Racism is increasingly recognised as a significant health determinant that contributes to health inequalities. In Australia efforts have been made to bridge the recognised health gap between Aboriginal and Torres Strait Islander people and other Australians. This systematic scoping review aimed to assess, synthesise, and analyse the evidence in Australia about the impacts of racism on the mental and physical health of Aboriginal and Torrens Strait Islander peoples.A systematic search was conducted to locate Australian studies in English published between 2000 and 2020. Five electronic databases were used: PubMed, CINAHL, Embase, Web of Science and the Australia’s National Institute for Aboriginal and Torres Strait Islander Health Research. The search strategy included a combination of key words related with racism, mental health, physical health and Indigenous people. Data were extracted based on review questions and findings were synthesized in a narrative summary.Of total 338 searched studies from five databases, 12 studies met the inclusion criteria for narrative synthesis where eight were cross-sectional studies and four prospective cohorts. General mental health and general health perception were the most frequently studied outcomes followed by child behaviour, smoking and substance consumption and specific health conditions. The prevalence of racism varied between 6.9 and 97%. The most common health outcomes associated with racism were general poor mental health and poor general health perception. More specific health outcomes such as anxiety, depression, child behaviour, asthma, increased BMI and smoking were also associated with racism but were analysed by a limited number of studies. Three studies analysed psychological distress, negative mental health, sleeping difficulties and negative perceived mental health according to severity of exposition to racism.Racism is associated with negative overall mental and negative general health outcomes among Aboriginal and Torres Strait Islander peoples. Strategies to prevent all forms and sources of racism are necessary to move forward to bridging the health gap between Aboriginal and Torres Strait Islander peoples and non-Indigenous Australians. Further research is needed to understand in more detail the impact of racism from an Aboriginal and Torres Strait Islander definition of health and wellbeing.The online version contains supplementary material available at 10.1186/s12889-021-11363-x. Racism has been defined as the manifestation of racist beliefs, emotions, behaviours, and practices that perpetuate and aggravate disparity of opportunity of an ethnoracial group . Racism Australia is inhabited by two different groups of Indigenous peoples: Aboriginal and Torres Strait Islanders. Each has its own distinctive and established values, cultural protocols, and unique living manner . The terIn Australia, the “Indigenous health” panorama is well known for the existence of what is called by the government and public health sector as “The gap.” It refers to the wide health disadvantage that Aboriginal and Torres Strait Islander peoples have in comparison to the rest of Australians. The Australian Institute of Health and Welfare estimated that Aboriginal and Torres Strait Islander people born between 2015and 2017 had 8.6 and 7.8 fewer years of life expectancy than other male and female Australians, respectively . In the Nationally and internationally, academics have argued that failure of efforts to bridge health inequalities has been due to interventions focusing primarily on behaviour change at individual and interpersonal levels despite the solid evidence recognising the relationship of structural determinants of health such as racism and health disparities –34. The ).The protocol for this scoping review was previously completed and published . The rep1This review followed the stages proposed on the methodological framework for scoping reviews by Arksey and O’Malley  and lateThe aim of this study is to understand and analyse the impacts of racism on the health of Aboriginal and Torres Strait Islander people living in Australia.A systematic search was conducted between between the 01st of January of 2000 and June 2020 using the following databases: the Australia’s National Institute for Aboriginal and Torres Strait Islander Health Research, CINAHL, PubMed, Embase and Web of Science. This timeframe was decided based on findings evidencing that no primary studies are lost when performing searches that include studies from the last 20 years . We UsedAll the search results were exported to the citation manager EndNote X9  and dupli.Studies in English conducted among Aboriginal and Torres Strait Islander peoples of all ages and gender regardless of any socio-demographic characteristics.Perceived experience of racism defined as the feeling of receiving an unequal valuation or unfair treatment for being an Aboriginal or Torres Strait Islander person. The experience of racism could be self-reported or reported by a child’s carer or a witness such as family or friends. Papers analysing health outcomes with racism exposure at any point in time before the study were included.ii.Outcomes measuring physical and mental health spheres along with other health-related outcomes. Physical health outcomes included chronic conditions such as, cardiovascular disease, chronic obstructive pulmonary disease (COPD) and asthma, hypertension, diabtes, cancer and abnormal body mass index. It also included health risk behaviours . Mental health outcomes including psychological factors like depression and anxiety, psychological distress, social and emotional wellbeing, illness representations  and suicide.iii.Only studies using quantitative methods  were included.i.Articles studying autoimmune disorders, and cystic fibrosis. (This decision was based on i) The multifactorial cause of such conditions and their strong polygenetic component –47 whichii.Experimental studies  and controlled clinical trials (CCTs)).iii.Studies published in language different to English, studies found only as abstract, letters to the editor, commentaries, editorials and reviews.Primary investigator extracted the data into an excel spreadsheet. The following information was extracted when available: author, year of publication, journal, type of study (study design), location of the study (state or city), sample size, sample source, sample demographic characteristics, exposure measure including tools or instruments, exposure timeframe and severity, studied outcomes, strength and direction of the associations between racism and health outcomes along with the type of data used to quantify the association . UNY randomly selected 10% of the articles meeting eligibility criteria to double check all the data listed before. Data was compared, and any discrepancies were resolved by consensus.The data of the studies included was analysed and summarized following a descriptive synthesis process based on the recommendations of the Joanna Briggs Institute Reviewer’s Manual . QualityTwo members of this review team (authors KBB and JC) who represent Aboriginal and Torres Strait Islander people living in Australia reviewed and validated the interpretations of the data. were conducted across different locations within Australia –55, ThreAll articles studied the effect of direct racism except one study that also studied the indirect effect of racism on the child where racism was experienced by the parent or carer . Eight oFifty percent (6/12) of the articles studied mental and physical health outcomes , 58, 60,Among the mental health component, negative general mental health was the most reported outcome 10/12, 83.