HCR-Assisted RTF-EXPAR-Based Lateral Flow Analysis for Sensitive Detection of H1N1 Influenza Virus.

The H1N1 influenza virus is a significant pathogen responsible for seasonal influenza, and its frequent outbreaks pose substantial challenges to global public health. The present study successfully developed a lateral flow analysis platform that integrates reverse transcription-free exponential amplification reaction (RTF-EXPAR) and hybridization chain reaction (HCR) processes with functionalized quantum dots for the direct detection of H1N1 influenza virus RNA, eliminating the need for reverse transcription. The fluorescence signal on the band recorded with a smartphone can be utilized for the quantitative determination of the target. Interestingly, the dual signal amplification strategy exhibits high sensitivity with a remarkably low detection limit of 10 aM. Moreover, this platform exhibits excellent flexibility and universality, where the various pathogens can be determined by replacing the specific nucleic acid fragments in RTF-EXPAR. The aforementioned advantages reveal its huge potential in the early diagnosis of H1N1 influenza virus infection and developing point-of-care testing (POCT) equipment for nucleic acid analysis.

Development and Validation of a Nomogram for Predicting Survival Based on Ferritin and Transferrin Ratio in Breast Cancer Patients.

BACKGROUND: Our objective is to develop a predictive model utilizing the ferritin and transferrin ratio (FTR) and clinical factors to forecast overall survival (OS) in breast cancer (BC) patients. METHODS: We conducted a retrospective analysis of clinical data from 2858 BC patients diagnosed between 2013 and 2021. Subsequently, the cohort of 2858 BC patients underwent random assignment into distinct subsets: a training cohort comprising 2002 patients and a validation cohort comprising 856 patients, maintaining a proportional ratio of 7:3. Employing multivariable Cox regression analysis within the training cohort, we derived a prognostic nomogram. The predictive performance was assessed using calibration curves, C-index, and decision curve analysis. RESULTS: The final prognostic model included the TNM stage, subtype, hemoglobin levels, and the ferritin-transferrin ratio. The nomogram achieved a C-index of .794 (95% CI: .777-.810). The nomogram demonstrated superior predictive accuracy for OS at 3, 5, and 7 years for BC, with area under the time-dependent curves of .812, .782, and .773, respectively. These values notably outperformed those of the conventional TNM stage. Decision curve analysis reaffirmed the greater net benefit of our nomogram compared to the TNM stage. These findings were subsequently validated in the independent validation cohort. CONCLUSION: The FTR-based prognostic model may predict a patient's OS better than the TNM stage in a clinical setting. The nomogram can provide an early, affordable, and reliable tool for survival prediction, as well as aid clinicians in treatment option-making and prognosis evaluation. However, further multi-center prospective trials are required to confirm the reliability of the existing nomogram.

BackgroundOur objective is to develop a predictive model utilizing the ferritin and transferrin ratio (FTR) and clinical factors to forecast overall survival (OS) in breast cancer (BC) patients.MethodsWe conducted a retrospective analysis of clinical data from 2858 BC patients diagnosed between 2013 and 2021. Subsequently, the cohort of 2858 BC patients underwent random assignment into distinct subsets: a training cohort comprising 2002 patients and a validation cohort comprising 856 patients, maintaining a proportional ratio of 7:3. Employing multivariable Cox regression analysis within the training cohort, we derived a prognostic nomogram. The predictive performance was assessed using calibration curves, C-index, and decision curve analysis.ResultsThe final prognostic model included the TNM stage, subtype, hemoglobin levels, and the ferritin-transferrin ratio. The nomogram achieved a C-index of .794 (95% CI: .777-.810). The nomogram demonstrated superior predictive accuracy for OS at 3, 5, and 7 years for BC, with area under the time-dependent curves of .812, .782, and .773, respectively. These values notably outperformed those of the conventional TNM stage. Decision curve analysis reaffirmed the greater net benefit of our nomogram compared to the TNM stage. These findings were subsequently validated in the independent validation cohort.ConclusionThe FTR-based prognostic model may predict a patient's OS better than the TNM stage in a clinical setting. The nomogram can provide an early, affordable, and reliable tool for survival prediction, as well as aid clinicians in treatment option-making and prognosis evaluation. However, further multi-center prospective trials are required to confirm the reliability of the existing nomogram.

