MRI or 18F-FDG PET for Brain Age Gap Estimation: Links to Cognition, Pathology, and Alzheimer Disease Progression.

Deviations of brain age from chronologic age, known as the brain age gap (BAG), have been linked to neurodegenerative diseases such as Alzheimer disease (AD). Here, we compare the associations of MRI-derived (atrophy) or 18F-FDG PET-derived (brain metabolism) BAG with cognitive performance, neuropathologic burden, and disease progression in cognitively normal individuals (CNs) and individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Methods: Machine learning pipelines were trained to estimate brain age from 185 matched T1-weighted MRI or 18F-FDG PET scans of CN from the Alzheimer's Disease Neuroimaging Initiative and validated in external test sets from the Open Access of Imaging and German Center for Neurodegenerative Diseases-Longitudinal Cognitive Impairment and Dementia studies. BAG was correlated with measures of cognitive performance and AD neuropathology in CNs, SCD subjects, and MCI subjects. Finally, BAG was compared between cognitively stable and declining individuals and subsequently used to predict disease progression. Results: MRI (mean absolute error, 2.49 y) and 18F-FDG PET (mean absolute error, 2.60 y) both estimated chronologic age well. At the SCD stage, MRI-based BAG correlated significantly with beta-amyloid1-42 (Aß1-42) in cerebrospinal fluid, whereas 18F-FDG PET BAG correlated with memory performance. At the MCI stage, both BAGs were associated with memory and executive function performance and cerebrospinal fluid Aß1-42, but only MRI-derived BAG correlated with phosphorylated-tau181/Aß1-42 Lastly, MRI-estimated BAG predicted MCI-to-AD progression better than 18F-FDG PET-estimated BAG (areas under the curve, 0.73 and 0.60, respectively). Conclusion: Age was reliably estimated from MRI or 18F-FDG PET. MRI BAG reflected cognitive and pathologic markers of AD in SCD and MCI, whereas 18F-FDG PET BAG was sensitive mainly to early cognitive impairment, possibly constituting an independent biomarker of brain age-related changes.

Getting big but not hard: A retrospective case-study of a male powerlifter's experience of steroid-induced erectile dysfunction.

This article aims to excavate the lived experience of suffering with steroid-induced erectile dysfunction. By drawing upon original qualitative data, we chart the subjective journey to recovery of a male powerlifter and draw attention to the potential dangers of a self-help approach to treatment. Erectile dysfunction is a common symptom of anabolic-androgenic steroid-induced hypogonadism, a condition not commonly reported or discussed and is therefore a poorly studied health issue. Often considered a taboo subject, detailed accounts of men's experience of erectile dysfunction are relatively sparce, and so this paper makes an important contribution to bolstering what is a limited literature base. Links between contemporary conceptions of masculinity, muscularity, and sexual prowess are explored and form the basis of a critical analysis of popular treatment and prevention strategies. Among the central findings, this article suggests that steroids are not consumed despite the well-known risks, but precisely because the risks are well-known and ostensibly mitigated through engagement with 'bro-science'. We conclude that there is a concerning misalignment in current treatment and prevention strategies that needs to be addressed if the issue of non-prescribed steroid use is to be effectively tackled. This research therefore raises serious questions for the healthcare profession and its approach towards treating and preventing steroid consumption.

A systematic comparison of VBM pipelines and their application to age prediction.

Voxel-based morphometry (VBM) analysis is commonly used for localized quantification of gray matter volume (GMV). Several alternatives exist to implement a VBM pipeline. However, how these alternatives compare and their utility in applications, such as the estimation of aging effects, remain largely unclear. This leaves researchers wondering which VBM pipeline they should use for their project. In this study, we took a user-centric perspective and systematically compared five VBM pipelines, together with registration to either a general or a study-specific template, utilizing three large datasets (n>500 each). Considering the known effect of aging on GMV, we first compared the pipelines in their ability of individual-level age prediction and found markedly varied results. To examine whether these results arise from systematic differences between the pipelines, we classified them based on their GMVs, resulting in near-perfect accuracy. To gain deeper insights, we examined the impact of different VBM steps using the region-wise similarity between pipelines. The results revealed marked differences, largely driven by segmentation and registration steps. We observed large variability in subject-identification accuracies, highlighting the interpipeline differences in individual-level quantification of GMV. As a biologically meaningful criterion we correlated regional GMV with age. The results were in line with the age-prediction analysis, and two pipelines, CAT and the combination of fMRIPrep for tissue characterization with FSL for registration, reflected age information better.

