Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution Characteristics and Prognostic Value of Immune Infiltration in Oligometastatic Breast Cancer

Background To assess the distribution characteristics and the prognostic value of immune infiltration in female oligometastatic breast cancer patients. Methods We retrospectively analyzed the clinicopathological data of oligometastatic breast cancer (OMBC) patients diagnosed between June 2000 and January 2020. Immune markers were quantified by immunohistochemistry on FFPE tissues in paired normal breast tissues, primary breast cancers and oligometastatic lesions. Survival analyses were performed using the Kaplan-Meier curves and Cox-proportional hazards model. Results A total of 95 female OMBC patients visited Sun Yat-sen University Cancer Center between June 2000 and January 2020, and 33 of them had matched normal breast tissues, primary cancers and oligometastatic lesions and were reviewed in immune infiltration analysis. CD8 of primary tumors had a higher expression than that in matched normal tissues. The expressions of CD8 and FOXP3 were higher in the primary sites than that in the oligometastatic lesions. CD3, CD4 and CD8 were significantly lower in the intratumoral regions than that in the peritumoral regions both in primary and oligometastatic lesions. Notably, the high percentage of CD3 in the intratumoral oligometastatic lesions predicted the longer PFS and OS, and higher CD4 in the same lesions also predicted a better OS. There was obviously positive correlation between CD4/CD3 and Ki-67 in primary cancers and negative correlation between CD4/CD3 and ER in oligometastatic sites. Conclusion We explored immune distribution and evolution in time and space in OMBC to provide new understandings for biological behaviors of this disease and further divided patients in different prognosis.
Design of a Database-Driven Nonlinear Generalized Predictive Controller

This paper addresses a regulation problem of non-linear systems via database-driven nonlinear generalized predictive controller without model information. In industrial processes, lots of controlled systems with unknown time-delay and strong nonlinearity, are difficult to be handled in terms of control performance. Advanced controllers are considered to be established to deal with those nonlinear systems. In several design methods, advanced controllers are designed based on model information. However, it is time- and cost-consuming to identify the model of controlled systems, and requires regular maintenance to maintain acceptable performance. The database-driven approach has been attracted attentions to tackle those issues without model information. The controller can be designed and tuned only based on data, which is the main feature of this approach. Besides, the database-driven approach can deal with strong nonlinear systems. Additionally, the Generalized Predictive Control (GPC) is one of predictive controllers and widely applied in industrial processes. The GPC controller is developed based on multi-step prediction, therefore, it is effective to those systems subject to unknown or time-delay. As a result, a nonlinear GPC controller in the proposed scheme inherits the advantage of GPC, and is also tuned by the database-driven approach. The effectiveness and benefits of the proposed scheme are demonstrated through a numerical simulation and a comparative study.
Editorial: Environmental DNA Innovations for Conservation

Environmental DNA (eDNA) analysis refers to the collection of bulk environmental samples such as water, sediment, or air, and studying the genetic remnants that organisms have shed into their environment to gain information about species presence. The earliest efforts to learn about organisms from genetic analysis of environmental samples occurred in the field of microbiology, where many focal organisms cannot be cultured under laboratory conditions (e.g., Ogram et al., 1987). A major innovation occurred in the early 2000s when paleoecologists began to apply similar genetic methods to study ancient communities of extinct multicellular organisms (e.g., Willerslev et al., 2003). The contemporary application of eDNA analysis was realized when Ficetola et al. (2008) demonstrated that informative genetic material was not only retrievable from ancient sediments that had been preserved under dark, cold, and stabilizing conditions, but from contemporary environmental samples as well. Since then, eDNA analysis has burgeoned into a powerful tool for ecological research and management. This Research Topic represents a collection of studies demonstrating the continued innovation of eDNA methods and applications, especially in the field of conservation. Several distinct trends emerge across this curated collection that make clear that innovation comes in many different forms, which we have envisioned as key “bases” of innovation (Figure 1). We believe that keeping these different basesor possibilitiesof innovation in mind will help researchers identify opportunities for continued innovation in the future, and we describe each base in more detail in the sections below as we introduce the contributions to our Research Topic, Environmental DNA Innovations for Conservation.
Energy Efficient, Hamming Code Technique for Error Detection/Correction Using In-Memory Computation

