlorine and its impact on organic matter concentration in sewage. Under residual chlorine stress, microbial community structure rapidly changed, and more complex microbial interactions were observed. Besides, pathways related to stress response such as two-component system were significantly enriched; pathways related to energy metabolism (such as carbon fixation in prokaryotes and citrate cycle) in microbial communities were inhibited, and carbon metabolism shifted from the Embden-Meyerhof pathway to the pentose phosphate pathway to enhance cellular reducing power, reduce oxidative stress, and consequently decrease organic matter degradation. Therefore, compared to sewers with normal disinfection, concentrations of COD and dissolved organic carbon in sewage under chlorine stress increased by 12.6 % and 7.4 %, respectively. Besides, the decay and transformation of residual chlorine in sewers were explored. These findings suggest a new approach to medical wastewater discharge management: placing the medical wastewater outlet at the upstream in sewer systems, which ensures that residual chlorine consumption reaches maximum during long-distance transportation, mitigating its harmful effects on WWTPs, and increases the influent organic matter concentration, thereby reducing the need for additional carbon sources.

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.

Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical aspects of clinical study design and biomarker discovery but also ensures that the 'right patient' receives the 'right treatment'. However, survival prediction is a highly complex task, given the large number of 'omics; and clinical features, as well as the high degree of freedom that drive patient survival. Prior knowledge could play a critical role in uncovering the complexity of a disease and understanding the driving factors affecting a patient's survival. We introduce a methodology for incorporating prior knowledge into machine learning-based models for prediction of patient survival through Knowledge Graphs, demonstrating the advantage of such an approach for NSCLC patients. Using data from patients treated with immuno-oncologic therapies in the POPLAR (NCT01903993) and OAK (NCT02008227) clinical trials, we found that the use of knowledge graphs yielded significantly improved hazard ratios, including in the POPLAR cohort, for models based on biomarker tumor mutation burden compared with those based on knowledge graphs. Use of a model-defined mutational 10-gene signature led to significant overall survival differentiation for both trials. We provide parameterized code for incorporating knowledge graphs into survival analyses for use by the wider scientific community.

Rapid detection of ceftriaxone-resistant Salmonella by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry combined with the ratio of optical density.

BACKGROUND: The increased resistance rate of Salmonella to third-generation cephalosporins represented by ceftriaxone (CRO) may result in the failure of the empirical use of third-generation cephalosporins for the treatment of Salmonella infection in children. The present study was conducted to evaluate a novel method for the rapid detection of CRO-resistant Salmonella (CRS). METHODS: We introduced the concept of the ratio of optical density (ROD) with and without CRO and combined it with matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) to establish a new protocol for the rapid detection of CRS. RESULTS: The optimal incubation time and CRO concentration determined by the model strain test were 2 h and 8 µg/ml, respectively. We then conducted confirmatory tests on 120 clinical strains. According to the receiver operating characteristic curve analysis, the ROD cutoff value for distinguishing CRS and non-CRS strains was 0.818 [area under the curve: 1.000; 95% confidence interval: 0.970-1.000; sensitivity: 100.00%; specificity: 100%; P < 10- 3]. CONCLUSIONS: In conclusion, the protocol for the combined ROD and MALDI-TOF MS represents a rapid, accurate, and economical method for the detection of CRS.

Predicting progression-free survival in patients with epithelial ovarian cancer using an interpretable random forest model.