Irregular migration in the time of counter-smuggling.

This special issue of Trends in Organized Crime brings together recent empirical research on migrant smuggling. Challenging the overemphasis on 'organized crime' and criminal networks that has long characterized mainstream discussions on smuggling, the contributions refocus our attention towards critical but underexamined dynamics present in the facilitation of irregular migration in a variety of geographic contexts, and shed light on the roles lesser examined elements in smuggling like race, ethnicity, gender, sex and intimacy play in irregular migration.

Brain-age prediction: A systematic comparison of machine learning workflows.

The difference between age predicted using anatomical brain scans and chronological age, i.e., the brain-age delta, provides a proxy for atypical aging. Various data representations and machine learning (ML) algorithms have been used for brain-age estimation. However, how these choices compare on performance criteria important for real-world applications, such as; (1) within-dataset accuracy, (2) cross-dataset generalization, (3) test-retest reliability, and (4) longitudinal consistency, remains uncharacterized. We evaluated 128 workflows consisting of 16 feature representations derived from gray matter (GM) images and eight ML algorithms with diverse inductive biases. Using four large neuroimaging databases covering the adult lifespan (total N = 2953, 18-88 years), we followed a systematic model selection procedure by sequentially applying stringent criteria. The 128 workflows showed a within-dataset mean absolute error (MAE) between 4.73-8.38 years, from which 32 broadly sampled workflows showed a cross-dataset MAE between 5.23-8.98 years. The test-retest reliability and longitudinal consistency of the top 10 workflows were comparable. The choice of feature representation and the ML algorithm both affected the performance. Specifically, voxel-wise feature spaces (smoothed and resampled), with and without principal components analysis, with non-linear and kernel-based ML algorithms performed well. Strikingly, the correlation of brain-age delta with behavioral measures disagreed between within-dataset and cross-dataset predictions. Application of the best-performing workflow on the ADNI sample showed a significantly higher brain-age delta in Alzheimer's and mild cognitive impairment patients compared to healthy controls. However, in the presence of age bias, the delta estimates in the patients varied depending on the sample used for bias correction. Taken together, brain-age shows promise, but further evaluation and improvements are needed for its real-world application.

COVID-19 and organized crime: an introduction to the special issue.

This is an introduction to the articles submitted to the special issue of Trends in Organized Crime on 'COVID-19 and Organized Crime'. The aim of the special issue is to draw together a range of empirical studies from around the world to explore the implications of the COVID-19 pandemic for both organized criminals and law enforcement agencies. The pandemic required organized criminals to adapt their practice in light of government restrictions, but it also created new profitable opportunities. At the same time, however, COVID-19 posed significant challenges for law enforcement.

Three-Dimensional Printing Technology in Orthodontics for Dental Models: A Systematic Review.

BACKGROUND: Three-dimensional printing technology is an additive manufacturing technology that is used to reconstruct 3D objects. In the last decade, it has been rapidly involved in dentistry and in orthodontics. This article aims to review the literature and present the accuracy of different 3D printer types and any factors that could affect the 3D printing of dental models in the orthodontic field. METHODS: The search strategy of this systematic review included keywords in combination with MeSH terms in Medline, Scopus, and Cochrane Library until June 2022 and only in English. RESULTS: Eleven articles were selected for our study. All the articles were in vitro prospective studies, and they presented a low risk of bias. The results suggested that the accuracy of a printed dental cast can be affected by the different types of 3D technologies, the dental cast's base design, and the printing materials. The accuracy appears to not be affected by the layer height and the position of the model on the building template. CONCLUSIONS: According to this systematic review, all different types of 3D technology can produce clinically accepted results for orthodontic purposes. There is a need for more studies to clarify the accuracy and added value of 3D printing technology in orthodontics.

