Specific Regions Research Articles

Proposition of In silico Pharmacophore Models for Malaria: A Review.

In the field of medicinal chemistry, the concept of pharmacophore refers to the specific region of a molecule that possesses essential structural and chemical characteristics for binding to a receptor and eliciting biological activity. Understanding the pharmacophore is crucial for drug research and development, as it allows the design of new drugs. Malaria, a widespread disease, is commonly treated with chloroquine and artemisinin, but the emergence of parasite resistance limits their effectiveness. This study aims to explore computer simulations to discover a specific pharmacophore for Malaria, providing new alternatives for its treatment. A literature review was conducted, encompassing articles proposing a pharmacophore for Malaria, gathered from the "Web of Science" database, with a focus on recent publications to ensure up-to-date analysis. The selected articles employed diverse methods, including ligand-based and structurebased approaches, integrating molecular structure and biological activity data to yield comprehensive analyses. Affinity evaluation between the proposed pharmacophore and the target receptor involved calculating free energy to quantify their interaction. Multiple linear regression was commonly utilized, though it is sensitive to multicollinearity issues. Another recurrent methodology was the use of the Schrödinger package, employing tools such as the Phase module and the OPLS force field for interaction analysis. Pharmacophore model proposition allows threedimensional representations guiding the synthesis and design of new biologically active compounds, offering a promising avenue for discovering therapeutic agents to combat Malaria.

Activation of Polycystin-1 Signaling by Binding of Stalk-derived Peptide Agonists.

Polycystin-1 (PC1) is the membrane protein product of the PKD1 gene whose mutation is responsible for 85% of the cases of autosomal dominant polycystic kidney disease (ADPKD). ADPKD is primarily characterized by the formation of renal cysts and potential kidney failure. PC1 is an atypical G protein-coupled receptor (GPCR) consisting of 11 transmembrane helices and an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Recently, signaling activation of the PC1 CTF was shown to be regulated by a stalk tethered agonist (TA), a distinct mechanism observed in the adhesion GPCR family. A novel allosteric activation pathway was elucidated for the PC1 CTF through a combination of Gaussian accelerated molecular dynamics (GaMD), mutagenesis and cellular signaling experiments. Here, we show that synthetic, soluble peptides with 7 to 21 residues derived from the stalk TA, in particular, peptides including the first 9 residues (p9), 17 residues (p17) and 21 residues (p21) exhibited the ability to re-activate signaling by a stalkless PC1 CTF mutant in cellular assays. To reveal molecular mechanisms of stalk peptide-mediated signaling activation, we have applied a novel Peptide GaMD (Pep-GaMD) algorithm to elucidate binding conformations of selected stalk peptide agonists p9, p17 and p21 to the stalkless PC1 CTF. The simulations revealed multiple specific binding regions of the stalk peptide agonists to the PC1 protein including an "intermediate" bound yet inactive state. Our Pep-GaMD simulation findings were consistent with the cellular assay experimental data. Binding of peptide agonists to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of the PC1 CTF signaling activation mechanism. Using sequence covariation analysis of PC1 homologs, we further showed that the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. Therefore, structural dynamic insights into the mechanisms of PC1 activation by stalk-derived peptide agonists have enabled an in-depth understanding of PC1 signaling. They will form a foundation for development of PC1 as a therapeutic target for the treatment of ADPKD.

Pathological Priors Inspired Network for Vertebral Osteophytes Recognition.

Automatic vertebral osteophyte recognition in Digital Radiography is of great importance for the early prediction of degenerative disease but is still a challenge because of the tiny size and high inter-class similarity between normal and osteophyte vertebrae. Meanwhile, common sampling strategies applied in Convolution Neural Network could cause detailed context loss. All of these could lead to an incorrect positioning predicament. In this paper, based on important pathological priors, we define a set of potential lesions of each vertebra and propose a novel Pathological Priors Inspired Network (PPIN) to achieve accurate osteophyte recognition. PPIN comprises a backbone feature extractor integrating with a Wavelet Transform Sampling module for high-frequency detailed context extraction, a detection branch for locating all potential lesions and a classification branch for producing final osteophyte recognition. The Anatomical Map-guided Filter between two branches helps the network focus on the specific anatomical regions via the generated heatmaps of potential lesions in the detection branch to address the incorrect positioning problem. To reduce the inter-class similarity, a Bilateral Augmentation Module based on the graph relationship is proposed to imitate the clinical diagnosis process and to extract discriminative contextual information between adjacent vertebrae in the classification branch. Experiments on the two osteophytes-specific datasets collected from the public VinDr-Spine database show that the proposed PPIN achieves the best recognition performance among multitask frameworks and shows strong generalization. The results on a private dataset demonstrate the potential in clinical application. The Class Activation Maps also show the powerful localization capability of PPIN. The source codes are available in https://github.com/Phalo/PPIN.

