Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.

PURPOSE: To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC). METHODS: The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit. RESULTS: 166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000-1.000) in the training set and 0.927 (95%CI: 0.837-0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837-0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908. CONCLUSION: This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.

Six new species of Cryptochironomus Kieffer (Diptera, Chironomidae) from the Nearctic region.

Six new species of Cryptochironomus Kieffer, 1918, C.absum Liu, sp. nov., C.beardi Liu, sp. nov., C.dentatus Liu, sp. nov., C.ferringtoni Liu, sp. nov., C.parallelus Liu, sp. nov. and C.taylorensis Liu, sp. nov., are described and illustrated based on adult males. The specimens were collected from various water systems in the United States and preserved by Dr. Leonard Charles Ferrington Jr. An updated key to adult males of all known Cryptochironomus species in the Nearctic region is also provided.

QiDongNing induces lung cancer cell apoptosis via triggering P53/DRP1-mediated mitochondrial fission.

Non-small-cell lung cancer (NSCLC) is a major cause of worldwide cancer death, posing a challenge for effective treatment. Our previous findings showed that Chinese herbal medicine (CHM) QiDongNing (QDN) could upregulate the expression of p53 and trigger cell apoptosis in NSCLC. Here, our objective was to investigate the mechanisms of QDN-induced apoptosis enhancement. We chose A549 and NCI-H460 cells for validation in vitro, and LLC cells were applied to form a subcutaneous transplantation tumour model for validation in more depth. Our findings indicated that QDN inhibited multiple biological behaviours, including cell proliferation, cloning, migration, invasion and induction of apoptosis. We further discovered that QDN increased the pro-apoptotic BAX while inhibiting the anti-apoptotic Bcl2. QDN therapy led to a decline in adenosine triphosphate (ATP) and a rise in reactive oxygen species (ROS). Furthermore, QDN elevated the levels of the tumour suppressor p53 and the mitochondrial division factor DRP1 and FIS1, and decreased the mitochondrial fusion molecules MFN1, MFN2, and OPA1. The results were further verified by rescue experiments, the p53 inhibitor Pifithrin-α and the mitochondrial division inhibitor Mdivi1 partially inhibited QDN-induced apoptosis and mitochondrial dysfunction, whereas overexpression of p53 rather increased the efficacy of the therapy. Additionally, QDN inhibited tumour growth with acceptable safety in vivo. In conclusion, QDN induced apoptosis via triggering p53/DRP1-mediated mitochondrial fission in NSCLC cells.

New descriptions of the larval and pupal stages of Orthocladiusnitidoscutellatus and Psectrocladiusnevalis from Xizang, China (Diptera, Chironomidae).

Background: Tibetan Plateau is one of the most typical areas of biodiversity in the world because of its unique environmental and regional units, which breed unique biological communities and concentrate on many unique and rare wild animals and plants. Research on Chironomidae in the Tibetan Plateau is relatively weak. At present, the identification of Chironomidae species mainly depends on male adults, while identification of larvae and pupae is relatively difficult and there is less research on them. New information: During the investigations of insect diversity in the Tibetan Plateau, larval and pupal stages of Orthocladiusnitidoscutellatus Lundström, 1915 and Psectrocladiusnevalis Akhrorov, 1977 were described and illustrated. Matching and identification of larval and pupal stages were based on DNA barcodes. Neighbour-joining trees were reconstructed, based on known Orthocladius and Psectrocladius COI DNA barcodes, respectively.

STADNet: Spatial-Temporal Attention-Guided Dual-Path Network for cardiac cine MRI super-resolution.

Cardiac cine magnetic resonance imaging (MRI) is a commonly used clinical tool for evaluating cardiac function and morphology. However, its diagnostic accuracy may be compromised by the low spatial resolution. Current methods for cine MRI super-resolution reconstruction still have limitations. They typically rely on 3D convolutional neural networks or recurrent neural networks, which may not effectively capture long-range or non-local features due to their limited receptive fields. Optical flow estimators are also commonly used to align neighboring frames, which may cause information loss and inaccurate motion estimation. Additionally, pre-warping strategies may involve interpolation, leading to potential loss of texture details and complicated anatomical structures. To overcome these challenges, we propose a novel Spatial-Temporal Attention-Guided Dual-Path Network (STADNet) for cardiac cine MRI super-resolution. We utilize transformers to model long-range dependencies in cardiac cine MR images and design a cross-frame attention module in the location-aware spatial path, which enhances the spatial details of the current frame by using complementary information from neighboring frames. We also introduce a recurrent flow-enhanced attention module in the motion-aware temporal path that exploits the correlation between cine MRI frames and extracts the motion information of the heart. Experimental results demonstrate that STADNet outperforms SOTA approaches and has significant potential for clinical practice.

