Real-time scheduling for energy harvesting sensor nodes

Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First scheduling.

Taxonomy-based relaxation of query answering in relational databases

Traditional information search in which queries are posed against a known and rigid schema over a structured database is shifting toward a Web scenario in which exposed schemas are vague or absent and data come from heterogeneous sources. In this framework, query answering cannot be precise and needs to be relaxed, with the goal of matching user requests with accessible data. In this paper, we propose a logical model and a class of abstract query languages as a foundation for querying relational data sets with vague schemas. Our approach relies on the availability of taxonomies, that is, simple classifications of terms arranged in a hierarchical structure. The model is a natural extension of the relational model in which data domains are organized in hierarchies, according to different levels of generalization between terms. We first propose a conservative extension of the relational algebra for this model in which special operators allow the specification of relaxed queries over vaguely structured information. We also study equivalence and rewriting properties of the algebra that can be used for query optimization. We then illustrate a logic-based query language that can provide a basis for expressing relaxed queries in a declarative way. We finally investigate the expressive power of the proposed query languages and the independence of the taxonomy in this context.     

Correlation of Immunological and Histopathological Features with Gene Expression-Based Classifiers in Colon Cancer Patients

The purpose of this study was to evaluate the association between four distinct histopathological features: (1) tumor infiltrating lymphocytes, (2) mucinous differentiation, (3) tumor-stroma ratio, plus (4) tumor budding and two gene expression-based classifiers—(1) consensus molecular subtypes (CMS) plus (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin sections of the most invasive part of the primary tumor in 218 stage II and III colon cancer patients from two independent cohorts (AMC-AJCC-90 and AC-ICAM). RNA-based CMS and CRIS assignments were independently obtained for all patients. Contingency tables were constructed and a χ2 test was used to test for statistical significance. Odds ratios with 95% confidence intervals were calculated. The presence of tumor infiltrating lymphocytes and a mucinous phenotype (>50% mucinous surface area) were strongly correlated with CMS1 (p < 0.001 and p = 0.008) and CRIS-A (p = 0.006 and p < 0.001). The presence of mucus (≥ 10%) was associated with CMS3: mucus was present in 64.1% of all CMS3 tumors (p < 0.001). Although a clear association between tumor-stroma ratio and CMS4 was established in this study (p = 0.006), still 32 out of 61 (52.5%) CMS4 tumors were scored as stroma-low, indicating that CMS4 tumors cannot be identified solely based on stromal content. Higher budding counts were seen in CMS4 and CRIS-B tumors (p = 0.045 and p = 0.046). No other associations of the measured parameters were seen for any of the other CRIS subtypes. Our analysis revealed clear associations between histopathologic features and CMS or CRIS subtypes. However, identification of distinct molecular subtypes solely based on histopathology proved to be infeasible. Combining both molecular and morphologic features could potentially improve patient stratification.     

Malignant Transformation of Giant Cell Tumour of Bone: A Review of Literature and the Experience of a Referral Centre

Giant cell tumour of bone (GCTB) is a benign, locally aggressive primary bone neoplasm that represents 5% of all bone tumours. The principal treatment approach is surgery. Although generally GCTB is considered only a locally aggressive disease, it can metastasise, and lung metastases occur in 1–9% of patients. To date, only the use of denosumab has been approved as medical treatment for GCTB. Even more rarely, GCTB undergoes sarcomatous transformation into a malignant tumour (4% of all GCTB), but history of this malignant transformation is unclear and unpredictable. Considering the rarity of the event, the data in the literature are few. In this review, we summarise published data of GCTB malignant transformation and we analyse three cases of malignant transformation of GCTB, evaluating histopathology, genetics, and radiological aspects. Despite the rarity of this event, we conclude that a strict follow up is recommended to detect early malignant transformation.     

Methylome Profiling in Fabry Disease in Clinical Practice: A Proof of Concept

Anderson–Fabry disease (FD) is an X-linked disease caused by a functional deficit of the α-galactosidase A enzyme. FD diagnosis relies on the clinical manifestations and research of GLA gene mutations. However, because of the lack of a clear genotype/phenotype correlation, FD diagnosis can be challenging. Recently, several studies have highlighted the importance of investigating DNA methylation patterns for confirming the correct diagnosis of different rare Mendelian diseases, but to date, no such studies have been reported for FD. Thus, in the present investigation, we analyzed for the first time the genome-wide methylation profile of a well-characterized cohort of patients with Fabry disease. We profiled the methylation status of about 850,000 CpG sites in 5 FD patients, all carrying the same mutation in the GLA gene (exon 6 c.901C>G) and presenting comparable low levels of α-Gal A activity. We found that, although the whole methylome profile did not discriminate the FD group from the unaffected one, several genes were significantly differentially methylated in Fabry patients. Thus, we provide here a proof of concept, to be tested in patients with different mutations and in a larger cohort, that the methylation state of specific genes can potentially identify Fabry patients and possibly predict organ involvement and disease evolution.     

