Case-control study: Unveiling human polyomaviruses and papillomavirus in Egyptian colorectal cancer patients.

BACKGROUND: Colorectal cancer (CRC) is a cancer type that is thought to be influenced by human papillomaviruses (HPVs) and human polyomaviruses (HPyVs). In Egypt, CRC ranks as the 7th most common cancer, accounting for 3.47% of male cancers and 3% of female cancers. However, there is currently a lack of information regarding the presence of PyVs and HPVs co-infection specifically in CRC cases in Egypt. Therefore, the aim of this study was to investigate the occurrence of HPVs and HPyVs (JCPyV, BKPyV, and SV40) infections, as well as co-infections, among CRC patients in Egypt. Additionally, the study aimed to assess any potential association between these viral infections and tumor stages. METHODS: In the present study, we analyzed a total of 51 tissue samples obtained from Egyptian CRC patients, along with 19 polyps' samples. Our investigation focused on the detection and genotyping of HPyVs using Real-Time PCR. Additionally, we employed real-time PCR for the detection of HPVs, and for their genotyping, we utilized a combination of PCR amplification followed by sequencing. RESULTS: In our study, we found evidence of HPyVs infection in the CRC patients, specifically SV40 (25.5%) and BKPyV (19.6%). However, JCPyV was not detected in the samples that were examined. Additionally, we discovered that HPV was present in 43.1% of the CRC patients. When considering viral co-infections, 19.6% of the CRC samples showed coexistence of multiple viruses, while no co-infections were found in the polyps samples. Importantly, we observed a significant correlation between the presence of HPVs and advanced colorectal tumor grades B2 and D. CONCLUSION: Our findings provide valuable data for the detection of oncogenic viruses in colorectal cancer (CRC) and underscore the association of viral co-infections with advanced tumor stages. However, further research with larger cohorts is necessary to validate these findings and strengthen their significance in the field of CRC.

The implication of miR-200a and miR-132 expression and their correlations with NF-κB/TNF-alpha signaling in adults with diabetic nephropathy.

Aim: The primary factor causing chronic renal failure is diabetic nephropathy (DN) worldwide. However, the current biomarkers for DN have limited diagnostic utility. Thus, this work aimed to clarify the implications of microRNA-200a (miR-200a) and microRNA-132 (miR-132) and their correlation with NF-κB (nuclear factor- kappa beta), and, TNF-α (tumor necrosis factor -alpha) signaling to identify biomarkers able to distinguish late-stage from early- stage DN. Methods: Fifty healthy controls, and 271 type 2 diabetic (T2D) patients (166 male plus 105 female) were enrolled. Participants were stratified into seven groups according to along with the estimated glomerular filtration rate (eGFR), glycated hemoglobin (HbA1c%), healthy controls, diabetes without DN (G1), diabetes with mild renal impairment (G2), and four DN grades (G3a, G3b, G4, and G5). Results: Compared to healthy controls, the DN groups exhibited linear increases in serum miR-200a, TNF-α, NF-κB, matrix metalloproteinase (MMP-9) and interleukin-6 (IL-6) levels and reductions in miR-132 serum expression. Among the patients, NF-κB and TNF-α produced a negative correlation with miR-132, while, positive correlation has been discovered with miR-200-a. The operating characteristic of the receiver curve (ROC), proved that, miR-200a also miR-132 had good diagnostic performance in distinguishing early from advanced DN. Conclusion: MiR-200a as well as miR-132 expression levels, and their correlations with NF-κB/TNF-alpha signaling, were able to differentiate between DN patients with lower eGFR, suggesting their utility as diagnostic and prognostic biomarkers.

Neoadjuvant therapy to improve resectability of advanced thyroid cancer: A real-world experience.

BACKGROUND: Experience with targeted neoadjuvant treatment for locoregionally advanced thyroid cancer is nascent. METHODS: Multicenter retrospective case series examining targeted neoadjuvant treatment for locoregionally advanced thyroid cancer. The primary outcome was change in surgical morbidity as measured by two metrics developed for use in clinical trials to characterize surgical complexity and morbidity. Secondary outcomes included percentage of patients proceeding to surgery and percentage receiving an R0/R1 resection. RESULTS: Seventeen patients with varied molecular alterations, pathologies, and treatment regimens were included. Mean surgical complexity scores decreased between time points for baseline and postneoadjuvant treatment, postneoadjuvant treatment and surgery, and between baseline and surgery. Eleven patients (64.7%) underwent surgical resection, with 10 (58.8%) receiving an R0/R1 resection. CONCLUSIONS: Neoadjuvant treatment of advanced thyroid cancer improves resectability and decreases the morbidity of required surgical procedures. However, treatment is not uniformly effective.

