Research progress of protein induced by vitamin K absence or antagonist II in liver transplantation for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common pathologic type of primary liver cancer. Liver transplantation (LT) is a radical strategy for treating patients with early-stage HCC, which may lead to a better prognosis compared to hepatectomy and ablation. However, survival of patients who develop HCC recurrence after LT is short, and early recurrence is the most common cause of death. Thus, efficient biomarkers are also needed in LT to guide precision therapy to improve patient prognosis and 5-year survival. Protein induced by vitamin K absence or antagonist II (PIVKA-II) is an abnormal prothrombin that cannot activate coagulation, and it is significantly increased in patients with HCC, obstructive jaundice, and those taking vitamin K antagonists. Over the past decades, substantial progress has been made in the study of PIVKA-II in diagnosing, surveilling, and treating HCC, but its role in LT still needs to be elaborated. In this review, we focused on the role of PIVKA-II as a biomarker in LT for HCC, especially its relationship with clinicopathologic features, early recurrence, long-term survival, and donor-recipient selection.

Au- ZnFe2O4 hollow microspheres based gas sensor for detecting the mustard gas simulant 2-chloroethyl ethyl sulfide.

Mustard gas, a representative of blister agents, poses a severe threat to human health. Although the structure of 2-chloroethyl ethyl sulfide (2-CEES) is similar to mustard gas, 2-CEES is non-toxic, rendering it a commonly employed simulant in related research. ZnFe2O4-based semiconductor gas sensors exhibit numerous advantages, including structural stability, high sensitivities, and easy miniaturization. However, they exhibit insufficient sensitivity at low concentrations and require high operating temperatures. Owing to the effect of electronic and chemical sensitization, the gas-sensing performance of a sensor may be remarkably enhanced via the sensitization method of noble metal loading. In this study, based on the morphologies of ZnFe2O4 hollow microspheres, a solvothermal method was adopted to realize different levels of Au loading. Toward 1 ppm of 2-CEES, the gas sensor based on 2 wt.% Au-loaded ZnFe2O4 hollow microspheres exhibited a response sensitivity twice that of the gas sensor based on pure ZnFe2O4; furthermore, the response/recovery times decreased. Additionally, the sensor displayed excellent linear response to low concentrations of 2-CEES, outstanding selectivity in the presence of several common volatile organic compounds, and good repeatability, as well as long-term stability. The Au-loaded ZnFe2O4-based sensor has considerable potential for use in detecting toxic chemical agents and their simulants.

The Influence of Synthetic Parameters on HgSe QDs.

HgSe quantum dots (QDs) were synthesized by a thermal injection method. The effects of material ratio, growth time, and reaction temperature on the growth and spectral properties of the QDs have been studied. The experimental results show that the QDs had the highest yield of 53.04% when the molar ratio of Se source to Hg source was 1.5. Also, the excess source of SeS2 was reduced to Se. In addition, the critical radius and spectral red-shift rate of QDs can be increased with the reaction temperature. When the reaction temperature was increased to 100 °C, the spectrum reached far-infrared and the growth rate was increased to 10 times and reached 0.63 nm/min. Differing particle morphologies can be obtained by increasing the growth time to 40 min. Moreover, the growth rate reached the minimum at 30 min and the maximum at 80 min of the growth time. This study can provide guidance for the synthesis of long-wave infrared QD materials.

Regional differences and dynamic evolution of agricultural water resources utilization efficiency in China.

Improving water resources utilization efficiency is conducive to achieving the sustainable development of water resources. It is essential to explore the regional differences and dynamic evolution of agricultural water resources utilization efficiency in China to promote high-quality development of agriculture. In this study, based on the unexpected output, we build a super slack-based measure model to measure agricultural water resources utilization efficiency in China's provinces from 2007 to 2018. In addition, we use the Dagum Gini coefficient to analyze the source of regional differences. Finally, we construct the distributed dynamics model to explore the distribution of the dynamic evolution trend of China's agricultural water resources utilization efficiency. The results reveal that regional difference is the main source of the overall difference in agricultural water resources utilization efficiency in China. Spatial imbalance exists in the development of agricultural water resources utilization efficiency in China. The agricultural water resources utilization efficiency in various provinces and regions of China is relatively stable, having the characteristics of club convergence. The probability of maintaining the initial state is high, and the internal mobility is low. However, with time, the degree of club convergence decreases.

