Childhood lead poisoning is an issue that continues to plague major U.S. cities. Despite efforts by the Philadelphia Department of Public Health to curtail systemic childhood lead poisoning, children continue to be identified with elevated blood lead levels. The persistence of elevated blood lead levels in children is concerning because lead poisoning has been linked to decreases in academic achievement and IQ, with associated repercussions for entire communities. This paper reports the results of an analysis of the spatial distribution of houses with lead paint , demolitions, and occurrence of historic smelters, in West and North Philadelphia, relative to elevated blood lead level data, to determine which lead sources act as primary lead‐risk factors. The presence of lead paint in homes and the number of demolitions of older properties were found to have the highest correlations to elevated blood lead levels for children in Philadelphia. Using lead‐risk factors including lead paint, housing code violations, demolitions, and owner‐occupied housing units, a lead‐risk assessment was performed at the census tract level to identify future soil sampling sites and high‐risk neighborhoods in Philadelphia. These sites of high risk for lead exposure, and in particular the census tracts 175 and 172, should be prioritized for lead poisoning prevention initiatives. In areas with high homeownership, owner‐occupied units can serve as lead‐risk indicators for childhood lead poisoningDemolitions and lead paint of older housing are critical lead‐source emissions for childhood lead poisoning in PhiladelphiaNorth Philadelphia soils, and especially open‐land around historic smelters, are highly undersampled In geneThe majority of the City of Philadelphia is considered at risk for lead hazards from lead paint but the issue of childhood lead poisoning is highly racist and classist , either directly or subsequent to chemical and physical alteration. Because lead strongly adsorbs onto soil, it is a persistent environmental pollutant, which creates an ongoing risk of exposure, particularly in soils that have not been remediated . Statistically non‐significant correlations are available in the data repository  evaluated within this study had nearly equal representation of owner‐occupied and renter‐occupied housing units within their populations Figure . Sixteen3.1.2A majority of the census tracts (76/94) evaluated were majority Black communities  for which median income data were available are below the U.S poverty line, which is defined as a median family income of $26,200/year for a family of four  of the census tracts evaluated have 90% of housing units built before 1980  had more than 30% of housing units built before 1950  of those demolitions were due to housing code violations. Of the 94 census tracts analyzed, only one census tract (267) had no demolitions within the timeframe. Sixteen census tracts  had 100 or more demolitions  were reported to have EBLLs, that is, a BLL ≥5 μg/dL. However, the number of children screened ranged greatly among the studied census tracts, with some census tracts reporting only 30 children screened, whereas others reported 685. Sixteen census tracts  screened less than 50% of children 0–5 years old. The percentage of screened children with EBLLs ranges among census tracts from 3.4% to 17.6%, with census tract 200 having the highest percentage. Thirty‐one census tracts  had 10% or more children screened with EBLLs  within the region of study. However, a previous study within Philadelphia identified a significant positive relationship between BLLs and soil‐Pb levels (Bradham et al., The emissions from lead sources evaluated in this study primarily settle on soil. Lead‐contaminated dust and paint may also settle on roads, porches, and inside homes, but these sites are often inaccessible for sampling. Bodies of water may also be a final sink for lead particulates, but they are not relevant in the area examined in our study. As such, soil becomes the most accessible and relevant environmental medium to investigate for the identification of sites with a high lead risk in need of preventive action. Previous studies have even used soil‐Pb data to predict spatial variation in BLLs (Mielke et al., Furthermore, recognizing that a child's EBLL is a reflection of recent cumulative exposure to lead from multiple sources, lead‐in‐soil data are a useful lead‐risk indicator for one important source of exposure in need of preventative action (Laidlaw et al., Evidence of historic smelters and significant numbers of demolitions with associated emission of lead‐contaminated dust in North Philadelphia further highlight a great need for soil sampling in this area. This is especially pressing when considering that previous work in Philadelphia identified floor dust at household entryways as a critical risk factor for childhood lead poisoning (Dignam et al., 4.8There are several limitations to this study, however, including missing lead sources such as census tract‐level data on highly frequented roads, along which leaded gasoline emissions from mobile sources would have accumulated, and locations of existing lead service lines. The PA‐DEP's Land Recycling Program reports include only those Brownfield sites that have been identified for clean‐up so that they can be re‐used. There are likely numerous other contaminant sites that are not included in these reports because they are not commercially viable. There is also a gap in the availability of soil data within North Philadelphia that needs to be closed in order to better understand the risk within that region. Certain data are also highly underrepresented due to limitations within L&I, including data on housing code violations, and especially lead violations. For these reasons, this study can only present conclusions based on the available data, and therefore does not provide a complete representation of the cumulative lead risk within the studied area of Philadelphia. Moreover, despite this study investigating lead risk in Philadelphia at the smallest geographic unit done to date, it is limited by the representation of data at the census tract level. In one study, census blocks rather than census tracts were found to better predict BLLs and other health effects, as health outcomes are more closely associated with an individual's immediate environment than with larger geographic areas (Kaplowitz et al., Another point illuminated by the data used here was the disparity in BLL screening of children. Despite having the greatest proportion of children with EBLLs relative to the total number of children screened, census tract 200 is one of the 16 census tracts with less than 50% of children screened, and it does not emerge as one of the highest lead‐risk census tracts (Figure S20 in the Supporting Information A historical analysis could be used to investigate the legacy of leaded gasoline emissions in Philadelphia, which could be achieved by identifying and mapping roads that were heavily trafficked during the timeframe of leaded gasoline use, and by determining the lead isotopic composition of soils adjacent to these roads, which may carry a unique gasoline isotopic signature (see, for example, Wang et al., 5Lead paint, housing code violations, demolitions, and owner‐occupied housing continue to be lead‐risk factors in Philadelphia. A significant finding of our research is that the lead risk is highly correlated with owner‐occupied housing in Philadelphia due to high homeownership in low‐income areas. This association should be further investigated in other cities, as its implications for policy and prevention of lead poisoning are critical. Furthermore, this research identified that demolitions are strongly associated with EBLLs in children, pointing to lead‐contaminated dusts released during the demolition process as an important source, suggesting that dusts from lead paint play an important role in lead poisoning. Lead‐contaminated dust from demolition activity warrants additional regulatory mitigation and greater code enforcement, as it impacts low‐income communities of color, that is, environmental justice communities, considerably more than higher‐income white communities in Philadelphia. Census tracts 175 and 172, which were identified as having the highest risk for childhood lead poisoning, should have resources directed to them in order to increase efforts to remediate homes, test and support children within these areas. The 16 census tracts with less than 50% of children screened for EBLLs should receive targeted screening programs by the Philadelphia Department of Public Health.It is important to note that the census tracts most frequently appearing as high risk are concentrated within the Strawberry Mansion area, especially when including the census tracts considered high risk in regard to seven of the thirteen lead‐risk factors (Figure S20 in the Supporting Information The authors declare no conflicts of interest relevant to this study.Supporting Information S1Click here for additional data file.


