children: differentiation using diffusion-weighted magnetic resonance imaging

Purpose To evaluate differences in magnetic resonance imaging (MRI) appearance between infantile hemangiomas and rhabdomyosarcomas of the orbit in pediatric patients using diffusion-weighted imaging. Methods A multicenter retrospective review of MRIs of pediatric patients with infantile hemangiomas and rhabdomyosarcomas of the orbit was performed. MRI examinations from a total of 21 patients with infantile hemangiomas and 12 patients with rhabdomyosarcomas of the orbit were independently reviewed by two subspecialty board-certified neuroradiologists masked to the diagnosis. A freehand region of interest was placed in the mass to obtain the mean apparent diffusion coefficient (ADC) value of the mass as well as within the medulla to obtain a ratio of the ADC mass to the medulla. A t test was used to compare mean ADC and ADC ratios between the two groups. Receiver operating characteristic analysis was performed to determine ADC value and ADC ratio thresholds for differentiation of infantile hemangioma and rhabdomyosarcoma. Results There was a statistically significant difference in the mean ADC value of infantile hemangiomas compared to rhabdomyosarcomas (1527 × 10−6 mm2/s vs 782 × 10−6 mm2/s; P = 0.0001) and the ADC ratio of the lesion to the medulla (1.77 vs 0.92; P = 0.0001). An ADC threshold of <1159 × 10−6 mm2/sec and an ADC ratio of <1.38 differentiated rhabdomyosarcoma from infantile hemangioma (sensitivity 100% and 100%; specificity 100% and 100%) with area under the curve of 1.0 and 1.0, respectively. Conclusions In conjunction with conventional MRI sequences, ADC values obtained from diffusion-weighted MRI are useful to differentiate orbital infantile hemangiomas from rhabdomyosarcomas in pediatric patients

Harmonized human biomonitoring in European children, teenagers and adults: EU-wide exposure data of 11 chemical substance groups from the HBM4EU Aligned Studies (2014-2021)

As one of the core elements of the European Human Biomonitoring Initiative (HBM4EU) a human biomonitoring (HBM) survey was conducted in 23 countries to generate EU-wide comparable HBM data. This survey has built on existing HBM capacity in Europe by aligning national or regional HBM studies, referred to as the HBM4EU Aligned Studies. The HBM4EU Aligned Studies included a total of 10,795 participants of three age groups: (i) 3,576 children aged 6-12 years, (ii) 3,117 teenagers aged 12-18 years and (iii) 4,102 young adults aged 20-39 years. The participants were recruited between 2014 and 2021 in 11-12 countries per age group, geographically distributed across Europe. Depending on the age group, internal exposure to phthalates and the substitute DINCH, halogenated and organophosphorus flame retardants, per- and polyfluoroalkyl substances (PFASs), cadmium, bisphenols, polycyclic aromatic hydrocarbons (PAHs), arsenic species, acrylamide, mycotoxins (deoxynivalenol (total DON)), benzophenones and selected pesticides was assessed by measuring substance specific biomarkers subjected to stringent quality control programs for chemical analysis. For substance groups analyzed in different age groups higher average exposure levels were observed in the youngest age group, i.e., phthalates/DINCH in children versus teenagers, acrylamide and pesticides in children versus adults, benzophenones in teenagers versus adults. Many biomarkers in teenagers and adults varied significantly according to educational attainment, with higher exposure levels of bisphenols, phthalates, benzophenones, PAHs and acrylamide in participants (from households) with lower educational attainment, while teenagers from households with higher educational attainment have higher exposure levels for PFASs and arsenic. In children, a social gradient was only observed for the non-specific pyrethroid metabolite 3-PBA and di-isodecyl phthalate (DiDP), with higher levels in children from households with higher educational attainment. Geographical variations were seen for all exposure biomarkers. For 15 biomarkers, the available health-based HBM guidance values were exceeded with highest exceedance rates for toxicologically relevant arsenic in teenagers (40%), 3-PBA in children (36%), and between 11 and 14% for total DON, Sigma (PFOA + PFNA + PFHxS + PFOS), bisphenol S and cadmium. The infrastructure and harmonized approach succeeded in obtaining comparable European wide internal exposure data for a prioritized set of 11 chemical groups. These data serve as a reference for comparison at the global level, provide a baseline to compare the efficacy of the European Commission's chemical strategy for sustainability and will give leverage to national policy makers for the implementation of targeted measures

