In Vivo Self-Sorting of Peptides via In Situ Assembly Evolution.

Despite significant progress achieved in artificial self-sorting in solution, operating self-sorting in the body remains a considerable challenge. Here, we report an in vivo self-sorting peptide system via an in situ assembly evolution for combined cancer therapy. The peptide E3C16-SS-EIY consists of two disulfide-connected segments, E3C16SH and SHEIY, capable of independent assembly into twisted or flat nanoribbons. While E3C16-SS-EIY assembles into nanorods, exposure to glutathione (GSH) leads to the conversion of the peptide into E3C16SH and SHEIY, thus promoting in situ evolution from the nanorods into self-sorted nanoribbons. Furthermore, incorporation of two ligand moieties targeting antiapoptotic protein XIAP and organellar endoplasmic reticulum (ER) into the self-sorted nanoribbons allows for simultaneous inhibition of XIAP and accumulation surrounding ER. This leads to the cytotoxicity toward the cancer cells with elevated GSH levels, through activating caspase-dependent apoptosis and inducing ER dysfunction. In vivo self-sorting of E3C16-SS-EIY decorated with ligand moieties is thoroughly validated by tissue studies. Tumor-bearing mouse experiments confirm the therapeutic efficacy of the self-sorted assemblies for inhibiting tumor growth, with excellent biosafety. Our findings demonstrate an efficient approach to develop in vivo self-sorting systems and thereby facilitating in situ formulation of biomedical agents.

A lightweight intelligent laryngeal cancer detection system for rural areas.

OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of laryngologists and limited computer resources. We present the intelligent laryngeal cancer detection system (ILCDS), a deep learning-based solution tailored for effective LC screening in resource-constrained rural areas. METHODS: We compiled a dataset comprised of 2023 laryngoscopic images and applied data augmentation techniques for dataset expansion. Subsequently, we utilized eight deep learning models-AlexNet, VGG, ResNet, DenseNet, MobileNet, ShuffleNet, Vision Transformer, and Swin Transformer-for LC identification. A comprehensive evaluation of their performances and efficiencies was conducted, and the most suitable model was selected to assemble the ILCDS. RESULTS: Regarding performance, all models attained an average accuracy exceeding 90 % on the test set. Particularly noteworthy are VGG, DenseNet, and MobileNet, which exceeded an accuracy of 95 %, with scores of 95.32 %, 95.75 %, and 95.99 %, respectively. Regarding efficiency, MobileNet excels owing to its compact size and fast inference speed, making it an ideal model for integration into ILCDS. CONCLUSION: The ILCDS demonstrated promising accuracy in LC detection while maintaining modest computational resource requirements, indicating its potential to enhance LC screening accuracy and alleviate the workload on otolaryngologists in rural areas.

Investigating esophageal sarcomatoid carcinoma and its comparison with esophageal squamous cell carcinoma on clinicopathological characteristics, prognosis, and radiomics features: a retrospective study.

Introduction: Esophageal sarcomatoid carcinoma (ESC) is a rare pathological subtype of esophageal carcinomas, wherein its epithelial component typically demonstrates squamous cell carcinoma (SCC). However, the clinicopathological features and prognosis of ESC remain unclear, alongside its unique aspects compared to esophageal SCC (ESCC). Methods: Between January 2008 and December 2018, we retrospectively reviewed 67 ESC patients treated at West China Hospital. Among them, 51 patients with resected ESC were matched with 98 resected ESCC patients over the same period using propensity score matching at 1:2. The survival time and radiomics features of the two groups were compared. Results: A total of 59 patients with resected ESC and eight patients with non-resected ESC were enrolled. Progression-free survival (PFS) and overall survival (OS) were significantly different in patients with different TNM stages (p < 0.001). A multivariate analysis showed that length of tumor was an independent factor for OS in resetable ESC (p = 0.041). Among matched ESC and ESCC patients, OS was significantly longer for patients with ESC than those with ESCC (5-year OS, 61.1% vs. 43.6%; HR 0.59, 95% CI 0.35-0.96; p = 0.032). A Rad-score for discriminating ESC from ESCC containing two CT-derived radiomics features was developed [area under the curve: 0.823 (95% CI 0.732-0.913) in the training cohort and 0.828 (95% CI 0.636-1.000) in the validation cohort, respectively]. Conclusions: ESC has a better prognosis when compared with ESCC. By developing a radiomics prediction model, we provide reliability and convenience for the differential diagnosis of ESC from ESCC.

Advancements in nanomedicine delivery systems: unraveling immune regulation strategies for tumor immunotherapy.

This review highlights the significant role of nanodrug delivery systems (NDDS) in enhancing the efficacy of tumor immunotherapy. Focusing on the integration of NDDS with immune regulation strategies, it explores their transformative impacts on the tumor microenvironment and immune response dynamics. Key advancements include the optimization of drug delivery through NDDS, targeting mechanisms like immune checkpoint blockade and modulating the immunosuppressive tumor environment. Despite the progress, challenges such as limited clinical efficacy and complex manufacturing processes persist. The review emphasizes the need for further research to optimize these systems, potentially revolutionizing cancer treatment by improving delivery efficiency, reducing toxicity and overcoming immune resistance.

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Rhein alleviates MPTP-induced Parkinson's disease by suppressing neuroinflammation via MAPK/IκB pathway.

Background: Parkinson's disease (PD) is a common neurodegenerative disease with a rapid increase in incidence in recent years. Existing treatments cannot slow or stop the progression of PD. It was proposed that neuroinflammation leads to neuronal death, making targeting neuroinflammation a promising therapeutic strategy. Our previous studies have demonstrated that rhein protects neurons in vitro by inhibiting neuroinflammation, and it has been found to exhibit neuroprotective effects in Alzheimer's disease and epilepsy, but its neuroprotective mechanisms and effects on PD are still unclear. Methods: PD animal model was induced by 1-methyl-4-phenyl-1,2,3, 6-tetrahydropyridine (MPTP). ELISA, RT-qPCR, western blot and Immunofluorescence were used to detect the levels of inflammatory cytokines and M1 polarization markers. The protein expression levels of signaling pathways were measured by western blot. Hematoxylin-eosin (HE) staining showed that rhein did not damage the liver and kidney. Two behavioral tests, pole test and rotarod test, were used to evaluate the improvement effect of rhein on movement disorders. The number of neurons in the substantia nigra was evaluated by Nissl staining. Immunohistochemistry and western blot were used to detect tyrosine hydroxylase (TH) and α-synuclein. Results: Rhein inhibited the activation of MAPK/IκB signaling pathway and reduced the levels of pro-inflammatory cytokines (IL-1ß, IL-6 and TNF-α) and M1 polarization markers of microglia in vivo. In a mouse model of PD, rhein ameliorated movement disorders, reduced dopaminergic neuron damage and α-synuclein deposition. Conclusion: Rhein inhibits neuroinflammation through MAPK/IκB signaling pathway, thereby reducing neurodegeneration, α-synuclein deposition, and improving movement disorders in Parkinson's disease.

Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors.

With the massive release of microplastics (MPs) into the environment, research related to MPs is advancing rapidly. Effective research methods are necessary to identify the chemical composition, shape, distribution, and environmental impacts of MPs. In recent years, artificial intelligence (AI)-driven machine learning methods have demonstrated excellent performance in analyzing MPs in soil and water. This review provides a comprehensive overview of machine learning methods for the prediction of MPs for various tasks, and discusses in detail the data source, data preprocessing, algorithm principle, and algorithm limitation of applied machine learning. In addition, this review discusses the limitation of current machine learning methods for various task analysis in MPs along with future prospect. Finally, this review finds research potential in future work in building large generalized MPs datasets, designing high-performance but low-computational-complexity algorithms, and evaluating model interpretability.

Rhein inhibits M1 polarization of BV2 microglia through MAPK/IκB signalling pathway and reduces neurotoxicity caused by neuroinflammation.

BACKGROUND: Rhein is an anthraquinone compound with anti-inflammatory pharmacological activity. It has been found to play a neuroprotective role in neurological diseases, but the neuroprotective mechanism of rhein remains unclear. METHODS: SH-SY5Y cells serving as neuron-like cells and BV2 microglia were used. The toxicity of rhein on BV2 microglia and the viability of SH-SY5Y cells were measured by CCK-8 assay. The mRNA expression and secretion of pro-inflammatory cytokines were detected by qPCR and ELISA. Iba1, CD86 and pathway signalling protein in BV2 microglia were assessed by Western blot and immunofluorescence. Apoptosis of SH-SY5Y cells exposed to neuroinflammation was analysed through flow cytometry. RESULTS: Rhein inhibited MAPK/IκB signalling pathways. Further studies revealed that rhein inhibited the production of pro-inflammatory cytokines TNF-α, IL-6, IL-1ß and iNOS in BV2 cells and also inhibited the expression of M1 polarization markers Iba1 and CD86 in BV2 cells. Furthermore, rhein reduced the apoptotic rate and restored cell viability of SH-SY5Y cells exposed to neuroinflammation. CONCLUSIONS: Our study demonstrated that rhein inhibited microglia M1 polarization via MAPK/IκB signalling pathway and protected nerve cells through suppressing neuroinflammation.