Globodera.Phylum Nematoda; class Chromadorea; order Rhabditida; suborder Tylenchina; infraorder Tylenchomorpha; superfamily Tylenchoidea; family Heteroderidae; subfamily Heteroderinae; Genus Potato cyst nematodes (PCN) are biotrophic, sedentary endoparasitic nematodes. Invasive (second) stage juveniles (J2) hatch from eggs in response to the presence of host root exudates and subsequently locate and invade the host. The nematodes induce the formation of a large, multinucleate syncytium in host roots, formed by fusion of up to 300 root cell protoplasts. The nematodes rely on this single syncytium for the nutrients required to develop through a further three moults to the adult male or female stage. This extended period of biotrophy—between 4 and 6 weeks in total—is almost unparalleled in plant–pathogen interactions. Females remain at the root while adult males revert to the vermiform body plan of the J2 and leave the root to locate and fertilize the female nematodes. The female body forms a cyst that contains the next generation of eggs.Solanum tuberosum), tomato (Solanum lycopersicum), and aubergine (Solanum melongena), over 170 species of Solanaceae are thought to be potential hosts for PCN .The host range of PCN is limited to plants of the Solanaceae family. While the most economically important hosts are potato , application of nematicides, crop rotation. Great effort is put into reducing the spread of PCN through quarantine measures and use of certified seed stocks.WormBase ParaSite.Genomic information for PCN is accessible through  PCN are biotrophic pathogens with a survival stage that allows them to persist in soil in the absence of a host facilitating their spread to all regions where potatoes are grown. While these species can infect numerous species of Solanum, they are, in economic terms, principally parasites of potatoes  and USDA‐APHIS (USA) developed guidelines on the application of sanitary and phytosanitary measures in accordance with the International Plant Protection Convention and the World Trade Organization Agreement. Soil samples are routinely collected and, on detection of PCN, movement of soil and crops (present and historic) from infected and adjacent fields is monitored and regulated until viable PCN are no longer detected. Infected land may not be used for host crop production unless PCN management plans are in place. Meanwhile in Australia, PCN biosecurity zones were established following detection of PCN in 1986 in Western Australia and in 1991 in Victoria. In New South Wales, biosecurity zones have been established to protect seed potato areas. Monitoring of this zone restricts import of potato propagative material, packaging, soil, and machinery from outside the area (Biosecurity Order 2017). Similarly, G. rostochiensis) was first reported from the region in Kenya , and natural host resistance. In addition, biological control methods, such as the use of antagonistic microbial agents, have been assessed and employed but are not widely used against PCN  indicates that within the UK alone costs due to PCN may average £31 million per annum in relation to yield losses and management costs. This figure excludes losses incurred as a result of growing alternative, less profitable crops or due to the inability to use infested land for seed potato production and is therefore likely to be an underestimate of the economic impact of PCN.3Juvenile PCN develop within a chitinous eggshell. Following embryogenesis, the first moult occurs within the egg, giving rise to the second stage infective juvenile (J2), which then hatches from the eggshell. Hatching depends on many environmental factors, such as soil temperature and moisture, but most significantly it depends on chemical cues within host root exudates. Responding specifically to host exudates allows this host‐specific pathogen to coordinate its life cycle with the presence of a host. The detailed chemical composition of host root exudates is complex and remains to be properly characterized. The mixture of chemicals includes a range of secondary metabolites whose structure is often difficult to determine. PCN responds to numerous compounds present in root exudates , including PCN, interact with their hosts. Genome sequences for both Like many other PPN, PCN are challenging experimental organisms to work with as they are obligate biotrophs with relatively long life cycles and no large‐scale in vitro culture system is available. The life stages that interact with the host are embedded in the roots and are microscopically small. The challenges of working with PPN means that our understanding of the basis by which they interact with plants has generally lagged behind that of other important plant pathogen groups. The application of genomics and transcriptomics to these nematodes has provided a blueprint for a more detailed analysis of their biology.G. pallida . In general, the overall genome features for both species (genome size and proportion of repetitive elements) are broadly similar and it is likely that the differences in original assembly quality reflect the fact that the G. pallida populations are derived from a much larger and more genetically diverse original introduction than that which occurred for G. rostochiensis  or parasitic  stages of PCN  and in mammalian Ca2+‐release channel Ryanodine receptors   domain proteins. SPRY domain proteins are ancient in evolutionary terms and are present in animals, plants, and fungi. The SPRY domain itself was originally identified in the spore lysis SP1a protein from the amoeba l‐glutamyl‐cysteinyl‐glycine, is an important antioxidant in plant and animal cells. It is synthesized in a two‐step process, with the final step being the addition of glycine to γ‐glutamylcysteine, catalysed by GS. Most animals analysed to date have a single GS present in their genomes, which encodes an intracellular housekeeping enzyme. However, in addition to this housekeeping sequence, cyst nematodes and related species have evolved a greatly expanded gene family of GS‐like sequences, whose proteins are secreted from the dorsal gland cell and are deployed as effectors during parasitism  effectors. Glutathione, the tripeptide γ‐G. pallida similar to the 4D06 sequences identified in H. glycines and G. rostochiensis  peptide mimics to modulate host developmental programmes for feeding cell formation. Genes encoding CLE‐like peptides have been found in a wide range of cyst nematode species, including PCN  has been identified that interacts with, and modulates, the activity of the LAX3 auxin influx transporter  gene for control of this species has been more challenging  and S. tuberosum subsp. andigena (H3) are widely used in commercial breeding programmes for G. pallida. The S. vernei Gpa5 source is controlled by two quantitative trait loci (QTLs) that are located on chromosomes V and IX  from the Netherlands. Gro1‐4 provides resistance against the Ro1 pathotype of G. rostochiensis only. By contrast, Hero provides broad‐spectrum resistance against all G. rostochiensis pathotypes tested and partial resistance against a wide range of G. pallida populations  domain at the N‐terminus, while Hero and Gpa2 encode CC‐NB‐LRR proteins, which have a coiled‐coil (CC) domain at the N‐terminus. However, more recently, the Cf‐2 gene, originally identified on the basis of its ability to confer resistance against the fungal pathogen Cladosporium fulvum, has been found to provide resistance against G. rostochiensis. Cf‐2 encodes an extracellular receptor‐like protein with an LRR domain  type of resistance gene. H. glycines, have shown that some resistance against cyst nematodes may be underpinned by entirely novel molecular mechanisms. In these cases, the underlying mechanism of resistance is based on a lethal toxic effect exerted through the feeding structure. Resistance provided through the rhg1 locus is based on an αSNAP protein that accumulates preferentially in the nematode feeding site and has amino acid differences that cause a failure of its normal function  that impedes the development of the feeding site, causing a failure of nutrient supply to the nematode  and recognition/loss of recognition is determined by a single amino acid polymorphism. Further analysis of sequence variation within RBP1 shows that this site is under strong selection pressure and is the only variable site that determines pathogen recognition  have been identified from PPN , have restricted ability to spread, and are limited to one generation per year (in most situations), meaning that resistance can be durable. Cultivars containing the 9Genomics and transcriptomics have provided an opportunity for a major change in the way that research on PCN is undertaken. We understand more about the biology of PCN and the nature of both the susceptible and resistant host response than ever before. However, there remain numerous key research needs. PCN is entirely dependent on host cues to be able to synchronize its life cycle with host plants. The spectra of chemicals within root exudates that PCN react to is intricate and complicated. Significant progress continues to be made, however, in the identification and understanding of the molecules that PCN responds to in order to hatch and locate host roots. Details of the changes in gene expression that occur in response to these molecules and as part of the restarting of the life cycle have also been characterized. However, we are yet to determine how these two aspects are linked at the molecular level. Details of the mechanisms by which PCN infects plants are emerging but research on host–parasite interactions is still hampered by our inability to genetically transform PCN, especially given the tools that might become available using CRISPR/Cas. We need to understand precisely how syncytia are induced and maintained and why PCN, like other biotrophic plant pathogens, deploys so many effectors during their infection. Understanding the detailed mechanisms behind host resistance to PCN, and whether the same types of novel resistance that do not involve NB‐LRR‐like proteins as described for resistance against soybean cyst nematodes, is also of critical importance towards deploying resistance in the field. Click here for additional data file.


Patients admitted to Roker ward  should have a decreased anticholinergic burden of medication on discharge compared to admission. This will be demonstrated by a reduced score on the Anticholinergic Cognitive Burden (ACB) scale on discharge compared to admission. Target: 80%.Where new medicines with anticholinergic burden are prescribed during admission, there should be evidence that the anticholinergic properties of these medications have been considered prior to prescribing (via documentation in care co-ordination reviews or progress notes). Target: 100%Electronic records were searched for all discharges from Roker ward between 1/1/2019 – 31/12/2019. For each record the follwing information was recorded: demographics; primary diagnosis; total ACB score on admission; and total ACB score on discharge. For all new medications started with an ACB score of over zero, records were searched to establish whether there was evidence that the anticholinergic properties of these medications had been considered.47 patients were identified who were discharged over the time period in question. 30 patients had no difference in ACB score between admission and discharge; 10 patients had a reduction in ACB score and 5 patients had an increase. A total of 9 new medications with ACB scores over zero had been started during all admissions; there were no occasions where there was documented evidence to show that the anticholinergic burden of these medications had been considered.27% of patients had a reduction in their total ACB score during admission; the target was 80%.The reasons for starting medications with an ACB score of greater than 1 were documented in 0% of cases; the target was 100%.Following discussion with the ward consultant and ward pharmacist, regular prescriber meetings have been set up which involve senior nursing staff, medical staff and pharmacy – anticholinergic burden is calculated for each patient as part of these meetingsA re-audit is recommended after 6 months.As both targets were missed by a significant margin, it was recognised that there were significant areas for improvement. The following plan was therefore implemented:


Patients with rheumatic diseases often have multiple comorbidities which may impact well‐being leading to high psychosocial complexity. This scoping review was undertaken to identify complexity measures/tools used in rheumatology that could help in planning and coordinating care.MEDLINE, EMBASE and CINAHL were searched from database inception to 14 December 2019 using keywords and Medical Subject Headings for “care coordination”, “complexity” and selected rheumatic diseases and known complexity measures/tools. Articles describing the development or use of complexity measures/tools in patients with adult rheumatologic diagnoses were included regardless of study design. Included articles were evaluated for risk of bias where applicable.The search yielded 407 articles, 37 underwent full‐text review and 2 were identified during a hand search with 9 included articles. Only 2 complexity tools used in populations of adult patients with rheumatic disease were identified: the SLENQ and the INTERMED. The SLENQ is a 97‐item patient needs questionnaire developed for patients with systemic lupus (n = 1 study describing tool development) and applied in 5 cross‐sectional studies. Three studies  applied the INTERMED, a clinical interview to ascertain complexity and support coordinated care, in patients with rheumatologic diagnoses.There is limited information on the use of patient complexity measures/tools in rheumatology. Such tools could be applied to coordinate multidisciplinary care and improve patient experience and outcomes.This scoping review will be presented to patient research partners involved in co‐designing a future study on patient complexity in rheumatic disease. These tools have been used in health‐care planning and care coordination, and can predict length of stay.Rheumatic diseases are typically systemic and therefore have the potential to impact multiple organ systems requiring lifelong frequent encounters with multiple health‐care providers. Complications of inflammatory rheumatic diseases are frequent and result in additional disease burden.The extent to which complexity tools have been used to better direct care coordination in rheumatology to improve health outcomes is unknown. The purpose of this scoping review was to understand and describe how patient complexity tools/measures have been used in rheumatic diseases to plan a future study aimed at improving care coordination and patient outcomes in rheumatology.2A scoping review is an appropriate knowledge synthesis strategy for this research topic given the emerging nature of patient complexity as a construct, especially in rheumatic disease. Scoping reviews are used to provide a broad overview of evidence and this strategy is helpful in determining knowledge gaps to plan future research.www.covidence.org). In addition, 15 authors of identified existing patient complexity tools found during our searches were contacted to identify any missed relevant publications in rheumatic disease.Title and abstract screening, as well as the article full‐text review, was conducted in duplicate independently by two authors (KH and CEHB) with any disagreements resolved by discussion. The following inclusion criteria were used: English language studies of any design were included if they developed, used or evaluated a tool to measure patient complexity in the context of an adult rheumatic disease including rheumatoid arthritis (RA), psoriatic arthritis, systemic lupus erythematosus (SLE) or vasculitis. Studies were excluded if they were non‐English, published in abstract form only or if they related to single constructs of patient care . Data were managed using Covidence , and findings on 88% of items demonstrated moderate to substantial levels of agreement (κ > 0.4) and high level of test‐retest reliability.Moses et alThe remaining five articles utilizing the SLENQ were cross‐sectional survey studies. Two studies3.2P = .09), was more likely to be receiving disability compensation (P = .03) and scored worse on the MOS SF‐36 as demonstrated by the physical and mental component score . These two clusters of patients also differed significantly on their subjective view of their health status, with the complex cluster rating themselves as more severely ill and having lower functional status. However, the clusters had similar scores on physician‐reported measures including their disease activity score (DAS 28), doctor's global assessment of disease, swollen joint count, tender joint count, blood sedimentation rate and radiographic score of hands and feet. The two clusters differed in health‐care utilization as well with the complex cluster experiencing higher frequencies of hospitalization (P = .04), more visits to the emergency room (P = .00), and more encounters with medical specialists (P = .01). Because the clusters did not differ in disease severity, the increased health‐care utilization demonstrated by the complex cluster was deemed to be likely due to case complexity and psychosocial vulnerabilities. The INTERMED appropriately identified complex patients with an elevated level of both disability and health‐care utilization. An INTERMED score of 21 has been proposed to identify patients who could benefit from case management.Koch et alStiefel et al’sP = .14] and higher levels of quality of life (QoL)  during follow‐up.P = .02).Of those screened (n = 701) with INTERMED, 35% (n = 247) qualified as complex and were included in the study . Overall, the intervention was associated with less depression [effect size in rheumatology patients: 1.7 (standard error (s.e.) = 1.1); The third study which utilized the INTERMED was a practice case article by Latour et al3.3There was a high risk of bias as measured by the Cochrane toolThe COSMIN checklistThe NHLBI quality assessment tool4This scoping review of complexity measures used in patients with rheumatic disease highlights a paucity of measures/tools used to evaluate patient complexity in this field and also emphasizes the evolving construct of patient complexity. Two tools were identified that have been investigated in populations with rheumatic disease to date: the INTERMED and the SLENQ.As the SLENQ was developed specifically for patients with SLE, the study describing its development and psychometric properties was included in our review and evaluated using the COSMIN checklist. We have concluded that the tool was of indeterminate quality, limited by the inability to provide our own rating of the questionnaire as instructed by COSMIN. Nonetheless, the SLENQ is reported to be acceptable, valid and reliable.As the INTERMED was not developed specifically for patients with rheumatic disease, the articles describing its developmentThrough initial stages of our scoping review, while developing our search strategy, we identified a number of other complexity tools; however, none of these met the inclusion criteria as they had not been used in rheumatic disease populations. In general, these other tools are used to evaluate complexity, identify factors interfering with care, indicate multidisciplinary care and facilitate care coordination,The presence of multiple chronic conditions is a growing reality for many patients with rheumatic diseases.While, to our knowledge, this is the first scoping review of complexity measures in rheumatic diseases, there are some limitations to discuss. Extensive preliminary searches were conducted; however, the final search strategy did not include the term ‘patient needs’ as this concept was identified after the final search was completed. As such, it is possible articles using this term alone could have been missed in our review. While the SLENQ is described by the authors as a ‘patient's needs’ questionnaire and not as a complexity tool, it was included as the authors highlight that this tool can be used to aid in directing care to better meet patient needs and the domains overlapped significantly with other complexity tools identified. Further study is warranted to evaluate the correlation between the SLENQ and other established measures of complexity, which often focus on the clinicians’ perspectives of the psychosocial elements leading to higher patient complexity. Additionally, although we recognize a potential relationship between frailty and patient complexity, a search for frailty specific measures was beyond the scope of the present review. Similarly, we acknowledge that different types of complexity tools may be used in children and adolescents with rheumatic diseases, but this population was not included in the scope of our review. This review may also have missed non‐English language complexity tools and tools in clinical use that have not been published. We did not include the PsychInfo database in our search strategy given the focus on rheumatic disease and limited findings during test searches. Other research teams could consider including this database in future search strategies of patient complexity measures in more general patient populations. While the results of our work will be presented to patient research partners to plan future work in designing interventions to better coordinate rheumatology care, patient partners were not directly involved in this work and the framing of this work may therefore have been impacted. Finally, some of the quality assessment tools used to assess the studies were developed recently (eg COSMIN), which could have led to lower study ratings given emerging new standards for patient‐reported measure development and study reporting.This review has identified two tools, the SLENQ and the INTERMED, which have been developed and/or tested in rheumatology patients. Though the SLENQ does not explicitly formulate a complexity score, it summarizes the magnitude of patient needs and the extent to which they are being met. The INTERMED can be used to direct patient care along various domains and also can produce a score that can be used to define complex versus non‐complex for care planning. However, the clinical utility and uptake of such tools are unknown and further study in this area is warranted. Additionally, potential avenues of future study include investigating the relationship between complexity measures and individual disease activity, functional status measures, and anxiety and depression screening scales to determine the set of measures that is most clinically useful in helping direct patient‐centred care while minimizing patient and clinician survey/interview burden. Evaluation of the utility of complexity tools such as the MCAM and PCAM used in other populations may be warranted in rheumatology patients. Lastly, future studies should evaluate the impact using complexity measures to direct care delivery on patient outcomes in rheumatology including patient experience with care, disease activity, patient activation, adherence and quality of life.The authors declare no conflicts of interest.Supplementary MaterialClick here for additional data file.


