A radiomics-based formula for the preoperative prediction of postoperative pancreatic fistula in patients with pancreaticoduodenectomy

Objective

The objective of the study was to develop and validate a radiomics-based formula for the preoperative prediction of postoperative pancreatic fistula (POPF) in patients undergoing pancreaticoduodenectomy (PD).

Materials and methods

A total of 117 consecutive patients who underwent PD were enrolled in this retrospective study. Radiomics features were extracted from portal venous phase computed tomography of the above patients. The least absolute shrinkage and selection operator logistic regression was used to construct a formula of Rad-score calculation. Then the performance of the formula was assessed with standard pancreatic Fistula Risk Score.

Results

The Rad-score could predict POPF with an area under the curve (AUC) of 0.8248 in the training cohort and of 0.7609 in the validation cohort. Patients who had experienced POPF generally had a statistically higher Rad-score than those who had not experienced POPF in both cohorts. The AUC of the Rad-score was statistically higher than the Fistula Risk Score for predicting POPF in both the training and validation cohort.

Conclusion

A novel radiomics-based formula was developed and validated for predicting POPF in patients who underwent PD, which provides a new method for identifying POPF risks and may help to improve informed decision-making in the prevention of POPF at low cost.

Sequential immunization of macaques with two differentially attenuated vaccines induced long-term virus-specific immune responses and conferred protection against AIDS caused by heterologous simian human immunodeficiency Virus (SHIV(89.6)P)

Four rhesus macaques were sequentially immunized with live vaccines DeltavpuDeltanefSHIV-4 (vaccine-I) and Deltavpu SHIV(PPC) (vaccine-II). The vaccine viruses did not replicate productively in the peripheral blood mononuclear cells (PBMCs) of the vaccinated animals. All four animals developed binding antibodies against both the vaccine-I and -II envelope glycoproteins but neutralizing antibodies only against vaccine-I. They developed vaccine virus-specific CTLs that also recognized homologous as well as heterologous pathogenic SHIVs. Thirty weeks after the last immunization, the vaccinated animals and three unvaccinated control animals were challenged iv with a highly virulent heterologous SHIV(89.6)P. As expected, the three unvaccinated control animals developed large numbers of infectious PBMCs, high plasma viremia, and precipitous loss of CD4(+) T cells. Two controls did not develop any immune response and succumbed to AIDS in about 6 months. The third control animal developed neutralizing antibodies and had a more chronic disease course, but eventually succumbed to AIDS-related complications 81 weeks after inoculation. The four vaccinated animals became infected with challenge virus as indicated by the presence of challenge virus-specific DNA in the PBMCs and RNA in plasma. However, virus in these animals replicated approximately 200- to 60,000-fold less efficiently than in control animals and eventually, plasma viral RNA became undetectable in three of the four vaccinates. The animals maintained normal CD4(+) T-cell levels throughout the observation period of 85 weeks after a transient drop at Week 3 postchallenge. They also maintained CTL responses throughout the observation period. These studies thus showed that the graded immunization schedule resulted in a safe and highly effective long-lasting immune response that was associated with protection against AIDS by highly pathogenic heterologous SHIV(89.6)P.

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

PURPOSE

A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors.

METHODS

The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence.

RESULTS

The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively.

CONCLUSIONS

The proposed automatic approach achieves robust, accurate, and fast liver segmentation for 3D CTce datasets. The AdaBoost voxel classifier can detect liver area quickly without errors and provides sufficient liver shape information for model initialization. The AdaBoost profile classifier achieves sufficient accuracy and greatly decreases segmentation time. These results show that the proposed segmentation method achieves a level of accuracy comparable to that of state-of-the-art automatic methods based on ASM.

Passively administered neutralizing serum that protected macaques against infection with parenterally inoculated pathogenic simian-human immunodeficiency virus failed to protect against mucosally inoculated virus

Macaques inoculated orally, vaginally, or parenterally with SHIV(KU-1) develop severe systemic infection, acute loss of CD4+ T cells, and AIDS. We showed in a previous report that passive immunization with neutralizing serum protected macaques against infection with parenterally inoculated pathogenic SHIV given 24 hr later. In the study reported here we asked whether the identical passive immunization protocol would protect macaques against infection with pathogenic SHIV following oral inoculation of the virus. Ten pigtail macaques were inoculated orally with one animal infectious dose of SHIV(KU-1). Four of the 10 had been given pooled anti-SHIV plasma (15 ml/kg) 24 hr earlier, 4 others were given the same dose of anti-SHIV plasma 2 hr after virus challenge, and the 2 remaining animals were used as controls. The neutralizing antibodies failed to protect macaques against infection after mucosal challenge with SHIV(KU-1).

Development of the Intrinsic Language Network in Preschool Children from Ages 3 to 5 Years

Resting state studies of spontaneous fluctuations in the functional magnetic resonance imaging (fMRI) blood oxygen level dependent signal have shown great potential in mapping the intrinsic functional connectivity of the human brain underlying cognitive functions. The aim of the present study was to explore the developmental changes in functional networks of the developing human brain exemplified with the language network in typically developing preschool children. To this end, resting-sate fMRI data were obtained from native Chinese children at ages of 3 and 5 years, 15 in each age group. Resting-state functional connectivity (RSFC) was analyzed for four regions of interest; these are the left and right anterior superior temporal gyrus (aSTG), left posterior superior temporal gyrus (pSTG), and left inferior frontal gyrus (IFG). The comparison of these RSFC maps between 3- and 5-year-olds revealed that RSFC decreases in the right aSTG and increases in the left hemisphere between aSTG seed and IFG, between pSTG seed and IFG, as well as between IFG seed and posterior superior temporal sulcus. In a subsequent analysis, functional asymmetry of the language network seeding in aSTG, pSTG and IFG was further investigated. The results showed an increase of left lateralization in both RSFC of pSTG and of IFG from ages 3 to 5 years. The IFG showed a leftward lateralized trend in 3-year-olds, while pSTG demonstrated rightward asymmetry in 5-year-olds. These findings suggest clear developmental trajectories of the language network between 3- and 5-year-olds revealed as a function of age, characterized by increasing long-range connections and dynamic hemispheric lateralization with age. Our study provides new insights into the developmental changes of a well-established functional network in young children and also offers a basis for future cross-culture and cross-age studies of the resting-state language network.

Scale-adaptive surface modeling of vascular structures

BACKGROUND

The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size.

METHODS

Our method first extracts the vascular boundary voxels from the segmentation result, and utilizes these voxels to build a three-dimensional (3D) point cloud whose normal vectors are estimated via covariance analysis. Then a 3D implicit indicator function is computed from the oriented 3D point cloud by solving a Poisson equation. Finally the vessel surface is generated by a proposed adaptive polygonization algorithm for explicit 3D visualization.

RESULTS

Experiments carried out on several typical vascular structures demonstrate that the presented method yields both a smooth morphologically correct and a topologically preserved two-manifold surface, which is scale-adaptive to the local curvature of the surface. Furthermore, the presented method produces fewer and better-shaped triangles with satisfactory surface quality and accuracy.

CONCLUSIONS

Compared to other state-of-the-art approaches, our method reaches good balance in terms of smoothness, accuracy, triangle quality and surface size. The vessel surfaces produced by our method are suitable for applications such as computational fluid dynamics simulations and real-time virtual interventional surgery.

Transverse momentum and centrality dependence of high-pT nonphotonic electron suppression in Au+Au collisions at sqrt[s NN]=200 GeV

The STAR collaboration at the BNL Relativistic Heavy-Ion Collider (RHIC) reports measurements of the inclusive yield of nonphotonic electrons, which arise dominantly from semileptonic decays of heavy flavor mesons, over a broad range of transverse momenta (1.2<p(T)<10 GeV/c) in p+p, d+Au, and Au+Au collisions at sqrt[s_{NN}]=200 GeV. The nonphotonic electron yield exhibits an unexpectedly large suppression in central Au+Au collisions at high p(T), suggesting substantial heavy-quark energy loss at RHIC. The centrality and p(T) dependences of the suppression provide constraints on theoretical models of suppression.

Subclinical hypothyroidism and the associations with macrovascular complications and chronic kidney disease in patients with Type 2 diabetes

AIMS

The prevalence of subclinical hypothyroidism (SCH) is high among patients with diabetes, although the relationship between SCH and diabetic vascular complications is unknown. This study aimed to determine the relationship between SCH and vascular complications in patients with Type 2 diabetes.

METHODS

In this cross sectional study, 991 patients with Type 2 diabetes were screened for thyroid function at their admission to the Second Affiliated Hospital of Chongqing Medical University. We compared the prevalence of coronary heart disease (CHD), ischaemic stroke and chronic kidney disease (CKD) with the prevalence of euthyroidism and SCH.

