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Abstract Improving cancer therapy by targeting the adverse tumor microenvironment (TME) rather than the cancer cells presents a novel and potentially effective strategy. In this study, we introduced FexMoyS nanoparticles (NPs), which act as sequential bioreactors to manipulate the TME. FexMoyS NPs were synthesized using thermal decomposition and modified with polyethylene glycol (PEG). Their morphology, chemical composition, and photothermal properties were characterized. The capability to produce ROS and deplete GSH was evaluated. Effects on CRC cells, including cell viability, apoptosis, and glycolysis, were tested through various in vitro assays. In vivo efficacy was determined using CRC-bearing mouse models and patient-derived xenograft (PDX) models. The impact on the MAPK signaling pathway and tumor metabolism was also examined. The FexMoyS NPs showed efficient catalytic activity, leading to increased ROS production and GSH depletion, inducing ferroptosis, and suppressing glycolysis in CRC cells. In vivo, the NPs significantly inhibited tumor growth, particularly when combined with NIR light therapy, indicating a synergistic effect of photothermal therapy and chemodynamic therapy. Biosafety assessments revealed no significant toxicity in treated mice. RNA sequencing suggested that the NPs impact metabolism and potentially immune processes within CRC cells. FexMoyS NPs present a promising multifaceted approach for CRC treatment, effectively targeting tumor cells while maintaining biosafety. The nanoparticles exhibit potential for clinical translation, offering a new avenue for cancer therapy.

Objectives: To investigate the health-related quality of life (HRQL) of long-term survivors of inoperable esophageal squamous cell carcinoma (ESCC) treated with definitive radiation therapy, the real-world trends in the use of advanced radiation techniques, and their impact on the survival outcomes of ESCC patients. Methods: In this multicenter retrospective observational study, the medical records related to demographics and treatment of ESCC patients who were treated with definitive radiation therapy at 14 provincial hospitals in China from 1 January 2015 to 31 December 2016 were analyzed. A HRQL questionnaire was completed by survivors and collected by doctors at the final follow-up. The difference in quality of life between patients with or without recurrence was compared using the Wilcoxon–Mann–Whitney test. Overall survival (OS) was estimated using the Kaplan–Meier method and the group differences were assessed by unstratified log-rank test. The Cox proportional hazards model with Efron's method of tie handling was used to calculate the risk factors for OS. Results: The data of a total of 3,308 patients were collected for this study, 248 were excluded because of missing data, and a final of 3,060 patients were included in the analysis. Most patients (2,901; 94.8%) received intensity-modulated radiotherapy (IMRT)/volumetric-modulated arc therapy (VMAT)/tomotherapy (TOMO). The 5-year OS rate was 30%. Patients who received either two-dimensional radiotherapy (2DRT; HR, 2.43 [95% CI, 1.70–3.47]; P 80% patients did not experience weight loss. Nearly 80% patients found life very enjoyable or were fairly enjoying life. Conclusions: This large, multicenter retrospective study on ESCC patients who received definitive radiation therapy found that most ESCC survivors are satisfied with their quality of life. Most patients received advanced radiation technology. Patients who received either 2DRT or 3DRT had a significantly increased risk of death compared to those who received advanced radiation technology.

The contamination of food by microplastics has garnered widespread attention, particularly concerning the health risks associated with small-sized microplastics. However, detecting these smaller microplastics in food poses challenges attributed to the complexity of food matrices and instrumental and method limitations. Here, we employed Raman imaging for visualization and identification of polystyrene particles synthesized in polymerization reactions, ranging from 400 to 2600 nm. We successfully developed a quantitative model of particle size and concentration for polystyrene, exhibiting excellent fit (R2 of 0.9946). We established procedures for spiked flavored yogurt using synthesized polystyrene, providing fresh insights into microplastic extraction efficiency. Recovery rates calculated from models validated the method’s feasibility. In practical applications, the assessment of the size, type, shape, and quantity of microplastics in unspiked flavored yogurt was conducted. The most common polymers found were polystyrene, polypropylene, and polyethylene, with the smallest polystyrene sizes ranging from 1 to 10 μm. Additionally, we conducted exposure assessments of microplastics in branded flavored yogurt. This study established a foundation for developing a universal method to quantify microplastics in food, covering synthesis of standards, method development, validation, and application.

Abstract Cutaneous melanoma could be treated by immunotherapy, which only has limited efficacy on uveal melanoma (UM). UM immunotyping for predicting immunotherapeutic responses and guiding immunotherapy should be better understood. This study identified molecular subtypes and key genetic markers associated with immunotherapy through immunosignature analysis. We screened a 6-immune cell signature simultaneously correlated with UM prognosis. Three immune subtypes (IS) were determined based on the 6-immune cell signature. Overall survival (OS) of IS3 was the longest. Significant differences of linear discriminant analysis (LDA) score were detected among the three IS types. IS3 with the highest LDA score showed a low immunosuppression. IS1 with the lowest LDA score was more immunosuppressive. LDA score was significantly negatively correlated with most immune checkpoint-related genes, and could reflect UM patients’ response to anti-PD1 immunotherapy. Weighted correlation network analysis (WGCNA) identified that salmon, purple, yellow modules were related to IS and screened 6 prognostic genes. Patients with high-expressed NME1 and TMEM255A developed poor prognosis, while those with high-expressed BEX5 and ROPN1 had better prognosis. There was no notable difference in OS between patients with high-expressed LRRN1 and ST13 and those with low-expressed LRRN1 and ST13. NME1, TMEM255A, Bex5 and ROPN1 showed potential prognostic significance in UM.

Abstract Background Colorectal cancer (CRC) is one of the most frequent malignancy and a leading cause of cancer-related deaths. Therefore, further researches are required to identify novel and more effective diagnoses and to identify molecular targets in treatment of CRC. Methods C2CD4A expression in CRC tissues and cell lines was detected by qRT-PCR and western blot. The biological functions of C2CD4A were performed both in vitro and in vivo. Western blot, cDNA array, IP-MS, Co-immunoprecipitation assay, and Ubiquitination assay were used to analyze the interaction between C2CD4A and p53. Bioinformatics analysis, FISH, RNA sequencing, luciferase reporter assay, RNA immunoprecipitation, RNA pull-down and rescue experiments, were deployed to detect upstream regulation mechanism of C2CD4A. Results C2CD4A was elevated in CRC tissues compared with adjacent normal colorectal tissues. C2CD4A knockdown significantly promoted cell apoptosis and with inhibited proliferation in vitro, and tumorigenicity in vivo, whereas C2CD4A overexpression led to opposite effects. Moreover, circSLC6A6 was upregulated and shown to positively regulate C2CD4A expression via sponging miR-1265. Fundamentally, C2CD4A inhibited p53 signaling pathway through interacting with p53 and increasing its ubiquitination and degradation. Conclusion Our results identified that circSLC6A6/miR-1265/C2CD4A axis, which was involved in CRC via the p53 signaling pathway, may serve as a therapeutic target for CRC.

This paper presents an SOC (State of Charge) prediction method based on a chaotic time series Volterra adaptive filter. This method first verifies the chaotic characteristics of the SOC time series of lithium-ion batteries and then implements the phase space reconstruction method to reorganize the voltage and current data into multi-dimensional data. Furthermore, we use the Volterra adaptive filter to predict the SOC of the lithium-ion battery pack on the reconstructed multi-dimensional data. This method can effectively solve the problem that the SOC estimation error increases due to the poor real-time performance of battery voltage, current, and other parameters of vehicular lithium-ion battery packs in electric vehicles obtained by the battery management system. According to the simulation and test results, the error of the SOC estimation algorithm studied in this paper is less than 0.6%, which indicates that the Volterra adaptive filter based on chaotic time series comprehensively uses the linear and non-linear parameter characteristics of lithium-ion batteries and recombines the voltage and current data into multi-dimensional data through phase space reconstruction technology. It can reveal the relationship between the battery SOC and other variables better, achieve higher precision lithium-ion battery SOC prediction, and have better realizability.