Extreme droughts are expected to increase in frequency and severity in many regions of the world, threatening multiple ecosystem services provided by forests. Effective strategies to adapt forests to such droughts require comprehensive information on the effects and importance of the factors influencing forest resistance and resilience. We used a unique combination of inventory and dendrochronological data from a long‐term (>30 years) silvicultural experiment in mixed silver fir and Norway spruce mountain forests along a temperature and precipitation gradient in southwestern Germany. We aimed at examining the mechanisms and forest stand characteristics underpinning the resistance and resilience to past mild and severe droughts. We found that (i) fir benefited from mild droughts and showed higher resistance  and resilience  than spruce to all droughts; (ii) species identity determined mild drought responses while species interactions and management‐related factors strongly influenced the responses to severe droughts; (iii) intraspecific and interspecific interactions had contrasting effects on the two species, with spruce being less resistant to severe droughts when exposed to interaction with fir and beech; (iv) higher values of residual stand basal area following thinning were associated with lower resistance and resilience to severe droughts; and (v) larger trees were resilient to mild drought events but highly vulnerable to severe droughts. Our study provides an analytical approach for examining the effects of different factors on individual tree‐ and stand‐level drought response. The forests investigated here were to a certain extent resilient to mild droughts, and even benefited from such conditions, but were strongly affected by severe droughts. Lastly, negative effects of severe droughts can be reduced through modifying species composition, tree size distribution and stand density in mixed silver fir‐Norway spruce forests. We examined mechanisms and stand characteristics underpinning the growth resistance (Rt), recovery (Rc) and resilience (Rs) to past mild and severe droughts in mixed silver fir and Norway spruce mountain forests in southwestern Germany. We found that the forests investigated were to a certain extent resilient to mild droughts, and even benefited from such conditions, but were strongly affected by severe droughts . Lastly, negative effects of severe droughts can be reduced through modifying species composition, tree size distribution and stand density in mixed silver fir‐Norway spruce forests. The climate is temperate to cool‐temperate and mean total annual precipitation ranges from c. 910 to 1920 mm for the period 1881–2016  differing in terms of the length of the regeneration period  and increment controls . The interventions were planned at 5‐year intervals in each stand , the Swabian‐Franconian Forest  and the southwestern Swabian Jura  the plots are part of a well‐documented experiment lasting >30 years, which is based on a strict experimental design and measurement protocol; (ii) the analyzed growth responses to drought are based on trees living at the time of sampling and on those progressively harvested over time, in contrast to most dendroecological studies using only living trees at the time of sampling, thereby missing the responses of trees that had previously been harvested or died; (iii) mortality events were precisely recorded at the tree level, thus eliminating uncertainties related to unknown past mortality  using the Lintab measuring device (precision 0.01 mm). In total, 2012 individual measurement series were obtained  across the six sites. Cross‐dating and ring‐width measurements of each series were checked for errors using the COFECHA software , all trees ≥4.0 cm in diameter at breast height  were mapped, measured  and tagged, recording c. 2000 trees in total. All tagged living trees were periodically remeasured at c. 5‐year intervals, at the end of the growing season. Tree removal occurred during the winter, before the beginning of the following growing season. Trees of poor quality or health, or that had died or disappeared during the interval between inventories were also recorded. The cause and time of death were assessed and the DBH and height at the time of death reconstructed. Annual tree radial growth was measured on discs collected at breast height from 289 trees harvested progressively between 1980 and 2017 from the treatment and control plots  and precipitation sum for each study site were obtained from the DWD Climate Data Center dataset ; the other two events  had the lowest average values of SPEIJuly,5m across sites after 2000  had the lowest average values of SPEI2.4A wide variety of stand structure‐ and composition‐related variables , traits related to resource‐use efficiency  and management‐related variables  was used as tree‐ and stand‐level predictors of growth responses to drought Table .t is the competition intensity experienced by treet, from n neighboring treesi within a radius of 10 m of treet; BA is the treei basal area (cm2); and distanceti is the distance (m) between the stem center of the central treet and its ith neighbor. Along a continuous range of radii, 10 m was selected because it maximized the R2 of the relationship between the periodic annual basal area increment and NIt  exerted by fir, spruce and other species was computed as a ratio of NIspX to NIt, where NIspX is the NIt calculated only considering fir, spruce or other species as neighboring trees, respectively.At the tree level, a distance‐dependent competition index (NI) was computed:x and y coordinates, considering slope and aspect in both x and y directions, to account for the shading of neighboring trees in the canopy. Individual tree APAR was computed as total annual APAR for evergreen species, or total APAR of the period between leaf unfolding and leaf discoloration in autumn for deciduous species  was predicted using the 3D tree‐level model Maestra Medlyn, . Maestraes Table . To avoies Table .vegan , led to similar results (correlation coefficient r > 0.9). A period of 2 years was selected because radial growth autocorrelation >0.5 was found for 1‐ and 2‐year lags , and used to select the model with lowest AICc (best model). Marginal and conditional R‐squared and coefficient of determination  and linear models (at the stand level). General individual‐tree APAR conditions—average values of APAR of the 2 years preceding drought—were included in the models. First, all weakly correlated predictors , with differences among treatments Figure . In cont3.2Drought responses varied considerably between drought events, with significantly lower values of resistance, recovery and resilience observed during severe droughts Figure . Compare3.3For mild drought events at the tree level, species identity and species interaction were the main predictors of resistance, recovery and resilience Table . Fir shoFor severe drought events, species identity, species interaction, drought severity and residual stand basal area at the time of drought were the main predictors of the analyzed growth responses Table . Fir sho3.4For mild drought events at the stand level, APAR, proportion of spruce, Shannon diversity index and number of years since the last thinning were the most important predictors of the analyzed growth responses Table . The ShaFor severe drought events, APAR and the proportion of spruce were the most important predictors of the analyzed growth responses Table . Stand‐l4Based on a unique long‐term silvicultural experiment in mixed silver fir and Norway spruce mountain forests in central Europe, we examined growth responses to mild and severe drought events at both the tree and the stand level. Furthermore, we evaluated the drivers of such responses, using models containing the most influential tree and stand characteristics as well as management‐related variables, to provide insights for the management of such forests under climate change.4.1Our results highlight the higher drought resistance and resilience of fir compared to spruce, although with variability among sites. This is consistent with other studies showing higher drought tolerance of fir at least in the recent past , and this effect continued after drought (recovery >1). Increased temperatures are the probable cause for the growth increase of fir in relation to these mild drought events. The growth of fir, in fact, likely benefits from warmer conditions, even under low precipitation  were associated with higher values of the growth response (particularly recovery and resilience) of fir and spruce to severe drought events (years 2003 and 2011). Drought severity and seasonality are generally important determinants of forest sensitivity  negatively affected the drought resistance of spruce during severe droughts. Broadleaf species such as beech are characterized during the growing season by a high interception of precipitation, stemflow (channel water more to their own rooting system), and may therefore play a negative role especially during periods of water shortage (Staelens et al., The recovery of fir following severe drought events was negatively affected by the presence of other species, including a higher presence of spruce. After a drought, it takes time until deeper soil layers are rewetted. Species with a shallow root system, such as spruce, are thus likely to profit first, at the expense of coexisting species with deeper root systems (Schume et al., The contrasting effects of species diversity on tree growth resilience to severe droughts observed here and elsewhere show that these effects in mixed stands are often complex and depend strongly on the local environment and the complementarity of species‐specific functional traits Ammer, .Stand‐level competition directly affects resource availability (Moreno‐Gutiérrez et al., 4.2.2Stand structural characteristics and composition, and years since the last thinning determined growth responses to drought at the stand level.Stands with larger and taller trees with larger leaf areas (i.e., higher APAR, Figure We found that resistance to mild droughts was higher in the immediate post‐intervention period. A possible explanation is that the first interventions at the beginning of the experiment led to a more intense competition release than later interventions, when the stands had already been thinned multiple times (Giuggiola et al., 4.3The cumulative effects of severe droughts and species composition are likely to have major consequences for mixed fir and spruce forests in central Europe. This study highlights the importance of stand composition for tree‐ and stand‐level drought responses. With adequate water supply and in the absence of disturbances, spruce is more productive than fir and most other species under similar site conditions (Pretzsch, Although the growth response to drought has been investigated for many tree species at the individual tree level, much remains unknown about the drought response of forest stands. This lack of knowledge results because many studies do not sample the full range of tree sizes, and are not based on random samples of trees. This inhibits the scaling of growth from individual trees across species and dimensions to whole stands. The scaling tasks is further complicated by the fact that typically there are no data for trees that have died or were removed over time, which is particularly relevant in managed forests or when the analysis extends over long periods.Overall, the mixed silver fir and Norway spruce stands in central Europe that we studied are resilient to mild drought events, and even profit from such conditions, but they suffer from severe droughts. Forest management can support these forests by promoting their growth resistance, recovery and resilience, specifically by controlling or modifying species composition, tree size distribution and stand density. The approach described here provides relevant information for the management of the widespread European mixed mountain forests dominated by fir and spruce in the face of climate change.The authors declare no conflict of interest.Supplementary MaterialClick here for additional data file.


Y6 and its derivatives have greatly improved the power conversion efficiency (PCE) of organic photovoltaics (OPVs). Further developing high‐performance Y6 derivative acceptor materials through the relationship between the chemical structures and properties of these materials will help accelerate the development of OPV. Here, machine learning and quantum chemistry are used to understand the structure–property relationships and develop new OPV acceptor materials. By encoding the molecules with an improved one‐hot code, the trained machine learning model shows good predictive performance, and 22 new acceptors with predicted PCE values greater than 17% within the virtual chemical space are screened out. Trends associated with the discovered high‐performing molecules suggest that Y6 derivatives with medium‐length side chains have higher performance. Further quantum chemistry calculations reveal that the end acceptor units mainly affect the frontier molecular orbital energy levels and the electrostatic potential on molecular surface, which in turn influence the performance of OPV devices. A series of promising Y6 derivative candidates is screened out and a rational design guide for developing high‐performance OPV acceptors is provided. The approach in this work can be extended to other material systems for rapid materials discovery and can provide a framework for designing novel and promising OPV materials. Twenty‐two new Y6 derivatives acceptor materials with the predicted power conversion efficiency higher than 17% are screened out by using machine learning. Combing the trends discovered by machine learning and quantum chemistry calculations, it is further found out the ways in which side chains and end acceptor units affect the performance of OPV. However, the conventional procedure for experimenters to develop new acceptors is by synthesizing molecules with various possible structures and then test their photoelectric conversion performance, which is time and resource consuming. Therefore, screening molecules in a chemical space  in advance to obtain potential OPV molecules with high performance will save resources and accelerate the development