Fetal indusium griseum is a possible biomarker of the regularity of brain midline development in 3T MR imaging: A retrospective observational study.

INTRODUCTION: This study aimed to assess the visibility of the indusium griseum (IG) in magnetic resonance (MR) scans of the human fetal brain and to evaluate its reliability as an imaging biomarker of the normality of brain midline development. MATERIAL AND METHODS: The retrospective observational study encompassed T2-w 3T MR images from 90 post-mortem fetal brains and immunohistochemical sections from 41 fetal brains (16-40 gestational weeks) without cerebral pathology. Three raters independently inspected and evaluated the visibility of IG in post-mortem and in vivo MR scans. Weighted kappa statistics and regression analysis were used to determine inter- and intra-rater agreement and the type and strength of the association of IG visibility with gestational age. RESULTS: The visibility of the IG was the highest between the 25 and 30 gestational week period, with a very good inter-rater variability (kappa 0.623-0.709) and excellent intra-rater variability (kappa 0.81-0.93). The immunochemical analysis of the histoarchitecture of IG discloses the expression of highly hydrated extracellular molecules in IG as the substrate of higher signal intensity and best visibility of IG during the mid-fetal period. CONCLUSIONS: The knowledge of developmental brain histology and fetal age allows us to predict the IG-visibility in magnetic resonance imaging (MRI) and use it as a biomarker to evaluate the morphogenesis of the brain midline. As a biomarker, IG is significant for post-mortem pathological examination by MRI. Therefore, in the clinical in vivo imaging examination, IG should be anticipated when an assessment of the brain midline structures is needed in mid-gestation, including corpus callosum thickness measurements.

Treatment of atrial fibrillation with second-generation cryoballoon followed by contact-sensing radiofrequency catheter ablation for arrhythmia recurrences-results of a 5-year follow-up.

INTRODUCTION: The aim of this study was to report the long-term follow-up results of cryoballoon (CB) ablation in patients with atrial fibrillation. METHODS: All consecutive patients who underwent second-generation CB ablation from February 2015 to December 2017 were included in our study. In all procedures, we used a 28-mm CB placed via a single transseptal puncture guided by intracardiac ultrasound. A 20-mm octapolar intraluminal circular catheter was used for intracardiac recordings. A single 180-s freeze strategy was employed. Repeated procedures were performed with a 3D mapping system and radiofrequency catheters. RESULTS: A total of 126 patients (69.8% male, mean age 57 ± 11 years), of which 77.0% had paroxysmal atrial fibrillation (PAF), were included in the study. After a 5-year period, 52.4% of patients were in sinus rhythm without AF recurrence, off antiarrhythmic drugs. A total of 61.9% of patients were free of AF recurrence when redo PVI procedures were performed. When accounting for redo pulmonary vein isolation and antiarrhythmic drugs, a total of 73.8% of the patients were without AF recurrence in long-term follow-up. The patients who underwent redo pulmonary vein isolation procedures had statistically significant lower rates of AF recurrence (p = 0.006). In patients with PAF, long-term success rates improved from 62.9 to 79.4% for patients who underwent the redo procedure (p = 0.020). In patients with persistent atrial fibrillation (PersAF), success rates went up from 41.4 to 55.1% for patients with single or repeated PVI procedure (p = 0.071). In the whole cohort, a total of 3 (2.4%) procedure-related major complications occurred which included persistent PNP, arterial pseudoaneurysm, and arteriovenous fistula. CONCLUSION: Our data suggest a favorable long-term safety and efficacy profile of second-generation CB ablation. In the mixed paroxysmal and persistent population, up to 73.8% of patients remained free of AF recurrence in the 5-year follow-up, when accounting for redo procedures and AADs. Only 2.4% of patients experienced major complications of the ablation procedure, none with permanent sequelae.

Machine learning to optimize cerebrospinal fluid dilution for analysis of MRZH reaction.

