Covalent Bonding of Salen Metal Complexes with Pyrene Chromophores to Porous Polymers for Photocatalytic Hydrogen Evolution.

The development of low-cost and efficient photocatalysts to achieve water splitting to hydrogen (H2) is highly desirable but remains challenging. Herein, we design and synthesize two porous polymers (Co-Salen-P and Fe-Salen-P) by covalent bonding of salen metal complexes and pyrene chromophores for photocatalytic H2 evolution. The catalytic results demonstrate that the two polymers exhibit excellent catalytic performance for H2 generation in the absence of additional noble-metal photosensitizers and cocatalysts. Particularly, the H2 generation rate of Co-Salen-P reaches as high as 542.5 µmol g-1 h-1, which is not only 6 times higher than that of Fe-Salen-P but also higher than a large amount of reported Pt-assisted photocatalytic systems. Systematic studies show that Co-Salen-P displays faster charge separation and transfer efficiencies, thereby accounting for the significantly improved photocatalytic activity. This study provides a facile and efficient way to fabricate high-performance photocatalysts for H2 production.

Associations between genetically predicted concentrations of plasma proteins and the risk of prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a leading cause of cancer-related death in men. Understanding the proteomic landscape associated with PCa risk can provide insights into its molecular mechanisms and pave the way for potential therapeutic interventions. METHODS: A proteome-wide Mendelian randomization (MR) analysis was employed to determine associations between genetically predicted protein concentrations in plasma and PCa risk. From an initial list of 4,364 proteins, significant associations were identified and validated. Multiple sensitivity analyses were also conducted to enhance the robustness of our findings. RESULTS: Of the 4,364 genetically predicted proteins, 308 exhibited preliminary associations with PCa risk. After rigorous statistical refinement, genetically predicted concentrations of 14 proteins showed positive associations with PCa risk, with odds ratios spanning from 1.55 (95% CI 1.28-1.87) for ATG4B to 2.67 (95% CI 1.94-3.67) for HCN1. In contrast, genetically predicted concentrations of ATG7, B2M, MSMB, and TMEM108 demonstrated inverse associations with PCa. The replication analysis further substantiated positive associations for MDH1 and LSM1, and a negative one for MSMB with PCa. A meta-analysis harmonizing primary and replication data mirrored these findings. Furthermore, the MVMR analysis pinpointed B2M and MSMB as having significant associations with PCa risk. CONCLUSION: The genetic evidence unveils a refined set of proteins associated with PCa risk. The findings underscore the potential of these proteins as molecular markers or therapeutic targets for PCa, calling for deeper mechanistic studies and exploration into their translational relevance.

Modulating the Microenvironments of Robust Metal Hydrogen-Bonded Organic Frameworks for Boosting Photocatalytic Hydrogen Evolution.

Hydrogen-bonded organic frameworks (HOFs) are outstanding candidates for photocatalytic hydrogen evolution. However, most of reported HOFs suffer from poor stability and photocatalytic activity in the absence of Pt cocatalyst. Herein, a series of metal HOFs (Co2-HOF-X, X=COOMe, Br, tBu and OMe) have been rationally constructed based on dinuclear cobalt complexes, which exhibit exceptional stability in the presence of strong acid (12 M HCl) and strong base (5 M NaOH) for at least 10 days. More impressively, by varying the -X groups of the dinuclear cobalt complexes, the microenvironment of Co2-HOF-X can be modulated, giving rise to obviously different photocatalytic H2 production rates, following the -X group sequence of -COOMe>-Br>-tBu>-OMe. The optimized Co2-HOF-COOMe shows H2 generation rate up to 12.8 mmol g-1 h-1 in the absence of any additional noble-metal photosensitizers and cocatalysts, which is superior to most reported Pt-assisted photocatalytic systems. Experiments and theoretical calculations reveal that the -X groups grafted on Co2-HOF-X possess different electron-withdrawing ability, thus regulating the electronic structures of Co catalytic centres and proton activation barrier for H2 production, and leading to the distinctly different photocatalytic activity.

Innovative modified T-shape oncoplastic technique for early-stage breast cancer: multicenter retrospective study.

