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Zachary Boswell,1 Jacopo Umberto Verga,1,2 James Mackle,1 Karen Guerrero-Vazquez,2 Olivier P Thomas,3 James Cray,4 Bethany J Wolf,5 Yeun-Mun Choo,6 Peter Croot,7 Mark T Hamann,8 Gary Hardiman1,5,9 1School of Biological Sciences and Institute for Global Security, Queen’s University, Belfast, Northern Ireland, UK; 2Genomic Data Science, University of Galway, Galway, Ireland; 3School of Biological and Chemical Sciences, Ryan Institute, University of Galway, Galway, H91TK33 Ireland; 4Department of Biomedical Education and Anatomy, College of Medicine and Division of Biosciences, College of Dentistry, Ohio State University, Columbus, OH, USA; 5Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA; 6Department of Chemistry, University of Malaya, Kuala Lumpur, Malaysia; 7Irish Centre for Research in Applied Geoscience, Earth and Ocean Sciences and Ryan Institute, School of Natural Sciences, University of Galway, Galway, Ireland; 8Departments of Drug Discovery and Biomedical Sciences and Public Health, Colleges of Pharmacy and Medicine, Medical University of South Carolina, Charleston, SC, USA; 9Department of Medicine, Medical University of South Carolina, Charleston, SC, USACorrespondence: Gary Hardiman, School of Biological Sciences and Institute for Global Food Security, Faculty of Medicine, Health, and Life Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland, UK, Email g.hardiman@qub.ac.ukAbstract: The urgent need for SARS-CoV-2 controls has led to a reassessment of approaches to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. There are yet no clinically approved broad-spectrum antivirals available for beta-coronaviruses. Discovery pipelines for pan-virus medications against a broad range of betacoronaviruses are therefore a priority. A variety of marine natural product (MNP) small molecules have shown inhibitory activity against viral species. Access to large data caches of small molecule structural information is vital to finding new pharmaceuticals. Increasingly, molecular docking simulations are being used to narrow the space of possibilities and generate drug leads. Combining in-silico methods, augmented by metaheuristic optimization and machine learning (ML) allows the generation of hits from within a virtual MNP library to narrow screens for novel targets against coronaviruses. In this review article, we explore current insights and techniques that can be leveraged to generate broad-spectrum antivirals against betacoronaviruses using in-silico optimization and ML. ML approaches are capable of simultaneously evaluating different features for predicting inhibitory activity. Many also provide a semi-quantitative measure of feature relevance and can guide in selecting a subset of features relevant for inhibition of SARS-CoV-2.Keywords: SARS-CoV-2, natural products, protease, methyl transferases, RNA dependent polymerases, viral transcription, genome replication, betacoronavirus

Abstract Background Succinic semialdehyde dehydrogenase deficiency (SSADHD) represents a model neurometabolic disease at the fulcrum of translational research within the Boston Children’s Hospital Intellectual and Developmental Disabilities Research Centers (IDDRC), including the NIH-sponsored natural history study of clinical, neurophysiological, neuroimaging, and molecular markers, patient-derived induced pluripotent stem cells (iPSC) characterization, and development of a murine model for tightly regulated, cell-specific gene therapy. Methods SSADHD subjects underwent clinical evaluations, neuropsychological assessments, biochemical quantification of γ-aminobutyrate (GABA) and related metabolites, electroencephalography (standard and high density), magnetoencephalography, transcranial magnetic stimulation, magnetic resonance imaging and spectroscopy, and genetic tests. This was parallel to laboratory molecular investigations of in vitro GABAergic neurons derived from induced human pluripotent stem cells (hiPSCs) of SSADHD subjects and biochemical analyses performed on a versatile murine model that uses an inducible and reversible rescue strategy allowing on-demand and cell-specific gene therapy. Results The 62 SSADHD subjects [53% females, median (IQR) age of 9.6 (5.4–14.5) years] included in the study had a reported symptom onset at ∼ 6 months and were diagnosed at a median age of 4 years. Language developmental delays were more prominent than motor. Autism, epilepsy, movement disorders, sleep disturbances, and various psychiatric behaviors constituted the core of the disorder’s clinical phenotype. Lower clinical severity scores, indicating worst severity, coincided with older age (R= -0.302, p = 0.03), as well as age-adjusted lower values of plasma γ-aminobutyrate (GABA) (R = 0.337, p = 0.02) and γ-hydroxybutyrate (GHB) (R = 0.360, p = 0.05). While epilepsy and psychiatric behaviors increase in severity with age, communication abilities and motor function tend to improve. iPSCs, which were differentiated into GABAergic neurons, represent the first in vitro neuronal model of SSADHD and express the neuronal marker microtubule-associated protein 2 (MAP2), as well as GABA. GABA-metabolism in induced GABAergic neurons could be reversed using CRISPR correction of the pathogenic variants or mRNA transfection and SSADHD iPSCs were associated with excessive glutamatergic activity and related synaptic excitation. Conclusions Findings from the SSADHD Natural History Study converge with iPSC and animal model work focused on a common disorder within our IDDRC, deepening our knowledge of the pathophysiology and longitudinal clinical course of a complex neurodevelopmental disorder. This further enables the identification of biomarkers and changes throughout development that will be essential for upcoming targeted trials of enzyme replacement and gene therapy.