of new OPV materials.Organic photovoltaic (OPV) cells based on non‐fullerene acceptor materials have made great progress in recent years and are expected to achieve highly efficient power conversion as the form of renewable energy. Since the star acceptor material Y6 was developed,1 the  to establish the aforementioned structure–performance relationship. As a data‐driven method, machine learning can learn from existing data, build relationships, and make predictions, even without relevant background knowledge.Due to the complexity of organic photovoltaic cells, it is difficult to establish a direct relationship between the chemical structure of materials and the performance of OPV devices using traditional computational simulation methods. In recent years, with the development of artificial intelligence, researchers have tried to use machine learning4 to e Recently, some outstanding works related to feature engineering and machine learning algorithms have been reported to improve the prediction accuracy. Interestingly, some have gone further and tried to obtain structure characteristics of high‐performance OPV materials by machine learning models. For example, Sahu et al. extracted the effect of unit changes on the photoelectric conversion performance through machine learning by using molecular descriptors computed from quantum chemistry as input and then dividing the predicted OPV material molecules into multiple functional units. Wu et al. used one‐hot encoding to convert OPV donor–acceptor pairs into input, and then they successfully obtained some high PCE donor–acceptor pairs by combing machine learning and experiments. However, few works can provide the design principles of new high‐performance OPV materials for experimentalists. And the existing works are based on old databases which lack new Y6 series acceptors. Although there are thousands of OPV experimental data, they are almost useless for the new material system of Y6. It is challenging to build the structure–performance relationship for Y6 series acceptors and discover new high‐efficiency Y6 derivative acceptors due to the small database available.Machine learning has been widely used to predict the PCE of OPV devices and screen new OPV materials.7, 8 (RF) algorithm shows a good predictive ability and was used to screen the chemical space formed by all possible molecular structures. Our machine learning model screened out 22 new high‐potential OPV acceptor materials with a predicted efficiency greater than 17%. The screening results show that high‐performance OPV non‐fullerene derivatives of Y6 acceptors typically possess medium‐length side chains. Further quantum chemistry calculations show that the end acceptor unit of molecules mainly modifies the frontier molecular orbital energy levels and the electrostatic potential (ESP) at the molecular surface, thereby leading to differences in photoelectric conversion performance.In this work, we established an OPV database with Y6 and its derivatives as acceptor materials. The acceptor molecules were divided into three parts and encoded by an improved one‐hot code as input for machine learning. The machine learning model based on Random Forest15 . The chemical structures of the acceptor materials along with their corresponding device PCE were then recorded to establish the original database. The PCE of OPV devices distribution in the database is shown in  Since all these acceptor molecules are symmetrical A‐D‐A‐D‐A type molecules, as shown in Figure TableIn order to facilitate the learning of the relationship between molecular structure and device performance, it is necessary to convert the molecules into code that can be recognized by computers.12 Sin (GBDT), are suitable for the fingerprint like input. We chose the RF algorithm to learn the relationship between the input that contains the molecular structures and the PCE of their based OPV devices. Figure  The mean absolute error (MAE) and correlation coefficient r on the training set are 0.43 and 0.97, respectively. While the MAE and r on the validation set are 1.08 and 0.66, respectively. The performance of the machine learning model on the training set is excellent, implying that the algorithm achieved a good fit to the input data. The performance on the validation set is worse than that on the training set because part of the fragment has only appeared once in the database. When the molecules with these fragments are divided into the validation set, machine learning cannot make reasonable prediction for the unlearned features. Nevertheless, the performance of the machine learning model on the training set and validation set is good enough to expect that the machine learning model can make accurate predictions for the new combinations based on the fragments as all of them have been learned by machine learning algorithm.According to previous research, ensemble methods, such as RF and Gradient Boosted Decision Tree16 . On D1 unit, 2‐butyloctyl usually shows higher performance than 2‐ethylhexyl and 2‐hexyldecyl , while nonyl usually shows higher PCE than hexyl and undecyl . The structure of these side chains is shown in FigureFor the A1 unit, the machine learning model provides a prediction but the general trend with changing A1 units is unclear. To further understand the impact of end acceptor unit, we selected 5 typical molecules denoted by Z1, Z2, Z3, Z4, and Z5, respectively. Their chemical structures and predicted PCE are shown in  Moreover, the difference between LUMO energy level of acceptor and HOMO energy level of donor is directly related to the open circuit voltage of the OPV device. Although the energy levels measured by cyclic voltammetry are not the same as the molecular orbital energy levels calculated by quantum chemistry methods, it has been shown that they exhibit the same trend to a certain extent. As shown in FigureFirstly, we calculated the frontier molecular orbital energy levels of these five molecules. The proper energy level alignment between the molecular orbitals of the donor and acceptor materials is very important in photoelectric conversion. The differences in highest occupied molecular orbital (HOMO) energy levels and lowest unoccupied molecular orbital (LUMO) energy levels between donors and acceptors influence exciton dissociation.18 MorEgfund) and optical gap (Egopt) is the electron–hole pair binding energy (Eb). The smaller the Eb, the easier it is for electron and hole to dissociate. The calculated results shown in Figure ES1) and lowest triplet excitation energy (ET1) is the singlet–triplet energy gap (ΔEST), and a lower ΔEST is conducive to simultaneously realize an enhancement in light absorption and a reduction of energy losses. The calculation results of TD‐DFT shown in Figure EST of the five molecules are also close, indicating that they withal yield high performance devices. This is in excellent agreement with the predicted high PCE values from the machine learning model.The difference between fundamental gap Egfund anFigureThe UV–vis absorption spectra of these five molecules calculated using TD‐DFT with two different functionals are shown in  due to its influence on molecular packing. In addition, the ESP difference between donor and acceptor molecules provides a driving force for exciton dissociation. The ESP, V (r), at the surface of a molecular is defined as sum of the Coulomb potential of each nucleus and electronsV (r) is written in terms of atomic units. ZA is the charge on nucleus A, RA is the coordinates of A, and ρ (r) is the charge density. Computations of ESP at the van der Waals surface of these five molecules were performed according to the method outlined in ref. [FigureRecently, the electrostatic potential (ESP) distribution on the molecular surface of OPV materials has attracted a lot of attention25 due in ref.  and the The ESP distribution on these five molecular surfaces is similar, with significant dissimilarities occurring near the end acceptor units. As shown in Figure 3In summary, we trained a machine learning model based on the OPV database constructed from Y6 and its derivatives. The machine learning model shows good predictive ability, and 22 new acceptor materials with predicted PCE higher than 17% were screened from the new virtual database. The acceptor molecules predicted to have higher performance possess medium‐length side chains. Quantum chemistry calculations on five high performance molecules with the same donor unit but with different acceptor units reveal that these molecules mainly show differences in frontier molecular orbital energy levels and the ESP distribution on the molecular surface. These differences were shown to be the origin in their different photoelectric properties. Our work has screened out a series of OPV acceptor materials with high potential, and provided a rational design guide for the development of high‐performance OPV materials. The approach in this work, for investigation of the relationship between the molecular structure of OPV materials and the PCE of their based OPV devices, can be extended to other material systems for rapid materials discovery and can provide a rational framework for the design of novel and promising OPV materials.4r were employed to evaluate the machine learning model.Cov is the covariance and Var is variance of data.Random forest (RF) algorithm was used to establish the structure–performance relationship between OPV materials and PCE of their based OPV devices. The number of trees in the forest was set to 50. The small size of the data set required that leave‐one‐out cross‐validation (LOOCV) technique was used for cross‐validation of the training set, for reliable model evaluation. Mean Absolute Error (MAE) and correlation coefficient  library on Python 3.x.The machine learning algorithms, model evaluation, and other related statistical analysis were performed using scikit‐learn28 libDensity functional theory (DFT) and time‐dependent density functional theory (TD‐DFT) were used to calculate the geometric structures and properties of molecules. The side chains of all molecules were removed in these calculations as they are identical. Since OPV usually worked in the form of solid films and the solvents were sometimes different even when tested in solvent environment, the solvent mode was not considered. combined with DFT‐D3 (BJ) dispersion correction. The optimized structures were obtained at the minimum energy points and with no imaginary frequencies.Geometry optimization and vibration analysis were performed at B3LYP/6‐31G level30 com The UV–vis absorption spectra of the molecules were obtained by calculating the first 80 excited states and broadening by Gaussian function. The full width at half maximum (FWHM) was set to 0.33333 eV.The frontier orbital energy levels, vertical ionization energies, and excited states of the molecules were calculated using B3LYP functional combined with 6‐31G basis set. The vertical electron affinity was calculated by combining the 6‐31+G basis set.33 The The analysis of wavefunction was performed by Multiwfn and visualization was performed by VMD.All DFT and TD‐DFT calculations were performed by Gaussian program.34 TheEgHM) was equal to the difference between LUMO and HOMO energy levels.E is the electronic energy of the system.HOMO‐LUMO gap  is defined as:n is the original number of electrons.Electron affinity (EA) is defined as:Egfund) is equal to the difference between IP and EA.Eb) is equal to the difference between fundamental gap and optical gap.EST) is equal to the difference between the lowest singlet excitation energy (ES1) and the lowest triplet excitation energy (ET1)Fundamental gap (ω parameter of long range corrected functional ωB97XD and the iteration results are shown in the Supporting Information. The conclusions are consistent with those obtained by the B3LYP functional. The optimal ω parameter has a value of 0.0943, which was optimized by minimizing function J2The above properties were all calculated iteratively via a tuned al ωB97XD37 andThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Current electroencephalography (EEG) practice relies on interpretation by expert neurologists, which introduces diagnostic and therapeutic delays that can impact patients’ clinical outcomes. As EEG practice expands, these experts are becoming increasingly limited resources. A highly sensitive and specific automated seizure detection system would streamline practice and expedite appropriate management for patients with possible nonconvulsive seizures. We aimed to test the performance