Inadequate tissue volume at the lower pole of the breast following tumor excision can compromise aesthetic outcomes when employing the conventional inverted-T reconstruction technique. With the aim of reducing postoperative deformities, we have refined this technique. A total of 104 patients underwent the T technique, while 32 underwent the modified T technique and 72 underwent the traditional T technique. In this study, we present the surgical outcomes of the modified T technique group and compare both surgical and oncological outcomes with those of the traditional T technique group. In the modified T technique group, the average tumor size was 23.34 mm, and the mean operation duration was 107.75 min, which was significantly shorter than that of the traditional T technique (p = 0.039). Additionally, the average blood loss was 95.93 mL, which was significantly lower than that of the traditional T technique (p = 0.011). Although complication rates did not differ significantly between the two groups (p = 0.839), the modified T technique yielded superior aesthetic outcomes compared to the traditional T technique (p = 0.019). Survival analysis indicated no significant difference in 5-year recurrence-free survival between the two groups, both before and after propensity score matching (p = 0.381 vs. p = 0.277). As part of our series of oncoplastic techniques for the lower breast quadrant, the modified inverted-T technique utilizes a cost-effective flap to address lower pole defects, mitigating deformities and restoring the breast's natural shape.

Unlocking Clinical Insights: Lymphocyte-Specific Protein Tyrosine Kinase Candidates as Promising Therapeutic Targets for Pancreatic Cancer Risk Stratification.

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer. Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined. Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis. Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Nanoformulation of dasatinib cannot overcome therapy resistance of pancreatic cancer cells with low LYN kinase expression.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most difficult to treat tumors. The Src (sarcoma) inhibitor dasatinib (DASA) has shown promising efficacy in preclinical studies of PDAC. However, clinical confirmation could not be achieved. Overall, our aim was to deliver arguments for the possible reinitiating clinical testing of this compound in a biomarker-stratifying therapy trial for PDAC patients. We tested if the nanofunctionalization of DASA can increase the drug efficacy and whether certain Src members can function as clinical predictive biomarkers. METHODS: Methods include manufacturing of poly(vinyl alcohol) stabilized gold nanoparticles and their drug loading, dynamic light scattering, transmission electron microscopy, thermogravimetric analysis, Zeta potential measurement, sterile human cell culture, cell growth quantification, accessing and evaluating transcriptome and clinical data from molecular tumor dataset TCGA, as well as various statistical analyses. RESULTS: We generated homo-dispersed nanofunctionalized DASA as an AuNP@PVA-DASA conjugate. The composite did not enhance the anti-growth effect of DASA on PDAC cell lines. The cell model with high LYN expression showed the strongest response to the therapy. We confirm deregulated Src kinetome activity as a prevalent feature of PDAC by revealing mRNA levels associated with higher malignancy grade of tumors. BLK (B lymphocyte kinase) expression predicts shorter overall survival of diabetic PDAC patients. CONCLUSIONS: Nanofunctionalization of DASA needs further improvement to overcome the therapy resistance of PDAC. LYN mRNA is augmented in tumors with higher malignancy and can serve as a predictive biomarker for the therapy resistance of PDAC cells against DASA. Studying the biological roles of BLK might help to identify underlying molecular mechanisms associated with PDAC in diabetic patients.

A 3'-pre-tRNA-derived small RNA tRF-1-Ser regulated by 25(OH)D promotes proliferation and stemness by inhibiting the function of MBNL1 in breast cancer.

BACKGROUND: We explored the potential novel anticancer mechanisms of 25-hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA-derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. METHODS: Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High-throughput RNA-sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF-1-Ser knockdown. RNA pull-down and high-performance liquid chromatography-mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF-1-Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF-1-Ser on breast cancer. Semi-quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. RESULTS: The expression of tRF-1-Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF-1-Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF-1-Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF-1-Ser plays a vital role in the anticancer effect of 25(OH)D. CONCLUSIONS: In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF-1-Ser in BRCA progression, and suggested that tRF-1-Ser could emerge as a new therapeutic target for BRCA.

Machine learning and new insights for breast cancer diagnosis.

Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and breast thermographic techniques. More recently, machine learning (ML) tools have been increasingly employed in diagnostic medicine for its high efficiency in detection and intervention. The subsequent imaging features and mathematical analyses can then be used to generate ML models, which stratify, differentiate and detect benign and malignant breast lesions. Given its marked advantages, radiomics is a frequently used tool in recent research and clinics. Artificial neural networks and deep learning (DL) are novel forms of ML that evaluate data using computer simulation of the human brain. DL directly processes unstructured information, such as images, sounds and language, and performs precise clinical image stratification, medical record analyses and tumour diagnosis. Herein, this review thoroughly summarizes prior investigations on the application of medical images for the detection and intervention of BC using radiomics, namely DL and ML. The aim was to provide guidance to scientists regarding the use of artificial intelligence and ML in research and the clinic.

Single-cell transcriptomics reveals comprehensive microenvironment and highlights the dysfuntional state of NK cells in endometrioid carcinoma.

