No axillary surgical treatment for lymph node-negative patients after ultra-sonography [NAUTILUS]: protocol of a prospective randomized clinical trial

Abstract Background Following sentinel lymph node biopsy (SLNB), the axillary recurrence rate is very low although SLNB has a false-negative rate of 5–10%. In the ACOSOG Z0011 trial, non-sentinel positive-lymph nodes were found in more than 20% of the axillary dissection group; the SLNB only group did not have a higher axillary recurrence rate. These findings raised questions about the direct therapeutic effect of the SLNB. SLNB has post-surgical complications including lymphedema. Considering advances in imaging modalities and adjuvant therapies, the role of SLNB in early breast cancer needs to be re-evaluated. Methods The NAUTILUS trial is a prospective multicenter randomized controlled trial involving clinical stage T1–2 and N0 breast cancer patients receiving breast-conserving surgery. Axillary ultrasound is mandatory before surgery with predefined imaging criteria for inclusion. Ultrasound-guided core needle biopsy or needle aspiration of a suspicious node is allowed. Patients will be randomized (1:1) into the no-SLNB (test) and SLNB (control) groups. A total of 1734 patients are needed, considering a 5% non-inferiority margin, 5% significance level, 80% statistical power, and 10% dropout rate. All patients in the two groups will receive ipsilateral whole-breast radiation according to a predefined protocol. The primary endpoint of this trial is the 5-year invasive disease-free survival. The secondary endpoints are overall survival, distant metastasis-free survival, axillary recurrence rate, and quality of life of the patients. Discussion This trial will provide important evidence on the oncological safety of the omission of SLNB for early breast cancer patients undergoing breast-conserving surgery and receiving whole-breast radiation, especially when the axillary lymph node is not suspicious during preoperative axillary ultrasound. Trial registration ClinicalTrials.gov, NCT04303715 . Registered on March 11, 2020

Hypomorphic Mutations in TONSL Cause SPONASTRIME Dysplasia

SPONASTRIME dysplasia is a rare, recessive skeletal dysplasia characterized by short stature, facial dysmorphism, and aberrant radiographic findings of the spine and long bone metaphysis. No causative genetic alterations for SPONASTRIME dysplasia have yet been determined. Using whole-exome sequencing (WES), we identified bi-allelic TONSL mutations in 10 of 13 individuals with SPONASTRIME dysplasia. TONSL is a multi-domain scaffold protein that interacts with DNA replication and repair factors and which plays critical roles in resistance to replication stress and the maintenance of genome integrity. We show here that cellular defects in dermal fibroblasts from affected individuals are complemented by the expression of wild-type TONSL. In addition, in vitro cell-based as-says and in silico analyses of TONSL structure support the pathogenicity of those TONSL variants. Intriguingly, a knock-in (KI) Tonsl mouse model leads to embryonic lethality, implying the physiological importance of TONSL. Overall, these findings indicate that genetic variants resulting in reduced function of TONSL cause SPONASTRIME dysplasia and highlight the importance of TONSL in embryonic development and postnatal growth.Peer reviewe

Scalable Algorithms for Maximizing Spatiotemporal Range Sum and Range Sum Change in Spatiotemporal Datasets

In this paper, we introduce the three-dimensional Maximum Range-Sum (3D MaxRS) problem and the Maximum Spatiotemporal Range-Sum Change (MaxStRSC) problem. The 3D MaxRS problem tries to find the 3D range where the sum of weights across all objects inside is maximized, and the MaxStRSC problem tries to find the spatiotemporal range where the sum of weights across all objects inside is maximally increased. The goal of this paper is to provide efficient methods for data analysts to find interesting spatiotemporal regions in a large historical spatiotemporal dataset by addressing two problems. We provide a mathematical explanation for each problem and propose several algorithms for them. Existing methods tried to find the optimal region over two-dimensional datasets or to monitor a burst region over two-dimensional data streams. The majority of them cannot directly solve our problems. Although some existing methods can be used or modified to solve the 3D MaxRS problems, they have limited scalability. In addition, none of them can be used to solve the MaxStRS-RC problem (a type of MaxStRSC problem). Finally, we study the performance of the proposed algorithms experimentally. The experimental results show that the proposed algorithms are scalable and much more efficient than existing methods