Abstract Background In peptide receptor radionuclide therapy (PRRT), accurate quantification of kidney activity on post-treatment SPECT images paves the way for patient-specific treatment. Due to the limited spatial resolution of SPECT images, the partial volume effect (PVE) is a significant source of quantitative bias. In this study, we aimed to evaluate the performance and robustness of anatomy-based partial volume correction (PVC) algorithms to recover the accurate activity concentration of realistic kidney geometries on $$^{177}$$ 177 Lu SPECT images recorded under clinical conditions. Methods Based on the CT scan data from patients, three sets of fillable kidneys with surface-to-volume (S:V) ratios ranging from 1.5 to 2.8 cm−1, were 3D printed and attached in a IEC phantom. Quantitative $$^{177}$$ 177 Lu SPECT/CT acquisitions were performed on a GE Discovery NM CT 870 DR camera for the three modified IEC phantoms and for 6 different Target-To-Background ratios (TBRs: 2, 4, 6, 8, 10, 12). Two region-based (GTM and Labbé) and five voxel-based (GTM + MTC, Labbé + MTC, GTM + RBV, Labbé + RBV and IY) methods were evaluated with this data set. Additionally, the robustness of PVC methods to Point Spread Function (PSF) discrepancies, registration mismatches and background heterogeneity was evaluated. Results Without PVC, the average kidney RCs across all TBRs ranged from 0.66 ± 0.05 (smallest kidney) to 0.80 ± 0.03 (largest kidney). For a TBR of 12, all anatomy-based method were able to recover the kidneys activity concentration with an error < 6%. All methods result in a comparable decline in RC restoration with decreasing TBR. The Labbé method was the most robust against PSF and registration mismatches but was also the most sensitive to background heterogeneity. Among the voxel-based methods, MTC images were less uniform than RBV and IY images at the outer edge of high uptake areas (kidneys and spheres). Conclusion Anatomy-based PVE correction allows for accurate SPECT quantification of the $$^{177}$$ 177 Lu activity concentration with realistic kidney geometries. Combined with recent progress in deep-learning algorithms for automatic anatomic segmentation of whole-body CT, these methods could be of particular interest for a fully automated OAR dosimetry pipeline with PVE correction.

Abstract Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis.

Abstract Tropospheric reactive bromine (Bry) influences the oxidation capacity of the atmosphere by acting as a sink for ozone and nitrogen oxides. Aerosol acidity plays a crucial role in Bry abundances through acid‐catalyzed debromination from sea‐salt‐aerosol, the largest global source. Bromine concentrations in a Russian Arctic ice‐core, Akademii Nauk, show a 3.5‐fold increase from pre‐industrial (PI) to the 1970s (peak acidity, PA), and decreased by half to 1999 (present day, PD). Ice‐core acidity mirrors this trend, showing robust correlation with bromine, especially after 1940 (r = 0.9). Model simulations considering anthropogenic emission changes alone show that atmospheric acidity is the main driver of Bry changes, consistent with the observed relationship between acidity and bromine. The influence of atmospheric acidity on Bry should be considered in interpretation of ice‐core bromine trends.

Aim: This observational study investigated the association between remdesivir treatment during hospitalization for COVID-19 and 30-day COVID-19-related and all-cause readmission across different variants time periods. Patients & methods: Hospitalization records for adult patients discharged from a COVID-19 hospitalization between 1 May 2020 to 30 April 2022 were extracted from the US PINC AI Healthcare Database. Likelihood of 30-day readmission was compared among remdesivir-treated and nonremdesivir-treated patients using multivariable logistic regression models adjusted for age, corticosteroid treatment, Charlson comorbidity index and intensive care unit stay during the COVID-19 hospitalization. Analyses were stratified by maximum supplemental oxygen requirement and variant time period (pre-Delta, Delta and Omicron). Results: Of the 440,601 patients discharged alive after a COVID-19 hospitalization, 248,785 (56.5%) patients received remdesivir. Overall, remdesivir patients had a 30-day COVID-19-related readmission rate of 3.0% and all-cause readmission rate of 6.3% compared with 5.4% and 9.1%, respectively, for patients who did not receive remdesivir during their COVID-19 hospitalization. After adjusting for demographics and clinical characteristics, remdesivir treatment was associated with significantly lower odds of 30-day COVID-19-related readmission (odds ratio 0.60 [95% confidence interval: 0.58–0.62]), and all-cause readmission (0.73 [0.72–0.75]). Significantly lower odds of 30-day readmission in remdesivir-treated patients was observed across all variant time periods. Conclusion: Treating patients hospitalized for COVID-19 with remdesivir is associated with a statistically significant reduction in 30- day COVID-19-related and all-cause readmission across variant time periods. These findings indicate that the clinical benefit of remdesivir may extend beyond the COVID-19 hospitalization.

The widespread use of high-throughput sequencing techniques is leading to a rapidly increasing number of disease-associated variants of unknown significance and candidate genes. Integration of knowledge concerning their genetic, protein as well as functional and conservational aspects is necessary for an exhaustive assessment of their relevance and for prioritization of further clinical and functional studies investigating their role in human disease. To collect the necessary information, a multitude of different databases has to be accessed and data extraction from the original sources commonly is not user-friendly and requires advanced bioinformatics skills. This leads to a decreased data accessibility for a relevant number of potential users such as clinicians, geneticist, and clinical researchers. Here, we present aRgus (https://argus.urz.uni-heidelberg.de/), a standalone webtool for simple extraction and intuitive visualization of multi-layered gene, protein, variant, and variant effect prediction data. aRgus provides interactive exploitation of these data within seconds for any known gene of the human genome. In contrast to existing online platforms for compilation of variant data, aRgus complements visualization of chromosomal exon-intron structure and protein domain annotation with ClinVar and gnomAD variant distributions as well as position-specific variant effect prediction score modeling. aRgus thereby enables timely assessment of protein regions vulnerable to variation with single amino acid resolution and provides numerous applications in variant and protein domain interpretation as well as in the design of in vitro experiments.