Galaxies in the zone of avoidance: Misclassifications using machine learning tools

Context. Automated methods for classifying extragalactic objects in large surveys offer significant advantages compared to manual approaches in terms of efficiency and consistency. However, the existence of the Galactic disk raises additional concerns. These regions are known for high levels of interstellar extinction, star crowding, and limited data sets and studies. Aims. In this study, we explore the identification and classification of galaxies in the zone of avoidance (ZoA). In particular, we compare our results in the near-infrared (NIR) with X-ray data. Methods. We analyzed the appearance of objects in the Galactic disk classified as galaxies using a published machine-learning (ML) algorithm and make a comparison with the visually confirmed galaxies from the VVV NIRGC catalog. Results. Our analysis, which includes the visual inspection of all sources cataloged as galaxies throughout the Galactic disk using ML techniques reveals significant differences. Only four galaxies were found in both the NIR and X-ray data sets. Several specific regions of interest within the ZoA exhibit a high probability of being galaxies in X-ray data but closely resemble extended Galactic objects. Our results indicate the difficulty in using ML methods for galaxy classification in the ZoA, which is mainly due to the scarcity of information on galaxies behind the Galactic plane in the training set. They also highlight the importance of considering specific factors that are present to improve the reliability and accuracy of future studies in this challenging region.

Suicide by Gunshot Wound to the Posterior Head and Neck: A Retrospective Case Series and Review of the Literature.

Suicide by firearm is a significant public health concern in specific regions of the world. Depending on firearm availability, any type of firearm may be used, including handguns, shotguns, and long rifles. Common entrance wound sites in suicidal gunshot wounds include the head, with classic gunshot wound locations including the temple, the forehead, the submental aspect of the chin, and inside the mouth. Occasionally, suicidal gunshot wounds occur in atypical body locations such as the back of the head and neck. Given their relative rarity, suicidal gunshot wounds in these regions may be mistaken for homicides. In this report, we present 5 cases of suicidal gunshot wounds to the back of the head and/or neck. In our series, we focus on differentiating each case from homicides involving gunshot wounds in similar areas of the head and neck.

SGXFault: An Efficient Page Fault Handling Mechanism for SGX Enclaves

Trusted Execution Environments (TEEs) such as Intel SGX are becoming a commonplace for the security in server processors. Intel SGX provides the guarantees of confidentiality, integrity and replay attack protection for a specific region of memory. However, the downside of it is the performance bottleneck due to the context switching overhead and the page faults for the larger memory footprint applications. In this paper, we propose a scheme <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SGXFault</i> which ensures for major part of the execution, the pages are available in the secure memory when needed. We do this decision at the last level cache (LLC) by locking the blocks of the frequent pages to the LLC using Cache Lockdown mechanism. In addition to this, we do a page-level prediction based prefetching when there is a miss in the LLC. Using the combination of both the approaches, we are able to outperform baseline Intel SGX and recent competing scheme by around 18.6% and 17.8% respectively.

A Physics-Based Methodology to Improve the Mitigation of Loss of Tail Rotor Effectiveness

Loss of tail rotor effectiveness (LTE), also known as unanticipated yaw, has been recognized to be a major contributing factor in several helicopter accidents due to the loss of directional control. Flight tests have identified specific wind azimuth regions that may alter the angle and the speed of the airflow through the tail rotor leading to LTE. Through the helicopter flight data monitoring (HFDM) program, pilots receive constant flight evaluation reports to support LTE risk mitigation. Nevertheless, the existing LTE safety metric presents several pitfalls that hinder the reliability of the detection of violations of boundaries for flight safety. To identify the appropriate methods to properly simulate and flag LTE events and develop a more comprehensive and reliable LTE safety metric to be used within the HFDM environment, a physics-based investigation of the different LTE flight characteristics is performed. The results from this investigation are expected to contribute towards an improvement in detection of LTE events, leading to a reduction in LTE-related accidents.

