This research employed extensive numerical analyses to locate the weak areas and determine the structural issues critical to preventing the spread of collapse. As a result, three specimens were tested using scaled models of strengthened and unstrengthened steel beam–column joint assemblies. The data were utilized to verify numerical models. One simple shear joint from the three experimental assemblies was used as the control specimen (unstrengthened joint). The second was a bolted steel beam–column joint utilized as a reference specimen to reflect the ideal beam–column joint generally employed in intermediate moment-resisting frames in seismic zones worldwide. Similar to the control, the third specimen (strengthened joint) had two side plates welded together to strengthen the connection site. Numerical finite element models were developed using ABAQUS (2020) software to extensively investigate the behavior of steel frame assemblies before and after upgrading. The FEM matrix comprised 17 specimens with varying parameters, including plate thickness, steel grade, a joint between the beam flange-strengthening plates, and a column that was either welded or not welded. The effectiveness of the strengthening techniques was established by comparing the mode of failure and load–displacement characteristics of the investigated specimens. The results indicate that the average increase in peak load due to a change in plate thickness for grades A36 and A572 is approximately 22% and 8%, respectively. Plates made of A572 steel increase peak load by 30%. All strengthened specimens attained catenary action, mitigating the possibility of progressive collapse. Progressive collapse is defined as the spread of a local failure from one portion to the next, causing the structure or a substantial portion of it to collapse. An alternate pathway approach is used to resist structure collapse. In this strategy, gradual collapse does not occur if a crucial component  fails. In case a column of steel building frame collapses due to blast or seismic loads, steel framed structures must have well-defined redundancies so that other load pathways are available by catenary action (CA) ,4,5,6,7.Many studies ,13,14,15Several different kinds of bolted steel beam–column connections were studied by Yang, B., and Tan KH.  using a After exploring the literature on moment connections under column loss, Alrubaidi, M. et al.  providedSteel beam–column joints must be successfully upgraded, which presented several difficulties. Previous published research literature on the subject of strengthening steel beam–column connections about mitigating or preventing progressive collapse have been lacking. For steel-framed buildings to improve their structural performance, some researchers, including Alrubaidi, M. et al.   joint specimen with bolted unstiffened extended endplate with pre-tensioned high-strength bolts designed and detailed as per ANSI/AISC 358-16 [The proposed strengthening system causes substantial improvement in the progressive collapse mitigation of the structure that is caused by the column damage, owing to the exposure of an extreme load event, leading to its ineffectiveness in carrying the loads. Although the proposed strengthening scheme is shown for a typical beam-–column connection, this can be easily implemented in all types of steel beam–column connections viz: (i) simple (pinned) connections, (ii) semi-rigid connections, and (iii) moment connections.The importance of this system is of strengthening beam–column connections of steel frames for making them capable of developing catenary action in beams for resisting progressive collapse under extreme load scenarios such as blast-generated waves, vehicle crash against a column, or earthquake, the supported floors start caving in, which is resisted by the proposed strengthening scheme through the development of catenary action in beams. The proposed system is simple and easy to construct. The connections are made using commercially available steel plates. The scheme does not require very precise construction and fabrication tolerances. The FE models of the three steel assemblies with typical existing simple shear, moment and the strengthened specimen were validated in a previous study by Alrubaidi, M. et al. . An experimental study was completed at King Saud University to examine the progressive collapse resistance of steel beam-column assemblies having two types of simple shear connections under the loss of the middle column ,29. The A single-plate shear connection was used in the first J-S-C specimen, shown in The test set-up and equipment required the limiting of lateral out-of-plane movement of steel beams and excessive rotation at the end of columns for all specimens to acquire the behavior of the full-scale structure and duplicate the effect of surrounding stories. u,CA, we used strain gages to monitor the axial strain change in the steel-beam section along the beam depth, as shown in u,FA) and CA resistance  contribute equally to the overall resistance Pu [To calculate the axial load in the steel-beams Ntance Pu ,29. The Peak vertical loads during the flexural and CA phases are shown in The test steel frame went through three different phases during the test of the J-M-C moment joint. The specimen was initially rigid because the bolts were pretensioned. However, after a 29 mm movement down for the middle steel column, the separation began at the middle connection between the column flange and the end plate, and the corresponding load was A 175 kN. Flexural stiffness decreased upon detachment , and as The failure mechanism of the J-S-S-EX specimen, which was strengthened with welded double-side steel plates within the joint area, is shown in A parametric numerical program that was developed using the ABAQUS (2020) software  is shownE-εE) curves obtained from each tensile test, we were able to get the true stress–strain (σtrue-εtrue) curves shown in Standard steel coupons (welded T-stub and bolted T-stub) were subjected to tensile testing in accordance with the 40. ASTM A370-05 ) to the Typical steel coupons appear to weaken after reaching their maximum load because to necking, although they are really hardening ,29. The It should be mentioned that in The fidelity of the FE models was checked against experimental data collected for this study. The load–displacement characteristic and failure mechanism in the FE research results are reviewed in light of this validation. The primary load–displacement findings for the steel test frame are compared between experimental and numerical predictions in Calibration of all connections between the steel beam and the steel column, and how to carry it out under progressive collapse, was one of the validation objectives for the experimental specimens developed in this work. After finding agreement between experimental and numerical studies, the team decided to expand their investigation by conducting a parametric study, which considers the strengthening investigation of steel beam–column joint using steel plates for progressive collapse mitigation by varying parameters such as plate thickness, steel grade, a joint between the beam flange-strengthening plates, and a column that was either welded or not welded.The calibrated FEMs were expanded to examine the effect of varying side double steel plate scheme parameters on the behavior of upgraded steel frames caused by the elimination of the central column. The FEM matrix had 17 specimens with varied features, including steel plate thickness, steel grade , and welding between the steel-beam flange-stiffening plates , we find the thickness from 6 mm to 12 mm, whether welded or non-welded, the collapse is in the critical region for sides plates, which is at the face of the column a–c. The When considering the effect of materials type between A572 and A36, the change in materials certainly has a significant effect on raising the efficiency of joints in mitigating progressive collapse , where iTo investigate the effects of welding the beam flange-stiffening plates to the removed center steel column on the progressive collapse , weldingThe numerical outcomes of the 17 specimens used in the parametric research are shown in It was discovered that there is a limit to the progressive collapse resistance offered by simple beam–column connections. The linkages between these elements (beam and column) need to be strengthened so that the danger of progressive collapse may be reduced in significant existing buildings.It’s possible that the IMF connection, which is good for providing resistance to ground motions, will not be able to resist the progressive collapse.It is advised that a scheme be used for strengthening connections in multistory steel structures in order to mitigate the possibility of progressive collapse.The validated numerical models can be used for studying progressive collapse resistance of: (i) existing steel beam–column connections upgraded with any new strengthening scheme, (ii) newly developed steel moment beam–column connections.The following findings, which were derived from the research carried out for the study and offered as recommendations, are as follows:Experimental and validated numerical finite modeling is recommended to study the behavior of different strengthening designs such as: post-tension wire systems within the beam–column connection.It is recommended to develop simplified reduced finite element models using beam and spring elements to predict the progressive collapse risk of different types of steel beam–column connections due to column-loss events. This may include simple shear, IMF, and strengthened connections, and the models will be validated using the experimental results of this study in addition to other tests available in the literature. The validated reduced models may be further utilized to study the progressive collapse risk of existing multistory steel framed buildings under column loss events. Additionally, the progressive collapse risk of the full steel framed buildings, simulated using reduced FEMs, may be numerically investigated under blast generated waves. Further research is needed to study experimentally and numerically the effect of composite RC slabs on reducing the progressive collapse potential of different types of steel beam–column connections  under column-loss scenarios. Effect of different designs of metal studs should be included.As a result of the work that were carried out as part of this study, a number of possibilities and requirements relating to research have become apparent. The following is a list of significant areas that need additional investigation:The shear-specimen J-S-C had a significantly high risk of progressive collapse because there were not enough load pathways available.The load-deformation response during a sudden column removal event was significantly enhanced by the employment of welded double-sided steel plates in the beam-to-column joint zone for the upgrading of shear beam-to-column joints. The enhanced frame J-S-S-EX could support around 5.5 times the maximum load of its predecessor, designated J-S-C (control specimen). However, in the final state, the amount of energy dissipated in the test frame J-S-S-EX was around 11.0 times that in the control frame J-S-C.The strengthened frame J-S-S-EX was able to support around 1.6 times as much weight as the IMF test frame J-M-C. In addition, the peak energy absorbed by test frame J-S-S-EX was almost 1.80% more than that of IMF specimen J-M-C.Three parameters were numerically investigated for strengthening of the shear beam–column connections using welded double side plates: (i) plate thickness, (ii) steel grade, and (iii) connection between the beam flange-stiffening plates and the column .It should be noted that the average increase in the peak load due to the change in plate thickness from 6 mm to 15 mm is about 22% and 8% for grades A36 and A572, respectively.The average increase in the peak load due to the change in steel grade of plates from A36 to A572 is about 30%.The average increase in the load-carrying capacity due to welding between the beam flange-stiffening plates and column is about 25%. The results of the analysis for all parameters of this scheme show that the catenary action stage was reached in all specimens, which helps mitigate (or diminish) the progressive collapse risk.The specimen that used a side plate with 15 mm of thickness, regardless of whether it was made of A36 or A572 material, showed the greatest performance in load displacement characteristics when subjected to the progressive collapse test out of all of the FE tested specimens.The most important findings of the research are as follows:


