Reassessing the role of urban green space in air pollution control.

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

The effectiveness of moderating harmful online content.

In 2022, the European Union introduced the Digital Services Act (DSA), a new legislation to report and moderate harmful content from online social networks. Trusted flaggers are mandated to identify harmful content, which platforms must remove within a set delay (currently 24 h). Here, we analyze the likely effectiveness of EU-mandated mechanisms for regulating highly viral online content with short half-lives. We deploy self-exciting point processes to determine the relationship between the regulated moderation delay and the likely harm reduction achieved. We find that harm reduction is achievable for the most harmful content, even for fast-paced platforms such as Twitter. Our method estimates moderation effectiveness for a given platform and provides a rule of thumb for selecting content for investigation and flagging, managing flaggers' workload.

CNApy: a CellNetAnalyzer GUI in Python for analyzing and designing metabolic networks.

SUMMARY: Constraint-based reconstruction and analysis (COBRA) is a widely used modeling framework for analyzing and designing metabolic networks. Here, we present CNApy, an open-source cross-platform desktop application written in Python, which offers a state-of-the-art graphical front-end for the intuitive analysis of metabolic networks with COBRA methods. While the basic look-and-feel of CNApy is similar to the user interface of the MATLAB toolbox CellNetAnalyzer, it provides various enhanced features by using components of the powerful Qt library. CNApy supports a number of standard and advanced COBRA techniques and further functionalities can be easily embedded in its GUI facilitating modular extension in the future. AVAILABILITY AND IMPLEMENTATION: CNApy can be installed via conda and its source code is freely available at https://github.com/cnapy-org/CNApy under the Apache 2 license.

StrainDesign: a comprehensive Python package for computational design of metabolic networks.

SUMMARY: Various constraint-based optimization approaches have been developed for the computational analysis and design of metabolic networks. Herein, we present StrainDesign, a comprehensive Python package that builds upon the COBRApy toolbox and integrates the most popular metabolic design algorithms, including nested strain optimization methods such as OptKnock, RobustKnock and OptCouple as well as the more general minimal cut sets approach. The optimization approaches are embedded in individual modules, which can also be combined for setting up more elaborate strain design problems. Advanced features, such as the efficient integration of GPR rules and the possibility to consider gene and reaction additions or regulatory interventions, have been generalized and are available for all modules. The package uses state-of-the-art preprocessing methods, supports multiple solvers and provides a number of enhanced tools for analyzing computed intervention strategies including 2D and 3D plots of user-selected metabolic fluxes or yields. Furthermore, a user-friendly interface for the StrainDesign package has been implemented in the GUI-based metabolic modeling software CNApy. StrainDesign provides thus a unique and rich framework for computational strain design in Python, uniting many algorithmic developments in the field and allowing modular extension in the future. AVAILABILITY AND IMPLEMENTATION: The StrainDesign package can be retrieved from PyPi, Anaconda and GitHub (https://github.com/klamt-lab/straindesign) and is also part of the latest CNApy package.

Modified skulls but conservative brains? The palaeoneurology and endocranial anatomy of baryonychine dinosaurs (Theropoda: Spinosauridae).

The digital reconstruction of neurocranial endocasts has elucidated the gross brain structure and potential ecological attributes of many fossil taxa, including Irritator, a spinosaurine spinosaurid from the "mid" Cretaceous (Aptian) of Brazil. With unexceptional hearing capabilities, this taxon was inferred to integrate rapid and controlled pitch-down movements of the head that perhaps aided in the predation of small and agile prey such as fish. However, the neuroanatomy of baryonychine spinosaurids remains to be described, and potentially informs on the condition of early spinosaurids. Using micro-computed tomographic scanning (µCT), we reconstruct the braincase endocasts of Baryonyx walkeri and Ceratosuchops inferodios from the Wealden Supergroup (Lower Cretaceous) of England. We show that the gross endocranial morphology is similar to other non-maniraptoriform theropods, and corroborates previous observations of overall endocranial conservatism amongst more basal theropods. Several differences of unknown taxonomic utility are noted between the pair. Baryonychine neurosensory capabilities include low-frequency hearing and unexceptional olfaction, whilst the differing morphology of the floccular lobe tentatively suggests less developed gaze stabilisation mechanisms relative to spinosaurines. Given the morphological similarities observed with other basal tetanurans, baryonychines likely possessed comparable behavioural sophistication, suggesting that the transition from terrestrial hypercarnivorous ancestors to semi-aquatic "generalists" during the evolution of Spinosauridae did not require substantial modification of the brain and sensory systems.

Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning.

Conventional monitoring systems for air quality, such as reference stations, provide reliable pollution data in urban settings but only at relatively low spatial density. This study explores the potential of low-cost sensor systems (LCSs) deployed at homes of residents to enhance the monitoring of urban air pollution caused by residential wood burning. We established a network of 28 Airly (Airly-GSM-1, SP. Z o.o., Poland) LCSs in Kristiansand, Norway, over two winters (2021-2022). To assess performance, a gravimetric Kleinfiltergerät measured the fine particle mass concentration (PM2.5) in the garden of one participant's house for 4 weeks. Results showed a sensor-to-reference correlation equal to 0.86 for raw PM2.5 measurements at daily resolution (bias/RMSE: 9.45/11.65 µg m-3). High-resolution air quality maps at a 100 m resolution were produced by combining the output of an air quality model (uEMEP) using data assimilation techniques with the network data that were corrected and calibrated by using a proposed five-step network data processing scheme. Leave-one-out cross-validation demonstrated that data assimilation reduced the model's RMSE, MAE, and bias by 44-56, 38-48, and 41-52%, respectively.

Survival-Adjusted FEV1 and BMI Percentiles for Patients with Cystic Fibrosis before the Era of Triple CFTR Modulator Therapy in Germany.

BACKGROUND: Pulmonary disease is the major cause for morbidity and mortality in cystic fibrosis (CF). In CF, forced expiratory volume in 1 s (FEV1) referenced against a healthy population (FEV1%predicted) and body mass index (BMI) do not allow for the comparison of disease severity across age and gender. OBJECTIVES: We aimed to determine updated FEV1 and BMI percentiles for patients with CF and to study their dependence on mortality attrition. METHODS: Age- and height-adjusted FEV1 and BMI percentiles for CF patients aged 6-50 years were calculated from 4,947 patients of the German CF Registry for the period 2016-2019 utilizing quantile regression and a Generalized Additive Model for Location, Scale and Shape (GAMLSS). Further, survival-adjusted percentiles were estimated. RESULTS: In patients with CF, FEV1 increased throughout childhood until maximal median values at 16 years in females (2.46 L) and 18 years in males (3.27 L). During adulthood, FEV1 decreased substantially. At 17 years of age, the 25th BMI percentile of patients with CF (females 18.50 and males 18.15 kg/m2) was below the 10th BMI percentile of the German reference cohort. From the age of 20 years, survival (96.3%) decreased tremendously. At 50 years of age (survival 15.0%), the 50th CF-specific FEV1 or BMI percentile among the survivors corresponded to the 92.5th percentile among the total CF birth cohort. CONCLUSIONS: Continuously updated disease-specific FEV1 and BMI percentiles with correction for survival may serve as age-independent measure of disease severity in CF (accessible via https://cfpercentiles.statup.solutions).

Ontogenetic changes in cortical bone vascular microstructure in the domestic duck (Anas platyrhynchos) and ring-necked pheasant (Phasianus colchicus).

Age-related changes in bone microstructure can inform our understanding the biology of both extant and fossil birds, but to date, histological work in birds, and particularly work using high-resolution 3D imaging, has largely been restricted to limited growth stages. We used minimally destructive synchrotron radiation-based X-ray computed tomography to visualise and measure key morphological and histological traits in 3D across development in the domestic duck and ring-necked pheasant. We use these measurements to build on the database of key reference material for interpreting bone histology. We found that growth patterns differed between the two species, with the ducks showing rapid growth in their lower limbs and early lower limb maturation, while pheasants grew more slowly, reflecting their later age at maturity. In the pheasant, both walking and flight occur early and their upper and lower limbs grew at similar rates. In the duck, flight and wing development are delayed until the bird is almost at full body mass. Through juvenile development, the second moment of area for the duck wing was low but increased rapidly towards the age of flight, at which point it became significantly greater than that of the lower limb, or the pheasant. On a microstructural level, both cortical porosity and canal diameter were related to cortical bone deposition rate. In terms of orientation, vascular canals in the bone cortex were more laminar in the humerus and femur compared with the tibiotarsus, and laminarity increased through juvenile development in the humerus, but not the tibiotarsus, possibly reflecting torsional vs compressive loading. These age-related changes in cortical bone vascular microstructure of the domestic duck and pheasant will help understanding the biology of both extant and fossil birds, including age estimation, growth rate and growth patterns, and limb function.

