This paper proposes an hybrid method based on both a spectral traffic analysis and a robust controller / observer for anomaly estimation inside UAV networks. This method is based on both Lyapunov ...Krasovskii functional and dynamic behavior of Transmission Control Protocol (TCP) and User Datagram Protocol (UDP). The proposed hybrid method considers, as a preliminary step, a statistical signature of the traffic exchanged in the network. By looking up this signature in a bank of signatures, it is possible to characterize the different anomalies that can be observed in UAV networks. Consequently, the different signatures that we can process, based on the different types of intrusion we generate in the network, are used to select the accurate model for robust control estimation. This selection is conducted by choosing a specific controller / observer among a dedicated bank of models. The first statistical signature extraction of the analyzed traffic is done with a multi-fractal analysis. This solution based on wavelet analysis has been selected because it offers a wide spectral characterization of the entire traffic process. The wavelet-based analysis methodology has been widely used for the last decade for Internet traffic characterization but this is the first time that this tool has been used on a UAV ad hoc network traffic. Moreover, several research studies on network anomaly estimation have been carried out using automatic control techniques. These studies provide methods for designing both observer and command laws dedicated to time delay problems while estimating the anomaly or intrusion in the system. As a first result, the spectral analysis tool has provided clearly distinguishable signatures between the traffics with and without anomalies. Then, the designed controller / observer system has been successfully applied to some relevant practical problems such as ad hoc networks for aerial vehicles and its effectiveness is illustrated by using real traffic traces including Distributed Denial of Service (DDoS) attacks. Our first results show promising perspectives for Intrusion Detection System (IDS) in a fleet of UAVs. Indeed, different types of anomaly have been considered and they are all accurately detected by the intrusion detection process we propose in this paper.
In this paper, we consider two challenging issues in reference-based super-resolution (RefSR) for smartphone, (i) how to choose a proper reference image, and (ii) how to learn RefSR in a ...self-supervised manner. Particularly, we propose a novel self-supervised learning approach for real-world RefSR from observations at dual and multiple camera zooms. Firstly, considering the popularity of multiple cameras in modern smartphones, the more zoomed (telephoto) image can be naturally leveraged as the reference to guide the super-resolution (SR) of the lesser zoomed (ultra-wide) image, which gives us a chance to learn a deep network that performs SR from the dual zoomed observations (DZSR). Secondly, for self-supervised learning of DZSR, we take the telephoto image instead of an additional high-resolution image as the supervision information, and select a center patch from it as the reference to super-resolve the corresponding ultra-wide image patch. To mitigate the effect of the misalignment between ultra-wide low-resolution (LR) patch and telephoto ground-truth (GT) image during training, we first adopt patch-based optical flow alignment to obtain the warped LR, then further design an auxiliary-LR to guide the deforming of the warped LR features. To generate visually pleasing results, we present local overlapped sliced Wasserstein loss to better represent the perceptual difference between GT and output in the feature space. During testing, DZSR can be directly deployed to super-solve the whole ultra-wide image with the reference of the telephoto image. In addition, we further take multiple zoomed observations to explore self-supervised RefSR, and present a progressive fusion scheme for the effective utilization of reference images. Experiments show that our methods achieve better quantitative and qualitative performance against state-of-the-arts. The code and pre-trained models will be publicly available.
Farnesene, as an important sesquiterpene isoprenoid polymer of acetyl-CoA, is a renewable feedstock for diesel fuel, polymers, and cosmetics. It has been widely applied in agriculture, medicine, ...energy, and other fields. In recent years, farnesene biosynthesis is considered a green and economical approach because of its mild reaction conditions, low environmental pollution, and sustainability. Metabolic engineering has been widely applied to construct cell factories for farnesene biosynthesis. In this paper, the research progress, common problems, and strategies of farnesene biosynthesis are reviewed. They are mainly described from the perspectives of the current status of farnesene biosynthesis in different host cells, optimization of the metabolic pathway for farnesene biosynthesis, and key enzymes for farnesene biosynthesis. Furthermore, the challenges and prospects for future farnesene biosynthesis are discussed.
Nonerythrocytic spectrin beta 1 (SPTBN1) is an important cytoskeletal protein that involves in normal cell growth and development via regulating TGFβ/Smad signaling pathway, and is aberrantly ...expressed in various cancer types. But, the exact role of SPTBN1 in pan-cancer is still unclear. This report aimed to display expression patterns and prognostic landscapes of SPTBN1 in human cancers, and further assess its prognostic/therapeutic value and immunological role in kidney renal carcinoma (KIRC) and uveal melanoma (UVM).