To evaluate, in-vitro, the change in crown inclination that occurs during orthodontic leveling and alignment using different archwire-bracket-ligation combinations. TM and Time3® self-ligating brackets, Mini-Taurus® and Victory SeriesTM conventional brackets, and Synergy® conventional-low friction bracket. Conventional brackets were ligated with both stainless steel and elastomeric ligatures. The simulated malocclusion comprised 2.0mm gingival and 2.0mm labial displacements of a maxillary right central incisor. Rotation around the Y-axis  was measured for the different archwire-bracket-ligation combinations.  Four archwire types were tested: (1) 0.012-in stainless steel and (2) 0.0155-in stainless steel multi-stranded, (3) 0.012-in nitinol Orthonol® and (4) 0.012-in nitinol Thermalloy®. Combinations with five types of 0.022-in slot orthodontic brackets were tested: SmartClipTM brackets  and with Synergy® brackets ligated with stainless steel ligatures . The lower rotation was recorded when Thermalloy®, multi-stranded, and Orthonol® wires were ligated with elastomeric rings to Mini-Taurus® brackets  and to Victory SeriesTM brackets .  The largest rotation was measured whith Orthonol® and Thermalloy® wires when combined with SmartClipAll archwire-bracket-ligation combinations produced lingual crown inclination; however, lower changes were observed when the conventional brackets were ligated with elastomeric rings. The multi-stranded archwire produced less rotation with nearly every bracket-ligation combination, compared to the other archwires. The effect of the archwire-bracket-ligation combination on tooth inclination during leveling and alignment should be considered during planning treatment mechanics.  Two ligation methods were used: (1) Stainless steel wire ligatures and (2) Elastomeric rings. Each archwire-bracket-ligation combination was tested 20 times using a new archwire each time.Material: Four archwire types; two stainless steel (1) 0.012-in stainless steel  and (2) 0.0155-in multi-stranded ; and two nitinol wires (3) 0.012-in Orthonol,Testing machine: The Orthodontic Measurement and Simulation System (OMSS) is based on two sensors capable of 3D-recording of forces and moments. The OMSS is built in a temperature-controlled compartment. This is especially important for heat-managed alloys; therefore, during testing the nitinol archwires the temperature was kept at 37±1°C. Further details about the OMSS and its applications in orthodontics can be found in articles devoted to that purpose.® bracket. Tying the steel ligatures around the bracket wings was short one turn from complete tightening, to ensure free play between the wire and the brackets. In the case of self-ligating brackets, the archwire was inserted and then the clips or doors of the self-ligating brackets were closed. The right central incisor bracket was then bonded to a bracket holder using a jig to standardize the position to be repeated with every bracket. The design of the setup included positioning the center of resistance of the simulated misaligned central incisor at 10.0mm apically and 4.5mm lingual to the point of the force application. This position was set based on the design of the whole setup and the position of the bracket and the bracket holder, representing the simulated displaced central incisor.Preparing the measurement setup: Brackets were bonded with a cyanoacrylate adhesive from the right second premolar to the left second premolar of fabricated maxillary arch resin models. These resin models had the right central incisor removed to create a space for a bracket holder that would be connected to one of the sensors of the OMSS. The tested archwire was then tied to the conventional brackets with either stainless steel ligatures or elastomeric rings. The ligature wires or the elastomeric rings were tied around the two central wings of the six wings of the SynergyMeasurement procedures: Resin model was fixed in its position of the OMSS, and the bracket holder, with the right central incisor bracket bonded to it, was fixed to one of the force sensors of the OMSS . The senData extraction: Data was transferred from the OMSS software to Excel® sheets. ® sheets, and descriptive statistics including means and standard deviations were calculated for each archwire-bracket-ligation combination. Raw data was tested for normality and, as the data revealed normal distribution, a two-way analysis of variance ANOVA followed by Tukey Post-Hoc Test and Student t-test was employed using IBM SPSS Statistics for Windows .Data organization and statistical analyses: The maximum absolute values of rotation around the Y-axis were arranged in the Excelp< 0.001) and the archwire  selections on the rotation of the tooth around the Y-axis, and also a significant interaction between bracket type and archwire type .The results of two-way ANOVA  revealedversus elastomeric rings to a conventional bracket, showed a significant difference in the case of Mini-Taurus® and Victory SeriesTM brackets but, not in the case of Synergy® brackets. Pairwise comparisons (® brackets ligated with elastomeric rings (p=0.466) and with Time3® (p=0.465). From the pairwise comparisons  between parisons  revealed® bracket ligated with elastomeric rings produced rotation comparable to that produced by self-ligating brackets and conventional brackets ligated with stainless steel ligatures. The boxplots compare changes in crown inclination produced by self-ligating brackets to conventional brackets ligated with stainless steel ligatures  and elasThe registered changes in the maxillary incisor inclination in the present study varied significantly between the different archwire-bracket-ligation combinations; however, the direction of the change was constantly negative (-). According to the sign system proposed by Burstone and Koenig® brackets ligated with elastomeric rings produced comparable or more rotation. In the current study, the elastomeric ring was tied around the two central wings of the Synergy® bracket, which are raised, preventing the contact between the archwire and the ligature and thus ensuring free play between the archwire and the bracket slot walls. Meanwhile, steel ligature was tied slightly loose because this is the preferred method during leveling and alignment to allow free sliding and efficient tooth movement with less force exerted on the tooth. The play between the wire and the bracket slot is probably the most important factor influencing the labio-palatal inclination of teeth.® and Victory SeriesTM brackets were ligated with stainless steel ligatures than elastomeric rings, but Synergy® brackets showed insignificant difference and significantly higher rotation with multi-stranded archwire ligated with elastomeric rings. Because of the nature of this in-vitro study, new elastomeric rings were used for ligating each archwire. Controlling rotation could be the result of the seating force of the new elastomeric on the archwire. However, elastomeric rings deteriorate quickly in the oral cavity to the extent that they have been found to lose 40% of their force in the first 24 hours.Evaluating changes in crown inclination produced by each bracket when combined with the different archwires, as seen in TM a passive self-ligating bracket, and Synergy® a low friction conventional bracket whether ligated with stainless steel or elastomeric rings. The design of the Synergy® bracket and the method of ligating the archwire around the central wings (elastomeric rings or loose steel ligatures) made it comparable to the passive self-ligating bracket. The rotation produced by the two types of steel archwires was higher with Time3® brackets than SmartClipTM brackets, but differences were not significant. The rotation that was produced by the two types of nitinol archwires was higher with SmartClipTM brackets than Time3® brackets, and the difference was significant in case of Orthonol® archwire. It is noted that the active self-ligating Time3® brackets showed a wide range of rotation values with multi-stranded and Thermalloy® archwires, this evidence could be attributed to the interaction of the clip with these archwire materials while exerting a seating force on the archwire.There was no statistical difference, as shown in ,The change in crown inclination in the present study is the result of a rotational moment dependent on the force applied on the tooth and the distance from that point of force application to the designated center of resistance of the simulated misaligned central incisor. In this study design, the distance was standardized for all tests, therefore the changing factor is the force applied to the tooth from each archwire-bracket-ligation combination. These archwire-bracket-ligation combinations showed a significant interaction between the archwire and the bracket type, and a consistently higher force applied on the displaced central incisor when elastomeric rings were used, which consequently affected the correction of the malocclusion.-Orthodontic tooth movement is the result of a combination of many mechanical factors related to the bracket-archwire-ligation combination, including: bracket prescription, bracket slot dimension, bracket material, archwire dimension, archwire material, inter-bracket distance, and method of ligation .Clinically, multiple teeth or arch segments involved in the malocclusion will lead to complex force systems that sometimes might be hard to predict. Realizing the true complexity of the force systems that could result from the used biomechanics in the oral cavity would help clinicians to use biomechanics more efficiently and simply.Clinical relevance: Results could be useful as a guide when comparing orthodontic materials and planning biomechanics. Results contribute primarily to the understanding of the performance of an orthodontic appliance and how the outcomes are affected by each of the appliance components, as well as the interplay among the components that are in the present study: archwire, bracket, and ligation.Conventional brackets ligated with elastomeric rings produced the smallest rotation; however, low-friction conventional brackets did not show similar behavior. Passive self-ligating bracket and low-friction conventional bracket produced comparable rotation. Multi-stranded archwires produced less rotation with every bracket-ligation combination, compared to the other archwires.Controlling tooth inclination could start from the leveling and alignment stage by careful selection of the archwire-bracket-ligation combination.