Pancreatic cancer (PC) is one of the deadliest gastrointestinal malignancies. Advances in molecular biology and surgery have significantly improved survival rates for other tumors in recent decades, but clinical outcomes for PC remained relatively unchanged. Chemodynamic therapy (CDT) and Photothermal therapy (PTT) represent an efficient and relatively safe cancer treatment modality. Here, we synthesized Mn-doped Prussian blue nanoparticles (MnPB NPs) through a simple and mild method, which have a high loading capacity for drugs and excellent CDT/PTT effect. Cell line experiments in vitro and animal experiments in vivo proved the safety of MnPB NPs. We stimulated the PC cells with MnPB NPs and performed transwell migration assays. The migration of PC cells was reduced company with the decrease of two classical proteins: matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9). Moreover, MnPB NPs induced ferroptosis, which mediated the MAPK pathway and achieved tumor elimination in nude mice. This effective and safe strategy controlled by irradiation represents a promising strategy for pancreatic cancer.

Transmission line fault detection using drones provides real-time assessment of the operational status of transmission equipment, and therefore it has immense importance in ensuring stable functioning of the transmission lines. Currently, identification of transmission line equipment relies predominantly on manual inspections that are susceptible to the influence of natural surroundings, resulting in sluggishness and a high rate of false detections. In view of this, in this study, we propose an insulator defect recognition algorithm based on a YOLOv5 model with a new lightweight network as the backbone network, combining noise reduction and target detection. First, we propose a new noise reduction algorithm, i.e., the adaptive neighborhood-weighted median filtering (NW-AMF) algorithm. This algorithm employs a weighted summation technique to determine the median value of the pixel point’s neighborhood, effectively filtering out noise from the captured aerial images. Consequently, this approach significantly mitigates the adverse effects of varying noise levels on target detection. Subsequently, the RepVGG lightweight network structure is improved to the newly proposed lightweight structure called RcpVGG-YOLOv5. This structure facilitates single-branch inference, multi-branch training, and branch normalization, thereby improving the quantization performance while simultaneously striking a balance between target detection accuracy and speed. Furthermore, we propose a new loss function, i.e., Focal EIOU, to replace the original CIOU loss function. This optimization incorporates a penalty on the edge length of the target frame, which improves the contribution of the high-quality target gradient. This modification effectively addresses the issue of imbalanced positive and negative samples for small targets, suppresses background positive samples, and ultimately enhances the accuracy of detection. Finally, to align more closely with real-world engineering applications, the dataset utilized in this study consists of machine patrol images captured by the Unmanned Aerial Systems (UAS) of the Yunnan Power Supply Bureau Company. The experimental findings demonstrate that the proposed algorithm yields notable improvements in accuracy and inference speed compared to YOLOv5s, YOLOv7, and YOLOv8. Specifically, the improved algorithm achieves a 3.7% increase in accuracy and a 48.2% enhancement in inference speed compared to those of YOLOv5s. Similarly, it achieves a 2.7% accuracy improvement and a 33.5% increase in inference speed compared to those of YOLOv7, as well as a 1.5% accuracy enhancement and a 13.1% improvement in inference speed compared to those of YOLOv8. These results validate the effectiveness of the proposed algorithm through ablation experiments. Consequently, the method presented in this paper exhibits practical applicability in the detection of aerial images of transmission lines within complex environments. In future research endeavors, it is recommended to continue collecting aerial images for continuous iterative training, to optimize the model further, and to conduct in-depth investigations into the challenges associated with detecting small targets. Such endeavors hold significant importance for the advancement of transmission line detection.

