Cancer causes a considerable amount of mortality in the world, while arthritis is an immunological dysregulation with multifactorial pathogenesis including genetic and environmental defects. Both conditions have inflammation as a part of their pathogenesis. Resistance to anticancer and disease-modifying antirheumatic drugs (DMARDs) happens frequently through the generation of energy-dependent transporters, which lead to the expulsion of cellular drug contents. Thymoquinone (TQ) is a bioactive molecule with anticancer as well as anti-inflammatory activities via the downregulation of several chemokines and cytokines. Nevertheless, the pharmacological importance and therapeutic feasibility of thymoquinone are underutilized due to intrinsic pharmacokinetics, including short half-life, inadequate biological stability, poor aqueous solubility, and low bioavailability. Owing to these pharmacokinetic limitations of TQ, nanoformulations have gained remarkable attention in recent years. Therefore, this compilation intends to critically analyze recent advancements in rheumatoid arthritis and cancer delivery of TQ. This literature search revealed that nanocarriers exhibit potential results in achieving targetability, maximizing drug internalization, as well as enhancing the anti-inflammatory and anticancer efficacy of TQ. Additionally, TQ-NPs (thymoquinone nanoparticles) as a therapeutic payload modulated autophagy as well as enhanced the potential of other drugs when given in combination. Moreover, nanoformulations improved pharmacokinetics, drug deposition, using EPR (enhanced permeability and retention) and receptor-mediated delivery, and enhanced anti-inflammatory and anticancer properties. TQ's potential to reduce metal toxicity, its clinical trials and patents have also been discussed.

Recent Findings on Thymoquinone and Its Applications as a Nanocarrier for the Treatment of Cancer and Rheumatoid Arthritis.

Objective: To determine the associated factors with mortality, in addition to age and sex, in a high-complexity hospital in Bogota, Colombia, during the first year of the pandemic. Design: A case-control study. Setting: High-complexity center above 2,640 meters above sea level (masl) in Colombia. Methods: A case-control study was conducted on 564 patients admitted to the hospital with confirmed COVID-19. Deceased patients (n: 282) and a control group (n: 282), matched by age, sex, and month of admission, were included. Clinical and paraclinical variables were retrospectively obtained by systematic revision of clinical records. Multiple imputations by chained equation (MICE) were implemented to account for missing variables. Classification and regression trees (CART) were estimated to evaluate the interaction of associated factors on admission and their role in predicting mortality during hospitalization. Results: Most of the patients included were males in the seventh decade of life. Most of the admissions occurred between July and August 2021. Surprisingly, recovered patients reported heterogeneous symptomatology, whereas deceased patients were most likely to present respiratory distress, dyspnea, and seizures on admission. In addition, the latter group exhibited a higher burden of comorbidities and alterations in laboratory parameters. After the imputation of datasets, CART analysis estimated 14 clinical profiles based on respiratory distress, LDH, dyspnea, hemoglobin, D-dimer, ferritin, blood urea nitrogen, C-reactive protein, PaO2/FiO2, dysgeusia, total bilirubin, platelets, and gastroesophageal reflux disease. The accuracy model for prediction was 85.6% (P < 0.0001). Conclusion: Multivariate analysis yielded a reliable model to predict mortality in COVID-19. This analysis revealed new interactions between clinical and paraclinical features in addition to age and sex. Furthermore, this predictive model could offer new clues for the personalized management of this condition in clinical settings. Keywords: SARS-CoV-2, COVID-19, Mortality, Predictors, Risk Factors

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Predictors of Mortality in Hospitalized Patients with COVID-19: A One-Year Case-Control Study