Prognostic models play a crucial role in providing personalised risk assessment, guiding treatment decisions, and facilitating the counselling of patients with cancer. However, previous imaging-based artificial intelligence models of epithelial ovarian cancer lacked interpretability. In this study, we aimed to develop an interpretable machine-learning model to predict progression-free survival in patients with epithelial ovarian cancer using clinical variables and radiomics features. A total of 102 patients with epithelial ovarian cancer who underwent contrast-enhanced computed tomography scans were enrolled in this retrospective study. Pre-surgery clinical data, including age, performance status, body mass index, tumour stage, venous blood cancer antigen-125 (CA125) level, white blood cell count, neutrophil count, red blood cell count, haemoglobin level, and platelet count, were obtained from medical records. The volume of interest for each tumour was manually delineated slice-by-slice along the boundary. A total of 2074 radiomic features were extracted from the pre- and post-contrast computed tomography images. Optimal radiomic features were selected using the Least Absolute Shrinkage and Selection Operator logistic regression. Multivariate Cox analysis was performed to identify independent predictors of three-year progression-free survival. The random forest algorithm developed radiomic and combined models using four-fold cross-validation. Finally, the Shapley additive explanation algorithm was applied to interpret the predictions of the combined model. Multivariate Cox analysis identified CA-125 levels (P = 0.015), tumour stage (P = 0.019), and Radscore (P < 0.001) as independent predictors of progression-free survival. The combined model based on these factors achieved an area under the curve of 0.812 (95 % confidence interval: 0.802-0.822) in the training cohort and 0.772 (95 % confidence interval: 0.727-0.817) in the validation cohort. The most impactful features on the model output were Radscore, followed by tumour stage and CA-125. In conclusion, the Shapley additive explanation-based interpretation of the prognostic model enables clinicians to understand the reasoning behind predictions better.

Insights Into the Patient Experience of Hormone Therapy for Early Breast Cancer Treatment Using Patient Forum Discussions and Natural Language Processing.

PURPOSE: Understanding the real-world experience of patients with early breast cancer (eBC) is imperative for optimizing outcomes and evolving patient care. However, there is a lack of patient-level data, hindering clinical development. This social listening study was performed to understand patient insights into symptoms and impacts of hormone therapy (HT) for eBC using posts from patient forums on breastcancer.org to inform future clinical research. METHODS: Natural language processing (NLP) and machine learning techniques were used to identify themes related to eBC from a sample of 500,000 posts. After relevant data selection, 362,074 eBC posts were retained for further analysis of symptoms and impacts related to HT, as well as insights into symptom severity, pain locations, and symptom management using exercise and yoga. RESULTS: Overall, 32 symptoms and nine impacts had significant associations with ≥one HT. Hot flush (relative risk [RR], 6.70 [95% CI, 3.36 to 13.36]), arthralgia (RR, 6.67 [95% CI, 3.53 to 12.59]), weight increased (RR, 4.83 [95% CI, 3.20 to 7.28]), mood swings (RR, 7.36 [95% CI, 5.75 to 9.42]), insomnia (RR, 4.76 [95% CI, 3.14 to 7.22]), and depression (RR, 3.05 [95% CI, 1.71 to 5.44]) demonstrated the strongest associations. Severe headache, dizziness, back pain, and muscle spasms showed significant associations with ≥one HT despite their low overall prevalence in eBC posts. CONCLUSION: The social listening approach allowed the identification of real-world insights from posts specific to eBC HT from a large-scale online breast cancer forum that captured experiences from a uniquely diverse group of patients. Using NLP has a potential to scale analysis of patient feedback and reveal actionable insights into patient experiences of treatment that can inform the development of future therapies and improve the care of patients with eBC.

Initial soil condition, stand age, and aridity alter the pathways for modifying the soil carbon under afforestation.

Afforestation is a crucial pathway for ecological restoration and has the potential to modify soil microbial community, thereby impacting the cycling and accumulation of carbon in soil across diverse patterns. However, the overall patterns of how afforestation impacts below-ground carbon cycling processes remain uncertain. In this comprehensive meta-analysis, we systematically evaluated 7045 observations from 210 studies worldwide to evaluate the influence of afforestation on microbial communities, enzyme activities, microbial functions, and associated physicochemical properties of soils. Afforestation increases microbial biomass, carbon and nitrogen hydrolase activities, and microbial respiration, but not carbon oxidase activity and nitrogen decomposition rate. Conversely, afforestation leads to a reduction in the metabolic quotient, with significant alteration of bacterial and fungal community structures and positive effects on the fungi: bacteria ratio rather than alpha and beta diversity metrics. We found a total 77 % increase in soil organic carbon (SOC) content after afforestation, which varied depending on initial SOC content before afforestation, afforestation stand age, and aridity index of afforestation sites. The modified SOC is associated with bacterial community composition along with intracellular metabolic quotient and extracellular carbon degrading enzyme activity playing a role. These findings provide insights into the pathways through which afforestation affects carbon cycling via microorganisms, thus improving our knowledge of soil carbon reservoir's responses to afforestation under global climate change.