RESULTS

Among the 991 patients, 126 (12.7%) patients had SCH. The prevalence of CHD was significantly higher in the SCH group than in the euthyroid group (22.2% and 15.0%, respectively; P = 0.039). In the logistic regression analyses, SCH was associated with CHD [odds ratio (OR): 1.993; 95% confidence interval (CI): 1.135-3.497; P = 0.016]. This association was stronger in patients aged ≥ 65 years than in younger patients [2.474 (1.173-5.220); P = 0.017]. No significant association was found between SCH and ischaemic stroke. Patients with severe SCH had a high risk of CKD [1.842 (1.120-3.029); P = 0.016].

CONCLUSIONS

This study provides evidence that SCH in patients with Type 2 diabetes is associated with a high prevalence of CHD (and CKD in severe SCH), although not with ischaemic stroke.

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

PURPOSE

Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via data-driven feedback. In surgical workflow analysis up to 91% average precision has been reported for phase recognition on an open data single-center video dataset. In this work we investigated the generalizability of phase recognition algorithms in a multicenter setting including more difficult recognition tasks such as surgical action and surgical skill.

METHODS

To achieve this goal, a dataset with 33 laparoscopic cholecystectomy videos from three surgical centers with a total operation time of 22 h was created. Labels included framewise annotation of seven surgical phases with 250 phase transitions, 5514 occurences of four surgical actions, 6980 occurences of 21 surgical instruments from seven instrument categories and 495 skill classifications in five skill dimensions. The dataset was used in the 2019 international Endoscopic Vision challenge, sub-challenge for surgical workflow and skill analysis. Here, 12 research teams trained and submitted their machine learning algorithms for recognition of phase, action, instrument and/or skill assessment.

RESULTS

F1-scores were achieved for phase recognition between 23.9% and 67.7% (n = 9 teams), for instrument presence detection between 38.5% and 63.8% (n = 8 teams), but for action recognition only between 21.8% and 23.3% (n = 5 teams). The average absolute error for skill assessment was 0.78 (n = 1 team).

CONCLUSION

Surgical workflow and skill analysis are promising technologies to support the surgical team, but there is still room for improvement, as shown by our comparison of machine learning algorithms. This novel HeiChole benchmark can be used for comparable evaluation and validation of future work. In future studies, it is of utmost importance to create more open, high-quality datasets in order to allow the development of artificial intelligence and cognitive robotics in surgery.

Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder

Objective

In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, high accuracy of diagnosis by an automated system can reduce the radiologist’s workload on scrutinizing the medical images.

Method

We present a deep learning model in order to efficiently detect abnormal levels or identify normal levels during mass chest screening so as to obtain the probability confidence of the CXRs. Moreover, a convolutional sparse denoising autoencoder is designed to compute the reconstruction error. We employ four publicly available radiology datasets pertaining to CXRs, analyze their reports, and utilize their images for mining the correct disease level of the CXRs that are to be submitted to a computer aided triaging system. Based on our approach, we vote for the final decision from multi-classifiers to determine which three levels of the images (i.e. normal, abnormal, and uncertain cases) that the CXRs fall into.

Results

We only deal with the grade diagnosis for physical examination and propose multiple new metric indices. Combining predictors for classification by using the area under a receiver operating characteristic curve, we observe that the final decision is related to the threshold from reconstruction error and the probability value. Our method achieves promising results in terms of precision of 98.7 and 94.3% based on the normal and abnormal cases, respectively.

Conclusion

The results achieved by the proposed framework show superiority in classifying the disease level with high accuracy. This can potentially save the radiologists time and effort, so as to allow them to focus on higher-level risk CXRs.

A radiomics-based nomogram for preoperative T staging prediction of rectal cancer

Purpose

To investigate the value of a radiomics-based nomogram in predicting preoperative T staging of rectal cancer.

Methods

A total of 268 eligible rectal cancer patients from August 2012 to December 2018 were enrolled and allocated into two datasets: training (n = 188) and validation datasets (n = 80). Another set of 32 patients from January 2019 to July 2019 was included in a prospective analysis. Pretreatment T2-weighted images were used to radiomics features extraction. Feature selection and radiomics score (Rad-score) construction were performed through a least absolute shrinkage and selection operator regression analysis. The nomogram, which included Rad-scores and clinical factors, was built using multivariate logistic regression. Discrimination, calibration, and clinical utility were used to evaluate the performance of the nomogram.