Accurate preoperative prediction of nodal metastasis in papillary thyroid microcarcinoma: Towards optimal management of patients.

OBJECTIVE: To enhance the accuracy in predicting lymph node metastasis (LNM) preoperatively in patients with papillary thyroid microcarcinoma (PTMC), refining the "low-risk" classification for tailored treatment strategies. METHODS: This study involves the development and validation of a predictive model using a cohort of 1004 patients with PTMC undergoing thyroidectomy along with central neck dissection. The data was divided into a training cohort (n = 702) and a validation cohort (n = 302). Multivariate logistic regression identified independent LNM predictors in PTMC, leading to the construction of a predictive nomogram model. The model's performance was assessed through ROC analysis, calibration curve analysis, and decision curve analysis. RESULTS: Identified LNM predictors in PTMC included age, tumor maximum diameter, nodule-capsule distance, capsular contact length, bilateral suspicious lesions, absence of the lymphatic hilum, microcalcification, and sex. Especially, tumors larger than 7 mm, nodules closer to the capsule (less than 3 mm), and longer capsular contact lengths (more than 1 mm) showed higher LNM rates. The model exhibited AUCs of 0.733 and 0.771 in the training and validation cohorts respectively, alongside superior calibration and clinical utility. CONCLUSION: This study proposes and substantiates a preoperative predictive model for LNM in patients with PTMC, honing the precision of "low-risk" categorization. This model furnishes clinicians with an invaluable tool for individualized treatment approach, ensuring better management of patients who might be proposed observation or ablative options in the absence of such predictive information.

Intraoperative AI-assisted early prediction of parathyroid and ischemia alert in endoscopic thyroid surgery.

BACKGROUND: The preservation of parathyroid glands is crucial in endoscopic thyroid surgery to prevent hypocalcemia and related complications. However, current methods for identifying and protecting these glands have limitations. We propose a novel technique that has the potential to improve the safety and efficacy of endoscopic thyroid surgery. PURPOSE: Our study aims to develop a deep learning model called PTAIR 2.0 (Parathyroid gland Artificial Intelligence Recognition) to enhance parathyroid gland recognition during endoscopic thyroidectomy. We compare its performance against traditional surgeon-based identification methods. MATERIALS AND METHODS: Parathyroid tissues were annotated in 32 428 images extracted from 838 endoscopic thyroidectomy videos, forming the internal training cohort. An external validation cohort comprised 54 full-length videos. Six candidate algorithms were evaluated to select the optimal one. We assessed the model's performance in terms of initial recognition time, identification duration, and recognition rate and compared it with the performance of surgeons. RESULTS: Utilizing the YOLOX algorithm, we developed PTAIR 2.0, which demonstrated superior performance with an AP50 score of 92.1%. The YOLOX algorithm achieved a frame rate of 25.14 Hz, meeting real-time requirements. In the internal training cohort, PTAIR 2.0 achieved AP50 values of 94.1%, 98.9%, and 92.1% for parathyroid gland early prediction, identification, and ischemia alert, respectively. Additionally, in the external validation cohort, PTAIR outperformed both junior and senior surgeons in identifying and tracking parathyroid glands (p < 0.001). CONCLUSION: The AI-driven PTAIR 2.0 model significantly outperforms both senior and junior surgeons in parathyroid gland identification and ischemia alert during endoscopic thyroid surgery, offering potential for enhanced surgical precision and patient outcomes.

Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures.

The role of urinary biomarker monocyte chemoattractant protein (MCP-1) in correlation with different histopathological classes of lupus nephritis in Egyptian patients.