The Influence of Road Transport on Carbon Footprint: A Case Study of the Black Sea Region

Recently, the increase in global warming and the spread of greenhouse gases is a major concern. The use of fossil fuels plays an important role in greenhouse gas emissions. Fossil fuels are primarily used in the transportation sector. Road transport plays a critical role in the transportation sector. This study analyzed carbon dioxide emissions from transport in a specific region. The amount of carbon dioxide emissions from transport in this region, called the Black Sea region, was analyzed from 2013 to 2022. As a result, it was determined that the amount of carbon dioxide emissions in the region has gradually increased at an alarming level.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics.

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

Publication of pharmacy resident research projects: A systematic review and meta-analysis.

Pharmacy residents often aspire to develop research skills through conducting a research project. Project publication rates among pharmacy residents are variable and at times low; however, previous studies have been limited to specific geographic regions and timeframes. This study sought to conduct a systematic review and meta-analysis to determine the proportion of pharmacy resident research projects published in the peer-reviewed literature. A systematic review of PubMed MEDLINE, Embase, and the Web of Science Core Collection was performed from database inception to May 25, 2023. Articles were included if they were full-text, peer-reviewed manuscripts of original research presenting observational data regarding pharmacy resident research project publication rates. Data extraction and assessment of risk of bias were conducted by 2 independent reviewers. A proportional meta-analysis using a random effects model of the included studies was conducted to generate a pooled, overall proportion. The search yielded 5,225 records and 12 articles that met the inclusion criteria. All studies were retrospective and observational. Risk of selection and cohort identification biases was "high," whereas that of detection and timeframe biases was "low." The included studies represented 6,990 resident research projects, 777 of which were published in the peer-reviewed literature. Publication rates across individual studies ranged from 1.8% to 36.2%. The pooled proportion (scale of 0 to 1) of projects published was 0.13 (95% CI, 0.09-0.19). Pharmacy resident research project publication rates are low at 13%. Furthermore, studies reporting project publication rates over time suggest a neutral or negative trend in publication rates despite an exponential increase in the number of pharmacy residents.

The impact of interfacial characteristics on the interfacial properties of 316 L/CuSn10 multi-material manufactured by laser powder bed fusion

Multi-material additive manufacturing (MMAM) enables the simultaneous creation of multi-material components in a single process, accomplishing customized different performances in specific regions of the same components. In particular, the copper-steel multi-material structure can provide considerable strength and high thermal conductivity, thus playing a crucial role in electronic components, heat exchangers and injection molds. However, few studies have explored the relationship between the microstructure and properties of the copper-steel fusion zone. Therefore, this study aims to reveal the heterogeneous evolution of the microstructure in the copper/steel fusion zone and its impact on the interfacial properties of 316 L/CuSn10 multi-material structure fabricated by laser powder bed fusion (L-PBF). We characterized the multi-layer specimens using laser confocal microscopy and SEM to obtain the macroscopic and microscopic microstructure, liquid metal embrittlement (LME) microcrack characteristics and precipitation evolution of the copper-steel fusion zone. The generation of liquid phase separation (LPS) was explored based on block specimens, and the textural characteristics of the fusion zone were analyzed using EBSD. As a result, because of multiple element precipitation and the high thermal conductivity of copper alloy, abrupt grain size changes occur in the fusion zone, affecting the fusion zone's corrosion resistance and nano-hardness. In tensile tests analyzing the anisotropy, the results show that LME microcracks have little impact on the interfacial bonding properties of the copper-steel bimetallic structure, among which the ultimate tensile strength of the specimens formed at 30° to the substrate reached a maximum of 562.9 MPa. These findings add substantially to our understanding of the relationship between the microstructure and properties of copper-steel bimetallic interface, and provide a theoretical reference for additive manufacturing copper-steel multi-material components.