Black Carbon is an important climate forcer with poorly constraint historic emission fluxes and therefore large emission uncertainty. Here, ice-core data are combined with modelling to reconstruct historical emissions of Black carbon and finding gaps with the existing inventories, which implies potential climate sensitivity biases

Abstract Pronounced glacial and interglacial climate cycles characterized northern ecosystems during the Pleistocene. Our understanding of the resultant community transformations and past ecological interactions strongly depends on the taxa found in fossil assemblages. Here, we present a shotgun metagenomic analysis of sedimentary ancient DNA (sedaDNA) to infer past ecosystem‐wide biotic composition (from viruses to megaherbivores) from the Middle and Late Pleistocene at the Batagay megaslump, East Siberia. The shotgun DNA records of past vegetation composition largely agree with pollen and plant metabarcoding data from the same samples. Interglacial ecosystems at Batagay attributed to Marine Isotope Stage (MIS) 17 and MIS 7 were characterized by forested vegetation (Pinus, Betula, Alnus) and open grassland. The microbial and fungal communities indicate strong activity related to soil decomposition, especially during MIS17. The local landscape likely featured more open, herb‐dominated areas, and the vegetation mosaic supported birds and small omnivorous mammals. Parts of the area were intermittently/partially flooded as suggested by the presence of water‐dependent taxa. During MIS 3, the sampled ecosystems are identified as cold‐temperate, periodically flooded grassland. Diverse megafauna (Mammuthus, Equus, Coelodonta) coexisted with small mammals (rodents). The MIS 2 ecosystems existed under harsher conditions, as suggested by the presence of cold‐adapted herbaceous taxa. Typical Pleistocene megafauna still inhabited the area. The new approach, in which shotgun sequencing is supported by metabarcoding and pollen data, enables the investigation of community composition changes across a broad range of taxonomic groups and inferences about trophic interactions and aspects of soil microbial ecology.

Glacial legacies preserved in permafrost such as buried glacial ice of the last ice age are of increasing concern in the Western Canadian Arctic. Permafrost collapse due to melting ground ice largely follows the margins of the maximum Laurentide Ice Sheet extent and therefore predetermines the postglacial landscape evolution in this region. Another type of ground ice, (i.e., wedge ice) of late Pleistocene and Holocene age associated with permafrost aggradation, is also widespread here. Our study on Herschel Island (Qikiqtaruk, Beaufort Sea) re-examines previous data and applies stable-isotope and dissolved organic carbon (DOC) analyses as well as radiocarbon dating on DOC and particulate plant macrofossil remains preserved in massive ground ice, wedge ice and host deposits.Newly obtained DOC ages of the massive ice span from 32 220 to 25 830 cal BP and extend the only previously available direct age determination (CO2-derived radiocarbon age of 21 290 cal BP) properly into the Last Glacial Maximum as the formation time of the massive ice. Its newly obtained isotopic composition exhibits mean values of −33.1 ± 0.6‰ in δ18O, of −257 ± 4‰ in δD and 7.6 ± 0.9‰ in deuterium excess (d) fitting into previously reported respective data ranges. The very low (negative) stable isotope composition of the massive ice, the numerous enclosed spherical air bubbles as well as the very low mean DOC content of 0.7 ± 0.1 mg L−1 provide strong evidence for an origin as glacier ice that was buried and has survived since deglaciation.The newly studied wedge ice on Herschel Island formed during the Holocene between 9220 and 3470 cal BP, and shows a distinct isotopic composition with mean values of −18.4 ± 1.1‰ in δ18O, −138 ± 9‰ in δD and a mean deuterium excess (d) of 8.8 ± 1.4‰. Such isotopic wedge-ice record as well as its mean DOC concentration of 4.3 ± 2.1 mg L−1 fall within the range of previously studied Holocene ice wedges in the region. The directly-dated stable isotope record of ice-wedge growth on Herschel Island indicates a winter cooling trend towards the mid-Holocene, even though most available records attribute this cooling rather to the warm season while the winter temperatures over this period are not constrained yet.The extraordinarily rich ground-ice inventory of Herschel Island offers insights into the glacial and postglacial landscape evolution of the Western Canadian Arctic. Here, paleoenvironmental research highlights ice sheet-permafrost interactions over glacial, deglacial and postglacial timescales.

The authors would like to make the following corrections to the published article [...]

TUBB2A tubulinopathy is a rare neurodevelopmental disorder with developmental delay, epilepsy, and less frequent malformations of cortical development compared to other tubulinopathies. Peripheral blood mononuclear cells (PBMCs) from a male subject harboring the heterozygous de novo TUBB2A variant c.[743C>T] (p.[Ala248Val]) were reprogrammed to induced pluripotent stem cells (iPSCs) using the CytoTune™-iPS 2.0 Sendai Reprogramming Kit (Invitrogen). Generated iPSCs showed a normal karyotype, expression of pluripotency markers, spontaneous in vitro differentiation in all three germ layers, and are a suitable human disease model to analyze pathomechanisms underlying TUBB2A tubulinopathy and potential therapeutic targets.