Subfunctionalisation and self-repression of duplicated E1 homologues finetunes soybean flowering and adaptation.

Soybean is a photoperiod-sensitive staple crop. Its photoperiodic flowering has major consequences for latitudinal adaptation and grain yield. Here, we identify and characterise a flowering locus named Time of flower 4b (Tof4b), which encodes E1-Like b (E1Lb), a homologue of the key soybean floral repressor E1. Tof4b protein physically associates with the promoters of two FLOWERING LOCUS T (FT) genes to repress their transcription and delay flowering to impart soybean adaptation to high latitudes. Three E1 homologues undergo subfunctionalisation and show differential subcellular localisation. Moreover, they all possess self-repression capability and each suppresses the two homologous counterparts. Subfunctionalisation and the transcriptional regulation of E1 genes collectively finetune flowering time and high-latitude adaptation in soybean. We propose a model for the functional fate of the three E1 genes after the soybean whole-genome duplication events, refine the molecular mechanisms underlying high-latitude adaption, and provide a potential molecular-breeding resource.

Direct design of ground-state probabilistic logic using many-body interactions for probabilistic computing.

In this work, an innovative design model aimed at enhancing the efficacy of ground-state probabilistic logic with a binary energy landscape (GSPL-BEL) is presented. This model enables the direct conversion of conventional CMOS-based logic circuits into corresponding probabilistic graphical representations based on a given truth table. Compared to the conventional approach of solving the configuration of Ising model-basic probabilistic gates through linear programming, our model directly provides configuration parameters with embedded many-body interactions. For larger-scale probabilistic logic circuits, the GSPL-BEL model can fully utilize the dimensions of many-body interactions, achieving minimal node overhead while ensuring the simplest binary energy landscape and circumventing additional logic synthesis steps. To validate its effectiveness, hardware implementations of probabilistic logic gates were conducted. Probabilistic bits were introduced as Ising cells, and cascaded conventional XNOR gates along with passive resistor networks were precisely designed to realize many-body interactions. HSPICE circuit simulation results demonstrate that the probabilistic logic circuits designed based on this model can successfully operate in free, forward, and reverse modes, exhibiting the simplest binary probability distributions. For a 2-bit × 2-bit integer factorizer involving many-body interactions, compared to the logic synthesis approach, the GSPL-BEL model significantly reduces the number of consumed nodes, the solution space (in the free-run mode), and the number of energy levels from 12, 4096, and 9-8, 256, and 2, respectively. Our findings demonstrate the significant potential of the GSPL-BEL model in optimizing the structure and performance of probabilistic logic circuits, offering a new robust tool for the design and implementation of future probabilistic computing systems.

Correction: Current overview on the genetic basis of key genes involved in soybean domestication.

[This corrects the article DOI: 10.1007/s42994-022-00074-5.].

Widespread Antioxidants during Storm Events Could Serve as Precursors of Regulated, Priority, and New Disinfection Byproducts.