Advancements of CRISPR technology in public health-related analysis.

Pathogens and contaminants in food and the environment present significant challenges to human health, necessitating highly sensitive and specific diagnostic methods. Traditional approaches often struggle to meet these requirements. However, the emergence of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) system has revolutionized nucleic acid diagnostics. The present review provides a comprehensive overview of the biological sensing technology based on the CRISPR/Cas system and its potential applications in public health-related analysis. Additionally, it explores the enzymatic cleavage capabilities mediated by Cas proteins, highlighting the promising prospects of CRISPR technology in addressing bioanalysis challenges. We discuss commonly used CRISPR-Cas proteins and elaborate on their application in detecting foodborne bacteria, viruses, toxins, other chemical pollution, and drug-resistant bacteria. Furthermore, we highlight the advantages of CRISPR-based sensors in the field of public health-related analysis and propose that integrating CRISPR-Cas biosensing technology with other technologies could facilitate the development of more diverse detection platforms, thereby indicating promising prospects in this field.

Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer.

Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes-C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)-emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.

Non-invasive diagnosis of bacterial and non-bacterial inflammations using a dual-enzyme-responsive fluorescent indicator.

Bacterial infections, as the second leading cause of global death, are commonly treated with antibiotics. However, the improper use of antibiotics contributes to the development of bacterial resistance. Therefore, the accurate differentiation between bacterial and non-bacterial inflammations is of utmost importance in the judicious administration of clinical antibiotics and the prevention of bacterial resistance. However, as of now, no fluorescent probes have yet been designed for the relevant assessments. To this end, the present study reports the development of a novel fluorescence probe (CyQ) that exhibits dual-enzyme responsiveness. The designed probe demonstrated excellent sensitivity in detecting NTR and NAD(P)H, which served as critical indicators for bacterial and non-bacterial inflammations. The utilization of CyQ enabled the efficient detection of NTR and NAD(P)H in distinct channels, exhibiting impressive detection limits of 0.26 µg mL-1 for NTR and 5.54 µM for NAD(P)H, respectively. Experimental trials conducted on living cells demonstrated CyQ's ability to differentiate the variations in NTR and NAD(P)H levels between A. baumannii, S. aureus, E. faecium, and P. aeruginosa-infected as well as LPS-stimulated HUVEC cells. Furthermore, in vivo zebrafish experiments demonstrated the efficacy of CyQ in accurately discerning variations in NTR and NAD(P)H levels resulting from bacterial infection or LPS stimulation, thereby facilitating non-invasive detection of both bacterial and non-bacterial inflammations. The outstanding discriminatory ability of CyQ between bacterial and non-bacterial inflammation positions it as a promising clinical diagnostic tool for acute inflammations.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests.

Background: Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management. Methods: We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies). Results: The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient. Conclusion: Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Near-infrared electrochemiluminescence biosensors facilitated by thermally activated delayed fluorescence (TADF) emitters for ctDNA analysis.

The near-infrared electrochemiluminescence technique (NIR ECL) has gained significant attention as a powerful analytical tool in biomedicine and clinical diagnosis due to its inherent advantages. In this work, we successfully synthesized a novel NIR ECL emitter of TPA-DCPP nanoparticles (NPs) with a D-π-A-π-D configuration. By utilizing the thermally activated delayed fluorescence (TADF) property, we achieved enhanced electrochemiluminescence (ECL) emission through complete exciton harvesting for radiative decay. Specifically, when BDEA was used as a co-reactant, the TPA-DCPP NPs exhibited strong bandgap ECL emission. Additionally, they demonstrated an exceptionally higher ECL efficiency compared to conventional near-infrared fluorescence organic nanomaterials (BSeT-BT NPs). By integrating the efficient anodic ECL performance of TPA-DCPP NPs with Exo III-assisted polymerase enzyme reaction cascade amplification, a highly efficient ECL resonance energy transfer (ECL-RET) platform was developed for ultrasensitive detection of circulating tumor DNA (ctDNA). The established biosensor demonstrated an exceptional linear dynamic range and achieved attomolar-level detection limit. This study highlights the immense potential of TADF emitters in enhancing ECL efficiency and extends the emission wavelength of organic nanomaterials to the NIR region, thereby expanding their applications in biological analysis.