Balancing High-performance and Lightweight: HL-UNet for 3D Cardiac Medical Image Segmentation.

RATIONALE AND OBJECTIVES: Cardiac magnetic resonance imaging is a crucial tool for analyzing, diagnosing, and formulating treatment plans for cardiovascular diseases. Currently, there is very little research focused on balancing cardiac segmentation performance with lightweight methods. Despite the existence of numerous efficient image segmentation algorithms, they primarily rely on complex and computationally intensive network models, making it challenging to implement them on resource-constrained medical devices. Furthermore, simplified models designed to meet the requirements of device lightweighting may have limitations in comprehending and utilizing both global and local information for cardiac segmentation. MATERIALS AND METHODS: We propose a novel 3D high-performance lightweight medical image segmentation network, HL-UNet, for application in cardiac image segmentation. Specifically, in HL-UNet, we propose a novel residual-enhanced Adaptive attention (REAA) module that combines residual-enhanced connectivity with an adaptive attention mechanism to efficiently capture key features of input images and optimize their representation capabilities, and integrates the Visual Mamba (VSS) module to enhance the performance of HL-UNet. RESULTS: Compared to large-scale models such as TransUNet, HL-UNet increased the Dice of the right ventricular cavity (RV), left ventricular myocardia (MYO), and left ventricular cavity (LV), the key indicators of cardiac image segmentation, by 1.61%, 5.03% and 0.19%, respectively. At the same time, the Params and FLOPs of the model decreased by 41.3 M and 31.05 G, respectively. Furthermore, compared to lightweight models such as the MISSFormer, the HL-UNet improves the Dice of RV, MYO, and LV by 4.11%, 3.82%, and 4.33%, respectively, when the number of parameters and computational complexity are close to or even lower. CONCLUSION: The proposed HL-UNet model captures local details and edge information in images while being lightweight. Experimental results show that compared with large-scale models, HL-UNet significantly reduces the number of parameters and computational complexity while maintaining performance, thereby increasing frames per second (FPS). Compared to lightweight models, HL-UNet shows substantial improvements across various key metrics, with parameter count and computational complexity approaching or even lower.

Root exudates and rhizosphere microbiota in responding to long-term continuous cropping of tobacco.

Soil sickness a severe problem in tobacco production, leading to soil-borne diseases and reduce in tobacco yield. This occurs as a result of the interaction between root exudates and rhizosphere microorganisms, which is however, little studied until now. By combining the field investigation and pot experiment, we found the output yield consistently decreased during the first 10 years of continuous cropping in a tobacco field, but increased at the 15th year (15Y). The root exudate and rhizosphere bacterial community was further analyzed to reveal the underlying mechanism of the suppressive soil formation. Root exudate of 15Y tobacco enriched in amino acids and derivatives, while depleted in the typical autotoxins including phenolic acids and alkaloids. This was correlated to the low microbial diversity in 15Y, but also the changes in community composition and topological properties of the co-occurrence network. Especially, the reduced autotoxins were associated with low Actinobacteria abundance, low network complexity and high network modularity, which significantly correlated with the recovered output yield in 15Y. This study revealed the coevolution of rhizosphere microbiota and root exudate as the soil domesticated by continuous cropping of tobacco, and indicated a potential role of the autotoxins and theirs effect on the microbial community in the formation of suppressive soil.

Pulmonary Rehabilitation Exercises Effectively Improve Chronic Cough After Surgery for Non-small Cell Lung Cancer.