We firstly analyzed expression patterns and prognostic landscapes of SPTBN1 in human cancers using various databases and web-based tools. The relationships between SPTBN1 expression and survival/tumor immunity in KIRC and UVM were further investigated via R packages and TIMER 2.0 platform. The therapeutic roles of SPTBN1 in KIRC and UVM were also explored via R software. Following this, the prognostic value and cancer immunological role of SPTBN1 in KIRC and UVM were validated in our cancer patients and GEO database.
Overall, cancer tissue had a lower expression level of SPTBN1 frequently in pan-cancer, compared with those in adjacent nontumor one. SPTBN1 expression often showed a different effect on survival in pan-cancer; upregulation of SPTBN1 was protective to the survival of KIRC individuals, which was contrary from what was found in UVM patients. In KIRC, there were significant negative associations between SPTBN1 expression and pro-tumor immune cell infiltration, including Treg cell, Th2 cell, monocyte and M2-macrophage, and expression of immune modulator genes, such as tumor necrosis factor superfamily member 9 (TNFSF9); while, in UVM, these correlations exhibited opposite patterns. The following survival and expression correlation analysis in our cancer cohorts and GEO database confirmed these previous findings. Moreover, we also found that SPTBN1 was potentially involved in the resistance of immunotherapy in KIRC, and the enhance of anti-cancer targeted treatment in UVM.
The current study presented compelling evidence that SPTBN1 might be a novel prognostic and therapy-related biomarker in KIRC and UVM, shedding new light on anti-cancer strategy.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With the continuous development of medical image informatics technology, more and more high-throughput quantitative data could be extracted from digital medical images, which has resulted in a new ...kind of omics-Radiomics. In recent years, in addition to genomics, proteomics and metabolomics, radiomic has attracted the interest of more and more researchers. Compared to other omics, radiomics can be perfectly integrated with clinical data, even with the pathology and molecular biomarker, so that the study can be closer to the clinical reality and more revealing of the tumor development. Mass data will also be generated in this process. Machine learning, due to its own characteristics, has a unique advantage in processing massive radiomic data. By analyzing mass amounts of data with strong clinical relevance, people can construct models that more accurately reflect tumor development and progression, thereby providing the possibility of personalized and sequential treatment of patients. As one of the cancer types whose treatment and diagnosis rely on imaging examination, radiomics has a very broad application prospect in head and neck cancers (HNC). Until now, there have been some notable results in HNC. In this review, we will introduce the concepts and workflow of radiomics and machine learning and their current applications in head and neck cancers, as well as the directions and applications of artificial intelligence in the treatment and diagnosis of HNC.
A fibrous meat substitute prepared from soybean protein and Coprinus comatus powder for manufacture of fermented sausages.
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•Fibrous-like meat substitutes were manufactured from ...soybean protein and edible fungus.•The fermentation process of meat substitutes improved sensory attributes.•The aroma profile of meat substitute fermented sausages were identified by HS-SPME-GC–MS.•The volatile flavor compounds were systemically compared and analyzed.•The MS-NCFS evaded the undesired off-flavors from 1-octen-3-ol.
Plant-based meat substitutes are emerging as healthy, balanced, and sustainable non-animal alternatives to alleviate stress from the increased demand for meat products. In this study, fibrous-like extrudates acting as meat substitutes were manufactured from soybean protein and Coprinus comatus by thermos-extrusion and fermentation processing improved the meat-like physicochemical and textural properties, taste, and flavor of products. The fermentation period was greatly shortened than animal meat-based fermented sausage. For comparison reasons, the aroma profiles of meat substitute fermented sausages (MS-FS), fermented sausages without curing (MS-NCFS) and natural fermented sausages (MS-NFS) were systemically analyzed by headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS). A total of 156 volatile compounds were identified, and the curing and fermenting process contributed to the increased contents of volatile compounds greatly. Moreover, the MS-FS without curing evaded undesired off-flavors like grass and bean flavor from 1-octen-3-ol. Sensory evaluation was also showed higher scores for MS-FS than other processing.