Inherited disorders of neurotransmitter metabolism represent a group of rare neurometabolic diseases characterized by movement disorders and developmental delay. Here, the authors report a standardized evaluation of a registry of 275 patients from 42 countries, and highlight an evolving phenotypic spectrum of this disease group and factors influencing diagnostic processes.

Abstract Background Following the broad application of new analytical methods, more and more pathophysiological processes in previously unknown diseases have been elucidated. The spectrum of clinical presentation of rare inherited metabolic diseases (IMDs) is broad and ranges from single organ involvement to multisystemic diseases. With the aim of overcoming the limited knowledge about the natural course, current diagnostic and therapeutic approaches, the project has established the first unified patient registry for IMDs that fully meets the requirements of the European Infrastructure for Rare Diseases (ERDRI). Results In collaboration with the European Reference Network for Rare Hereditary Metabolic Disorders (MetabERN), the Unified European registry for Inherited Metabolic Diseases (U-IMD) was established to collect patient data as an observational, non-interventional natural history study. Following the recommendations of the ERDRI the U-IMD registry uses common data elements to define the IMDs, report the clinical phenotype, describe the biochemical markers and to capture the drug treatment. Until today, more than 1100 IMD patients have been registered. Conclusion The U-IMD registry is the first observational, non-interventional patient registry that encompasses all known IMDs. Full semantic interoperability for other registries has been achieved, as demonstrated by the use of a minimum common core data set for equivalent description of metabolic patients in U-IMD and in the patient registry of the European Rare Kidney Disease Reference Network (ERKNet). In conclusion, the U-IMD registry will contribute to a better understanding of the long-term course of IMDs and improved patients care by understanding the natural disease course and by enabling an optimization of diagnostic and therapeutic strategies.

Abstract Background Silver-Russell syndrome (SRS) is an imprinting disorder which is characterised by severe primordial growth retardation, relative macrocephaly and a typical facial gestalt. The clinical heterogeneity of SRS is reflected by a broad spectrum of molecular changes with hypomethylation in 11p15 and maternal uniparental disomy of chromosome 7 (upd(7)mat) as the most frequent findings. Monogenetic causes are rare, but a clinical overlap with numerous other disorders has been reported. However, a comprehensive overview on the contribution of mutations in differential diagnostic genes to phenotypes reminiscent to SRS is missing due to the lack of appropriate tests. With the implementation of next generation sequencing (NGS) tools this limitation can now be circumvented. Main body We analysed 75 patients referred for molecular testing for SRS by a NGS-based multigene panel, whole exome sequencing (WES), and trio-based WES. In 21/75 patients a disease-causing variant could be identified among them variants in known SRS genes (IGF2, PLAG1, HMGA2). Several patients carried variants in genes which have not yet been considered as differential diagnoses of SRS. Conclusions WES approaches significantly increase the diagnostic yield in patients referred for SRS testing. Several of the identified monogenetic disorders have a major impact on clinical management and genetic counseling.

Rare diseases, such as inherited metabolic diseases, have been identified as a health priority within the European Union more than 20 years ago and have become an integral part of EU health programs and European Reference Networks. Having the potential to pool data, to achieve sufficient sample size, to overcome the knowledge gap on rare diseases and to foster epidemiological and clinical research, patient registries are recognized as key instruments to evidence-based medicine for individuals with rare diseases. Patient registries can be used for multiple purposes, such as (1) describing the natural history and phenotypic diversity of rare diseases, (2) improving case definition and indication to treat, (3) identifying strategies for risk stratification and early prediction of disease severity (4), evaluating the impact of preventive, diagnostic, and therapeutic strategies on individual health, health economics, and the society, and (5) informing guideline development and policy makers. In contrast to clinical trials, patient registries aim to gather real-world evidence and to achieve generalizable results based on patient cohorts with a broad phenotypic spectrum. In order to develop a consistent and sustained framework for rare disease registries, uniform core principles have been formulated and have been formalized through the European Rare Disease Registration Infrastructure. Adherence to these core principles and compliance with the European general data protection regulations ensures that data collected and stored in patient registries can be exchanged and pooled in a protected environment. To illustrate the benefits and limitations of patient registries on rare disease research this review focuses on inherited metabolic diseases.

An amendment to this paper has been published and can be accessed via the original article.

Abstract Background Tetrahydrobiopterin (BH4) deficiencies comprise a group of six rare neurometabolic disorders characterized by insufficient synthesis of the monoamine neurotransmitters dopamine and serotonin due to a disturbance of BH4 biosynthesis or recycling. Hyperphenylalaninemia (HPA) is the first diagnostic hallmark for most BH4 deficiencies, apart from autosomal dominant guanosine triphosphate cyclohydrolase I deficiency and sepiapterin reductase deficiency. Early supplementation of neurotransmitter precursors and where appropriate, treatment of HPA results in significant improvement of motor and cognitive function. Management approaches differ across the world and therefore these guidelines have been developed aiming to harmonize and optimize patient care. Representatives of the International Working Group on Neurotransmitter related Disorders (iNTD) developed the guidelines according to the SIGN (Scottish Intercollegiate Guidelines Network) methodology by evaluating all available evidence for the diagnosis and treatment of BH4 deficiencies. Conclusion Although the total body of evidence in the literature was mainly rated as low or very low, these consensus guidelines will help to harmonize clinical practice and to standardize and improve care for BH4 deficient patients.