Widely used antioxidants can enter the environment via urban stormwater systems and form disinfection byproducts (DBPs) during chlorination in downstream drinking water processes. Herein, we comprehensively investigated the occurrence of 39 antioxidants from stormwater runoff to surface water. After a storm event, the concentrations of the antioxidants in surface water increased by 1.4-fold from 102-110 ng/L to 128-139 ng/L. Widespread antioxidants during the stormwater event could transform into toxic DBPs during disinfection. Moreover, the yields of trihalomethanes, haloacetaldehydes, haloacetonitriles (HANs), and halonitromethanes during the chlorination of widely used antioxidants considerably increased with an increasing chlorine dose and contact time. Specifically, the yields of dichloroacetonitrile during the chlorination of diphenylamine (DPA) and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) were higher than those of most reported amino acid precursors, indicating that DPA and 6PPD might be important precursors of HANs. Exploring the intermediates using GC × GC-time-of-flight high-resolution mass spectrometry helped reveal potential pathways from DPA to HANs, whose formation could be attributed to the intermediate carbazole and indole moieties detected in this study. This study provides insights into the transport and transformation of commonly used antioxidants in a water environment and during water treatment processes, highlighting the potential risks of anthropogenic pollutants from a DBP perspective.

Acquired immune thrombotic thrombocytopenic purpura (TTP) associated with inactivated COVID-19 vaccine CoronaVac.

Corona virus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has affected the whole world. Acquired thrombotic thrombocytopenic purpura (TTP) has been reported after administration of mRNA- or adenoviral vector-based COVID-19 vaccines, including Ad26.COV2-S, BNT162b2, mRNA-1273, and ChAdOx1 nCov-19. However, whether inactivated vaccines, such as CoronaVac, could cause TTP and whether the symptoms in TTPs caused by inactivated vaccines are different from previously reported cases are unknown. In this study, two cases were reported. Both cases developed TTP after the second CoronaVac vaccination shot, but not the first. They demonstrated symptoms of fever, neurological abnormalities, renal dysfunction, thrombocytopenia, and hemolysis. Both patients achieved complete remission through several sessions of plasma exchanges and immune suppression. The incidence of TTP in Nanjing area was analyzed. The number of patients with TTP was 12 in 2019, 6 in 2020, 16 in 2021, and 19 in 2022. To the authors' knowledge, this report is the first report of TTP associated with inactivated COVID-19 vaccine (CoronaVac). The rarity and delayed onset may be due to the relatively milder immune response caused by the inactivated vaccines than mRNA-based ones. Timely plasma exchange is a vital treatment for CoronaVac-related TTP, similar to activated vaccine-related TTP.

Sonocatalytic oncolysis microbiota curb intrinsic microbiota lactate metabolism and blockade CD24-Siglec10 immune escape to revitalize immunological surveillance.

Intrinsic lactate retention of chemically- or genetically-engineered bacteria therapy aggravates tumor immunosuppression, which will collaborate with immune escape to cause immunological surveillance failure. To address them, sonocatalytic oncolysis Escherichia coli (E.coli) that chemically chelated anti-CD24 and TiO1+x have been engineered to blockade CD24-siglec10 interaction, regulate microbiota colonization and curb its lactate metabolism, which are leveraged to revitalize immunological surveillance and repress breast cancer. The chemically-engineered E.coli inherited their parent genetic information and expansion function. Therefore, their intrinsic hypoxia tropism and CD24 targeting allow them to specifically accumulate and colonize in solid breast cancer to lyse tumor cells. The conjugated CD24 antibody is allowed to blockade CD24-Siglec10 signaling axis and revitalize immunological surveillance. More significantly, the chelated TiO1+x sonosensitizers produce ROS to render bacteria expansion controllable and curb immunosuppression-associated lactate birth that are usually neglected. Systematic experiments successfully vlaidate hypoxia-objective active targeting, sonocatalytic therapy, microbiota expansion-enabled oncolysis, CD24-Siglec10 communication blockade and precise microbiota abundance & lactate metabolism attenuations. These actions contribute to the potentiated anti-tumor immunity and activated anti-metastasis immune memory against breast cancer development. Our pioneering work provide a route to sonocatalytic cancer immunotherapy.

Soybean hypocotyl elongation is regulated by a MYB33-SWEET11/21-GA2ox8c module involving long-distance sucrose transport.

