Screening immune-related blood biomarkers for DKD-related HCC using machine learning.

Background: Diabetes mellitus is a significant health problem worldwide, often leading to diabetic kidney disease (DKD), which may also influence the occurrence of hepatocellular carcinoma (HCC). However, the relationship and diagnostic biomarkers between DKD and HCC are unclear. Methods: Using public database data, we screened DKD secretory RNAs and HCC essential genes by limma and WGCNA. Potential mechanisms, drugs, and biomarkers for DKD-associated HCC were identified using PPI, functional enrichment, cMAP, and machine learning algorithms, and a diagnostic nomogram was constructed. Then, ROC, calibration, and decision curves were used to evaluate the diagnostic performance of the nomograms. In addition, immune cell infiltration in HCC was explored using CIBERSORT. Finally, the detectability of critical genes in blood was verified by qPCR. Results: 104 DEGs associated with HCC using WGCNA were identified. 101 DEGs from DKD were predicated on secreting into the bloodstream with Exorbase datasets. PPI analysis identified three critical modules considered causative genes for DKD-associated HCC, primarily involved in inflammation and immune regulation. Using lasso and RM, four hub genes associated with DKD-associated HCC were identified, and a diagnostic nomogram confirmed by DCA curves was established. The results of immune cell infiltration showed immune dysregulation in HCC, which was associated with the expression of four essential genes. PLVAP was validated by qPCR as a possible blood-based diagnostic marker for DKD-related HCC. Conclusion: We revealed the inflammatory immune pathways of DKD-related HCC and developed a diagnostic nomogram for HCC based on PLVAP, C7, COL15A1, and MS4A6A. We confirmed with qPCR that PLVAP can be used as a blood marker to assess the risk of HCC in DKD patients.

An oxygen vacancy-modulated bifunctional S-NiMoO4 electrocatalyst for efficient alkaline overall water splitting.

S-doped nickel molybdate nanorods grown on nickel foam (S-NiMoO4/NF) were fabricated by a two-step hydrothermal method. The resultant S-NiMoO4/NF exhibited remarkable bifunctional electrocatalytic activity, with overpotentials of 235 mV for the hydrogen evolution reaction and 150 mV for the oxygen evolution reaction at a current density of 50 mA cm-2. Assembled into the two-electrode S-NiMoO4/NF electrolyzer in alkaline electrolytes for overall water splitting, it required only low cell voltages of 1.55 V and 1.63 V to drive 50 mA cm-2 and 100 mA cm-2, respectively. No significant performance degradation occurred during the water electrolysis process. The experimental results confirmed that S-doping induced the increase of the oxygen vacancies, accelerating the reaction kinetics and thus improving the electrocatalytic performance. Meanwhile, more active sites exposure on the surface of S-NiMoO4/NF enhanced the reactivity. This work may guide the development of efficient bifunctional catalysts in alkaline electrolysis through oxygen vacancy regulation.

Toward the Long-Term Stability of Cobalt Benzoate Confined Highly Dispersed PtCo Alloy Supported on a Nitrogen-Doped Carbon Nanosheet/Fe3C Nanoparticle Hybrid as a Multifunctional Catalyst for Zinc-Air Batteries.

This work reports a new type of platinum-based heterostructural electrode catalyst that highly dispersed PtCo alloy nanoparticles (NPs) confined in cobalt benzoate (Co-BA) nanowires are supported on a nitrogen-doped ultra-thin carbon nanosheet/Fe3C hybrid (PtCo@Co-BA-Fe3C/NC) to show high electrochemical activity and long-term stability. One-dimensional Co-BA nanowires could alleviate the shedding and agglomeration of PtCo alloy NPs during the reaction so as to achieve satisfactory long-term durability. Moreover, the synergistic effect at the interface optimizes the surface electronic structure and prominently accelerates the electrochemical kinetics. The oxygen reduction reaction half-wave potential is 0.923 V, and the oxygen evolution reaction under the condition of 10 mA•cm-2 is 1.48 V. Higher power density (263.12 mW•cm-2), narrowed voltage gap (0.49 V), and specific capacity (808.5 mAh•g-1) for PtCo@Co-BA-Fe3C/NC in Zn-air batteries are achieved with long-term cycling measurements over 776 h, which is obviously better than the Pt/C + RuO2 catalyst. The interfacial electronic interaction of PtCo@Co-BA-Fe3C/NC is investigated, which can accelerate electron transfer from Fe to Pt. Density functional theory calculations also indicate that the interfacial potential regulates the binding energies of the intermediates to achieve the best performance.