OBJECTIVES: To create a supervised machine learning algorithm aimed at predicting an optimal cerebrospinal fluid (CSF) dilution when determining virus specific antibody indices to reduce the need for repeated tests. METHODS: The CatBoost model was trained, optimized, and tested on a dataset with five input variables: albumin quotient, immunoglobulin G (IgG) in CSF, IgG quotient (QIgG), intrathecal synthesis (ITS) and limes quotient (LIM IgG). Albumin and IgG concentrations in CSF and serum were performed by immunonephelometry on Atellica NEPH 630 (Siemens Healthineers, Erlangen, Germany) and ITS and LIM IgG were calculated according to Reiber. Concentrations of IgG antibodies to measles, rubella, varicella zoster and herpes simplex 1/2 viruses were analysed in CSF and serum by ELISA (Euroimmun, Lübeck, Germany). Optimal CSF dilution was defined for each virus and used as a classification variable while the standard operating procedure was set to start at 2×-dilution of CSF. RESULTS: The dataset included 571 samples with the imbalanced distribution of the optimal CSF dilutions: 2× dilution n=440, 3× dilution n=109, 4× dilution n=22. The optimized CatBoost model achieved an area under the curve (AUC) score of 0.971, and a test accuracy of 0.900. The model falsely classified 14 (9.9 %) samples of the testing set but reduced the need for repeated testing compared to the standard protocol by 42 %. The output of the CatBoost model is mostly dependant on the QIgG, ITS and CSF IgG variables. CONCLUSIONS: An accurate algorithm was achieved for predicting the optimal CSF dilution, which reduces the number of test repeats.

Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A Retrospective Single-Center Study.

This study aimed to explore the potential of multi-phase dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomics for classifying breast cancer surrogate subtypes. This retrospective study analyzed 360 breast cancers from 319 patients who underwent pretreatment DCE-MRI between January 2015 and January 2019. The cohort consisted of 33 triple-negative, 26 human epidermal growth factor receptor 2 (HER2)-positive, 109 luminal A-like, 144 luminal B-like HER2-negative, and 48 luminal B-like HER2-positive lesions. A total of 1781 radiomic features were extracted from manually segmented breast cancers in each DCE-MRI sequence. The model was internally validated and selected using ten times repeated five-fold cross-validation on the primary cohort, with further evaluation using a validation cohort. The most successful models were logistic regression models applied to the third post-contrast subtraction images. These models exhibited the highest area under the curve (AUC) for discriminating between luminal A like vs. others (AUC: 0.78), luminal B-like HER2 negative vs. others (AUC: 0.57), luminal B-like HER2 positive vs. others (AUC: 0.60), HER2 positive vs. others (AUC: 0.81), and triple negative vs. others (AUC: 0.83). In conclusion, the radiomic features extracted from multi-phase DCE-MRI are promising for discriminating between breast cancer subtypes. The best-performing models relied on tissue changes observed during the mid-stage of the imaging process.

Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.

The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, we present a principled veridical data science methodology for quantitative histology that shifts focus from image-level investigations towards neuron-level representations of cortical regions, with the neurons in the image as a subject of study, rather than pixel-wise image content. Our methodology relies on the automatic segmentation of neurons across whole histological sections and an extensive set of engineered features, which reflect the neuronal phenotype of individual neurons and the properties of neurons' neighborhoods. The neuron-level representations are used in an interpretable machine learning pipeline for mapping the phenotype to cortical layers. To validate our approach, we created a unique dataset of cortical layers manually annotated by three experts in neuroanatomy and histology. The presented methodology offers high interpretability of the results, providing a deeper understanding of human cortex organization, which may help formulate new scientific hypotheses, as well as to cope with systematic uncertainty in data and model predictions.

Impact of CPAP Therapy on New Inflammation Biomarkers.