Lupus nephritis (LN) affects almost two-thirds of systemic lupus erythematosus (SLE) patients. Renal biopsy is the gold standard for the diagnosis of LN. However, repeated biopsies are not always performed in clinical practice, and they carry some risk. Therefore, minimally invasive techniques, as urinary biomarkers, are promising tools for the diagnosis and monitoring of SLE. Previous studies evaluated urinary monocyte chemoattractant protein-1 (MCP-1) in patients with SLE, reported higher levels of urinary MCP-1 in patients with active LN than non-active LN. Other studies reported higher levels of urinary MCP-1 in LN patients with proliferative forms (III and IV). This study aimed to evaluate urinary MCP-1 as a noninvasive diagnostic biomarker tool for LN, and to determine its association with different LN histopathological stages and chronicity indices. The study included 40 SLE patients with biopsy-proven LN class II, III, IV or V, and 20 patients with inactive LN as a control group. In LN active patients, the mean creatinine was 1.71 ± 0.55 mg/dl, and 0.84 ± 0.10 mg/dl in the control group. The mean MCP-1 level was 618.4 ± 294.2 ng/l in active LN patients and 120.05 ± 87.53 ng/l in inactive LN patients. The receiver operating characteristic (ROC) curve analysis indicated a better diagnostic performance of MCP-1 than conventional biomarkers. At area under the curve of 0.990, the best cut-off level was >245 ng/L (sensitivity 97.5 %, Specificity 95 %). In conclusion, urinary MCP-1 distinguished active LN from inactive renal disease. It can be proposed as a good noninvasive diagnostic biomarker with a high sensitivity and specificity for detection of LN activity..

Recovery of Recurrent Laryngeal Nerve Function With Neoadjuvant Treatment: Neural Characterization.

OBJECTIVES: Neoadjuvant targeted therapy has emerged as a promising treatment strategy for locally aggressive thyroid cancer. Its impact on tumor and adjacent tissues remains a nascent area of study. Here we report on a series of six subjects with locally advanced thyroid cancer and recurrent laryngeal nerve (RLN) paralysis who experienced recovery of RLN function with neoadjuvant treatment and describe the morphologic and electrophysiologic characteristics of these recovered nerves. METHODS: This is a multicenter retrospective review. Descriptive analysis was conducted to examine the following parameters for recovered nerves: (1) nerve morphology, characterized as Type A (involving epineurium only) versus Type B (extending beyond epineurium); (2) proximal stimulability (normal vs. abnormal vs. absent); and (3) surgical management (resection vs. preservation). RESULTS: Six subjects with unilateral VFP were identified. Median time to return of VF mobility was 3 months (range 2-13.5). All nerves (100%) were noted to have Type A morphology at surgery. Proximal stimulability was normal in four subjects (66.7%), abnormal in one (16.7%), and absent in one (16.7%). Nerves that had improvement of function through neoadjuvant therapy were able to be surgically preserved in five subjects (83.3%). CONCLUSIONS: This represents the first characterization of RLNs that have recovered function with neoadjuvant treatment of locally advanced thyroid cancer. Although much remains unknown, our findings indicate carcinomatous neural invasion is a reversible process and recovered nerves may demonstrate normal morphology and electrophysiologic activity. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:3415-3419, 2024.

Noninvasive monitoring of the vagus nerve during thyroid surgery using cutaneous adhesive and needle electrodes: What is the optimal configuration?

OBJECTIVE: Endotracheal tube (ETT) surface electrodes are used to monitor the vagus nerve (VN), recurrent laryngeal nerve (RLN), and external branch of the superior laryngeal nerve (EBSLN) during thyroid and parathyroid surgery. Alternative nerve monitoring methods are desirable when intubation under general anesthesia is not desirable or possible. In this pilot study, we compared the performance of standard ETT electrodes to four different noninvasive cutaneous recording electrode types (two adhesive electrodes and two needle electrodes) in three different orientations. METHODS: The VN was stimulated directly during thyroid and parathyroid surgery using a Prass stimulator probe. Electromyographic (EMG) responses for each patient were recorded using an ETT plus one of the following four cutaneous electrode types: large-foot adhesive, small-foot adhesive, long-needle and short-needle. Each of the four electrode types was placed in three orientations: (1) bilateral, (2) ipsilateral mediolateral, and (3) ipsilateral craniocaudal. RESULTS: Four surgical cases were utilized for data collection with the repetitive measures obtained in each subject. Bilateral electrode orientation was superior to ipsilateral craniocaudal and ipsilateral mediolateral orientations. Regardless of electrodes type, all amplitudes in the bilateral orientation were >100 µV. When placed bilaterally, the small-foot adhesive and the long-needle electrodes obtained the highest EMG amplitudes as a percentage of ETT amplitudes. CONCLUSION: Cutaneous electrodes could potentially be used to monitor the VN during thyroid and parathyroid procedures. Different electrode types vary in their ability to record amplitudes and latencies. Bilateral orientation improves EMG responses in all electrode types. Additional validation of cutaneous electrodes as an alternative noninvasive method to monitor the VN is needed.

