Effects of paternal ionizing radiation exposure on fertility and offspring's health.

Purpose: The intergenerational effects of ionizing radiation remain controversial. Extensive insights have been revealed for DNA mutations and cancer incidence in progeny, yet many of these results were obtained by immediate post-radiation mating. However, conception at short times after radiation exposure is likely to be avoided. After a long period of fertility recovery, whether unexposed sperm derived from exposed spermatogonia would challenge the health of the offspring is not yet clearly demonstrated. Methods: Ten-week-old C57BL/6J males underwent whole-body acute γ irradiation at 0 and 6.4 Gy. Testes and sperm were collected at different times after radiation to examine reproductive changes. The reproductive, metabolic, and neurodevelopmental parameters were measured in the offspring of controls and the offspring derived from irradiated undifferentiated spermatogonia. Results: Paternal fertility was lost after acute 6.4 Gy γ radiation and recovered at 10-11 weeks post irradiation in mice. The reproductive, metabolic, and neurodevelopmental health of offspring born to irradiated undifferentiated spermatogonia were comparable to those of controls. Conclusion: The male mice could have healthy offspring after recovery from the damage caused by ionizing radiation.

A cuproptosis-related gene expression signature predicting clinical prognosis and immune responses in intrahepatic cholangiocarcinoma detected by single-cell RNA sequence analysis.

BACKGROUND: Cholangiocarcinoma represents a malignant neoplasm originating from the hepatobiliary tree, with a subset of tumors developing inside the liver. Intrahepatic cholangiocarcinomas (ICC) commonly exhibit an asymptomatic presentation, rendering both diagnosis and treatment challenging. Cuproptosis, an emerging regulated cell death pathway induced by copper ions, has garnered attention recently. As cancer cells show altered copper metabolism and comparatively higher copper needs, cuproptosis may play a role in the development of ICC. However, studies investigating this possibility are currently lacking. METHODS: Single-cell and bulk RNA sequence data were analyzed, and correlations were established between the expression of cuproptosis-related molecules and ICC patient survival. Genes with predicting survival were used to create a CUPT score using Cox and LASSO regression and tumor mutation burden (TMB) analysis. The CIBERSORT software was employed to characterize immune cell infiltration within the tumors. Furthermore, immune infiltration prediction, biological function enrichment, and drug sensitivity analyses were conducted to explore the potential implications of the cuproptosis-related signature. The effects of silencing solute carrier family 39 member 4 gene (SLC39A4) expression using siRNA were investigated using assays measuring cell proliferation, colony formation, and cell migration. Key genes of cuproptosis were detected by western blotting. RESULTS: The developed CUPT score divided patients into high and low CUPT score groups. Those with a low score had significantly better prognosis and longer survival. In contrast, high CUPT scores were associated with worse clinical outcomes and significantly higher TMB. Comparisons of the two groups also indicated differences in the immune infiltrate present in the tumors. Finally, we were able to identify 95 drugs potentially affecting the cuproptosis pathway. Some of these might be effective in the treatment of ICC. The in vitro experiments revealed that suppressing the expression of SLC39A4 in ICC cell lines resulted in reduced cell proliferation, colony formation, and cell migration. It also led to an increase in cell death and the upregulation of key genes associated with cuproptosis, namely ferredoxin 1 (FDX1) and dihydrolipoyl transacetylase (DLAT). These findings strongly suggest that this cuproptosis-associated molecule may play a pivotal role in the development and metastasis of ICC. CONCLUSIONS: Changes in the expression of a cuproptosis-related gene signature can predict the clinical prognosis of ICC with considerable accuracy. This supports the notion that cuproptosis influences the diversity and complexity of the immune microenvironment, mutational landscape, and biological behavior of ICC. Understanding this pathway better may hold promise for the development of innovative strategies in the management of this disease.

A convolutional neural network algorithm for breast tumor detection with magnetic detection electrical impedance tomography.

Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of patients. Magnetic Detection Electrical Impedance Tomography (MDEIT) based on the Convolutional Neural Network (CNN), which aims to realize non-invasive, high resolution detection of breast tumors, is proposed. First, the MDEIT forward problem of the coronal and horizontal planes of the breast was simulated and solved using the Finite Element Method to obtain sample datasets of different lesions. Then, the CNN was built and trained to predict the conductivity distribution in different orientations of the breast model. Finally, noise and phantom experiments were performed in order to assess the anti-noise performance of the CNN algorithm and its feasibility of detecting breast tumors in practical applications. The simulation results showed that the reconstruction relative error with the CNN algorithm can be reduced to 10%, in comparison with the truncated singular value decomposition algorithm and back propagation algorithm. The CNN algorithm had better stability in the anti-noise performance test. When the noise of 60 dB was added, the shape of the breast tumor could still be restored by the CNN algorithm. The phantom experimental results showed that through the CNN based reconstruction algorithm, the reconstruction conductivity distribution image was legible and the position of the breast tumor could be determined. It is reasonable to conclude that the MDEIT reconstruction method proposed in this study has practical importance for the early and non-invasive detection of breast tumors.

Enhancement of signal-to-noise ratio for fluorescence endoscope image based on fast digital lock-in algorithm.

In this paper, the signal-to-noise ratios (SNR) of two image channels were enhanced with the fast digital lock-in algorithm. In order to simultaneously improve the quality of white and fluorescence images obtained by fluorescence endoscope, and improve the SNR to achieve a better image processing effect, two sources of white light and near-infrared light of a fluorescence endoscope were modulated, then the acquired images were demodulated into white and fluorescence images. A fluorescent endoscope experimental platform was setup to acquire endoscopic images of a target dyed by indocyanine green. The experimental results showed that the SNR of white and fluorescent images without the lock-in algorithm were 36.56 dB and 33.47 dB, respectively. However, with the lock-in algorithm, the SNR of white and fluorescent images were 39.54 dB and 35.70 dB, respectively. The SNR of white and fluorescent images was increased by 8.2% and 6.7%, respectively, by appling the digital lock-in algorithm. Therefore, this novel fluorescence endoscope based on the fast digital lock-in algorithm can rapidly and simultaneously obtain two-channel images of white light and fluorescence, effectively enhance the SNR of white and fluorescent images, and improve the imaging quality.

Application of Deep Convolutional Neural Networks for Discriminating Benign, Borderline, and Malignant Serous Ovarian Tumors From Ultrasound Images.

OBJECTIVE: This study aimed to evaluate the performance of the deep convolutional neural network (DCNN) to discriminate between benign, borderline, and malignant serous ovarian tumors (SOTs) on ultrasound(US) images. MATERIAL AND METHODS: This retrospective study included 279 pathology-confirmed SOTs US images from 265 patients from March 2013 to December 2016. Two- and three-class classification task based on US images were proposed to classify benign, borderline, and malignant SOTs using a DCNN. The 2-class classification task was divided into two subtasks: benign vs. borderline & malignant (task A), borderline vs. malignant (task B). Five DCNN architectures, namely VGG16, GoogLeNet, ResNet34, MobileNet, and DenseNet, were trained and model performance before and after transfer learning was tested. Model performance was analyzed using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). RESULTS: The best overall performance was for the ResNet34 model, which also achieved the better performance after transfer learning. When classifying benign and non-benign tumors, the AUC was 0.96, the sensitivity was 0.91, and the specificity was 0.91. When predicting malignancy and borderline tumors, the AUC was 0.91, the sensitivity was 0.98, and the specificity was 0.74. The model had an overall accuracy of 0.75 for in directly classifying the three categories of benign, malignant and borderline SOTs, and a sensitivity of 0.89 for malignant, which was better than the overall diagnostic accuracy of 0.67 and sensitivity of 0.75 for malignant of the senior ultrasonographer. CONCLUSION: DCNN model analysis of US images can provide complementary clinical diagnostic information and is thus a promising technique for effective differentiation of benign, borderline, and malignant SOTs.

Therapeutic potential of fucoidan in the reduction of hepatic pathology in murine schistosomiasis japonica.