Chloroplast genome of Calamus tetradactylus revealed rattan phylogeny

BackgroundCalamus tetradactylus, a species primarily distributed in Vietnam, Laos, and southern China, is highly valued for its utilization as a small-diameter rattan material. While its physical and mechanical properties have been extensively studied, the genomic characteristics of C. tetradactylus remain largely unexplored.ResultsTo gain a better understanding of its chloroplast genomic features and evolutionary relationships, we conducted sequencing and assembly of the chloroplast genome of C. tetradactylus. The complete chloroplast genome exhibited the typical highly conserved quartile structure, with specific variable regions identified in the single-copy region (like psbF-psbE, π = 0.10327, ndhF-rpl32, π = 0.10195), as well as genes such as trnT-GGU (π = 0.05764) and ycf1 (π = 0.03345) and others. We propose that these regions and genes hold potential as markers for species identification. Furthermore, phylogenetic analysis revealed that C. tetradactylus formed a distinct clade within the phylogenetic tree, alongside other Calamus species, and C. tetradactylus was most closely related to C. walkeri, providing support for the monophyly of the genus.ConclusionThe analysis of the chloroplast genome conducted in this study provides valuable insights that can contribute to the improvement of rattan breeding programs and facilitate sustainable development in the future.

Navigating Real-World Partial Label Learning: Unveiling Fine-Grained Images with Attributes

Partial label learning (PLL), a significant research area, addresses the challenge of annotating each sample with a candidate label set containing the true label when obtaining accurate labels is infeasible. However, existing PLL methods often rely on generic datasets like CIFAR, where annotators can readily differentiate candidate labels and are unlikely to confuse, making it less realistic for real-world partial label applications. In response, our research focuses on a rarely studied problem, PLL on fine-grained images with attributes. And we propose a novel framework called Shared to Learn, Distinct to Disambiguate (SoDisam). Within the candidate label set, the categories may exhibit numerous shared attribute features, posing a challenge in accurately distinguishing them. Rather than perceiving it as an impediment, we capitalize on these shared attributes as definitive sources of supervision. This insight guides us to learn attribute space visual representation to focus on the information from these shared attributes. Moreover, we introduce an attribute attention mechanism tailored to harness the remaining distinct attributes. This mechanism directs the originally holistic feature towards specific regions, capturing corresponding discriminative features. In addition, a dynamic disambiguation module is introduced, continuously adjusting the two aforementioned mechanisms and achieve the final disambiguation process. Extensive experiments demonstrate the effectiveness of our approach on fine-grained partial label datasets. The proposed SoDisam framework not only addresses the challenges associated with fine-grained partial label learning but also provides a more realistic representation of real-world partial label scenarios.

Regional suitability assessment for different tillage practices in Northeast China: A machine learning aided meta-analysis

Northeast China is known as the “Corn Belt” of China. Long-term conventional tillage has led to severe soil degradation, threatening the food production and China’s food security. Regenerative farming practices such as no-tillage and deep ploughing have proven effective in protecting soil and promoting sustainable agriculture. However, the effects of no-tillage and deep ploughing on corn yield are hotly debated, and their regional suitability in Northeast China remains unclear. As a solution, a regional machine learning aided meta-analysis was performed to assess the effects of field management practices, climate conditions, and soil properties on crop productivity of no-tillage and deep ploughing versus conventional tillage, and to evaluate the probability of yield increase under no-tillage and deep ploughing across Northeast China. The results showed that the overall effect of no-tillage and deep ploughing significantly increased corn yield by 5.1% and 6.4%, respectively, compared to conventional tillage. Climate conditions had the greatest importance on crop yield under no-tillage, while management practices were the most explainable variable under deep ploughing. Data driven models reveled that the probabilities of yield increase under no-tillage and deep ploughing had large geographical differences. No-tillage performed better in warm arid regions with alkaline soil and low initial soil organic matter. In cold and humid areas with neutral soil and high soil organic matter content, deep ploughing had the greatest possibility of increasing yield. Our study revealed the effects and importance of factors affecting crop productivity of no-tillage and deep ploughing, which helps to optimize these practices. Furthermore, our results provide a reference for agricultural managers to select appropriate tillage practices that simultaneously contribute to food production and sustainable agricultural goals in specific regions of Northeast China.