%) [.% 3, 51, 57–60 fRegarding the physical health component, its association with experiences of racism was mainly studied through the assessment of general health perception 7/12, 58%) , 57, 60.% , 57, 6Racism was associated with a negative overall mental health component in 100% of the studies that reported the outcome (10/10) , 57–60. Almost 43% of the papers studying general health perception found that a negative health perception is associated with racism  , 60. OneThree articles studied the association between racism and health outcomes according to the severity of the exposure , 53, 54.The quality of the 12 studies included was assessed using The Joanna Briggs Institute critical appraisal tools for cohort and cross-sectional studies , 50. ThiAboriginal and Torres Strait Islander peoples have survived and thrived over millennia and are the world’s longest continuing living civilization. Since colonisation, however, disempowerment and ongoing manifestations of racism have undermined Aboriginal and Torres Strait Islander peoples , 64, 65.For Aboriginal and Torres Strait Islander people, health is holistic and understood from a whole of life view that goes beyond the physical to encompass social, emotional, and cultural wellbeing of not just an individual but also the whole community , 69. DifCurrent scoping review results are in line with international evidence demonstrating the association of racism with poorer physical and mental health outcomes. In this review, the studies reported the association across different age groups indicating that racism produces detrimental health effects on physical and mental health outcomes of Aboriginal and Torres Strait Islander people at any stage of life. Racism had greater negative effects on the mental health component, especially with negative general mental health which was the most studied outcome , 57–60. Three out of seven articles (42.%) that studied general health perception found a statistically significant negative association with racism , 34, 60.In the present review, one study reported the association of racism with smoking and alcohol consumption . StudiesThere is an urgent need to address institutional racism as a strategy in Australia in order to improve the health and wellbeing of Aboriginal and Torres Strait Islanders , 86. WhiThe prevalence of racism varied from study to study and was as high as 97%. Aboriginal and Torres Strait Islander people aged 12–45 years represent the group with the highest racism experience. A high prevalence of racism against indigenous people has also been reported in other developed countries , 91. LooThere were five studies conducted across all of Australia , 51–55; No studies were found comparing differences of the health impact of racism between Aboriginal people and Torres Strait Islander people. Comparative research could provide more understanding of possible variations in factors such as the most prevalent type of racism by location or differences in the impact of racism on health outcomes in different Aboriginal and Torres Strait Islander communities.The quality of the included studies was assessed by two authors (CK and UNY) using the Joanna Briggs Institute tool , 50 and Strengths of the present study include i) the use of meticulous database search and following standard guidelines during the review process, ii) use of the well-developed protocol with including members from indigenous community (authors KBB and JC), iii) the inclusion of four electronic databases in our search strategy plus manual search on the websites of relevant organisations and snowball technique, iv) a quality appraisal of the included studies using a widely used tool , 50.One limitation of the studies included that nearly all of the studies measured the racism exposure within a 12-month timeframe and used a 4-week timeframe. Although asking explicit timeframes is deemed to be cognitively easier , restricContrary to Aboriginal and Torres Strait Islander people’s definition of health, the approach used in this review separated physical from behavioural and mental health outcomes and didn’t evaluate cultural or community wellbeing. This approach was taken since we understand that this method facilitates the statistical analysis and demonstration of the impacts of racism on measurable and objective outcomes. Our research team included two members who are representatives of Aboriginal and Torres Strait Islander communities and with extensive expertise in this research field. However, this limitation highlights the need to include Indigenous methodologies in further studies to ensure that the methods and data analysis better represent Aboriginal and Torres Strait Islander people’s health conception –103. MorOur study findings indicate that racism is strongly related to adverse effects on the mental health wellbeing. Furthermore, it was found that racism is also negatively associated with general health self-perception whilst its direct association with more specific physical health conditions might be underestimated due to lack of studies. Based on our findings, we suggest the need for the implementation of strategies to address all forms of racism against Aboriginal and Torres Strait Islander peoples as part of the efforts to bridge the health inequity in Australia. Hence, we believe that public health practitioners and policymakers could use our findings as guiding evidence to address racism in partnership with Aboriginal and Torres Strait Islander communities without any delay. We also argue the need for effective implementation of strategies against racism. More research is needed that understands racism and its impacts from an Aboriginal and Torres Strait Islander definition of health and wellbeing. Furthermore, research using longitudinal designs to study the impacts of racism on health outcomes and studies comparing outcomes among states and territories and studies comparing outcomes among states and territories is needed. Aboriginal and Torres Strait Islander-led research studies would also guide self-determined and culturally safe, tailored, and effective interventions for Aboriginal and Torres Strait Islander people.Additional file 1. PRISMA extension for Scoping Reviews (PRISMA-SCR) checklist.