BACKGROUND: Hepatic granuloma formation and fibrosis as the consequence of tissue entrapped eggs produced by female schistosomes characterize the pathology of Schistosoma japonicum infection. It has been proposed that fucoidan, a sulfated polysaccharide existing naturally in brown seaweed Fucus vesiculosus, plays a diversified role to perform immunomodulatory activities. However, whether fucoidan functions in the host hepatic pathology is unknown and identifying the potential mechanism that is responsible for hepatic improvement is still necessary. METHODS: We evaluated the hepatic pathology from S. japonicum-infected mice after treatment with fucoidan. qRT-PCR and immunofluorescence were used to detect the pro- or anti-inflammatory factors and the phosphorylated p65 in the livers. In addition, flow cytometry was also performed to investigate the T cell subsets in the S. japonicum-infected mice after treatment with fucoidan, and functional molecules relatively specific to Treg cells were detected in vitro. Furthermore, macrophages were treated with fucoidan in vitro and to detect the inflammatory cytokines. RESULTS: Treatment with fucoidan significantly reduced the hepatic granuloma size and fibrosis response during S. japonicum infection. The attenuated phospho-p65 protein levels and the mRNA levels of pro-inflammatory cytokines (IL-6, IL-12 and TNF-α) were observed in the livers from fucoidan-treated S. japonicum-infected mice; however, the mRNA levels of anti-inflammatory cytokines (IL-4 and IL-13) were increased. In addition, the infiltration of Treg cells was significantly enhanced both in the livers and spleens from fucoidan-treated S. japonicum-infected mice. Consistent with this, the mRNA levels of IL-10 and TGF-ß were dramatically increased in the livers from S. japonicum-infected mice after fucoidan treatment. Furthermore, in vitro stimulated splenocytes with fucoidan resulted in increasing Treg cells in splenocytes as well as the functional expression of CC chemokine receptor type 4 (CCR4) and CXC chemokine receptor type 5 (CXCR5) in Treg cells. Additionally, fucoidan promoted the mRNA levels of IL-4 and IL-13 in macrophages. CONCLUSIONS: These findings suggest an important role of natural fucoidan in reducing hepatic pathology in the progress of S. japonicum infection with a stronger Treg response, which may reveal a new potential therapeutic strategy for hepatic disease caused by parasitic chronic infection.

ASF1B promotes cervical cancer progression through stabilization of CDK9.

Cervical cancer (CC) is one of the most deadly cancers in women, its current treatments still result in poor outcomes and developing the novel targets and therapeutic strategies are urgently needed. Recent studies have shown that anti-silencing function 1B (ASF1B) might be used as a new proliferation marker for cancer diagnosis and prognosis. However, the expression and function of ASF1B in cervical cancer remain unclear. Here, we induced ASF1B knockdown and overexpression in cervical cancer cell lines and detected the biological behavior changes in vitro. Furthermore, we established two murine models using stable ASF1B-shRNA HeLa cells or normal HeLa cells following AAV-shRNA-ASF1B administration to evaluate how suppression of ASF1B affects tumor growth. We showed that ASF1B functions as an oncogene in cervical cancer cells. Silence of ASF1B suppressed cervical cancer cell growth in vitro and in vivo, while, ASF1B overexpression accelerated cancer cell proliferation. Furthermore, ASF1B deficiency induced cell cycle arrest and apoptosis. Mechanistically, we found that ASF1B formed stable complexes with cyclin-dependent kinase 9 (CDK9), and positively regulated CDK9 stabilization. Taken together, tumorigenic ASF1B could be targeted to suppress cervical cancer tumor growth by inducing apoptotic cell death.

Automated detection of focal cortical dysplasia using a deep convolutional neural network.

Focal cortical dysplasia (FCD) is one of the commonest epileptogenic lesions, and is related to malformations of the cortical development. The findings on magnetic resonance (MR) images are important for the diagnosis and surgical planning of FCD. In this paper, an automated detection technique for FCD is proposed using MR images and deep learning. The input MR image is first preprocessed to correct the bias field, normalize intensities, align with a standard atlas, and strip the non-brain tissues. All cortical patches are then extracted on each axial slice, and these patches are classified into FCD and non-FCD using a deep convolutional neural network (CNN) with five convolutional layers, a max pooling layer, and two fully-connected layers. Finally, the false and missed classifications are corrected in the post-processing stage. The technique is evaluated using images of 10 patients with FCD and 20 controls. The proposed CNN shows a superior performance in classifying cortical image patches compared with multiple CNN architectures. For the system-level evaluation, nine of the ten FCD images are successfully detected, and 85% of the non-FCD images are correctly identified. Overall, this CNN based technique could learn optimal cortical (texture and symmetric) features automatically, and improve the FCD detection.

Signal-to-noise ratio analysis and improvement for fluorescence tomography imaging.

CCD-based fluorescence tomography is widely used for small animal whole-body imaging. In this report, systematic signal-to-noise ratio (SNR) analyses of a fluorescence tomography imaging (FTI) system were performed, resulting in an easy-to-follow strategy to optimize hardware configurations and operational conditions for acquiring high-quality imaging data and for improving the overall system performance. Phantom experiments were conducted to demonstrate the performance improvement by these optimizations. The improved performance was further verified by imaging a tumor-bearing mouse in vivo. This report provides general and practical guidelines for setting up a high-performance electron multiplying charge coupled device based FTI system to achieve an optimized SNR, which can be useful for future FTI technology development.

Review: Porous Metal Filters and Membranes for Oil-Water Separation.

In recent years, oil-water separation has been widely researched to reduce the influences of industrial wastewater and offshore oil spills. A filter membrane with special wettability can achieve the separation because of its opposite wettability for water phase and oil phase. In the field of filter membrane with special wettability, porous metal filter membranes have been much investigated because of the associated high efficiency, portability, high plasticity, high thermal stability, and low cost. This article provides an overview of the research progress of the porous metal filter membrane fabrication and discusses the future developments in this field.

Fast localization method of an anomaly in tissue based on differential optical density.

The position of the source-detector (S-D) relative to an anomaly has an important influence on the detection effect in non-invasive near-infrared spectroscopy-based methods. In this study, a single-source multi-detector structure was designed in order to realize the rapid localization of anomalies within tissue. This method uses finite element analysis of the optical density distribution for different horizontal positions, depths and diameters of anomalies. The difference in optical density between the detectors was then calculated. The simulation results show that the horizontal position of the anomaly in the tissue can be quickly located according to the differential optical density difference curves formed by the multiple detectors. The Gaussian fitting feature of these curves shows strong correlation with the horizontal positions, depths and diameters of the anomaly. Through the differential optical density difference curves, rapid localization within the region of interest can be achieved. This method provides an important reference for sources and detectors location for tumor detection, brain function optical imaging and other fields using near infrared spectroscopy, and improves its detection accuracy.

Computer-aided diagnosis of cavernous malformations in brain MR images.

Cavernous malformation or cavernoma is one of the most common epileptogenic lesions. It is a type of brain vessel abnormality that can cause serious symptoms such as seizures, intracerebral hemorrhage, and various neurological disorders. Manual detection of cavernomas by physicians in a large set of brain MRI slices is a time-consuming and labor-intensive task and often delays diagnosis. In this paper, we propose a computer-aided diagnosis (CAD) system for cavernomas based on T2-weighted axial plane MRI image analysis. The proposed technique first extracts the brain area based on atlas registration and active contour model, and then performs template matching to obtain candidate cavernoma regions. Texture, the histogram of oriented gradients and local binary pattern features of each candidate region are calculated, and principal component analysis is applied to reduce the feature dimensionality. Support vector machines (SVMs) are finally used to classify each region into cavernoma or non-cavernoma so that most of the false positives (obtained by template matching) are eliminated. The performance of the proposed CAD system is evaluated and experimental results show that it provides superior performance in cavernoma detection compared to existing techniques.

Construction of ICG encapsulated W18O49@MSN as a fluorescence carrier for real-time tracked photothermal therapy.

Photothermal therapy (PTT) has drawn tremendous attention because of its high therapeutic efficiency in targeting cells while minimizing the damage to normal tissues and organs. Tungsten oxide (W18O49, WO) plays a pivotal role in PTT development and its use in PTT systems has been extensively studied. However, it is difficult to control morphology of WO through conventional hydrothermal method. Which make its related researches have been limited up to now. In this study, we describe the construction and effects on tumor of a novel nanoplatform based on WO and indocyanine green (ICG) loaded in mesoporous silica nanoparticles (MSN) for dual-modal PTT and near-infrared imaging. (WO+ICG)@MSN could efficiently control WO shape without the need of surface modification due to its water-soluble of MSN. (WO+ICG)@MSN produced a PTT synergistic effect under irradiation of a single 808nm near-infrared (NIR) laser. Notably, an enhanced lethal effect of the 808nm laser triggering dual-modal therapy on B16 tumor cells was observed. The in vivo animal experiments showed that (WO+ICG)@MSN induced an effective solid tumor reduction under 808nm NIR light irradiation, revealing the potential of these nanocomposites as a NIR-mediated dual-modal therapeutic platform for cancer treatment.

A new theoretical model for transmembrane potential and ion currents induced in a spherical cell under low frequency electromagnetic field.