Endometrioid endometrial cancer (EEC) is one of the most common gynecologic malignancies. The interaction between cancer cells and the cells in the tumor microenvironment (TME) plays a crucial role in determining disease progression and response to treatment. To better understand the diversity in the TME of ECC, we conducted a comprehensive analysis using single-cell RNA sequencing across 21 samples, including 16 ECC and 5 adjacent normal tissues. We primarily focused on tumor-infiltrating natural killer (NK) cells and their cell-cell interactions with other immune cell types. We identified a CD56dim_DNAJB1 NK cells subset, which had low cytotoxic capability and high stress levels, suggesting a dysfunctional state. This subset showed strong interactions with tumor-associated macrophages through several ligand-receptor pairs. Additionally, we observed that tumor-infiltrating LAMP3+ dendritic cells may inhibit CD8+ T cells or attract regulatory T cells to the tumor area. These dendritic cells also had impaired activation effects on NK cells within the TME. Our study provides valuable insights into the role of NK cells in cancer immunity and highlights the potential of targeting specific NK cell subsets for therapeutic purposes.

A dicarbonate solvent electrolyte for high performance 5 V-Class Lithium-based batteries.

Rechargeable lithium batteries using 5 V positive electrode materials can deliver considerably higher energy density as compared to state-of-the-art lithium-ion batteries. However, their development remains plagued by the lack of electrolytes with concurrent anodic stability and Li metal compatibility. Here we report a new electrolyte based on dimethyl 2,5-dioxahexanedioate solvent for 5 V-class batteries. Benefiting from the particular chemical structure, weak interaction with lithium cation and resultant peculiar solvation structure, the resulting electrolyte not only enables stable, dendrite-free lithium plating-stripping, but also displays anodic stability up to 5.2 V (vs. Li/Li+), in additive or co-solvent-free formulation, and at low salt concentration of 1 M. Consequently, the Li | |LiNi0.5Mn1.5O4 cells using the 1 M LiPF6 in 2,5-dioxahexanedioate based electrolyte retain >97% of the initial capacity after 250 cycles, outperforming the conventional carbonate-based electrolyte formulations, making this, and potentially other dicarbonate solvents promising for future Lithium-based battery practical explorations.

Combination of Atractylenolide I, Atractylenolide III, and Paeoniflorin promotes angiogenesis and improves neurological recovery in a mouse model of ischemic Stroke.

BACKGROUND: Prognosis is critically important in stroke cases, with angiogenesis playing a key role in determining outcomes. This study aimed to investigate the potential protective effects of Atractylenolide I (Atr I), Atractylenolide III (Atr III), and Paeoniflorin (Pae) in promoting angiogenesis following cerebral ischemia. METHODS: The bEnd.3 cell line was used to evaluate the effects of these three compounds on vascular endothelial cell proliferation, migration, and tube formation. Male C57BL/6 mice underwent transient middle cerebral artery occlusion (MCAO), followed by daily intragastric administration of the Chinese medicine compounds to assess their impact on brain protection and angiogenesis. In vivo experiments included measuring infarct size and assessing neurological function. Immunofluorescence staining and an angiogenesis antibody array were used to evaluate angiogenesis in ischemic brain tissue. Functional enrichment analysis was performed to further investigate the pathways involved in the protective effects of the compounds. Molecular docking analysis explored the potential binding affinity of the compounds to insulin-like growth factor 2 (IGF-2), and Western blotting was used to measure levels of angiogenesis-related proteins. RESULTS: In vitro, the combination of Atr I, Atr III, and Pae enhanced cell proliferation, promoted migration, and stimulated tube formation. In vivo, the combined treatment significantly facilitated neurological function recovery and angiogenesis by day 14. The treatment also increased levels of angiogenesis-related proteins, including IGF-2. Pearson correlation analysis revealed a strong positive association between IGF-2 levels in ischemic brain tissue and angiogenesis, suggesting a good affinity of the compounds for the IGF-2 binding site, as supported by molecular docking analysis. CONCLUSION: The administration of Atr I, Atr III, and Pae has shown significant enhancements in long-term stroke recovery in mice, likely due to the promotion of angiogenesis via increased activation of the IGF-2 pathway in ischemic brain tissue.

Immunosuppressive Ability of Trichinella spiralis Adults Can Ameliorate Type 2 Inflammation in a Murine Allergy Model.