Harmonized human biomonitoring in European children, teenagers and adults: EU-wide exposure data of 11 chemical substance groups from the HBM4EU Aligned Studies (2014–2021)

As one of the core elements of the European Human Biomonitoring Initiative (HBM4EU) a human biomonitoring (HBM) survey was conducted in 23 countries to generate EU-wide comparable HBM data. This survey has built on existing HBM capacity in Europe by aligning national or regional HBM studies, referred to as the HBM4EU Aligned Studies. The HBM4EU Aligned Studies included a total of 10,795 participants of three age groups: (i) 3,576 children aged 6–12 years, (ii) 3,117 teenagers aged 12–18 years and (iii) 4,102 young adults aged 20–39 years. The participants were recruited between 2014 and 2021 in 11–12 countries per age group, geographically distributed across Europe. Depending on the age group, internal exposure to phthalates and the substitute DINCH, halogenated and organophosphorus flame retardants, per- and polyfluoroalkyl substances (PFASs), cadmium, bisphenols, polycyclic aromatic hydrocarbons (PAHs), arsenic species, acrylamide, mycotoxins (deoxynivalenol (total DON)), benzophenones and selected pesticides was assessed by measuring substance specific biomarkers subjected to stringent quality control programs for chemical analysis. For substance groups analyzed in different age groups higher average exposure levels were observed in the youngest age group, i.e., phthalates/DINCH in children versus teenagers, acrylamide and pesticides in children versus adults, benzophenones in teenagers versus adults. Many biomarkers in teenagers and adults varied significantly according to educational attainment, with higher exposure levels of bisphenols, phthalates, benzophenones, PAHs and acrylamide in participants (from households) with lower educational attainment, while teenagers from households with higher educational attainment have higher exposure levels for PFASs and arsenic. In children, a social gradient was only observed for the non-specific pyrethroid metabolite 3-PBA and di-isodecyl phthalate (DiDP), with higher levels in children from households with higher educational attainment. Geographical variations were seen for all exposure biomarkers. For 15 biomarkers, the available health-based HBM guidance values were exceeded with highest exceedance rates for toxicologically relevant arsenic in teenagers (40%), 3-PBA in children (36%), and between 11 and 14% for total DON, Σ (PFOA + PFNA + PFHxS + PFOS), bisphenol S and cadmium. The infrastructure and harmonized approach succeeded in obtaining comparable European wide internal exposure data for a prioritized set of 11 chemical groups. These data serve as a reference for comparison at the global level, provide a baseline to compare the efficacy of the European Commission's chemical strategy for sustainability and will give leverage to national policy makers for the implementation of targeted measures

Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE

Brave New World: 3D Printing of the Orbit for Anatomy, Pathology, Surgical Simulation (.pdf)

3-Dimensional printing (3D printing), or additive manufacturing, is a novel technique used for rapidly producing physical models of complex structures. These physical models can be used to teach anatomy, simulate procedures, or test surgical anatomical approaches. This project explores the application of 3D printing to ophthalmologic disease. 3D printing has become more affordable and applicable to the clinical setting. Complex orbital anatomy and pathology can be evaluated using a multifaceted approach. We propose a paradigm to create orbital models to teach anatomy and demonstrate pathologies: thyroid related eye disease, idiopathic orbital inflammatory disease, neoplasm, and maxillofacial trauma.Purpose:To demonstrate how 3D printing can be used to produce physical orbit models for the teaching of orbital anatomy, demonstrating pathology, and simulating surgical and interventional procedures