Predicting the mechanism of action of YQYYJD prescription in the treatment of non-small cell lung cancer using transcriptomics analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: The efficacy of the herbal formula Yiqi Yangyin Jiedu (YQYYJD) in the treatment of advanced lung cancer has been reported in clinical trials. However, the key anti-lung cancer herbs and molecular mechanisms underlying its inhibition of lung cancer are not well-understood. AIM OF THE STUDY: To identify the key anti-lung cancer herbs in the YQYYJD formula and investigate their therapeutic effect and potential mechanism of action in non-small cell lung cancer (NSCLC) using transcriptomics and bioinformatics techniques. MATERIALS AND METHODS: A mouse Lewis lung carcinoma (LLC) subcutaneous inhibitory tumor model was established with 6 mice in each group. Mice were treated with the YQYYJD split formula: Yiqi Formula (YQ), Yangyin Formula (YY), and Ruanjian Jiedu Formula (RJJD) for 14 days. The tumor volume and mouse weight were recorded, and the status of tumor occurrence was further observed by taking photos. The tumor was stained with hematoxylin-eosin to observe its histopathological changes. Immunohistochemistry was used to detect the expression of the proliferation marker Ki67 and the apoptotic marker Caspase-3 in tumor tissues. Flow cytometry was used to detect the number of CD4+ and CD8+ T cells and cytokines interleukin-2 (IL-2) and interferon-gamma (IFN-γ) in the spleen and tumor tissues. The differential genes of key drugs against tumors were obtained by transcriptome sequencing of tumors. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed on differential genes to obtain pathways and biological processes where targets were aggregated. TIMER2.0 and TISIDB databases were used to evaluate the impact of drugs on immune cell infiltration and immune-related genes. The binding activity of the key targets and compounds was verified by molecular docking. RESULTS: YQ, YY, and RJJD inhibited the growth of subcutaneous transplanted tumors in LLC mice to varying degrees and achieved antitumor effects by inhibiting the expression of tumor cell proliferation, apoptosis, and metastasis-related proteins. Among the three disassembled prescriptions, YQ better inhibited the growth of subcutaneous transplanted tumors in LLC mice, significantly promoted tumor necrosis, significantly increased the expression of Caspase-3 protein in tumor tissue, and significantly decreased the expression of Ki-67 (P < 0.05), thereby increasing the infiltration of CD8+ T cells. YQ significantly increased the expression of CD4+ and CD8+ T cells in tumor and splenic tissues of tumor-bearing mice and up-regulated the expression of IL-2 and IFN-γ. Transcriptome sequencing and bioinformatics results showed that after YQ intervention, differentially expressed genes were enriched in more than one tumor-related pathway and multiple immune regulation-related biological functions. There were 12 key immune-related target genes. CONCLUSION: YQ was the key disassembled prescription of YQYYJD, exerting significant antitumor effects and immune regulation effects on NSCLC. It may have relieved T cell exhaustion and regulated the immune microenvironment to exert antitumor effects by changing lung cancer-related targets, pathways, and biological processes.

Opportunity and challenges in recovering and functionalizing anode graphite from spent lithium-ion batteries: A review.

Recent concerns have emerged regarding the improper disposal of spent lithium-ion batteries (LIBs), which has garnered widespread societal attention. Graphite materials accounted for 12-21 wt % of LIBs' mass, typically contain heavy metals, binders, and residual electrolytes. Regenerating spent graphite not only alleviated the shortage of plumbago, but also contributed to the supports environmental protection as well as national carbon peak and neutrality ("dual carbon" goals). Despite significant advancements in recycling spent LIBs had been made, a comprehensive overview of the processes for pretreatment, regeneration, and functionalization of spent graphite from retired LIBs, along with the associated technical standards and industry regulations enabling their smooth implementation still needed to be mentioned. Hence, we conducted the following research work. Firstly, the pre-treatment process of spent graphite, including discharging, crushing, and screening was summed up. Next,. Subsequently, graphite recovery methods, such as acid leaching, pyrometallurgy, and combined methods were summarized. Moreover, the modification and doping approach was used to enhance the electrochemical properties of graphite. Afterwards, we reviewed the functionalization of anode graphite from an economically and environmentally friendly view. Meanwhile, the technical standards and industry regulations of spent LIBs in domestic and oversea industries were described. Finally, we provided an overview of the technical challenges and development bottlenecks in graphite recycling, along with future prospects Overall, this study outlined the opportunities and challenges in recovering and functionalizing of anode materials via a efficient and sustainable processes.