Obstructive sleep apnea (OSA) is a common sleep disorder leading to increased risk of developing cardiovascular diseases (CVDs) by supporting a low-grade chronic inflammation as one of the pathological mechanisms. The continuous positive airway pressure (CPAP) device is used as an effective treatment for moderate and severe OSA. Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), white blood cell-mean platelet volume ratio (WMR), C-reactive protein-albumin ratio (CAR) and fibrinogen-albumin ratio (FAR) are new potential inflammatory biomarkers that are widely available and were shown to be possibly favorable screening or follow-up tools for moderate- or severe-grade OSA, as well as indirect indicators for cardiovascular risk. Our study evaluated the impact of CPAP therapy in patients with severe OSA and acceptable therapy adherence on NLR, PLR, WMR, FAR and CAR. Of 57 patients who were initially enrolled and had no exclusion criteria, 37 had a satisfactory CPAP adherence (usage of ≥4 h per night) after a minimum of 6 months of therapy. There was a statistically significant difference in NLR (2.122 ± 0.745 before therapy vs. 1.888 ± 0.735 after therapy) and FAR (86.445 ± 18.763 before therapy vs. 77.321 ± 19.133 after therapy) suggesting a positive effect of the CPAP therapy on chronic inflammatory states, thereby possibly reducing cardiovascular risk.

Direct Identification of Urinary Tract Pathogens by MALDI-TOF/TOF Analysis and De Novo Peptide Sequencing.

For mass spectrometry-based diagnostics of microorganisms, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used to identify urinary tract pathogens. However, it requires a lengthy culture step for accurate pathogen identification, and is limited by a relatively small number of available species in peptide spectral libraries (≤3329). Here, we propose a method for pathogen identification that overcomes the above limitations, and utilizes the MALDI-TOF/TOF MS instrument. Tandem mass spectra of the analyzed peptides were obtained by chemically activated fragmentation, which allowed mass spectrometry analysis in negative and positive ion modes. Peptide sequences were elucidated de novo, and aligned with the non-redundant National Center for Biotechnology Information Reference Sequence Database (NCBInr). For data analysis, we developed a custom program package that predicted peptide sequences from the negative and positive MS/MS spectra. The main advantage of this method over a conventional MALDI-TOF MS peptide analysis is identification in less than 24 h without a cultivation step. Compared to the limited identification with peptide spectra libraries, the NCBI database derived from genome sequencing currently contains 20,917 bacterial species, and is constantly expanding. This paper presents an accurate method that is used to identify pathogens grown on agar plates, and those isolated directly from urine samples, with high accuracy.

Percutaneous CT-Guided Bone Lesion Biopsy for Confirmation of Bone Metastases in Patients with Breast Cancer.

We aimed to determine diagnostic accuracy of CT-guided bone lesion biopsy for the confirmation of bone metastases in patients with breast cancer and assessment of hormone receptor status in metastatic tissue. A total of 56 female patients with breast cancer that underwent CT-guided biopsy of suspected bone metastasis were enrolled in this retrospective study. Three different techniques were employed to obtain samples from various sites of skeleton. Collectively, 11 true negative and 3 false negative findings were revealed. The sensitivity of CT-guided biopsy for diagnosing bone metastases was 93.6%, specificity was 100% and accuracy was 94.8%. Discordance in progesterone receptor status and complete concordance in estrogen receptor status was observed. Based on our single-center experience, bone metastasis biopsy should be routinely performed in patients with breast cancer and suspicious bone lesions, due to the impact on further treatment.

Changes in psychiatric services dynamics during the COVID-19 pandemic: Recognizing the need for resources shift.

With the significant impact of COVID-19 pandemic on the health, and the functioning of health care system, it has become increasingly important to understand changes in the ways health services were utilized and the factors influencing it. Drop in psychiatric admissions was seen during the pandemic, but also an increase in acute hospitalizations and emergency visits. Our aim was to analyze changes in out- and in-patient services utilization in the largest Croatian psychiatric institution during the first year of the pandemic, observed through the lens of the stringency index, and compare it to the pre-pandemic year. Along with an overall drop in hospitalizations, but a unit-specific rise in hospitalization, we have observed a non-significant overall drop in regular outpatient visits, and a significant drop coinciding with strictest epidemiological measures. There was also a significant increase in emergency visits coinciding with epidemiological measures that failed to return to pre-pandemic values, pointing to an expected significant and prolonged burden on emergency services. Simultaneous analysis of changing dynamics of mental health care service utilization during the pandemic helps us identify specific points of increased burden, and help us plan for early and flexible resources shift in order to adequately respond to evolving challenges.

Experiences and attitudes of medical professionals on treatment of end-of-life patients in intensive care units in the Republic of Croatia: a cross-sectional study.