INTRODUCTION: Cough is a major complication after lung cancer surgery, potentially impacting lung function and quality of life. However, effective treatments for managing long-term persistent postoperative cough remain elusive. In this study, we investigated the potential of a pulmonary rehabilitation training program to effectively address this issue. METHODS: Between January 2019 and December 2022, a retrospective review was conducted on patients with non-small cell lung cancer (NSCLC) who underwent lobectomy and lymph node dissection via video-assisted thoracoscopic surgery (VATS) at Daping hospital. Based on their postoperative rehabilitation methods, the patients were categorized into 2 groups: the traditional rehabilitation group and the pulmonary rehabilitation group. All patients underwent assessment using the Leicester cough questionnaire (LCQ) on the third postoperative day. Additionally, at the 6-month follow-up, patients' LCQ scores and lung function were re-evaluated to assess the long-term effects of the pulmonary rehabilitation training programs. RESULTS: Among the 276 patients meeting the inclusion criteria, 195 (70.7%) were in the traditional rehabilitation group, while 81 (29.3%) participated in the pulmonary rehabilitation group. The pulmonary rehabilitation group showed a significantly lower incidence of cough on the third postoperative day (16.0% vs 29.7%, P = .018) and higher LCQ scores in the somatic dimension (5.09 ± .81 vs 4.15 ± 1.22, P = .007) as well as in the total score (16.44 ± 2.86 vs 15.11 ± 2.51, P = .018, whereas there were no significant differences in psychiatric and sociological dimensions. At the 6-month follow-up, the pulmonary rehabilitation group continued to have a lower cough incidence (3.7% vs 12.8%, P = .022) and higher LCQ scores across all dimensions: somatic (6.19 ± .11 vs 5.75 ± 1.20, P = .035), mental (6.37 ± 1.19 vs 5.85 ± 1.22, P = .002), sociological (6.76 ± 1.22 vs 5.62 ± 1.08, P < .001), and total (18.22 ± 2.37 vs 16.21 ± 2.53, P < .001). Additionally, lung function parameters including FVC, FVC%, FEV1, FEV1%, MVV, MVV%, DLCO SB, and DLCO% were all significantly higher in the pulmonary rehabilitation group compared to the traditional group. CONCLUSION: Pulmonary rehabilitation exercises significantly reduced the incidence of postoperative cough and improved cough-related quality of life in patients undergoing lobectomy, with sustained benefits observed at the 6-month follow-up. Additionally, these exercises demonstrated superior lung function outcomes compared to traditional rehabilitation methods.

Pulmonary rehabilitation exercises significantly reduced the incidence of postoperative cough and improved cough-related quality of life in patients undergoing lobectomy, with sustained benefits observed at the 6-month follow-up. Additionally, these exercises demonstrated superior lung function outcomes compared to traditional rehabilitation methods.

The role of serum chloride ion in the prognosis of COPD.

BACKGROUND: As exacerbations of chronic obstructive pulmonary disease (COPD) are one of the leading causes of hospitalization and are associated with significant mortality, it is particularly important to accurately assess the risk of exacerbations in COPD. Most of the current clinical biomarkers are related to inflammation and few consider how ion levels affect COPD. Chloride ion, the second most abundant serum electrolyte, has been shown to be associated with poor prognoses in several diseases, but their relationship with COPD remains unclear. METHODS: In total, 105 patients with acute exacerbations of COPD were recruited. Data on clinical characteristics, lung function, blood count, blood biochemistry, relevant scales including the Clinical COPD Questionnaire (CCQ), BODE (BMI, airflow obstruction, dyspnea, exercise capacity) index and the St. George's Respiratory Questionnaire (SGRQ) were collected from all patients for statistical analysis. RESULT: There were significant differences in lung function indicators and disease severity in the low chloride ion subgroup compared with the high chloride ion subgroup. On multiple logistic regression analysis, chloride ion was an independent factor affecting lung function in COPD patients (OR=0.808, 95% CI: 0.708 - 0.922, p=0.002). The sensitivity of chloride ion in predicting COPD severity was 78%, the specificity was 63%, and the area under the curve was 0.734 (p<0.001). Subgroup analysis showed that chloride ion was a stronger predictor in male and smoking patients. CONCLUSIONS: Chloride ion was a novel prognostic biomarker for COPD, and low levels of chloride ion were independently associated with exacerbations in COPD patients.

Diversity of extracellular HSP70 in cancer: advancing from a molecular biomarker to a novel therapeutic target.