Comparative Analysis of the Cell Fates of Induced Schwann Cells from Subcutaneous Fat Tissue and Naïve Schwann Cells in the Sciatic Nerve Injury Model

Purpose. The fate and function of the induced Schwann cells (iSCs) like cells from adipose tissue have not been critically evaluated in vivo after transplantation. The objective of this study is to compare the fate of iSCs with naïve SCs (nSCs) after transplantation into the lesion sites of sciatic nerve, respectively. Methods. Adipose-derived stem cells from eGFP-expressing transgenic rat’s subcutaneous fat were induced to iSCs in vitro. iSCs were injected to the sciatic nerve lesion area after crush injury and the cells fate was comparatively analyzed with that of nSCs from the same rat. Results. At 12 weeks after transplantation, nSCs were detected only in the restricted area of cell transplantation site but iSCs were widely distributed all over the sciatic nerve. Based on double fluorescence observations, both iSCs and naïve ones were colocalized with P0-expressing myelin sheath, outbound by laminin-expressing basal membrane, and terminated at contactin-associated protein-expressing doublets. However, some of iSCs were also differentiated to the fibrocyte/fibroblast-like cells. In the histological analysis of repaired sciatic nerves, axon density was higher in iSC-received group than in the nSCs group and normal sciatic nerve. Conclusion. iSCs induced from subcutaneous fat tissues have higher engraftment and migration capacity than nSCs

DNN-SAM: Split-and-Merge DNN Execution for Real-Time Object Detection

As real-time object detection systems, such as autonomous cars, need to process input images acquired from multiple cameras, they face significant challenges in delivering accurate and timely inferences often based on machine learning (ML). To meet these challenges, we want to provide different levels of object detection accuracy and timeliness to different portions within each input image with different criticality levels. Specifically, we develop DNN-SAM, a dynamic Split-And-Merge Deep Neural Network (DNN) execution and scheduling framework, that enables seamless split-and-merge DNN execution for unmodified DNN models. Instead of processing an entire input image once in a full DNN model, DNN-SAM first splits a DNN inference task into two smaller sub-tasks-a mandatory sub-task dedicated for a safety-critical (cropped) portion of each image and an optional sub-task for processing a down-scaled image-then executes them independently, and finally merges their results into a complete inference. To achieve DNN-SAM's timely and accurate detection of objects in each image, we also develop two scheduling algorithms that prioritize sub-tasks according to their criticality levels and adaptively adjust the scale of the input image to meet the timing constraints while minimizing the response time of mandatory sub-tasks or maximizing the accuracy of optional sub-tasks. We have implemented and evaluated DNN-SAM on a representative ML framework. Our evaluation shows DNN-SAM to improve detection accuracy in the safety-critical region by 2.0-3.7× and lower average inference latency by 4.8-9.7× over existing approaches without violating any timing constraints. © 2022 IEEE

Stretchable Triboelectric Multimodal Tactile Interface Simultaneously Recognizing Various Dynamic Body Motions

Human cutaneous tactile receptors are deformable, and can distinguish touch, strain, relative moving distance, and relative moving velocity. In addition, the tactile potential is self-activated when external stimulation is exerted and the potential is transmitted to the nerve system, resembling the wake-up function in electronic devices. In this study, we mimic such characteristics of the human tactile receptors. We designed a stretchable triboelectric nanogenerator (TENG) for the stimuli-responsive potential generator. The TENG device has a multilayer structure independently recognizing lateral strain by the sliding mode, touch by the contact mode, the relative moving distance, and the relative moving velocity. In addition, the device design allows simultaneous sensing of strain and touch without signal interference. The self-triggered potentials generated by various body motions such as touching, joint bending, and the combinations turn on a sleeping microcontroller unit (MCU) and are used as the distinct motion signals. This study demonstrates a wearable low-power remote tactile interface that controls the 3D movements of a mobile device (drone) by the body motions.11Nsciescopu

Nanoscale-nMOSFET junction design: Quantum transport approach

Employing quantum transport solver, we have demonstrated the impact of junction proximity and abruptness on device performance. To entail the discrete dopant effect accurately, impurity scattering has been introduced in non-perturbative way. The electrostatic metrics and effective current have been evaluated for practical dimensions and technologically relevant junctions. A simple guideline for junction design has been concluded

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells

Background Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. Results We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS G12D, were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS G12D mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS G12D and low risk score. Conclusions Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies