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The escalating resistance of agricultural pests to chemical insecticides necessitates the development of novel, efficient, and safe biological insecticides. Conus quercinus, a vermivorous cone snail, yields a crude venom rich in peptides for marine worm predation. This study screened six α-conotoxins with insecticidal potential from a previously constructed transcriptome database of C. quercinus, characterized by two disulfide bonds. These conotoxins were derived via solid-phase peptide synthesis (SPPS) and folded using two-step iodine oxidation for further insecticidal activity validation, such as CCK-8 assay and insect bioassay. The final results confirmed the insecticidal activities of the six α-conotoxins, with Qc1.15 and Qc1.18 exhibiting high insecticidal activity. In addition, structural analysis via homology modeling and functional insights from molecular docking offer a preliminary look into their potential insecticidal mechanisms. In summary, this study provides essential references and foundations for developing novel insecticides.

Both UV spectrophotometry and dynamic light scattering techniques present substantial limitations in characterizing mixed colloid size distributions, challenging their transport studies. We developed a synthetic DNA‐labeling/qPCR approach to distinguish mixed colloids (0.05, 0.5, and 5 μm) transport in porous media. Contrary to single‐size systems where larger colloids (5 μm) were more retained, mixed‐size systems showed higher retention of smaller colloids (0.05 μm). Scanning electron microscopy and filtration analyses revealed size‐dependent heteroaggregation, where smaller colloids deposited on larger ones, forming pore‐blocking aggregates. HYDRUS‐1D simulations identified three governing factors: pore size, surface potential, and media heterogeneity. These findings demonstrate: (a) mixed colloid transport cannot be predicted from monodisperse system behavior and (b) high‐resolution tracking is essential for accurate mixed colloid transport prediction. This work provides critical insights for assessing colloid‐facilitated contaminant transport in groundwater systems.

Peptide toxins found in sea anemones venom have diverse properties that make them important research subjects in the fields of pharmacology, neuroscience and biotechnology. This study used high-throughput sequencing technology to systematically analyze the venom components of the tentacles, column, and mesenterial filaments of sea anemone Heteractis crispa , revealing the diversity and complexity of sea anemone toxins in different tissues. A total of 1049 transcripts were identified and categorized into 60 families, of which 91.0% were proteins and 9.0% were peptides. Of those 1049 transcripts, 416, 291, and 307 putative proteins and peptide precursors were identified from tentacles, column, and mesenterial filaments respectively, while 428 were identified when the datasets were combined. Of these putative toxin sequences, 42 were detected in all three tissues, including 33 proteins and 9 peptides, with the majority of peptides being ShKT domain, β-defensin, and Kunitz-type. In addition, this study applied bioinformatics approaches to predict the family classification, 3D structures, and functional annotation of these representative peptides, as well as the evolutionary relationships between peptides, laying the foundation for the next step of peptide pharmacological activity research.

The prognostic significance of the C-reactive protein-to-albumin ratio (CAR) in patients undergoing noncardiac surgery has not been conclusively determined. This study aimed to investigate the correlation and predictive capacity of the CAR for major perioperative adverse cardiovascular events (MACEs) in noncardiac surgical patients. Individuals who underwent noncardiac surgical procedures were identified within the perioperative medicine database (INSPIRE 1.1) and stratified into tertiles on the basis of the CAR. The associations between the CAR and the risk of MACEs (all-cause death, perioperative myocardial infarction, and acute heart failure) were analysed via Cox proportional hazards regression analysis, and restricted cubic splines were subsequently used to examine the shape of the associations. Additionally, the CAR’s incremental predictive value for MACEs was evaluated using the C statistic, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI), in order to quantify the improvement in predictive performance achieved by adding the CAR to the Revised Cardiac Risk Index (RCRI). The feature significance and predictive models were developed via the Boruta algorithm and machine learning techniques. A total of 7,366 patients were included. There was a significant difference in the perioperative MACE risk among the three groups (tertiles 1 to 3: 0.24% vs. 0.69% vs. 1.63%; log-rank P < 0.001). Compared with patients in the lowest tertile, those with the highest CAR had a significantly increased risk of MACEs (hazard ratio [HR] 4.43, 95% confidence interval [CI] 1.53–12.86, P = 0.006), and an L-shaped association was observed. For each SD (standard deviation) increase in the CAR, the risk of perioperative MACE increased by 1.22 times (HR 1.22, 95% CI 1.06–1.41). Furthermore, incorporating the CAR into the Revised Cardiac Risk Index (RCRI) or baseline risk models significantly enhanced the ability of the CAR to predict perioperative MACEs. The CatBoost algorithm model showed the best performance (AUC = 0.865). The CAR was associated with an increased risk of perioperative MACEs in patients undergoing noncardiac surgery, indicating its potential as a valuable and reliable prognostic tool for evaluating the risk of perioperative MACEs.