Blueberry is a crop that is increasing globally, both in terms of yield and extent, mostly thanks to the recent introduction of North American blueberry in the temperate areas of Europe, Asia, and South America. As blueberry depends largely on insects for pollination, farmers in these expansion areas face the challenge of adapting this crop to unexpected pollinator species, whose traits and features may not entirely fit the pollination needs of the introduced crop. Here we study the abundance, the behaviour, and the response to environmental conditions of different managed and wild native pollinators of blueberry in northern Spain. Our findings suggest the dominant role of native wild bumblebees and managed honeybee as suppliers of pollination service. Honeybee and bumblebees differed in both when and where they occurred, in how they responded to environmental conditions, and in how they behaved as an effective pollinator. The role of bumblebees and honeybee as blueberry pollinators thus seems complementary and additive. These results encourage the preservation of populations of native wild bees in order to ensure the effective management of introduced blueberry crops.Vaccinium ashei) can be expanded into new territories  far from their original area of domestication (North America). Insect visits to blueberry flowers were monitored in a plantation on 12 different days, at 8 different times during day and covering various weather conditions. Abundance, visitation rate, pollen gathering behaviour, and frequency of inter-plant and inter-row movements were recorded. The pollinator assemblage was basically composed of one managed honeybee species (50.8% of visits) and three native bumblebee species (48.3%). There was a marked pattern of seasonal segregation throughout bloom, with bumblebees dominating the early bloom and honeybee the late bloom. Pollinators also segregated along gradients of daily temperature and relative humidity. Finally, the two pollinator types differed in foraging behaviour, with bumblebees having a visitation rate double that of honeybee, collecting pollen more frequently and changing plant and row more frequently. The spatio-temporal and functional complementarity between honeybee and bumblebees suggested here encourages the consideration of an integrated crop pollination strategy for blueberries, based on the concurrence of both wild and managed bees.The entomophilous pollination niche  helps to understand and better manage crop pollination. We apply this niche approach to assess how an entomophilous crop (blueberry,  The production of many crop plants around the world depends greatly on pollination by insects, including both managed  and wild  species ,2,3. OneVaccinium spp. Ericaceae) as a crop has shown a marked increase in global yield, as well as a strong expansion worldwide )This study evidences that American blueberry crops introduced into northern Spain show traits that facilitate high enough levels of flower visitation by insects that yields comparable to those found in the native area can be achieved (e.g., . FarmersWhether farmers in northern Spain might decline to set up honeybee hives and rely exclusively on wild pollinators for blueberry pollination requires further analysis (see also . Nonethe


The Central American brocket deer is a vulnerable species. Geographically isolated populations have been affected by poaching and habitat fragmentation, leading to local extinctions. It is therefore important to understand this species’ habitat characteristics, particularly of resting sites, which play a crucial role in survival and fitness. We describe the characteristics and distribution patterns of Central American brocket deer resting sites at the microhabitat and landscape scales in San Bartolo Tutotepec, Hidalgo, México. We conducted eight bimonthly field surveys between November 2017 and March 2019, consisting of 32 transects of 500 m length to search for fecal pellets, footprints, scrapes, and browsed plants. At each resting site we identified, we measured canopy closure, horizontal thermal cover, protection from predators for fawns and adults, escape routes, slope from the ground, presence of scrapes, cumulative importance value of the edible plant species, and distance from the resting site to the nearest water resource to characterize the site at the microhabitat scale. At the landscape scale, we identified the type of biotope, elevation, aspect, and slope. We compared all of these parameters from resting sites with a paired randomly selected site to serve as a control. We performed a multiple logistic regression to identify the parameters associated with the resting sites and a point pattern analysis to describe their distribution. We characterized 43 resting sites and their corresponding control plots. At the microhabitat scale, resting sites were associated with higher vertical thermal cover, more concealment cover, more escape routes, more edible plant species, higher slope from the ground, and closer distance to water resources. At the landscape scale, resting sites were associated with beech forest, oak forest, secondary forest, and ravine biotopes and negatively associated with pine forest, houses, and roads. Resting sites had an aggregated spatial pattern from 0 to 900 m, but their distribution was completely random at larger scales. Our study revealed that Central American brocket deer selected places with specific characteristics to rest, at both microhabitat and landscape scales. We therefore suggest that existing habitat be increased by reforesting with native species—particularly Mexican beech forest and oak forest—to improve the deer’s conservation status in the study area. The Central American brocket deer is a vulnerable species, with geographically isolated populations mainly found in mountain cloud forests