An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets.

The concept of minimal cut sets (MCS) provides a flexible framework for analyzing properties of metabolic networks and for computing metabolic intervention strategies. In particular, it has been used to support the targeted design of microbial strains for bio-based production processes. Herein we present a number of major extensions that generalize the existing MCS approach and broaden its scope for applications in metabolic engineering. We first introduce a modified approach to integrate gene-protein-reaction associations (GPR) in the metabolic network structure for the computation of gene-based intervention strategies. In particular, we present a set of novel compression rules for GPR associations, which effectively speedup the computation of gene-based MCS by a factor of up to one order of magnitude. These rules are not specific for MCS and as well applicable to other computational strain design methods. Second, we enhance the MCS framework by allowing the definition of multiple target (undesired) and multiple protected (desired) regions. This enables precise tailoring of the metabolic solution space of the designed strain with unlimited flexibility. Together with further generalizations such as individual cost factors for each intervention, direct combinations of reaction/gene deletions and additions as well as the possibility to search for substrate co-feeding strategies, the scope of the MCS framework could be broadly extended. We demonstrate the applicability and performance benefits of the described developments by computing (gene-based) Escherichia coli strain designs for the bio-based production of 2,3-butanediol, a chemical, that has recently received much attention in the field of metabolic engineering. With our extended framework, we could identify promising strain designs that were formerly unpredictable, including those based on substrate co-feeding.

Nanostructure surveys of macroscopic specimens by small-angle scattering tensor tomography.

The mechanical properties of many materials are based on the macroscopic arrangement and orientation of their nanostructure. This nanostructure can be ordered over a range of length scales. In biology, the principle of hierarchical ordering is often used to maximize functionality, such as strength and robustness of the material, while minimizing weight and energy cost. Methods for nanoscale imaging provide direct visual access to the ultrastructure (nanoscale structure that is too small to be imaged using light microscopy), but the field of view is limited and does not easily allow a full correlative study of changes in the ultrastructure over a macroscopic sample. Other methods of probing ultrastructure ordering, such as small-angle scattering of X-rays or neutrons, can be applied to macroscopic samples; however, these scattering methods remain constrained to two-dimensional specimens or to isotropically oriented ultrastructures. These constraints limit the use of these methods for studying nanostructures with more complex orientation patterns, which are abundant in nature and materials science. Here, we introduce an imaging method that combines small-angle scattering with tensor tomography to probe nanoscale structures in three-dimensional macroscopic samples in a non-destructive way. We demonstrate the method by measuring the main orientation and the degree of orientation of nanoscale mineralized collagen fibrils in a human trabecula bone sample with a spatial resolution of 25 micrometres. Symmetries within the sample, such as the cylindrical symmetry commonly observed for mineralized collagen fibrils in bone, allow for tractable sampling requirements and numerical efficiency. Small-angle scattering tensor tomography is applicable to both biological and materials science specimens, and may be useful for understanding and characterizing smart or bio-inspired materials. Moreover, because the method is non-destructive, it is appropriate for in situ measurements and allows, for example, the role of ultrastructure in the mechanical response of a biological tissue or manufactured material to be studied.

Calibration of CO, NO2, and O3 Using Airify: A Low-Cost Sensor Cluster for Air Quality Monitoring.

During the last decade, extensive research has been carried out on the subject of low-cost sensor platforms for air quality monitoring. A key aspect when deploying such systems is the quality of the measured data. Calibration is especially important to improve the data quality of low-cost air monitoring devices. The measured data quality must comply with regulations issued by national or international authorities in order to be used for regulatory purposes. This work discusses the challenges and methods suitable for calibrating a low-cost sensor platform developed by our group, Airify, that has a unit cost five times less expensive than the state-of-the-art solutions (approximately €1000). The evaluated platform can integrate a wide variety of sensors capable of measuring up to 12 parameters, including the regulatory pollutants defined in the European Directive. In this work, we developed new calibration models (multivariate linear regression and random forest) and evaluated their effectiveness in meeting the data quality objective (DQO) for the following parameters: carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). The experimental results show that the proposed calibration managed an improvement of 12% for the CO and O3 gases and a similar accuracy for the NO2 gas compared to similar state-of-the-art studies. The evaluated parameters had different calibration accuracies due to the non-identical levels of gas concentration at which the sensors were exposed during the model's training phase. After the calibration algorithms were applied to the evaluated platform, its performance met the DQO criteria despite the overall low price level of the platform.

