Paraneoplastic Syndromes in Patients with Keratinocyte Skin Cancer

A variety of well-characterized cutaneous paraneoplastic syndromes (PNS) are diagnosed during internal malignancies; however, the spectrum of keratinocyte skin neoplasms (KSC) related to PNS is still obscure. The aim of the present review is to compile and evaluate the literature data on PNS associated with a keratinocyte skin neoplasm (KSC). Employing Pubmed, MEDLINE was searched for KSC-associated PNS reports. Forty relevant entries were assembled, reporting a total of 41 PNS cases associated with a KSC (34 male). No review paper compiling this topic was found. Six distinct PNS entities were identified, and malignancy associated hypercalcemia (MAH; 78%), anemia (10%) and Bazex syndrome (5%) were the most frequently reported among them. 85% of the PNS were reported in association with SCC, 10% with BCC, and the rest with adnexal tumors. The median age of the patients at the time of PNS diagnosis was 58 years (range: five–83 years). In most cases the PNS was diagnosed either concurrently or after the KSC diagnosis. KSC predisposing conditions, as scars (22%) or hidradenitis suppurativa (20%), were reported in >70% of the PNS cases. Most PNS resolved after KSC treatment. In conclusion, PNS of a rather limited spectrum of entities are reported in association with KSC. They also seem to be rare, possibly reflecting a limited capacity of KSC to provoke overt PNS.

Hierarchical Multi-User Detection for Highly Overloaded Uplink Grant-Free NOMA

Grant-Free Non Orthogonal Multiple Access (NOMA) offers promising solutions to realize uplink (UL) massive Machine Type Communication (mMTC) using limited spectrum resources, while reducing signalling overhead. Because of the sparse, sporadic activities exhibited by the user equipments (UE), the active user detection (AUD) problem is often formulated as a compressive sensing problem. In line of that, greedy sparse recovery algorithms are spearheading the development of compressed sensing based multi-user detectors (CS-MUD). However, for a given number of resources, the performance of CS-MUD algorithms are fundamentally limited at higher overloading of NOMA. To circumvent this issue, in this work, we propose a two-stage hierarchical multi-user detection framework, where the UEs are randomly assigned to some pre-defined clusters. The active UEs split their data transmission frame into two phases. In the first phase an UE uses the sinusoidal spreading sequence (SS) of its cluster. In the second phase the UE uses its own unique random SS. At phase 1 of detection, the active clusters are detected, and a reduced sensing matrix is constructed. This matrix is used in Phase 2 to recover the active UE indices using some sparse recovery algorithm. Numerical investigations validate the efficacy of the proposed algorithm in highly overloaded scenarios.

Hierarchical Multi-User Detection for Highly Overloaded Uplink Grant-Free NOMA

Grant-Free Non Orthogonal Multiple Access (NOMA) offers promising solutions to realize uplink (UL) massive Machine Type Communication (mMTC) using limited spectrum resources, while reducing signalling overhead. Because of the sparse, sporadic activities exhibited by the user equipments (UE), the active user detection (AUD) problem is often formulated as a compressive sensing problem. In line of that, greedy sparse recovery algorithms are spearheading the development of compressed sensing based multi-user detectors (CS-MUD). However, for a given number of resources, the performance of CS-MUD algorithms are fundamentally limited at higher overloading of NOMA. To circumvent this issue, in this work, we propose a two-stage hierarchical multi-user detection framework, where the UEs are randomly assigned to some pre-defined clusters. The active UEs split their data transmission frame into two phases. In the first phase an UE uses the sinusoidal spreading sequence (SS) of its cluster. In the second phase the UE uses its own unique random SS. At phase 1 of detection, the active clusters are detected, and a reduced sensing matrix is constructed. This matrix is used in Phase 2 to recover the active UE indices using some sparse recovery algorithm. Numerical investigations validate the efficacy of the proposed algorithm in highly overloaded scenarios.

Karyotype Diversity, Mode, and Tempo of the Chromosomal Evolution of Attina (Formicidae: Myrmicinae: Attini): Is There an Upper Limit to Chromosome Number?