of a recently FDA-cleared machine learning method  that measures the burden of seizure activity in real time and generates bedside alerts for possible status epilepticus (SE).n = 353) who underwent evaluation of possible seizures with Rapid Response EEG system . Automated detection of seizure activity and seizure burden throughout a recording  was performed with Claritγ, and various thresholds of seizure burden were tested . The sensitivity and specificity of Claritγ’s real-time seizure burden measurements and SE alerts were compared to the majority consensus of at least two expert neurologists.We retrospectively identified adult patients (n = 249), highly epileptiform patterns , or seizures . The algorithm generated a SE alert (≥ 90% seizure burden) with 100% sensitivity and 93% specificity. The sensitivity and specificity of various thresholds for seizure burden during EEG recordings for detecting patients with seizures were 100% and 82% for ≥ 50% seizure burden and 88% and 60% for ≥ 10% seizure burden. Of the 179 EEG recordings in which the algorithm detected no seizures, seizures were identified by the expert reviewers in only two cases, indicating a negative predictive value of 99%.Majority consensus of neurologists labeled the 353 EEGs as normal or slow activity (Claritγ detected SE events with high sensitivity and specificity, and it demonstrated a high negative predictive value for distinguishing nonepileptiform activity from seizure and highly epileptiform activity.Ruling out seizures accurately in a large proportion of cases can help prevent unnecessary or aggressive over-treatment in critical care settings, where empiric treatment with antiseizure medications is currently prevalent. Claritγ’s high sensitivity for SE and high negative predictive value for cases without epileptiform activity make it a useful tool for triaging treatment and the need for urgent neurological consultation. The timely diagnosis and treatment of patients with seizures can prevent significant morbidity and mortality . ApproxiUnfortunately, the conventional practice of EEG in critical care and emergency department settings suffers from both delayed access to EEG recordings and significant delays in its interpretation by skilled neurologists , 12. Wheseizure burden  to help bedside practitioners caring for critically ill patients. Providing such feedback would allow for risk stratification and evaluation of treatment response, as well as for determining the urgency of requesting neurological consultation, in real time.The use of artificial intelligence (AI) in clinical medicine has been on the rise, and within the specialty of neurology, brain signals have proven particularly amenable to the machine learning approach . There arisk stratification tool using EEG data in real time [The use of AI-assisted programs for EEG interpretation is becoming increasingly necessary as the utilization of EEG is expanding in the fields of critical care and emergency medicine while human resources are scarce, and detailed review of many simultaneous continuous EEG recordings by neurologists in real time is simply too cost prohibitive to be deployed at scale. As a result, there exists a significant unmet need for automated algorithms that could assist nonexperts by providing a reliable eal time , 20, 21.In the current study, we aim to validate a supervised machine learning algorithm, labeled as Claritγ , that was recently approved by the FDA and is being used in clinical settings as a clinical decision support tool. We designed this retrospective study to measure the performance of the algorithm applied to EEG data acquired using Ceribell’s Rapid Response EEG system (Rapid-EEG) from patients in critical care and emergency department settings and to describe its potential clinical implications.www.ceribell.com for additional information) consists of a headband with ten electrodes connected to a handheld recorder. The headband is placed circumferentially around the head and is fastened over the forehead with a locking clasp, and EEG setup is typically performed by nurses, allied health professionals, or healthcare providers trained by either online or in-person sessions. The Rapid-EEG electrodes  correspond approximately to the lateral chains of the International 10–20 system , and a longitudinal bipolar montage is constructed to display the EEG waveforms. During EEG recording, the system simultaneously measures the impedance between two adjacent electrodes once per minute using a test frequency that is outside the EEG recording band to avoid creating artifact. The data are acquired as digital samples at a rate of 250 Hz. The handheld recorder displays, records, and wirelessly transmits the data to a remote cloud server, where a cloud-based seizure detection software continuously monitors the EEG recording.The Rapid-EEG system . The recordings were from adult patients (≥ 18 years old) undergoing evaluation for altered mental status and possible seizures in intensive care units and emergency departments at six academic and community hospitals across the USA between January 2018 and April 2019. EEG data were anonymized, and no identifying demographic or clinical information was accessed for this study. The study was classified as exempt research according to the US Department of Health and Human Services regulation 45 CFR 46.104(d)(4), and individual patient consent was not required. It should be noted that the Claritγ algorithm was developed using training and testing datasets that were entirely different and independent from the dataset we have used in the current study for the validation of the algorithm performance.We validated the performance of the Claritγ algorithm in a cohort of 353 Rapid-EEG recordings from 353 patients. An overview of the algorithm is shown in Fig. Seizure burden, the prevalence of seizure activity within any 5-min period, was described using thresholds adapted from American Clinical Neurophysiology Society guidelines  as folloEach EEG file was independently reviewed by at least two independent neurologists with fellowship training in clinical neurophysiology or epilepsy. Reviewers were blinded to patients’ clinical information, including medical history, indication for EEG monitoring, prior treatment with antiseizure medication, and Claritγ seizure burden trend. Expert consensus (reference standard) was defined by agreement between a minimum of two neurologists; additional reviewers were consulted if the first two neurologists did not agree until a majority consensus was reached. Reviewers were instructed to indicate whether the EEG contained normal, diffusely slow, highly epileptiform, or seizure activity. Highly epileptiform patterns (HEP) included activity that did not fully meet the Salzburg criteria  for elecWe defined the reference (“gold”) standard as the consensus agreement of at least two neurologists reading the same EEG, both for each overall EEG record and for individual episodes of expert-identified seizures. We then tabulated Claritγ algorithm output of seizure burden against this reference standard. Using these tabulations, we calculated the sensitivity, specificity, and false detection rate  of various seizure burden thresholds  against the expert consensus; 95% CIs for sensitivity and specificity measures were calculated using established formulas . It shouκ.Given the wealth of evidence –36 descrA total of 353 Rapid-EEG recordings were evaluated in this study with a cumulative EEG recording duration of 1052 h (mean EEG duration: 233 ± 227 min). No cases were excluded. Expert consensus determined the most severe feature of the overall EEG record to be status epilepticus in nine cases, seizures (duration < 4.5 min) in eight cases, HEP in 87 cases, and normal or low background in 249 cases  of these false detections, the expert consensus categorization of the EEG was HEP, indicating that there was concerning epileptiform activity present in the record, even if no unequivocal seizures were agreed to be present by both reviewers.Claritγ correctly identified 41 of the 47 total discrete seizure events of any duration (88.2% sensitivity). In the 1052 h of cumulative EEG across the 353 EEG recordings, Claritγ had 383 false detections, resulting in an overall false detection rate of 0.36 per hour. Of the 179 EEG recordings in which Claritγ detected no seizures, seizures were identified by the expert reviewers in only two cases . In both cases, the seizures missed by Claritγ were less than 30 s in duration.The four experts reviewed at least 250 h of the overall dataset . When these four reviewers’ identifications of status epilepticus were compared to the majority consensus Table , individseizure burden measurement using EEG data acquired with Rapid Response EEG. This algorithm showed high sensitivity (100%) in the detection of status epilepticus  and accurately identified 88% of seizures of any duration when compared to the reference standard of consensus of expert neurologists  impact on physicians’ clinical decision making and patient management. We remind the reader that the output of any AI algorithm ought to be interpreted in the context of the user’s pretest clinical judgment. In keeping with this, we have made an initial attempt to recommend a possible workflow for the use of our algorithm in the current clinical practice of Rapid-EEG Table . We are risk stratification tool to streamline the practice of stat EEG and guide emergent triage and more precise treatment for patients with low or high suspicion for nonconvulsive seizures. Moreover, it also can lessen the stress and unnecessary burden on neurologists with EEG expertise. We are hopeful that simplified risk stratification offered by our algorithm combined with the earlier and easier acquisition of EEG will lead to better management of patients in need.As suggested in this workflow, Claritγ algorithm has potential utility as the first of its kind The lack of clinical data provided to reviewers during their retrospective EEG review was the most important limitation of this study and should be considered highly relevant to the interpretation of its findings. In clinical practice, patient history  and bedside or video observations  are used to inform EEG interpretation and make definitive determinations of seizure versus nonseizure, and treatment is tailored to the patient as a whole rather than the EEG in isolation. Claritγ, like all other automated seizure detection algorithms, does not consider ancillary clinical information, and it is critical to acknowledge that output from such an algorithm does not provide the final diagnostic conclusion for the patient. Indeed, the sensitivity and specificity of any system for EEG review (human or machine) would be significantly improved by access to additional patient data.The implementation of Claritγ and its impact on real-world diagnostic and treatment decisions were not studied here and may be addressed in future investigations. As noted in the discussion of clinical workflow, individual providers or practice groups may utilize different alarm thresholds to expedite EEG review and treatment or establish treatment protocols that rely on the various functions of Rapid-EEG  based on providers’ comfort with each.Our cohort contained a relatively low number of status epilepticus cases (nine out of 353 EEGs) which affects the reliability of our sensitivity estimate. A larger cohort of Rapid-EEG data would be helpful to address this. However, it should be noted that this multisite cohort was obtained without excluding cases and could be considered reflective of the population being studied.The Rapid-EEG system lacks midline and parasagittal electrodes, and consequently a focal seizure that is highly localized to the parasagittal region would not be detected by Rapid-EEG or identified by Claritγ (although prior research –39 has aImplementation of artificial intelligence tools in the field of neurology and epileptology remains limited despite the urgent need for tools to accommodate the expanding practice of EEG and address the inefficiencies of the current EEG infrastructure. Claritγ provides highly sensitive detection of status epilepticus and may be useful as a risk stratification tool that could expedite diagnosis and treatment of patients with nonconvulsive seizures. We believe that machine learning tools will never replace a careful history and examination filtered through a well-honed clinical acumen of the user and recommend its safe use by interpreting its output in the context of proper clinical judgment.