Characterization of near death experiences using text mining analyses: A preliminary study.

The notion that death represents a passing to an afterlife, where we are reunited with loved ones and live eternally in a utopian paradise, is common in the reports of people who have encountered a "Near-Death Experience" (NDE). NDEs are thoroughly portrayed by the media but empirical studies are rather recent. The definition of the phenomenon as well as the identification of NDE experiencers is still a matter of debate. To date, NDEs' identification and description in studies have mostly derived from answered items in questionnaires. However, questionnaires' content could be restricting and subject to personal interpretation. We believe that in addition to their use, user-independent statistical text examination of freely expressed NDEs narratives is of prior importance to help capture the phenomenology of such a subjective and complex phenomenon. Towards that aim, we included 158 participants with a firsthand retrospective narrative of their self-reported NDE that we analyzed using an automated text-mining method. The output revealed the top words expressed by experiencers. In a second step, a hierarchical clustering analysis was conducted to visualize the relationships between these words. It revealed three main clusters of features: visual perceptions, emotions and spatial components. We believe the user-independent and data-driven text mining approach used in this study is promising by contributing to the building a rigorous description and definition of NDEs.

Nociception Coma Scale-Revised Allows to Identify Patients With Preserved Neural Basis for Pain Experience.

The Nociception Coma Scale-Revised (NCS-R) was developed to help assess pain in patients with disorders of consciousness (DOC). Several studies have shown its sensitivity in assessing response to acute noxious stimuli. However, they failed to determine a reliable cut-off score that could be used to infer pain processing in these patients. This retrospective cross-sectional study aimed to determine a NCS-R cut-off score supporting preserved neural basis for pain experience, based on brain metabolism preservation as measured by fluorodeoxyglucose positron emission tomography (FDG-PET). We included patients in unresponsive wakefulness syndrome (UWS) confirmed by the FDG-PET and examined the NCS-R total scores. As the highest score was 4, we defined the cut-off to be 5 and compared the brain metabolism of these patients to matched patients with DOC and a NCS-R cut-off score ≥5 (ie, potential pain), as well as healthy subjects. We found a higher global cerebral metabolism in healthy subjects compared to both patient groups and also in patients with potential pain compared with FDG-PET confirmed UWS. We observed a preserved metabolism in the left insula in patients with potential pain compared with FDG-PET confirmed UWS. PERSPECTIVES: Our data suggest that using the cut-off score of 5 could be helpful to improve pain management in patients with DOC. Future studies should focus on patients showing scores below this cut-off to better characterize their profile and improve care.

Anabolic-androgenic steroids (AAS) users on AAS use: Negative effects, 'code of silence', and implications for forensic and medical professionals.

Anabolic-androgenic steroids (AAS) are image and performance enhancing drugs (IPEDs) that can improve endurance and athletic performance, reduce body fat and stimulate muscle growth. The use of steroids has been studied in the medical and psychological literature, in the sociology of sport, health and masculinity, and relatively recently in criminology. Whilst there is significant medical and psychological evidence on the short term and longer side effects of AAS, there is surprisingly very little evidence based on the users' perception of the negative aspects of AAS use. Drawing on ethnographic research conducted in a locale in the Northeast of England and additional interviews with 24 AAS users, the article offers an account of the negatives aspects of AAS as put forwards by users (acne, abscess, and mood alterations), and highlights the 'code of silence' that exists around AAS use. This 'code' makes AAS users a 'hard-to-reach' group for medical professionals. By listening to the participants' perspectives, forensic and medical professionals can be better informed towards monitoring and reducing harms from AAS.

Enabling second harmonic generation as a contrast mechanism for optical projection tomography (OPT) and scanning laser optical tomography (SLOT).