Tolerance,Adaptation, and Cell Response Elicited by Micromonospora sp. Facing Tellurite Toxicity: A Biological and Physical-Chemical Characterization

The intense use of tellurium (Te) in industrial applications, along with the improper disposal of Te-derivatives, is causing their accumulation in the environment, where oxyanion tellurite (TeO₃²⁻) is the most soluble, bioavailable, and toxic Te-species. On the other hand, tellurium is a rare metalloid element whose natural supply will end shortly with possible economic and technological effects. Thus, Te-containing waste represents the source from which Te should be recycled and recovered. Among the explored strategies, the microbial TeO₃²⁻ biotransformation into less toxic Te-species is the most appropriate concerning the circular economy. Actinomycetes are ideal candidates in environmental biotechnology. However, their exploration in TeO₃²⁻ biotransformation is scarce due to limited knowledge regarding oxyanion microbial processing. Here, this gap was filled by investigating the cell tolerance, adaptation, and response to TeO₃²⁻ of a Micromonospora strain isolated from a metal(loid)-rich environment. To this aim, an integrated biological, physical-chemical, and statistical approach combining physiological and biochemical assays with confocal or scanning electron (SEM) microscopy and Fourier-transform infrared spectroscopy in attenuated total reflectance mode (ATR-FTIR) was designed. Micromonospora cells exposed to TeO₃²⁻ under different physiological states revealed a series of striking cell responses, such as cell morphology changes, extracellular polymeric substance production, cell membrane damages and modifications, oxidative stress burst, protein aggregation and phosphorylation, and superoxide dismutase induction. These results highlight this Micromonospora strain as an asset for biotechnological purposes.     

The Neuroprotective Potentiality of Flavonoids on Alzheimer’s Disease

Alzheimer’s disease (AD), due to its spread, has become a global health priority, and is characterized by senile dementia and progressive disability. The main cause of AD and other neurodegenerations (Huntington, Parkinson, Amyotrophic Lateral Sclerosis) are aggregated protein accumulation and oxidative damage. Recent research on secondary metabolites of plants such as polyphenols demonstrated that they may slow the progression of AD. The flavonoids’ mechanism of action in AD involved the inhibition of acetylcholinesterase, butyrylcholinesterase, Tau protein aggregation, β-secretase, oxidative stress, inflammation, and apoptosis through modulation of signaling pathways which are implicated in cognitive and neuroprotective functions, such as ERK, PI3-kinase/Akt, NFKB, MAPKs, and endogenous antioxidant enzymatic systems. This review focuses on flavonoids and their role in AD, in terms of therapeutic potentiality for human health, antioxidant potential, and specific AD molecular targets.     

Towards Precision Medicine for Osteoarthritis: Focus on the Synovial Fluid Proteome

Osteoarthritis (OA) is a joint degenerative disease that most affects old age. The study of proteomics in synovial fluid (SF) has the task of providing additional elements to diagnose and predict the progress of OA. This review aims to identify the most significant biomarkers in the study of OA and to stimulate their routine use. Some of the major components of the ECM, such as proteoglycan aggrecan and decorin, were found considerably reduced in OA. Some biomarkers have proved useful for staging the temporality of OA: Periostin was found to be increased in early OA, while CRTA1 and MMPs were found to be increased in late OA. In its natural attempt at tissue regeneration, Collagen III was found to be increased in early OA while decreased in late OA. Some molecules studied in other areas, such as ZHX3 (oncological marker), LYVE1, and VEGF (lymph and angiogenesis markers), also have been found to be altered in OA. It also has been recorded that alteration of the hormonal pathway, using a dosage of PPAR-γ and RETN, can influence the evolution of OA. IL-1, one of the most investigated biomarkers in OA-SF, is not as reliable as a target of OA in recent studies. The study of biomarkers in SF appears to be, in combination with the clinical and radiological aspects, an additional weapon to address the diagnosis and staging of OA. Therefore, it can guide us more appropriately towards the indication of arthroplasty in patients with OA.