An adaptive threshold based gait authentication by incorporating quality measures

In this paper, an adaptive threshold-based gait authentication model is proposed, which incorporates the quality measure in the distance domain and maps them into the gradient domain to realize the optimal threshold of each gait sample, in contrast to the fixed threshold, as most of the authentication model utilizes. For accessing the quality measure of each gait, a gait covariate invariant generative adversarial network (GCI-GAN) is proposed to generate normal gait (canonical condition) irrespective of covariates (carrying, and viewing conditions) while preserving the subject identity. In particular, GCI-GAN connects to gradient weighted class activation mapping (Grad-CAMs) to obtain an attention mask from the significant components of input features, employs blending operation to manipulate specific regions of the input, and finally, multiple losses are employed to constrain the quality of generated samples. We validate the approach on gait datasets of CASIA-B and OU-ISIR and show a substantial increase in authentication rate over other state-of-the-art techniques.

Multiplex PCR method for MinION sequencing of Bagaza virus isolated from wild caught mosquitoes in South Africa

Bagaza virus (BAGV) is a mosquito-borne orthoflavivirus known to occur in regions of southern Europe, Africa, India and the Middle East. The virus has been associated with neurological disease and fatalities in various wild bird species. Association with human disease is not confirmed although limited serological evidence has suggested human infection. Surveillance programs for screening mosquitoes for evidence of arbovirus infection play an important role in providing information regarding the circulation and spread of viruses in specific regions. BAGV was detected in a mosquito pool during surveillance of mosquitoes collected in central South Africa between November 2019 and March 2023. Homogenized mosquito pools were screened for flaviviral RNA using conventional RT-PCR and virus isolation was attempted on positive samples. BAGV was detected and subsequently isolated using cell culture. A multiplex tiling PCR method for targeted enrichment using a PCR based or amplicon sequencing approach of the complete genome of BAGV was developed and optimized. Primers were designed using alignment of complete genome sequence data retrieved from GenBank to identify suitable primer sites that would generate overlapping fragments spanning the complete genome. Six forward primers and eight reverse primers were identified that target the complete genome and amplified nine overlapping fragments, that ranged in length from 1954 to 2039 with an overlap ranging from 71 to 711 base pairs. The design strategy included multiple forward and reverse primer pairs for the 5’ and 3’ ends. Phylogenetic analysis with other isolates was performed and BAGV isolate VBD 74/23/3 was shown to share high similarity with previous BAGV isolates from all regions, with genetic distance ranging from 0.026 to 0.083. VBD 74/23/3 was most closely related to previous isolates from southern Africa, ZRU96/16/2 isolated from a post-mortem sample from a pheasant in 2016 and MP-314-NA-2018 isolated from mosquitoes in northwestern Namibia with genetic distance 0.0085 and 0.016 respectively. Currently there is limited complete genome sequence data available for many of the arboviruses circulating in Africa. The multiplex tiling method provided a simple and cost-effective method for obtaining complete genome sequence. This method can be readily applied to other viruses using sequence data from publicly available databases and would have important application facilitating genomic surveillance of arboviruses in low resource countries.

Natural compound plumbagin based inhibition of hIAPP revealed by Markov state models based on MD data along with experimental validations.

Human islet amyloid polypeptide (amylin or hIAPP) is a 37 residue hormone co-secreted with insulin from β cells of the pancreas. In patients suffering from type-2 diabetes, amylin self-assembles into amyloid fibrils, ultimately leading to the death of the pancreatic cells. However, a research gap exists in preventing and treating such amyloidosis. Plumbagin, a natural compound, has previously been demonstrated to have inhibitory potential against insulin amyloidosis. Our investigation unveils collapsible regions within hIAPP that, upon collapse, facilitates hydrophobic and pi-pi interactions, ultimately leading to aggregation. Intriguingly plumbagin exhibits the ability to bind these specific collapsible regions, thereby impeding the aforementioned interactions that would otherwise drive hIAPP aggregation. We have used atomistic molecular dynamics approach to determine secondary structural changes. MSM shows metastable states forming native like hIAPP structure in presence of PGN. Our in silico results concur with in vitro results. The ThT assay revealed a striking 50% decrease in fluorescence intensity at a 1:1 ratio of hIAPP to Plumbagin. This finding suggests a significant inhibition of amyloid fibril formation by plumbagin, as ThT fluorescence directly correlates with the presence of these fibrils. Further TEM images revealed disappearance of hIAPP fibrils in plumbagin pre-treated hIAPP samples. Also, we have shown that plumbagin disrupts the intermolecular hydrogen bonding in hIAPP fibrils leading to an increase in the average beta strand spacing, thereby causing disaggregation of pre-formed fibrils demonstrating overall disruption of the aggregation machinery of hIAPP. Our work is the first to report a detailed atomistic simulation of 22 μs for hIAPP. Overall, our studies put plumbagin as a potential candidate for both preventive and therapeutic candidate for hIAPP amyloidosis.