In this work, for the first time, we have proposed and implemented the In-memory computation (IMC) of Hamming code for redundant bit generation(encoding) and syndrome calculation(decoding) with two different design techniques 2 Bit X-or based Hamming code Design (2BxHCD) and Bit Specific X-or based Hamming code Design (BSxHCD) with the 8T static random-access memory (SRAM), in the standard 90nm CMOS technology. The key objective of the proposed techniques is reducing the latency and power consumption to increase the overall performance of the system. The latency of the proposed 2BxHCD and BSxHCD is 1.41× and 1.26× lower than the conventional design, respectively. In comparison to conventional design, power consumption is 6.52× and 3.07× less in proposed 2BxHCD and BSxHCD, respectively. Furthermore, energy consumption which is an important figure of merit (FoM) is 9.45× and 4.08× lower than the conventional Hamming code encoder design.
Prediction of Maize Phenotypic Traits With Genomic and Environmental Predictors Using Gradient Boosting Frameworks

The development of crop varieties with stable performance in future environmental conditions represents a critical challenge in the context of climate change. Environmental data collected at the field level, such as soil and climatic information, can be relevant to improve predictive ability in genomic prediction models by describing more precisely genotype-by-environment interactions, which represent a key component of the phenotypic response for complex crop agronomic traits. Modern predictive modeling approaches can efficiently handle various data types and are able to capture complex nonlinear relationships in large datasets. In particular, machine learning techniques have gained substantial interest in recent years. Here we examined the predictive ability of machine learning-based models for two phenotypic traits in maize using data collected by the Maize Genomes to Fields (G2F) Initiative. The data we analyzed consisted of multi-environment trials (METs) dispersed across the United States and Canada from 2014 to 2017. An assortment of soil- and weather-related variables was derived and used in prediction models alongside genotypic data. Linear random effects models were compared to a linear regularized regression method (elastic net) and to two nonlinear gradient boosting methods based on decision tree algorithms (XGBoost, LightGBM). These models were evaluated under four prediction problems: (1) tested and new genotypes in a new year; (2) only unobserved genotypes in a new year; (3) tested and new genotypes in a new site; (4) only unobserved genotypes in a new site. Accuracy in forecasting grain yield performance of new genotypes in a new year was improved by up to 20% over the baseline model by including environmental predictors with gradient boosting methods. For plant height, an enhancement of predictive ability could neither be observed by using machine learning-based methods nor by using detailed environmental information. An investigation of key environmental factors using gradient boosting frameworks also revealed that temperature at flowering stage, frequency and amount of water received during the vegetative and grain filling stage, and soil organic matter content appeared as important predictors for grain yield in our panel of environments.
Neurofilament Light Chain Protein Is a Predictive Biomarker for Stroke After Surgical Repair for Acute Type A Aortic Dissection

Background: Although great progress has been made in surgery and perioperative care, stroke is still a fatal complication of acute type A aortic dissection (ATAAD). Serum biomarkers may help assess brain damage and predict patient's prognosis. Methods: From March, 2019 to January, 2020, a total of 88 patients underwent surgical treatment at the Department of Cardiovascular Surgery of Beijing Anzhen Hospital, China, and were enrolled in this study. Patients were divided into two groups according to whether they had suffered a stroke after the operation. Blood samples were collected at 8 time points within 3 days after surgery to determine the level of S100β, neuron-specific enolase (NSE) and neurofilament light chain protein (NFL). Receiver operating characteristic curves (ROC) were established to explore the biomarker predictive value in stroke. The area under the curve (AUC) was used to quantify the ROC curve. Results: The patient average age was 48.1 ± 11.0 years old and 70 (79.6%) patients were male. Fifteen (17.0%) patients suffered stroke after surgery. The NFL levels of patients in the stroke group at 12 and 24 h after surgery were significantly higher than those in the non-stroke group (all P < 0.001). However, the NSE and S100β levels did not differ significantly at any time point between the two groups. The predictive value of NFL was the highest at 12 and 24 h after surgery, and the AUC was 0.834 (95% CI, 0.723–0.951, P < 0.001) and 0.748 (95% CI, 0.603–0.894, P = 0.004), respectively. Its sensitivity and specificity at 12 h were 86.7 and 71.6%, respectively. The NFL cutoff value for the diagnosis of stroke at 12 h after surgery was 16.042 ng/ml. Conclusions: This study suggests that NFL is an early and sensitive serum marker for predicting post-operative neurological prognosis of ATAAD patients. Further studies, including large-scale prospective clinical trials, are necessary to test whether the NFL can be used as a biomarker for clinical decision-making.
Human Platelet Lysate Maintains Stemness of Umbilical Cord-Derived Mesenchymal Stromal Cells and Promote Lung Repair in Rat Bronchopulmonary Dysplasia