Chimeric antigen receptor (CAR) therapies have revolutionized cancer treatment by enabling immune cells to target tumor cells with high specificity. While extensive research has focused on optimizing single-chain variable fragment (scFv) affinity in CAR-T cells, its impact on CAR-natural killer (NK) cell function remains less understood. A recent study by Rahnama et al, published in the Journal for ImmunoTherapy of Cancer, addresses this gap by investigating how fine-tuning scFv affinity influences CAR-NK efficacy against acute myeloid leukemia. The study demonstrates that lower-affinity 7G3-based CAR-NK cells exhibit superior antigen discrimination, prolonged persistence, and enhanced tumor control compared with their high-affinity counterparts. However, findings with 26292-based CAR-NK cells reveal a more complex, context-dependent relationship between scFv affinity and cytotoxic function. These results highlight the need for individualized optimization of CAR designs, considering factors such as epitope accessibility, ligand-binding kinetics, and cellular context. Future studies incorporating real-time kinetic analyses and tumor microenvironment modeling will be crucial for refining CAR-NK therapies. Striking the right balance between binding affinity, dwell time, and serial killing capacity could enhance CAR-NK therapeutic potential while minimizing toxicity risks.

The South China Sea is rich in cone snail resources, known for producing conotoxins with diverse biological activities such as analgesic, anticancer, and insecticidal effects. In this study, five vermivorous cone snail samples were collected from the South China Sea and their crude venom was extracted to investigate the variations in venom components and activities, aiming to identify highly active samples for further research. Cluster analysis using reverse-phase high-performance liquid chromatography (RP-HPLC) fingerprints and mitochondrial cytochrome c oxidase I (COI) gene sequences revealed that the diversity of venom components across different conotoxin species is genetically correlated. Activity assays demonstrated that all five cone snail venoms exhibited lethal effects on insects and zebrafish. Notably, the crude venom of Conus quercinus showed the highest insecticidal activity with an LD50 of 0.6 μg/mg, while C. tessellatus venom exhibited the most potent zebrafish lethality with an LD50 of 0.2 μg/mg. Furthermore, the crude venom from four cone snail species demonstrated toxicity against ovarian cancer cells, and only C. caracteristicu venom displayed significant analgesic activity. This study systematically identifies cone snail samples with promising insecticidal, anticancer, and analgesic properties, paving the way for the development and utilization of cone snail resources from the South China Sea and offering a novel approach for advancing marine peptide drug research.

Background The predictive importance of the stress hyperglycemia ratio (SHR), which is composed of admission blood glucose (ABG) and glycated hemoglobin (HbA1c), has not been fully established in noncardiac surgery. This study aims to evaluate the association and predictive capability the SHR for major perioperative adverse cardiovascular events (MACEs) in noncardiac surgery patients. Methods Individuals who underwent noncardiac surgical procedures between 2011 and 2020, including both diabetic and non-diabetic patients, were identified in the perioperative medicine database (INSPIRE 1.1) and classified into tertiles based on their SHR. The connection between the SHR and the risk of MACEs was studied using Cox proportional hazards regression analysis, then restricted cubic spline (RCS) was employed to assess the association’s form. Additionally, the SHR’s incremental predictive utility for MACEs was assessed by the C-statistic, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI), thereby quantifying the enhancement in predictive accuracy brought by incorporating the SHR into existing risk models. Feature importance and predictive models were generated utilizing the Boruta algorithm and machine learning approaches. Results A total of 5609 patients were enrolled. With an upwards shift in SHR vertices, the rate of perioperative MACEs and cardiac death event steadily rose. The RCS analysis for perioperative MACEs and cardiac death event both indicated J-shaped associations. Inflection points occurred at SHR = 0.81 for MACEs and SHR = 0.97 for cardiac death. The model’s fit improved significantly, with a continuous NRI of 0.067 (95% CI: 0.025–0.137, P  < 0.001) and an IDI of 0.305 (95% CI: 0.155–0.430, P  < 0.001). When SHR was added as a categorical variable (> 0.81), the C-statistic increased to 0.785 (95% CI: 0.756–0.814) with a ΔC-statistic of 0.035 ( P  = 0.009), a continuous NRI of 0.007 (95% CI: 0.000-0.021, P  = 0.016), and an IDI of 0.076 (95% CI -0.024-0.142, P  = 0.092). In the Boruta algorithm, variables identified as important features in the green area were incorporated into the machine learning models development. Conclusions The SHR was related with an increased risk of perioperative MACEs in patients following noncardiac surgery, highlighting its potential as a useful and reliable predictive tool for assessing the risk of perioperative MACEs. Graphical Abstract