Volumetric imaging of connective tissue provides insights into the structure of biological tissue. Second harmonic generation (SHG) microscopy has become a standard method to image collagen rich tissue like skin or cornea. Due to the non-centrosymmetric architecture, no additional label is needed and tissue can be visualized noninvasively. Thus, SHG microscopy enables the investigation of collagen associated diseases, providing high resolution images and a field of view of several hundreds of µm. However, the in toto visualization of larger samples is limited to the working distance of the objective and the integration time of the microscope setup, which can sum up to several hours and days. A faster imaging technique for samples in the mesoscopic range is scanning laser optical tomography (SLOT), which provides linear fluorescence, scattering and absorption as intrinsic contrast mechanisms. Due to the advantages of SHG and the reduced measurement time of SLOT, the integration of SHG in SLOT would be a great extension. This way SHG measurements could be performed faster on large samples, providing isotropic resolution and simultaneous acquisition of all other contrast mechanisms available, such as fluorescence and absorption. SLOT is based on the principle of computed tomography, which requires the rotation of the sample. The SHG signal, however, depends strongly on the sample orientation and the polarization of the laser, which results in SHG intensity fluctuation during sample rotation and prevents successful 3D reconstruction. In this paper we investigate the angular dependence of the SHG signal by simulation and experiment and found a way to eliminate reconstruction artifacts caused by this angular dependence in SHG-SLOT data. This way, it is now possible to visualize samples in the mesoscopic range using SHG-SLOT, with isotropic resolution and in correlation to other contrast mechanisms as absorption, fluorescence and scattering.

Is oral feeding compatible with an unresponsive wakefulness syndrome?

OBJECTIVE: The aim of the study is to explore the possibility of oral feeding in unresponsive wakefulness syndrome/vegetative state (UWS/VS) patients. METHOD: We reviewed the clinical information of 68 UWS/VS patients (mean age 45 ± 11; range 16-79 years) searching for mention of oral feeding. UWS/VS diagnosis was made after repeated behavioural assessments using the Coma Recovery Scale-Revised. Patients also had complementary neuroimaging evaluations (positron emission tomography, functional magnetic resonance imaging and electroencephalography and diffusion tensor imaging). RESULTS: Out of the 68 UWS/VS patients, only two could resume oral feeding (3%). The first patient had oral feeding (only liquid and semi liquid) in addition to gastrostomy feeding and the second one could achieve full oral feeding (liquid and mixed solid food). Clinical assessments concluded that they fulfilled the criteria for a diagnosis of UWS/VS. Results from neuroimaging and neurophysiology were typical for the first patient with regard to the diagnosis of UWS/VS but atypical for the second patient. CONCLUSION: Oral feeding that implies a full and complex oral phase could probably be considered as a sign of consciousness. However, we actually do not know which components are necessary to consider the swallowing conscious as compared to reflex. We also discussed the importance of swallowing assessment and management in all patients with altered state of consciousness.

Three-dimensional hard and soft tissue imaging of the human cochlea by scanning laser optical tomography (SLOT).

The present study focuses on the application of scanning laser optical tomography (SLOT) for visualization of anatomical structures inside the human cochlea ex vivo. SLOT is a laser-based highly efficient microscopy technique which allows for tomographic imaging of the internal structure of transparent specimens. Thus, in the field of otology this technique is best convenient for an ex vivo study of the inner ear anatomy. For this purpose, the preparation before imaging comprises decalcification, dehydration as well as optical clearing of the cochlea samples in toto. Here, we demonstrate results of SLOT imaging visualizing hard and soft tissue structures with an optical resolution of down to 15 µm using extinction and autofluorescence as contrast mechanisms. Furthermore, the internal structure can be analyzed nondestructively and quantitatively in detail by sectioning of the three-dimensional datasets. The method of X-ray Micro Computed Tomography (µCT) has been previously applied to explanted cochlea and is solely based on absorption contrast. An advantage of SLOT is that it uses visible light for image formation and thus provides a variety of contrast mechanisms known from other light microscopy techniques, such as fluorescence or scattering. We show that SLOT data is consistent with µCT anatomical data and provides additional information by using fluorescence. We demonstrate that SLOT is applicable for cochlea with metallic cochlear implants (CI) that would lead to significant artifacts in µCT imaging. In conclusion, the present study demonstrates the capability of SLOT for resolution visualization of cleared human cochleae ex vivo using multiple contrast mechanisms and lays the foundation for a broad variety of additional studies.