Protein kinases are major drug targets. Most kinase inhibitors are directed against the adenosine triphosphate (ATP) cofactor binding site, which is largely conserved across the human kinome. Hence, such kinase inhibitors are often thought to be promiscuous. However, experimental evidence and activity data for publicly available kinase inhibitors indicate that this is not generally the case. We have investigated whether inhibitors of closely related human kinases with single- or multi-kinase activity can be differentiated on the basis of chemical structure. Therefore, a test system consisting of two distinct kinase triplets has been devised for which inhibitors with reported triple-kinase activities and corresponding single-kinase activities were assembled. Machine learning models derived on the basis of chemical structure distinguished between these multi- and single-kinase inhibitors with high accuracy. A model-independent explanatory approach was applied to identify structural features determining accurate predictions. For both kinase triplets, the analysis revealed decisive features contained in multi-kinase inhibitors. These features were found to be absent in corresponding single-kinase inhibitors, thus providing a rationale for successful machine learning. Mapping of features determining accurate predictions revealed that they formed coherent and chemically meaningful substructures that were characteristic of multi-kinase inhibitors compared with single-kinase inhibitors. In drug discovery, the ability of small molecules to interact with more than one protein in a well-defined manner provides the basis of polypharmacology; that is, the induction of the desired (or undesired) in vivo effects of drugs through the engagement of multiple targets ,2,3,4,5.In addition to experimental methods, computational data analysis and predictive modeling are also applicable to aid in the analysis of the multi-target activities of small molecules ,7,8,9. FSince ML model decisions are typically difficult to rationalize, the identification of structural features that determine accurate predictions requires the application of approaches for explaining ML ,23,24,25Using the tree-based SHAP approach, we previously attempted to identify the structural features that determined the accurate prediction of compounds active against given target pairs  vs. corresponding ST-CPDs . TargetsIn this work, we aimed to differentiate compounds with reported activity against single or multiple protein kinases, representing a scenario completely distinct from investigating compounds that are active against unrelated targets. Kinases represent a major class of drug targets  and the In order to investigate compounds with different activity against closely related targets, we assembled inhibitors with reported activity against triplets or in part very closely related kinases and other inhibitors only reported to be active against one of these kinases. First, we addressed the question of whether these corresponding single- and triple-kinase inhibitors  can be distinguished using ML models exclusively derived on the basis of chemical structure. Second, we attempted to rationalize the results of these predictions using the SHAP formalism and identified structural features decisive for prediction outcomes. Third, the findings were interpreted from a chemical perspective. i, IC50, or Kd) and an exact potency value (“=”) of at least 10 µM against human kinases were extracted  from ChEMBL (version 29) triazolopyridine substructure was present in 210 of 223 MT-CPDs, but in only 19 of 1206 JAK2, 2 of 722 JAK3 ST-CPDs and none of the 505 FAK1 ST-CPDs. Thus, the substructure was characteristic of triplet 1 MT-CPDs. This finding also explained the decisive role of extracted features defining this substructure for accurate predictions. All 210 MT-CPDs containing this substructure originated from a single patent source establishing triple-kinase activity . It follFor triplet 2, the substructure in MT-CPDs identified by feature mapping was imidazopyridazine, as depicted in For both characteristic substructures, we also found an X-ray structure of a complex formed between an inhibitor containing the substructure and a kinase from triple 1 and triple 2, respectively. In this work, we attempted to differentiate inhibitors with triple-kinase or corresponding single-kinase activity by ML on the basis of chemical structure, identify features determining accurate predictions, and interpret key features in chemical terms. Exploring the molecular origins of the varying promiscuity of ATP site-directed kinase inhibitors continues to be a topic of intense investigation in medicinal chemistry. For our analysis, we generated a test system consisting of kinase triplets for which sufficient numbers of MT- and ST-CPDs with high-confidence activity data were available to enable meaningful ML. Moreover, we specifically aimed to investigate closely related kinases from the same family most likely to have similar compound-binding characteristics. MT- and ST-CPDs from kinase triplet 1 and 2 were differentiated with high accuracy using ML models, providing evidence for the presence of distinguishing structural features. SHAP analysis then identified features determining the predictions. An important finding shows that accurate predictions resulted from features that were present in MT- but absent in ST-CPDs. These features were found to be chemically sensible, forming coherent substructures that were characteristic of MT-CPDs. ML prediction accuracy was nearly perfect for kinase triplet 1 and in this case, the characteristic substructure was present in 94% of all MT- and absent in 99% of all ST-CPDs, thus reflecting the high consistency of ML results and feature analysis. Taken together, the findings reported herein have methodological implications as well as implications for kinase inhibitor research. From a methodological point of view, our results clearly support the utility of explainable ML to rationalize predictions from a chemical or biological perspective and reveal structural information important for drug discovery and design, as exemplified by the identification of substructures characteristic of MT-CPDs. However, despite the consistency of the obtained results, they are difficult to generalize for kinase inhibitor research. ML and feature analysis, at least in part, depend on the composition of the investigated data sets and care must be taken not to over-interpret the findings. For example, while we can conclude with certainty from our analysis that the triazolopyridine and imidazopyridazine moieties identified herein are signatures of multi-kinase activity, we cannot conclude that the designated ST-CPDs assembled on the basis of currently available activity data are kinase-selective. Here, varying test frequencies among kinase inhibitors might come into play that are for the most part unknown for compounds collected from different sources and thus cannot be considered in the computational analysis. On the other hand, it makes perfect sense that designated ST-CPDs do not share characteristic structural features determining their prediction. The presence of such features in ST-CPDs would principally not be consistent with kinase selectivity, while the absence of shared features supports differences between these compounds. Clearly, such considerations are important for putting the results into perspective. However, explainable ML as presented herein yields, at the very least, experimentally testable hypotheses for distinguishing between inhibitors with single- and multi-kinase activity and for exploring further structural features implicated in promiscuity vs. selectivity.


There have been numerous risk tools developed to enable triaging of SARS-CoV-2 positive patients with diverse levels of complexity. Here we presented a simplified risk-tool based on minimal parameters and chest X-ray (CXR) image data that predicts the survival of adult SARS-CoV-2 positive patients at hospital admission. We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS-CoV-2 positive patients, respectively. External validation of the final model was conducted on 741 Accident and Emergency (A&E) admissions with suspected SARS-CoV-2 infection from a separate NHS Trust. The LUCAS mortality score included five strongest predictors , which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the area under the receiving operating characteristics curve (AUC-ROC) in development cohort 0.765 : 0.738–0.790), in internal validation cohort 0.744 (CI: 0.673–0.808), and in external validation cohort 0.752 (CI: 0.713–0.787). The discriminatory power of LUCAS increased slightly when including the CXR image data. LUCAS can be used to obtain valid predictions of mortality in patients within 60 days of SARS-CoV-2 RT-PCR results into low, moderate, high, or very high risk of fatality. Conditions remain strained, and there is a need to develop risk tools to enable accurate and rapid triaging of SARS-CoV-2 positive patients. While prognostic tools are available, there is an ongoing need to develop tools that enable healthcare professionals to prevent unnecessary hospital admission and also work in combination with other predictive models commonly used in practice. Any new model must support the healthcare professional’s experiential knowledge and clinical reasoning2 in both patient care management and allocation of limited healthcare resources.The UK National Health Service (NHS) experienced unprecedented pressure due to the recurrent surges of coronavirus disease 2019 (COVID-19) cases caused by the SARS-CoV-2 virus. To date, more than two million confirmed cases in the UK have forced healthcare professionals to face complex decisions on how to effectively triage patients on admission who may need acute care. Admissions to hospital have increased from 6894 to 8431 in the seven days ending 8th March 2022 in the UK where routine lateral flow testing by the general public is no longer required and are ‘incidentally diagnosed’5 scans. While CT is a sensitive tool, it is not used for periodic monitoring of patients. The use of x-ray is widespread and is used routinely to determine severity of lung injury. Its use has been included in numerous prognostic tools6, and in combination with other blood markers such as D-dimer, white blood count, and neutrophils7. However, some biomarkers such as D-dimer are not being routinely measured during hospital admission and triage.In hospitals, the main method used to detect COVID-19 is the reverse transcription-polymerase chain reaction (RT-PCR), and the severity of the infection determined by blood markers and chest radiological imaging such as X-ray and computed tomography (CT)9. Although favourable amongst healthcare professionals10, this predictive tool has caused increased false trigger rates for SARS-CoV-2 positive patients12. Another familiar tool in practice in the UK is the Acute Physiology and Chronic Health Evaluation II (APACHE II), which is a validated intensive care unit (ICU) scoring tool used to estimate ICU mortality. However, it has underestimated the mortality risk in SARS-CoV-2 positive patients13. Several published models have aimed to meet the clinician’s need to stratify high-risk SARS-CoV-2 positive patients; but they are yet to be widely clinically implemented or had poor clinician feedback14.Predictive models such as the National Early Warning Score 2 (NEWS2) is widely used in practice to observe and identify deteriorating patients15, which indicates that a low lymphocyte count is not an accurate marker taken alone17. Many studies have suggested the use of Interleukin 6 (IL6)16, Interleukin 10 (IL10)16, ferritin16, and D-Dimer17, since they are good discriminators of disease prognosis; but they are not routinely measured upon admission to hospital.There are varying reports of changes in the full blood count, with it being reported that 80% of COVID-19 patients with severe symptoms and 20% of mild cases presented with lymphopenia18. This model combines clinical data, routine laboratory tests and chest x-ray (CXR) data to improve risk stratification and clinical intervention for SARS-CoV-2 infection. Studies have shown CXR results add value in the triage of patients who are SARS-CoV-2 positive19; however, the incremental prognostic value of CXR6 in addition to clinical data and routine laboratory tests remains to be consolidated in practice.Here, we