Cerebral ischemia–reperfusion (I/R) injury occurs due to the restoration of blood perfusion after cerebral ischemia, which results in the damage of the brain structures and functions. Unfortunately, currently there are no effective methods for preventing and treating it. The pumilio 2 (PUM2) is a type of RBPs that has been reported to participate in the progression of several diseases. Ferroptosis is reported to be involved in I/R injury. Whether PUM2 modulated I/R injury through regulating ferroptosis remains to be elucidated. The cerebral I/R models including animal middle cerebral artery occlusion/reperfusion (MCAO/R) model and oxygen–glucose deprivation/reperfusion (OGD/R)-induced cortical neuron injury cell model of were established and, respectively. RT-qPCR was applied for evaluating PUM2, SIRT1 and SLC7A11 expression. Western blot was employed for measuring the protein expression levels. The viability of cortical neurons was tested by MTT assay. The histological damage of the brain tissues was assessed by H&E staining. The level of PUM2 was boosted in both the brain tissues of the MCAO model and OGD/R-induced cortical neuron injury model. Silence of PUM2 alleviated MCAO-induced brain injury and decreased the death of PC12 cell exposed to OGD/R. PUM2 also aggravated the accumulation of free iron in MCAO mice and OGD/R-induced cortical neuron injury model. In addition, PUM2 suppressed SLC7A11 via inhibiting expression of SIRT1. Rescue assays unveiled that downregulation of SLC7A11 reversed PUM2 mediated neuroinflammation and brain damage induced by I/R. PUM2 aggravated I/R-induced neuroinflammation and brain damage through the SLC7A11-dependent inhibition of ferroptosis by suppressing SIRT1, highlighting the role of PUM2 in preventing or treating cerebral I/R injury.

Rationale: To define an [¹⁸F]-FDG PET/MR enterography index as a hybrid surrogate marker for active ileocolonic inflammation in Crohn’s disease (CD) and assess its diagnostic performance in comparison to validated MR indices (MaRIA, Clermont score). Methods: 52 CD patients with recurrent symptoms underwent ileocolonoscopy and [¹⁸F]-FDG PET/MR enterography. 303 ileocolonic segments were analyzed for assessment of inflammation utilizing the MaRIA and Clermont score as well as the newly defined PET-MR index. Based on tobit regression the PET-MR index was defined as 0.87*wall thickness + 1.97*edema + 0.83*ulceration + 0.55*SUV_max_ratio+ 1.14. The endoscopic activity of inflammation was determined by the Simplified Endoscopic Activity Score for CD (SES-CD). Receiver Operating Characteristic (ROC) curves for each surrogate marker were performed and tested against each other utilizing the DeLong’ test and diagnostic accuracies were compared using the McNemar test. Correlations between surrogate markers and SES-CD were tested with Spearman’s rank correlation test. Results: The PET-MR index showed a comparable sensitivity but a significantly higher specificity and accuracy than MaRIA and Clermont in prediciting both active and severe inflammation (active inflammation: specificities 0.933, 0.711, 0.707 and accuracies 0.921, 0.739, 0.736, P < 0.001; severe inflammation: specificities 0.91, 0.81, 0.785 and accuracies 0.914, 0.818, 0.795, P < 0.01, respectively). All surrogate markers correlated moderately with SES-CD on segmental basis and gobal level (0.5 < ρ < 0.7, all P < 0.001). Conclusion: As a hybrid surrogate marker comprised of MR parameters and the PET component, the PET-MR index yielded significantly improved specificity and diagnostic accuracy compared to conventional MR indices (MaRIA and Clermont), demonstrating its high potential for non-invasive assessment of CD.

Objective: To investigate a Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak event involving multiple healthcare facilities in Riyadh, Saudi Arabia; to characterize transmission; and to explore infection control implications.Design: Outbreak investigation.Setting: Cases presented in 4 healthcare facilities in Riyadh, Saudi Arabia: a tertiary-care hospital, a specialty pulmonary hospital, an outpatient clinic, and an outpatient dialysis unit.Methods: Contact tracing and testing were performed following reports of cases at 2 hospitals. Laboratory results were confirmed by real-time reverse transcription polymerase chain reaction (rRT-PCR) and/or genome sequencing. We assessed exposures and determined seropositivity among available healthcare personnel (HCP) cases and HCP contacts of cases.Results: In total, 48 cases were identified, involving patients, HCP, and family members across 2 hospitals, an outpatient clinic, and a dialysis clinic. At each hospital, transmission was linked to a unique index case. Moreover, 4 cases were associated with superspreading events (any interaction where a case patient transmitted to ≥5 subsequent case patients). All 4 of these patients were severely ill, were initially not recognized as MERS-CoV cases, and subsequently died. Genomic sequences clustered separately, suggesting 2 distinct outbreaks. Overall, 4 (24%) of 17 HCP cases and 3 (3%) of 114 HCP contacts of cases were seropositive.Conclusions: We describe 2 distinct healthcare-associated outbreaks, each initiated by a unique index case and characterized by multiple superspreading events. Delays in recognition and in subsequent implementation of control measures contributed to secondary transmission. Prompt contact tracing, repeated testing, HCP furloughing, and implementation of recommended transmission-based precautions for suspected cases ultimately halted transmission.

Short tau inversion recovery (STIR) sequences are frequently used in magnetic resonance imaging (MRI) of the spine. However, STIR sequences require a significant amount of scanning time. The purpose of the present study was to generate virtual STIR (vSTIR) images from non-contrast, non-fat-suppressed T1- and T2-weighted images using a conditional generative adversarial network (cGAN). The training dataset comprised 612 studies from 514 patients, and the validation dataset comprised 141 studies from 133 patients. For validation, 100 original STIR and respective vSTIR series were presented to six senior radiologists (blinded for the STIR type) in independent A/B-testing sessions. Additionally, for 141 real or vSTIR sequences, the testers were required to produce a structured report of 15 different findings. In the A/B-test, most testers could not reliably identify the real STIR (mean error of tester 1–6: 41%; 44%; 58%; 48%; 39%; 45%). In the evaluation of the structured reports, vSTIR was equivalent to real STIR in 13 of 15 categories. In the category of the number of STIR hyperintense vertebral bodies (p = 0.08) and in the diagnosis of bone metastases (p = 0.055), the vSTIR was only slightly insignificantly equivalent. By virtually generating STIR images of diagnostic quality from T1- and T2-weighted images using a cGAN, one can shorten examination times and increase throughput.