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Background and objectivesNeuropathic pain is partially refractory to currently available treatments. Although some studies have reported that apoptosis signal-regulating kinase 1 (ASK1) may inhibit chronic pain, the mechanisms underlying this process have not been fully elucidated.MethodsChronic constriction injury (CCI) of the rat sciatic nerve was used to establish a neuropathic pain model. Nociception was assessed using von Frey hair and Hargreaves’ methods. Western blot and immunofluorescence were used to detect the cell signaling pathway. BV2 cell line was cultured for in vitro evaluation.ResultsOur results indicated that spinal ASK1 was co-expressed with the microglia marker ionized calcium binding adaptor 1. Additionally, intrathecal administration of ASK1 inhibitor suppressed the activation of spinal microglia and attenuated CCI-induced neuropathic pain. The ASK1 inhibitor also decreased the levels of phosphorylated ASK1 (p-ASK1), p65, p38 mitogen-activated protein kinase (MAPK) and tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) messenger RNA in lipopolysaccharide-stimulated BV2 microglia cells. Intragastric administration of levo-corydalmine (l-CDL) significantly attenuated CCI-induced neuropathic pain and inhibited the expression of p-ASK1 in the spinal cord. l-CDL conspicuously suppressed the activation of spinal microglia in vitro and in vivo. Translocation of nuclearfactor-kappa B (NF-κB) and upregulation of p-p65, TNF-α, IL-1β were inhibited by l-CDL. Further, the analgesic effects of l-CDL were associated with reduced levels of phosphorylated protein kinase C (PKC γ), c-JunNH2-terminal kinase, and extracellular signal-regulated kinase.ConclusionsThis study showed that the expression of ASK1 in spinal microglia and ASK1 inhibitor suppressed microglia activation via suppression of p38 MAPK/NF-κB, which ultimately attenuated CCI-induced neuropathic pain. l-CDL also inhibited the ASK1-P38 MAPK/NF-κB axis to attenuate CCI-induced neuropathic pain.

Chromatinopathies can be defined as a class of neurodevelopmental disorders caused by mutations affecting proteins responsible for chromatin remodeling and transcriptional regulation. The resulting dysregulation of gene expression favors the onset of a series of clinical features such as developmental delay, intellectual disability, facial dysmorphism, and behavioral disturbances. Cornelia de Lange syndrome (CdLS) is a prime example of a chromatinopathy. It is caused by mutations affecting subunits or regulators of the cohesin complex, a multisubunit protein complex involved in various molecular mechanisms such as sister chromatid cohesion, transcriptional regulation and formation of topologically associated domains. However, disease-causing variants in non-cohesin genes with overlapping functions have also been described in association with CdLS. Notably, the majority of these genes had been previously found responsible for distinct neurodevelopmental disorders that also fall within the category of chromatinopathies and are frequently considered as differential diagnosis for CdLS. In this review, we provide a systematic overview of the current literature to summarize all mutations in non-cohesin genes identified in association with CdLS phenotypes and discuss about the interconnection of proteins belonging to the chromatinopathies network.

Behavioural phenotype and autism-related traits of 38 patients affected by Cornelia de Lange syndrome (CdLS) were assessed using a specific neuropsychiatric protocol. Subsequently,we search for possible genotype–phenotype correlations comparing individuals with NIPBL variants and patients with negative molecular results. Firstly results showed a higher percentage of subjects with normal intellectual quotient (IQ) and borderline IQ; adaptive skills were lower than expected for age in all participants. 39.5% of the sample presented with autism spectrum disorder (ASD), NIPBL mutated individuals demonstrated a worse trend in comparison with the clinical diagnosis group. non-truncating individuals displayed no ASD and better communication abilities than truncating individuals. Findings increase our awareness of the strengths and weaknesses points in CdLS individuals.

Vertebrates have two cohesin complexes that consist of Smc1, Smc3, Rad21/Scc1 and either SA1 or SA2, but their functional specificity is unclear. Mouse embryos lacking SA1 show developmental delay and die before birth. Comparison of the genome‐wide distribution of cohesin in wild‐type and SA1‐null cells reveals that SA1 is largely responsible for cohesin accumulation at promoters and at sites bound by the insulator protein CTCF. As a consequence, ablation of SA1 alters transcription of genes involved in biological processes related to Cornelia de Lange syndrome (CdLS), a genetic disorder linked to dysfunction of cohesin. We show that the presence of cohesin‐SA1 at the promoter of myc and of protocadherin genes positively regulates their expression, a task that cannot be assumed by cohesin‐SA2. Lack of SA1 also alters cohesin‐binding pattern along some gene clusters and leads to dysregulation of genes within. We hypothesize that impaired cohesin‐SA1 function in gene expression underlies the molecular aetiology of CdLS. Loss of the cohesin subunit SA1 causes developmental defects and transcriptional deregulation resembling familial cohesin dysfunction disorders such as CdLS. SA1‐containing complexes are enriched at insulator and promoter regions, suggesting gene expression control specifically by SA1‐, not SA2‐cohesin.