In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, therefore supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and natural enemy species, the underlying landscape structure, and their interaction, may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that increased SNH presence boosts predator populations by sustaining high predator density that regulates and keeps pest density below the pesticide application threshold. However, predator presence over all the landscape helps to stabilize the pest population by keeping it under this threshold, which tends to increase pest density at the landscape scale. In addition, the joint effect of SNH presence and predator dispersal ability among hedge and field interface results in a stronger pest regulation, which also limits pest growth. Considering properties of both fields and linear elements, such as local structure and geometric features, provides deeper insights for pest regulation; for example, hedge presence at crop field boundaries clearly strengthens CBC. Our results highlight that the integration of species behaviors and traits with landscape structure at multiple scales is necessary to provide useful insights for CBC. Author summary In the agricultural context, the loss of semi-natural surfaces often results in high pest abundance requiring elevated pesticide loads. Habitat heterogeneity resulting from the agricultural intermixing of arable fields and semi-natural areas is key to allow organism fluxes across agro-ecological interfaces by influencing ecological processes. Semi-natural habitats (SNH) are often restricted to linear structures, such as hedgerows, but they play an important role by hosting a large number of species. However, the effect of hedgerows is controversial, as it could result in a positive, ineffective or negative effect for CBC. Usually, the impacts of landscape structure on pest population dynamics and resulting CBC are assessed through field experiments with a specific focus, which cannot be generalized, lack flexibility and are limited by the need to manipulate relatively large landscapes. Here, we tackle the challenge to investigate the controversial role of semi-natural habitats for CBC by presenting a simulation-based approach, which allows us to characterize the joint influence of landscape structure and species traits on CBC service. Our study corroborates that spatial heterogeneity, species traits and their interactions are fundamental for CBC. We show that hedge presence alone is not sufficient to lead to strong pest reduction, but hedge-based predators help to maintain the pest density under the pesticide threshold. Instead, SNH presence coupled with appropriate predator traits leads to stronger decrease of pest population. Moreover, we highlight an important scaling effect of SNH, which at the local scale has an even more important impact on CBC as local properties are considered.

This commentary provides an overview of the putamen as an established target site for gene therapy in treating aromatic l‐amino acid decarboxylase (AADC) deficiency and Parkinson’s disease, two debilitating neurological disorders that involve motor dysfunction caused by dopamine deficiencies. The neuroanatomy and the function of the putamen in motor control provide good rationales for targeting this brain structure. Additionally, the efficacy and safety of intraputaminal gene therapy demonstrate that restoration of dopamine synthesis in the putamen by using low doses of adeno‐associated viral vector serotype 2 to deliver the hAADC gene is well tolerated. This restoration leads to sustained improvements in motor and nonmotor symptoms of AADC deficiency and improved uptake and conversion of exogenous l‐DOPA into dopamine in Parkinson’s patients.

Ice- and organic-rich deposits of late Pleistocene age, known as Yedoma Ice Complex (IC), are widespread across large permafrost regions in Northeast Siberia. To reconstruct Yedoma IC formation in Central Yakutia, we analyzed the geochemistry, sedimentology, and stratigraphy of thawed and frozen deposits below two thermokarst lakes in different evolutionary stages (a mature alas lake and a initial Yedoma lake) from the Yukechi site in the Lena-Aldan interfluve. We focused on inorganic geochemical characteristics and mineral weathering in two ∼17 m long sediment cores to trace syngenetic permafrost aggradation and degradation over time. Geochemical properties, element ratios, and specific weathering indices reflect varying sedimentation processes and seasonal thaw depths under variable environmental conditions. Deeper thaw during the interstadial Marine Isotope Stage (MIS) 3 enabled increasing mineral weathering and initial thermokarst processes. Sedimentological proxies reflect high transport energy and short transport paths and mainly terrestrial sediment supply. The Yedoma formation resulted from fluvial, alluvial and aeolian processes. Low mean TOC contents in both cores contrast with Yedoma deposits elsewhere. Likely, this is a result of the very low organic matter content of the source material of the Yukechi Yedoma. Pronounced cryostructures and strongly depleted pore water stable isotopes show a perennially frozen state and preserved organic matter for the lower part of the Yedoma lake core, while changing permafrost conditions, conditions promoting weathering, and strong organic matter decomposition are suggested by our proxies for its middle and upper parts. For the alas lake core, less depleted water stable isotopes reflect the influence of recent precipitation, i.e. the infiltration of rain and lake water into the unfrozen ground. The FENG, MIA(R), and ICV weathering indices have proven to be promising proxies for the identification of conditions that promote mineral weathering to different degrees in the stratigraphy of the thawed and frozen Yedoma deposits, for which we assume a rather homogeneous chemical composition of the parent material. Our study highlights that the understanding of environmental conditions during Yedoma formation and degradation processes by specific geochemical proxies is crucial for assessing the potential decomposition and preservation of the frozen and unfrozen Yedoma inventories.