Novel translucent monolithic zirconia has improved optical properties, and it may fulfill patient's esthetic demands and overcome the chipping risk of bilayer metal‐ceramic restorations. New zirconia's microstructures allow us to mimic natural teeth. Novel translucent monolithic zirconia has improved optical properties, and it may fulfill patient's esthetic demands and overcome the chipping risk of bilayer metal‐ceramic restorations. New zirconia's microstructures allow us to mimic natural teeth.  The patAt the following clinical appointment, isolation was provided with a rubber dam  from #4 through #13, placing clamps on #4 and #13  and old porcelain‐fused‐to‐metal restorations shade A2 were removed , and full monolithic translucent zirconia restorations were digitally designed  following the patient's esthetic desire Figure . Monolit3The patient presented with esthetic concerns after having porcelain‐fused‐to‐metal (PFM) restorations in the maxillary anterior region. After the initial evaluation, gingival inflammation and bleeding on the margin of crown #8 were found. The patient was informed that a conservative approach could be provided with dental prophylaxis followed by monitoring the restorations. The patient's dissatisfaction with the previous dental care outcome drove her to request the restorations' replacement without any metal and providing a harmonious smile.Porcelain‐fused‐to‐metal crowns have been considered to be a gold standard in dentistry for a long time.Translucent monolithic zirconia restorations could be opaquer than glass‐ceramics. However, patients were looking to have a “Hollywood smile”,The workflow of these restorations was a combination of conventional and novel techniques. Conventional polyvinyl siloxane impression was taken, followed by conventional cast fabrication of dental model with type IV dental stone. Then, the cast was scanned for digital designing of restorations. Final restorations were milled out of zirconia ceramic, but a dental technician manually provided the characterization and staining. This type of restorations can be entirely fabricated with a digital workflow; however, the artistic micro details provided by a technician's hands still cannot be reproduced by the milling equipment. The software used in this case  allows for a personalized digital design of the restorations with different shapes such as square, round and ovoid and patient and clinician can see the images of the designs and select them before their fabrication. The final translucent zirconia restorations provided in this report showed appropriate esthetic and clinical performance. High esthetic results for translucent zirconia crowns in the esthetic zone can be achieved through the procedures described above, but the outcome depends on a detailed treatment plan evaluating esthetic and functional parameters while considering patients' desires. Furthermore, the patient's cooperation during treatment and post‐operative care of the restorations is crucial to achieving a positive outcome.4Monolithic translucent zirconia crowns in the anterior zone may provide high esthetic results similar to glass‐ceramic restorations. A dental technician must provide stain and characterization with anatomic features in the ceramic during the fabrication process.The authors declare that there is no conflict of interest regarding the publication of this article.CAJ and JVT contributed to concepts and manuscript editing. CAJ and AT contributed to design. HH and RSH contributed to definition of intellectual content. HH and JVT contributed to manuscript editing. JVT and AT contributed to literature search and manuscript review.The patients described were fully informed on the method and the purpose of the case report. Written consent to participate and for publication was obtained by the patients and is available upon request.All authors have confirmed during submission that patients' consents have been signed and collected in accordance with the journal's patient consent policy.


This paper revisits the themes of an influential 1993 review regarding the factors shaping the mental health and psychosocial well‐being of refugees to take stock of developments in the evidence base and conceptualisation of issues for refugee children over the last 25 years.The study deployed a systematic search strategy. This initially identified 784 papers, which was reduced to 65 studies following application of inclusion and exclusion criteria. We used a later iteration of Bronfenbrenner’s bioecological model of human development – the PPCT model – to consolidate evidence.We identify a range of risk and protective factors operating at individual, familial, community and institutional and policy levels that influence outcomes for refugee children. The dynamics shaping the interaction of these influences are linked to the life course principles of socio‐historical time and developmental age, proximal processes and child agency.Actions at individual, familial, community, school, institutional and policy levels all have potential traction on mental health and psychosocial well‐being of refugee children. However, evidence suggests that greatest impact will be secured by multilevel interventions addressing synergies between ecological systems, approaches engaging proximal processes (including parenting programmes) and interventions facilitating the agency of the developing refugee child. Of the estimated global refugee population of approaching 26 million refugees, over a half are under the age of eighteen UNHCR, . The ‘glWorld Mental Health: Problems and Priorities in Low‐Income Settings  was developed A systematic search was undertaken in five databases – MEDLINE (EBSCO), CINAHL (EBSCO), PsycINFO (EBSCO) and SCOPUS (Pro‐Quest) for peer‐reviewed evidence published in English since January 2010 up to November 2019. Restriction by publication date was applied to capture the evidence reflective of the effects of recent political and war‐driven displacement in Middle East, Asia, Sub‐Saharan Africa and Latin America. Search terms and keywords were developed in consultation with a subject‐specialist librarian. The following combination of terms were used: child OR minor* OR young OR adolescent OR youth OR teenage AND asylum seeker OR refuge* OR displaced person OR internally displaced person AND psychiatr* OR psycholog* OR psychosocial well‐being OR psychosocial wellbeing OR mental OR mental health OR mental issue OR distress OR stress OR emotional stress OR emotion AND risk factor* OR stressor* OR trauma OR vulnerability factor* AND protective factor* OR adaptation* OR modifying factor* OR resilience OR develop* OR social support* OR coping* OR psychosocial support* OR recovery OR wellbeing OR well‐being OR adjustment OR behavio?r OR outcome.Studies were included if (a) the primary aim was to explore risks (stressors) and/or protective factors/processes contributing to mental health and psychosocial well‐being of refugee children and (b) study participants were refugee children (age range 0–18 years or mean age < 18 years) or caregivers sharing information about their refugee children. A risk factor was defined as a psychosocial adversity or event that would be considered a stressor to most people and that may hinder normal functioning Masten, . ProtectData extraction was performed using a standardized data extraction form. Details were extracted on (a) the study design, (b) population demographics, (c) setting and length of stay, (d) methods of data collection, (e) factors intrinsic to the child and (f) factors related to ecological systems of potential influence in Bronfenbrenner’s bioecological model , Australia (10), the United States (7), mainland Europe (9), Canada (2) and the United Kingdom (2). Nineteen studies were focused in the Middle East: including Palestine (7), Turkey (6), Jordan (2) and Lebanon (5). Four studies were based in Africa and two in Asia. Forty‐one studies (63.1%) employed quantitative, 19 (29.2%) qualitative and 5 (7.7%) mixed‐method study designs, varying substantially in terms of sample size , participants’ ages , and methods of data collection . Thirteen (20%) studies reported on unaccompanied refugee children; eight (61.5%) of which presented quantitative data. Two qualitative articles used the same study participants, but different data collection methods  and those sharing a common ethnic and refugee background , the most marked development in the evidence base over the last 25 years is with respect to the stressors of settlement (either temporary – or protracted – within camps or urban settings) and resettlement . There is strong evidence regarding the impacts of these  can both enhance and inhibit a protective environment for children , inter‐parental conflict  and low quality of parent–child interactions   to navigate to the resources necessary to sustain positive functioning under stress, as well as the capacity of systems to negotiate for resources to be provided in ways that are experienced as meaningful’ Ungar, . This unSeveral limitations should be noted. Refugee children are a widely diverse group. Elaborations presented in this review do not distinguish between specific needs of high‐risk refugee populations, for example, unaccompanied refugee minors, trafficked and undocumented children, former child soldiers and those with a history of torture, who might need more urgent and tailored mental health support interventions. We collate evidence from studies in widely differing social, economic and cultural contexts, including children in protracted camp settlements and those resettled in high‐income host countries, within the same analytic frame. This allows us to observe trends in common across these diverse experiences, but should not be taken to underplay the significance of differences in these contexts. Evidence is collated from peer‐reviewed articles indexed in four electronic databases in English. This may have introduced publication and language biases. Although these biases have received much less consideration in narrative reviews than systematic reviews and meta‐analyses, their potential effects should be acknowledged. Most importantly, there are constraints associated with the use of a framework of risk and protective factors to organise literature search and data extraction. Although we adopted clear definitions for these terms, we acknowledge that selected studies drew on a wide range of alternative theoretical framings for these constructs. Further, the relative impact on developmental trajectories of the risk and protective factors considered should not be implied: this has not been formally assessed and – as indicated by the analysis – will, indeed, vary widely across contexts and time‐course.The study notes the burgeoning literature on mental health and psychosocial well‐being of refugee children, significantly deepening our understanding of factors shaping experience and outcomes. A bioecological framing of the varied risks and protective factors influencing refugee children’s well‐being serves as a suitable frame for collating this evidence, especially with regard to processes of their interaction. Bronfenbrenner’s later PPCT model serves to highlight the interaction of historical time and developmental age, the pivotal role of proximal processes and the influence of child agency in determining outcomes. Informed by this framing of the evidence base, mental health‐promoting interventions should place greater emphasis on promoting positive proximal processes operating between an active, evolving refugee child and ‘significant others’ , symbols  and objects (policies and institutions) in their daily environment. These interventions targeting proximal processes are necessary if appropriate actions to address risks and stressors at individual, community, school, institution and policy levels are to have traction on mental health and psychosocial well‐being.


