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.

Enhancing polycyclic aromatic hydrocarbon soil remediation in cold climates using immobilized low-temperature-resistant mixed microorganisms.

Polycyclic aromatic hydrocarbons (PAHs), widespread organic pollutants, significantly impact human health and environmental integrity. Recent approaches to ameliorate PAH-contaminated soils, particularly in cold environments, have been insufficient. This study investigates the use of immobilized low-temperature-resistant mixed microorganisms (LTRMM) for enhancing the degradation of PAHs in soils from coke plants and the Shenfu irrigation area. Our results demonstrate that treatment with immobilized mixed microorganisms (MC-HS) is more effective than treatments with free bacteria (H-S) and control (CK). Specifically, the degradation rates in the MC-HS1 treatment were 10.10 %-41.13 % higher than those in the coking plant soil treated with CK1 and H-S1. Similarly, in the Shenfu irrigation area soil, MC-HS2 showed improvements of 6.00 % to 52.56 % over CK2 and H-S2. A kinetic model was used to analyze the enhanced degradation capabilities, revealing that the half-life of PAHs under the immobilized mixed microorganism treatment (T3) was significantly shorter compared to the free bacteria (T2) and control treatments (T1). These findings suggest that employing immobilized LTRMM could significantly improve the remediation efficiency of PAH-contaminated soils in cold climates.

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.

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.

Primer exchange reaction-amplified protein-nucleic acid interactions for ultrasensitive and specific microRNA detection.

Protein-nucleic acid interactions are not only fundamental to genetic regulation and cellular metabolism, but molecular basis to artificial biosensors. However, such interactions are generally weak and dynamic, making their specific and sensitive quantitative detection challenging. By using primer exchange reaction (PER)-amplified protein-nucleic acid interactions, we here design a universal and ultrasensitive electrochemical sensor to quantify microRNAs (miRNAs) in blood. This PER-miR sensor leverages specific recognition between S9.6 antibodies and miRNA/DNA hybrids to couple with PER-derived multi-enzyme catalysis for ultrasensitive miRNA detection. Surface binding kinetic analysis shows a rational Kd (8.9 nM) between the miRNA/DNA heteroduplex and electrode-attached S9.6 antibody. Based on such a favorable affinity, the programmable PER amplification enables the sensor to detect target miRNAs with sensitivity up to 90.5 aM, three orders of magnitude higher than that without PER in routine design, and with specificity of single-base resolution. Furthermore, the PER-miR sensor allows detecting multiple miRNAs in parallel, measuring target miRNA in lysates across four types of cell lines, and differentiating tumor patients from healthy individuals by directly analyzing the human blood samples (n = 40). These advantages make the sensor a promising tool to enable quantitative sensing of biomolecular interactions and precision diagnostics.

Bottom-Up Signal Boosting with Fractal Nanostructuring and Primer Exchange Reaction for Ultrasensitive Detection of Cancerous Exosomes.

Exosomes are emerging as promising biomarkers for cancer diagnosis, yet sensitive and accurate quantification of tumor-derived exosomes remains a challenge. Here, we report an ultrasensitive and specific exosome sensor (NPExo) that initially leverages hierarchical nanostructuring array and primer exchange reaction (PER) for quantitation of cancerous exosomes. This NPExo uses a high-curvature nanostructuring array (bottom) fabricated by single-step electrodeposition to enhance capturing of the target exosomes. The immuno-captured exosome thus provides abundant membrane sites to insert numerous cholesterol-DNA probes with a density much higher than that by immune pairing, which further allows PER-based DNA extension to assemble enzyme concatemers (up) for signal amplification. Such a bottom-up signal-boosting design imparts NPExo with ultrahigh sensitivity up to 75 particles/mL (i.e., <1 exosome per 10 µL) and a broad dynamic range spanning 6 orders of magnitude. Furthermore, our sensor allows monitoring subtle exosomal phenotypic transition and shows high accuracy in discrimination of liver cancer patients from healthy donors via blood samples, suggesting the great potential of NPExo as a promising tool in clinical diagnostics.

Interfacial DNA Framework-Enhanced Background-to-Signal Transition for Ultrasensitive and Specific Micro-RNA Detection.

Interfacial DNA self-assembly is fundamental to solid nucleic acid biosensors, whereas how to improve the signal-to-noise ratio has always been a challenge, especially in the charge-based electrochemical DNA sensors because of the large noise from the negatively charged DNA capture probes. Here, we report a DNA framework-reversed signal-gain strategy through background-to-signal transition for ultrasensitive and highly specific electrical detection of microRNAs (miRNAs) in blood. By using a model of enzyme-catalyzed deposition of conductive molecules (polyaniline) targeting to DNA, we observed the highest signal contribution per unit area by the highly charged three-dimensional (3D) tetrahedral DNA framework probe, relative to the modest of two-dimensional (2D) polyA probe and the lowest of one-dimensional (1D) single-stranded (ss)DNA probe, suggesting the positive correlation of background DNA charge with signal enhancement. Using such an effective signal-transition design, the DNA framework-based electrochemical sensor achieves ultrasensitive miRNAs detection with sensitivity up to 0.29 fM (at least 10-fold higher than that with 1D ssDNA or 2D polyA probes) and high specificity with single-base resolution. More importantly, this high-performance sensor allows for a generalized sandwich detection of tumor-associated miRNAs in the complex matrices (multiple cell lysates and blood serum) and further distinguishes the tumor patients (e.g., breast, lung, and liver cancer) from the normal individuals. These advantages signify the promise of this miRNA sensor as a versatile tool in precision diagnosis.

Structural origin of hardness decrease in irradiated sodium borosilicate glass.

Mechanical properties such as hardness and modulus of sodium borosilicate (NBS) glasses in irradiation conditions were studied extensively in recent years. With irradiation of heavy ions, a trend that the hardness of NBS glasses decreased and then stabilized with increase of dose has been reported. Variations in network structures were suggested for the decrease of hardness after irradiation. However, details of these variations in a network of glass are not clear yet. In this paper, molecular dynamics was applied to simulate the network variations in a type of NBS glass and the changes in hardness after xenon irradiation. The simulation results indicated that hardness variation decreased with fluence in an exponential law, which was consistent with experimental results. The origin of hardness decrease after irradiation might be attributed to the break of Biv-O links that could be derived from the (1) decrease of average coordinate number of boron, (2) decrease of Si-O-Biv bonds, and (3) increase of non-bridging oxygen.

All-optical regenerative NRZ-to-RZ format conversion using coupled ring-resonator optical waveguide.

This paper proposes a scheme for format conversion from a distorted non-return-to-zero (NRZ) signal to a high-quality return-to-zero (RZ) signal, using the nonlinearity in a coupled ring-resonator optical waveguide (CROW) on a silicon chip. In this method, a distorted NRZ signal is amplified and fed into the CROW together with an RZ pulse train. The CROW performs as a nonlinear step gate for the RZ pulse train, which outputs amplitude-equalized RZ pulses inheriting the information from the NRZ signal. Clearly, the integration of the format conversion and regeneration simplifies the system. Our simulations performed at 10 Gb/s and 40 Gb/s verify the feasibility of our proposal.