Neuro-Ophthalmologic Monitoring in the Management of Increased Intracranial Pressure From Leaking Arachnoid Cysts

Intracranial arachnoid cysts are common incidental imaging findings. They may rarely rupture, leading to the development of subdural hygromas and high intracranial pressure (ICP). Neurosurgical intervention has been advocated in the past, but recent evidence indicates that most cases resolve spontaneously. The role of neuro-ophthalmologic monitoring in identifying the few cases that have persisting vision-threatening papilledema that justifies intervention has not been emphasized

Modulation of SLFN11 induces changes in DNA Damage response in breast cancer

Abstract Background Lack of Schlafen family member 11 (SLFN11) expression has been recently identified as a dominant genomic determinant of response to DNA damaging agents in numerous cancer types. Thus, several strategies aimed at increasing SLFN11 are explored to restore chemosensitivity of refractory cancers. In this study, we examined various approaches to elevate SLFN11 expression in breast cancer cellular models and confirmed a corresponding increase in chemosensitivity with using the most successful efficient one. As oncogenic transcriptomic downregulation is often driven by methylation of the promotor region, we explore the demethylation effect of 5-aza-2′-deoxycytidine (decitabine), on the SLFN11 gene. Since SLFN11 has been reported as an interferon inducible gene, and interferon is secreted during an active anti-tumor immune response, we investigated the in vitro effect of IFN-γ on SLFN11 expression in breast cancer cell lines. As a secondary approach to pick up cross talk between immune cells and SLFN11 expression we used indirect co-culture of breast cancer cells with activated PBMCs and evaluated if this can drive SLFN11 upregulation. Finally, as a definitive and specific way to modulate SLFN11 expression we implemented SLFN11 dCas9 (dead CRISPR associated protein 9) systems to specifically increase or decrease SLFN11 expression. Results After confirming the previously reported correlation between methylation of SLFN11 promoter and its expression across multiple cell lines, we showed in-vitro that decitabine and IFN-γ could increase moderately the expression of SLFN11 in both BT-549 and T47D cell lines. The use of a CRISPR-dCas9 UNISAM and KRAB system could increase or decrease SLFN11 expression significantly (up to fivefold), stably and specifically in BT-549 and T47D cancer cell lines. We then used the modified cell lines to quantify the alteration in chemo sensitivity of those cells to treatment with DNA Damaging Agents (DDAs) such as Cisplatin and Epirubicin or DNA Damage Response (DDRs) drugs like Olaparib. RNAseq was used to elucidate the mechanisms of action affected by the alteration in SLFN11 expression. In cell lines with robust SLFN11 promoter methylation such as MDA-MB-231, no SLFN11 expression could be induced by any approach. Conclusion To our knowledge this is the first report of the stable non-lethal increase of SLFN11 expression in a cancer cell line. Our results show that induction of SLFN11 expression can enhance DDA and DDR sensitivity in breast cancer cells and dCas9 systems may represent a novel approach to increase SLFN11 and achieve higher sensitivity to chemotherapeutic agents, improving outcome or decreasing required drug concentrations. SLFN11-targeting therapies might be explored pre-clinically to develop personalized approaches

Additional file 1 of Modulation of SLFN11 induces changes in DNA Damage response in breast cancer

