Neutrophils are the first cells to be recruited to sites of acute inflammation and contribute to host defense through phagocytosis, degranulation and neutrophil extracellular traps (NETs). Neutrophils are rarely found in the brain because of the highly selective blood-brain barrier (BBB). However, several diseases disrupt the BBB and cause neuroinflammation. In this regard, neutrophils and NETs have been visualized in the brain after various insults, including traumatic (traumatic brain injury and spinal cord injury), infectious (bacterial meningitis), vascular (ischemic stroke), autoimmune (systemic lupus erythematosus), neurodegenerative (multiple sclerosis and Alzheimer’s disease), and neoplastic (glioma) causes. Significantly, preventing neutrophil trafficking into the central nervous system or NET production in these diseases alleviates brain pathology and improves neurocognitive outcomes. This review summarizes the major studies on the contribution of NETs to central nervous system (CNS) disorders.

Machine learning techniques have been used extensively in the field of clinical medicine, especially when used for the construction of prediction models. The aim of the study was to use machine learning to predict the stone-free status after percutaneous nephrolithotomy (PCNL). This is a retrospective cohort study of 137 patients. Data from adult patients who underwent PCNL at our institute were used for the purpose of this study. Three supervised machine learning algorithms were employed: Logistic Regression, XGBoost Regressor, and Random Forests. A set of variables comprising independent attributes including age, gender, body mass index (BMI), chronic kidney disease (CKD), hypertension (HTN), diabetes mellitus, gout, renal and stone factors (previous surgery, stone location, size, and staghorn status), and pre-operative surgical factors (infections, stent, hemoglobin, creatinine, and bacteriuria) were entered. 137 patients were identified. The majority were males (65.4%; n = 89), aged 50 years and above (41.9%; n = 57). The stone-free status (SFS) rate was 86% (n = 118). An inverse relation was detected between SFS, and CKD and HTN. The accuracies were 71.4%, 74.5% and 75% using Logistic Regression, XGBoost, and Random Forest algorithms, respectively. Stone size, pre-operative hemoglobin, pre-operative creatinine, and stone type were the most important factors in predicting the SFS following PCNL. The Random Forest model showed the highest efficacy in predicting SFS. We developed an effective machine learning model to assist physicians and other healthcare professionals in selecting patients with renal stones who are most likely to have successful PCNL treatment based on their demographics and stone characteristics. Larger multicenter studies are needed to develop more powerful algorithms, such as deep learning and other AI subsets.

Methotrexate (MTX) is potent chemotherapeutic agent, often administered intrathecally to treat or prevent central nervous system involvement in lymphomas and leukemias, particularly T-cell lymphoblastic leukemia (T-LBL). MTX has been linked to adverse neurologic effects that mimic acute stroke, including facial drooping, hemiplegia, impaired consciousness, and seizures, as well as changes on imaging—known as MTX-induced leukoencephalopathy (LE). We report a case of a 17-year-old male diagnosed with T-LBL, who had been receiving MTX chemotherapy for 4 months. After receiving his fourth dose of MTX, he presented to the emergency department with fever, facial drooping, and acute left-sided weakness. Brain magnetic resonance imaging (MRI) revealed bilateral deep white matter T2 hyperintense foci, increased on the right, with associated diffusion restriction in the right centrum semiovale—consistent with MTX-induced LE. After his symptoms resolved, he was discharged on leucovorin. Six months afterward, he was rechallenged with MTX and developed recurrence of symptoms. Repeat MRI showed well-defined T2/FLAIR hyperintensities in the right centrum semiovale without corresponding diffusion restriction. The left centrum semiovale hyperintensity became less conspicuous in comparison to the previous MRI study. We report a rare case of recurrence of LE after MTX rechallenge and discuss mechanisms, best imaging modalities, and possible treatment options for MTX-induced LE. Given the ominous presentation of MTX-induced LE, we urge clinicians to maintain a high index of suspicion for this condition. Further research is necessary to understand why only certain patients develop recurrence of LE after subsequent doses of MTX.