BACKGROUND: There is an increase in the global incidence of allergies. The hygiene hypothesis and the old friend hypothesis reveal that helminths are associated with the prevalence of allergic diseases. The therapeutic potential of Trichinella spiralis is recognized; however, the stage at which it exerts its immunomodulatory effect is unclear. METHODS: We evaluated the differentiation of bone marrow-derived macrophages stimulated with T spiralis excretory-secretory products. Based on an ovalbumin-induced murine model, T spiralis was introduced during 3 allergy phases. Cytokine levels and immune cell subsets in the lung, spleen, and peritoneal cavity were assessed. RESULTS: We found that T spiralis infection reduced lung inflammation, increased anti-inflammatory cytokines, and decreased Th2 cytokines and alarms. Recruitment of eosinophils, CD11b+ dendritic cells, and interstitial macrophages to the lung was significantly suppressed, whereas Treg cells and alternatively activated macrophages increased in T spiralis infection groups vs the ovalbumin group. Notably, when T spiralis was infected prior to ovalbumin challenge, intestinal adults promoted proportions of CD103+ dendritic cells and alveolar macrophages. CONCLUSIONS: T spiralis strongly suppressed type 2 inflammation, and adults maintained lung immune homeostasis.

Electronic Modulation in Homonuclear Dual-Atomic Catalysts for Enhanced CO2 Electroreduction.

Homonuclear dual-atomic catalysts showcase unique electronic modulation due to their dual metal centres, providing new direction in development of efficient catalysts for CO2 electroreduction. This article highlights a few cutting-edge homonuclear dual-atomic catalysts, focusing on their inherent advantages in efficient and selective CO2 electroreduction, to spotlight the potential application of dual-atomic catalysts in CO2 electroreduction.

Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach.

The escalating use of alicyclic compounds in modern industrial production has led to a rapid increase of these substances in the environment, posing significant health hazards. Addressing this challenge necessitates a comprehensive understanding of these compounds, which can be achieved through the deep learning approach. Graph neural networks (GNN) known for its' extraordinary ability to process graph data with rich relationships, have been employed in various molecular prediction tasks. In this study, alicyclic molecules screened from PCBA, Toxcast and Tox21 are made as general bioactivity and biological targets' activity prediction datasets. GNN-based models are trained on the two datasets, while the Attentive FP and PAGTN achieve best performance individually. In addition, alicyclic carbon atoms make the greatest contribution to biological activity, which indicate that the alicycle structures have significant impact on the carbon atoms' contribution. Moreover, there are terrific number of active molecules in other public datasets, indicates that alicyclic compounds deserve more attention in POPs control. This study uncovered deeper structural-activity relationships within these compounds, offering new perspectives and methodologies for academic research in the field.

Integrating a microRNA signature as a liquid biopsy-based tool for the early diagnosis and prediction of potential therapeutic targets in pancreatic cancer.

INTRODUCTION: Pancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies. MATERIALS AND METHODS: The analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved. RESULTS: Our multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients. CONCLUSION: A panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

Hypoxic postconditioning drives protective microglial responses and ameliorates white matter injury after ischemic stroke.

BACKGROUND: Ischemic stroke (IS) is a cerebrovascular disease with high incidence and mortality. White matter repair plays an important role in the long-term recovery of neurological function after cerebral ischemia. Neuroprotective microglial responses can promote white matter repair and protect ischemic brain tissue. AIMS: The aim of this study was to investigate whether hypoxic postconditioning (HPC) can promote white matter repair after IS, and the role and mechanism of microglial polarization in white matter repair after HPC treatment. MATERIALS & METHODS: Adult male C57/BL6 mice were randomly divided into three groups: Sham group (Sham), MCAO group (MCAO), and hypoxic postconditioning group (HPC). HPC group were subjected to 45 min of transient middle cerebral artery occlusion (MCAO) immediately followed by 40 min of HPC. RESULTS: The results showed that HPC reduced the proinflammatory level of immune cells. Furthermore, HPC promoted the transformation of microglia to anti-inflammatory phenotype on the third day after the procedure. HPC promoted the proliferation of oligodendrocyte progenitors and increased the expression of myelination-related proteins on the 14th day. On the 28th day, HPC increased the expression of mature oligodendrocytes, which enhanced myelination. At the same time, the motor neurological function of mice was restored. DISCUSSION: During the acute phase of cerebral ischemia, the function of proinflammatory immune cells was enhanced, long-term white matter damage was aggravated, and motor sensory function was decreased. CONCLUSION: HPC promotes protective microglial responses and white matter repair after MCAO, which may be related to the proliferation and differentiation of oligodendrocytes.

Boosting CO2 Photoreduction to Formate or CO with High Selectivity over a Covalent Organic Framework Covalently Anchored on Graphene Oxide.