(1) Background: Phenotypic diversity and long-term health outcomes of individuals with urea cycle disorders (UCDs) have been described in detail. However, there is limited information on the burden on affected families. (2) Methods: To evaluate the family burden in parents with children suffering from UCDs, we used validated questionnaires. Socio-demographic characteristics were evaluated, and an adapted version of the Parental Need Scale for Rare Diseases questionnaire was used. The survey was conducted in families of UCD patients cared for at the University Children’s Hospital Heidelberg. (3) Results: From April to November 2021, 59 participants were interviewed (mothers n = 34, fathers n = 25). The affected patients most frequently suffered from ornithine transcarbamylase deficiency (OTC-D) (female n = 12, male n = 12), followed by argininosuccinate synthetase deficiency (ASS-D, n = 13) and argininosuccinate lyase deficiency (ASL-D, n = 8). About one-third of the participants were “dissatisfied” or “extremely dissatisfied” with health professionals’ disease knowledge. In addition, 30% of the participants reported a medium or high need for “additional information on the development of their children”, and 44% reported a medium or high need “for information on available services”. A majority of 68% reported a need for additional support regarding services such as support groups (42%) or psychological counseling (29%). (4) Conclusions: Our study indicates that there is an unmet need for sufficient information about the development of children with UCDs, as well as for information about available support services for families with UCD patients. Furthermore, the results highlight the importance of establishing or improving family-centered care approaches. This pilot study may serve as a template for the assessment of the family burden associated with other inherited metabolic diseases.

Androgen Receptor (AR) alterations (amplification, point mutations, and splice variants) are master players in metastatic castration resistant prostate cancer (CRPC) progression and central therapeutic targets for patient management. Here, we have developed two multiplexed droplet digital PCR (ddPCR) assays to detect AR copy number (CN) and the key point mutation T877A. Overcoming challenges of determining gene amplification from liquid biopsies, these assays cross-validate each other to produce reliable AR amplification and mutation data from plasma cell free DNA (cfDNA) of advanced prostate cancer (PC) patients. Analyzing a mixed PC patient cohort consisting of CRPC and hormone sensitive prostate cancer (HSPC) patients showed that 19% (9/47) patients had AR CN amplification. As expected, only CRPC patients were positive for AR amplification, while interestingly the T877A mutation was identified in two patients still considered HSPC at the time. The ddPCR based analysis of AR alterations in cfDNA is highly economic, feasible, and informative to provide biomarker detection that may help to decide on the best follow-up therapy for CRPC patients.

The degradation of ice-rich permafrost deposits has the potential to release large amounts of previously freeze-locked carbon (C) and nitrogen (N) with local implications, such as affecting riverine and near-shore ecosystems, but also global impacts such as the release of greenhouse gases into the atmosphere. Here, we study the rapid erosion of the up to 27.7 m high and 1,660 m long Sobo-Sise yedoma cliff in the Lena River Delta using a remote sensing-based time-series analysis covering 53 years and calculate the mean annual sediment as well as C and N release into the Lena River. We find that the Sobo-Sise yedoma cliff, which exposes ice-rich late Pleistocene to Holocene deposits, had a mean long-term (1965–2018) erosion rate of 9.1 m yr–1 with locally and temporally varying rates of up to 22.3 m yr–1. These rates are among the highest measured erosion rates for permafrost coastal and river shoreline stretches. The fluvio-thermal erosion led to the release of substantial amounts of C (soil organic carbon and dissolved organic carbon) and N to the river system. On average, currently at least 5.2 × 106 kg organic C and 0.4 × 106 kg N were eroded annually (2015–2018) into the Lena River. The observed sediment and organic matter erosion was persistent over the observation period also due to the specific configuration of river flow direction and cliff shore orientation. Our observations highlight the importance to further study rapid fluvio-thermal erosion processes in the permafrost region, also because our study shows increasing erosion rates at Sobo-Sise Cliff in the most recent investigated time periods. The organic C and N transport from land to river and eventually to the Arctic Ocean from this and similar settings may have severe implications on the biogeochemistry and ecology of the near-shore zone of the Laptev Sea as well as for turnover and rapid release of old C and N to the atmosphere.

Abstract Background Educating doctors is expensive and poor performance by future graduates can literally cost lives. Whilst the practice of medicine is highly evidence based, medical education is much less so. Research on medical school selection, undergraduate progression, Fitness to Practise (FtP) and postgraduate careers has been hampered across the globe by the challenges of uniting the data required. This paper describes the creation, structure and access arrangements for the first UK-wide attempt to do so. Overview A collaborative approach has created a research database commencing with all entrants to UK medical schools in 2007 and 2008 (UKMED Phase 1). Here the content is outlined, governance arrangements considered, system access explained, and the potential implications of this new resource discussed. The data currently include achievements prior to medical school entry, admissions tests, graduation point information and also all subsequent data collected by the General Medical Council, including FtP, career progression, annual National Training Survey (NTS) responses, career choice and postgraduate exam performance data. UKMED has grown since the pilot phase with additional datasets; all subsequent years of students/trainees and stronger governance processes. The inclusion of future cohorts and additional information such as admissions scores or bespoke surveys or assessments is now being piloted. Thus, for instance, new scrutiny can be applied to selection techniques and the effectiveness of educational interventions. Data are available free of charge for approved studies from suitable research groups worldwide. Conclusion It is anticipated that UKMED will continue on a rolling basis. This has the potential to radically change the volume and types of research that can be envisaged and, therefore, to improve standards, facilitate workforce planning and support the regulation of medical education and training. This paper aspires to encourage proposals to utilise this exciting resource.