Ferroptosis boosted oral cancer photodynamic therapy by carrier-free Sorafenib-Ce6 self-assembly nanoparticles.

Oral cancer is a disease with high morbidity and mortality worldwide and greatly impacts the quality of life, especially in patients with advanced stages. Photodynamic therapy (PDT) is one of the most effective clinical treatments for oral cancers. However, most clinically applied photosensitizers have several deficiencies, including oxygen dependence, poor aqueous solubility, and a lack of tumor-targeting ability. Herein, the carrier-free multifunctional Sorafenib (Sor), chlorin e6 (Ce6), and Fe3+ self-assembly co-delivery nanoparticles (Sor-Ce6 NPs) were constructed via combining a ferroptosis inducer Sor and a photosensitizer Ce6 for synergetic therapy. The as-synthesized Sor-Ce6 NPs presented excellent colloidal stability and water dispersity with good in vivo tumor-targeting ability. More significantly, the low dose of Sor-Ce6 NPs had little dark toxicity but produced significantly enhanced ROS and supplied O2 sustainably to increase phototoxicity through ferroptosis pathway. Notably, the Sor-Ce6 NPs showed significantly higher in vitro and in vivo anti-tumor efficacy than the Sor/Ce6 mixture due to the improvement of cellular uptake and the incorporation of foreign Fe ions in the system, which also confer the T1 magnetic resonance-guided imaging ability to the formed Sor-Ce6 NPs. Our study demonstrates a promising self-assembled strategy for overcoming hypoxia-related PDT resistance for oral cancer treatment.

Eco-friendly treatment of copper smelting flue dust for recovering multiple heavy metals with economic and environmental benefits.

Handling flue dust in an environmentally friendly manner has become an urgent task for pollution prevention in the copper industry. Here, driven by the low-carbon notion, we report a process that enables the selective retrieval of multiple metals (As, Cu, Pb, Zn, and Bi) from copper smelting flue dust (CSFD). This process employed low-temperature roasting to separate arsenic from heavy metals, thereby eliminating the tedious separation steps required by existing processes. Subsequently, Zn and Cu were dissolved in water, while Pb and Bi were left as a solid residue. We achieved 98.23% extraction of Cu via Zn cementation at a micro-voltage of 0.50 V. Utilizing the difference in solubility, Bi was selectively dissolved from the residue using a NaCl-HCl medium, which enabled the subsequent production of metallic Bi through electrowinning. Finally, more than 99% of Pb in the solid was reduced to elemental Pb by mechanochemical reduction. Through optimized process conditions, high-purity As2O3 (99.04%), lead ingot (99.95%), metallic copper (94.16%), and bismuth (99.20%) were obtained. Our economic assessment revealed significant advantages, demonstrating the industrial feasibility of this process. Consequently, this study presents an effective and cost-efficient system for CSFD disposal while minimizing the environmental impact and fostering a circular economy.

Progressive low-temperature volatilization control: Efficient separation of arsenic and antimony from smelter dust.

Given the high toxicity of arsenic (As) and the strategic importance of antimony (Sb), the separation of As and Sb has become a pivotal concern in the disposal of arsenic­antimony flue dust and other arsenic­antimony hazardous wastes. In this study, we propose a controlled roasting process employing anthracite and sulfuric acid additives to efficiently separate As and Sb at relatively low temperatures. Thermodynamic calculations revealed that the interactive reactions between arsenic and antimony oxides in conventional pyrometallurgical processes were the primary hindrance to their effective separation. However, the synergistic effect of anthracite and sulfuric acid not only disrupted the interactive reactions but also promoted the high-efficiency volatilization of As at low temperatures, thereby creating favorable conditions for the separation of As and Sb. Furthermore, a series of comparative experiments and comprehensive analyses regarding the evolution of phase composition, valence state, and morphology were conducted, revealing the underlying mechanisms of the effects of temperature and carbon addition. Through optimization, 91.24 % of As was successfully volatilized, while the volatilization efficiency of Sb was significantly reduced to 9.43 % under optimal conditions, involving a roasting temperature of 400 °C, anthracite addition of 1.6 %, sulfuric acid dosage of 0.135 mL/g, and a roasting duration of 3 h.