and evergreen forests . The speResting sites have important effects on survival and fitness; they provide adults and offspring with protection from predators, thermal cover, comfort, and access to food and water resources .Puma concolor), an essential part of the diet of jaguar (Panthera onca) and an occasional prey of tayras  also attack and kill Central American brocket deer . For instance, some large herbivores that inhabit this ecosystem locate their resting sites near to some ponds that contained water all year for cooling off during the hottest hours of the day , gray fox (Urocyon cinereoargenteus), jaguarundi (Puma yagouaroundi), ocelot , margay (Leopardus wiedii), American hog-nosed skunk (Conepatus leuconotus), hooded skunk (Mephitis macroura), long-tailed weasel (Mustela frenata), ringtails (Bassariscus astutus), white-nosed coati (Nasua narica), kinkajou (Potos flavus), raccoon (Procyon lotor), nine-banded armadillo (Dasypus novemcinctus), Eastern cottontails (Sylvilagus floridanus), lowland paca (Cuniculus paca) and Mexican red-bellied squirrel (Sciurus aureogaster) among others (Puma concolor), had been extirpated from the area, but recent observations confirm its presence .The study was carried out in the mountain cloud forest of San Bartolo Tutotepec, which spans over 6070.1 ha in eastern Hidalgo, Mexico . Each transect was 500 m long and were distributed uniformly within the part of the study area that is suitable for brocket deer, according to ng sites .We identified resting sites based on the presence of fecal pellets following 2 surrounding the resting site) and the landscape (the 30 m2 surrounding the resting site).To describe the resting site, we assessed habitat characteristics at two different spatial scales: the microhabitat  between 9:00 am and 12:00 pm using a densiometer to estimate vertical thermal cover  and third segments (100–150 cm) as protection from predators for adults , which we considered the potential escape routes from predators.We measured concealment cover following r adults . We alsocomfort signs, we measured the slope from the ground by using a clinometer (SUUNTO), and we registered the presence/absence of scrapes and the tree and/or tree fern species under which the site was located to determine whether there was a preference for a particular species of tree/tree fern for resting sites.As cumulative importance value of the edible plant species with the following formulas:To evaluate food availability, we identified the plant species along the transect and compared to the to the lists of plant species consumed by deer compiled by access to water, we measured the linear distance from the resting site to the nearest water source , using a measuring tape . Elevation was derived directly from a digital elevation model (DEM), and aspect and slope that were calculated with the Surface toolbox in Arc Map 10.3 from the DEM. Erdas Imagine software v.14.0 was used to reproject the Landsat and DEM images and to perform atmospheric and radiometric corrections (Intergraph Corporation). Pixel size for both images was 30 m2.Since we hypothesized that the habitat preferences of the Central American brocket deer influenced the selection of its resting sites, we used four landscape-scale variables to describe resting sites. For each resting site surveyed, we established a paired control plot where we measured the same microhabitat and landscape attributes. Control plots were selected by measuring at the point 50 m from the identified resting site in a randomly selected cardinal direction.s ≥ —0.7—). Then, multiple logistic regressions were used to differentiate combinations of variables associated with the resting sites. We chose this analysis because multiple logistic regressions are especially useful when the data consist of both discrete and continuous variables  defined by λ (u). Finally, we performed first-order characteristics analysis of a spatial process for a general location , then used the Kernel-smoothed intensity to measure the mean number of occurrences per unit at a point \doce  is an edge correction weight and λ(u).where We found and characterized 43 resting sites and their corresponding control plots. It is important to note that this is the first time that latrine formation is reported for Central American brocket deer. At the microhabitat scale, we observed that the probability of being a resting site in the area was positively associated with vertical thermal cover, concealment cover, the number of escape routes and the presence of edible plant species and negatively associated with the distance to water resources. Resting sites were found on flat and nearly flat surfaces, and scrapes were only recorded at resting sites .At the landscape scale, we observed that the probability of being a resting site was positively associated with beech forest, oak forest, secondary forest and ravine biotopes and negatively associated with pine forest, houses and roads and grazing area biotopes .The highest density of resting sites occurred in two “hotspots” located at the center of the study area . K and LOur results support the idea that resting sites are important places for Central American brocket deer, since they provide adults and offspring with thermal cover, protection from predators, comfort, and access to food and water resources. Central American brocket deer selected resting site locations with high canopy closure, probably seeking protection from extreme heat and radiation during solar noon and from the rain and excess moisture in the extremely rainy environment of the mountain cloud forest .Puma concolor, and of free-ranging and feral dogs that can also act as predators  to rest, and the presence of scrapes by pawing the soil were common. This was despite the fact that resting sites were located in areas where the overall