Results

The Rad-score containing nine selected features was significantly related to T staging. Patients who had locally advanced rectal cancer (LARC) generally had higher Rad-scores than patients with early-stage rectal cancer. The nomogram incorporated Rad-scores and carcinoembryonic antigen levels and showed good discrimination, with an area under the curve (AUC) of 0.882 (95% confidence interval [CI] 0.835–0.930) in the training dataset and 0.846 (95% CI 0.757–0.936) in the validation dataset. The calibration curves confirmed high goodness of fit, and the decision curve analysis revealed the clinical value. A prospective analysis demonstrated that the AUC of the nomogram to predict LARC was 0.859 (95% CI 0.730–0.987).

Conclusion

A radiomics-based nomogram is a novel method for predicting LARC and can provide support in clinical decision making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00261-021-03137-1.

Plasmas from lymphocyte- and macrophage-tropic SIVmac-infected macaques have antibodies with a broader spectrum of virus neutralization activity in macrophage versus lymphocyte cultures

We examined plasma from macaques infected with three different phenotypes of SIVmac for their ability to neutralize the infectivity of homologous and heterologous virus in lymphocyte (CEMx174 cells or normal rhesus macaque peripheral blood lymphocytes) or normal rhesus macaque macrophage (Mphi) cultures. Similar to previous findings, we observed that some plasmas failed to neutralize or poorly neutralized the infectivity of SIVmac239 and SIVmac251(<1:20 plasma dilution) in lymphocyte cultures. In contrast, when primary rhesus Mphi cultures were used as the indicator cells, the same plasmas neutralized both viruses at high dilutions (1:200 to 1:20,000). Neutralization of virus infectivity by the various plasmas was confirmed by SIV core antigen capture assays. We excluded the possibility that this differential neutralization in Mphi was related to the differences in the ability of the virus strain to replicate in these two cell types by demonstrating that the replication efficiency of SIVmac251 in CEMx174 cells, PBMC, and Mphi cultures was very similar. The role of Fc receptors on the Mphi surface in the clearance of the virus-antibody complexes was also excluded since similar neutralizing results were obtained using whole plasmas, purified IgG antibodies, and purified Fab fragments derived from the IgG fraction of these plasmas. The mechanism of virus neutralization in Mphi does not appear to involve blocking of virus entry into the cells since radiolabeled virus reacted with anti-SIV antibodies was taken up by rhesus Mphi as efficiently as virus reacted with normal antibody. DNA of the neutralized virus was identified in the Mphi cultures, but virus replication, as evidenced by accumulation of viral protein products, was not detectable so long as the antibodies were present in the medium. Removal of the antibodies resulted in a resumption of virus replication in the Mphi. These results indicate that virus infectivity can be efficiently neutralized by antibodies in Mphi cultures by a mechanism that is fundamentally different from that in lymphocyte cultures.

MDCC-Net: Multiscale double-channel convolution U-Net framework for colorectal tumor segmentation

PURPOSE

Multiscale feature fusion is a feasible method to improve tumor segmentation accuracy. However, current multiscale networks have two common problems: 1. Some networks only allow feature fusion between encoders and decoders of the same scale. It is obvious that such feature fusion is not sufficient. 2. Some networks have too many dense skip connections and too much nesting between the coding layer and the decoding layer, which causes some features to be lost and means that not enough information will be learned from multiple scales. To overcome these two problems, we propose a multiscale double-channel convolution U-Net (MDCC-Net) framework for colorectal tumor segmentation.

METHODS

In the coding layer, we designed a dual-channel separation and convolution module and then added residual connections to perform multiscale feature fusion on the input image and the feature map after dual-channel separation and convolution. By fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

RESULTS

The segmentation results show that our proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 83.57%, which is an improvement of 9.59%, 6.42%, and 1.57% compared with nnU-Net, U-Net, and U-Net++, respectively.

CONCLUSION

The experimental results show that our proposed method has good performance in the segmentation of colorectal tumors and is close to the expert level. The proposed method has potential clinical applicability.