Qilian Formula Inhibits Tumor Cell Growth in a Bone Metastasis Model of Lung Cancer.

BACKGROUND: Bone metastasis is frequently common in advanced lung cancer with the major issue of a pathological fracture. Previous studies suggested that Astragalus membranaceus (Qi) and Ampelopsis japonica (Lian), which are used as folk medicine in China, have potential effects on inhibiting tumor growth and protecting bones, respectively. In this study, an experiment on the inhibitory effect of the Qilian formula (AAF) in vivo was designed to examine tumor growth in bone and osteoclast formation. MATERIALS AND METHODS: The bone metastasis xenograft models were established by implanting NCI-H460-luc2 lung cancer cells into the right tibiae bones of mice. After confirming the model's viability through optical imaging 7 days post-implantation, 2 groups, namely the AAF group and the control group, were administered 0.3 mL of AAF extract (9 g/kg/day) or normal saline via intragastric delivery for a duration of 4 weeks. Throughout the study, we longitudinally assessed tumor burden, bone destruction, and weight-bearing capacity in vivo using reporter gene bioluminescence imaging (BLI), micro-CT, and dynamic weight-bearing (DWB) tests. Mechanistic insights were gained through Hematoxylin-eosin (H&E) staining, immunohistochemical (IHC) analysis, western blotting, and flow cytometry. RESULTS: Qilian formula produced significant inhibition to the progress of bone destruction and tumor burden in the right tibiae bone in the treatment group. It was further evidenced by molecular imaging in vivo via small animal micro-CT and BLI with parametric quantification, characterizing significantly lower uptake of BLI signal in the treated tumor lesions and improving the pathological changes in the microstructure of bone. Furthermore, DWB tests revealed that Qilian formula treatment significantly maintained the weight-bearing capacity. According to immunohistochemical analysis, the effect of the Qilian formula appeared to involve the suppression of osteoclast formation by lower expression of the tartrate-resistant acid phosphatase. Cell apoptosis and death induction were evidenced by a higher percentage of Bal2、BAX and caspase 3 expressions of Qilian formula-treated tumor tissues. CONCLUSIONS: Our study demonstrated a significant inhibitory effect of the Qilian formula on the progression of osteolytic invasion in vivo by suppressing osteoclastogenesis and promoting apoptotic cell death.

Integrated bioinformatics analysis of microarray data from non-small cell lung cancer.

Non-small cell lung cancer (NSCLC), with its high mortality rate, lack of early diagnostic markers and prevention of distant metastases are the main challenges in treatment. To identify potential miRNAs and key genes in NSCLC to find new biomarkers and target gene therapies. The GSE102286, GSE56036, GSE25508, GSE53882, GSE29248 and GSE101929 datasets were obtained from the Gene Expression Omnibus (GEO) database and screened for differentially co-expressed miRNAs (DE-miRNAs) and lncRNAs (DElncRs) by GEO2R and R software package. Pathway enrichment analysis of DE-miRNAs-target genes was performed by String and Funrich database to construct protein-protein interaction (PPI) and competing endogenous RNA (ceRNA) network and visualized with Cytoscape software. Nineteen co-expressed DE-miRNAs were screened from five datasets. The 7683 predicted up- and down-regulated DE-miRNAs-target genes were significantly concentrated in cancer-related pathways. The top 10 hub nodes in the PPI were identified as hub genes, such as MYC, EGFR, HSP90AA1 and TP53, MYC, and ACTB. By constructing miRNA-hub gene networks, hsa-miR-21, hsa-miR-141, hsa-miR-200b and hsa-miR-30a, hsa-miR-30d, hsa-miR-145 may regulate most hub genes and hsa-miR-141, hsa-miR-200, hsa-miR-145 had higher levels in the miRNA and ceRNA regulatory networks, respectively. In conclusion, the identification of hsa-miR-21, hsa-miR-141, hsa-miR-200b hsa-miR-30a, hsa-miR-30d and hsa-miR-145 provides a new theoretical basis for understanding the development of NSCLC.

Colon-Targeted Release of Gel Microspheres Loaded with Antioxidative Fullerenol for Relieving Radiation-Induced Colon Injury and Regulating Intestinal Flora.

Radiation-induced colitis is a serious clinical problem worldwide. However, the current treatment options for this condition have limited efficacy and can cause side effects. To address this issue, colon-targeted fullerenol@pectin@chitosan gel microspheres (FPCGMs) are developed, which can aggregate on colon tissue for a long time, scavenge free radicals generated in the process of radiation, and regulate intestinal flora to mitigate damage to colonic tissue. First, FPCGMs exhibit acid resistance and colon-targeted release properties, which reduce gastrointestinal exposure and extend the local colonic drug residence time. Second, fullerenol, which has a superior scavenging ability and chemical stability, reduces oxidative stress in colonic epithelial cells. Based on this, it is found that FPCGMs significantly reduce inflammation in colonic tissue, mitigated damage to tight junctions of colonic epithelial cells, and significantly relieved radiation-induced colitis in mice. Moreover, 16S ribosomal DNA (16S rDNA) sequencing results show that the composition of the intestinal flora is optimized after FPCGMs are utilized, indicating that the relative abundance of probiotics increases while harmful bacteria are inhibited. These findings suggest that it is a promising candidate for treating radiation-induced colitis.

Study on myocardial toxicity induced by lead halide perovskites nanoparticles.

Lead halide perovskites (LHPs) are outstanding candidates for next-generation optoelectronic materials, with considerable prospects of use and commercial value. However, knowledge about their toxicity is scarce, which may limit their commercialization. Here, for the first time, we studied the cardiotoxicity and molecular mechanisms of representative CsPbBr3 nanoparticles in LHPs. After their intranasal administration to Institute of Cancer Research (ICR) mice, using advanced synchrotron radiation, mass spectrometry, and ultrasound imaging, we revealed that CsPbBr3 nanoparticles can severely affect cardiac systolic function by accumulating in the myocardial tissue. RNA sequencing and Western blotting demonstrated that CsPbBr3 nanoparticles induced excessive oxidative stress in cardiomyocytes, thereby provoking endoplasmic reticulum stress, disturbing calcium homeostasis, and ultimately leading to apoptosis. Our findings highlight the cardiotoxic effects of LHPs and provide crucial toxicological data for the product.

Fullerenols Mitigate Radiation-Induced Myocardial Injury.

Radiation-induced heart disease is a serious side effect of radiation therapy that can lead to severe consequences. However, effective and safe methods for their prevention and treatment are presently lacking. This study reports the crucial function of fullerenols in protecting cardiomyocytes from radiation injury. First, fullerenols are synthesized using a simple base-catalyzed method. Next, the as-prepared fullerenols are applied as an effective free radical scavenger and broad-spectrum antioxidant to protect against X-ray-induced cardiomyocyte injury. Their ability to reduce apoptosis via the mitochondrial signaling pathway at the cellular level is then verified. Finally, it is observed in animal models that fullerenols accumulate in the heart and alleviate myocardial damage induced by X-rays. This study represents a timely and essential analysis of the prevention and treatment of radiological myocardial injury, providing new insights into the applications of fullerenols for therapeutic strategies.

Adaptive channel-modulated personalized federated learning for magnetic resonance image reconstruction.

Magnetic resonance imaging (MRI) is extensively utilized in clinical practice for diagnostic purposes, owing to its non-invasive nature and remarkable ability to provide detailed characterization of soft tissues. However, its drawback lies in the prolonged scanning time. To accelerate MR imaging, how to reconstruct MR images from under-sampled data quickly and accurately has drawn intensive research interest; it, however, remains a challenging task. While some deep learning models have achieved promising performance in MRI reconstruction, these models usually require a substantial quantity of paired data for training, which proves challenging to gather and share owing to high scanning costs and data privacy concerns. Federated learning (FL) is a potential tool to alleviate these difficulties. It enables multiple clinical clients to collaboratively train a global model without compromising privacy. However, it is extremely challenging to fit a single model to diverse data distributions of different clients. Moreover, existing FL algorithms treat the features of each channel equally, lacking discriminative learning ability across feature channels, and hence hindering their representational capability. In this study, we propose a novel Adaptive Channel-Modulated Federal learning framework for personalized MRI reconstruction, dubbed as ACM-FedMRI. Specifically, considering each local client may focus on features in different channels, we first design a client-specific hypernetwork to guide the channel selection operation in order to optimize the extracted features. Additionally, we introduce a performance-based channel decoupling scheme, which dynamically separates the global model at the channel level to facilitate personalized adjustments based on the performance of individual clients. This approach eliminates the need for heuristic design of specific personalization layers. Extensive experiments on four datasets under two different settings show that our ACM-FedMRI achieves outstanding results compared to other cutting-edge federated learning techniques in the field of MRI reconstruction.