Research progress of microfluidics-based food safety detection.

High demands for food safety detection and analysis have been advocated with people's increasing living standards. Even though numerous analytical testing techniques have been proposed, their widespread adoption is still constrained by the high limit of detection, narrow detection ranges, and high implementation costs. Due to their advantages, such as reduced sample and reagent consumption, high sensitivity, automation, low cost, and portability, using microfluidic devices for food safety monitoring has generated significant interest. This review provides a comprehensive overview of the latest microfluidic detection platforms (published in recent 4 years) and their applications in food safety, aiming to provide references for developing efficient research strategies for food contaminant detection and facilitating the transition of these platforms from laboratory research to practical field use.

Molecular Engineering of Bright NIR-I/NIR-II Nanofluorophores for High-Resolution Bioimaging and Tumor Detection in Vivo.

A comprehensive approach for the construction of NIR-I/NIR-II nanofluorophores with exceptional brightness and excellent chemo- and photostability has been developed. This study first confirmed that the amphiphilic molecules with stronger hydrophobic moieties and weaker hydrophilic moieties are superior candidates for constructing brighter nanofluorophores, which are attributed to its higher efficiency in suppressing the intramolecular charge transfer/aggregation-caused fluorescence quenching of donor-acceptor-donor type fluorophores. The prepared nanofluorophore demonstrates a fluorescence quantum yield exceeding 4.5% in aqueous solution and exhibits a strong NIR-II tail emission up to 1300 nm. The superior performance of the nanofluorophore enabled the achievement of high-resolution whole-body vessel imaging and brain vessel imaging, as well as high-contrast fluorescence imaging of the lymphatic system in vivo. Furthermore, their potential for highly sensitive fluorescence detection of tiny tumors in vivo has been successfully confirmed, thus supporting their future applications in precise fluorescence imaging-guided surgery in the early stages of cancer.

Clonorchis sinensis infection amplifies hepatocellular carcinoma stemness, predicting unfavorable prognosis.

BACKGROUND: Extensive evidence links Clonorchis sinensis (C. sinensis) to cholangiocarcinoma; however, its association with hepatocellular carcinoma (HCC) is less acknowledged, and the underlying mechanism remains unclear. This study was designed to investigate the association between C. sinensis infection and HCC and reveal the relationship between C. sinensis infection and cancer stemness. METHODS: A comprehensive analysis of 839 HCC patients categorized into C. sinensis (-) HCC and C. sinensis (+) HCC groups was conducted. Chi-square and Mann-Whitney U tests were used to assess the association between C. sinensis infection and clinical factors. Kaplan-Meier and Cox regression analyses were used to evaluate survival outcomes. Immunohistochemistry was used to determine CK19 and EpCAM expression in HCC specimens. RESULTS: Compared to C. sinensis (-) HCC patients, C. sinensis (+) HCC patients exhibited advanced Barcelona Clinic Liver Cancer (BCLC) stage, higher male prevalence and more liver cirrhosis as well as elevated alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), eosinophil, complement 3 (C3), and complement 4 (C4) values. C. sinensis infection correlated with shorter overall survival (OS) (p < 0.05) and recurrence-free survival (RFS) (p < 0.05). Furthermore, Cox multivariate analysis revealed that C. sinensis infection was an independent prognostic factor for OS in HCC patients. Importantly, C. sinensis infection upregulated the expression of HCC cancer stem cell markers CK19 and EpCAM. CONCLUSION: HCC patients with C. sinensis infection exhibit a poor prognosis following hepatectomy. Moreover, C. sinensis infection promotes the acquisition of cancer stem cell-like characteristics, consequently accelerating the malignant progression of HCC. AUTHOR SUMMARY: Clonorchis sinensis (C. sinensis) is a prominent food-borne parasite prevalent in regions such as China, particularly in Guangxi. C. sinensis has been associated with various hepatobiliary system injuries, encompassing inflammation, periductal fibrosis, cholangiocarcinoma and even hepatocellular carcinoma (HCC). A substantial body of evidence links C. sinensis to cholangiocarcinoma, However, the connection between C. sinensis and HCC and the intricate mechanisms underlying its contribution to HCC development remain incompletely elucidated. Our study demonstrates clear clinicopathological associations between C. sinensis and HCC, such as gender, BCLC stage, liver cirrhosis, MVI, AFP, CA19-9, circulating eosinophils and complements. Furthermore, we found that the co-occurrence of C. sinensis exhibited a significant association with shorter OS and RFS in patients diagnosed with HCC. A major finding was that C. sinensis infection promotes the acquisition of cancer stem cell-like characteristics, consequently accelerating the malignant progression of HCC. Our results provide a more comprehensive comprehension of the interplay between C. sinensis and HCC, shedding fresh light on the carcinogenic potential of C. sinensis.