Genetic Risk of Rheumatoid Arthritis: A Case Control Study.

Vitamin D effects are mediated by vitamin D receptors (VDRs), which are influenced by various genetic polymorphisms, including ApaI and BsmI. These polymorphisms have been linked to several diseases, including rheumatoid arthritis (RA). This study aimed to compare the frequency and association of VDR ApaI and BsmI gene polymorphisms, serum 25-hydroxy vitamin D (25-(OH)-D) levels, and calcium (Ca) levels between a RA group and a matched healthy control group. In one hundred RA patients and fifty healthy controls, the genotypes of the VDR ApaI and BsmI gene polymorphisms were analyzed using polymerase chain reaction restriction fragment length polymorphisms (PCR-RFLP). Both Serum 25-(OH)-D level and calcium level were measured in the two groups. There was no significant difference between the cases and controls regarding the VDR ApaI gene polymorphism (p = 0.89). A significant difference was observed between the cases and controls in terms of the VDR BsmI gene polymorphism (p = < 0.001). The serum levels of 25-(OH)-D and calcium were significantly lower in the RA group compared to the control group (p = 0.04 and < 0.001 respectively). Significantly higher serum vitamin D levels were associated with the aa genotype (p = 0.007). Significantly increased calcium levels were associated with the AA genotype (p = 0.02). No significant difference was found among BsmI polymorphisms regarding vitamin D and Ca levels (p = 0.25 and 0.87 respectively). Vitamin D receptor gene BsmI polymorphism but not ApaI polymorphism could be a marker of RA susceptibility. Vitamin D and Ca levels are negatively affected by RA. Vitamin D receptor gene ApaI polymorphism contributes to vitamin D and Ca levels.

AI-driven Discovery of Celecoxib and Dexamethasone for Exploring their Mode of Action as Human Interleukin (IL-6) Inhibitors to Treat COVID-19-induced Cytokine Storm in Humans.

BACKGROUND: In the case of COVID-19 patients, it has been observed that the immune system of the infected person exhibits an extreme inflammatory response known as cytokine release syndrome (CRS) where the inflammatory cytokines are swiftly produced in quite large amounts in response to infective stimuli. Numerous case studies of COVID-19 patients with severe symptoms have documented the presence of higher plasma concentrations of human interleukin-6 (IL-6), which suggests that IL-6 is a crucial factor in the pathophysiology of the disease. In order to prevent CRS in COVID-19 patients, the drugs that can exhibit binding interactions with IL-6 and block the signaling pathways to decrease the IL-6 activity may be repurposed. METHODS: This research work focused on molecular docking-based screening of the drugs celecoxib (CXB) and dexamethasone (DME) to explore their potential to interact with the binding sites of IL-6 protein and reduce the hyper-activation of IL-6 in the infected personnel. RESULTS: Both of the drugs were observed to bind with the IL-6 (IL-6 receptor alpha chain) and IL-6Rα receptor with the respective affinities of -7.3 kcal/mol and -6.3 kcal/mol, respectively, for CXB and DME. Moreover, various types of binding interactions of the drugs with the target proteins were also observed in the docking studies. The dynamic behaviors of IL-6/IL-6Rα in complex with the drugs were also explored through molecular dynamics simulation analysis. The results indicated significant stabilities of the acquired drug-protein complexes up to 100 ns. CONCLUSION: The findings of this study have suggested the potential of the drugs studied to be utilized as antagonists for countering CRS in COVID-19 ailment. This study presents the studied drugs as promising candidates both for the clinical and pre-clinical treatment of COVID-19.

Significant role of some miRNAs as biomarkers for the degree of obesity.