terrain was steep; this suggests that they chose locally flat sites to avoid sliding off of the resting site, which could be interpreted as a comfort sign . It has M. temama in the Huasteca region of San Luis Potosí, Mexico. Despite the availability of different biotopes, a relatively high percentage of resting sites were found in Mexican beech forest habitats. Remnants of Mexican beech forest are considered hotspots with high connectivity and low disturbance in our study area (Puma cursivas) or dogs. Other mammals, such as the common genet (Genetta genetta) in the Mediterranean, have been shown to use ravines similarly as safe passages and resting site locations . In our study area, there are only a few forest patches that meet Central American brocket deer resting site requirements; most of the habitat is unsuitable for this behavior due to disturbance, including intense agricultural and livestock activity. This scenario has been observed in most of the studies of this species, and Central American brocket deer habitat is frequently highly fragmented. Therefore, we recommend increasing the existing habitat by reforesting with native species, especially in Mexican beech forest and oak forest, to improve the species’ conservation status in the area.10.7717/peerj.12587/supp-1Supplemental Information 1e.g., canopy coverage, slope orientation, herbaceous cover).Characteristics of the resting sites (Click here for additional data file.


Diabetes and cognitive dysfunction, ranging from mild cognitive impairment to dementia, often coexist in individuals over 65 years of age. Vascular contributions to cognitive impairment/dementia (VCID) are the second leading cause of dementias under the umbrella of Alzheimer’s disease and related dementias (ADRD). Over half of dementia patients have VCID either as a single pathology or a mixed dementia with AD. While the prevalence of type 2 diabetes in individuals with dementia can be as high as 39% and diabetes increases the risk of cerebrovascular disease and stroke, VCID remains to be one of the less understood and less studied complications of diabetes. We have identified cerebrovascular dysfunction and compromised endothelial integrity leading to decreased cerebral blood flow and iron deposition into the brain, respectively, as targets for intervention for the prevention of VCID in diabetes. This review will focus on targeted therapies that improve endothelial function or remove iron without systemic effects, such as agents delivered intranasally, that may result in actionable and disease-modifying novel treatments in the high-risk diabetic population. The global incidence of diabetes has more than tripled in the last 20 years  and post stroke cognitive impairment (PSCI), which collectively contribute to the VCID spectrum . OngoingRegulation of cerebrovascular integrity and function is key in proper cerebral perfusion and neuronal function . In thisFrom a clinical perspective, increased hemoglobinA1C is associated with decreased CBF due to vasogenic edema and reduction in cerebral autoregulation . MicrovaFrom a preclinical perspective, experimental models of VCID and metabolic disease have lower CBF, greater white matter damage, reduced oligodendrocytes progenitor cells, impaired spatial memory, and reduced cue fear memory along with neurodegeneration . It has Collectively, it is evident from both clinical and experimental studies that diabetes-mediated microvascular dysfunction plays a critical role in the development and progression of VCID by promoting BBB disruption, exacerbating neurovascular damage after ischemic injury and impairing vasotrophic coupling necessary for the repair processes. Innovative approaches to improve cerebral microvascular function, endothelial integrity, and trophic coupling within the NVU hold great potential to develop preventive and therapeutic strategies for diabetes-associated cognitive dysfunction. Thus, after a brief summary of IN drug delivery, we will review the potential IN use of insulin, iron chelator deferoxamine (DFX), phosphodiesterase-3 (PDE3) inhibitor cilostazol, endothelin (ET) receptor antagonists, and brain derived neurotrophic factor (BDNF) for improvement of microvascular function and vasoneuronal health in diabetes.IN drug delivery is an emerging field in neurodegenerative diseases. Currently, potential treatments for ADRD, including VCID, are limited by the physiological and anatomical characteristics of the central nervous system CNS; . IN deliin situ hydrogels, and nanosystems  internalization of the molecule by an olfactory neuron, (2) endocytic vesicular trafficking to the neuron’s projection site, and (3) release by exocytosis  in muscle and adipose tissue, greater glycogen synthesis in liver and muscle, enhanced protein synthesis, and decreased lipolysis. Identification of insulin and its receptors in the brain around 1980s  promotes its well-studied metabolic effects such as increased glucose uptake/utilization nd 1980s ,b and thnd 1980s . The widnd 1980s .via a saturable transendothelial process by binding to insulin receptors on endothelial cells that form the BBB and then is released at the basal membrane  receptors and divalent metal transporter-1 (DMT-1) on BMVECs and to a lesser extent in epithelial cells of the choroid plexus . Once inWhile the exact mechanisms of iron contribuion to neurovascular pathologies are not fully understood, compounding evidence points to ferroptosis, an iron dependent form of cell death . In the Well documented evidence for iron accumulation in the brain in neurodegenerative diseases led to preclinical and clinical investigations with iron chelators. DFX, an FDA-approved iron chelator routinely used in iron overload cases, is the most commonly tested iron chelator in these studies . While ivia multiple mechanisms.Cyclic adenosine