Colorectal cancer (CRC) is one of the most common cancers of the digestive tract, and patients with advanced-stage cancer have poor survival despite the use of multidrug conventional chemotherapy regimens. Intra-tumor heterogeneity of cancerous cells is the main obstacle in the way to effective cancer treatments. Therefore, we are looking for novel approaches to eliminate just cancer cells including nanoparticles (NPs). PPy@Fe3O4 NPs were successfully synthesized through a portable method. The characterization of transmission electron microscopy (TEM), Fourier-Transformed infrared spectrometer, and X-ray powder diffraction have further proved successful preparation of PPy@Fe3O4 NPs. NIR irradiation was used to test the photothermal properties of NPs and an infrared camera was used to record their temperature. The direct effects of PPy@Fe3O4 NPs on colorectal cancer cell DLD1 were assessed using CCK8, plate clone, transwell, flow cytometry, and western blotting in CRC cell. The effect of PPy@Fe3O4 NPs on neoplasm growth in nude mice was evaluated in vivo. This study demonstrated that PPy@ Fe3O4 NPs significantly inhibit the growth, migration, and invasion and promote ferroptosis to the untreated controls in colorectal cancer cells. Mechanical exploration revealed that PPy@Fe3O4 NPs inhibit the multiplication, migration, and invasion of CRC cells in vitro by modulating the NF-κB signaling pathway. Importantly, Ferroptosis inhibitors Fer-1 can reverse the changes in metastasis-associated proteins caused by NPs treatment. Collectively, our observations revealed that PPy@Fe3O4 NPs were blockers of tumor progression and metastasis in CRC. This study brought new insights into bioactive NPs, with application potential in curing CRC or other human disorders.

Molecular classification based on transcriptional characteristics is often used to study tumor heterogeneity. Human cancer has different cell populations with distinct transcription in tumors, and their heterogeneity is the focus of tumor therapy. Our purpose was to explore the tumor heterogeneity of uveal melanoma (UM) through RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq). Based on the consensus clustering assays of the prognosis-related immune gene set, the immune subtype (IS) of UM and its corresponding immune characteristics were comprehensively analyzed. The heterogeneous cell groups and corresponding marker genes of UM were identified from GSE138433 using scRNA-seq analysis. Pseudotime trajectory analysis and SCENIC analysis were conducted to explore the trajectory of cell differentiation and the regulatory network of single-cell transcription factors (TFs). Based on 37 immune gene sets, UM was divided into two different immune subtypes (IS1 and IS2). The two kinds of ISs have different characteristics in prognosis, immune-related molecules, immune score, and immune cell infiltration. According to 11,988 cells of scRNA-seq data from six UM samples, 11 cell clusters and 10 cell types were identified. The subsets of C1, C4, C5, C8, and C9 were related to the prognosis of UM, and different TF–target gene regulatory networks were involved. These five cell subsets differentiated into 3 different states. Our results provided valuable information about the heterogeneity of UM tumors and the expression patterns of TFs in different cell types.

Abstract Purpose To investigate the interobserver variability (IOV) in target volume delineation of definitive radiotherapy for thoracic esophageal cancer (TEC) among cancer centers in China, and ultimately improve contouring consistency as much as possible to lay the foundation for multi-center prospective studies. Methods Sixteen cancer centers throughout China participated in this study. In Phase 1, three suitable cases with upper, middle, and lower TEC were chosen, and participants were asked to contour a group of gross tumor volume (GTV-T), nodal gross tumor volume (GTV-N) and clinical target volume (CTV) for each case based on their routine experience. In Phase 2, the same clinicians were instructed to follow a contouring protocol to re-contour another group of target volume. The variation of the target volume was analyzed and quantified using dice similarity coefficient (DSC). Results Sixteen clinicians provided routine volumes, whereas ten provided both routine and protocol volumes for each case. The IOV of routine GTV-N was the most striking in all cases, with the smallest DSC of 0.37 (95% CI 0.32–0.42), followed by CTV, whereas GTV-T showed high consistency. After following the protocol, the smallest DSC of GTV-N was improved to 0.64 (95% CI 0.45–0.83, P = 0.005) but the DSC of GTV-T and CTV remained constant in most cases. Conclusion Variability in target volume delineation was observed, but it could be significantly reduced and controlled using mandatory interventions.

Abstract Stainless steels are widely used in hospitals and public transportation vehicles as one of the most common touch surfaces. Retrofitting stainless steel surfaces with an antimicrobial layer can bring potential public health benefits by reducing the ability of inanimate objects, or fomites, to transmit infections. Here, a facile surface conversion reaction between stainless steel and a solution of KMnO4 and CuSO4 is reported, which leads to a conformal and robust oxyhydroxide layer. Microscopy observations show that the layer is amorphous, continuous, and pinhole‐free with a thickness of only 10–15 nm. The coating adheres strongly to stainless steel and can resist rubbing in simulated friction tests, which is attributed to its intermixing with the substrate without forming a sharp interface. Cu ions incorporated into the surface layer can be released into water droplets deposited on the surface and induce antimicrobial activities against bacteria (Pseudomonas aeruginosa PA14) after 30 min of contact.