High-accumulation sites are crucial for understanding the patterns and mechanisms of climate and environmental change in Antarctica since they allow gaining high-resolution proxy records from firn and ice. Here, we present new glacio- and isotope-geochemical data at sub-annual resolution from a firn core retrieved from an ice cap on Plateau Laclavere (LCL), northern Antarctic Peninsula, covering the period 2012–2015. The signals of two volcanic eruptions and two forest fire events in South America could be identified in the non-sea-salt sulphur and black carbon records, respectively. Mean annual snow accumulation on LCL amounts to 2500 kg m−2 a−1 and exhibits low inter-annual variability. Time series of δ18O, δD and d excess show no seasonal cyclicity, which may result from (1) a reduced annual temperature amplitude due to the maritime climate and (2) post-depositional processes. The firn core stratigraphy indicates strong surface melt on LCL during austral summers 2013 and 2015, likely related to large-scale warm-air advection from lower latitudes and temporal variations in sea ice extent in the Bellingshausen-Amundsen Sea. The LCL ice cap is a highly valuable natural archive since it captures regional meteorological and environmental signals as well as their connection to the South American continent.

Temporal variations of the radionuclide 10Be are broadly synchronous across the globe and thus provide a powerful tool to synchronize ice core chronologies from different locations. We compared the 10Be record of the Akademii Nauk (AN) ice core (Russian Arctic) for the time period CE 1590–1950 to the 10Be records of two well-dated Greenland ice cores (Dye3 and NGRIP). A high correlation (r = 0.59) was found between the AN and Dye3 records whereas the correlation with NGRIP was distinctly lower (r = 0.45). Sources of deviations may include local fluctuations in the deposition of 10Be due to changes in the precipitation patterns, and artefacts due to the core-sampling strategy. In general, the existing age model was validated, confirming the AN ice core to be a unique and well-dated source of palaeoclimate parameters for the Russian Arctic. We further used numerical simulations to test the influence of the core-sampling strategy on the results and derived an optimized sampling strategy for the deeper parts of the ice core.

Fibroblasts from a female patient carrying a heterozygous variation in GTP cyclohydrolase 1 (GCH1; OMIM: 600225; HGNC: 4193; c.235_240del/p.(L79_S80del)), the rate-limiting enzyme of tetrahydrobiopterin (BH4) synthesis, were reprogrammed to iPSCs using the Cytotune®-iPS 2.0 Sendai Reprogramming Kit (Invitrogen) delivering the four reprogramming factors Oct3/4, Sox2, c-Myc and Klf4. Pluripotency of HDMC0061i-GCH1 was verified using immunohistochemistry and RT-PCR analysis. Cells differentiated spontaneously into the 3 germ layers in vitro and presented a normal karyotype. HDMC0061i-GCH1 represents the first model system to elucidate the pathomechanism underlying this rare metabolic disease and a useful tool for drug testing.

Skin fibroblasts were isolated from a male patient with DNAJC12 deficiency and reprogrammed to iPSCs using the Cytotune®-iPS 2.0 Sendai Reprogramming Kit (Invitrogen). Two clones, DHMCi003-A and DHMCi003-B, were characterized for expression of pluripotency marker genes (Oct4, Nanog, Lin28, SSEA-4, TRA-1-60) and differentiated into all three germ layers using embryoid body (EB) formation. Karyotype of both clones was normal and presence of the homozygous mutation in the DNAJC12 gene was verified by PCR and Sanger sequencing. Both clones represent a useful tool to study the pathomechanisms underlying the deficiency.

Dihydropteridine reductase (QDPR) catalyzes the recycling of tetrahydrobiopterin (BH4), a cofactor in dopamine, serotonin, and phenylalanine metabolism. QDPR-deficient patients develop neurological symptoms including hypokinesia, truncal hypotonia, intellectual disability and seizures. The underlying pathomechanisms are poorly understood. We established a zebrafish model for QDPR deficiency and analyzed the expression as well as function of all zebrafish QDPR homologues during embryonic development. The homologues qdpra is essential for pigmentation and phenylalanine metabolism. Qdprb1 is expressed in the proliferative zones of the optic tectum and eye. Knockdown of qdprb1 leads to up-regulation of pro-proliferative genes and increased number of phospho-histone3 positive mitotic cells. Expression of neuronal and astroglial marker genes is concomitantly decreased. Qdprb1 hypomorphic embryos develop microcephaly and reduced eye size indicating a role for qdprb1 in the transition from cell proliferation to differentiation. Glutamine accumulation biochemically accompanies the developmental changes. Our findings provide novel insights into the neuropathogenesis of QDPR deficiency.

Succinic semialdehyde dehydrogenase deficiency (SSADHD) is a rare, monogenic disorder affecting the degradation of the main inhibitory neurotransmitter γ-amino butyric acid (GABA). Pathogenic variants in the ALDH5A1 gene that cause an enzymatic dysfunction of succinic semialdehyde dehydrogenase (SSADH) lead to an accumulation of potentially toxic metabolites, including γ-hydroxybutyrate (GHB). Here, we present a patient with a severe phenotype of SSADHD caused by a novel genetic variant c.728T > C that leads to an exchange of leucine to proline at residue 243, located within the highly conserved nicotinamide adenine dinucleotide (NAD)+ binding domain of SSADH. Proline harbors a pyrrolidine within its side chain known for its conformational rigidity and disruption of protein secondary structures. We investigate the effect of this novel variant in vivo, in vitro, and in silico. We furthermore examine the mutational spectrum of all previously described disease-causing variants and computationally assess all biologically possible missense variants of ALDH5A1 to identify mutational hotspots.