monophosphate  and guanosine monophosphate  are important second messengers in signaling cascades that regulate many biological processes. cAMP generated by adenylate cyclase activates protein kinase A (PKA). cGMP generated by soluble guanylyl cyclase upon activation by nitric oxide (NO) activates PKG. Both cAMP and cGMP are rapidly hydrolyzed by various members of the phosphodiesterase (PDE) family of enzymes, most of which are expressed in the brain . PDE3 caIndeed, the potential role of PDE inhibitors for the treatment of AD has been investigated in various preclinical and clinical studies . For thevia upregulation of endothelial nitric oxide synthase (eNOS) phosphorylation and vascular endothelial growth factor (VEGF) expression  of arteries and arterioles as well as on pericytes surrounding capillaries, is responsible for the contractile and proliferative responses to ET-1  improve ischemic stroke outcomes and cognitive impairment, there are also conflicting reports with selective ETB agonism preventing the development of cognitive impairment  mediated signaling. Whereas its precursor protein, proBDNF, and p75NTR signaling have been linked to neuronal apoptosis , VA Senior Research Career Scientist Award (IK6 BX004471), NIH RF1 NS083559 (formerly R01 NS083559) and R01 NS104573  to AE; NRSA Individual Postdoctoral Fellowship to VW (F32 HL158011-01) and a South Carolina Clinical & Translational Research (SCTR) Institute (UL1TR001460) discovery grant (SCTR2201) to YA.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Mobile health  platforms have become increasingly popular for delivering health interventions in recent years and particularly in light of the COVID-19 pandemic. Childhood obesity treatment is an area where mHealth interventions may be useful due to the multidisciplinary nature of interventions and the need for long-term care. Many mHealth apps targeting youth exist but the evidence base underpinning the methods for assessing technical usability, user engagement and user satisfaction of such apps with target end-users or among clinical populations is unclear, including for those aimed at paediatric overweight and obesity management. This review aims to examine the current literature and provide an overview of the scientific methods employed to test usability and engagement with mHealth apps in children and adolescents with obesity. A narrative literature review was undertaken following a systematic search. Four academic databases were searched. Inclusion criteria were studies describing the usability of mHealth interventions for childhood obesity treatment. Following the application of inclusion and exclusion criteria, fifty-nine articles were included for full-text review, and seven studies met the criteria for usability and engagement in a clinical paediatric population with obesity. Six apps were tested for usability and one for engagement in childhood obesity treatment. Sample sizes ranged from 6–1120 participants. The included studies reported several heterogenous measurement instruments, data collection approaches, and outcomes. Recommendations for future research include the standardization and validation of instruments to measure usability and engagement within mHealth studies in this population.  The scale and complexity of treating child and adolescent obesity place substantial demands on healthcare resources. Delivery of best-practice multidisciplinary, family-based treatment programmes requires extensive networks of adequately trained healthcare professionals, administration, appropriate clinical treatment spaces, and time . Direct the cost-effective and secure use of information and communications technologies in support of health and health-related field, including health care services, health surveillance, health literature, and health education, knowledge and research” [n = 3) that formally reported usability assessments of the mHealth intervention [Technology has enabled significant advancements in healthcare and digital health has been relied on during the ongoing COVID-19 pandemic . Digitalesearch” . Mobile esearch” . Alternaesearch” . Despiteesearch” . Currentesearch” . Due to esearch” . Additioesearch” . Accordiesearch”  and 95,7esearch” . Even thrvention .The complexity of obesity with its mixed aetiology and multiple associated comorbidities complicates the designing and testing of treatment interventions, particularly in deciding which outcome criteria will determine the success of the intervention . The NatDiet and PA are multifaceted behaviours, affected by many psychological, social, and environmental influences . SpecifiConsiderable testing of apps by end-users is required to reveal the best methods and design of the app for particular clinical groups  and enabUsability is the degree to which a product can achieve specific tasks efficiently, effectively and satisfactorily by identified users and in an established setting . The folGiven the requirement for mHealth solutions for paediatric obesity treatments and the fast-emerging field of mHealth interventions in this population, there is a need for usability and engagement measurement tools for use in research and practice. We aimed to summarise the published literature describing studies that assessed usability and/or engagement of mHealth interventions for childhood obesity treatment and their findings.A narrative literature review was conducted, after implementing a systematic search  in orderA formalised search of four electronic databases including the Cochrane Library, Web of Science, Scopus, and PubMed was undertaken on 12 August 2021. Literature published from 2009 onwards (up to August 2021) was included as smartphones were first brought to mainstream market with the introduction of the Apple iPhone in 2007 followed by Android models including Samsung and High Tech