Background: Policy makers in Saudi Arabia greatly rely on published studies to make major public health decisions. Prostate cancer (PCa) studies in Saudi Arabia are either outdated or limited to local regions. Aim: The authors aim to analyze the Saudi Cancer Registry to determine the incidence of PCa across all regions of the Kingdom and the risk factors of poor prognosis in the population. Methods: Patients diagnosed with primary PCa from 1 January 2008 to 31 December 2017 were included in the study from the Saudi Cancer Registry. Incidence rates and risk factors for poor survival were calculated. Results: A total of 3607 PCa patients were retrieved. PCa incidence rates ranged from 0.2 to 1.4 per 100 000. Most of the patients were aged 60 and older (86.5%; n=3120), married (97%; n=3497) and lived in the central region (38.1%; n=1375). The mean age at diagnosis was 71.1 (10.8) years. Over half of all tumors were poorly differentiated (64.2%; n=2317), and localized (60.4%; n=2180). The all-time metastasis rate reached 31.4% (n=1131). The lowest mean survival was in those with distant metastasis (P=0.039). Age groups, marital status, tumor morphology, place of residency, and grade were not proven to significantly influence survival. Conclusion: The high metastasis rate and evidence of a greater incidence of newly diagnosed metastatic PCa indicate that the idea of select screening for certain high-risk populations is not farfetched. The authors encourage the promotion of awareness regarding PCa risk factors and screening to optimize prognosis and minimize late presentations and high metastasis rates.

The majority of available data on molnupiravir come from an unvaccinated COVID-19 population. Therefore, we conducted this meta-analysis to integrate evidence from recent randomized controlled trials (RCTs) as well as observational studies stratified by vaccination status to determine the clinical efficacy and safety of molnupiravir in COVID-19 outpatients. We searched PubMed, Embase, the Cochrane Library, medRxiv, and ClinicalTrials.gov from inception to November 2023. We conducted our meta-analysis using RevMan 5.4 with risk ratio (RR) as the effect measure. We included 8 RCTs and 5 observational studies in our meta-analysis. Molnupiravir reduced the risk of all-cause mortality (RR 0.28; 95% CI: 0.20-0.79, I² = 0%) but did not decrease the hospitalization rate (RR 0.67; 95% CI: 0.45-1.00, I² = 53%) in the overall population; in the immunized population, no benefits were observed. Molnupiravir lowered the rate of no recovery (RR 0.78; 95% CI: 0.76-0.81, I² = 0%) and increased virological clearance at day 5 (RR 2.68; 95% CI: 1.94-4.22, I² = 85%). There was no increase in the incidence of adverse events. Molnupiravir does not decrease mortality and hospitalization rates in immunized patients with COVID-19. However, it does shorten the disease course and increases the recovery rate. The use of molnupiravir will need to be considered on a case-by-case basis in the context of the prevailing social circumstances, the resource setting, drug costs, and the healthcare burden.

Moyamoya syndrome (MMS) is a cerebrovascular disease characterized by stenosis of the internal carotid arteries and the formation of an abnormal vascular network at the base of the brain. MMS usually occurs secondary to various conditions, particularly Down syndrome, and sickle cell anemia, and presents with motor deficits, sensory symptoms, recurrent ischemic strokes, hemodynamic transient ischemic attacks, recurrent seizures, and hemorrhage. Trisomy 13 (Patau Syndrome) is a chromosomal abnormality that may be characterized by full or partial trisomy of chromosome 13. Phenotypic features of partial trisomy 13 include leukoencephalopathy, hippocampal hypoplasia, intellectual disability, facial anomalies, and others. Herein, we report a case of a 19-year-old female diagnosed with partial trisomy 13q, characterized by two large duplications in the 13q14 and 13q31 regions, with trisomy-induced bilateral MMS - the first known case to be discussed in literature. Particularly, our patient was identified to have a gain of 22Mb within the 13q14.11q21.31 region - a duplication that has not been described previously. Our patient suffered four strokes between the ages of 5 and 7, later developing intractable seizures, hemiplegia, spasticity in all limbs, global delay, and regression. Despite bilateral encephaloduroarteriosynangiosis and being on several antiepileptic medications, the MMS continued to progress, confounded by the partial trisomy 13. Studies must elucidate the association between mitochondrial damage and MMS, as well as mechanisms of epilepsy associated with chromosomal abnormalities, particularly in the context of underlying mitochondrial diseases.