Spermidine, but not spermine, is essential for pigment pattern formation in zebrafish

Polyamines are small poly-cations essential for all cellular life. The main polyamines present in metazoans are putrescine, spermidine and spermine. Their exact functions are still largely unclear; however, they are involved in a wide variety of processes affecting cell growth, proliferation, apoptosis and aging. Here we identify idefix, a mutation in the zebrafish gene encoding the enzyme spermidine synthase, leading to a severe reduction in spermidine levels as shown by capillary electrophoresis-mass spectrometry. We show that spermidine, but not spermine, is essential for early development, organogenesis and colour pattern formation. Whereas in other vertebrates spermidine deficiency leads to very early embryonic lethality, maternally provided spermidine synthase in zebrafish is sufficient to rescue the early developmental defects. This allows us to uncouple them from events occurring later during colour patterning. Factors involved in the cellular interactions essential for colour patterning, likely targets for spermidine, are the gap junction components Cx41.8, Cx39.4, and Kir7.1, an inwardly rectifying potassium channel, all known to be regulated by polyamines. Thus, zebrafish provide a vertebrate model to study the in vivo effects of polyamines

Patterns of risk—Using machine learning and structural neuroimaging to identify pedophilic offenders

BackgroundChild sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA.AimTo use machine learning and MRI data to identify PO individuals.MethodsFrom a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals.ResultsThe classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P5000 = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending.ConclusionAberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts

The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics

Schons M, Pilgram L, Reese J-P, et al. The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics. European Journal of Epidemiology . 2022.The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON's goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36-62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON's design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registration https://clinicaltrials.gov/ct2/show/NCT04768998 . https://clinicaltrials.gov/ct2/show/NCT04747366 . https://clinicaltrials.gov/ct2/show/NCT04679584. © 2022. The Author(s)

Apoptoseinduktion durch Taurolidin und rhTRAIL in humanen Ösophagus-Plattenepithelkarzinomzellen

• In dieser Arbeit wurde die antikanzergogene Wirkung von Taurolidin als Einzelsubstanz und in Kombination mit rhTRAIL auf humane Plattenepithelkarzinomzellen des Ösophagus untersucht. • Vitalität, Apoptose und Nekrosestadien wurden mit Hilfe des TUNEL Assays visualisiert und in der FACS Analyse quantifiziert. Es erfolgte eine Analyse relevanter Apoptosemarker auf Gen- und Proteinebene und eine gezielte Untersuchung des TRAIL Rezeptorstatus mittels rtPCR. • Es konnte herausgearbeitet werden, dass eine kombinierte Verabreichung von Taurolidin und rhTRAIL den apoptotischen Zelltod signifikant steigert und dazu in der Lage ist, spezifische Resistenzen gegenüber rhTRAIL zu überwinden. Die Tatsache, dass eine kombinierte Anwendung von Taurolidin und rhTRAIL zu einer Dosisreduktion und Vermeidung potentiell toxischer Effekte führen könnte, befähigt die Kombinationstherapie zu einer attraktiven Alternative in der Behandlung des ösophagealen Plattenepithelkarzinoms

Myofasciitis under nivolumab treatment

We report the case of a 73-year-old female patient with malignant melanoma who developed rapidly progressive dermatosclerosis of the arms and legs as well as myalgia and flexion contractures during treatment with the immune checkpoint inhibitor nivolumab. The diagnosis of a myofasciitis was confirmed by imaging and biopsy. Following consultation with the treating dermato-oncologists nivolumab treatment was paused and treatment with methotrexate and prednisolone was initiated. Immune checkpoint inhibitors can induce a variety of immune-mediated side effects and can also imitate symptoms of rheumatological diseases. The occurrence of myofasciitis under immune checkpoint inhibition has been reported in the literature only in a few cases. Further oncological and rheumatological treatment management should be carried out in close interdisciplinary coordination.Wir schildern den Fall einer 73-jährigen Patientin mit malignem Melanom, die eine rasch progrediente Dermatosklerose der Arme und Beine sowie Myalgien und Beugekontrakturen unter der Therapie mit dem Immuncheckpoint-Inhibitor Nivolumab entwickelte. Bildmorphologisch und bioptisch konnte die Diagnose einer Myofasziitis gesichert werden. Nach Rücksprache mit den behandelnden Dermatoonkologen wurde die Nivolumab-Therapie bei gutem Ansprechen des Malignoms pausiert und eine immunmodulierende Therapie mit Methotrexat und Prednisolon eingeleitet. Immuncheckpointinhibitoren können vielfältige immunvermittelte Nebenwirkungen induzieren und auch rheumatologische Krankheitsbilder imitieren. Das Auftreten einer Myofasziitis unter Immuncheckpointinhibition ist nur in wenigen Fällen in der Literatur berichtet. Sinnvoll für die Diagnostik sind insbesondere die Bestimmung der eosinophilen Leukozyten, eine bildgebende Diagnostik mittels Sonographie und/oder MRT sowie die Gewinnung einer Gewebebiopsie. Die weitere onkologische und rheumatologische Therapiesteuerung sollte in enger interdisziplinärer Abstimmung erfolgen

Patterns of risk-Using machine learning and structural neuroimaging to identify pedophilic offenders

BackgroundChild sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA. AimTo use machine learning and MRI data to identify PO individuals. MethodsFrom a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals. ResultsThe classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P-5000 = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending. ConclusionAberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts.Peer reviewe

Telemedicine in Prehospital Acute Stroke Care

Background: Mobile stroke units ( MSU s), equipped with an integrated computed tomography scanner, can shorten time to thrombolytic treatment and may improve outcome in patients with acute ischemic stroke. Original (German) MSU s are staffed by neurologists trained as emergency physicians, but patient assessment and treatment decisions by a remote neurologist may offer an alternative to neurologists aboard MSU. Methods and Results: Remote neurologists examined and assessed emergency patients treated aboard the MSU in Berlin, Germany. Audiovisual quality was rated by the remote neurologist from 1 (excellent) to 6 (insufficient), and duration of video examinations was assessed. We analyzed interrater reliability of diagnoses, scores on the National Institutes of Health Stroke Scale and treatment decisions (intravenous thrombolysis) between the MSU neurologist and the remote neurologist. We included 90 of 103 emergency assessments (13 patients were excluded because of either failed connection, technical problems, clinical worsening during teleconsultation, or missing data in documentation) in this study. The remote neurologist rated audiovisual quality with a median grade for audio quality of 3 (satisfactory) and for video quality of 2 (good). Mean time for completion of teleconsultations was about 19±5 minutes. The interrater reliabilities between the onboard and remote neurologist were high for diagnoses (Cohen's κ=0.86), National Institutes of Health Stroke Scale sum scores (intraclass correlation coefficient, 0.87) and treatment decisions (16 treatment decisions agreed versus 2 disagreed; Cohen's κ=0.93). Conclusions: Remote assessment and treatment decisions of emergency patients are technically feasible with satisfactory audiovisual quality. Agreement on diagnoses, neurological examinations, and treatment decisions between onboard and remote neurologists was high

Data_Sheet_1_Patterns of risk—Using machine learning and structural neuroimaging to identify pedophilic offenders.DOCX

BackgroundChild sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA.AimTo use machine learning and MRI data to identify PO individuals.MethodsFrom a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals.ResultsThe classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P5000 = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending.ConclusionAberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts.</p