BACKGROUND: Decisions about limitations of life sustaining treatments (LST) are made for end-of-life patients in intensive care units (ICUs). The aim of this research was to explore the professional and ethical attitudes and experiences of medical professionals on treatment of end-of-life patients in ICUs in the Republic of Croatia. METHODS: A cross-sectional study was conducted among physicians and nurses working in surgical, medical, neurological, and multidisciplinary ICUs in the total of 9 hospitals throughout Croatia using a questionnaire with closed and open type questions. Exploratory factor analysis was conducted to reduce data to a smaller set of summary variables. Mann-Whitney U test was used to analyse the differences between two groups and Kruskal-Wallis tests were used to analyse the differences between more than two groups. RESULTS: Less than third of participants (29.2%) stated they were included in the decision-making process, and physicians are much more included than nurses (p < 0.001). Sixty two percent of participants stated that the decision-making process took place between physicians. Eighteen percent of participants stated that 'do-not-attempt cardiopulmonary resuscitations' orders were frequently made in their ICUs. A decision to withdraw inotropes and antibiotics was frequently made as stated by 22.4% and 19.9% of participants, respectively. Withholding/withdrawing of LST were ethically acceptable to 64.2% of participants. Thirty seven percent of participants thought there was a significant difference between withholding and withdrawing LST from an ethical standpoint. Seventy-nine percent of participants stated that a verbal or written decision made by a capable patient should be respected. Physicians were more inclined to respect patient's wishes then nurses with high school education (p = 0.038). Nurses were more included in the decision-making process in neurological than in surgical, medical, or multidisciplinary ICUs (p < 0.001, p = 0.005, p = 0.023 respectively). Male participants in comparison to female (p = 0.002), and physicians in comparison to nurses with high school and college education (p < 0.001) displayed more liberal attitudes about LST limitation. CONCLUSIONS: DNACPR orders are not commonly made in Croatian ICUs, even though limitations of LST were found ethically acceptable by most of the participants. Attitudes of paternalistic and conservative nature were expected considering Croatia's geographical location in Southern Europe.

The Stereological Analysis and Spatial Distribution of Neurons in the Human Subthalamic Nucleus.

The subthalamic nucleus (STN) is a small, ovoid structure, and an important site of deep brain stimulation (DBS) for the treatment of Parkinson's disease. Although the STN is a clinically important structure, there are many unresolved issues with regard to it. These issues are especially related to the anatomical subdivision, neuronal phenotype, neuronal composition, and spatial distribution. In this study, we have examined the expression pattern of 8 neuronal markers [nNOS, NeuN, parvalbumin (PV), calbindin (CB), calretinin (CR), FOXP2, NKX2.1, and PAX6] in the adult human STN. All of the examined markers, except CB, were present in the STN. To determine the neuronal density, we have performed stereological analysis on Nissl-stained and immunohistochemical slides of positive markers. The stereology data were also used to develop a three-dimensional map of the spatial distribution of neurons within the STN. The nNOS population exhibited the largest neuronal density. The estimated total number of nNOS STN neurons is 281,308 ± 38,967 (± 13.85%). The STN neuronal subpopulations can be divided into two groups: one with a neuronal density of approximately 3,300 neurons/mm3 and the other with a neuronal density of approximately 2,200 neurons/mm3. The largest density of STN neurons was observed along the ventromedial border of the STN and the density gradually decreased toward the dorsolateral border. In this study, we have demonstrated the presence of 7 neuronal markers in the STN, three of which were not previously described in the human STN. The human STN is a collection of diverse, intermixed neuronal subpopulations, and our data, as far as the cytoarchitectonics is concerned, did not support the tripartite STN subdivision.

Developmental Differences Between the Limbic and Neocortical Telencephalic Wall: An Intrasubject Slice-Matched 3 T MRI-Histological Correlative Study in Humans.

