LatentPCN: latent space-constrained point cloud network for reconstruction of 3D patient-specific bone surface models from calibrated biplanar X-ray images.

PURPOSE: Accurate three-dimensional (3D) models play crucial roles in computer assisted planning and interventions. MR or CT images are frequently used to derive 3D models but have the disadvantages that they are expensive or involving ionizing radiation (e.g., CT acquisition). An alternative method based on calibrated 2D biplanar X-ray images is highly desired. METHODS: A point cloud network, referred as LatentPCN, is developed for reconstruction of 3D surface models from calibrated biplanar X-ray images. LatentPCN consists of three components: an encoder, a predictor, and a decoder. During training, a latent space is learned to represent shape features. After training, LatentPCN maps sparse silhouettes generated from 2D images to a latent representation, which is taken as the input to the decoder to derive a 3D bone surface model. Additionally, LatentPCN allows for estimation of a patient-specific reconstruction uncertainty. RESULTS: We designed and conducted comprehensive experiments on datasets of 25 simulated cases and 10 cadaveric cases to evaluate the performance of LatentLCN. On these two datasets, the mean reconstruction errors achieved by LatentLCN were 0.83 mm and 0.92 mm, respectively. A correlation between large reconstruction errors and high uncertainty in the reconstruction results was observed. CONCLUSION: LatentPCN can reconstruct patient-specific 3D surface models from calibrated 2D biplanar X-ray images with high accuracy and uncertainty estimation. The sub-millimeter reconstruction accuracy on cadaveric cases demonstrates its potential for surgical navigation applications.

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy.

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and robot-assisted needle insertion. Based on a high-precision optical tracking system, novel methods for ultrasound probe and robot hand-eye calibration are proposed. Specifically, we first fix optically trackable markers to the ultrasound probe and to the robot, respectively. We then design a five-wire phantom to calibrate the ultrasound probe. Finally, an effective method taking advantage of steady movement of the robot but without an additional calibration frame or the need to solve the AX=XB equation is proposed for hand-eye calibration. After calibrations, our system allows for in situ definition of target lesions and aiming trajectories from intra-operatively acquired ultrasound images in order to align the robot for precise needle biopsy. Comprehensive experiments were conducted to evaluate accuracy of different components of our system as well as the overall system accuracy. Experiment results demonstrated the efficacy of the proposed methods.

A Novel Point Set Registration-Based Hand-Eye Calibration Method for Robot-Assisted Surgery.

Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand-eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm systems. In this paper, we propose an effective hand-eye calibration method, namely registration-based hand-eye calibration (RHC), which estimates the calibration transformation via point set registration without the need to solve the AX=XB equation. Our hand-eye calibration method consists of tool-tip pivot calibrations in two-coordinate systems, in addition to paired-point matching, where the point pairs are generated via the steady movement of the robot arm in space. After calibration, our system allows for robot-assisted, image-guided pedicle screw insertion. Comprehensive experiments are conducted to verify the efficacy of the proposed hand-eye calibration method. A mean distance deviation of 0.70 mm and a mean angular deviation of 0.68° are achieved by our system when the proposed hand-eye calibration method is used. Further experiments on drilling trajectories are conducted on plastic vertebrae as well as pig vertebrae. A mean distance deviation of 1.01 mm and a mean angular deviation of 1.11° are observed when the drilled trajectories are compared with the planned trajectories on the pig vertebrae.

An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international multicenter cohorts.

BACKGROUND: Gastric cancer (GC) is a major health problem worldwide, with high prevalence and mortality. The present GC staging system provides inadequate prognostic information and does not reflect the chemotherapy benefit of GC. METHODS: Two hundred fifty-five patients who underwent surgical resection were enrolled in our study (training cohort = 212, internal validation cohort = 43). Nine clinicopathologic features were obtained to construct an support vector machine (SVM) model. The cohorts from 4 domestic centres and The Cancer Genome Atlas (TCGA) were used for external validation. RESULTS: In the training cohort, the AUCs were 0.773 (95% CI 0.708-0.838) for 5-year overall survival (OS) and 0.751 (95% CI 0.683-0.820) for 5-year disease-free survival (DFS); in the domestic validation cohort, the AUCs were 0.852 (95% CI 0.810-0.894) and 0.837 (95% CI 0.792-0.882), respectively. The model performed better than the TNM staging system according to the receiver operator characteristic(ROC) curve. GC patients were significantly divided into low, moderate and high risk based on the SVM. High-risk TNM stage Ⅱ and Ⅲ patients were more likely to benefit from adjuvant chemotherapy than low-risk patients. CONCLUSIONS: The SVM-based model may be used to predict OS and DFS in GC patients and the benefit of adjuvant chemotherapy in TNM stage Ⅱ and Ⅲ GC patients.