A stable ratiometric fluorescent probe for hypochlorous acid detection and rheumatoid arthritis evaluation.

A ratiometric fluorescent probe (MeO-CNPPV Pdots) based on the principle of fluorescence resonance energy transfer (FRET) was designed for hypochlorous acid (HOCl) and rheumatoid arthritis (RA) detection. The presence of HOCl can block the energy transfer from CNPPV to MeOTPATBT, resulting in a ratio change in the fluorescence of Pdots (I600 nm/I680 nm). This strategy provides a valuable paradigm in early RA evaluation.

A portable CRISPR-Cas12a triggered photothermal biosensor for sensitive and visual detection of Staphylococcus aureus and Listeria monocytogenes.

The detection of foodborne pathogens is crucial for ensuring the maintenance of food safety. In the present study, a portable CRISPR-Cas12a triggered photothermal biosensor integrating branch hybrid chain reaction (bHCR) and DNA metallization strategy for sensitive and visual detection of foodborne pathogens was proposed. The sheared probes were utilized to block the locker probes, which enabled preventing the assembly of bHCR in the absence of target bacteria, while target bacteria can activate the cleavage of sheared probes through CRISPR-Cas12a. Therefore, the locker probes functioned as initiating chains, triggering the formation of the branching double-stranded DNA consisting of H1, H2, and H3. The silver particles, which were in situ deposited on the DNA structure, functioned as a signal factor for conducting photothermal detection. Staphylococcus aureus and Listeria monocytogenes were selected as the foodborne pathogens to verify the analytical performance of this CRISPR-Cas12a triggered photothermal sensor platform. The sensor exhibited a sensitive detection with a low detection limit of 1 CFU/mL, while the concentration ranged from 100 to 108 CFU/mL. Furthermore, this method could efficiently detect target bacteria in multiple food samples. The findings demonstrate that this strategy can serve as a valuable reference for the development of a portable platform enabling quantitative analysis, visualization, and highly sensitive detection of foodborne bacteria.

Facile prepared microfluidic chip for multiplexed digital RT-qPCR test.

The chip-based digital polymerase chain reaction (PCR) is an indispensable technique for amplifying and quantifying nucleic acids, which has been widely employed in molecular diagnostics at both fundamental and clinical levels. However, the previous designs have yet to achieve widespread application due to limitations in complex chip fabrication, pretreatment procedures, special surface properties, and low throughput. This study presents a facile digital microfluidic chip driven by centrifugal force for digital PCR analysis. Interestingly, regardless of the hydrophilicity or hydrophobicity of the inner chip surface, an efficient digitization process can be achieved. PCR reagents introduced into the inlet can be allocated to 9600 microchambers and subsequently isolated by the immiscible phase (silicone oil). The centrifugal priming approach offers a facile means to achieve high-throughput analysis. The design was further employed for the quantification of nucleic acids using digital PCR. The calculated result exhibited a strong correlation with the measured value at the concentrations from 1 copy/µL to 1000 copies/µL (R2  = 0.99). Additionally, the chip also allowed digital multiplexed analysis, thereby indicating its potential for multi-target detection applications.

Microfluidic-based platforms for cell-to-cell communication studies.

Intercellular communication is critical to the understanding of human health and disease progression. However, compared to traditional methods with inefficient analysis, microfluidic co-culture technologies developed for cell-cell communication research can reliably analyze crucial biological processes, such as cell signaling, and monitor dynamic intercellular interactions under reproducible physiological cell co-culture conditions. Moreover, microfluidic-based technologies can achieve precise spatial control of two cell types at the single-cell level with high throughput. Herein, this review focuses on recent advances in microfluidic-based 2D and 3D devices developed to confine two or more heterogeneous cells in the study of intercellular communication and decipher the advantages and limitations of these models in specific cellular research scenarios. This review will stimulate the development of more functionalized microfluidic platforms for biomedical research, inspiring broader interests across various disciplines to better comprehend cell-cell communication and other fields, such as tumor heterogeneity and drug screening.