A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients.

Background: Edmondson-Steiner (E-S) grade is a pathological indicator of the degree of hepatocellular carcinoma (HCC) differentiation, and E-S grade III-IV is a poor prognostic factor for HCC patients. Predicting poorly differentiated HCC has essential significance for clinical decision-making. Although some studies have developed predictive models based on magnetic resonance imaging (MRI) and radiomics, radiomic features that require specific software for analysis are impractical for clinical work. This study aims to develop a novel and user-friendly nomogram model to predict E-S grade III-IV. Patients and Methods: Medical data on patients meeting the inclusion criteria were obtained from the Nanjing Drum Tower Hospital HCC database (January 2020 to December 2022). Univariate analysis was used to screen for risk factors associated with E-S grade III-IV. A novel nomogram was established based on the subsequent multivariate logistic regression analysis. The performance of the established model was evaluated through diagnostic ability, calibration, and clinical benefits. Results: Overall, 240 HCC patients were included in this study. Among them, 103 were highly differentiated (E-S grade I-II) HCC and 137 were poorly differentiated (E-S grade III-IV) HCC. A nomogram model that integrated alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibodies (HCVAb), aspartate aminotransferase to lymphocyte ratio index (ALRI), and macrovascular invasion was established. The novel model had a good diagnostic performance with an area under the curve (AUC) value of 0.763. Meanwhile, the model had a diagnostic accuracy of 72.5%, a sensitivity of 78.1%, and a specificity of 65.1%. The calibration curve showed good calibration of the nomogram model (mean absolute error = 0.043), and the decision curve analysis (DCA) demonstrated that the clinical benefit was provided. Conclusion: Our developed nomogram model could successfully predict E-S grade III-IV in HCC patients, which may be helpful in clinical decision-making.

Imaging features based on CT and MRI for predicting prognosis of patients with intrahepatic cholangiocarcinoma: a single-center study and meta-analysis.

BACKGROUND: To evaluate the prognostic role of imaging features based on CT and MRI in intrahepatic cholangiocarcinoma (ICC). METHODS: Two hundred and four patients from a single-center database who underwent radical ICC surgery from 2010 to 2019 were enrolled in the study. Cox proportional hazard model was used for survival analysis of imaging features. A meta-analysis was performed to determine imaging features that predict overall survival (OS) and event-free survival (EFS) in ICC. RESULTS: In the CT group of the retrospective cohort, tumor multiplicity, infiltrative tumor margin, lymph node metastasis, enhancement pattern in hepatic arterial phase and tumor necrosis correlated with poorer EFS and OS; moreover, enhancing capsules, high carcinoembryonic antigen levels contributed to poor OS. In the MRI group, tumor multiplicity and enhancement pattern were prognostic factors for OS; tumor multiplicity and enhancement pattern resulted in poor EFS. A total of 13 articles containing 1822 patients with ICC were enrolled in the adjusted hazard ratios meta-analysis. The results showed that enhancement pattern and infiltrative tumor margin were predictors of OS and EFS, whereas bile duct invasion was a predictor of OS. CONCLUSIONS: Arterial enhancement patterns and tumor margin status were associated with both OS and EFS of ICC patients following resection.

A lipid scramblase TMEM41B is involved in the processing and transport of GPI-anchored proteins.

Protein modification by glycosylphosphatidylinositol (GPI) takes place in the endoplasmic reticulum (ER). GPI-anchored proteins (GPI-APs) formed in the ER are transported to the cell surface through the Golgi apparatus. During transport, the GPI-anchor structure is processed. In most cells, an acyl chain modified to the inositol of GPI is removed by a GPI-inositol deacylase, PGAP1, in the ER. Inositol-deacylated GPI-APs become sensitive to bacterial phosphatidylinositol-specific phospholipase C (PI-PLC). We previously reported that GPI-APs are partially resistant to PI-PLC when PGAP1 activity is weakened by the deletion of selenoprotein T (SELT) or cleft lip and palate transmembrane protein 1 (CLPTM1). In this study, we found that the loss of TMEM41B, an ER-localized lipid scramblase, restored PI-PLC sensitivity of GPI-APs in SELT-knockout (KO) and CLPTM1-KO cells. In TMEM41B-KO cells, the transport of GPI-APs as well as transmembrane proteins from the ER to the Golgi was delayed. Furthermore, the turnover of PGAP1, which is mediated by ER-associated degradation, was slowed in TMEM41B-KO cells. Taken together, these findings indicate that inhibition of TMEM41B-dependent lipid scrambling promotes GPI-AP processing in the ER through PGAP1 stabilization and slowed protein trafficking.

High-performance metal-oxide gas sensors based on hierarchical core-shell ZnFe2O4 microspheres for detecting 2-chloroethyl ethyl sulfide.

Mustard gas, an erosive chemical agent, is primarily used as a chemical weapon, which seriously threatens human life and health. Therefore, detecting mustard gas and its simulant, 2-chloroethyl ethyl sulfide (2-CEES), is a very important task. As a binary metal oxide with a spinel structure, ZnFe2O4 is widely used for fabricating gas sensors because of its stable chemical structure and abundant oxygen vacancies. In this study, gas-sensing ZnFe2O4 microspheres with a hierarchical core-shell nanosheet structure were prepared via a simple one-step solvothermal method. Scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and N2 adsorption analyses were performed to characterize the morphology, structure, and chemical composition of these microspheres. A gas sensor was fabricated from the as-synthesized material, and its gas sensing performance was evaluated, using 2-CEES as a target gas. The obtained ZnFe2O4-based sensor exhibited a high sensitivity of 9.07 to 1 ppm 2-CEES at the optimal working temperature of 250 °C. The sensor response and recovery times were 18 and 546 s, respectively, and its detection sensitivity of 2.87 achieved at a 2-CEES concentration of 0.01 ppm was within an acceptable range. Additionally, the sensor demonstrated sufficiently high 2-CEES selectivity, repeatability, and long-term stability.

[Characteristics of Ozone Pollution and High-impact Meteorological Factors in Urban Cities: A Case of Suzhou].

The problem of urban ozone (O3) pollution has become prominent in recent years. However, the meteorological factors associated with O3 pollution remain unclear. Analyzing the characteristics of O3 pollution in Suzhou, as a typical urban city, and exploring the high-impact meteorological factors with O3 pollution are crucial to the prevention and control of air pollution in this region. This study used correlation analysis and machine learning methods to analyze the variation in O3 concentration and the relationship between meteorological driving factors in Suzhou based on the O3 concentration data provided by Suzhou Environmental Monitoring Center and the contemporaneous meteorological observation data in Suzhou from April to September in 2015 to 2020. The results showed that: ① O3 pollution exceeding the standard rate was more than 20% in ozone seasons during the past six years; further, pollution days of O3 and the number of pollution days of O3 as the primary pollutant increased yearly. Evidently, the problem of O3 pollution has become increasingly prominent. ② The diurnal variations in O3 were unimodal with the valley point at 07:00 and the highest peak between 15:00 and 16:00. Similar trends were found in diurnal variations of both air temperature and solar radiation, but the daily highest peak came earlier than that of O3. The results also showed an apparent weekend effect of O3 concentration in 2017 and 2019 and a significant correlation between O3 concentration and solar irradiance during the week. In addition, the monthly variation in O3 concentration and pollution exceeding the standard rate was bimodal. ③The occurrence of ozone pollution was affected by various meteorological conditions. The maximum number of days appeared when daily sunshine hours lasted longer than 7 hours, with a daily maximum air temperature around 30℃, solar irradiance ranging from 350 to 440 kW·m-2, and relative humidity ranging from 50% to 75%, at which time the intensity of pollution was the strongest. When the wind speed of easterly wind was less than 1.5 m·s-1, or the wind speed of southwest wind was less than 3.5 m·s-1, moderate ozone pollution occurred. ④ An optimal prediction model of O3 concentration was established based on machine learning, which had good predictive ability for O3 concentration in April, May, July, and September but did not perform well when O3 concentration exceeded 200 µg·m-3. Meanwhile, it was found that solar radiation had the most obvious effect on O3 concentration, followed by relative humidity, whereas the temperature and wind were less important than the former two factors.

Influence of Ink Properties on the Morphology of Long-Wave Infrared HgSe Quantum Dot Films.

As the core device of the miniature quantum dot (QD) spectrometer, the morphology control of the filter film array cannot be ignored. We eliminated strong interference from additives on the spectrum of a long-wave infrared (LWIR) QD filter film by selecting volatile additives. This work is significant for detecting targets by spectroscopic methods. In this work, a filter film with characteristic spectral bands located in the LWIR was obtained by the natural evaporation of QD ink, which was prepared by mixing various volatile organic solvents with HgSe QD-toluene solution. The factors affecting the morphology of HgSe LWIR films, including ink surface tension, particle size, and solute volume fraction, were the main focus of the analysis. The experimental results suggested that the film slipped in the evaporation process, and the multilayer annular deposition formed when the surface tension of the ink was no more than 24.86 mN/m. The "coffee ring" and the multilayer annular deposition essentially disappeared when the solute particles were larger than 188.11 nm. QDs in the film were accumulated, and a "gully" morphology appeared when the solute volume fraction was greater than 0.1. In addition, both the increase rate of the film height and the decrease rate of the transmission slowed down. The relationship between film height and transmission was obtained by fitting, and the curve conformed to the Lambert-Beer law. Therefore, a uniform and flat film without "coffee rings" can be prepared by adjusting the surface tension, particle size, and volume fraction. This method could provide an empirical method for the preparation of LWIR QD filter film arrays.

Coulombic effects on resolution of ion mobility spectrometry and its application in online qualitative analysis.

Ion mobility spectrometry is an important gas analysis method used in the rapid detection field. However, due to a lacking of explicit mathematical model of ion peak, it is difficult to extract characteristic analyte peaks from a spectrum containing overlapping peaks to achieve online qualitative analysis. Here, we present an asymmetric peak model for processing ion mobility peaks. For the asymmetric peak model, the key is to accurately estimate the standard deviation of the peak model and the fitting function of the tailing edge. We focused on the Coulombic effects on resolution of ion mobility spectrometry based on a new hypothesis of ion cloud shape and derived a formula for calculating the standard deviation taking the initial pulse width, diffusion and Coulomb repulsion factors into account. The proposed asymmetric peak model combines the advantages of optimal physical and chemical interpretation and explicit mathematical meaning. A fast decomposition method based on the peak model was developed to decompose overlapping peaks. Two overlapping simulated data sets and one real data set (a mixture of acetone and methyl salicylate) were used to test the method. The results indicated that our proposed method successfully decomposed the overlapping spectrum into individual peaks and performed markedly better than other three available methods in terms of the execution time. The proposed method meets the requirements for online qualitative analysis.

Multiscale orthogonal matching pursuit algorithm combined with peak model for interpreting ion mobility spectra and achieving quantitative analysis.

Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks). A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models.

A fast progressive spectrum denoising combined with partial least squares algorithm and its application in online Fourier transform infrared quantitative analysis.