The venoms of various sea anemones are rich in diverse toxins, which usually play a dual role in capturing prey and deterring predators. However, the complex components of such venoms have not been well known yet. Here, venomics of integrating transcriptomic and proteomic technologies was applied for the first time to identify putative protein and peptide toxins from different tissues of the representative sea anemone, Heteractis magnifica. The transcriptomic analysis of H. magnifica identified 728 putative toxin sequences, including 442 and 381 from the tentacles and the column, respectively, and they were assigned to 68 gene superfamilies. The proteomic analysis confirmed 101 protein and peptide toxins in the venom, including 91 in the tentacles and 39 in the column. The integrated venomics also confirmed that some toxins such as the ShK-like peptides and defensins are co-expressed in both the tentacles and the column. Meanwhile, a homology analysis was conducted to predict the three-dimensional structures and potential activity of seven representative toxins. Altogether, this venomics study revealed the venom complexity of H. magnifica, which will help deepen our understanding of cnidarian toxins, thereby supporting the in-depth development of valuable marine drugs.

The advent of novel cancer immunotherapy approaches is revolutionizing the treatment for cancer. Current small animal models for most cancers are syngeneic or genetically engineered mouse models or xenograft models based on immunodeficient mouse strains. These models have been limited in evaluating immunotherapy regimens due to the lack of functional human immune system. Development of animal models for bone cancer faces another challenge in the accessibility of tumor engraftment sites. Here, we describe a protocol to develop an orthotopic humanized mouse model for a bone and soft tissue sarcoma, Ewing sarcoma, by transplanting fresh human cord blood CD34 + hematopoietic stem cells into young NSG-SGM3 mice combined with subsequent Ewing sarcoma patient derived cell engraftment in the tibia of the humanized mice. We demonstrated early and robust reconstitution of human CD45 + leukocytes including T cells, B cells, natural killer cells and monocytes. Ewing sarcoma xenograft tumors successfully orthotopically engrafted in the humanized mice with minimal invasive procedures. We validated the translational utility of this orthotopic humanized model by evaluating the safety and efficacy of an immunotherapy antibody, magrolimab. Treatment with magrolimab induces CD47 blockade resulting in significantly decreased primary tumor growth, decreased lung metastasis and prolonged animal survival in the established humanized model. Furthermore, the humanized model recapitulated the dose dependent toxicity associated with the CD47 blockade as observed in patients in clinical trials. In conclusion, this orthotopic humanized mouse model of Ewing sarcoma represents an improved platform for evaluating immunotherapy in bone and soft tissue sarcoma, such as Ewing sarcoma. With careful design and optimization, this model is generalizable for other bone malignancies.

The South China Sea is rich in sea anemone resources, and the protein and peptide components from sea anemone toxins comprise an important treasure trove for researchers to search for leading compounds. This study conducted a comprehensive transcriptomic analysis of the tentacles and column of Macrodactyla doreensis and explored the distribution and diversity of proteins and peptides in depth using bioinformatics, initially constructing a putative protein and peptide database. In this database, typical peptide families are identified through amino acid sequence analysis, and their 3D structures and potential biological activities are revealed through AlphaFold2 modeling and molecular docking. A total of 4239 transcripts were identified, of which the putative protein accounted for 81.53%. The highest content comprised immunoglobulin and a variety of proteases, mainly distributed in the column and related to biological functions. Importantly, the putative peptide accounted for 18.47%, containing ShK domain and Kunitz-type peptides, mainly distributed in the tentacles and related to offensive predatory behavior. Interestingly, 40 putative peptides belonging to eight typical peptide families were identified, and their structures and targets were predicted. This study reveals the diversity and complexity of Macrodactyla doreensis toxins and predicts their structure and targets based on amino acid sequences, providing a feasible approach for research regarding the discovery of peptides with potentially high activity.