Contrast-Enhanced Computed Tomography-Based Radiogenomics Analysis for Predicting Prognosis in Gastric Cancer.

Objective: The aim of this study is to identify prognostic imaging biomarkers and create a radiogenomics nomogram to predict overall survival (OS) in gastric cancer (GC). Material: RNA sequencing data from 407 patients with GC and contrast-enhanced computed tomography (CECT) imaging data from 46 patients obtained from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA) were utilized to identify radiogenomics biomarkers. A total of 392 patients with CECT images from the Nanfang Hospital database were obtained to create and validate a radiogenomics nomogram based on the biomarkers. Methods: The prognostic imaging features that correlated with the prognostic gene modules (selected by weighted gene coexpression network analysis) were identified as imaging biomarkers. A nomogram that integrated the radiomics score and clinicopathological factors was created and validated in the Nanfang Hospital database. Nomogram discrimination, calibration, and clinical usefulness were evaluated. Results: Three prognostic imaging biomarkers were identified and had a strong correlation with four prognostic gene modules (P < 0.05, FDR < 0.05). The radiogenomics nomogram (AUC = 0.838) resulted in better performance of the survival prediction than that of the TNM staging system (AUC = 0.765, P = 0.011; Delong et al.). In addition, the radiogenomics nomogram exhibited good discrimination, calibration, and clinical usefulness in both the training and validation cohorts. Conclusions: The novel prognostic radiogenomics nomogram that was constructed achieved excellent correlation with prognosis in both the training and validation cohort of Nanfang Hospital patients with GC. It is anticipated that this work may assist in clinical preferential treatment decisions and promote the process of precision theranostics in the future.

A Projector-Based Augmented Reality Navigation System for Computer-Assisted Surgery.

In the medical field, guidance to follow the surgical plan is crucial. Image overlay projection is a solution to link the surgical plan with the patient. It realizes augmented reality (AR) by projecting computer-generated image on the surface of the target through a projector, which can visualize additional information to the scene. By overlaying anatomical information or surgical plans on the surgery area, projection helps to enhance the surgeon's understanding of the anatomical structure, and intuitively visualizes the surgical target and key structures of the operation, and avoid the surgeon's sight diversion between monitor and patient. However, it still remains a challenge to project the surgical navigation information on the target precisely and efficiently. In this study, we propose a projector-based surgical navigation system. Through the gray code-based calibration method, the projector can be calibrated with a camera and then be integrated with an optical spatial locator, so that the navigation information of the operation can be accurately projected onto the target area. We validated the projection accuracy of the system through back projection, with average projection error of 3.37 pixels in x direction and 1.51 pixels in y direction, and model projection with an average position error of 1.03 ± 0.43 mm, and carried out puncture experiments using the system with correct rate of 99%, and qualitatively analyzed the system's performance through the questionnaire. The results demonstrate the efficacy of our proposed AR system.

Reversing Bacterial Resistance to Gold Nanoparticles by Size Modulation.

One major frustration in developing antibiotics is that bacteria can quickly develop resistance that would require an entirely new cycle of research and clinical testing to overcome. Although plenty of bactericidal nanomaterials have been developed against increasingly severe superbugs, few reports have studied the resistance to these nanomaterials. Herein, we show that antibacterial 4,6-diamino-2-pyrimidine thiol (DAPT)-capped gold nanoparticles (AuDAPTs) can induce a 16-fold increased minimum inhibitory concentration (MIC) of E. coli only after very long term exposure (183 days), without developing cross-resistance to commercialized antibiotics. Strikingly, we recovered the bactericidal activities of AuDAPTs to the resistant strain by tuning the sizes of AuDAPTs without employing new chemicals. Such slow, easy-to-handle resistance induced by AuDAPTs is unprecedented compared to traditional antibiotics or other nanomaterials. In addition to the novel antibacterial activities and biocompatibilities, our approach will accelerate the development of gold nanomaterial-based therapeutics against multi-drug-resistant (MDR) bacterial infections.

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation, transcriptional regulation, post-transcriptional regulation and other aspects, thus participating in various biological processes such as cell proliferation, differentiation and apoptosis. As a new nova of anti-tumor therapy, immunotherapy has been shown to be effective in many tumors of which PD-1/PD-L1 monoclonal antibodies has been proofed to increase overall survival rate in advanced gastric cancer (GC). Microsatellite instability (MSI) was known as a biomarker of response to PD-1/PD-L1 monoclonal antibodies therapy. The aim of this study was to identify lncRNAs signatures able to classify MSI status and create a predictive model associated with MSI for GC patients. METHODS: Using the data of Stomach adenocarcinoma from The Cancer Genome Atlas (TCGA), we developed and validated a lncRNAs model for automatic MSI classification using a machine learning technology - support vector machine (SVM). The C-index was adopted to evaluate its accuracy. The prognostic values of overall survival (OS) and disease-free survival (DFS) were also assessed in this model. RESULTS: Using the SVM, a lncRNAs model was established consisting of 16 lncRNA features. In the training cohort with 94 GC patients, accuracy was confirmed with AUC 0.976 (95% CI, 0.952 to 0.999). Veracity was also confirmed in the validation cohort (40 GC patients) with AUC 0.950 (0.889 to 0.999). High predicted score was correlated with better DFS in the patients with stage I-III and lower OS with stage I-IV. CONCLUSION: This study identify 16 LncRNAs signatures able to classify MSI status. The correlation between lncRNAs and MSI status indicates the potential roles of lncRNAs interacting in immunotherapy for GC patients. The pathway of these lncRNAs which might be a target in PD-1/PD-L1 immunotherapy are needed to be further study.

A high-fat, high-protein diet attenuates the negative impact of casein-induced chronic inflammation on testicular steroidogenesis and sperm parameters in adult mice.

The interaction between obesity and chronic inflammation has been studied. Diet-induced obesity or chronic inflammation could reduce the testicular functions of males. However, the mechanism underlying the reproductive effects of fattening foods in males with or without chronic inflammation still needs further discussion. This study was aimed to investigate the effects of high-fat, high-protein diet on testicular steroidogenesis and sperm parameters in adult mice under physiological and chronic inflammatory conditions. Because casein can trigger a non-infectious systemic inflammatory response, we used casein injection to induce chronic inflammation in male adult Kunming mice. Twenty-four mice were randomly and equally divided into four groups: (i) normal diet+saline (Control); (ii) normal diet+casein (ND+CS); (iii) high-fat, high-protein diet+saline (HFPD+SI); (iv) high-fat, high-protein diet+casein (HFPD+CS). After 8weeks, there was a significant increase in body weight for groups HFPD+SI and HFPD+CS and a decrease in group ND+CS compared with the control. The serum levels of tumor necrosis factor alpha (TNF-α), interleukin-10 (IL-10) and lipid profiles were increased markedly in groups ND+CS, HFPD+SI and HFPD+CS compared with the control. A remarkable reduction of serum adiponectin level occurred in group HFPD+CS compared with group ND+CS. Sperm parameters (sperm count, viability and abnormality) were also adversely affected in groups ND+CS and HFPD+SI. Groups ND+CS and HFPD+SI showed severe pathological changes in testicular tissues. Semiquantitative RT-PCR, Western blot and immunohistochemical staining also showed significant reductions in both testicular mRNA and protein levels of steroidogenic acute regulatory (StAR) and cytochrome P450scc (CYP11A1) in groups HFPD+SI and HFPD+CS compared with the control, whereas testicular mRNA and protein levels of 3ß-hydroxysteroid dehydrogenase (3ß-HSD) in groups HFPD+SI and HFPD+CS significantly increased. The mRNA and protein levels of the StAR and 3ß-HSD in group HFPD+CS were both higher than those of in group ND+CS. These results indicated that Kunming male mice with high-fat, high-protein diet and casein injection for 8weeks can be used to establish a diet-induced obesity and chronic systemic inflammation. The sperm parameters in groups ND+CS and HFPD+SI decreased accompanied by pathological changes of testicular tissue. This resultant effect of reduced serum testosterone levels was associated with the overproduction of TNF-α and IL-10 and down-regulation of StAR and CYP11A1. Under the same casein-induced chronic inflammation condition, the mice with high-fat, high-protein diet had better testicular steroidogenesis activity and sperm parameters compared with the mice in normal diet, indicating that the mice with casein-induced inflammatory injury consuming a high-fat, high-protein diet gained weight normally, reduced serum adiponectin level and increased testosterone production by an upregulation of 3ß-HSD expression. High-fat, high-protein diet attenuated the negative impact of casein-induced chronic inflammation on testicular steroidogenesis and sperm parameters.

N-Heterocyclic molecule-capped gold nanoparticles as effective antibiotics against multi-drug resistant bacteria.

We demonstrate that N-heterocyclic molecule-capped gold nanoparticles (Au NPs) have broad-spectrum antibacterial activity. Optimized antibacterial activity can be achieved by using different initial molar ratios (1 : 1 and 10 : 1) of N-heterocyclic prodrugs and the precursor of Au NPs (HAuCl4). This work opens up new avenues for antibiotics based on Au NPs.

An Early-Stage Atherosclerosis Research Model Based on Microfluidics.

The arterial microenvironment plays a vital role in the pathology of atherosclerosis (AS). However, the interplay between the arterial microenvironment and atherogenesis remains unclear, partially due to the gap between cell culture and animal experiments. Addressing this problem, the present study reports a microfluidic AS model reconstituting early-stage AS. Physiological or AS-prone hemodynamic conditions are recapitulated on the model. The on-chip model recaptures the atherogenic responses of endothelial cells (ECs) in ways that the Petri dish could not. Significant cytotoxicity of a clinical anti-atherosclerotic drug probucol is discovered on the model, which does not appear on Petri dish but is supported by previous clinical evidence. Moreover, the anti-AS efficiency of platinum-nanoparticles (Pt-NPs) on the model shows excellent consistency with animal experiments. The early-stage AS model shows an excellent connection between Petri dish and animal experiments and highlights its promising role in bridging fundamental AS research, drug screening, and clinical trials.

Screening reactive oxygen species scavenging properties of platinum nanoparticles on a microfluidic chip.

Hyperglycemia, hyperlipidemia and inflammation are key risk factors for atherosclerosis and can lead to overproduction of reactive oxygen species (ROS), which plays a critical role in vascular endothelial dysfunction and subsequent progress of atherosclerosis. However, there is currently a lack of effective drugs that deal with ROS. Platinum nanoparticles (Pt-NPs) have proven to be promising antioxidant drugs in vitro and in vivo. To optimize the efficacy of Pt-NP based drugs, we synthesized and characterized the ROS scavenging properties of three kinds of small molecules that capped Pt-NPs (Pt-AMP-NPs, Pt-ATT-NPs, Pt-MI-NPs) on a blood vessel-mimicking microfluidic chip. The Pt-NPs showed superior superoxide dismutase (SOD)-like functions and can scavenge ROS and recover compromised cell-cell junctions under hyperglycemic, hyperlipidemic and proinflammatory conditions. Amongst these NPs, Pt-AMP-NPs showed the most superior antioxidant properties, suggesting its potency to serve as a novel drug to treat vascular diseases such as atherosclerosis. Our microfluidic chip, providing physiological hemodynamic conditions for the experiments, is potentially a promising tool for a wide range of biological research on the vascular system.

Antithrombotic functions of small molecule-capped gold nanoparticles.

Here we report the antithrombotic functions of pyrimidinethiol-capped gold nanoparticles (Au_DAPT NPs). They can prolong coagulation parameters when injected intravenously in normal mice. Applied in two typical thrombosis models, mice tail thrombosis and pulmonary thromboembolism, gold NPs can inhibit both thrombosis and improve the survival rates of mice tremendously, without increasing the bleeding risk. The anticoagulant mechanisms include inhibiting the platelet aggregation as well as interfering with thrombin and fibrin generation.