Computer Corporation (HTC) in 2008  and it iKey search terms developed from PCC outlined in Written in English,Involving children and/or adolescents with overweight or obesity (as defined by the study authors),Under the age of 18 years,Focussed on usability and engagement testing of mHealth applications.Interventions involving participants older than 18 years or those based on text messages or other digital health platforms apart from mHealth apps were excluded.The primary outcome of interest was measures of overall usability and engagement as reported by original studies. Given the limited and novel research for mHealth usability, no restrictions on methods of measurement were applied. Secondary outcomes of interest included technical usability and user satisfaction.n = 1) or both diet and PA (n = 6). The apps included functions for self-monitoring (n = 7), tips and advice (n = 5), social support (n = 3), goal setting (n = 2), and rewards (n = 1) as depicted in n = 6) and engagement (n = 2). One study (n = 1) used quantitative methods only and measured engagement alone, not usability.As illustrated in n = 7) that tested usability and engagement with apps aimed at children/adolescents with overweight/obesity specifically, including the directly relevant study characteristics.SUS ideal format” to compare usability scores for two different versions of the same app [Usability was measured across studies using various usability definitions and methods. One article stated that usability is not fixed as it is only relevant to the specific context in which it is applied . Anothersame app . Anothersame app . The majsame app ,32,50,51same app . It alsosame app .n = 7), a mixed-methods approach provided more contextual findings compared to quantitative alone. This includes focus groups and interviews for qualitative data, and questionnaires and engagement metrics derived from the technology itself for quantitative data. Descriptive statistics were the main method reported for analysing quantitative data and thematic analysis for qualitative data. Future research needs to standardise and validate usability tools with this population. There is also the need for consensus on clear definitions around aspects of usability, for which work is ongoing [This study aimed to provide a summary of usability and engagement testing methods of mHealth interventions for childhood obesity treatment. Ideally, to evaluate usability completely, the relationship between users, devices, and tasks in a defined setting needs to be measured . Our fin ongoing . A syste ongoing . This exAlthough there were limited search results specific to paediatric overweight and obesity, the broader search identified further methods of testing usability and engagement of mHealth interventions for other paediatric health conditions including concussion  and mildQuestionnaires were used in many studies to measure usability, user engagement and satisfaction amongst young people with mHealth apps in the studies identified. Although a major challenge mentioned across the literature is that traditional usability evaluation methods such as surveys and qualitative approaches, are aimed at adults and need to be adapted to account for developmental differences in children and adolescents in addition to privacy and ethical considerations . The UseAlthough some evidence exists for the effectiveness of eHealth interventions in treating paediatric overweight and obesity, knowledge gaps still remain for determining the most suitable and efficacious intervention features, long-term effects, and sustainability . MoreoveIt is worth noting findings in the literature that investigated the potential benefits and drawbacks of incorporating a combined approach of mHealth and usual care. A recent study evaluated the usage and user experiences of an mHealth support system for paediatric obesity treatment, which was provided alongside standardised care and compared this to standardised care alone . The resAdditionally, data protection and privacy policies are major considerations when balancing the relevant potential benefits of using mHealth interventions, especially in this vulnerable group and crucially because such protocols vary extensively worldwide . FurtherLimitations of usability testing in original studies with young people include response bias with questionnaires and social acceptability bias when survey facilitators are present . HoweverAs this is a narrative literature review, findings are limited and the quality of the included studies has not been evaluated with a quality assessment tool. Conducting a systematic review on this topic following the PRISMA guidelines and assessing the quality of the included studies using an approved quality assessment tool is recommended to further inform the evidence base and those interested in this field, as usability methods and technologies rapidly develop.mHealth technology could present a nascent therapeutic option for childhood obesity and the development of mobile apps for paediatric health is increasing. It is difficult to ascertain the direct effect of mHealth technologies on clinical outcome measures for paediatric obesity, including BMI and changes in PA, sedentary activity and eating behaviours, as many studies involved other interventions in addition to mHealth apps.From the literature search, only six apps aimed at targeting childhood obesity were tested for their usability and one for engagement levels alone; six focussed on diet and all seven incorporated PA functions. In order to advance mHealth apps to a level that they can be used effectively and more extensively for paediatric obesity, further research needs to be channelled into identifying the best practice for technical usability testing and developing evidence-based and expert-led interventions for youth populations.