aim to avoid ‘clinical resistance’ by developing and validating a new simple and explainable prognostic tool that extends the widely used NEWS2 model20. The model’s development and reporting adhered to the TRIPOD  guidelines22 to publish a simple, user-friendly scoring system for adult patients admitted to hospital with SARS-CoV-2 infection. This resulted in improved integration of the best evidence into clinical care pathways that will assist clinicians in risk, patient, and resource management. The aim of this study was to develop a simple objective tool for risk stratification in SARS-CoV-2 infection by integrating results from rapid and routine clinical, laboratory and CXR image data that would easily support established triage practice in the hospital setting.We used well-defined predictors and outcomes to limit model overfitting23 that collated clinical data from secondary and tertiary NHS Trusts across the UK with the aim to support SARS-CoV-2 care pathways To evaluate the tool’s generalised performance, a second dataset was used for external validation. The data extracted from the Laboratory Information Management System (LIMS) came from a large NHS Foundation Trust hospital in north-east England UK, which had not participated in the NCCID initiative. Patients who were admitted with suspected SARS-CoV-2 infection at the Accident and Emergency (A&E) Department between 1st March 2020 and 21st August 2020 were included. This population was representative of the adult general population and therefore patients aged 16 years and younger were excluded, as the laboratory data thresholds vary compared to adults. The datasets are retrospective and therefore consent is not possible.The three datasets  consisted of data for adult patients with positive RT-PCR results for the SARS-CoV-2 virus. To mitigate the issues with the lower RT-PCR sensitivity and accuracy during the initial stages of the pandemic, NCCID provided an overall SARS-CoV-2 status that was derived from cumulative RT-PCR tests. This approach was also applied to identify SARS-CoV-2 positive patients in the external validation dataset.To evaluate the tool’s predictive performance, the NCCID dataset was non-randomly split with the admissions before 30th April 2020 making up the development cohort n = 1434) and admissions on or after 1st May 2020 making up the internal validation cohort (n = 310) , medications, clinical observations, chest imaging data, and laboratory parameters measured on admission. Chest X-ray (CXR) reports from the NCCID model development dataset and the external dataset were dichotomised as normal versus abnormal. All laboratory tests were measured before SARS-CoV-2 RT-PCR test and mortality date, which ensured these potential predictors were blinded to the outcome. The SARS-CoV-2 swab and RT-PCR results established the final COVID-19 status. In the event of deterioration, data points such as the NEWS2 score, Acute Physiology And Chronic Health Evaluation (APACHE) score, Intensive Therapy Unit (ITU) admission, intubation and mortality date were also recorded. Since the focus of the study was to identify predictors that were available at the point of admission, the ITU admission and intubation data were excluded in the final analysis.24.From this extensive list, only the demographics, clinical observations, and laboratory parameters recorded at the time of admission for SARS-CoV-2 positive patients were included in the analysis as key predictors. Previous medical history, smoking status and current pharmaceutical interventions were not included in the analysis. This rationale was based on consultations with biomedical scientists and clinicians working in A&E departments to determine which rapid and routine laboratory tests would be clinically relevant candidate predictors, as well as previously published literature on prognostic factors associated with SARS-CoV-2 infection for the model development25.To account for the risk of spurious selection or exclusion of important predictors in the model development, a minimum sample size of 380 was determined based on 10 outcome events per variable. Based on previous studies, a minimum sample size of 100 mortality events and 100 non-mortality events were required for external validation26. Continuous predictors such as the laboratory tests and age were retained as continuous variables and not converted into categorical predictors using thresholds.Reliability of data was ensured by excluding patients from the development and internal validation datasets if information was missing on key characteristics, such as RT-PCR SARS-CoV-2 positive results at admission, and mortality dates outside the 60-day prediction interval Fig. . Missing2). Elastic Net (GLMNET)27, weighted combination of Least Absolute Shrinkage and Selection Operator (LASSO), and ridge regression were used to select predictors of importance. The optimal value of the shrinkage estimator for LASSO and the relative weights for LASSO and ridge regression were chosen using a ten-fold cross validation using the R-package caret28. Additionally, the performance of the MLR model was compared with the performance of the Random Forest Machine Learning approach29. The variable selection and construction of the Random Forest was performed using ten-fold cross validation. In each case, the imbalance in the positive and negative training samples was accommodated using the Synthetic Minority Oversampling Technique (SMOTE).An initial multivariable logistic regression (MLR) model started with 13 predictors with less than 40% missing values , Creatinine, Platelets, Diastolic BP (Blood Pressure), Systolic BP, Temperature, Heart rate, PaOA second separate MLR model took a more pragmatic approach in predictor selection. From the 13 predictors of the first MLR model, we used only the blood panel measurements  along with age and sex. In addition, it was assessed whether the inclusion of either NEWS2 or CXR or both improved this model’s performance.30. We also evaluated the goodness of fit using the Brier score31, which is a measure to quantify the closeness of the probabilistic predictions to the binary ground-truth class labels. The score varies between 0 and 1, with the lower score indicating superior performance. Finally, the accuracy of the models was evaluated using the standard cut-off value of 0.5.Each model’s performance was assessed using Area Under the Receiving Operating Characteristics Curve (AUC-ROC) with a 95% confidence interval. The calibration performance of each model was measured as the slope of the calibration curve. The internal and external validation of each model were assessed with resampling. The predictor selection and entire modelling process were repeated in 1,000 bootstrap samples to estimate the realistic predictive measures for future patient cohorts. An AUC-ROC of 0.5 indicated a prediction based on random chance, 0.7–0.8 was considered acceptable, above 0.8 demonstrated excellent performance, and a value of 1.0 showed a perfect predictionThe internal validation included the NEWS2 score, which was not available for the external validation dataset. The statistical package R (3.5.3) was used to perform all statistical analyses and implement the methods employed in the model development, validation workflow, and primary model fitting, followed by both internal and external validation.De-identified and pseudo-anonymised patient data were obtained from datasets, and the methods used were approved by the ethics committee as part of the existing Cardiac Magnetic Resonance Imaging (MRI) Database NHS Research Ethics Committee (REC) Integrated Research Application System (IRAS) Ref: 222349 and University of Brighton REC (8011). The need for informed consent was waived by the ethics committee due to retrospective nature of the study.Overall, the NCCID database comprised of 3,818 patients (from 23rd January 2020 to 31st December 2020). The number of patients that met the inclusion and missingness criteria were 1434 and 310, for the development and internal validation datasets, respectively  Fig. . Each suAlong with the exact values of the probability of fatal outcome based on the five predictors, we propose a risk stratification Table  based onThough the percentage of missing predictors in our reduced models were negligible, sensitivity analysis was performed using complete case data and as expected the model performance did not change. We also note that the simple logistic regression was preferred over machine learning approaches such as Random Forest starting from same set of predictors, based on simplicity and their performance in the validation dataset.We have performed validation on an internal validation (NCCID Data between 1st May 2020 and 7th December 2020) cohort and external validation cohort consisting of data from a separate A&E site  with a small overlap with the available predictors from the derivation and internal validation cohort. However, all five predictors from the proposed model were present .The median age of patients from the internal validation dataset was 74 years (IQR 62–84), which was not significantly different from the external validation dataset with a median of 76 years IQR 61–84). The proportion of male patients was similar in both groups; 58% male in the internal validation set, and 55% male in external validation set  with an accuracy 0.796 at the standard cut-off of 0.50 for the probability of a SARS-CoV-2 positive patient dying within 60 days of a positive test  compared to the internal dataset . By including CXR information, there is an improved prediction performance, with an AUC-ROC of 0.791 (CI: 0.746–0.833). Note that the NEWS2 score was not available for the external validation cohort, so this result could not be externally validated.We have developed and validated a simplified, fast-track mortality calculator based on three rapid and routine blood parameter measurements, age and sex, with the option to use CXR results. The LUCAS calculator is freely available, relies on objective measurements only, and has been both internally and externally validated. The primary intended use of the LUCAS calculator is to aid triage on patient admission to A&E following a positive SARS-CoV-2 RT-PCR test. The robustness and generalised results in the validation process classify the tool as an excellent candidate for risk management of the mortality level in a 60-day survival interval of adult SARS-CoV-2 positive patients. The LUCAS calculator delivered higher accuracy of the external validation compared with the internal validation set, which indicates a high level of generalisation. In addition, the incorporation of CXR results as normal versus abnormal improved the prediction performance.11, was also performed. As a result, a comprehensive study and evaluation of all the possible blood markers and clinical patient information were taken into consideration. This study shows that a simple and objective tool can risk stratify SARS-CoV-2 positive patients within one hour after hospital admission. The primary objective showed that rapid and routine laboratory blood tests and chest imaging data added predictive value beyond the RT-PCR test and clinical observations with high AUC-ROC.The NCCID dataset collected 38 clinical data points for each patient which served as candidate predictors. These predictors were categorised into demographics, risk factors, past medical history (PMH), medications, clinical observations, chest-imaging data, and laboratory parameters measured on admission to hospital. All laboratory tests were measured before the SARS-CoV-2 RT-PCR test result and mortality date, which ensured these potential predictors were blinded to the outcome. The SARS-CoV-2 swab and RT-PCR results established the final COVID-19 status. Moreover, thorough study of other included measures, such as the NEWS2 scoreThe ability of the LUCAS calculator to predict future outcomes was evaluated by non-randomly splitting the NCCID dataset to train on admissions before 30th April 2020 and predicting the outcomes for patients admitted on or after 1st May 2020. The high prediction results of LUCAS in the internal validation dataset, as well as in the external validation dataset from a different NHS site (between 1st March 2020 and 21st August 2020), demonstrates the model’s robust and generalised performance.32 and QCOVID33, which included large number of predictors in their algorithms. Our study is the first to