Abstract Background As a novel type of noncoding RNAs, covalently closed circular RNAs (circRNAs) are ubiquitously expressed in eukaryotes. Emerging studies have related dysregulation of circRNAs to tumorigenesis. However, the biogenesis, regulation, function and mechanism of circRNAs in gastric cancer (GC) remain largely unclear. Methods The expression profile of circRNAs in 6 pairs of GC tissues and adjacent non-tumor tissues was analyzed by RNA-sequencing. Quantitative real-time PCR was used to determine the expression level of circCCDC9 in GC tissues and cell lines. Then, functional experiments in vitro and in vivo were employed to explore the effects of circCCDC9 on tumor growth and metastasis in GC. Mechanistically, dual luciferase reporter, fluorescence in situ hybridization (FISH), RNA immunoprecipitation (RIP) and RNA pull-down assays were performed to confirm that circCCDC9 directly sponged miR-6792-3p and alleviated suppression on target CAV1 expression. Results Evidently down-regulated expression of circCCDC9 was observed in both GC tissues and cell lines. Expression of circCCDC9 was negatively correlated with tumor size, lymph node invasion, advanced clinical stage and overall survival in GC patients. Functionally, overexpression of circCCDC9 significantly inhibited the proliferation, migration and invasion of GC cell lines in vitro and tumor growth and metastasis in vivo, whereas miR-6792-3p mimics counteracted these effects. Mechanistic analysis demonstrated that circCCDC9 acted as a “ceRNA” of miR-6792-3p to relieve the repressive effect of miR-6792-3p on its target CAV1, then suppressed the tumorigenesis of GC. Conclusions CircCCDC9 functions as a tumor suppressor in inhibiting the progression of GC through miR-6792-3p/CAV1 axis, which has provided an exploitable biomarker and therapeutic target for patients with GC.

The exact region of attraction plays an important role in autonomous nonlinear system, while the results based on the conventional method, such as Lyapunov function approach, are always conservative. However, results via the manifold method, which is the main approach studied, are exact. This method optimizes the distribution of points on the circle through modifying the end point of the former trajectory and inserting/deleting point on the circle on the basis of trajectory arc length method to improve the accuracy and efficiency. First, the basic theory of manifold method is introduced. Secondly, a methodology for determining stable manifold are proposed, which is the core of the manifold method in stability boundary determining. Finally, on this basis, three examples about academic model, power system and aviation system are taken to illustrate the advantages of the method. The results show that the method can improve the accuracy and significantly reduce the calculation time, and can be widely used in engineering systems.

Battery capacity is an important metric for evaluating and predicting the health status of lithium-ion batteries. In order to determine the answer, the battery’s capacity must be, with some difficulty, directly measured online with existing methods. This paper proposes a multi-dimensional health indicator (HI) battery state of health (SOH) prediction method involving the analysis of the battery equivalent circuit model and constant current discharge characteristic curve. The values of polarization resistance, polarization capacitance, and initial discharge resistance are identified as the health indicators reflective of the battery’s state of health. Moreover, the retention strategy genetic algorithm (e-GA) selects the optimal voltage drop segment, and the corresponding equal voltage drop discharge time is also used as a health indicator. Based on the above health indicator selection strategy, a battery SOH prediction model based on particle swarm optimization (PSO) and LSTM neural network is constructed, and its accuracy is validated. The experimental results demonstrate that the suggested strategy is accurate and generalizable. Compared with the prediction model with single health indicator input, the accuracy is increased by 0.79%.

This work develops a morphing decision strategy to optimize the cruising efficiency for a variable-sweep morphing aircraft, and a simple and practical guidance and control system is given as well. They can work in tandem to accomplish a cruise mission effectively. To make the morphing decision accurately, we take into account the equilibrium equations of forces; the variations in airspeed, altitude, and mass and the optimal configurations for different cruise conditions are solved based on the nonlinear programming method with the objective of minimum engine thrust. Considering that a large amount of computational resources are required to solve the nonlinear programming problems, we establish an offline database of the optimal configurations and design a database-based online morphing decision process. In addition, the proposed morphing decision strategy includes an anti-disturbance mechanism, which ensures that the optimal configuration can be given accurately without chattering under fluctuating airspeed measurements. Comparative results from the simulations finally validate the effectiveness of the proposed strategy.