Characterizing and ranking computed metabolic engineering strategies.

MOTIVATION: The computer-aided design of metabolic intervention strategies has become a key component of an integrated metabolic engineering approach and a broad range of methods and algorithms has been developed for this task. Many of these algorithms enforce coupling of growth with product synthesis and may return thousands of possible intervention strategies from which the most suitable strategy must then be selected. RESULTS: This work focuses on how to evaluate and rank, in a meaningful way, a given pool of computed metabolic engineering strategies for growth-coupled product synthesis. Apart from straightforward criteria, such as a preferably small number of necessary interventions, a reasonable growth rate and a high product yield, we present several new criteria useful to pick the most suitable intervention strategy. Among others, we investigate the robustness of the intervention strategies by searching for metabolites that may disrupt growth coupling when accumulated or secreted and by checking whether the interventions interrupt pathways at their origin (preferable) or at downstream steps. We also assess thermodynamic properties of the pathway(s) favored by the intervention strategy. Furthermore, strategies that have a significant overlap with alternative solutions are ranked higher because they provide flexibility in implementation. We also introduce the notion of equivalence classes for grouping intervention strategies with identical solution spaces. Our ranking procedure involves in total ten criteria and we demonstrate its applicability by assessing knockout-based intervention strategies computed in a genome-scale model of E.coli for the growth-coupled synthesis of l-methionine and of the heterologous product 1,4-butanediol. AVAILABILITY AND IMPLEMENTATION: The MATLAB scripts that were used to characterize and rank the example intervention strategies are available at http://www2.mpi-magdeburg.mpg.de/projects/cna/etcdownloads.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

X-ray Micro-Computed Tomography for Nondestructive Three-Dimensional (3D) X-ray Histology.

Historically, micro-computed tomography (µCT) has been considered unsuitable for histologic analysis of unstained formalin-fixed, paraffin-embedded soft tissue biopsy specimens because of a lack of image contrast between the tissue and the paraffin. However, we recently demonstrated that µCT can successfully resolve microstructural detail in routinely prepared tissue specimens. Herein, we illustrate how µCT imaging of standard formalin-fixed, paraffin-embedded biopsy specimens can be seamlessly integrated into conventional histology workflows, enabling nondestructive three-dimensional (3D) X-ray histology, the use and benefits of which we showcase for the exemplar of human lung biopsy specimens. This technology advancement was achieved through manufacturing a first-of-kind µCT scanner for X-ray histology and developing optimized imaging protocols, which do not require any additional sample preparation. 3D X-ray histology allows for nondestructive 3D imaging of tissue microstructure, resolving structural connectivity and heterogeneity of complex tissue networks, such as the vascular network or the respiratory tract. We also demonstrate that 3D X-ray histology can yield consistent and reproducible image quality, enabling quantitative assessment of a tissue's 3D microstructures, which is inaccessible to conventional two-dimensional histology. Being nondestructive, the technique does not interfere with histology workflows, permitting subsequent tissue characterization by means of conventional light microscopy-based histology, immunohistochemistry, and immunofluorescence. 3D X-ray histology can be readily applied to a plethora of archival materials, yielding unprecedented opportunities in diagnosis and research of disease.

Quantifying intracortical bone microstructure: A critical appraisal of 2D and 3D approaches for assessing vascular canals and osteocyte lacunae.