combine a minimum number of blood results along with CXR data, to generate a simplified calculator based on as few objective predictors as possible.There have been many prognostic tools published, most notably the 4C Mortality Score32. However, gaining an accurate past medical history during triage is not always practical, and the 4C calculator was not externally validated. Our aim was to use the minimum number of predictors without losing accuracy, which was achieved using LUCAS that exhibits a similar level of prediction as the more complex and detailed 4C algorithm. The primary QCOVID score was developed as a risk prediction algorithm to estimate hospital admission and mortality outcomes, which also included large number of predictors including PMH33.The 4C Mortality Score includes 8 parameters including PMH, demographics and blood measurables, resulting in a higher AUC-ROC of 0.79034 or external validation35. Our study improves on these issues by conforming to the Prediction model Risk of Bias Assessment Tool (PROBAST)21 and being both internally validated from the same large NCCID dataset and externally validated in a smaller, separate hospital database. In addition, many studies require past medical history, or base the prediction on the underlying health conditions of the patient36. These data may be difficult to assess accurately on admission to hospital and may mislead should the patient have undiagnosed conditions. For this reason, we focused our model on measurables taken routinely on admission.Numerous prediction models have been developed to aid triage and research into COVID-19 disease severity. While a great deal of useful insight into the disease has been gained from these studies and prognostic tools, there is a range of outcomes mostly due to some having a high risk of bias, lack of transparency or lack of internal9. This compares to our NEWS2 findings of an AUC-ROC 0.59 in development cohort and 0.66 in internal validation cohort. When we combined NEWS2 with LUCAS in predicting mortality within 60 days, this increased the AUC-ROC to 0.77 in development cohort and 0.75 in internal validation cohort, thus indicating an improvement of accuracy when in combination with the LUCAS algorithm. This large increase in predictive power also gives weight to the use of LUCAS over NEWS2 in prognosis modelling for COVID-19.The NEWS2 score has been used routinely in hospitals to detect clinical deterioration, although it has mixed results in its success. In one multicentre retrospective study involving the inclusion of data from 1263 patients, the NEWS2 score was used to predict mortality, ICU admission and hospital mortality and resulted in an AUC-ROC of 0.65 for 30-day mortality37, urea38, and CRP44 are recognised as key measurable predictors of severity of SARS-CoV-2 infection, and age and sex are also well-known predictors of mortality43. While these factors have been used in other prediction models, our study is the first to use only these predictors in a prognostic score along with the option to use CXR data.All the predictors used in the LUCAS calculator have been shown to be useful predictors in other published studies. Lymphocyte count35 along with ten other parameters . More recently, some of the studies have included the CXR imaging in prognostic models46, with good accuracy; however, they have either utilised information such as electronic health records45 including comorbidities47, which are not always known at the point of care, additional blood biomarkers such as D-Dimer41 and lactate dehydrogenase42, which are not measured routinely during triage, or incorporated complex deep-learning methodologies46, affecting the explainability and simplicity of the model. Indeed, in a parallel study, we have developed a highly accurate deep-learning based model (DenResCov-19) to classify from CXR images patients positive for SARS-CoV-2, tuberculosis, and other forms of pneumonia6, which will be integrated into the LUCAS calculator in a future study. Our focus in this study, however, was to form a simplified model on rapid and routine blood test results, with the option to use CXR images, which we have achieved.Inclusion of CXR data is optional for the online LUCAS calculator and based on simple outcome of normal/abnormal image results. The ability to include CXR results is not widely available in other prediction calculators and has been included in a studyThroughout the study, we have carefully considered the risk of bias that is inherent in retrospective studies. By conducting both internal and external validation, the study here indicates a robust model with reduced bias, since only patients testing positive for SARS-CoV-2 were included in the development of the LUCAS algorithm. The size of the external validation set was smaller than the development set allowing us to check for discrimination of population size, and the results indicate that the LUCAS calculator can predict from small cohorts as well as it can from larger size populations.48. While these changes in therapeutic interventions change over time49, multiple studies have reported the associated changes to inflammatory markers that are found in severe cases of COVID-1939. While improvements in medical care have significantly reduced mortality, the immunological responses that indicate severe cases of COVID-19 have not changed, making the use of prediction modelling important to aid in the triage of patients.The patient data was collected at an early stage of the pandemic when treatments differed compared to later in the year, which would affect the death rate in hospital. In addition, our results do not account for non-hospital deaths or deaths outside the 60-day window following diagnosis. Over time, any algorithm of mortality will change due to improvements in therapies as well as the use of vaccination which will change the profile of those at risk of COVID-19 related death6 and combine with LUCAS to deliver an automated, integrated biomarker-imaging analysis.The major strengths of this study in mortality prediction of COVID-19 patients include the analytical approach taken, the comparison with the widely used NEWS2 score, the inclusion of CXR data, and the evaluation in both internal and external validation cohorts. The CXR data contributes to an improvement in the mortality prediction of the patient, although the CXR information used in the LUCAS calculator is binary . Further development of this work is currently ongoing, which will extract CXR image features using machine learning or deep learning methodsSupplementary Information.


Background: Coronavirus disease 2019 (Covid-19) has many different ocular manifestations. This study evaluates the effects of the disease and the steroid used in this disease on ocular structures.Purpose: To evaluate the effects of Covid-19 and the steroids used in the treatment of severe infection on ocular structures and choroidal thickness.Methods: This prospective study included 76 eyes of 76 patients who were hospitalized due to Covid-19 and 30 eyes of 30 healthy volunteering controls. Group I included 35 eyes who were hospitalized due to moderate-to-severe involvement that received steroid treatment, group II included 41 eyes with moderate involvement that did not require steroid treatment, and group III included 30 eyes with age- and gender-matched control subjects. Ophthalmological examination and imaging results of the patients obtained in the third week and third month after the diagnosis were compared between the groups.p<0.001). Moreover, choroidal thicknesses were significantly higher in group I and group II than in the control group . In the third month, all the groups had similar choroidal thickness values .Results: Mean age of all participants was 40.2 ± 6.1 years. In the third week after the diagnosis of Covid-19, choroidal thickness in all regions  was significantly greater in group I than in group II (for all, Conclusion: Our findings showed that Covid-19 infection causes choroidal thickening by affecting the choroidal layer and that steroid treatment further increases this thickness in the acute period. In addition, the reversal of this thickening to the normal level within a period of three months indicates that the effect of the disease on the choroid is reversible. Coronavirus disease 2019 (Covid-19), which manifested in Wuhan, China with severe pneumonia in December 2019, entered our lives with the declaration of a pandemic by the World Health Organization (WHO) in January 2020 .Ocular manifestations caused by Covid-19 have been reported such as episcleritis, conjunctivitis, keratitis, foreign body sensation, dry eye, epiphora or retinal vein occlusion due to thrombotic complications, and paracentral acute middle maculopathy (PAMM) -6. OculaStudies have shown that the use of systemic steroids in Covid-19 patients with severe respiratory involvement and severe hypoxemia has a positive effect on the prognosis of the disease . Some otIn this study, we aimed to evaluate the effects of corticosteroid usage on Covid-19 infection on anterior and posterior segments of the eye and evaluated the choroidal thickness.The study was designed as a prospective, comparative, observational case-control study and included 76 eyes of 76 patients aged 18-45 years who were hospitalized due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Erciyes University Department of Ophthalmology and 30 eyes of 30 healthy volunteering controls. Ophthalmological examination and imaging results of the patients were obtained in the third week and third month after the diagnosis of Covid-19 infection and were compared with the results of the control group. The study was approved by the local ethics committee . Informed consent was obtained from each participant.Study groups and inclusion/exclusion criteriaGroup I included 35 eyes of 35 patients who were hospitalized due to moderate-to-severe pulmonary involvement that did not require intubation and received steroid treatment (methylprednisolone (MP)). The oxygen saturation (SpO2) of the patients in Group I was in the range of 89-93%, and all of them received oxygen support with a high-flow nasal cannula or mask. Group II included 41 eyes of 41 patients with moderate involvement that did not require steroid treatment, and group III included 30 eyes of 30 healthy age- and gender-matched volunteers. Patients in group I had completed their total steroid course prior to the study. All the patients received low-molecular-weight heparin (LMWH) therapy.Patients with systemic diseases such as diabetes and hypertension, history of ocular surgery, trauma, glaucoma, uveitis, retinal pathologies, smoking, cataracts other than posterior subcapsular cataracts, a spherical equivalent of more than 3.00 diopters, history of systemic steroid therapy due to other reasons, hospitalization periods longer than three weeks, history of chronic radiation exposure, low signal strength  on optical coherence tomography (OCT), and a history of medical treatment other than LMWH treatment  were excluded from the study.Data collectionFor standardization purposes, the right eye of patients and controls were included in the study. Ophthalmological examination , slit lamp examination (biomicroscopy), fundoscopy, intraocular pressure measurement (Goldmann applanation tonometry), and autorefractometry ) was performed at the third week and third month after the diagnosis of Covid-19. BCVA was assessed using the Snellen decimal scale converted to a logarithm of the minimum angle of resolution (logMAR). Fundus examination was performed using a +90 D lens after pupillary dilation. The Lens Opacities Classification System III (LOCS III) was used for grading cataract severity . In all Subfoveal choroidal thickness (SFCT) and the choroidal thicknesses at 1000 μm nasal (N1000) and 1000 μm temporal (T1000) to the fovea were measured manually from the outer portion of the reflective line corresponding to the inner scleral border with the built-in caliper of the SD-OCT device software. The choroidal thickness measurement procedure is shown in Figure Interobserver evaluationsAll the ophthalmological examinations and measurements were evaluated separately by two ophthalmologists , and patients with similar results were included in the study.Statistical analysisData were analyzed using Statistical Product and Service Solutions (SPSS) . The normal distribution of continuous variables was assessed using the