Ants are an important insect group that exhibits considerable diversity in chromosome numbers. Some species show only one chromosome, as in the males of the Australian bulldog ant Myrmecia croslandi, while some have as many as 60 chromosomes, as in the males of the giant Neotropical ant Dinoponera lucida. Fungus-growing ants are a diverse group in the Neotropical ant fauna, engaged in a symbiotic relationship with a basidiomycete fungus, and are widely distributed from Nearctic to Neotropical regions. Despite their importance, new chromosome counts are scarcely reported, and the marked variation in chromosome number across species has been poorly studied under phylogenetic and genome evolutionary contexts. Here, we present the results of the cytogenetic examination of fungus-farming ants and compile the cytogenetic characteristics and genome size of the species studied to date to draw insights regarding the evolutionary paths of karyotype changes and diversity. These data are coupled with a fossil-calibrated phylogenetic tree to discuss the mode and tempo of chromosomal shifting, considering whether there is an upper limit for chromosome number and genome size in ants, using fungus-farming ants as a model study. We recognize that karyotypes are generally quite variable across fungus-farming ant phylogeny, mostly between genera, and are more numerically conservative within genera. A low chromosome number, between 10 and 12 chromosomes, seems to present a notable long-term evolutionary stasis (intermediate evolutionary stasis) in fungus-farming ants. All the genome size values were inside a limited spectrum below 1 pg. Eventual departures in genome size occurred with regard to the mean of 0.38 pg, indicating that there is a genome, and likely a chromosome, number upper limit.

Isoeugenol Affects Expression Pattern of Conidial Hydrophobin Gene RodA and Transcriptional Regulators MedA and SomA Responsible for Adherence and Biofilm Formation in Aspergillus fumigatus

Aspergillus fumigatus is one of the major pathogenic fungal species, causing life-threatening infections. Due to a limited spectrum of available antifungals, exploration of new drug targets as well as potential antifungal molecules has become pertinent. Rodlet layer plays an important role in adherence of fungal conidia to hydrophobic cell surfaces in host, which also leads to A. fumigatus biofilm formation, contributing factor to fungal pathogenicity. From decades, natural sources have been known for the development of new active molecules. The present study investigates effect of isoeugenol on genes responsible for hydrophobins (RodA), adhesion as well as biofilm formation (MedA and SomA) of A. fumigatus. Minimum inhibitory concentrations (MIC and IC50) of isoeugenol against A. fumigatus were determined using broth microdilution assay. The IC50 results showed reduced hydrophobicity and biofilm formation after treatment with the compound and electron micrograph data corroborated these findings. The qRT-PCR showed a significant downregulation of genes RodA, MedA, SomA and pksP involved in hydrophobicity and biofilm formation. SwissADME studies potentiated drug-like propensity for isoeugenol which formed four hydrogen bonds with low binding energy (-4.54 Kcal/mol) at the catalytic site of RodA protein studied via AutoDock4. Hence, the findings conclude that isoeugenol inhibits conidial hydrophobicity and biofilm formation of A. fumigatus and further investigations are warranted in this direction.

Transitioning from Oxime to the Next Potential Organophosphorus Poisoning Therapy Using Enzymes

For years, organophosphorus poisoning has been a major concern of health problems throughout the world. An estimated 200,000 acute pesticide poisoning deaths occur each year, many in developing countries. Apart from the agricultural pesticide poisoning, terrorists have used these organophosphorus compounds to attack civilian populations in some countries. Recent misuses of sarin in the Syrian conflict had been reported in 2018. Since the 1950s, the therapy to overcome this health problem is to utilize a reactivator to reactivate the inhibited acetylcholinesterase by these organophosphorus compounds. However, many questions remain unanswered regarding the efficacy and toxicity of this reactivator. Pralidoxime, MMB-4, TMB-4, obidoxime, and HI-6 are the examples of the established oximes, yet they are of insufficient effectiveness in some poisonings and only a limited spectrum of the different nerve agents and pesticides are being covered. Alternatively, an option in the treatment of organophosphorus poisoning that has been explored is through the use of enzyme therapy. Organophosphorus hydrolases are a group of enzymes that look promising for detoxifying organophosphorus compounds and have recently gained much interest. These enzymes have demonstrated remarkable protective and antidotal value against some different organophosphorus compounds in vivo in animal models. Apart from that, enzyme treatments have also been applied for decontamination purposes. In this review, the restrictions and obstacles in the therapeutic development of oximes, along with the new strategies to overcome the problems, are discussed. The emerging interest in enzyme treatment with its advantages and disadvantages is described as well.