Additional file 1: gRNA location and CRISPR modification. (Fig. S1A) The predicted promoter region of SLFN11 (in green) is surrounding the gene’s exon1 and CpG island (in red) analysis show its location in the center of the promoter area. gRNAs were therefore designed along the central region of the promoter of SLFN11 (N1 to N10). (Fig. S1B) Schematic representation of the strategy adopted to respectively increase SLFN11 expression using UNISAM system and decrease SLFN11 expression using KRAB system. After insertion of the gRNA into the respective plasmids, cells were transformed with the integrative plasmids using electroporation and selected for the expression of respectively mCherry or GFP reporter genes. Cells were then analyzed for SLFN11 expression by westernblot and by Q-RT-PCR. Additional file 2: Screening of gRNA efficiency at upregulating or downregulating SLFN11 using UNISAM or KRAB systems. (Fig. S2A–Fig. S2D) Relative mRNA expression of SLFN11 analyzed by Q-RT-PCR (N = 3, technical replicates) (Fig. S2A–Fig. S2C) and relative SLFN11 protein expression analyzed by CWB (N = 2, technical replicates) (Fig. S2B–Fig. S2D) in BT-549 cancer cell lines modified with each gRNA for CRISPR-dCas9-UNISAM (Fig. S2A, Fig. S2B) or CRISPR-dCas9-KRAB (Fig. S2C, Fig. S2D) relative to non-modified cell line. (Fig. S2E–Fig. S2H) Relative mRNA expression of SLFN11 analyzed by Q-RT-PCR (N = 3, technical replicates) (Fig. S2E–Fig. S2G) and relative SLFN11 protein expression analyzed by CWB (N = 2, technical replicates) (Fig. S2F–Fig. S2H) in T47D cancer cell lines modified with each gRNA for CRISPR-dCas9-UNISAM (Fig. S2E–Fig. S2F) or 5 (N1, N2, N6, N7 and N10) of the 7 gRNA for CRISPR-dCas9-KRAB (Fig. S2G, Fig. S2H) relative to non-modified cell line. (Fig. S2I) Relative mRNA expression of SLFN11 analyzed by Q-RT-PCR in MDA-MB-231 cancer cell lines modified with each gRNA for CRISPR-dCas9-UNISAM relative to non-modified cell line. Additional file 3: Representative CWB results. (Fig. S3A) Representative CWB results of the analysis of SLFN11 protein expression in the 8 tested unmodified breast cancer cell lines compared to HFF. (Fig. S3B) Representative SLFN11 protein expression in BT-549, T47D and MDA-MB-231 analyzed by CWB after treatment with 5uM of DAC for 72 h compared to the expression level in untreated HFF. (Fig. S3C) Representative SLFN11 protein expression in BT-549, T47D and MDA-MB-231 analyzed by CWB after treatment with 5 nM of IFN-γ for 24 h compared to the expression level in untreated HFF. (Fig. S3D–Fig. S3E) Representative SLFN11 protein expression in BT-549 (D) or T47D (Fig. S3E) modified with UNISAM and each of the 7 gRNA compared to the respective unmodified cells. (Fig. S3F-Fig. S3G) Representative SLFN11 protein expression in BT-549 (Fig. S3F) or T47D (Fig. S3G) modified with KRAB and each of the 7 gRNA compared to the respective unmodified cells. (Fig. S3H-Fig. S3I) Representative SLFN11 protein expression level analyzed by CWB in BT-549 (Fig. S3H) or T47D (Fig. S3I) after modification with UNISAM (gRNA 7 or gRNA SCR) or KRAB (gRNA 7 or gRNA SCR) compared to respective unmodified cells and HFF. (Fig. S3J) Representative SLFN11 protein expression level analyzed by CWB in MDA-MB-231 after modification with UNISAM (gRNA 7) compared to respective unmodified cells and HFF. Additional file 4: Fig. S4. Principal component analysis pre and post-combat. Principal component analysis based on gene expression for all samples (baseline and cisplatin-treated samples) pre and post performing combat on samples to remove batch effect for BT-549 and T47D cell lines. Additional file 5: Fig. S5 Pathway enrichment analysis. Enriched pathways associated with DEG (n = 181, FDR   = 1) from limma analysis in UNISAM up/KRAB down and UNISAM down/KRAB up, using Ingenuity Pathway Analysis (IPA)