Observational analyses comparing coronary artery bypass surgery (CABG) and percutaneous coronary intervention (PCI) among elderly or frail patients are likely biased by treatment selection. PCI is typically chosen for frail patients, while CABG is more common for patients with good recovery potential.We hypothesized that skilled nursing facility (SNF) use after revascularization is a measure of relative frailty associated with outcomes following coronary revascularization.We used a 20 percent sample of Medicare beneficiaries aged 65 years or older who received inpatient PCI or CABG between 2007–2014. Key explanatory variables were the revascularization strategy and SNF use after revascularization. We used Cox regression to evaluate death and repeat revascularization within one year and logistic regression to evaluate SNF use and 30‐day readmissions/death.CABG patients were 25.1 percentage points  more likely to use SNF following revascularization than inpatient PCI patients. SNF use was associated with a higher death rate (hazard ratio (HR): 3.19 ) and a 16.2 percentage point  increase in 30‐day readmissions/death. Among patients with SNF use, CABG was associated with a decrease in 30‐day readmissions/death compared to PCI.While CABG was associated with higher rates of SNF use and 30‐day readmission/death overall, CABG was associated with significantly lower rates of 30‐day readmissions/death among patients with SNF use. The findings suggest that caution is needed in treatment selection for patients at high‐risk for SNF use and that selection of inpatient PCI over CABG may be associated with frailty and worse outcomes for some patients. CABG is associated with lower rates of mortality in observational researchDespite prior research, gaps exist in our understanding of how the evidence applies to elderly or frail patients. Patients who are very elderly (85 and older) or frail are typically excluded or underrepresented in in randomized trials comparing CABG to PCI.In this study, we addressed these gaps by using a large data source of elderly and frail patients. We sought to compare the utilization of SNF based on initial revascularization strategy and patient co‐morbidities. We then evaluated the association of treatment and SNF use with key outcomes including all‐cause mortality, repeat revascularization, and 30‐day readmissions or death. In particular, we assessed whether the association of treatment with outcomes was different among patients who did or did not have SNF use after discharge from inpatient revascularization.2We derived the study cohort from a 20 percent random sample of Medicare beneficiaries 65 and older who had simultaneous coverage of Medicare Parts A, B, and D for at least 1 month between 2007–2014. We identified all patients who had PCI or CABG as part of an inpatient admission. We limited our sample to patients who had Medicare fee‐for‐service (Parts A and B) during the month of coronary revascularization since these patients have full claims data. We also excluded patients who had PCI performed as an outpatient procedure because these patients tend to be healthier and not likely to require SNF services. Lastly, we excluded patients who were already in a nursing home before revascularization because such patients were already frail and may be more likely to use SNF after revascularization. All data came from Medicare claims and enrollment records. We received Institutional Review Board Approval from the University of North Carolina at Chapel Hill. We did not obtain informed consent from patients because of the de‐identified nature of this secondary data source.We focused on three outcomes following live discharge after revascularization: time to all‐cause death, time to first repeat revascularization, and 30‐day readmissions or death. We measured all‐cause death using the Centers for Medicare & Medicaid (CMS) date of death variable. We identified the date of repeat revascularization and readmissions using claims data. The time to all‐cause death and repeat revascularization were measured starting at the discharge date for the index hospitalization during which the patient received an initial revascularization.The key explanatory variables were whether the patient used Medicare inpatient post‐acute care services within 30 days following discharge and the initial revascularization strategy (PCI or CABG). The inpatient post‐acute care services included stays in long‐term care hospitals (LTAC), inpatient rehabilitation facilities (IRF), and SNF. The vast majority of post‐acute care utilization was for SNF (82.5%) and so we refer to this dichotomous explanatory variable as ‘SNF’ although it also encompasses LTAC and IRF. In addition, we controlled for additional clinical and demographic factors that may be associated with outcomes: age, race/ethnicity, admitting diagnoses, multi‐vessel vs. single‐vessel PCI, the Charlson Comorbidity Index, Medicare/Medicaid dual eligibility, hemodialysis status, and discharge year.We performed the analyses using Stata version 16 . We first evaluated SNF use as an intermediate outcome using logistic regression and then included SNF use as an explanatory variable in all subsequent regressions. We did not attempt to adjust for the fact that SNF use technically occurs after revascularization choice, so all estimation results pertain to associations rather than causal effects. We evaluated time‐to‐death and time‐to‐revascularization using Cox proportional hazards regression for deaths and for revascularizations for up to 365 days following discharge. In addition to these regression models, we also evaluated time‐to‐death between 30 and 365 days by excluding patients who died within the first 30 days. We performed this additional regression because SNF use was measured within the first 30 days. Since patients had to survive long enough to receive SNF at some point in the first 30 days, this measure could have led to immortal time bias.We evaluated the Cox proportional hazards assumptions using the Schoenfeld residuals test.3N = 125 077) and patients who received CABG (N = 62 334). The use of SNF services in the first 30 days after revascularization was lower for PCI patients (8.2%) than CABG patients (28.4%). PCI patients were also older (75.2 vs. 74.1), and had a slightly higher Charlson Comorbidity Index (2.66 vs. 2.57) compared to CABG patients.The descriptive statistics Table  show difThe unadjusted outcomes are stratified by treatment (PCI and CABG), age group, and SNF use Table . The perThe adjusted outcomes were similar to the unadjusted outcomes Table . For theFor all‐cause mortality, SNF use was associated with a much greater rate of death for the 0–365 days death model (hazard ratio (HR): 3.19 ). The rate of death was also lower for patients who received CABG compared to single‐vessel inpatient PCI . However, the rate of death was slightly for patients with multi‐vessel PCI compared to patients with single‐vessel PCI . Overall, the results for the 30–365 days death model were similar in magnitude and direction as the 0–365 days model. However, the difference for CABG compared to inpatient PCI did become larger  and the difference for multi‐vessel PCI compared to single‐vessel PCI became non‐significant.For repeat revascularization, SNF use was associated with a slightly lower rate . The rate of repeat revascularization was much lower for patients who received CABG compared to inpatient PCI  and slightly higher for patients with multi‐vessel PCI .SNF use was associated with a higher predicted percentage of 30‐day readmissions/death Table . The preThe extended Cox model results allowed the HRs for death to vary by time period . The HRs for PCI and CABG patients with SNF compared to PCI patients without SNF were greater in magnitude for days 0–90 and the magnitude steadily declined to the period for days 270–365. The findings were similar for the 30–365 days model . This pattern suggests that the association between SNF use and death was stronger for time periods closer to the date of revascularization.For repeat revascularization, the results were more stable over the time periods . The rate of repeat revascularization for PCI with SNF use was slightly lower and the rate for CABG with SNF was much lower compared to PCI without SNF across all four periods.4In a large sample of patients receiving inpatient coronary revascularization, SNF use was more common following CABG compared to PCI. However, among patients with SNF utilization, mortality was significantly higher among patients selected for PCI. These findings were present despite adjustment for age, sex, multi‐vessel vs. single‐vessel PCI and medical comorbidities, suggesting that unmeasured confounders are associated with SNF use and subsequent mortality, rather than revascularization itself. In addition, SNF use overall was associated with lower rates of revascularization despite higher mortality, suggesting that patients transferred to SNF were less likely to be offered repeat procedures and were likely treated more conservatively due to higher burden of comorbidities.We found that SNF use was strongly associated with an increased all‐cause mortality and 30‐day readmissions. While it is not surprising that patients with SNF use had worse outcomes since these patients are more likely to be in worse health, have experienced postoperative complications and have had prolonged stays, this association was significant despite controlling for comorbidity burden and age. The strong association with all‐cause mortality also remained after excluding patients who died within the first 30 days (the same period when SNF use was measured). We also found that the association was strongest in the first period after revascularization and weaker in later periods, suggesting that post‐discharge SNF utilization is a particularly strong predictor of early mortality.These results add important context to the tradeoffs that exist when selecting a revascularization strategy for elderly and frail patients. Like previous studies, we found that patients who received CABG had a slightly lower all‐cause mortalitySNF use was a stronger predictor for poor outcomes among patients who received inpatient PCI compared CABG. For this subset, CABG was associated with a decrease in mortality and the percentage of patients with readmission or mortality compared to PCI. However, the proportion of CABG patients who required SNF use was much higher. Additionally, PCI inpatients with SNF use also had a higher comorbidity burden and were older than CABG patients with SNF use. These results suggest that the small subset of patients who received PCI and required SNF use were a group that was at especially high risk for poor outcomes. This is particularly important given recent findings of randomized clinical trials demonstrating the effectiveness of medical therapy alone as an initial treatment strategy for patients with stable coronary artery disease.These findings also have important implications with respect to treatment selection for revascularization patients who are elderly and frail who remain candidates for invasive evaluation. First, the findings support the concerns about the risk of CABG use in this frail and elderly population. CABG patients were much more likely to require SNF use despite being younger and having a lower average comorbidity burden. The results suggest greater caution may be warranted when selecting treatment for patients at high risk for SNF use. Second, the results suggest that there is selection in favor of PCI among patients with extreme frailty and more advanced age at baseline. Inpatient PCI patients were older, had a higher comorbidity burden, and had a worse prognosis conditional on having SNF use. This selection of patients with extreme frailty to receive inpatient PCI may be reasonable since PCI is a minimally invasive procedure whereas CABG is an invasive surgery that was associated with a greater risk of post‐revascularization SNF use. However, the poor outcomes among the subset of inpatients with PCI and SNF use may reflect a need for greater consideration for whether patients with extreme frailty are good candidates for revascularization. Additionally, such selection presents a challenge for observational research that compares outcomes between PCI and CABG. The patients who receive inpatient PCI may be more frail in unobservable ways and have a worse prognosis prior to revascularization. This issue may partially explain the survival advantage for CABG compared to PCI that was found in this study and in prior observational research.The strengths of this cohort include the large sample size and that it is nationally representative of elderly Medicare fee‐for‐service beneficiaries. The study also has several limitations. First, we excluded Medicare Advantage beneficiaries and our results may not generalize to these patients. Second, as an observational study, the associations between receipt of CABG or inpatient PCI and outcomes should not be interpreted as causal. A randomized controlled trial would be necessary to evaluate the comparative effectiveness of inpatient PCI and CABG in this population. Third, SNF use is an indicator associated with functional status, postoperative complications, and prolong stays that occurs after revascularization and did not cause the observed associations with outcomes. Fourth, while we were able to control for comorbidity burden and admission diagnoses, we were unable to control for clinical fa//ctors that are not available in claims data such as severity of CAD or anatomic variants.In summary, among a large cohort of elderly and frail Medicare fee‐for‐service beneficiaries receiving revascularization, we found that CABG was associated with a lower rate of death and repeat revascularization, but a higher risk of readmissions. We also found that SNF use was more likely among CABG patients and that SNF use was associated with poor outcomes, particularly among patients receiving inpatient PCI. These observations highlight the important limitations in conducting observational research in the comparative effectiveness of CABG compared to inpatient PCI. The results suggest that caution is needed in treatment selection for patients at high‐risk for SNF use and that selection of inpatient PCI over CABG may be associated with greater frailty and a worse overall prognosis.None.Figure S1 XXXClick here for additional data file.