The length of hypocotyl affects the height of soybean and lodging resistance, thus determining the final grain yield. However, research on soybean hypocotyl length is scarce, and the regulatory mechanisms are not fully understood. Here, we identified a module controlling the transport of sucrose, where sucrose acts as a messenger moved from cotyledon to hypocotyl, regulating hypocotyl elongation. This module comprises four key genes, namely MYB33, SWEET11, SWEET21 and GA2ox8c in soybean. In cotyledon, MYB33 is responsive to sucrose and promotes the expression of SWEET11 and SWEET21, thereby facilitating sucrose transport from the cotyledon to the hypocotyl. Subsequently, sucrose transported from the cotyledon up-regulates the expression of GA2ox8c in the hypocotyl, which ultimately affects the length of the hypocotyl. During the domestication and improvement of soybean, an allele of MYB33 with enhanced abilities to promote SWEET11 and SWEET21 has gradually become enriched in landraces and cultivated varieties, SWEET11 and SWEET21 exhibit high conservation and have undergone a strong purified selection and GA2ox8c is under a strong artificial selection. Our findings identify a new molecular pathway in controlling soybean hypocotyl elongation and provide new insights into the molecular mechanism of sugar transport in soybean.

Mechanism of Bile Acid in Regulating Platelet Function and Thrombotic Diseases.

Platelets play a key role in physiological hemostasis and pathological thrombosis. Based on the limitations of current antiplatelet drugs, it's important to elucidate the mechanisms of regulating platelet activation. In addition to dissolving lipid nutrients, bile acids (BAs) can regulate platelet function. However, the specific mechanisms underlying BAs-mediated effects on platelet activation and thrombotic diseases remain unknown. Therefore, the effects of BAs on platelets and intracellular regulatory mechanisms are explored. It is showed that the inhibitory effect of secondary BAs is more significant than that of primary BAs; lithocholic acid (LCA) shows the highest inhibitory effect. In the process of platelet activation, BAs suppress platelet activation via the spleen tyrosine kinase (SYK), protein kinase B (Akt), and extracellular signal-regulated kinase1/2 (Erk1/2) pathways. Nck adaptor proteins (NCK1) deficiency significantly suppress the activity of platelets and arterial thrombosis. Phosphorylated proteomics reveal that LCA inhibited phosphorylation of syntaxin-11 at S80/81 in platelets. Additional LCA supplementation attenuated atherosclerotic plaque development and reduced the inflammation in mice. In conclusion, BAs play key roles in platelet activation via Syk, Akt, ERK1/2, and syntaxin-11 pathways, which are associated with NCK1. The anti-platelet effects of BAs provide a theoretical basis for the prevention and therapy of thrombotic diseases.

UAV-Assisted Mobile Edge Computing: Dynamic Trajectory Design and Resource Allocation.

The recent advancements of mobile edge computing (MEC) technologies and unmanned aerial vehicles (UAVs) have provided resilient and flexible computation services for ground users beyond the coverage of terrestrial service. In this paper, we focus on a UAV-assisted MEC system in which the UAV equipped with MEC servers is used to assist user devices in computing their tasks. To minimize the weighted average energy consumption and delay in the UAV-assisted MEC system, a LQR-Lagrange-based DDPG (LLDDPG) algorithm, which jointly optimizes the user task offloading and the UAV trajectory design, is proposed. To be specific, the LLDDPG algorithm consists of three subproblems. The DDPG algorithm is used to address the issue of UAV desired trajectory planning, and subsequently, the LQR-based algorithm is employed to achieve the real-time tracking control of UAV desired trajectory. Finally, the Lagrange duality method is proposed to solve the optimization problem of computational resource allocation. Simulation results indicate that the proposed LLDDPG algorithm can effectively improve the system resource management and realize the real-time UAV trajectory design.

The impact of fear of cancer recurrence on the quality of life of breast cancer patients: A longitudinal study of the mediation effect of cortisol and hope.