Two dimensional shear wave elastography—Basic principles and current applications

AbstractUltrasound‐based elastography techniques are increasingly available on modern ultrasound systems. The application of elastography extends the utility of ultrasound, yielding new information about the impact of disease on tissue biomechanics. By modifying the B‐mode imaging pulse, an Acoustic Radiation Force Impulse produces shear waves in selected tissue. Quantifying the speed of the resultant shear wave provides an indirect assessment of tissue stiffness, with stiffer tissue producing faster shear wave movement than softer tissue. Two main types of ultrasound shear wave elastography are currently in use. Point shear wave elastography uses one or two pulses to measure shear wave speeds over a small fixed area. Alternatively, two‐dimensional shear‐wave elastography provides a colour elastogram map over a larger area, allowing the operator to select specific regions of interest to measure shear wave speed. This article will discuss the essential physics principles, and clinical uses of two‐dimensional shear wave elastography, aiming to provide sonographers with a basic understanding of the technology and current applications.

Transcriptomic analysis of rat brain response to alternating current electrical stimulation: unveiling insights via single-nucleus RNA sequencing.

Electrical brain stimulation (EBS) has gained popularity for laboratory and clinical applications. However, comprehensive characterization of cellular diversity and gene expression changes induced by EBS remains limited, particularly with respect to specific brain regions and stimulation sites. Here, we presented the initial single-nucleus RNA sequencing profiles of rat cortex, hippocampus, and thalamus subjected to intracranial alternating current stimulation (iACS) at 40Hz. The results demonstrated an increased number of neurons in all three regions in response to iACS. Interestingly, less than 0.1% of host gene expression in neurons was significantly altered by iACS. In addition, we identified Rgs9, a known negative regulator of dopaminergic signaling, as a unique downregulated gene in neurons. Unilateral iACS produced a more focused local effect in attenuating the proportion of Rgs9+ neurons in the ipsilateral compared to bilateral iACS treatment. The results suggested that unilateral iACS at 40Hz was an efficient approach to increase the number of neurons and downregulate Rgs9 gene expression without affecting other cell types or genes in the brain. Our study presented the direct evidence that EBS could boost cerebral neurogenesis and enhance neuronal sensitization to dopaminergic drugs and agonists, through its downregulatory effect on Rgs9 in neurons.

Heterozygous Pyrin (MEFV) E148Q allele carriers indicate a reduced glaucoma risk for Turkish population: a prospective clinical analysis

ABSTRACT Purpose The MEFV gene encodes pyrin, a protein linked to increased severity of symptoms in Familial Mediterranean Fever (FMF). We consider that inflammation due to MEFV variants would increase eye inflammation and damage aqueous humor regulation. The present study is the first analysis investigating a MEFV (E148Q) variant as a marker protecting from glaucoma. Methods In this prospective clinical analyze, we performed detailed gene sequencing focusing on 22 specific regions of the pyrin (MEFV) gene. The study involved two distinct groups: individuals diagnosed with glaucoma (n = 200) and control subjects without glaucoma (n = 100). Both groups were carefully selected to exclude individuals with symptoms or a previous diagnosis of Familial Mediterranean Fever (FMF). The diagnosis of glaucoma for each participant was rigorously established through comprehensive direct ophthalmic examinations. Results A significant odds ratio for protection against glaucoma was found in carriers of the subclinical E148Q allele (OR:2.22; 95%CI: 1.098–4.485). No significant differences were found for other variants. One mutant E148Q-allele could decrease the probability of glaucoma development by approximately 68,9%. We observed no differences in the genotype frequency between glaucoma and healthy for the other MEFV gene variants. Conclusion The pyrin variant of the MEFV gene resulting in a subclinical phenotype appears to reduce the incidence of glaucoma, and heterozygous pyrin (MEFV) E148Q allele carriers confer protection against glaucoma. It is important to consider the limitations arising from the relatively small number of studies conducted on this topic.