Gastric cancer (GC) is one of the digestive tract malignancies with high invasion and mortality rates. Recent studies have reported that non-coding RNAs (ncRNAs) seem to play a crucial part in many tumors. Due to their high stability, ncRNAs may used as novel biomarkers to predict the occurrence and prognosis of GC. Here, we measured miRNA, lncRNA and cirRNA expression profiles of GC patients by using microarray and RNA-sequencing data from tissue samples. The diagnosis prediction model based on the ncRNA signatures and clinical features was evaluated by circulating and tissue validation and ROC analysis. Nine miRNAs and eight lncRNAs were obtained from the microarray analysis. Six miRNAs (miR-550a-5p, miRNA-936, miR-1306-3p, miR-3185, miR-6083, miR-6792-3p) and three lncRNAs (lnc-MB21D1-3:5, lnc-PSCA-4:2 and lnc-ABCC5-2:1) were abnormally expressed in circulating and tissue samples compared with normal control (NC), which was closely related to clinical pathology and survival time of GC patients; circRNA sequencing and qRT-PCR revealed four circRNAs (circASHL2, circCCDC9, circNHSL1 and cirMLLT10) were abnormally expressed in GC tissues and parts of them were negative relationship with their predicted binding miRNAs. These ncRNAs might act as promising molecular markers for the diagnosis and prognosis of gastric cancer.

Abstract Background Mounting evidences indicate that circular RNAs (circRNAs) play vital roles in the development and progression of various cancers. However, the detail functions and underlying mechanisms of circRNAs in gastric cancer remain largely unknown. Methods The expression profile of metastasis-related circRNAs was screened by RNA-seq analysis. qRT-PCR was used to determine the level and prognostic values of circNHSL1 in gastric cancer tissues. In vitro cell wound healing and transwell (migration and invasion) and in vivo tumorigenesis and metastasis assays were performed to evaluate the functions of circNHSL1. Luciferase reporter, RNA immunoprecipitation (RIP) and rescued assays were employed to confirm the interactions between circNHSL1, miR-1306-3p and SIX1. It’s widely accepted that as a mesenchymal marker, Vimentin promotes invasion and metastasis in various cancers. Luciferase reporter assay was used to determine the regulation of SIX1 on Vimentin. In addition, In situ hybridization (ISH) was performed to detect the level and prognostic values of miR-1306-3p. Results We found that the level of circNHSL1 was significantly up-regulated in gastric cancer, and positively correlated with clinicopathological features and poor prognosis of patients with gastric cancer. Functionally, circNHSL1 promoted cell mobility and invasion, as well as in vivo tumorgenesis and metastasis. Mechanistically, circNHSL1 acted as a miR-1306-3p sponge to relieve the repressive effect of miR-1306-3p on its target SIX1. Moreover, SIX1 enhanced Vimentin expression in the transcriptional level through directly binding to the promoter domain of Vimentin, thereby promoting cell migration and invasion. In addition, miR-1306-3p was down-regulated and negatively correlated with pathological features and poor prognosis in gastric cancer. Conclusions CircNHSL1 promotes gastric cancer progression through miR-1306-3p/SIX1/Vimentin axis, and may serve as a novel diagnostic marker and target for treatment of gastric cancer patients.