Kolmogorov-Smirnov test and Histogram plots. Based on these analyses, continuous variables showing normal distribution were expressed as mean ± standard deviation (SD) and those with nonnormal distribution were expressed as median (1st-3rd quartile). Categorical variables were expressed as percentages (%). Continuous variables with normal distribution were compared among three or more independent groups using the One-Way ANOVA test and the continuous variables with nonnormal distribution were compared using the Kruskal-Wallis test. The Bonferroni test was used as a post hoc test to determine the different groups in One-Way ANOVA. In pairwise comparisons, continuous variables with normal distribution were compared using paired-samples t-test and the continuous variables with nonnormal distribution were compared using the Wilcoxon signed-rank test. Statistical graphs were created using GraphPad Prism Version 8 . A p-value of <0.05 was considered significant.The mean age of all participants was 40.2 ± 6.1 years. The groups were similar in terms of female-to-male ratio, mean age, mean body mass index (BMI), and mean BCVA. Table No significant difference was found between the patient groups and the control group with regard to mean intraocular pressure measured at the post-Covid-19 third week and third month (p>0.05).Posterior subcapsular cataract (PSC) developed in one patient in group I at the third month. This patient had cataract grade 1 (P1) according to LOCS III and had deterioration in vision in one line of Snellen acuity. No cataract was detected in any participant in groups II and III.At the third week after the diagnosis of Covid-19, choroidal thickness in all regions  was significantly greater in group I than in group II . Moreover, choroidal thickness was significantly higher in group I and group II than in the control group .At the third month after the diagnosis of Covid-19, all the groups had similar choroidal thickness values . A comparison of the third-week and third-month choroidal thickness values of the groups is presented in Table In contrast, a comparison of the patient groups with regard to the change between the third-week and third-month measurements revealed a significant decrease in choroidal thickness in all regions . Figure Systemic ocular manifestations of Covid-19 have been reported in numerous studies -9. In coAbrishami et al. compared a total of 30 steroid-free Covid-19 patients with mild and moderate involvement with healthy controls and detected choroidal vascular dilatation in 68% of the patients . The resIt is known that hypoxia may also cause changes in choroidal blood flow. Hayreh, SS showed that hypoxia can cause an increase in choroidal blood flow by vasodilation . Türker It is commonly reported that one of the many ocular side effects of corticosteroids is undoubtedly seen on the retina and choroid ,20-22. IAlthough the mechanism of cataract induction remains unclear for steroid-induced posterior subcapsular cataract (SI-PSC), it is considered to be caused by glucocorticoid-inducible gene expression in lens epithelial cells and other intraocular cells . In a stOur study was limited in several ways. First, it had a small number of cases and a short follow-up period. Second, the differences in disease severity and oxygen saturation are likely to have affected the choroidal thickness in both patient groups, albeit minimally. In addition, no baseline examinations and measurements were performed at the time of diagnosis in any patient due to technical difficulties and the risk of infection transmission during the pandemic period. A control group was included in the study in order to alleviate these limitations to some extent.Our findings indicated that although there is an increase in choroidal thickness in patients with Covid-19 during the early stage of the disease, this increase is further exacerbated with steroid treatment but it is often reversible. In addition, our results showed that the steroids administered to support treatment did not have a significant role in the development of cataracts. There are studies in the literature on ocular complications and structural choroidal changes induced by Covid-19. However, to our knowledge, our study is the first of its kind to investigate the role of steroid treatment in such patients. Considering the clinical features of retinal vasculopathy and choroidopathy associated with Covid-19, we believe that patients requiring steroid treatment have a higher risk of choroidal disorders and may require closer ophthalmological follow-up. Further studies with larger series and longer follow-up periods including the examination findings of the patients at the time of diagnosis are needed to substantiate our findings.


Background: Regular and moderate physical activity is beneficial for physical and mental health, resulting in an increase in life expectancy for both sexes. From a cardiovascular point of view, although the benefits of regular moderate physical exercise have been established, the long-term effects of repeated ultra-endurance running events are still unknown. Hypothesis: The aim of our study is to evaluate the 10-year evolution of the parameters of the left ventricular systolic and diastolic functions of amateur subjects regularly practising ultra-endurance running events using resting echocardiography. Study design: Cross-sectional study. Level of evidence: Level 3—non-randomized controlled cohort/follow-up study. Methods: The 66 participants who participated in the 2011 edition of the Eco-Trail de Paris® were contacted by e-mail. Demographic data, sports practice, and the results of an echocardiography scan carried out during the year 2021 evaluating left ventricular systolic and diastolic function variables were collected. Echographic variables from 2011 and 2021 were compared using the paired Student’s t-test. Results: Forty-six (70%) participants responded positively. Twenty (30%) participants could not be reached and were not analysed. Of the 46 respondents, 42 (91%) provided data from a trans-thoracic cardiac ultrasound performed in 2021. Over the past 10 years, the participants reported having completed an average of 4 ± 2 ultra-trails per year. No significant differences were observed between left ventricular diastolic and systolic echocardiographic parameters between the years 2011 and 2021. Conclusions: Among amateur participants, long-distance running is not associated with an alteration in the echocardiographic parameters of resting left ventricular systolic and diastolic function after 10 years of practice. Clinical relevance: Long-term long-distance running practice is not associated with left ventricular cardiac function alteration. These results suggest a potential adaptation role of the cardiovascular system to regular and moderate long-distance running practice. Physical activity is a major determinant of health status and physical condition and of cardio-respiratory capacity, muscular condition, and the maintenance of autonomy with advancing age in particular, but also of the quality of life at any age. In the general population, regular and moderate physical activity is beneficial for health and the extension of life expectancy for both sexes , with a From the cardiovascular point of view, while the benefits of regular moderate exercise are established , the effAfter an ultra-endurance running event, i.e., a race lasting more than 6 h, we demonstrated the occurrence of transient left ventricular diastolic and systolic dysregulations with complete recovery 9 days after the end of the event . We haveThe objective of our study is to evaluate the 10-year evolution of the parameters of the left ventricular systolic and diastolic functions of amateur subjects regularly practising ultra-endurance running events using resting echocardiography.® . Multiple imputations based on the Markov chain Monte Carlo method were performed for missing data from cardiac ultrasound scans performed in 2021 using the mice package method.p-value < 0.05. All analyses were performed using R 3.4.2 software .Comparisons between the variables of interest from the 2011 and 2021 echocardiography scans were performed using the paired Student’s t-test to account for the repeated-measure design of the study. All tests were two-tailed with a statistically significant The study protocol was approved by an independent ethics committee .®, 46 (70%) responded favourably and were included in the analysis. Twenty participants (30%) could not be reached and were not included in the analysis. Of the 46 respondents, 42 (91%) provided data from a trans-thoracic cardiac ultrasound performed during the year 2021. For the remaining four (9%) who did not perform an echocardiogram in 2021, the data were imputed . Annex reports indicate the competitions in which the participants participated in between 2011 and 2021.The health problems reported were one case of arterial hypertension without the need for treatment (2%), one case of periostitis (2%), one case of tendonitis (2%), two cases of low back pain (4%), and one case of a meniscal tear that required surgery (2%). No runner reported cardiac rhythm disturbance.The treatments reported were non-steroidal anti-inflammatory drugs for four participants (9%).Four participants (9%) declared that their health problems had impacted their sports activity, and three (7%) declared that these problems were related to ultra-trail running. One runner (2%) stopped running ultra-trails in 2012 but continues to run as a leisure activity and was not included in the analysis.No significant differences were observed between the echocardiographic parameters assessing end-diastolic and end-systolic geometric measurements or left ventricular diastolic and systolic function between the years 2011 and 2021 .In this study, we reported the absence of alterations in the parameters of left ventricular systolic and diastolic cardiac functions evaluated by resting transthoracic echocardiography in amateur long-distance participants after 10 years of practice.Although the beneficial effects of regular and moderate physical activity on health  are now In addition, during an ultra-endurance running event, transient left ventricular dysregulation, first diastolic and then systolic, was observed with resolution ad integrum on the 9th day post-exercise , suggestRegular moderate physical activity has been reported to prevent and treat age-related degeneration ,41. FromOur results are consistent with the data in the literature reporting the absence of deleterious cardiovascular effects of moderate-intensity endurance exercise . ContrarHowever, this study has limitations. Our sample size is modest, and for 30% of the participants, we could not obtain information about their health status and were not able to clearly specify whether the absence of these respondents was random or not and therefore if it could have affected our results. The absence of deleterious echocardiographic effects does not mean that the regular ultra-trail practice is beneficial since we reported the absence of deterioration and not improvement in the echocardiographic parameters of left ventricular cardiac function—even if we could suppose an expected low level of deterioration since the participants had aged 10 years. In this study, we did not use the same echocardiograph that was used 10 years earlier. Moreover, we did not explore the echocardiographic parameters of right ventricular cardiac function. Our statistical approach is descriptive and not causal, so our results do not allow us to conclude that ultra-trail running is part of the inverse relationship described between the intensity of physical activity and the incidence of atheromatous cardiovascular disease ,66,67,68However, to the best of our knowledge, this is the first study assessing the long-term cardiac effects among regular amateur long-distance running practice participants.In amateur long-distance running participants, no alterations in the parameters of the left ventricular systolic and diastolic cardiac functions evaluated by resting transthoracic echocardiography were observed after 10 years of practice. Our results suggest a potential adaptation role of the cardiovascular system to regular and moderate long-distance running practice. Further studies are needed to confirm this preliminary data during exercise but also to specify the possible beneficial effect of regular long-distance running.