Background Despite multiple attempts have been made to develop risk stratification within high-risk neuroblastoma (NB) patients (age of diagnosis greater than or equal to 18 month-old with metastatic ...NB), the definition of "ultra high-risk NB" is still lack of consensus, and indicators for identifying this subgroup are still unclear. This study aimed to develop a nomogram based on easy-to-obtain blood-derived biofactors for identifying ultra high-risk NB patients with highest risk of death within 3 or 5 years. Methods One hundred sixty-seven NB patients who treated at Sun Yat-sen University Cancer Center between 2015 and 2023 were recruited and clustered randomly into training and validation cohorts (116 and 51 cases, respectively). Univariate and multivariate Cox analysis were performed in training set to screen independent prognostic indicators for constructing nomogram model of predicting 1-, 3- and 5-year overall survival (OS). The discrimination power of the nomogram in training and validation sets were assessed by concordance index (C-index) and calibration plot. Based on the risk score obtained from nomogram model, the prognostic accuracy of 1-, 3- and 5-year OS rates in training and validation cohorts were further evaluated using the area under receiver operating characteristic (ROC) curves (AUC). Results Through univariate and multivariate Cox analysis, independent prognostic indicators, including serum lactate dehydrogenase (LDH) and albumin (ALB), were identified in training set, and used to establish a nomogram model. The model showed good discrimination power with C-index in training cohort being 0.706 (95%CI: 0.633--0.788). According to the cut-point calculated based on the established nomogram, patients with a nomogram score > 34 points could be stratified to ultra high-risk NB subgroup, and this subgroup had poorer OS than those in non-ultra one (p < 0.001). AUC values of ROC curves for 3- and 5-year OS rates in the training set were 0.758 and 0.756, respectively. Moreover, based on the cut-point score (34 points) developed in training set, The model also showed good discrimination power with C-index of 0.773 (95%CI: 0.664--0.897) and powerful prognostic accuracy of AUC for 3- and 5-year OS rates being 0.825 and 0.826, respectively, in validation cohort. Conclusions We developed a simple-to-use nomogram based on common laboratory indicators to identify the subgroup of ultra high-risk NB before treatment, providing these children even from developing countries or regions access to intensified multimodal treatments earlier and thus improving their long-term outcome. Keywords: Ultra high-risk neuroblastoma, Nomogram, Pretreatment, Lactate dehydrogenase, Albumin, Overall survival, Developing country/region
To evaluate the efficacy and safety of dust mite subcutaneous immunotherapy (SCIT) in monosensitized and polysensitized children with allergic rhinitis (AR).
Prospective cohort study.
Tertiary ...referral center.
One hundred thirty children were enrolled and categorized into 2 groups: monosensitized to only dust mites and polysensitized to at least 1 additional allergen beyond dust mites. All patients received SCIT targeting dust mites for 3 years, followed by a 5-year monitoring period. The Total Nasal Symptom Score (TNSS), Symptom and Medication Score (SMS), Visual Analogue Scale (VAS), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) were assessed before SCIT (T0); at 1 (T1) and 2 (T2) years of SCIT; immediately after SCIT (T3); and 2 years post-SCIT (T5). Safety was assessed based on adverse events (AEs).
Fifty-one monosensitized and 50 polysensitized children completed the study. At T3, 47 monosensitized and 46 polysensitized children were effectively treated, with no significant between-group difference in efficacy (P > .05). The TNSS, SMS, VAS scores, and RQLQ score were significantly lower at T1, T2, T3, and T5 than at T0 in both groups (P < .05). The differences in the TNSS, SMS, VAS score, and RQLQ score between the 2 groups were nonsignificant at T0, T1, T2, and T3 (P > .05), but significant at T5 (P < .05). No serious AEs were reported.
Monosensitized and polysensitized children exhibited similar beneficial efficacy and safety after 3 years of dust mite SCIT. Monosensitized children derived more benefits 2 years after discontinuation.
•The review provides comprehensive understanding of the clinical features, imaging and pathology for ACC, to arrive at a policy for proper diagnosis, preoperative evaluation, and therapeutic ...management.•We present the current treatment options for ACC with the expectation of elucidating the therapeutic procedures for different stages including R/M ACC.•Exploration of tumor microenvironment and its interaction with the neural niche is needed to identify and develop new targeted therapies, improve and promote the immune response, achieve personalized treatment, and move toward precision medicine in treatment of ACC.
Adenoid cystic carcinoma (ACC) is a rare malignant tumor derived mainly from the salivary glands, representing approximately 1% of all headandneck carcinomasand 10% of all salivary gland neoplasms. ACC displays a paradoxical behavioral combination of an indolent growth pattern but an aggressive progression, with local recurrence and distant metastasis. The propensity of ACC of the head and neck (ACCHN) for perineural invasion and its anatomical location, especially if it extends to the nasal cavity and paranasal sinuses, facilitates tumor involvement in the surrounding structures, such as the orbit, pterygopalatine fossa, Meckel'scave, and cavernous sinus, which can lead to skull base involvement and intracranial extension. Despite advances in molecular mechanisms and diagnostic imaging, ACC treatment remainschallenging due to the lack ofconsensuson treatment patterns. In this review, we aimed toprovideanupdatedinsight intothe understanding of ACCHN by focusing on clinical behavior, imaging diagnosis, pathological features, and therapeutic strategies. We reviewed the molecular mechanisms, especially in ACCHN with perineural invasion, and elaborated on treatment options, including chemotherapy, targeted therapies, and immunotherapy, to establish a comprehensive understanding of ACC to arrive at a policy for proper diagnosis, preoperative evaluation, and therapeutic strategies.
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