The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5

In recent years, research on human functional brain imaging using resting-state fMRI techniques has been increasingly prevalent. The term "default mode" was proposed to describe a baseline or default state of the brain during rest. Recent studies suggested that the default mode network (DMN) is comprised of two functionally distinct subsystems: a dorsal-medial prefrontal cortex (DMPFC) subsystem involved in self-oriented cognition (i.e., theory of mind) and a medial temporal lobe (MTL) subsystem engaged in memory and scene construction; both subsystems interact with the anterior medial prefrontal cortex (aMPFC) and posterior cingulate (PCC) as the core regions of DMN. The present study explored the development of DMN core regions and these two subsystems in both hemispheres from 3- to 5-year-old children. The analysis of the intrinsic activity showed strong developmental changes in both subsystems, and significant changes were specifically found in MTL subsystem, but not in DMPFC subsystem, implying distinct developmental trajectories for DMN subsystems. We found stronger interactions between the DMPFC and MTL subsystems in 5-year-olds, particularly in the left subsystems that support the development of environmental adaptation and relatively complex mental activities. These results also indicate that there is stronger right hemispheric lateralization at age 3, which then changes as bilateral development gradually increases through to age 5, suggesting in turn the hemispheric dominance in DMN subsystems changing with age. The present results provide primary evidence for the development of DMN subsystems in early life, which might be closely related to the development of social cognition in childhood.

Neuropathogenesis of chimeric simian human immunodeficiency virus infection in rhesus macaques

Comparative studies were performed to determine the neuropathogenesis of infection in macaques with simian human immunodeficiency virus (SHIV)89.6P and SHIV(KU). Both viruses utilize the CD4 receptor and CXCR4 co-receptor. However, in addition, SHIV89.6P uses the CCR5 co-receptor. Both agents are dual tropic for CD4+ T cells and blood-derived macrophages of rhesus macaques. Following inoculation into macaques, both caused rapid elimination of CD4+ T cells but they varied greatly in mechanisms of neuropathogenesis. Two animals infected with SHIV89.6P developed typical lentiviral encephalitis in which multinucleated giant cell formation, nodular accumulations of microglial cells, activated macrophages and astrocytes, and perivascular accumulations of mononuclear cells were present in the brain. Many of the macrophages in these lesions contained viral RNA. Three macaques infected with SHIV(KU) and killed on days 6, 11 and 18, respectively, developed a slowly progressive infection in the CNS but macrophages were not productively infected and there were no pathological changes in the brain. Two other animals infected with this virus and killed several months later showed minimal infection in the brain even though one of the two developed encephalitis of unknown etiology. The basic difference in the mechanisms of neuropathogenesis by the two viruses may be related to co-receptor usage. SHIV89.6P, in utilizing the CCR5 co-receptor, caused neuropathogenic effects that are similar to other neurovirulent primate lentiviruses.

Details preserved unsupervised depth estimation by fusing traditional stereo knowledge from laparoscopic images

Depth estimation plays an important role in vision-based laparoscope surgical navigation systems. Most learning-based depth estimation methods require ground truth depth or disparity images for training; however, these data are difficult to obtain in laparoscopy. The authors present an unsupervised learning depth estimation approach by fusing traditional stereo knowledge. The traditional stereo method is used to generate proxy disparity labels, in which unreliable depth measurements are removed via a confidence measure to improve stereo accuracy. The disparity images are generated by training a dual encoder-decoder convolutional neural network from rectified stereo images coupled with proxy labels generated by the traditional stereo method. A principled mask is computed to exclude the pixels, which are not seen in one of views due to parallax effects from the calculation of loss function. Moreover, the neighbourhood smoothness term is employed to constrain neighbouring pixels with similar appearances to generate a smooth depth surface. This approach can make the depth of the projected point cloud closer to the real surgical site and preserve realistic details. The authors demonstrate the performance of the method by training and evaluation with a partial nephrectomy da Vinci surgery dataset and heart phantom data from the Hamlyn Centre.

Longitudinal double-spin asymmetry and cross section for inclusive jet production in polarized proton collisions at square root of s = 200 GeV

We report a measurement of the longitudinal double-spin asymmetry A(LL) and the differential cross section for inclusive midrapidity jet production in polarized proton collisions at square root of s = 200 GeV. The cross section data cover transverse momenta 5 < pT < 50 GeV/c and agree with next-to-leading order perturbative QCD evaluations. The A(LL) data cover 5 < pT < 17 GeV/c and disfavor at 98% C.L. maximal positive gluon polarization in the polarized nucleon.

Strange baryon resonance production in sqrt s NN=200 GeV p+p and Au+Au collisions

We report the measurements of Sigma(1385) and Lambda(1520) production in p+p and Au+Au collisions at sqrt[s{NN}]=200 GeV from the STAR Collaboration. The yields and the p(T) spectra are presented and discussed in terms of chemical and thermal freeze-out conditions and compared to model predictions. Thermal and microscopic models do not adequately describe the yields of all the resonances produced in central Au+Au collisions. Our results indicate that there may be a time span between chemical and thermal freeze-out during which elastic hadronic interactions occur.