Expression and clinical significance of PD-L1 and c-Myc in non-small cell lung cancer.

BACKGROUND: It is known that there are insufficient prognostic factors for non-small cell lung cancer (NSCLC). It was reported that PD-L1 was a prognostic factor for NSCLC,and c-Myc regulated the expression of PD-L1. Herein, we investigated c-Myc and PD-L1 expression and their association with overall survival (OS) in NSCLC. METHODS: Formalin-fixed paraffin-embedded specimens were obtained from 128 patients with surgically resected primary NSCLC. Immunohistochemistry was used to assess the expression of PD-L1 and c-Myc in this study. Pearson's Chi squared test or Fisher's exact test was used to analyze the correlation of the expression of PD-L1 and c-Myc with clinicopathologic features. The relationship between OS and the expression of PD-L1 and c-Myc was evaluated by the Kaplan-Meier method and Cox proportional hazards model, respectively. RESULTS: Positive expression of PD-L1 was detected in 59 patients (46.1%). Patients with negative expression of PD-L1 had remarkably longer OS than those with positive expression of PD-L1. The positive expression rate of c-Myc in NSCLC accounted for 58.6% (75/128) and its expression was significantly more frequent in males (p = 0.002) and patients with lymph node metastasis (p = 0.029). PD-L1 expression was positively correlated with c-Myc expression (r = 0.459, p < 0.001). The PD-L1 and c-Myc double-positive group had a worse prognosis than other subgroups (p < 0.05), and the PD-L1 and c-Myc double-negative group had a better OS than other subgroups (p < 0.05). CONCLUSION: Conjoint analysis of the expression of PD-L1 and c-Myc was a better prognostic approach for NSCLC patients.

Trends in incidence and survival in patients with melanoma, 1974-2013.

Melanoma is a rare malignancy that invades the skin and the mucosa. Research has been conducted on melanoma incidence and the survival of patients with melanoma; however, no studies in melanoma incidence and the survival spanning 40 years and based on a large population have thus far been reported. We obtained data on patients with melanoma for each decade from 1974 to 2013 from the Surveillance, Epidemiology, and End Results (SEER) database. Disparities in survival by decade, age group, gender, race, site, and socioeconomic status (SES) within the aforementioned period were analyzed by comparison of Kaplan-Meier curves. We collected data on 133,996 melanoma patients in 18 SEER registry regions for the period 1974-2013. Our study found that the melanoma incidence increased continuously for the total population as well as for most age groups. The survival of patients with melanoma (except mucosal melanoma) also increased. This study showed increases in incidence and survival in melanoma across four decades in a large sample; meanwhile, the survival rates for mucosal melanoma decreased in the latter three decades, suggesting the need to improve melanoma diagnosis, broaden melanoma awareness among health care providers, and initiate the development of more effective treatments than the existing ones.

Moving Target Detection Using Dynamic Mode Decomposition.

It is challenging to detect a moving target in the reverberant environment for a long time. In recent years, a kind of method based on low-rank and sparse theory was developed to study this problem. The multiframe data containing the target echo and reverberation are arranged in a matrix, and then, the detection is achieved by low-rank and sparse decomposition of the data matrix. In this paper, we introduce a new method for the matrix decomposition using dynamic mode decomposition (DMD). DMD is usually used to calculate eigenmodes of an approximate linear model. We divided the eigenmodes into two categories to realize low-rank and sparse decomposition such that we detected the target from the sparse component. Compared with the previous methods based on low-rank and sparse theory, our method improves the computation speed by approximately 4⁻90-times at the expense of a slight loss of detection gain. The efficient method has a big advantage for real-time processing. This method can spare time for other stages of processing to improve the detection performance. We have validated the method with three sets of underwater acoustic data.

Diagnostic Value of Gd-EOB-DTPA-MRI for Hepatocellular Adenoma: A Meta-Analysis.