Mesenchymal stromal cells (MSCs) show potential for treating preclinical models of newborn bronchopulmonary dysplasia (BPD), but studies of their therapeutic effectiveness have had mixed results, in part due to the use of different media supplements for MSCs expansion in vitro. The current study sought to identify an optimal culture supplement of umbilical cord-derived MSCs (UC-MSCs) for BPD therapy. In this study, we found that UC-MSCs cultured with human platelet lysate (hPL-UCMSCs) were maintained a small size from Passage 1 (P1) to P10, while UC-MSCs cultured with fetal bovine serum (FBS-UCMSCs) became wide and flat. Furthermore, hPL was associated with lower levels of senescence in UC-MSCs during in vitro expansion compared with FBS, as indicated by the results of β-galactosidase staining and measures of senescence-related genes (CDKN2A, CDKN1A, and mTOR). In addition, hPL enhanced the proliferation and cell viability of the UC-MSCs and reduced their doubling time in vitro. Compared with FBS-UCMSCs, hPL-UCMSCs have a greater potential to differentiate into osteocytes and chondrocytes. Moreover, using hPL resulted in greater expression of Nestin and specific paracrine factors (VEGF, TGF-β1, FGF2, IL-8, and IL-6) in UC-MSCs compared to using FBS. Critically, we also found that hPL-UCMSCs are more effective than FBS-UCMSCs for the treatment of BPD in a rat model, with hPL leading to improvements in survival rate, lung architecture and fibrosis, and lung capillary density. Finally, qPCR of rat lung mRNA demonstrated that hPL-UCMSCs had lower expression levels of inflammatory factors (TNF-α and IL-1β) and a key chemokine (MCP-1) at postnatal day 10, and there was significant reduction of CD68+ macrophages in lung tissue after hPL-UCMSCs transplantation. Altogether, our findings suggest that hPL is an optimal culture supplement for UC-MSCs expansion in vitro, and that hPL-UCMSCs promote lung repair in rat BPD disease.
Serotonin Signals Modulate Mushroom Body Output Neurons for Sustaining Water-Reward Long-Term Memory in Drosophila

Memory consolidation is a time-dependent process through which an unstable learned experience is transformed into a stable long-term memory; however, the circuit and molecular mechanisms underlying this process are poorly understood. The Drosophila mushroom body (MB) is a huge brain neuropil that plays a crucial role in olfactory memory. The MB neurons can be generally classified into three subsets: γ, αβ, and α′β′. Here, we report that water-reward long-term memory (wLTM) consolidation requires activity from α′β′-related mushroom body output neurons (MBONs) in a specific time window. wLTM consolidation requires neurotransmission in MBON-γ3β′1 during the 0–2 h period after training, and neurotransmission in MBON-α′2 is required during the 2–4 h period after training. Moreover, neurotransmission in MBON-α′1α′3 is required during the 0–4 h period after training. Intriguingly, blocking neurotransmission during consolidation or inhibiting serotonin biosynthesis in serotoninergic dorsal paired medial (DPM) neurons also disrupted the wLTM, suggesting that wLTM consolidation requires serotonin signals from DPM neurons. The GFP Reconstitution Across Synaptic Partners (GRASP) data showed the connectivity between DPM neurons and MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3, and RNAi-mediated silencing of serotonin receptors in MBON-γ3β′1, MBON-α′2, or MBON-α′1α′3 disrupted wLTM. Taken together, our results suggest that serotonin released from DPM neurons modulates neuronal activity in MBON-γ3β′1, MBON-α′2, and MBON-α′1α′3 at specific time windows, which is critical for the consolidation of wLTM in Drosophila.
Beyond Personalist Virtue Ethics: Transcendental Anthropology and its Implications for Interpersonal Communication