Heat shock protein 70 (HSP70) is a highly conserved protein functioning as a "molecular chaperone", which is integral to protein folding and maturation. In addition to its high expression within cells upon stressful challenges, HSP70 can be translocated to the cell membrane or released from cells in free form or within extracellular vesicles (EVs). Such trafficking of HSP70 is also present in cancer cells, as HSP70 is overexpressed in various types of patient samples across a range of common malignancies, signifying that extracellular HSP70 (eHSP70) can serve as a tumor biomarker. eHSP70 is involved in a broad range of cancer-related events, including cell proliferation and apoptosis, extracellular matrix (ECM) remodeling, epithelial-mesenchymal transition (EMT), angiogenesis, and immune response. eHSP70 can also induce cancer cell resistance to various treatments, such as chemotherapy, radiotherapy, and anti-programmed death-1 (PD-1) immunotherapy. Though the role of eHSP70 in tumors is contradictory, characterized by both pro-tumor and anti-tumor effects, eHSP70 serves as a promising target in cancer treatment. In this review, we comprehensively summarized the current knowledge about the role of eHSP70 in cancer progression and treatment resistance and discussed the feasibility of eHSP70 as a cancer biomarker and therapeutic target.

Continuous cropping system altered soil microbial communities and nutrient cycles.

Understanding the response of microbial communities and their potential functions is essential for sustainability of agroecosystems under long-term continuous cropping. However, limited research has focused on investigating the interaction between soil physicochemical factors and microbial community dynamics in agroecosystems under long-term continuous cropping. This study probed into the physicochemical properties, metabolites, and microbial diversity of tobacco rhizosphere soils cropped continuously for 0, 5, and 20 years. The relative abundance of bacterial genera associated with nutrient cycling (e.g., Sphingomonas) increased while potential plant pathogenic fungi and beneficial microorganisms showed synergistic increases with the duration of continuous cropping. Variations in soil pH, alkeline nitrogen (AN) content, and soil organic carbon (SOC) content drove the shifts in soil microbial composition. Metabolites such as palmitic acid, 3-hydroxypropionic acid, stearic acid, and hippuric acid may play a key role in soil acidification. Those results enhance our ability to predict shifts in soil microbial community structure associated with anthropogenic continuous cropping, which can have long-term implications for crop production.

Sulfatase-Induced In Situ Formulation of Antineoplastic Supra-PROTACs.

Proteolysis targeting chimera (PROTAC) technology is an innovative strategy for cancer therapy, which, however, suffers from poor targeting delivery and limited capability for protein of interest (POI) degradation. Here, we report a strategy for the in situ formulation of antineoplastic Supra-PROTACs via intracellular sulfatase-responsive assembly of peptides. Coassembling a sulfated peptide with two ligands binding to ubiquitin VHL and Bcl-xL leads to the formation of a pro-Supra-PROTAC, in which the ratio of the two ligands is rationally optimized based on their protein binding affinity. The resulting pro-Supra-PROTAC precisely undergoes enzyme-responsive assembly into nanofibrous Supra-PROTACs in cancer cells overexpressing sulfatase. Mechanistic studies reveal that the pro-Supra-PROTACs selectively cause apparent cytotoxicity to cancer cells through the degradation of Bcl-xL and the activation of caspase-dependent apoptosis, during which the rationally optimized ligand ratio improves the bioactivity for POI degradation and cell death. In vivo studies show that in situ formulation enhanced the tumor accumulation and retention of the pro-Supra-PROTACs, as well as the capability for inhibiting tumor growth with excellent biosafety when coadministrating with chemodrugs. Our findings provide a new approach for enzyme-regulated assembly of peptides in living cells and the development of PROTACs with high targeting delivering and POI degradation efficiency.

Recurrence timing and patterns incorporating lymph node status after neoadjuvant chemoradiotherapy plus esophagectomy for esophageal squamous cell carcinoma.

Purpose: About 40% of esophageal squamous cell carcinoma (ESCC) patients experienced recurrence after neoadjuvant chemoradiotherapy (nCRT) plus esophagectomy. While limited information was available on recurrence risk stratification in ESCC after neoadjuvant treatment. Our previous study showed ypN status was a reliable tool to differentiate and predict the prognosis in the recurrent population. Here, we evaluated recurrence timing and patterns in ESCC patients, taking into consideration lymph node status after nCRT. Materials and methods: A total of 309 ESCC patients treated with nCRT plus esophagectomy between 2018 and 2021 were enrolled in this observational cohort study. Lymph node status was recorded by the pathologist according to the surgical specimens. We retrospectively investigated the timing and patterns of recurrence and the prognoses in ESCC patients, taking into consideration lymph node status after nCRT. Results: After nCRT plus surgery in ESCC patients, lymph node metastasis was associated with unfavorable clinicopathological factors and high risks of recurrence. In the recurrent subgroup, ypN+ patients experienced earlier recurrence, especially for locoregional recurrence within the first year. Moreover, ypN+ patients had poorer prognosis. However, the recurrence patterns in the ypN- and ypN+ groups were similar. Besides, there were no significant differences in surgery to recurrence, recurrence to death, or overall survival among patients with locoregional or distant recurrence for overall patients and within ypN- or ypN+ groups. Conclusions: Lymph node metastasis was correlated with unfavorable clinicopathological factors and high risks of recurrence. Despite a similar recurrence pattern in the recurrent subgroup between the ypN- and ypN+ groups, ypN+ patients exhibited earlier recurrence and a worse prognosis.

Redox-Regulated In Situ Seed-Induced Assembly of Peptides.

Morphology-transformational self-assembly of peptides allows for manipulation of the performance of nanostructures and thereby advancing the development of biomaterials. Acceleration of the morphological transformation process under a biological microenvironment is important to efficiently implement the tailored functions in living systems. Herein, we report redox-regulated in situ seed-induced assembly of peptides via design of two co-assembled bola-amphiphiles serving as a redox-resistant seed and a redox-responsive assembly monomer, respectively. Both of the peptides are able to independently assemble into nanoribbons, while the seed monomer exhibits stronger assembling propensity. The redox-responsive monomer undergoes morphological transformation from well-defined nanoribbons to nanoparticles. Kinetics studies validate the role of the assembled inert monomer as the seeds in accelerating the assembly of the redox-responsive monomer. Alternative addition of oxidants and reductants into the co-assembled monomers promotes the redox-regulated assembly of the peptides facilitated by the in situ-formed seeds. The reduction-induced assembly of the peptide could also be accelerated by in situ-formed seeds in cancer cells with a high level of reductants. Our findings demonstrate that through precisely manipulating the assembling propensity of co-assembled monomers, the in situ seed-induced assembly of peptides could be achieved. Combining the rapid assembly kinetics of the seed-induced assembly with the common presence of redox agents in a biological microenvironment, this strategy potentially offers a new method for developing biomedical materials in living systems.

Nomogram for predicting pathologic complete response to neoadjuvant chemoradiotherapy in patients with esophageal squamous cell carcinoma.

PURPOSE: A pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) is seen in up to 40% of the patients with esophageal squamous cell carcinoma (ESCC). No nomogram has been constructed for the prediction of pCR for patients whose primary chemotherapy was a taxane-based regimen. The aim is to identify characteristics associated with a pCR through analyzing multiple pre- and post-nCRT variables and to develop a nomogram for the prediction of pCR for these patients by integrating clinicopathological characteristics and hematological biomarkers. MATERIALS AND METHODS: We analyzed 293 patients with ESCC who underwent nCRT followed by esophagectomy. Clinicopathological factors, hematological parameters before nCRT, and hematotoxicity during nCRT were collected. Univariate and multivariate logistic regression analyses were performed to identify predictive factors for pCR. A nomogram model was built and evaluated for both discrimination and calibration. RESULTS: After surgery, 37.88% of the study patients achieved pCR. Six variables were included in the nomogram: sex, cN stage, chemotherapy regimen, duration of nCRT, pre-nCRT neutrophil-to-lymphocyte ratio (NLR), and pre-nCRT platelet-to-lymphocyte ratio (PLR). The nomogram indicated good accuracy and consistency in predicting pCR, with a C-index of 0.743 (95% confidence interval: 0.686, 0.800) and a p value of 0.600 (>0.05) in the Hosmer-Lemeshow goodness-of-fit test. CONCLUSIONS: Female, earlier cN stage, duration of nCRT (< 62 days), chemotherapy regimen of taxane plus platinum, pre-nCRT NLR (≥2.199), and pre-nCRT PLR (≥99.302) were significantly associated with a higher pCR in ESCC patients whose primary chemotherapy was a taxane-based regimen for nCRT. A nomogram was developed and internally validated, showing good accuracy and consistency.

Immune checkpoint inhibitor-associated cardiovascular toxicities: A review.

Immune checkpoint inhibitors (ICIs) have revolutionary effects on therapeutic strategies for multiple malignancies. Their efficacy depends on their ability to reactivate the host immune system to fight cancer cells. However, adverse reactions to ICIs are common and involve several organs, limiting their use in clinical practice. Although the incidence of cardiovascular toxicity is relatively low, it is associated with serious consequences and high mortality rates. The primary cardiovascular toxicities include myocarditis, pericarditis, Takotsubo syndrome, arrhythmia, vasculitis, acute coronary syndrome, and venous thromboembolism. Currently, the mechanism underlying ICI-associated cardiovascular toxicity remains unclear and underexplored. The diagnosis and monitoring of ICI-associated cardiovascular toxicities mainly include the following indicators: symptoms, signs, laboratory examination, electrocardiography, imaging, and pathology. Treatments are based on the grade of cardiovascular toxicity and mainly include drug withdrawal, corticosteroid therapy, immunosuppressants, and conventional cardiac treatment. This review focuses on the incidence, underlying mechanisms, clinical manifestations, diagnoses, and treatment strategies.

Pathological α-synuclein detected by real-time quaking-induced conversion in synucleinopathies.

synucleinopathies are diseases characterized by the aggregation of α-synuclein (α-syn), which forms fibrils through misfolding and accumulates in a prion-like manner. To detect the presence of these α-syn aggregates in clinical samples, seed amplification assays (SAAs) have been developed. These SAAs are capable of amplifying the α-syn seeds, allowing for their detection. αSyn-SAAs have been reported under the names 'protein misfolding cyclic amplification' (αSyn-PMCA) and 'real-time quaking-induced conversion'α-Syn-RT-QuIC. The α-Syn RT-QuIC, in particular, has been adapted to amplify and detect α-syn aggregates in various biospecimens, including cerebrospinal fluid (CSF), skin, nasal brushing, serum and saliva. The α-syn RT-QuIC assay has demonstrated good sensitivity and specificity in detecting pathological α-syn, particularly in Parkinson's disease (PD) and dementia with Lewy bodies (DLB) cases, with an accuracy rate of up to 80 %. Additionally, differential diagnosis between DLB and PD, as well as PD and multiple system atrophy (MSA), can be achieved by utilizing certain kinetic thioflavin T (ThT) parameters and other parameters. Moreover, the positive detection of α-syn in the prodromal stage of synucleinopathies provides an opportunity for early intervention and management. In summary, the development of the α-syn RT-QuIC assay has greatly contributed to the field of synucleinopathies. Therefore, we review the development of α-syn RT-QuIC assay and describe in detail the recent advancements of α-syn RT-QuIC assay for detecting pathological α-syn in synucleinopathies.

LeaNet: Lightweight U-shaped architecture for high-performance skin cancer image segmentation.

Skin cancer diagnosis often relies on image segmentation as a crucial aid, and a high-performance segmentation can lower misdiagnosis risks. Part of the medical devices often have limited computing power for deploying image segmentation algorithms. However, existing high-performance algorithms for image segmentation primarily rely on computationally intensive large models, making it challenging to meet the lightweight deployment requirement of medical devices. State-of-the-art lightweight models are not able to capture both local and global feature information of lesion edges due to their model structures, result in pixel loss of lesion edge. To tackle this problem, we propose LeaNet, a novel U-shaped network for high-performance yet lightweight skin cancer image segmentation. Specifically, LeaNet employs multiple attention blocks in a lightweight symmetric U-shaped design. Each blocks contains a dilated efficient channel attention (DECA) module for global and local contour information and an inverted external attention (IEA) module to improve information correlation between data samples. Additionally, LeaNet uses an attention bridge (AB) module to connect the left and right sides of the U-shaped architecture, thereby enhancing the model's multi-level feature extraction capability. We tested our model on ISIC2017 and ISIC2018 datasets. Compared with large models like ResUNet, LeaNet improved the ACC, SEN, and SPEC metrics by 1.09 %, 2.58 %, and 1.6 %, respectively, while reducing the model's parameter number and computational complexity by 570x and 1182x. Compared with lightweight models like MALUNet, LeaNet achieved improvements of 2.07 %, 4.26 %, and 3.11 % in ACC, SEN, and SPEC, respectively, reducing the parameter number and computational complexity by 1.54x and 1.04x.