A dual-responsive ratiometric indicator designed for in vivo monitoring of oxidative stress and antioxidant capacity.

The imbalance between oxidative stress and antioxidant capacity is strongly associated with the development of numerous degenerative diseases, including cardiovascular diseases, diabetes, neurodegenerative diseases, and cancer. Therefore, monitoring oxidative stress and antioxidant capacity in vivo is crucial for maintaining cellular homeostasis and the stability of the organism's internal environment. Here, we present the findings of our study on DQ1, a dual-responsive indicator designed specifically for imaging H2O2 and NAD(P)H, which are critical indicators of oxidative stress and antioxidant capacity. DQ1 facilitated the colorimetric and fluorescence detection of H2O2 and NAD(P)H in two well-separated channels, exhibiting a detection limit of 1.0 µM for H2O2 and 0.21 nM for NAD(P)H, respectively. Experiments conducted on living cells and zebrafish demonstrated that DQ1 could effectively detect changes in H2O2 and NAD(P)H levels when exposed to exogenous hypoxic conditions and chemical stimuli. Furthermore, the effectiveness of the as-fabricated indicator was investigated in two distinct mouse models: evaluating H2O2 and NAD(P)H levels in myocardial cell dysfunction during acute myocardial infarction and liver tissue damage under trichloroethylene stress conditions. In vivo experiments demonstrated that the levels of the two cardiac biomarkers increase progressively with the development of myocardial infarction, eventually reaching a steady state after 7 days when the damaged cells in the infarcted region become depleted. Moreover, during 14 continuous days of exposure to trichloroethylene, the two biomarkers in liver tissue exhibited a sustained increase, indicating a significant enhancement in intracellular oxidative stress and antioxidant capacity attributed to the mouse liver's robust metabolic capacity. The aforementioned studies underscore the efficacy of DQ1 as a valuable tool for scrutinizing redox states at both the single-cell and biological tissue levels. It presents significant potential for investigating the dynamic alternations in oxidative stress and antioxidant capacity within disease models as the disease progresses, thereby facilitating a more profound comprehension of these processes across various disease models.

Strategies and materials for the prevention and treatment of biofilms.

Biofilms are aggregates of organized microbial growth that function as barriers and create a stable internal environment for cell survival. The bacteria in the biofilms exhibit characteristics that are quite different from the planktonic bacteria, such as strong resistance to antibiotics and other bactericides, getting out of host immunity, and developing in harsh environments, which all contribute to the persistent and intractable treatment. Hence, there is an urgent need to develop novel materials and strategies to combat biofilms. However, most of the reviews on anti-biofilms published in recent years are based on specific fields or materials. Microorganisms are ubiquitous, except in the context of medical and health issues; however, biofilms exert detrimental effects on the advancement and progress of various fields. Therefore, this review aims to provide a comprehensive summary of effective strategies and methodologies applicable across all industries. Firstly, the process of biofilms formation was introduced to enhance our comprehension of the "enemy". Secondly, strategies to intervene in the important links of biofilms formation were discussed, taking timely action during the early weak stages of the "enemy". Thirdly, treatment strategies for mature biofilms were summarized to deal with biofilms that break through the defense line. Finally, several substances with antibacterial properties were presented. The review concludes with the standpoint of the author about potential developments of anti-biofilms strategies. This review may help researchers quickly understand the research progress and challenges in the field of anti-biofilms to design more efficient methods and strategies to combat biofilms.

A prognostic model related to necrotizing apoptosis of breast cancer based on biorthogonal constrained depth semi-supervised nonnegative matrix decomposition and single-cell sequencing analysis.