Tuning the composition of AuPt bimetallic nanoparticles for antibacterial application.

We show that bimetallic nanoparticles (NPs) of AuPt without any surface modification are potent antibiotic reagents, while pure Au NPs or pure Pt NPs display no antibiotic activities. The most potent antibacterial AuPt NPs happen to be the most effective catalysts for chemical transformations. The mechanism of antibiotic action includes the dissipation of membrane potential and the elevation of adenosine triphosphate (ATP) levels. These bimetallic NPs are unique in that they do not produce reactive oxygen species as most antibiotics do. Being non-toxic to human cells, these bimetallic noble NPs might open an entry to a new class of antibiotics.

A peptide-based nanofibrous hydrogel as a promising DNA nanovector for optimizing the efficacy of HIV vaccine.

This report shows that a nanovector composed of peptide-based nanofibrous hydrogel can condense DNA to result in strong immune responses against HIV. This nanovector can strongly activate both humoral and cellular immune responses to a balanced level rarely reported in previous studies, which is crucial for HIV prevention and therapy. In addition, this nanovector shows good biosafety in vitro and in vivo. Detailed characterizations show that the nanofibrous structure of the hydrogel is critical for the dramatically improved immune responses compared to existing materials. This peptide-based nanofibrous hydrogel shows great potential for efficacious HIV DNA vaccines and can be potentially used for delivering other vaccines and drugs.

Synergy of non-antibiotic drugs and pyrimidinethiol on gold nanoparticles against superbugs.

Co-presenting non-antibiotic drugs and pyrimidinethiol on gold nanoparticles (NPs) can generate broad-spectrum antibacterial and bactericidal activities against superbugs. Dimethylbiguanide (metformin), an anti-hyperglycemic drug, shows the best enhanced activity via increasing the ability to compromise bacterial cell walls. Synergistic effects are also reflected in the eradicating biofilm cells. Our findings suggest a large chemical space to develop new antibacterial materials to treat superbugs.

Multiple strategies to activate gold nanoparticles as antibiotics.

Widespread antibiotic resistance calls for new strategies. Nanotechnology provides a chance to overcome antibiotic resistance by multiple antibiotic mechanisms. This paper reviews the progress in activating gold nanoparticles with nonantibiotic or antibiotic molecules to combat bacterial resistance, analyzes the gap between experimental achievements and real clinical application, and suggests some potential directions in developing antibacterial nanodrugs.

Nanomaterials for ultrasensitive protein detection.

The advances of nanomaterials have provided exciting technologies and novel materials for protein detection, based on the unique properties associated with nanoscale phenomena such as plasmon resonance, catalysis and energy transfer. This article reviews a series of nanomaterials including nanoparticles, nanofibers, nanowires, and nanosheets, and evaluates their performances in the application for protein detection, focusing on approaches that realize ultrasensitive detection. Many of these nanomaterials were used to analyze clinically relevant protein biomarkers. Their detection in the picomolar, femtomolar or even zeptomolar regime has been realized, sometimes even with naked-eye readout. We summarize the detection methods and results according to materials and targets, review the current challenges, and discuss the solution in the context of technological integration such as combining nanomaterials with microfluidics, and classical analytical technologies.

Mussel-inspired anchoring for patterning cells using polydopamine.

This Article introduces a simple method of cell patterning, inspired by the mussel anchoring protein. Polydopamine (PDA), artificial polymers made from self-polymerization of dopamine (a molecule that resembles mussel-adhesive proteins), has recently been studied for its ability to make modifications on surfaces in aqueous solutions. We explored the interfacial interaction between PDA and poly(ethylene glycol) (PEG) using microcontact printing (µCP). We patterned PDA on several substrates such as glass, polystyrene, and poly(dimethylsiloxane) and realized spatially defined anchoring of mammalian cells as well as bacteria. We applied our system in investigating the relationship between areas of mammalian nuclei and that of the cells. The combination of PDA and PEG enables us to make cell patterns on common laboratorial materials in a mild and convenient fashion.