Objective: This study aimed to systematically review the gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-MRI) findings of hepatocellular adenoma (HCA), especially focusing on the diagnostic value of low signal intensity (SI) in the hepatocyte-phase (HBP) for differentiating HCA from focal nodular hyperplasia (FNH). Methods: A thorough literature search was conducted in PubMed, Excerpta Medica Database (EMBASE) and China National Knowledge Infrastructure databases (CNKI) to identify studies evaluating Gd-EOB-DTPA-MRI presentations of HCA. Published studies using pathological examinations as the gold standard were included. The pooled proportions of low SI in the HBP, arterial-phase, portal venous-phase (PVP) in HCA were calculated, as well as pooled proportions of bleeding, fatty degeneration, and central scar. Meta-analysis was used to evaluate the diagnostic value of low SI in the HBP for HCA. Results: The search yielded 90 studies, with 8 assessing a total of 256 HCA cases included in this study, total of 229 lesions showed low signal in the HBP. Pooled proportions of low SI in the arterial-phase, PVP, and HBP were 2% (95% CI: 0.01-0.05), 39% (95% CI: 0.25-0.55), and 89% (95% CI: 0.80-0.94), respectively. Pooled proportions of bleeding, fatty degeneration, and central scar in HCA were 11% (95% CI: 0.03-0.19), 37% (95% CI: 0.27-0.49), and 10% (95% CI: 0.03-0.27), respectively. The meta-analysis revealed the following characteristics of low SI in the HBP for HCA diagnosis: 1) pooled sensitivity, 0.917 (95% CI: 0.86-0.96); 2) pooled specificity, 0.952 (95% CI: 0.91-0.98); 3) pooled positive likelihood ratio, 15.028 (95% CI: 7.10-31.82); 4) pooled negative likelihood ratio, 0.105 (95% CI: 0.07-0.17); 5) area under the ROC, 0.9802 (Q value of 0.9375), The sensitivity analysis showed that no single study was found to influence the overall pooled estimates significantly, which indicated the stability of the meta-analysis results were good. Conclusions: Low SI on the HBP of Gd-EOB-DTPA-MRI was helpful for the diagnosis of HCA and differentiating from FNH, but it was overvalued, especially for some HCA pathological subtypes. Combining low SI in the HBP with routine MRI presentations and the risk factors of liver diseases could substantially improve its diagnosis value for HCA as well as differential diagnosis.

A perfectly matched layer for fluid-solid problems: Application to ocean-acoustics simulations with solid ocean bottoms.

A time-domain Legendre spectral-element method is described for full-wave simulation of ocean acoustics models, i.e., coupled fluid-solid problems in unbounded or semi-infinite domains, taking into account shear wave propagation in the ocean bottom. The technique can accommodate range-dependent and depth-dependent wave speed and density, as well as steep ocean floor topography. For truncation of the infinite domain, to efficiently absorb outgoing waves, a fluid-solid complex-frequency-shifted unsplit perfectly matched layer is introduced based on the complex coordinate stretching technique. The complex stretching is rigorously taken into account in the derivation of the fluid-solid matching condition inside the absorbing layer, which has never been done before in the time domain. Two implementations are designed: a convolutional formulation and an auxiliary differential equation formulation because the latter allows for implementation of high-order time schemes, leading to reduced numerical dispersion and dissipation, a topic of importance, in particular, in long-range ocean acoustics simulations. The method is validated for a two dimensional fluid-solid Pekeris waveguide and for a three dimensional seamount model, which shows that the technique is accurate and numerically long-time stable. Compared with widely used paraxial absorbing boundary conditions, the perfectly matched layer is significantly more efficient at absorbing both body waves and interface waves.

Improved survival of patients with hepatocellular carcinoma and disparities by age, race, and socioeconomic status by decade, 1983-2012.

Hepatocellular carcinoma (HCC), accounting for the majority of liver cancer, is a highly aggressive malignancy with poor prognosis and therefore adds up the financial burden. Incidence data of HCC in three decades during 1983-2012 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database with incidence rates of 1.9, 3.1 and 4.9 per 100,000 respectively. In addition, to evaluate the survival changes in the same period, a total of 63,640 HCC cancer cases were accessed from SEER database. The six-month relative survival rates improved each decade from 31.0% to 42.9% to 57.2% and the higher increase can be seen in the last two decades. More importantly, the disparities of survival among different racial groups and socioeconomic status (SES) were confirmed by the inferiority of survival in Black race and high-poverty group respectively. This research analyzed the incidence and survival data of HCC in the past three decades and may help predict the future trends of incidence and survival. Furthermore, this study may help better design healthcare policies and clinical management programs to balance the disparities of survival between SES groups, races, ages and sexes confirmed in this study and thereby improve the clinical management of HCC.

[Application of improved PCNN algorithm in retinal macular edema segmentation].

In order to extract the outlines of macular edema from OCT images of macular, and estimate the volume of edema, we have to accurately segment the macular edema region. In this paper, an improved PCNN algorithm was proposed to conduct the above process. Combined with the adaptive base threshold, and the simplified neural network parameters, a binary image of macular edema was produced. According to the principle of maximum image entropy, the optimal number of iterations was determined as 8, which was evaluated by its misclassification rate. Simulation showed that the proposed algorithm could extract the macular edema region rapidly and accurately, providing the basis for further OCT image analysis.