There is a need of deeper understanding of what human beings are for facing adequately global challenges. The aim of this article is to point to the possible contributions that transcendental anthropology would represent for complementing and expanding the valuable, but still incomplete solutions put forward by personalist virtue ethics to face these challenges. In particular, the question of the moral motivation and the complex relations between virtue and freedom are addressed, taking as a starting point the understanding of the uniqueness of the personal act-of-being and the transcendentality of human freedom, which is in dialogue with human nature and society, but ultimately not subdued to none of them. Some implications of the transcendental anthropology in the field of interpersonal communication ethics are put forward.
Effects of Temperature and Additives on NO x Emission From Combustion of Fast-Growing Grass

Fast-growing grass, as a popular renewable energy, is low in sulfur content, so NO x is the major pollutant during its combustion. To study the emission characteristics of NO x and obtain the data of controlling NO x emission, the effects of combustion temperature as well as the additive type and mass fraction were investigated on the emission characteristics of NO x from the combustion of fast-growing grass. Results revealed that the first peak for NO x emission from this combustion gradually increases with an increase in temperature. Moreover, the additives were found to dramatically impact the amount of NO x emission and its representative peak. The optimal additives and their optimal mass fractions were determined at various specific temperatures to reduce NO x emission. At combustion temperatures of 600, 700, 750, 800, and 850°C, the optimal conditions to limit NO x emissions were 5% SiO2, 3% Al2O3, 3% Ca(OH)2, 15% Al2O3, and 3% SiO2 (or 3% Al2O3), respectively; the corresponding emission peaks decreased by 43.59, 44.21, 47.99, 24.18, and 30.60% (or 31.51%), with denitration rates of 63.28, 50.34, 57.44, 27.05, and 27.34% (or 27.28%), respectively.
Dictionary of renewable resources.

This work provides a comprehensive compilation of all renewable plant and animal resources and the substances derived from these. Featuring over 500 separate entries, it includes detailed descriptions of resources such as Jasmine, Waxes, Jojoba and Peanut Oil. Many entries are also accompanied by detailed illustrations. Standard technologies of isolation and derivatization of each resource are discussed, and their major fields of application, both classical and modern, are evaluated with particular regard to their economic aspects and future developments. Recommendations for further reading and production figures for each resource, when available, are also featured. The book provides a source for a broad spectrum of users, including industrial chemists, agricultural scientists, natural products chemists, ecologists, and the pharmaceutical, cosmetic and perfume industry.
Warthy-Basaloid Squamous Cell Carcinoma of Penile – Case Report

Objective The aim of the study was to present a case of penile squamous cell carcinoma and immunohistochemical identification and evaluation of E-cadherin and β-catenin expression. Methods We are presenting a 70-year old man with a variant of penile squamous cell carcinoma with mixed warty and basaloid features. After diagnosis, the patient underwent partial penectomy. Samples taken from the material after surgery were subjected to basic histological staining and immunohistochemical identification of E-cadherin and β-catenin. A Real-time PCR study was conducted to investigate the expression of E-cadherin and β-catenin. Results Routine histopathological examinations revealed the characteristic features of warty-basaloid squamous cell carcinoma. In the case studied, a positive immunohistochemical reaction was observed for E-cadherin and β-catenin. QRT-PCR analysis showed a statistically significant decrease in E-cadherin expression in tumor samples compared to healthy tissue. In contrast, expression of the gene encoding β-catenin was slightly higher in tumor samples compared to normal tissue. Conclusions The reduced level of the complex of adhesive elements, E-cadherin-β-catenin, disturbs cell differentiation, promotes a more invasive phenotype-stromal infiltration and the formation of distant metastases. In the described case of the penile tumor, a decrease in E-cadherin expression was noted, which could be related to the occurrence of neoplastic infiltration of the spongy body space. In summary, E-cadherin and β-catenin expression and the immunoreactivity of these proteins are expressed at different levels in tumor cells and in penile interstitial cells. Regulation of expression during various physiological and pathophysiological processes indicates a potentially important role of E-cadherin and β-catenin in cell proliferation and adhesion.
A Lumped, Resonant Switched Capacitor Converter

