HBV inhibits apoB production via the suppression of MTP expression

<p>Abstract</p> <p>Background</p> <p>Liver dominates the production and secretion of apolipoprotein B (apoB) and evidence shows that liver malfunction induced by hepatitis B virus (HBV) infection could lead to apolipoprotein metabolism disorders. The present study was undertaken to assess the effects of HBV on apoB expression.</p> <p>Methods</p> <p>Clinical examination: serum apoB levels in patients with chronic HBV infection and in healthy individuals were measured by immunoturbidimetry using biochemical analyzer Olympus 5400. Cell study: mRNA and protein expression levels of apoB in HepG2 and HepG2.2.15 cells were measured by RT-PCR and Western blot. Alternatively, HBV infectious clone pHBV1.3 or control plasmid pBlue-ks were tranfected into HepG2 cells, and mRNA and protein expression levels of apoB, as well as the microsomal triglyceride transfer protein (MTP) in tranfected HepG2 cells were also measured by RT-PCR and western blot.</p> <p>Results</p> <p>Serum apoB level was much lower in chronic HBV patients as compared to healthy individuals (P < 0.05). Expression of apoB mRNA and protein was lower in HepG2.2.15 cells than in HepG2 cells. Similarly, expression of apoB mRNA and protein was lower in pHBV1.3 transfected HepG2 cells than in pBlue-ks transfected HepG2 cells. Expression of MTP mRNA and protein in pHBV1.3 transfected HepG2 cells was reduced in a dose-dependent fashion.</p> <p>Conclusion</p> <p>HBV infection plays an inhibitory effect on apoB expression.</p

The symbiotic bacteria Alcaligenes faecalis of the entomopathogenic nematodes Oscheius spp. exhibit potential biocontrol of plant- and entomopathogenic fungi

Soil-dwelling entomopathogenic nematodes (EPNs) kill arthropod hosts by injecting their symbiotic bacteria into the host hemolymph and feed on the bacteria and the tissue of the dying host for several generations cycles until the arthropod cadaver is completely depleted. The EPN-bacteria-arthropod cadaver complex represents a rich energy source for the surrounding opportunistic soil fungal biota and other competitors. We hypothesized that EPNs need to protect their food source until depletion and that the EPN symbiotic bacteria produce volatile and non-volatile exudations that deter different soil fungal groups in the soil. We isolated the symbiotic bacteria species (Alcaligenes faecalis) from the EPN Oscheius spp. and ran infectivity bioassays against entomopathogenic fungi (EPF) as well as against plant pathogenic fungi (PPF). We found that both volatile and non-volatile symbiotic bacterial exudations had negative effects on both EPF and PPF. Such deterrent function on functionally different fungal strains suggests a common mode of action of A.faecalis bacterial exudates, which has the potential to influence the structure of soil microbial communities, and could be integrated into pest management programs for increasing crop protection against fungal pathogens

Quantifying fetal heart health in gestational diabetes: a new approach with fetal heart quantification technology

ObjectiveThis study aimed to assess the impact of gestational diabetes mellitus (GDM) on fetal heart structure and function using a technique called fetal heart quantification (Fetal HQ), with a focus on mitochondrial dynamics, which employs advanced imaging technology for comprehensive analysis.MethodsA total of 180 fetuses with normal heart structures, aged 24–40 weeks of gestation, were examined. A 2–3 s cine loop in the standard four-chamber oblique view was captured and analyzed using the speckle-tracking technique with Fetal HQ. Various echocardiographic parameters were evaluated, including four-chamber view (4CV), global spherical index (GSI), global longitudinal strain (GLS), 24-segment spherical index (SI), ventricular fractional area change (FAC), cardiac output (CO), and stroke volume (SV). These parameters were compared between the GDM group and the control group during two gestational periods: 24+0 to 28+0 weeks and 28+1 to 40+1 weeks. Statistical analysis was performed using independent samples t-tests and Mann-Whitney U tests to identify significant differences.ResultsTwenty fetuses from mothers with GDM and 40 from the control group were recruited at 24+0 to 28+0 weeks. At 28+1 to 40+1 weeks, 40 fetuses from mothers with GDM and 80 from the control group were recruited. The fetal left ventricular global longitudinal function was similar between the GDM and control groups. However, compared to the controls, right ventricular function in the GDM group was lower only at 28+1 to 40+1 weeks. In the GDM group, the global spherical index (GSI) was lower than in the control group at 28+1 to 40+1 weeks (1.175 vs. 1.22; p = 0.001). There were significant decreases in ventricular FAC (38.74% vs. 42.83%; p &lt; 0.0001) and 4CV GLS for the right ventricle (−22.27% vs. −26.31%; p = 0.005) at 28+1 to 40+1 weeks.ConclusionOur findings suggest that GDM is associated with decreased right ventricular function in the fetal heart, particularly during the later stages of pregnancy (28+1 to 40+1 weeks), compared to fetuses from healthy pregnancies. The Fetal HQ technique represents a valuable tool for evaluating the structure and function of fetal hearts affected by GDM during the advanced stages of pregnancy

Evaluation of fetal cardiac morphology and function in hypertensive disorders of pregnancy using Fetal HQ technology combined with uterine artery ultrasound parameters

ObjectiveHypertensive disorders of pregnancy (HDP) significantly affect both maternal and fetal health, with uterine artery hemodynamic parameters playing a critical role in assessing fetal well-being, though they do not provide early insights into fetal cardiac function. Fetal Heart Quantification (Fetal HQ) technology offers a non-invasive, highly accurate method for evaluating fetal heart morphology and function, making it a valuable tool for assessing the impact of HDPs on fetal cardiac health.MethodsThis study investigates fetal heart function and morphology in hypertensive disorders of pregnancy (HDPs) using fetal heart quantification (HQ) technology combined with uterine artery ultrasound parameters. A total of 70 normal fetuses and 59 fetuses with HDPs were included, with 30 cases showing normal and 29 cases showing abnormaluterine artery blood flow patterns. Uterine artery hemodynamic parameters (PI, RI, S/D) and fetal echocardiographic parameters (FRAC, FS, GLS, EF, 4CVCirc, GSI) were assessed.ResultsResults showed that in the HDP group with abnormal uterine artery blood flow, PI, RI, and S/D were significantly higher than in both the control and HDP groups with normal blood flow (P &lt; 0.05). Right ventricular function, including FRAC, GLS, and FS, was significantly decreased in the HDP group with abnormal blood flow, while 4CVCirc and GSI were significantly different from controls. Left ventricular function showed no significant differences. The area under the ROC curve for predicting fetal heart morphology and function via multiple right ventricular parameters was 0.901, and 0.825 for right heart function.ConclusionThese findings suggest that the fetal right ventricle is more sensitive to hemodynamic changes in HDP pregnancies, with right heart functional and morphological indicators potentially serving as predictive markers

Investigation on Numerical Simulation of Radiation Heating Thermal Environment in Car Cabin

Abstract Based on the automobile energy saving and requirements for thermal comfort of heating environment in a car, a capillary radiation heating system for automobile is presented, and the 3D flow field and temperature field of air in the passenger compartment are simulated by using SC/Tetra software. To consider the effect of human thermoregulation, human thermal regulatory model is incorporated with numerical simulation. The thermal comfort of passenger compartment is evaluated by PMV-PPD comfort index basing on the simulation results. It concludes that the distributions of flow field and temperature field of radiation heating environment are relatively homogeneous. Human thermoregulation has a big influence on the temperature distribution in the near region around the human body. Analyzing the PMV values of body surfaces, it concludes that the radiation penal surface temperature should be set to 30°C under the most comfortable environment for human. The research results provide basis for the using of radiation heating technology in a car.</jats:p

Mechanical Behavior of Sediment-Type High-Impurity Salt Cavern Gas Storage during Long-Term Operation

With the development of salt cavern gas storage technology, the construction of large-scale salt cavern gas storage using sediment voids is expected to solve the problems of low effective volume formation rate and poor construction economy of high-impurity salt mines. At present, there are few studies on the long-term operational mechanical behavior of salt cavern gas storage under the influence of sediment accumulation. The present paper studies the influence of sediment height, particle gradation, and operating pressure on the stability of salt caverns by constructing a coupling model of sediment particle discontinuous medium and surrounding rock continuous medium. The continuous&ndash;discontinuous coupling algorithm is suitable for analyzing the influence of sediment height and particle gradation on the creep shrinkage of salt caverns. The increase in sediment height slows down the creep shrinkage of the cavern bottom, which strengthens the restraining effect on the surrounding rock of the cavern. As a result, the position of the maximum displacement of the surrounding rock moves to the upper part of the cavern. The sediment particle gradation has little effect on the cavern volume shrinkage rate. The greater the coarse particle content, the smaller the cavern volume shrinkage rate. The greater the operating pressure, the more conducive to maintaining the stability of the cavern. This situation slows down the upward movement of the sediment accumulation and increases the gas storage space in the upper part of the cavern. The obtained results can provide a reference for evaluating the long-term operational stability of sediment-type high-impurity salt cavern gas storage

Detection Method of Apple Alternaria Leaf Spot Based on Deep-Semi-NMF

[Objective]Apple Alternaria leaf spot can easily lead to premature defoliation of apple tree leaves, thereby affecting the quality and yield of apples. Consequently, accurately detecting of the disease has become a critical issue in the precise prevention and control of apple tree diseases. Due to factors such as backlighting, traditional image segmentation-based methods for detecting disease spots struggle to accurately identify the boundaries of diseased areas against complex backgrounds. There is an urgent need to develop new methods for detecting apple Alternaria leaf spot, which can assist in the precise prevention and control of apple tree diseases.[Methods]A novel detection method named Deep Semi-Non-negative Matrix Factorization-based Mahalanobis Distance Anomaly Detection (DSNMFMAD) was proposed, which combines Deep Semi-Non-negative Matrix Factorization (DSNMF) with Mahalanobis distance for robust anomaly detection in complex image backgrounds. The proposed method began by utilizing DSNMF to extract low-rank background components and sparse anomaly features from the apple Alternaria leaf spot images. This enabled effective separation of the background and anomalies, mitigating interference from complex background noise while preserving the non-negativity constraints inherent in the data. Subsequently, Mahalanobis distance was employed, based on the Singular Value Decomposition (SVD) feature subspace, to construct a lesion detector. The detector identified lesions by calculating the anomaly degree of each pixel in the anomalous regions. The apple tree leaf disease dataset used was provided by PaddlePaddle AI-Studio. Each image in the dataset has a resolution of 512×512 pixels, in RGB color format, and was in JPEG format. The dataset was captured in both laboratory and natural environments. Under laboratory conditions, 190 images of apple leaves with spot-induced leaf drop were used, while 237 images were collected under natural conditions. Furthermore, the dataset was augmented with geometric transformations and random changes in brightness, contrast, and hue, resulting in 1 145 images under laboratory conditions and 1 419 images under natural conditions. These images reflect various real-world scenarios, capturing apple leaves at different stages of maturity, in diverse lighting conditions, angles, and noise environments. This diversed dataset ensured that the proposed method could be tested under a wide range of practical conditions, providing a comprehensive evaluation of its effectiveness in detecting apple Alternaria leaf spot.[Results and Discussions]DSNMFMAD demonstrated outstanding performance under both laboratory and natural conditions. A comparative analysis was conducted with several other detection methods, including GRX (Reed-Xiaoli detector), LRX (Local Reed-Xiaoli detector), CRD (Collaborative-Representation-Based Detector), LSMAD (LRaSMD-Based Mahalanobis Distance Detector), and the deep learning model Unet. The results demonstrated that DSNMFMAD exhibited superior performance in the laboratory environment. The results demonstrated that DSNMFMAD attained a recognition accuracy of 99.8% and a detection speed of 0.087 2 s/image. The accuracy of DSNMFMAD was found to exceed that of GRX, LRX, CRD, LSMAD, and Unet by 0.2%, 37.9%, 10.3%, 0.4%, and 24.5%, respectively. Additionally, the DSNMFMAD exhibited a substantially superior detection speed in comparison to LRX, CRD, LSMAD, and Unet, with an improvement of 8.864, 107.185, 0.309, and 1.565 s, respectively. In a natural environment, where a dataset of 1 419 images of apple Alternaria leaf spot was analysed, DSNMFMAD demonstrated an 87.8% recognition accuracy, with an average detection speed of 0.091 0 s per image. In this case, its accuracy outperformed that of GRX, LRX, CRD, LSMAD, and Unet by 2.5%, 32.7%, 5%, 14.8%, and 3.5%, respectively. Furthermore, the detection speed was faster than that of LRX, CRD, LSMAD, and Unet by 2.898, 132.017, 0.224, and 1.825 s, respectively.[Conclusions]The DSNMFMAD proposed in this study was capable of effectively extracting anomalous parts of an image through DSNMF and accurately detecting the location of apple Alternaria leaf spot using a constructed lesion detector. This method achieved higher detection accuracy compared to the benchmark methods, even under complex background conditions, demonstrating excellent performance in lesion detection. This advancement could provide a valuable technical reference for the detection and prevention of apple Alternaria leaf spot