The purpose of the study was to investigate the interrelation of the signal intensities and thicknesses of the transient developmental zones in the cingulate and neocortical telencephalic wall, using T2-weighted 3 T-magnetic resonance imaging (MRI) and histological scans from the same brain hemisphere. The study encompassed 24 postmortem fetal brains (15-35 postconceptional weeks, PCW). The measurements were performed using Fiji and NDP.view2. We found that T2w MR signal-intensity curves show a specific regional and developmental stage profile already at 15 PCW. The MRI-histological correlation reveals that the subventricular-intermediate zone (SVZ-IZ) contributes the most to the regional differences in the MRI-profile and zone thicknesses, growing by a factor of 2.01 in the cingulate, and 1.78 in the neocortical wall. The interrelations of zone or wall thicknesses, obtained by both methods, disclose a different rate and extent of shrinkage per region (highest in neocortical subplate and SVZ-IZ) and stage (highest in the early second half of fetal development), distorting the zones' proportion in histological sections. This intrasubject, slice-matched, 3 T correlative MRI-histological study provides important information about regional development of the cortical wall, critical for the design of MRI criteria for prenatal brain monitoring and early detection of cortical or other brain pathologies in human fetuses.

White matter mean diffusivity correlates with myelination in tuberous sclerosis complex.

OBJECTIVE: Diffusion tensor imaging (DTI) of the white matter is a biomarker for neurological disease burden in tuberous sclerosis complex (TSC). To clarify the basis of abnormal diffusion in TSC, we correlated ex vivo high-resolution diffusion imaging with histopathology in four tissue types: cortex, tuber, perituber, and white matter. METHODS: Surgical specimens of three children with TSC were scanned in a 3T or 7T MRI with a structural image isotropic resolution of 137-300 micron, and diffusion image isotropic resolution of 270-1,000 micron. We stained for myelin (luxol fast blue, LFB), gliosis (glial fibrillary acidic protein, GFAP), and neurons (NeuN) and registered the digitized histopathology slides (0.686 micron resolution) to MRI for visual comparison. We then performed colocalization analysis in four tissue types in each specimen. Finally, we applied a linear mixed model (LMM) for pooled analysis across the three specimens. RESULTS: In white matter and perituber regions, LFB optical density measures correlated with fractional anisotropy (FA) and inversely with mean diffusivity (MD). In white matter only, GFAP correlated with MD, and inversely with FA. In tubers and in the cortex, there was little variation in mean LFB and GFAP signal intensity, and no correlation with MRI metrics. Neuronal density correlated with MD. In the analysis of the combined specimens, the most robust correlation was between white matter MD and LFB metrics. INTERPRETATION: In TSC, diffusion imaging abnormalities in microscopic tissue types correspond to specific histopathological markers. Across all specimens, white matter diffusivity correlates with myelination.

Gene expression profiling of the dorsolateral and medial orbitofrontal cortex in schizophrenia.

Schizophrenia is a complex polygenic disorder of unknown etiology. Over 3,000 candidate genes associated with schizophrenia have been reported, most of which being mentioned only once. Alterations in cognitive processing - working memory, metacognition and mentalization - represent a core feature of schizophrenia, which indicates the involvement of the prefrontal cortex in the pathophysiology of this disorder. Hence we compared the gene expression in postmortem tissue from the left and right dorsolateral prefrontal cortex (DLPFC, Brodmann's area 46), and the medial part of the orbitofrontal cortex (MOFC, Brodmann's area 11/12), in six patients with schizophrenia and six control brains. Although in the past decade several studies performed transcriptome profiling in schizophrenia, this is the first study to investigate both hemispheres, providing new knowledge about possible brain asymmetry at the level of gene expression and its relation to schizophrenia. We found that in the left hemisphere, twelve genes from the DLPFC and eight genes from the MOFC were differentially expressed in patients with schizophrenia compared to controls. In the right hemisphere there was only one gene differentially expressed in the MOFC. We reproduce the involvement of previously reported genes TARDBP and HNRNPC in the pathogenesis of schizophrenia, and report seven novel genes: SART1, KAT7, C1D, NPM1, EVI2A, XGY2, and TTTY15. As the differentially expressed genes only partially overlap with previous studies that analyzed other brain regions, our findings indicate the importance of considering prefrontal cortical regions, especially those in the left hemisphere, for obtaining disease-relevant insights.