OBJECTIVE: This longitudinal study sought to explore the impact of cortisol and hope levels on Fear of Cancer Recurrence (FCR) and Quality of Life (QOL) in a cohort of 552 breast cancer patients from three centers in Wuhan City. METHOD: A longitudinal study involving 552 breast cancer patients from three centers in Wuhan City utilized Chinese versions of the Fear of Progression Questionnaire-Short Form (FoP-Q-SF), the Herth Hope Index (HHI), and the Functional Assessment of Cancer Therapy-Breast (FACT-B) scale. Cortisol levels were measured thrice daily, and data was collected longitudinally three times. Data analysis was conducted using SPSS 26.0 and Mplus 8.3, employing a longitudinal path model constructed via the cross-lagged method. RESULTS: The results showed there were significant correlations between FCR, cortisol levels, and QOL at different time points. A significant mediating model was found with outcomes related to hope levels. Specifically, FCR predicted a decrease in hope levels (ß = -0.163, p < 0.001), which in turn led to a decrease in overall QOL (ß = -0.078, p < 0.001), with a mediation effect accounting for 10.34%. Although there were correlations between FCR, cortisol levels, and QOL at different time points, further analysis revealed that cortisol levels did not exhibit a mediating effect between the two (95% confidence interval: -0.002 to 0.001). CONCLUSION: This study demonstrated there were significant correlations among FCR, QOL, and hope levels. Considering hope as a crucial mediator between FCR and QOL, potential intervention strategies for optimizing the QOL of breast cancer patients are proposed.

A Customized Biohybrid Presenting Cascade Responses to Tumor Microenvironment.

Intrinsic characteristics of microorganisms, including non-specific metabolism sites, toxic byproducts, and uncontrolled proliferation constrain their exploitation in medical applications such as tumor therapy. Here, the authors report an engineered biohybrid that can efficiently target cancerous sites through a pre-determined metabolic pathway to enable precise tumor ablation. In this system, DH5α Escherichia coli is engineered by the introduction of hypoxia-inducible promoters and lactate oxidase genes, and further surface-armored with iron-doped ZIF-8 nanoparticles. This bioengineered E. coli can produce and secrete lactate oxidase to reduce lactate concentration in response to hypoxic tumor microenvironment, as well as triggering immune activation. The peroxidase-like functionality of the nanoparticles extends the end product of the lactate metabolism, enabling the conversion of hydrogen peroxide (H2O2) into highly cytotoxic hydroxyl radicals. This, coupled with the transformation of tirapazamine loaded on nanoparticles to toxic benzotriazinyl, culminates in severe tumor cell ferroptosis. Intravenous injection of this biohybrid significantly inhibits tumor growth and metastasis.

Covalent Binding of Reactive Anhydride of Cantharidin to Biological Amines.

Cantharidin is a terpenoid from coleoptera beetles. Cantharidin has been used to treat molluscum contagiosum and some types of tumors. Cantharidin is highly toxic, and cantharidin poisoning and fatal cases have been reported worldwide. The mechanisms underlying cantharidin-induced toxicity remain unclear. Cantharidin contains anhydride, which may react with biologic amines. This study aimed to examine the chemical reactivity of cantharidin toward nucleophiles and characterize adducts of cantharidin with biologic amines in vitro and in mice. Here two types of conjugates were formed in the incubation of cantharidin under physiologic conditions with free amino acids, a mimic peptide, or amine-containing compounds, respectively. Amide-type conjugates were produced by the binding of cantharidin anhydride with the primary amino group of biologic amines. Imide-type conjugates were generated from the dehydration and cyclization of amide-type conjugates. The structure of the conjugates was characterized by using high-resolution mass spectrometry. We introduced the 14N/15N and 79Br/81Br isotope signatures to confirm the formation of conjugates using L-(ε)15N-lysine, L-lysine-15N2, and bromine-tagged hydrazine, respectively. The structure of imide conjugate was also confirmed by nuclear magnetic resonance experiments. Furthermore, the amide and imide conjugates of cantharidin with amino acids or N-acetyl-lysine were detected in mouse liver and urine. Cantharidin was found to modify lysine residue proteins in mouse liver. Pan-cytochrome P450 inhibitor 1-aminobenzotriazole significantly increased the urine cantharidin-N-acetyl-lysine conjugates, whereas it decreased cantharidin metabolites. In summary, cantharidin anhydride can covalently bind to biologic amines nonenzymatically, which facilitates a better understanding of the role of nonenzymatic reactivity in cantharidin poisoning. SIGNIFICANCE STATEMENT: Anhydride moiety of cantharidin can covalently bind to the primary amino group of biological amines nonenzymatically. Amide and imide conjugates were generated after the covalent binding of cantharidin anhydride with the primary amino groups of amino acids, a mimic peptide, and protein lysine residues. The structure of conjugates was confirmed by 14N/15N and 79Br/81Br isotope signatures using isotope-tagged reagents and nuclear magnetic resonance experiments. This study will facilitate the understanding of the role of nonenzymatic reactivity in cantharidin poisoning.