Here, we used the transient middle cerebral artery occlusion (tMCAO) mouse model to characterize the spatio-temporal alterations within the ischemic core from the acute to the chronic phase using multiple-epitope-ligand cartography (MELC) for sequential immunohistochemistry. We found that around 14 days post-stroke, significant angiogenesis occurs in the ischemic core, as determined by the presence of CD31+/CD34+ double-positive endothelial cells. This neovascularization was accompanied by the recruitment of CD4+ T-cells and dendritic cells as well as IBA1+ and IBA1− microglia. Neighborhood analysis identified, besides pericytes only for T-cells and dendritic cells, a statistically significant distribution as direct neighbors of CD31+/CD34+ endothelial cells, suggesting a role for these cells in aiding angiogenesis. This process was distinct from neovascularization of the peri-infarct area as it was separated by a broad astroglial scar. At day 28 post-stroke, the scar had emerged towards the cortical periphery, which seems to give rise to a neuronal regeneration within the peri-infarct area. Meanwhile, the ischemic core has condensed to a highly vascularized subpial region adjacent to the leptomeningeal compartment. In conclusion, in the course of chronic post-stroke regeneration, the astroglial scar serves as a seal between two immunologically active compartments—the peri-infarct area and the ischemic core—which exhibit distinct processes of neovascularization as a central feature of post-stroke tissue remodeling. Based on our findings, we propose that neovascularization of the ischemic core comprises arteriogenesis as well as angiogenesis originating from the leptomenigeal vasculature. Ischemic stroke is a highly prevalent vascular disease leading to oxygen- and glucose deprivation in the brain. In response, ischemia-induced neovascularization occurs, which is supported by circulating CD34 Ischemic stroke is a highly prevalent vascular disease that carries a relevant burden of disability and socioeconomic strain. It is a consequence of the acute occlusion of a cerebral artery leading to oxygen- and glucose deprivation in the brain parenchyma of the respective vascular territory. In this context, the activation of microglia and rapid deterioration of neurons occurs, leading to the release of damage-associated molecular pattern molecules (DAMPS) and thereby to further glial activation and subsequent secretion of cytokines and matrix metalloproteinases . As a reSo far, studies on post-stroke recovery focused on the peri-infarct area because it is considered to represent the closest histological correlate of the penumbra. The penumbra was characterized in 1977 by Astrup et al. as a region where blood flow has dropped below the threshold necessary to uphold electrophysiological neuronal functions, but not yet below the threshold necessary to maintain structural integrity, retaining the potential of full recovery in case of reperfusion within a certain time window . Today, vasculogenesis, the sprouting of new vasculature mainly taking place during embryogenesis and tumor formation, but also observed to a certain extent in cardio-vascular diseases [arteriogenesis, which means the enlargement of pre-existing collaterals mainly driven by shear stress sensed by the affected endothelium [angiogenesis, where a stress signal such as ischemia activates endothelial cells to form new vessels, which is supported by circulating endothelial progenitor cells (EPCs) [Furthermore, significant regenerative potential is attributed to the peri-infarct area, which is reflected, e.g., by the occurrence of strong ischemia-induced neovascularization . This tediseases ; (b) artothelium ; and (c)s (EPCs) . These Es (EPCs) . They sts (EPCs) . Tip cels (EPCs) . Supports (EPCs) . During s (EPCs) . Although these newly formed vessels during post-stroke recovery have shown to lack a fully equipped BBB and possibly recede over the long term , angiogeNevertheless, evidence is accumulating that certain aspects of the post-stroke inflammatory process are specific to this region ,20. It hWe therefore aimed at a comprehensive characterization of the spatio-temporal alterations within the ischemic core from the acute to the chronic phase after experimental stroke using a multiple-epitope immunohistochemical approach. For this purpose, mice were nursed following an intensive post-stroke care protocol  and examAll animals involved in the presented experiments were approved by the local Ethics Committees for Animal Research (Darmstadt) under the permit number FU/1182. Experiments were performed in accordance with the German Protection of Animals Act and the guidelines for care and use of laboratory animals by the local committee (Regierungspräsidium Darmstadt).In total, 25 male C57Bl/6J mice (25–30 g) at the age of 10 to 12 weeks old were purchased from Charles River Laboratories . The right middle cerebral artery was occluded as described previously . In brieMELC technology is an automated immunohistological imaging method and can be used to visualize very high numbers of antibodies on the same sample as described before ,25,26. BIn the first step, all greyscale antibody channel images were processed using ImageJ 1.52v to diminish noise, background fluorescence and remove artefacts for further analyses if necessary. The staining for NeuN, GFAP and Map2 were used to divide the images in areas containing stroke or healthy tissue. Subsequently, Cell Profiler (version 3.1.9)  was usedt-test was carried out with Welch’s correction. A p value of <0.05 was considered statistically significant.All data are presented as mean ± SEM. Determination of statistically significant difference in all experiments including was conducted with one-way analysis of variance (ANOVA) followed by post hoc Bonferroni correction using GraphPad Prism. 7. For in vitro experiments comparing only two groups, Student’s Using a recently established protocol for murine post-stroke care, we were able to achieve full recovery in 76% of the mice in the tMCAO model ,33. The To investigate the time course of neovascularization and immune cell recruitment in the tMCAO model, we used the MELC technology for multiple sequential immunohistochemistry. The MELC technology is an automated system, allowing the imaging of an unrestricted number of directly labelled antibodies on the same tissue sample. Overall, 26 antibodies were used to image vessels, neurons, glia cells and immune cells . Since tIn a first step, brain slices were stained with either cresyl violet or hematoxylin/eosin stain to define stroke areas. Cresyl violet and hematoxylin/eosin staining showed a dramatic cellular loss in the right hemisphere starting 1 day after stroke; thereafter, the affected area decreased significantly over time towards a defined subpial cortical region A. TwentyIn accordance with previous reports, the ischemic area was defined by the absence of neurons and low expression of MAP2  ,35 FiguD. Thus, +/CD34+ vessels over the course of 28 days in the stroke area using the MELC technology. The fields of vision for MELC analyses were chosen at the border of the stroke area to compare vascularization in the ischemic core and peri-infarct area. For quantitative assessment of CD31+/CD34+ endothelial tip cells, we used a segmentation mask to extract single-cell data from images including abundances of all measured markers and the microenvironment of each cell such as cell neighbors and cell crowding. This information was compiled into a flow cytometry standard format (.fcs) file for further analysis, which showed a strong upregulation of CD31+/CD34+ endothelial cells starting at day 14 after stroke induction (−/CD34+) in the ischemic core regions, apart from the CD31+/CD34+-populated IC-ANV  were detectable in the ischemic core  the peri-infarct area, which is separated by (b) a broad astroglial scar from (c) the ischemic core . In the In this context, the striking regenerative potential of the peri-infarct area in mice becomes apparent, which goes along with comprehensive neural repopulation of the post-ischemic hippocampus as well as the surrounding peri-infarcted parenchyma outside the astroglial scar. This correlates well with complete normalization of the animals’ clinical neurological status and indicates a remarkable capacity for adult neurogenesis in the rodent brain. Artificial selection of mildly affected animals at late post-stroke stages was ruled-out in our study due to (1) the utilization of an intensive post-stroke care protocol. At this, we achieved a mortality rate of 26%, which reflects the one of patients facing a severe stroke of the anterior cerebral circulation  and redu+/CD34+ tip cells to CD31+/CD34− mature endothelial cells organized in clear tubular formations, hinting at the delayed induction of angiogenesis in this distinct zone within the IC. As the expected acute leptomeningeal arteriogenesis, defined as the activation of leptomeningeal collaterals, is rather dominated by the action of monocytes [+/CD34+ stem cells would not integrate into the vessel wall as seen here [angiogenetic potential of the leptomeningeal vasculature in the regenerative phase after stroke.Apart from this, a high degree of endothelial-cell proliferative activity developed within the ischemic cortex at late stages of post-stroke recovery. This IC-ANV was completely surrounded by the astroglial scar and was therefore clearly separated from the peri-infarct area. By immunohistochemical examination, we identified several subgroups of endothelial cells ranging from endothelial progenitor cells (EPCs) over CD31onocytes  and circeen here , we postangiogenesis in the IC-ANV, which might be due to the distance from the neural stem cell niche in the SVZ and the separation by the astroglial scar. In contrast to the peri-infarct area, the IC-ANV seems to condensate over time and might resolve completely at later timepoints in mice. Thus, the IC-ANV might represent a site of removal of necrotic tissue rather than regeneration of surviving tissue, whereas the scar serves as a separative seal between those two compartments. In this light, current attempts to modulate astrocyte polarization after stroke [Differing from previous reports, we did not observe neural regeneration accompanying the r stroke ,43 shoulThe assumingly leptomeningeal origin of the sprouting capillaries is interesting in that these vessels differ from the central cerebral vasculature, e.g., by the lack of an external elastic lamina  and by b+/CD34+ co-expression with infiltrating or intravascular hematopoietic stem cells was not observed in the IC-ANV since CD31−/CD34+ were basically absent in this area.In principle, the infiltrating immune cell populations identified by MELC analysis within the IC-ANV match previous reports in temporal dynamics and quantity ,54. OverOne limitation of our study is the restricted field of view, which does not allow imaging of the complete ischemic hemisphere by which particular regional alterations might have gone unnoticed. Moreover, we can only assume the leptomeningeal origin of angiogenesis within the IC-AVN due to its strictly subpial localization. Further studies are required to characterize this vascular compartment and to identify potential therapeutic targets, e.g., for differential immunomodulatory, cytoprotective or pro-angiogenic treatment strategies. For instance, acceleration of the post-ischemic clearing processes could create a secure time window for glial-focused therapeutic strategies, which might expand the regenerative potential of the peri-infarct area towards the ischemic core. On the other hand, cytoprotective agents such as the PSD-95 modulator Nerinetide, which is currently under clinical investigation in the context of large vessel occlusion with reperfusion, might exert higher effects when delivered specifically to the site of action outside the astroglial scar.In conclusion, we assume that in the course of chronic post-stroke regeneration, a distinct process of neovascularization originating from the leptomeningeal vasculature plays a critical role for structural and functional recovery. Further insights into the compartment-specific infiltration and action of immune cells might allow tailor-made drug design in the future to enhance either regenerative or clearance processes within the affected hemisphere.


Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and vaccinations targeting the spike protein (S) offer protective immunity against coronavirus disease 2019 (COVID-19). This immunity may further be shaped by cross-reactivity with common cold coronaviruses. Mutations arising in S that are associated with altered intrinsic virus properties and immune escape result in the continued circulation of SARS-CoV-2 variants. Potentially, vaccine updates will be required to protect against future variants of concern, as for influenza. To offer potent protection against future variants, these second-generation vaccines may need to redirect immunity to epitopes associated with immune escape and not merely boost immunity toward conserved domains in preimmune individuals. For influenza, efficacy of repeated vaccination is hampered by original antigenic sin, an attribute of immune memory that leads to greater induction of antibodies specific to the first-encountered variant of an immunogen compared with subsequent variants. In this Review, recent findings on original antigenic sin are discussed in the context of SARS-CoV-2 evolution. Unanswered questions and future directions are highlighted, with an emphasis on the impact on disease outcome and vaccine design. Curre disease .A footprint of adaptive immune responses to pathogens and vaccinations, including those against SARS-CoV-2 and COVID-19 vaccines, remains in the form of memory B and T cells. Re-exposure to pathogens or antigens that were encountered earlier in life will induce memory recall, where these memory immune cells tend to be boosted faster and to a greater magnitude than inexperienced naive immune cells, increasing the chance of protection from infection , 13. UpoThe concept and clinical impact of OAS have been debated, and currently different interpretations of the notion of OAS still exist , 24. In There are other terms in the literature to describe features of a boosted memory response upon heterologous challenge that emphasize different aspects of the underlying mechanism and have a more neutral or more positive connotation than OAS . WhereasOAS, imprinting effects, and antigenic seniority have been shown to modulate protection against influenza viruses in numerous independent human cohorts, including their impact to limit vaccine efficacy for prevention of infection –36. DespTheoretically, positive and negative side effects of memory recall can occur side by side in any new variant emerging from circulating pathogens. Nevertheless, memory recall side effects are important for specific viral pathogens from which new variants can emerge and spread globally, which leads to a large immune population. Mutations that confer intrinsic transmission advantages to the emerging variants, including mutations that allow variants to escape herd immunity by changing their antigenic properties, are selected and may allow the spread of the variant. In this context, OAS has mostly been reported for influenza viruses, which are present globally and must escape population immunity by mutating epitopes that are most vulnerable to neutralizing antibodies, resulting in the generation of immune escape variants , 38–40.The ongoing evolution of SARS-CoV-2 is shown by the substantial sequence variation of virus variants that are circulating in the human population . StrainsThe recent VOCs are spreading in populations that are increasingly preimmune to SARS-CoV-2 as a result of vaccination or infection with preceding strains. Most slight differences between variants have had a limited impact on the effectiveness of the preexisting immunity in the population. The Omicron lineages, however, carry an unexpected high mutation load compared with the previously dominant variants Alpha and Delta, and largely escape from preexisting immunity , 43. TheBesides mutations that alter intrinsic characteristics of the virus, detailed insights into the genetic changes that result in significant immune escape are imperative in order to understand which variants may become established next. This underscores the need for continuous monitoring of SARS-CoV-2 antigenic evolution and testing of vaccine efficacy for SARS-CoV-2 , 45.Immune escape mutations are those that lead to modifications in the antigenic properties of pathogens to avoid preexisting immunity. The continuous adaptation of viruses in their antigenic properties is known as antigenic evolution. To date, the antigenic evolution of SARS-CoV-2 is primarily described for S, since this is the main target of COVID-19 vaccines and an immunodominant target during SARS-CoV-2 infection.2, containing the fusion apparatus, and the outer domain S1, containing the RBD. Homology between S of SARS-CoV-2 variants is higher in S2 compared with S1, which is most variable in the RBD and the NTD  and hemagglutinin (HA) of influenza viruses. Both S and HA are required for binding and fusion with the target cell and are dominant targets for neutralizing antibodies –50. S pr the NTD . Influen the NTD . Both S HA stalk –53  the kinetics, i.e., the speed and magnitude of the memory versus naive B and T cell responses; (b) the affinity and functionality of the immune response; and (c) the immunological breadth of the response at the time of exposure.+ T cells, memory recall and a delayed de novo response may occur because human memory CD8+ T cells have higher immunological synapse propensity than naive CD8+ populations . Currently there is limited evidence of CD4+ or CD8+ T cell epitope escape for SARS-CoV-2 variants , induces imprinting effects on SARS-CoV-2 immunity or vice versa.In the case of CD4hallenge –82. This breadth , 82. Thivariants –63. HoweMemory B cells also possess an intrinsic proliferative advantage over their naive B cell counterparts . As a reIn contrast to T cells, memory B cells can mold their specificity by secondary GC reactions for further affinity maturation with the help of follicular helper T cells (Tfh cells). When the antigenic distance between the priming and the boosting variant is limited, memory B cells can be affinity trained to also target the new strain , 90. HowThe effect of original SARS-CoV-2 strain immunity induced by vaccination or infection on the protection against new VOCs is under debate. Although the earlier VOCs  carried signature mutations associated with immune escape from neutralizing antibodies, convalescent and post-vaccination sera with high titers still neutralized the variants , 93. HowThe longevity of protection against VOCs by solely homologous boosting may be limited because of the potentially continuous antigenic evolution of SARS-CoV-2 and waning immunity. As a result, antibody titers sufficient to cross-neutralize future VOCs may only be reached for a short period after vaccination or boost with original S antigens. Another concern is that homologous boosting of original S-specific responses by repeated vaccination or Wuhan-Hu-1 infection may induce imprinting of the original strain and therefore result in an OAS type of response when challenged with VOCs . Indeed,Heterologous vaccination strategies using VOC-specific vaccines are tested in small cohort studies and animal models for their efficacy and safety. Individuals who were vaccinated twice with mRNA-1273  were boosted with homologous vaccines or the Beta variant mRNA vaccine mRNA-1273.351 or a mixture thereof. Although preliminary results suggest that the vaccines were safe and the overall neutralizing titers were increased for all study participants, neutralization of the Beta variant was not significantly better upon administration of the variant boost . Also, iAlthough homologous and heterologous boosts with SARS-CoV-2 spike vaccine and hybrid immunity resulted in increased neutralization titers against VOCs, it is important to monitor how well immunity can be shaped to target neoepitopes in VOCs. Owing to extensive GC reactions that induce somatic hypermutation and memory B cell turnover, broadly reactive neutralizing antibodies are selected and maintained in the repertoire that potentially protect against VOCs . NotablyPreexisting serum antibodies and B and T cells that can recognize SARS-CoV-2 have been detected in naive, unvaccinated individuals. These responses are most likely shaped by prior infections with the widespread seasonal human coronaviruses (HCoVs) that cause common cold symptoms, including the alphacoronaviruses HCoV-229E and HCoV-NL63 and the betacoronaviruses HCoV-OC43 and HCoV-HKU1 , 112. A 2–specific IgG titers are boosted in serum, but these antibodies are associated neither with protection against SARS-CoV-2 or neutralization, nor with HCoV-OC43 neutralization  combinations of immunizations to optimize minimal imprinting effects and maximal effectiveness against SARS-CoV-2 variants and other virus families with complex antigenic properties. Investigation of heterologous priming and boosting exposures with the current knowledge regarding COVID-19 vaccination could turn OAS into positive back-boost effects.