Corrigendum: Temporality of Features in Near-Death Experience Narratives.

[This corrects the article on p. 311 in vol. 11, PMID: 28659779.].

Temporality of Features in Near-Death Experience Narratives.

Background: After an occurrence of a Near-Death Experience (NDE), Near-Death Experiencers (NDErs) usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area. Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives) as well as the most frequently reported temporality sequences of features. Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32). A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features. Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs. Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

Scanning laser optical tomography for in toto imaging of the murine cochlea.

The mammalian cochlea is a complex macroscopic structure due to its helical shape and the microscopic arrangements of the individual layers of cells. To improve the outcomes of hearing restoration in deaf patients, it is important to understand the anatomic structure and composition of the cochlea ex vivo. Hitherto, only one histological technique based on confocal laser scanning microscopy and optical clearing has been developed for in toto optical imaging of the murine cochlea. However, with a growing size of the specimen, e.g., human cochlea, this technique reaches its limitations. Here, we demonstrate scanning laser optical tomography (SLOT) as a valuable imaging technique to visualize the murine cochlea in toto without any physical slicing. This technique can also be applied in larger specimens up to cm3 such as the human cochlea. Furthermore, immunolabeling allows visualization of inner hair cells (otoferlin) or spiral ganglion cells (neurofilament) within the whole cochlea. After image reconstruction, the 3D dataset was used for digital segmentation of the labeled region. As a result, quantitative analysis of position, length and curvature of the labeled region was possible. This is of high interest in order to understand the interaction of cochlear implants (CI) and cells in more detail.

Regeneration of axotomized olfactory neurons in young and adult locusts quantified by fasciclin I immunofluorescence.

The olfactory pathway of the locust Locusta migratoria is characterized by a multiglomerular innervation of the antennal lobe (AL) by olfactory receptor neurons (ORNs). After crushing the antenna and thereby severing ORN axons, changes in the AL were monitored. First, volume changes were measured at different times post-crush with scanning laser optical tomography in 5th instar nymphs. AL volume decreased significantly to a minimum volume at 4 days post-crush, followed by an increase. Second, anterograde labeling was used to visualize details in the AL and antennal nerve (AN) during de- and regeneration. Within 24 h post-crush (hpc) the ORN fragments distal to the lesion degenerated. After 48 hpc, regenerating fibers grew through the crush site. In the AL, labeled ORN projections disappeared completely and reappeared after a few days. A weak topographic match between ORN origin on the antenna and the position of innervated glomeruli that was present in untreated controls did not reappear after regeneration. Third, the cell surface marker fasciclin I that is expressed in ORNs was used for quantifying purposes. Immunofluorescence was measured in the AL during de- and regeneration in adults and 5th instar nymphs: after a rapid but transient, decrease, it reappeared. Both processes happen faster in 5th instar nymphs than in adults.

"Look at my classifier's result": Disentangling unresponsive from (minimally) conscious patients.

Given the fact that clinical bedside examinations can have a high rate of misdiagnosis, machine learning techniques based on neuroimaging and electrophysiological measurements are increasingly being considered for comatose patients and patients with unresponsive wakefulness syndrome, a minimally conscious state or locked-in syndrome. Machine learning techniques have the potential to move from group-level statistical results to personalized predictions in a clinical setting. They have been applied for the purpose of (1) detecting changes in brain activation during functional tasks, equivalent to a behavioral command-following test and (2) estimating signs of consciousness by analyzing measurement data obtained from multiple subjects in resting state. In this review, we provide a comprehensive overview of the literature on both approaches and discuss the translation of present findings to clinical practice. We found that most studies struggle with the difficulty of establishing a reliable behavioral assessment and fluctuations in the patient's levels of arousal. Both these factors affect the training and validation of machine learning methods to a considerable degree. In studies involving more than 50 patients, small to moderate evidence was found for the presence of signs of consciousness or good outcome, where one study even showed strong evidence for good outcome.

A combined method for correlative 3D imaging of biological samples from macro to nano scale.