Intelligent Dynamic Spectrum Resource Management Based on Sensing Data in Space-Time and Frequency Domain

Edge computing offers a promising paradigm for implementing the industrial Internet of things (IIoT) by offloading intensive computing tasks from resource constrained machine type devices to powerful edge servers. However, efficient spectrum resource management is required to meet the quality of service requirements of various applications, taking into account the limited spectrum resources, batteries, and the characteristics of available spectrum fluctuations. Therefore, this study proposes intelligent dynamic spectrum resource management consisting of learning engines that select optimal backup channels based on history data, reasoning engines that infer idle channels based on backup channel lists, and transmission parameter optimization engines based genetic algorithm using interference analysis in time, space and frequency domains. The performance of the proposed intelligent dynamic spectrum resource management was evaluated in terms of the spectrum efficiency, number of spectrum handoff, latency, energy consumption, and link maintenance probability according to the backup channel selection technique and the number of IoT devices and the use of transmission parameters optimized for each traffic environment. The results demonstrate that the proposed method is superior to existing spectrum resource management functions.

A Survey on the AI and Spectrum Management for Cache-Enabled Internet of Things in Smart Cities

In this paper, we provide a comprehensive survey for the artificial intelligence and spectrum management, which are used for cache-enabled Internet of Things (IoT) in smart cities. In smart cities, there emerge a lot of new applications such as data collection and communication, environment monitoring, and real-time processing, which cannot be supported by the conventional wireless transmission techniques. Hence, some new wireless transmission techniques should be developed to support the emerging applications in smart cities. In this survey, we focus on the artificial intelligence, spectrum management, and caching techniques, where the interference arises due to the limited spectrum resources. In particular, we first review the current research status of these new techniques and, then, give some challenges on the system design. We further provide several feasible solutions on these challenges, in order to implement the IoT networks in smart cities. Finally, we conclude the work in the part of conclusions and give some discussions on the future works.

A de novo SEMA6B variant in a Chinese patient with progressive myoclonic epilepsy-11 and review of the literature

Progressive myoclonic epilepsy is a group of neurodegenerative diseases with complex clinical and genetic heterogeneity, which is associated with spontaneous or action-induced myoclonus and progressive neurodegeneration. Since 2020, 4 families with progressive myoclonic epilepsy-11 [OMIM#618876] have been reported with a very limited spectrum of SEMA6B pathogenic variants. In our study, whole-exome sequencing was used in a proband from a nonconsanguineous Chinese family presenting with growth retardation and recurrent atonic seizures. A deletion mutation (c.1960_1978del, p.Leu654Argfs*25) in the last exon of SEMA6B was detected, which is a de Novo variant and pathogenic. The new genetic evidence we reported here strengthened the gene-disease relationship, and the gene curation level between SEMA6B and progressive myoclonic epilepsy-11 became “strong” following the ClinGen SOP. Therefore, the results of this study broaden the mutation spectrum of SEMA6B in different ethnic groups and strengthen the gene-disease relationship between SEMA6B and progressive myoclonic epilepsy-11.

D2D Assisted Cellular Networks in Licensed and Unlicensed Spectrum: Matching-Iteration-Based Joint User Access and Resource Allocation

Device-to-Device (D2D) communications, which enable direct communication between nearby user devices over the licensed spectrum, have been considered a key technique to improve spectral efficiency and system throughput in cellular networks (CNs). However, the limited spectrum resources cannot be sufficient to support more cellular users (CUs) and D2D users to meet the growth of the traffic data in future wireless networks. Therefore, Long-Term Evolution-Unlicensed (LTE-U) and D2D-Unlicensed (D2D-U) technologies have been proposed to further enhance system capacity by extending the CUs and D2D users on the unlicensed spectrum for communications. In this paper, we consider an LTE network where the CUs and D2D users are allowed to share the unlicensed spectrum with Wi-Fi users. To maximize the sum rate of all users while guaranteeing each user’s quality of service (QoS), we jointly consider user access and resource allocation. To tackle the formulated problem, we propose a matching-iteration-based joint user access and resource allocation algorithm. Simulation results show that the proposed algorithm can significantly improve system throughput compared to the other benchmark algorithms.