Succinic semialdehyde dehydrogenase deficiency (SSADH-D) is a genetic disorder that results from the aberrant metabolism of the neurotransmitter γ-amino butyric acid (GABA). The disease is caused by impaired activity of the mitochondrial enzyme succinic semialdehyde dehydrogenase. SSADH-D manifests as varying degrees of mental retardation, autism, ataxia, and epileptic seizures, but the clinical picture is highly heterogeneous. So far, there is no approved curative therapy for this disease. In this review, we briefly summarize the molecular genetics of SSADH-D, the past and ongoing clinical trials, and the emerging features of the molecular pathogenesis, including redox imbalance and mitochondrial dysfunction. The main aim of this review is to discuss the potential of further therapy approaches that have so far not been tested in SSADH-D, such as pharmacological chaperones, read-through drugs, and gene therapy. Special attention will also be paid to elucidating the role of patient advocacy organizations in facilitating research and in the communication between researchers and patients.

Detection of androgen receptor (AR) variant 7 (AR-V7) is emerging as a clinically important biomarker in castrate resistant prostate cancer (CRPC). Detection is possible from tumor tissue, which is often inaccessible in the advanced disease setting. With recent progress in detecting AR-V7 in circulating tumor cells (CTCs), circulating tumor RNA (ctRNA) and exosomes from prostate cancer patients, liquid biopsies have emerged as an alternative to tumor biopsy. Therefore, it is important to clarify whether these approaches differ in sensitivity in order to achieve the best possible biomarker characterization for the patient. In this study, blood samples from 44 prostate cancer patients were processed for CTCs and ctRNA with subsequent AR-V7 testing, while exosomal RNA was isolated from 16 samples and tested. Detection of AR and AR-V7 was performed using a highly sensitive droplet digital PCR-based assay. AR and AR-V7 RNA were detectable in CTCs, ctRNA and exosome samples. AR-V7 detection from CTCs showed higher sensitivity and has proven specificity compared to detection from ctRNA and exosomes. Considering that CTCs are almost always present in the advanced prostate cancer setting, CTC samples should be considered the liquid biopsy of choice for the detection of this clinically important biomarker.

Background: Pancreatic cancer is among the most dismal of human malignancies. The 5-year survival rate is lower than 5%. The identification of precursor lesions would be the main step to improve this fatal outcome. One precursor lesions are called pancreatic intraepithelial neoplasia (PanIN) and are graduated in grade 1 to 3, whereas grade 3 is classified as carcinoma in situ. Currently, no reliable, noninvasive imaging technique (e.g., ultrasound, computed tomography, magnet resonance imaging) exists to verify PanINs. Methods: Recently, a transgenic mouse model of pancreatic cancer was established in which the tumor progression of human pancreatic carcinoma is reproduced. These so-called Pdx-1-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+mice develop PanINs, which transform to invasive growing pancreatic carcinoma. The pancreata of mice of different ages were immunohistochemically stained using α-GLUT-2 antibodies. Furthermore, mice underwent positron emission tomography (PET)-computed tomography (CT) with 18F-fluorodeoxyglucose (FDG) to evaluate early detection of PanIN lesions. Results: An expression of GLUT-2 in murine PanINs was found in PanINs of grade 1B and higher. This finding is associated with an elevated glucose metabolism, leading to the detection of precursor lesions of pancreatic cancer in the FDG PET-CT scan. In addition, immunohistochemical staining of GLUT-2 was detectable in 45 (75%) of 60 human PanINs, whereas PanINs of grade 1B and higher showed a very extensive expression. Conclusions: In conclusion, we demonstrate for the first time that an elevated glucose metabolism occurs already in precursor lesions of murine and human pancreatic carcinoma. These findings are the basis for the detection of precursor lesions by PET-CT, thereby helping improving the prognosis of this devastating disease.

Role of changing climatic conditions on permafrost degradation and hydrology was investigated in the transition zone between the tundra and forest ecotones at the boundary of continuous and discontinuous permafrost of the lower Yenisei River. Three watersheds of various sizes were chosen to represent the characteristics of the regional landscape conditions. Samples of river flow, precipitation, snow cover, and permafrost ground ice were collected over the watersheds to determine isotopic composition of potential sources of water in a river flow over a two year period. Increases in air temperature over the last forty years have resulted in permafrost degradation and a decrease in the seasonal frost which is evident from soil temperature measurements, permafrost and active-layer monitoring, and analysis of satellite imagery. The lowering of the permafrost table has led to an increased storage capacity of permafrost affected soils and a higher contribution of ground water to river discharge during winter months. A progressive decrease in the thickness of the layer of seasonal freezing allows more water storage and pathways for water during the winter low period making winter discharge dependent on the timing and amount of late summer precipitation. There is a substantial seasonal variability of stable isotopic composition of river flow. Spring flooding corresponds to the isotopic composition of snow cover prior to the snowmelt. Isotopic composition of river flow during the summer period follows the variability of precipitation in smaller creeks, while the water flow of larger watersheds is influenced by the secondary evaporation of water temporarily stored in thermokarst lakes and bogs. Late summer precipitation determines the isotopic composition of texture ice within the active layer in tundra landscapes and the seasonal freezing layer in forested landscapes as well as the composition of the water flow during winter months.