BACKGROUND: Obesity is one of the most serious problems over the world. MicroRNAs have developed as main mediators of metabolic processes, playing significant roles in physiological processes. Thus, the present study aimed to evaluate the expressions of (miR-15a, miR-Let7, miR-344, and miR-365) and its relationship with the different classes in obese patients. METHODS: A total of 125 individuals were enrolled in the study and classified into four groups: healthy non-obese controls (n = 50), obese class I (n = 24), obese class II (n = 17), and obese class III (n = 34) concerning body mass index (BMI < 30 kg/m2, BMI 30-34.9 kg/m2, BMI 35-39.9 kg/m2 and BMI ≥ 40 kg/m2, respectively). BMI and the biochemical measurements (fasting glucose, total cholesterol, triglycerides, HDL and LDL, urea, creatinine, AST, and ALT) were determined. The expressions of (miR-15a, miR-Let7, miR-344, and miR-365) were detected through quantitative real-time PCR (RT-qPCR). RESULTS: There was a significant difference between different obese classes and controls (P < 0.05) concerning (BMI, TC, TG, HDL, and LDL). In contrast, fasting glucose, kidney, and liver functions had no significant difference. Our data revealed that the expression of miR-15a and miR-365 were significantly associated with different obese classes. But the circulating miR-Let7 and miR-344 were not significantly related to obesity in different classes. CONCLUSION: Our study indicated that miR-15a and miR-365 might consider as biomarkers for the obesity development into different obese classes. Thus, the relationship between regulatory microRNAs and disease has been the object of intense investigation.

parazitCUB: An R package to streamline the process of investigating the adaptations of parasites' codon usage bias.

Examining the intricate association between parasites and their hosts, particularly at the codon level, assumes paramount importance in comprehending evolutionary processes and forecasting the characteristics of novel parasites. While diverse metrics and statistical analyses are available to explore codon usage bias (CUB), there presently exists no dedicated tool for examining the co-adaptation of codon usage between parasites and hosts. Therefore, we introduce the parazitCUB R package to address this challenge in a scalable and efficient manner, as it is capable of handling extensive datasets and simultaneously analyzing of multiple parasites with optimized performance. parazitCUB enables the elucidation of parasite-host interactions and the evolutionary patterns of parasites through the implementation of various indices, cluster analysis, multivariate analysis, and data visualization techniques. The tool can be accessed at the following location: https://github.com/AliYoussef96/parazitCUB.

Genetic clues to COVID-19 severity: exploring the stromal cell-derived factor-1/CXCL12 rs2839693 polymorphism in adult Egyptians.

BACKGROUND: A novel corona virus called SARS-CoV-2 was identified at the end of December 2019, and the illness induced by it was designated as coronavirus disease 2019 (COVID-19). Severity of the disease could vary significantly since most of the infected individuals experience mild to moderate respiratory symptoms and recover without specialized care. Genetic polymorphisms have implications in influencing the varying degrees of COVID-19 severity. This study aims to assess the potential association between the CXCL12 rs2839693 polymorphism and the severity of COVID-19 in Assiut University Quarantine Hospital during the period from May 2022 to August 2022. METHODS: The present study is a cross-sectional study and is applied to 300 COVID-19 patients confirmed by RT-PCR admitted to Assiut University Quarantine Hospital from May 2022 to August 2022. Based on the clinical symptoms, the recruited participants had been divided into two groups. Group I involved mild or moderate cases; Group II involved severe or critical conditions. The rs2839693 polymorphism was detected by real time PCR using TaqMan assay probe. RESULTS: The frequency of the T allele and the TT genotype was significantly higher in the severe or critical group compared with the mild or moderate group (p value < 0.001). C-reactive protein (CRP) and D-dimers are significantly elevated in the combined variants (CT + TT) and the TT compared with the CC (P value 0.006 and 0.017 respectively) and the CC,CT genotypes (p value 0.019 and 0.002 respectively). The combined variants (CT + TT) of CXCL12 were found to be independent predictors to severe or critical COVID-19 risk with P value = < 0.001, OR = 3.034& 95% CI = 1.805-5.098. CONCLUSION: Our findings revealed that CXCL12 rs2839693 had a role in the development and seriousness of COVID-19. Patients with the TT genotype or the T allele at increased risk developed severe or critical rather than mild or moderate disease.

Biochemical markers and FokI and TaqI vitamin D receptor genes polymorphism in rheumatoid arthritis.