Time-varying electromagnetic fields (EMF) can induce some physiological effects in neuronal tissues, which have been explored in many applications such as transcranial magnetic stimulation. Although transmembrane potentials and induced currents have already been the subjects of many theoretical studies, most previous works about this topic are mainly completed by utilizing Maxwell's equations, often by solving a Laplace equation. In previous studies, cells were often considered to be three-compartment models with different electroconductivities in different regions (three compartments are often intracellular regions, membrane, and extracellular regions). However, models like that did not take dynamic ion channels into consideration. Therefore, one cannot obtain concrete ionic current changes such as potassium current change or sodium current change by these models. The aim of the present work is to present a new and more detailed model for calculating transmembrane potentials and ionic currents induced by time-varying EMF. Equations used in the present paper originate from Nernst-Plank equations, which are ionic current-related equations. The main work is to calculate ionic current changes induced by EMF exposure, and then transmembrane potential changes are calculated with Hodgkin-Huxley model. Bioelectromagnetics. 37:481-492, 2016. © 2016 Wiley Periodicals, Inc.

Bright and Stable Near-Infrared Pluronic-Silica Nanoparticles as a Contrast Agent for in vivo Optical Imaging.

Near-infrared (NIR) fluorescent nanostructured materials have emerged as novel contrast agents for non-invasive bioimaging. Here we report a class of polymer-silica nanoparticles doped with a NIR fluorescent dye prepared through a facile one-pot strategy. Hydrophobic NIR fluorescent dyes such as IR 780 iodide could be easily encapsulated into the micellar core by self-assembly of amphiphilic triblock copolymer Pluronic F127. When subsequently adding silane in aqueous solution, nanoparticles with a cross-linked core and a hydrophilic PEG shell were formed. The structure of the as-obtained nanoparticles was confirmed by transmission electron microscopy (TEM) and dynamic light scattering (DLS). The nanoparticles exhibited a well-defined spherical structure with a mean diameter of approximately 30 nm, and excellent monodispersity and stability in aqueous solution. In addition, the photo-stability of IR 780 was significantly improved by encapsulation into the nanoparticles. In vitro MTT assay with cell lines HEK293 and A431 demonstrated that the IR 780 loaded nanoparticles (termed as IR780@NPs) were biocompatible. In vivo sentinel lymph node imaging revealed that the fluorescent intensity and retention time of the IR780@NPs were clearly superior to its constituent free dye, making it amenable to in vivo bioimaging. Further in vivo tumor imaging indicated that IR780@NPs have a longer retention time and much higher accumulation on the tumor site compared to free dye after intravenous administration. Overall this hydrophilic NIR fluorescent contrast agent exhibits excellent photophysical characteristics and low cytotoxicity, and holds a strong promise for a variety of applications including bioimaging and therapy.

Dual regulation of ets-activated gene expression by SP1.

The human folate receptor (hFR) type gamma gene is driven by a TATA-less promoter that uses a canonical Sp1 element for basal transcription. Using nuclear extract from 293 (human embryonic) cells, we mapped a second (non-canonical) Sp1 element to which Sp1 bound with a comparable affinity and which overlaps a functional ets binding site (EBS). Mutagenesis experiments revealed that the binding of ets to the EBS activates the promoter synergistically with Sp1 bound at the downstream site; however, binding of Sp1 to the EBS does not contribute to promoter activity. A further increase in Sp1 by inducible expression in recombinant 293 cells resulted in a small but significant decrease in the hFR-gamma promoter activity, but the decrease was abolished when the EBS was deleted from the promoter. In 293 cells, which do not express hFR-gamma, the Sp1 level was relatively high whereas in the hFR-gamma-positive HL60 leukemia cells, the Sp1 level was low and the EBS predominantly bound an ets protein. To account for the above observations, we propose a model in which when the Sp1 level is low, ets out competes Sp1 for binding to the EBS and synergistically enhances the hFR-gamma promoter activity by interacting with Sp1 bound at the canonical site whereas at higher levels, Sp1 represses the promoter by competitively inhibiting the binding of ets. As a partial extension of this model to the regulation of other ets activated genes, we show that Sp1 can predictably bind to a variety of ets elements including those responsive to Ets1 and Spi.1/Pu.1. A dual concentration-dependent action of Sp1 as an activator or a repressor offers a potential mechanism contributing to tissue-specific regulation of ets-dependent genes by Sp1.