Describing and quantifying vascular canal orientation and volume of osteocyte lacunae in bone is important in studies of bone growth, mechanics, health and disease. It is also an important element in analysing fossil bone in palaeohistology, key to understanding the growth, life and death of extinct animals. Often, bone microstructure is studied using two-dimensional (2D) sections, and three-dimensional (3D) shape and orientation of structures are estimated by modelling the structures using idealised geometries based on information from their cross sections. However, these methods rely on structures meeting strict geometric assumptions. Recently, 3D methods have been proposed which could provide a more accurate and robust approach to bone histology, but these have not been tested in direct comparison with their 2D counterparts in terms of accuracy and sensitivity to deviations from model assumptions. We compared 2D and 3D methodologies for estimating key microstructural traits using a combination of experimental and idealised test data sets. We generated populations of cylinders (canals) and ellipsoids (osteocyte lacunae), varying the cross-sectional aspect ratios of cylinders and orientation of ellipsoids to test sensitivity to deviations from cylindricality and longitudinal orientation, respectively. Using published methods, based on 2D sections and 3D data sets, we estimated cylinder orientation and ellipsoid volume. We applied the same methods to six CT data sets of duck cortical bone, using the full volumes for 3D measurements and single CT slices to represent 2D sections. Using in silico test data sets that did deviate from ideal cylinders and ellipsoids resulted in inaccurate estimates of cylinder or canal orientation, and reduced accuracy in estimates of ellipsoid and lacunar volume. These results highlight the importance of using appropriate 3D imaging and quantitative methods for quantifying volume and orientation of 3D structures and offer approaches to significantly enhance our understanding of bone physiology based on accurate measures for bone microstructures.

Imaging techniques for observing laminar geometry in the feather shaft cortex.

Bird feather shafts are light, stiff and strong, but the fine details of how their structure, mechanics and function relate to one another remains poorly understood. The missing piece in our understanding may be the various fibrous layers that make up the shaft's cortex. Detailed imaging techniques are needed to enable us to capture, analyse and quantify these layers before we can begin to unravel the relationship between their structure, mechanics and function. We show that Serial-Block-Face scanning electron microscopy, scanning confocal polarised microscopy and synchrotron-based computed tomography are three suitable techniques to investigate layer thickness and fibre orientation in the feather cortex. These techniques and other are discussed in terms of their ability to resolve the fibrous laminar structure of the feather cortex, on sample preparation, and on throughput. Annotated images are presented for each and less suitable techniques are presented in the Supplementary Material. LAY DESCRIPTION: Bird feathers have a light, stiff and strong central shaft. However, the fine details of how their structure, mechanics and function relate to one another remains poorly understood. The missing piece in our understanding may have to do with how fibrous layers within the shaft vary in thickness and alignment. Detailed imaging techniques are needed so that we can quantify some of this variation before we can revisit some long-unanswered questions about the feather shaft's structure, mechanics and function. We investigate a number of microscopy techniques and show that three techniques are suitable for the sort of investigation that is required. These techniques and others are discussed in terms of their ability to resolve the layers' thickness and alignment, on sample preparation, and on the sample sizes they are able to process. Annotated images are presented and discussed for each of the three techniques and unsuitable techniques receive the same examination in the Supplementary Material.

Precursor-Directed Biosynthesis and Fluorescence Labeling of Clickable Microcystins.

Microcystins, cyclic nonribosomal heptapeptides, are the most well-known cyanobacterial toxins. They are exceptionally well studied, but open questions remain concerning their physiological role for the producing microorganism or their suitability as lead compounds for anticancer drug development. One means to study specialized metabolites in more detail is the introduction of functional groups that make a compound amenable for bioorthogonal, so-called click reactions. Although it was reported that microcystins cannot be derivatized by precursor-directed biosynthesis, we successfully used this approach to prepare clickable microcystins. Supplementing different azide- or terminal alkyne containing amino acid analogues into the cultivation medium of microcystin-producing cyanobacteria strains, we found that these strains differ strongly in their substrate acceptance. Exploiting this flexibility, we generated more than 40 different clickable microcystins. We conjugated one of these derivatives with a fluorogenic dye and showed that neither incorporation of the unnatural amino acid analogue nor attachment of the fluorescent label significantly affects the cytotoxicity against cell lines expressing the human organic anion transporting polypeptides 1B1 or 1B3. Using time-lapse microscopy, we observed that the fluorescent microcystin is rapidly taken up into eukaryotic cells expressing these transporters.

Method for direct coupling of a semiconductor quantum dot to an optical fiber for single-photon source applications.

We present an effective method for direct fiber coupling of a quantum dot (QD) that is deterministically incorporated into a cylindrical mesa. For precise positioning of the fiber with respect to the QD-mesa, we use a scanning procedure relying on interference of light reflected back from the fiber end-face and the top surface of the mesa, applicable for both single-mode and multi-mode fibers. The central part of the fiber end-face is etched to control the required distance between the top surface of the mesa and the fiber core. Emission around 1260 nm from a fiber-coupled InGaAs/GaAs QD is demonstrated and its stability is proven over multiple cooling cycles. Moreover, a single photon character of emission from such system for a line emitting above 1200 nm is proven experimentally by photon autocorrelation measurements with an obtained value of the second order correlation function at zero time-delay well below 0.5.

Numerical optimization of the extraction efficiency of a quantum-dot based single-photon emitter into a single-mode fiber.

We present a numerical method for the accurate and efficient simulation of strongly localized light sources, such as quantum dots, embedded in dielectric micro-optical structures. We apply the method in order to optimize the photon extraction efficiency of a single-photon emitter consisting of a quantum dot embedded into a multi-layer stack with further lateral structures. Furthermore, we present methods to study the robustness of the extraction efficiency with respect to fabrication errors and defects.

Localized real-time information on outdoor air quality at kindergartens in Oslo, Norway using low-cost sensor nodes.

In Norway, children in kindergartens spend significant time outdoors under all weather conditions, and there is thus a natural concern about the quality of outdoor air. It is well known that air pollution is associated with a wide variety of adverse health impacts for children, with greater impact on children with asthma. Especially during winter and spring, kindergartens in Oslo that are situated close to streets with busy traffic, or in areas where wood burning is used for house heating, can experience many days with bad air quality. During these periods, updated information on air quality levels can help the kindergarten teachers to plan appropriate outdoor activities and thus protect children's health. We have installed 17 low-cost air quality nodes in kindergartens in Oslo. These nodes are smaller, cheaper and less complex to use than traditional equipment. Performance evaluation shows that while they are less accurate and suffer from higher uncertainty than reference equipment, they still can provide reliable coarse information about local pollution. The main challenge when using this technology is that calibration parameters might change with time depending on the atmospheric conditions. Thus, even if the sensors are calibrated a priori, once deployed, and especially if they are deployed for a long time, it is not possible to determine if a node is over- or under-estimating the concentration levels. To enhance the data from the sensors, we employed a data fusion technique that allows generating a detailed air quality map merging the data from the sensors and the data from an urban model, thus being able to offer air quality information to any location within Oslo. We arranged a focus group with the participation of local administration, kindergarten staff and parents to understand their opinion and needs related to the air quality information that was provided to the participant kindergartens. They expressed concern about the data quality but agree that having updated information on the air quality in the surroundings of kindergartens can help them to reduce children's exposure to air pollution.

[Analysis of medical diagnostic reports (constats) on dental injuries from terminological, dental and forensic medical points of view]. / Fogászati sérülésekrol készült látleletek komplex terminológiai, fogászati és igazságügyi orvosszakértoi elemzése.

Writing a constat is a professional skill required of every general physician and dentist. Constats are issued by healthcare providers on the investigating authority's, court's or injured person's request. This document is an official judicial evidence, a record of medical examination, and it is also a medical opinion which can determine the outcome of the subsequent legal process. Incomplete and incorrect injury descriptions make it difficult for forensic experts to form accurate and appropriate opinions. The authors examined 147 dental and oral surgical constats from the Universities of Pécs and Debrecen using multidisciplinary approach (according to terminological, dental, surgical, forensic and criminal legal aspects). Several medical reports contained mistakes in terms of inaccuracies and self-contradictions, terminology and professional medical practice. The documents included 352 injuries (11.1% of which were tooth injuries, 47.7% bone injuries and 41.2% soft-tissue injuries). The low number of attributes per injury (0.64 on average) indicates insufficient documentation. As a result of the comparative analysis, significant differences were found between the documentation of dental injuries and that of other bone injuries pertaining to their information content. We can state that physicians are most consistent when describing bone injuries, while they are less articulate about tooth injuries. The authors provide an overview of the legal consequences of injuries as well as the legal practice regarding tooth injuries in Germany and Austria, and recommend the creation of a nationwide, unified terminology for both dental and trauma departments on nasal and dental injuries. Orv Hetil. 2018; 159(51): 2154-2161.