BACKGROUND: Previous studies have reported the role of genes in different metabolic processes in the human body, and any variation in gene polymorphisms could lead to disturbances in these processes and different diseases. OBJECTIVE: This study aimed to compare vitamin D receptor (VDR) FokI and TaqI genotypes in terms of parathyroid hormone (PTH) and some biomarkers of inflammation and susceptibility to rheumatoid arthritis (RA) disease. METHODS: This study included 100 patients with rheumatoid arthritis (RA). Genotyping was performed by polymerase chain reaction (PCR) and examined by specific restriction enzymes using restriction fragment length polymorphism (RFLP). Serum intact PTH, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), rheumatoid factor (RF), and anti-cyclic citrullinated peptide antibodies (ACCPs) levels were measured. RESULTS: An increased PTH level (> 65 pg/ml) was found in 8% of patients. No significant differences among FokI and TaqI vitamin D receptor genes polymorphism regarding positive and negative RF or ACCPs were found. A significant difference was found among FokI (p = 0.009) and none in TaqI genotypes regarding intact parathyroid hormone level categories. No significant correlation was found between the serum intact PTH level and ESR or CRP levels (P = 0.13 and 0.28, respectively). The parathyroid hormone level was not a good predictor for RF or ACCPs (P = 0.5 and 0.06, respectively). CONCLUSION: The FokI gene may play a role in controlling PTH levels in patients with RA. There was no significant correlation found between the serum intact PTH level and RA severity according to ESR and CRP inflammatory biomarkers. There are no differences between VDR genes FokI and TaqI polymorphism in terms of RA susceptibility (for RF and ACCPs).

The role of miRNAs in multiple sclerosis pathogenesis, diagnosis, and therapeutic resistance.

In recent years, microRNAs (miRNAs) have gained increased attention from researchers around the globe. Although it is twenty nucleotides long, it can modulate several gene targets simultaneously. Their mal expression is a signature of various pathologies, and they provide the foundation to elucidate the molecular mechanisms of each pathology. Among the debilitating central nervous system (CNS) disorders with a growing prevalence globally is the multiple sclerosis (MS). Moreover, the diagnosis of MS is challenging due to the lack of disease-specific biomarkers, and the diagnosis mainly depends on ruling out other disabilities. MS could adversely affect patients' lives through its progression, and only symptomatic treatments are available as therapeutic options, but an exact cure is yet unavailable. Consequently, this review hopes to further the study of the biological features of miRNAs in MS and explore their potential as a therapeutic target.

Some genetic differences in patients with rheumatoid arthritis.

OBJECTIVE: Vitamin D is important for bone and cartilage metabolism. Changes in vitamin D blood level may be related to pathological disorders such as rheumatoid arthritis (RA). The main aim of this study is to investigate the association between RA and the vitamin D receptor (VDR) genes FokI and TaqI polymorphisms. One hundred RA patients and fifty healthy matched controls were assessed for VDR FokI and TaqI genotyping. Intact parathyroid hormone (PTH) and calcium (Ca) levels were measured, categorized, and compared between the cases and control groups. RESULTS: We found that the FokI genotype frequencies for the RA cases and control groups were FF:Ff:ff = 46%:52%:2% and 50%:50%:0%, respectively (P = 0.76). The TaqI genotype frequencies for the RA cases and control groups were TT:Tt:tt = 45%:44%:11% and 42%:42%:16%, respectively (P = 0.69). A statistically significant high serum PTH level was associated with the ff genotype (p = 0.03), and a significantly low serum Ca level was associated with the TT genotype (p = 0.003). In comparison with controls, no influence of VDR FokI and TaqI genotypes on RA susceptibility or risk was demonstrated.

SLAV-Sim: A Framework for Self-Learning Autonomous Vehicle Simulation.

With the advent of autonomous vehicles, sensors and algorithm testing have become crucial parts of the autonomous vehicle development cycle. Having access to real-world sensors and vehicles is a dream for researchers and small-scale original equipment manufacturers (OEMs) due to the software and hardware development life-cycle duration and high costs. Therefore, simulator-based virtual testing has gained traction over the years as the preferred testing method due to its low cost, efficiency, and effectiveness in executing a wide range of testing scenarios. Companies like ANSYS and NVIDIA have come up with robust simulators, and open-source simulators such as CARLA have also populated the market. However, there is a lack of lightweight and simple simulators catering to specific test cases. In this paper, we introduce the SLAV-Sim, a lightweight simulator that specifically trains the behaviour of a self-learning autonomous vehicle. This simulator has been created using the Unity engine and provides an end-to-end virtual testing framework for different reinforcement learning (RL) algorithms in a variety of scenarios using camera sensors and raycasts.