Thermodynamic analysis and application for extracting valuable components from iron-phosphorus residue of spent catalysts.

The method of extracting valuable metals from spent catalysts has been developed in recent years. In this paper, the solid waste produced in the treatment of spent catalyst was studied and named iron-phosphorus residue (IPR). IPR was composed of FePO4·2H2O, Fe3(PO4)2·3H2O, Fe5(PO4)4(OH)3·2H2O, and SiO2. Appreciable quantities of Ni, Co, V, Mo, and W were detected in IPR. Based on E-pH diagrams, different atmospheric leaching strategies were used to extract valuable components from IPR. Both the HCl and NaOH leaching are appropriate for treating IPR. An in-depth investigation on HCl atmospheric leaching showed that >95% of Fe, Ni, Co, V, and Mo, 76.9% of W, and 89.3% of P were extracted efficiently and SiO2 was enriched into the leach residue, at leaching temperature of 90 ℃, leaching time of 180 min, initial HCl concentration of 5 mol/L and liquid to solid ratio of 8:1 mL/g. The leaching mechanism was discussed via XRD, XPS, and FTIR. An efficient and green process for the recovery of valuable components in IPR has been developed. This research achieves the sufficient extraction of valuable components in IPR and provides significant guidance for the management of similar solid waste.

Lung Toxicity and Molecular Mechanisms of Lead-Based Perovskite Nanoparticles in the Respiratory System.

Lead-based perovskite nanoparticles (Pb-PNPs) have found extensive applications across diverse fields. However, because of poor stability and relatively strong water solubility, the potential toxicity of Pb-PNPs released into the environment during their manufacture, usage, and disposal has attracted significant attention. Inhalation is a primary route through which human exposure to Pb-PNPs occurs. Herein, the toxic effects and underlying molecular mechanisms of Pb-PNPs in the respiratory system are investigated. The in vitro cytotoxicity of CsPbBr3 nanoparticles in BEAS-2B cells is studied using multiple bioassays and electron microscopy. CsPbBr3 nanoparticles of different concentrations induce excessive oxidative stress and cell apoptosis. Furthermore, CsPbBr3 nanoparticles specifically recruit the TGF-ß1, which subsequently induces epithelial-mesenchymal transition. In addition, the biodistribution and lung toxicity of representative CsPbBr3 nanoparticles in ICR mice are investigated following intranasal administration. These findings indicate that CsPbBr3 nanoparticles significantly induce pulmonary inflammation and epithelial-mesenchymal transition and can even lead to pulmonary fibrosis in mouse models. Above findings expose the adverse effects and molecular mechanisms of Pb-PNPs in the lung, which broadens the safety data of Pb-PNPs.

A Coarse-to-Fine Fusion Network for Small Liver Tumor Detection and Segmentation: A Real-World Study.

Liver tumor semantic segmentation is a crucial task in medical image analysis that requires multiple MRI modalities. This paper proposes a novel coarse-to-fine fusion segmentation approach to detect and segment small liver tumors of various sizes. To enhance the segmentation accuracy of small liver tumors, the method incorporates a detection module and a CSR (convolution-SE-residual) module, which includes a convolution block, an SE (squeeze and excitation) module, and a residual module for fine segmentation. The proposed method demonstrates superior performance compared to conventional single-stage end-to-end networks. A private liver MRI dataset comprising 218 patients with a total of 3605 tumors, including 3273 tumors smaller than 3.0 cm, were collected for the proposed method. There are five types of liver tumors identified in this dataset: hepatocellular carcinoma (HCC); metastases of the liver; cholangiocarcinoma (ICC); hepatic cyst; and liver hemangioma. The results indicate that the proposed method outperforms the single segmentation networks 3D UNet and nnU-Net as well as the fusion networks of 3D UNet and nnU-Net with nnDetection. The proposed architecture was evaluated on a test set of 44 images, with an average Dice similarity coefficient (DSC) and recall of 86.9% and 86.7%, respectively, which is a 1% improvement compared to the comparison method. More importantly, compared to existing methods, our proposed approach demonstrates state-of-the-art performance in segmenting small objects with sizes smaller than 10 mm, achieving a Dice score of 85.3% and a malignancy detection rate of 87.5%.