Covalent organic frameworks (COFs) have been widely studied in photocatalytic CO2 reduction reaction (CO2 RR). However, pristine COFs usually exhibit low catalytic efficiency owing to the fast recombination of photogenerated electrons and holes. In this study, we fabricated a stable COF-based composite (GO-COF-366-Co) by covalently anchoring COF-366-Co on the surface of graphene oxide (GO) for the photocatalytic CO2 reduction. Interestingly, in absolute acetonitrile (CH3 CN), GO-COF-366-Co shows a high selectivity of 94.4 % for the photoreduction of CO2 to formate, with a formate yield of 15.8 mmol/g, which is approximately four times higher than that using the pristine COF-366-Co. By contrast, in CH3 CN/H2 O (v : v=4 : 1), the main product for the photocatalytic CO2 reduction over GO-COF-366-Co is CO (96.1 %), with a CO yield as high as 52.2 mmol/g, which is also approximately four times higher than that using the pristine COF-366-Co. Photoelectrochemical experiments demonstrate the covalent bonding of COF-366-Co and GO to form the GO-COF-366-Co composite facilitates charge separation and transfer significantly, thereby accounting for the enhanced catalytic activity. In addition, theoretical calculations and in situ Fourier transform infrared spectroscopy reveal H2 O can stabilize the *COOH intermediate to further form a *CO intermediate via O-H(aq)⋅⋅⋅O(*COOH) hydrogen bonding, thus explaining the regulated photocatalytic performance.

Establishment of a developmental atlas and transgenetic tools in the ascidian Styela clava.

The ascidian Styela clava is an ecologically important species that is distributed along coastal regions worldwide. It has a long history as a model animal for evolutionary and developmental biology research owing to its phylogenetic position between vertebrates and invertebrates, and its classical mosaic expression patterns. However, the standard developmental atlas and protocols and tools for molecular manipulation of this organism are inadequate. In this study, we established a standard developmental table and provided a web-based digital image resource for S. clava embryogenesis at each developmental stage from fertilized eggs to hatching larvae by utilizing confocal laser microscopy and 3D reconstruction images. It takes around 10 h for fertilized eggs to develop into swimming larvae and 20-30 min to complete the tail regression processes at the metamorphic stage. We observed that the notochord cells in S. clava embryos did not produce an extracellular lumen like Ciona robusta, but showed polarized elongation behaviors, providing us an ideal comparative model to study tissue morphogenesis. In addition, we established a chemical-washing procedure to remove the chorion easily from the fertilized eggs. Based on the dechorionation technique, we further realized transgenic manipulation by electroporation and successfully applied tissue-specific fluorescent labeling in S. clava embryos. Our work provides a standard imaging atlas and powerful genetic tools for investigating embryogenesis and evolution using S. clava as a model organism. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00200-2.

Association between Urinary Lead and Female Breast Cancer: A Population-Based Cross-Sectional Study.

BACKGROUND: Previous studies have explored the relationship between serum lead levels and the risk of female breast cancer (FBC). However, it is still uncertain whether urinary lead levels are associated with FBC. This study aimed to investigate the potential association between urinary lead and FBC. METHODS: A cross-sectional case-control study was conducted using the National Health and Nutrition Examination Survey (NHANES), which is a series of cross-sectional, nationally representative surveys of the United States population consisting of 10 survey waves from 1999 to 2018. This study analyzed a total of 2795 female participants (≥20 years), consisting of 210 participants with FBC and 2585 healthy controls. Urinary lead was detected using Inductively Coupled Plasma-Mass Spectrometry, which was divided into four levels by using quartiles-defining cut points. Multivariate logistic regression was used to analyze the association between urinary lead and FBC. RESULTS: Multivariate logistic regression revealed that urinary lead was positively correlated with FBC (Odds ratio [OR], 2.16; 95% confidence interval [CI]: [1.18, 3.95], p < 0.05) in a fully adjusted model. There were significantly increased ORs of FBC in quartile 4 (Q4) and quartile 3 (Q3), compared with the lowest quartile 1 (Q1) (Q4, OR = 1.48, 95% CI [0.89, 2.48]; Q3: OR = 1.01, 95% CI [0.59, 1.73], p for trend = 0.021). No significant interaction effects were observed between urinary lead levels and FBC between the subgroups (age, race, educational status, body mass index (BMI), marital status, family income to poverty ratio, hypertension status, diabetes status, renal function status, smoking history, ever been pregnant, oral contraceptive use, occupation classification, etc.) (All interaction p-value > 0.05). CONCLUSIONS: Urinary lead is likely positively associated with FBC in the US population.