The effect of phage T7 lysozyme on the production of biologically active porcine somatotropin in Escherichia coli from a gene transcribed by T7 RNA polymerase

We have analyzed the inducible synthesis of recombinant porcine somatotropin (rPST) from the phage T7 gene 10 promotor on the vector pET3a [Rosenberg et al., Gene 56 (1987) 125-135]. Low-level synthesis of phage T7 lysozyme is crucial for high-level synthesis (40%) of rPST, which is greatly reduced if T7 lysozyme synthesis is absent or too high. The synthesis of rPST mRNA is optimized in those constructs coding for low levels of T7 lysozyme, with a reduction in mRNA levels in constructs coding for higher levels of T7 lysozyme or no lysozyme. The rPST can be readily purified following a single chromatographic step and is biologically active as determined by the tibia test following administration to hypophysectomized rats.

Unsupervised learning of depth estimation from imperfect rectified stereo laparoscopic images

BACKGROUND

Learning-based methods have achieved remarkable performances on depth estimation. However, the premise of most self-learning and unsupervised learning methods is built on rigorous, geometrically-aligned stereo rectification. The performances of these methods degrade when the rectification is not accurate. Therefore, we explore an approach for unsupervised depth estimation from stereo images that can handle imperfect camera parameters.

METHODS

We propose an unsupervised deep convolutional network that takes rectified stereo image pairs as input and outputs corresponding dense disparity maps. First, a new vertical correction module is designed for predicting a correction map to compensate for the imperfect geometry alignment. Second, the left and right images, which are reconstructed based on the input image pair and corresponding disparities as well as the vertical correction maps, are regarded as the outputs of the generative term of the generative adversarial network (GAN). Then, the discriminator term of the GAN is used to distinguish the reconstructed images from the original inputs to force the generator to output increasingly realistic images. In addition, a residual mask is introduced to exclude pixels that conflict with the appearance of the original image in the loss calculation.

RESULTS

The proposed model is validated on the publicly available Stereo Correspondence and Reconstruction of Endoscopic Data (SCARED) dataset and the average MAE is 3.054 mm.

CONCLUSION

Our model can effectively handle imperfect rectified stereo images for depth estimation.

Elevated aerobic glycolysis in renal tubular epithelial cells influences the proliferation and differentiation of podocytes and promotes renal interstitial fibrosis

OBJECTIVE

The aim of this study was to elaborate the influence of changing energy metabolism pattern of renal tubular epithelial cells in the process of renal interstitial fibrosis on podocytes. Meanwhile, we also investigated the relationship between energy metabolism pattern and the development of renal interstitial fibrosis.

MATERIALS AND METHODS

We established a model of renal interstitial fibrosis by unilateral ureteral obstruction (UUO). The protein and messenger RNA (mRNA) expression of fibrosis signs, such as α-smooth muscle actin (α-SMA) and fibronectin (FN) were detected. We also measured the protein and mRNA expression of key glycolytic enzymes, including pyruvate kinase muscle isozyme 2 (PKM2) and human glandular kallikrein 2 (HK2). The proliferation and differentiation of podocytes during fibrosis were observed by monitoring the expression of nephrin and myocardin. In vitro experiments, primary podocytes were extracted, cultured, and stimulated with lactate. Then the alterations during the process were observed. Finally, PKM2 expression was inhibited by intravenous infusion of the plasmid. The link between the expression of marker protein as well as differentiation protein in podocytes and renal interstitial fibrosis was analyzed.

RESULTS

During the process of renal interstitial fibrosis, phenotypic changes and enhanced expression of fibrosis and proliferation markers were found in fibroblasts. Meanwhile, in renal tubular epithelial cells, increased expression of key enzymes of glycolysis, the level of glycolysis as well as lactate metabolites cooperatively led to hypoxic and acidic environment, eventually inhibiting the proliferation and differentiation of podocytes and aggravating fibrosis. When the level of glycolysis in renal tubular epithelial cells was reduced, the number and function of podocytes were partially restored, and renal interstitial fibrosis was alleviated.

CONCLUSIONS

During renal interstitial fibrosis, glycolysis of renal tubular epithelial cell was increased, leading to the recodification of energy metabolism. This process affected the number and function of podocytes and aggravated renal interstitial fibrosis.