Correlative analysis requires examination of a specimen from macro to nano scale as well as applicability of analytical methods ranging from morphological to molecular. Accomplishing this with one and the same sample is laborious at best, due to deformation and biodegradation during measurements or intermediary preparation steps. Furthermore, data alignment using differing imaging techniques turns out to be a complex task, which considerably complicates the interconnection of results. We present correlative imaging of the accessory rat lung lobe by combining a modified Scanning Laser Optical Tomography (SLOT) setup with a specially developed sample preparation method (CRISTAL). CRISTAL is a resin-based embedding method that optically clears the specimen while allowing sectioning and preventing degradation. We applied and correlated SLOT with Multi Photon Microscopy, histological and immunofluorescence analysis as well as Transmission Electron Microscopy, all in the same sample. Thus, combining CRISTAL with SLOT enables the correlative utilization of a vast variety of imaging techniques.

Neural correlates of consciousness in patients who have emerged from a minimally conscious state: a cross-sectional multimodal imaging study.

BACKGROUND: Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients regain the capacity for functional communication, object use, or both. We investigated neural correlates of consciousness in these patients compared with patients with disorders of consciousness and healthy controls, by multimodal imaging. METHODS: In this cross-sectional, multimodal imaging study, patients with unresponsive wakefulness syndrome, patients in a minimally conscious state, and patients who had emerged from a minimally conscious state, diagnosed with the Coma Recovery Scale-Revised, were recruited from the neurology department of the Centre Hospitalier Universitaire de Liège, Belgium. Key exclusion criteria were neuroimaging examination in an acute state, sedation or anaesthesia during scanning, large focal brain damage, motion parameters of more than 3 mm in translation and 3° in rotation, and suboptimal segmentation and normalisation. We acquired resting state functional and structural MRI data and (18)F-fluorodeoxyglucose (FDG) PET data; we used seed-based functional MRI (fMRI) analysis to investigate positive default mode network connectivity (within-network correlations) and negative default mode network connectivity (between-network anticorrelations). We correlated FDG-PET brain metabolism with fMRI connectivity. We used voxel-based morphometry to test the effect of anatomical deformations on functional connectivity. FINDINGS: We recruited a convenience sample of 58 patients (21 [36%] with unresponsive wakefulness syndrome, 24 [41%] in a minimally conscious state, and 13 [22%] who had emerged from a minimally conscious state) and 35 healthy controls between Oct 1, 2009, and Oct 31, 2014. We detected consciousness-level-dependent increases (from unresponsive wakefulness syndrome, minimally conscious state, emergence from minimally conscious state, to healthy controls) for positive and negative default mode network connectivity, brain metabolism, and grey matter volume (p<0·05 false discovery rate corrected for multiple comparisons). Positive default mode network connectivity differed between patients and controls but not among patient groups (F test p<0·0001). Negative default mode network connectivity was only detected in healthy controls and in those who had emerged from a minimally conscious state; patients with unresponsive wakefulness syndrome or in a minimally conscious state showed pathological between-network positive connectivity (hyperconnectivity; F test p<0·0001). Brain metabolism correlated with positive default mode network connectivity (Spearman's r=0·50 [95% CI 0·26 to 0·61]; p<0·0001) and negative default mode network connectivity (Spearman's r=-0·52 [-0·35 to -0·67); p<0·0001). Grey matter volume did not differ between the studied groups (F test p=0·06). INTERPRETATION: Partial preservation of between-network anticorrelations, which are seemingly of neuronal origin and cannot be solely explained by morphological deformations, characterise patients who have emerged from a minimally conscious state. Conversely, patients with disorders of consciousness show pathological between-network correlations. Apart from a deeper understanding of the neural correlates of consciousness, these findings have clinical implications and might be particularly relevant for outcome prediction and could inspire new therapeutic options. FUNDING: Belgian National Funds for Scientific Research (FNRS), European Commission, Natural Sciences and Engineering Research Council of Canada, James McDonnell Foundation, European Space Agency, Mind Science Foundation, French Speaking Community Concerted Research Action, Fondazione Europea di Ricerca Biomedica, University and University Hospital of Liège (Liège, Belgium), and University of Western Ontario (London, ON, Canada).