Progesterone Enhances Niraparib Efficacy in Ovarian Cancer by Promoting Palmitoleic-Acid-Mediated Ferroptosis.

Poly (adenosine 5'-diphosphate-ribose) polymerase inhibitors (PARPi) are increasingly important in the treatment of ovarian cancer. However, more than 40% of BRCA1/2-deficient patients do not respond to PARPi, and BRCA wild-type cases do not show obvious benefit. In this study, we demonstrated that progesterone acted synergistically with niraparib in ovarian cancer cells by enhancing niraparib-mediated DNA damage and death regardless of BRCA status. This synergy was validated in an ovarian cancer organoid model and in vivo experiments. Furthermore, we found that progesterone enhances the activity of niraparib in ovarian cancer through inducing ferroptosis by up-regulating palmitoleic acid and causing mitochondrial damage. In clinical cohort, it was observed that progesterone prolonged the survival of patients with ovarian cancer receiving PARPi as second-line maintenance therapy, and high progesterone receptor expression combined with low glutathione peroxidase 4 (GPX4) expression predicted better efficacy of PARPi in patients with ovarian cancer. These findings not only offer new therapeutic strategies for PARPi poor response ovarian cancer but also provide potential molecular markers for predicting the PARPi efficacy.

Wrecking neutrophil extracellular traps and antagonizing cancer-associated neurotransmitters by interpenetrating network hydrogels prevent postsurgical cancer relapse and metastases.

Tumor-promoting niche after incomplete surgery resection (SR) can lead to more aggressive local progression and distant metastasis with augmented angiogenesis-immunosuppressive tumor microenvironment (TME). Herein, elevated neutrophil extracellular traps (NETs) and cancer-associated neurotransmitters (CANTs, e.g., catecholamines) are firstly identified as two of the dominant inducements. Further, an injectable fibrin-alginate hydrogel with high tissue adhesion has been constructed to specifically co-deliver NETs inhibitor (DNase I)-encapsulated PLGA nanoparticles and an unselective ß-adrenergic receptor blocker (propranolol). The two components (i.e., fibrin and alginate) can respond to two triggers (thrombin and Ca2+, respectively) in postoperative bleeding to gelate, shaping into an interpenetrating network (IPN) featuring high strength. The continuous release of DNase I and PR can wreck NETs and antagonize catecholamines to decrease microvessel density, blockade myeloid-derived suppressor cells, secrete various proinflammatory cytokines, potentiate natural killer cell function and hamper cytotoxic T cell exhaustion. The reprogrammed TME significantly suppress locally residual and distant tumors, induce strong immune memory effects and thus inhibit lung metastasis. Thus, targetedly degrading NETs and blocking CANTs enabled by this in-situ IPN-based hydrogel drug depot provides a simple and efficient approach against SR-induced cancer recurrence and metastasis.