This paper considers the output short-circuit protection of a Series-Parallel (S-P), switched capacitor converter for interfacing high-power PV farms and/or MV DC micro-grids. A so-called active interrupter can be used to isolate the converter from the fault; however, the inductor associated with this interrupter can used as the resonant inductor for the circuit, offering potential savings in inductor size/weight/cost and losses. A number of alternative S-P topologies were devised, which were compared against the existing circuit. Results from a scaled hardware prototype are presented, which highlights a number of practical issues related to circuit parasitcs.
The Integration of the Pre-Treatment Neutrophil-to-Lymphocyte Ratio in the Eighth Edition of the AJCC Staging System for Nasopharynx Cancer

Objective The present study aimed to evaluate the role of integrating the pretreatment neutrophil-to-lymphocyte ratio (NLR) into the eighth edition of the AJCC staging system for nasopharynx cancer in an endemic region. Methods Between May 2007 and December 2012, a total of 713 cases with NPC were retrospectively analyzed. The separation ability in terms of overall survival (OS), local failure-free survival (LFFS), distant metastasis-free survival (DMFS), and failure-free survival (FFS) was evaluated. The discriminatory ability was assessed using Harrell’s concordance index (c-index). Recursive partitioning analysis (RPA) was conducted and incorporated with pretreatment NLR. Results When integrated with NLR, the separate and discriminatory abilities for N classifications were improved in terms of OS and DMFS, but not for T categories. By using Recursive partitioning analysis, five subgroups were generated. Compared with the overall stage, the integration of NLR could not enhance the separate and discriminatory abilities. However, patients in the RPA 4 group gained significant benefits in terms of OS (HR 0.390 (95%CI 0.212-0.716), P = 0.002) and FFS (HR 0.548 (95%CI 0.314-0.958), P = 0.032) from the additional adjuvant chemotherapy after concurrent chemoradiotherapy. Conclusion The integration of NLR into the 8th edition of the AJCC staging system could enhance the separation and discriminatory abilities for N classifications, but not for T categories. In addition, patients in the RPA 4 group could benefit from the addition of adjuvant chemotherapy to concurrent chemoradiotherapy.
Laparoscopic Scene Reconstruction Based on Multiscale Feature Patch Tracking Method

In minimally invasive laparoscopic surgery, doctors use laparoscopic images to guide surgical operations. During the operation, the visual field is narrow and the operation space is limited, which is not conducive to the observation and operation for doctors. Comprehensive intra-abdominal scene information exerts an enormous function on understanding anatomical structure for doctors, compensating errors in surgical navigation, and displaying in augmented reality surgery. In this paper, a laparoscopic reconstruction method based on multiscale feature patch tracking is proposed. The new method uses a multiscale Kernel Correlation Filter (KCF) to track feature patches in Simultaneous Localization and Mapping (SLAM) framework, which is called MKCF-SLAM. The proposed method is applied in stereoscopic laparoscopy, which can reconstruct laparoscopic scene under the conditions of less texture, high reflection, and target scale changes. The new method is validated on a public invivo data set. Compared with feature-based SLAM methods and our previous work, the proposed method can get better and more stable work in some special difficult environments. The results suggest that the proposed method can reconstruct the laparoscopic scene accurately and robustly.