Background/Aims: Krüppel-like factor 4 (KLF4), a member of the KLF family of zinc finger transcription factors, has been identified as a tumor suppressor gene in a variety of tumors. However, the molecular mechanisms by which KLF4 inhibits epithelial-to-mesenchymal transition (EMT) and metastasis in pancreatic cancer remain unclear. Methods: KLF4 expression in pancreatic cancer was analyzed using public datasets (Oncomine and The Cancer Genome Atlas). The expression of KLF4, caveolin-1 (Cav-1), E-cadherin, and vimentin, and their correlations with clinicopathological characteristics were evaluated by immunohistochemistry in pancreatic cancer tissues. The biological functions and underlying mechanisms of KLF4 expression on EMT and metastasis were also investigated in vitro and in vivo. Results: Public datasets showed that KLF4 expression was significantly decreased in pancreatic cancer and correlated with the depth of invasion and disease stage. The expression of KLF4, Cav-1, E-cadherin, and vimentin protein in pancreatic cancer tissues was closely associated with pathological grade, disease stage, and metastasis. KLF4 expression was also positively correlated with E-cadherin expression and negatively correlated with vimentin expression, whereas Cav-1 expression was negatively associated with E-cadherin expression and positively correlated with vimentin expression. Knockdown of KLF4 expression promoted EMT and facilitated pancreatic cancer cell growth and metastasis in vitro and in vivo. In addition, immunohistochemistry (IHC) results indicated that KLF4 expression was negatively correlated with Cav-1 expression. Furthermore, down-regulating KLF4 expression increased Cav-1 and vimentin expression and decreased E-cadherin expression. Mechanistically, KLF4 could transcriptionally inhibit Cav-1 expression by binding directly to the promoter domain of Cav-1. Conclusions: KLF4 inhibits pancreatic cancer EMT and metastasis by down-regulating Cav-1 expression, suggesting that the KLF4/Cav-1 signaling pathway may be a novel diagnostic and therapeutic target.

After publication of the article [1], the authors reported errors of inter-duplication in Figure 3.

Food detection technologies play a vital role in ensuring food safety in the supply chains. Conventional food detection methods for biological, chemical, and physical contaminants are labor-intensive, expensive, time-consuming, and often alter the food samples. These limitations drive the need of the food industry for developing more practical food detection tools that can detect contaminants of all three classes. Raman spectroscopy can offer widespread food safety assessment in a non-destructive, ease-to-operate, sensitive, and rapid manner. Recent advances of Raman spectroscopic methods further improve the detection capabilities of food contaminants, which largely boosts its applications in food safety. In this review, we introduce the basic principles of Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), and micro-Raman spectroscopy and imaging; summarize the recent progress to detect biological, chemical, and physical hazards in foods; and discuss the limitations and future perspectives of Raman spectroscopic methods for food safety surveillance. This review is aimed to emphasize potential opportunities for applying Raman spectroscopic methods as a promising technique for food safety detection.

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Currently, the applicant has chosen a target plasma trough concentration for nirmatrelvir, which is adjusted to 292 ng/mL based on the drug's molecular weight (499.54 Daltons), its binding to human plasma proteins (69%), and the in vitro antiviral EC90 value (181 nM). However, the current exposure‐effect relationships (ER) analysis of viral load in patients enrolled in the EPIC‐HR study has not revealed clinically significant trends in the ER. Given that the lungs are the primary site of COVID‐19 infection, we aim to further understand this exposure relationship by exploring and analyzing the penetration characteristics of nirmatrelvir in the lungs. Objectives To explore and understand the target plasma concentration of 292 ng/mL in antiviral activity. Methods We identified all critically ill patients with coronavirus disease 2019 who received nirmatrelvir/ritonavir treatment in the respiratory intensive care unit of Changhai hospital between January 2023 and October 2023. Samples of plasma and bronchoalveolar lavage fluid were obtained at pre‐dose trough concentrations after administration of nirmatrelvir (NMV). The relationship between NMV levels in plasma and the epithelial lining fluid (ELF) was assessed by determining concentrations of NMV. Results There was a significant relationship between NMV levels in plasma and ELF (ELF = 0.4976*PLASMA‐ 204; R = 0.96), with a correlation whose slope (0.4976) suggested that the blood‐to‐ELF ratio of drug penetration was 2:1. A negative value from the equation indicates that NMV requires to reach baseline concentration to penetrate the ELF. Conclusions The relationship between NMV levels in plasma and ELF with low permeability and a negative baseline value suggests that the target plasma concentration of 292 ng/mL is insufficient for antiviral activity. This study provides a unique perspective to explore and understand no clinically meaningful trend of exposure‐response relationships in patients enrolled in EPIC‐HR.