The purpose of this study was to determine the relationship between cadmium exposure and the likelihood of developing or exacerbating symptoms of inflammatory arthritis (IA). The study included 51 IA patients and 46 control subjects. Demographic and lifestyle data were collected. Haematological and biochemical parameters and blood cadmium levels (Cd-B) were determined. Cd-B correlated positively with age, smoking, living in a high-traffic area, and serum levels of inflammatory markers and negatively with mean corpuscular haemoglobin concentration (MCHC). The binary logistic regression model implied that high Cd-B (≥0.65 μg/L) is linked with an increased risk of IA in the studied population (odds ratio: 4.4). High levels of DNA oxidative damage marker (8-hydroxy-2’-deoxyguanosine) (≥7.66 ng/mL) and cyclooxygenase-2 (≥22.9 ng/mL) and frequent consumption of offal was also associated with increased risk of IA. High Cd-B was related to increased risk of disease symptoms onset in the group of IA patients, decreased the level of interleukin 10, and positively correlated with the disease activity. Increased Cd-B is associated with intensified inflammatory processes and decreased haemoglobin levels; in IA patients with decreased anti-inflammatory interleukin 10. These changes partly explain why cadmium exposure and a high cadmium body burden may raise the risk of IA and of disease symptoms exacerbation.

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Cadmium Body Burden and Inflammatory Arthritis: A Pilot Study in Patients from Lower Silesia, Poland

Association between serum Toll-like receptor 4 and 8-hydroxy-2′-deoxyguanosine levels with disease activity in rheumatoid arthritis patients

Background: The coronavirus disease (COVID-19) pandemic has made a great impact on health-care services. The prognosis of the severity of the disease help reduces mortality by prioritizing the allocation of hospital resources. Early mortality prediction of this disease through paramount biomarkers is the main aim of this study. Materials and Methods: In this retrospective study, a total of 205 confirmed COVID-19 patients hospitalized from June 2020 to March 2021 were included. Demographic data, important blood biomarkers levels, and patient outcomes were investigated using the machine learning and statistical tools. Results: Random forests, as the best model of mortality prediction, (Matthews correlation coefficient = 0.514), were employed to find the most relevant dataset feature associated with mortality. Aspartate aminotransferase (AST) and blood urea nitrogen (BUN) were identified as important death-related features. The decision tree method was identified the cutoff value of BUN >47 mg/dL and AST >44 U/L as decision boundaries of mortality (sensitivity = 0.4). Data mining results were compared with those obtained through the statistical tests. Statistical analyses were also determined these two factors as the most significant ones with P values of 4.4 × 10−7 and 1.6 × 10−6, respectively. The demographic trait of age and some hematological (thrombocytopenia, increased white blood cell count, neutrophils [%], RDW-CV and RDW-SD), and blood serum changes (increased creatinine, potassium, and alanine aminotransferase) were also specified as mortality-related features (P < 0.05). Conclusions: These results could be useful to physicians for the timely detection of COVID-19 patients with a higher risk of mortality and better management of hospital resources.

Identification of High Death Risk Coronavirus Disease-19 Patients using Blood Tests

Background This paper mainly focuses on patients with ruptured pulmonary Echinococcus granulosus infections (alveolar hydatid disease), who suffered from ruptured alveolar hydatid cyst. In this study we aimed to remove these ruptured central and peripheral pulmonary hydatid cysts by the bronchoscopic saline injection method (ME Hejazi method). Case description In this retrospective study, we evaluated eight patients from an endemic area who were non-surgically treated for ruptured pulmonary hydatid cysts at Imam Reza hospital between 2016-2017. By the bronchoscopic saline injection method (ME Hejazi method), we extracted the entire hydatid cysts of all patients by fiber optic bronchoscopy for the detachment of the underlying membrane from the cavity wall. There were three female and five male patients, with a mean age of 40 ± 23 years (range 17–63 years). Ruptured cysts were located in the peripheral (2) and central (6) parts of the lungs. All of our experiences have been successful without any complications and residual cyst membrane. During the follow-ups, clinical and radiological recovery were seen in these patients. Conclusions In the peripheral ruptured hydatid cysts, accurate recognition and location of the cyst is essential and the blind approach is not recommended because it needs several bronchoscopic interventions. Therefore the Hejazi method will be a beneficial and suitable alternative method for surgery in the treatment of patients with ruptured pulmonary hydatid cyst with cyst membrane adhesions.

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Saeede Maddahi

Papers

Association between serum Toll-like receptor 4 and 8-hydroxy-2′-deoxyguanosine levels with disease activity in rheumatoid arthritis patients

Identification of High Death Risk Coronavirus Disease-19 Patients using Blood Tests

Bronchoscope saline injection method (ME Hejazi Method) in ruptured peripheral and central pulmonary hydatid cysts: a case series