Purpose In cochlear implantation, thorough preoperative planning together with measurement of the cochlear duct length (CDL) assists in choosing the correct electrode length. For measuring the CDL, different techniques have been introduced in the past century along with the then available technology. A tablet-based software offers an easy and intuitive way to visualize and analyze the anatomy of the temporal bone, its proportions and measure the CDL. Therefore, we investigated the calculation technique of the CDL via a tablet-based software on our own cohort retrospectively. Methods One hundred and eight preoperative computed tomography scans of the temporal bone (slice thickness < 0.7 mm) of already implanted FLEX28™ and FLEXSOFT™ patients were found eligible for analysis with the OTOPLAN software. Measurements were performed by two trained investigators independently. CDL, angular insertion depth (AID), and cochlear coverage were calculated and compared between groups of electrode types, sex, sides, and age. Results Mean CDL was 36.2 ± 1.8 mm with significant differences between sex (female: 35.8 ± 0.3 mm; male: 36.5 ± 0.2 mm; p  = 0.037), but none concerning side or age. Differences in mean AID (FLEX28: 525.4 ± 46.4°; FLEXSOFT: 615.4 ± 47.6°), and cochlear coverage (FLEX28: 63.9 ± 5.6%; FLEXSOFT: 75.8 ± 4.3%) were significant ( p  < 0.001). Conclusion A broad range of CDL was observed with significant larger values in male, but no significant differences concerning side or age. Almost every cochlea was measured longer than 31.0 mm. Preoperative assessment aids in prevention of complications (incomplete insertion, kinking, tipfoldover), attempt of atraumatic insertion, and addressing individual necessities (hearing preservation, cochlear malformation). The preferred AID of 720° (two turns of the cochlea) was never reached, opening the discussion for the requirement of longer CI-electrodes versus a debatable audiological benefit for the patient in his/her everyday life.

Time-resolved spectroscopic and electron–ion coincidence techniques are essential to study dynamic processes in materials or chemical compounds. For this type of analysis, it is necessary to have detectors capable of providing, in addition to image-related information, the time of arrival for each individual detected particle (“x, y, time”). The electronics capable of handling such sensors must meet requirements achievable only with time-to-digital converters (TDC) with a resolution on the order of tens of picoseconds and the use of a field-programmable gate array (FPGA) to manage data acquisition and transmission. This study introduces the design and implementation of an innovative TDC based on two FPGAs working symbiotically with different tasks: the first (AMD/Xilinx Artix® 7) directly implements a TDC, aiming for a temporal precision of 12 picoseconds, while the second (Intel Cyclone® 10) manages the acquisition and connectivity with the external world. The TDC has been optimized to operate on eight channels (+ sync) simultaneously but is potentially extendable to a greater number of channels, making it particularly suitable for coincidence measurements where it is necessary to temporally correlate multiple pieces of information from various measurement systems.

The success of next-generation Internet of Things (IoT) applications could be boosted with state-of-the-art communication technologies, including the operation of millimeter-wave (mmWave) bands and the implementation of three-dimensional (3D) networks. With some access points (APs) mounted on unmanned aerial vehicles (UAVs), the probability of line-of-sight (LoS) connectivity to IoT nodes could be augmented to address the high path loss at mmWave bands. Nevertheless, system optimization is essential to maintaining reliable communication in 3D IoT networks, particularly in dense urban areas with elevated buildings. This research adopts the implementation of a geometry-based stochastic channel model. The model customizes the standard clustered delay line (CDL) channel profile based on the environmental geometry of the site to obtain realistic performance and optimize system design. Simulation validation is conducted based on the actual maps of highly dense urban areas to demonstrate that the proposed approach is comprehensive. The results reveal that the use of standard channel models in the analysis introduces errors in the channel quality indicator (CQI) that can exceed 50% due to the effect of the environmental geometry on the channel profile. The results also quantify accuracy improvements in the wireless channel and network performance in terms of the CQI and downlink (DL) throughput.

Machine learning combined with satellite image time series can quickly, and reliably be implemented to map crop distribution and growth monitoring necessary for food security. However, obtaining a large number of field survey samples for classifier training is often time-consuming and costly, which results in the very slow production of crop distribution maps. To overcome this challenge, we propose an ensemble learning approach from the existing historical crop data layer (CDL) to automatically create multitudes of samples according to the rules of spatiotemporal sample selection. Sentinel-2 monthly composite images from 2017 to 2019 for crop distribution mapping in Jilin Province were mosaicked and classified. Classification accuracies of four machine learning algorithms for a single-month and multi-month time series were compared. The results show that deep neural network (DNN) performed the best, followed by random forest (RF), then decision tree (DT), and support vector machine (SVM) the least. Compared with other months, July and August have higher classification accuracy, and the kappa coefficients of 0.78 and 0.79, respectively. Compared with a single phase, the kappa coefficient gradually increases with the growth of the time series, reaching 0.94 in August at the earliest, and then the increase is not obvious, and the highest in the whole growth cycle is 0.95. During the mapping process, time series of different lengths produced different classification results. Wetland types were misclassified as rice. In such cases, authors combined time series of two lengths to correct the misclassified rice types. By comparing with existing products and field points, rice has the highest consistency, followed by corn, whereas soybeans have the least consistency. This shows that the generated sample data set and trained model in this research can meet the crop mapping accuracy and simultaneously reduce the cost of field surveys. For further research, more years and types of crops should be considered for mapping and validation.