Breast cancer (BC) is one of the most common malignant tumours in women, and its prognosis is poor. The prognosis of BC patients can be improved by immunotherapy. However, due to the heterogeneity of BC, the identification of new biomarkers is urgently needed to improve the prognosis of BC patients. Necrotic apoptosis has been shown to play an essential role in many cancers. First, this study proposed a novel clustering algorithm called biorthogonal constrained depth semisupervised nonnegative matrix factorization (DO-DSNMF). The DO-DSNMF algorithm added multilayer nonlinear transformation to the coefficient matrix obtained after decomposition, which was used to mine the nonlinear relationship between samples. In addition, we also added orthogonal constraints on the basis matrix and coefficient matrix to reduce the influence of redundant features and samples on the results. We applied the DO-DSNMF algorithm and analysed the differences in survival and immunity between the subtypes. Then, we used prognosis analysis to construct the prognosis model. Finally, we analysed single cells using single-cell sequencing (scRNA-seq) data from the GSE75688 dataset in the GEO database. We identified two BC subtypes based on the BC transcriptome data in the TCGA database. Immune infiltration analysis showed that the necrotizing apoptosis-related genes of BC were related to various immune cells and immune functions. Necrotizing apoptosis was found to play a role in BC progression and immunity. The role of prognosis-related NRGs in BC was also verified by cell experiments. This study proposed a novel clustering algorithm to analyse BC subtypes and constructed an NRG prognostic model for BC. The prognosis and immune landscape of BC patients were evaluated by this model. The cell experiment supported its role in BC, which provides a potential therapeutic target for the treatment of BC.

Polymeric engineering of AIEgens for NIR-II fluorescence imaging and detection of abdominal metastases of ovarian cancer in vivo.

A polymeric engineering design principle is proposed for the construction of small-sized (∼20 nm) NIR-II AIEgen-doped nanodots (AIEdots) with high brightness and prolonged circulation time in blood vessels. With the utilization of the as-designed NIR-II AIEdots, the successful achievement of high-resolution NIR-II fluorescence imaging of tumor vessels and precise detection of abdominal metastases of ovarian cancer has been attained.

Beta2-Microglobulin as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram.

Background: Accurate prognosis is crucial for improving hepatocellular carcinoma (HCC) patients, clinical management, and outcomes post-liver resection. However, the lack of reliable prognostic indicators poses a significant challenge. This study aimed to develop a user-friendly nomogram to predict HCC patients' post-resection prognosis. Methods: We retrospectively analyzed the data from 1091 HCC patients, randomly split into training (n=767) and validation (n=324) cohorts. Receiver operating characteristic (ROC) curves determined the optimal cut-off value for alpha1-microglobulin (α1MG) and Beta2-microglobulin (ß2MG). Kaplan-Meier analysis assessed microglobulin's impact on survival, followed by Cox regression to identify prognostic factors and construct a nomogram. The predictive accuracy and discriminative ability of the nomogram were measured by the concordance index (C-index), calibration curves, area under the ROC curve (AUC), and decision curve analysis (DCA), and were compared with the BCLC staging system, Edmondson grade, or BCLC stage plus Edmondson grade. Results: Patients with high ß2MG (≥2.395mg/L) had worse overall survival (OS). The nomogram integrated ß2MG, BCLC stage, Edmondson grade, microvascular invasion (MVI), and serum carbohydrate antigen 199 (CA199) levels. C-index for training and validation cohorts (0.712 and 0.709) outperformed the BCLC stage (0.660 and 0.657), Edmondson grade (0.579 and 0.564), and the combination of BCLC stage with Edmondson grade (0.681 and 0.668), improving prognosis prediction. Calibration curves demonstrated good agreement between predicted and observed survival. AUC values exceeded 0.700 over time, highlighting the nomogram's discriminative ability. DCA revealed superior overall net income compared to other systems, emphasizing its clinical utility. Conclusion: Our ß2MG-based nomogram accurately predicts HCC patients' post-resection prognosis, aiding intervention and follow-up planning. Significantly, our nomogram surpasses existing prognostic indicators, including BCLC stage, Edmondson grade, and the combination of BCLC stage with Edmondson grade, by demonstrating superior predictive performance.

Integrated portable food safety testing pipette based on a color-switchable fluorescence probe for rapid visual discrimination of mild food deterioration.

A sensitive, portable, easy-to-operate, directly-readable food freshness monitoring device has been developed for rapid visual identification of mild food spoilage.