Fourier transform infrared (FTIR) spectroscopy is an important method in analytical chemistry. A material can be qualitatively and quantitatively analyzed from its FTIR spectrum. Spectrum denoising is commonly performed before online FTIR quantitative analysis. The average method requires a long time to collect spectra, which weakens real-time online analysis. The Savitzky-Golay smoothing method makes peaks smoother with the increase of window width, causing useful information to be lost. The sparse representation method is a common denoising method, that is used to reconstruct spectrum. However, for the randomness of noise, we can't achieve the sparse representation of noise. Traditional sparse representation algorithms only perform denoising once, and the noise can not be removed completely. FTIR spectrum denoising should therefore be performed in a progressive way. However, it is difficult to determine to what degree of denoising is required. Here, a fast progressive spectrum denoising combined with partial least squares method was developed for online FTIR quantitative analysis. Two real sample data sets were used to test the performance of the proposed method. The experimental results indicated that the progressive spectrum denoising method combined with the partial least squares method performed markedly better than other methods in terms of root mean squared error of prediction and coefficient of determination in the FTIR quantitative analysis.

Self-made microextraction by packed sorbent device for the cleanup of polychlorinated biphenyls from bovine serum.

Microextraction by packed sorbent, a miniaturized form of the solid-phase extraction, is a new sample pretreatment technology mainly used for bioanalysis. In this work, self-made device was fabricated by packing C18 sorbent into a microinjection needle (50 µL) and then applied for the analysis of polychlorinated biphenyls in bovine serum followed by gas chromatography with mass spectrometry determination. Compared with conventional solid-phase extraction, the developed method bears many intriguing properties such as low consumption of the sample and organic solvent, time-saving and easy operation, which are of great interest and desire for bioanalysis applications. A series of parameters that affect the analytical performance, such as the type of elution, the aspirating/dispensing cycles of sample loading and elution, washing solution, and matrix effects, was investigated in detail. Under the optimized conditions, the proposed method presented a good linearity (R ≥ 0.986) and satisfactory sensitivity and limits of detection (0.06-0.53 ng/mL) and quantification (0.20-1.77 ng/mL), respectively. In addition, satisfactory recoveries (60.0-91.4%) and accuracy (RSD ≤ 5.72%) were achieved after optimizing the conditions when applying the developed method to real sample analysis. The screening of polychlorinated biphenyls residues in bovine serum samples by the developed method demonstrated that the assay is ideally suited as a monitoring method for polychlorinated biphenyls residues in bioanalysis.

Research on the interaction of hydrogen-bond acidic polymer sensitive sensor materials with chemical warfare agents simulants by inverse gas chromatography.

Hydrogen-bond acidic polymers are important high affinity materials sensitive to organophosphates in the chemical warfare agent sensor detection process. Interactions between the sensor sensitive materials and chemical warfare agent simulants were studied by inverse gas chromatography. Hydrogen bonded acidic polymers, i.e., BSP3, were prepared for micro-packed columns to examine the interaction. DMMP (a nerve gas simulant) and 2-CEES (a blister agent simulant) were used as probes. Chemical and physical parameters such as heats of absorption and Henry constants of the polymers to DMMP and 2-CEES were determined by inverse gas chromatography. Details concerning absorption performance are also discussed in this paper.

Portable solid phase micro-extraction coupled with ion mobility spectrometry system for on-site analysis of chemical warfare agents and simulants in water samples.

On-site analysis is an efficient approach to facilitate analysis at the location of the system under investigation as it can result in more accurate, more precise and quickly available analytical data. In our work, a novel self-made thermal desorption based interface was fabricated to couple solid-phase microextraction with ion mobility spectrometry for on-site water analysis. The portable interface can be connected with the front-end of an ion mobility spectrometer directly without other modifications. The analytical performance was evaluated via the extraction of chemical warfare agents and simulants in water samples. Several parameters including ionic strength and extraction time have been investigated in detail. The application of the developed method afforded satisfactory recoveries ranging from 72.9% to 114.4% when applied to the analysis of real water samples.