To establish an enterprise initiative for improving health and health care through interoperable electronic health record (EHR) innovations.We developed a unifying mission and vision, established multidisciplinary governance, and formulated a strategic plan. Key elements of our strategy include establishing a world-class team; creating shared infrastructure to support individual innovations; developing and implementing innovations with high anticipated impact and a clear path to adoption; incorporating best practices such as the use of Fast Healthcare Interoperability Resources (FHIR) and related interoperability standards; and maximizing synergies across research and operations and with partner organizations.University of Utah Health launched the ReImagine EHR initiative in 2016. Supportive infrastructure developed by the initiative include various FHIR-related tooling and a systematic evaluation framework. More than 10 EHR-integrated digital innovations have been implemented to support preventive care, shared decision-making, chronic disease management, and acute clinical care. Initial evaluations of these innovations have demonstrated positive impact on user satisfaction, provider efficiency, and compliance with evidence-based guidelines. Return on investment has included improvements in care; over $35 million in external grant funding; commercial opportunities; and increased ability to adapt to a changing healthcare landscape.Key lessons learned include the value of investing in digital innovation initiatives leveraging FHIR; the importance of supportive infrastructure for accelerating innovation; and the critical role of user-centered design, implementation science, and evaluation.EHR-integrated digital innovation initiatives can be key assets for enhancing the EHR user experience, improving patient care, and reducing provider burnout. Just asSMART on FHIR innovations can help meet clinician needs inadequately supported by the native EHR. Such needs can include support for high-level clinical reasoning, communicating and coordinating care, and complying with rules and regulations.,,SMART on FHIR adoption is increasing, with use in over 500 hospitalsKnowledge sharing and coordination could enable more rapid progress in the adoption and impact of FHIR-based digital health innovations. However, beyond descriptions of individual innovations, there is a lack of literature on the larger initiatives producing these innovations and the lessons learned. To address this gap in the literature, we describe here the UUH ReImagine EHR initiative. UUH was an early innovator in the development, implementation, and evaluation of digital innovations leveraging SMART on FHIR and related interoperability standards. By describing the initiative and lessons learned, we hope to catalyze a more rapid transformation of health care through this promising approach to digital medicine.® EHR system-wide since 2014.UUH is an academic health system with 5 hospitals and 12 community clinic centers. UUH has used the EpicPresented as a case study, we describe an enterprise initiative for EHR optimization at an academic health system leveraging SMART on FHIR and related interoperability standards. Key lessons learned are highlighted in the discussion. All human subjects research was approved by the Institutional Review Board (IRB).In the methods, we describe our motivation, facilitators, mission, vision, governance, structure, strategy, projects phases, and funding. In the results, we describe the developed infrastructure, individual innovations, and return on investment. In the discussion, we describe lessons learned.®.The primary motivation for launching ReImagine EHR was growing recognition that traditional EHR optimization methods were insufficient for fully meeting patient and provider needs. We also sought to better coordinate emerging efforts spanning both research and operations to maximize synergies. For example, research innovations must be translated into clinical practice to impact care. Similarly, difficult operational challenges can be addressed through research. We also aimed to increase our technical capacity to adapt to a rapidly changing healthcare landscape. Facilitators included the local availability of relevant experts as well as the increasing adoption of underlying standards by EHR systems including EpicThe mission of ReImagine EHR is to improve patient care and the provider experience. The focus is EHR-integrated digital innovations capable of widespread dissemination across diverse health systems and EHR platforms. ReImagine EHR is a multi-stakeholder collaborative effort. The steering committee is co-chaired by the CMIO and CIO, and includes the Associate CMIO, the chair of the Department of Biomedical Informatics, the Director of Clinical Information Systems, the Director of Nursing Informatics, and the Chief Technology Officer. Key stakeholders are regularly consulted. ReImagine EHR is directed by the Associate CMIO.The ReImagine EHR team includes 10 core members reporting to the director; other members contributing to many or most projects; and project-specific collaborators. The team includes clinical informaticists, physician leaders, cognitive psychologists, evaluation experts, and operational information technology leaders.Core elements of the ReImagine EHR strategy include (1) establishing a world-class team; (2) creating supportive infrastructure; (3) focusing on the most impactful, sustainable, desirable, and feasible projects; (4) following best practices; and (5) maximizing synergies. Projects typically consist of 5 iterative and overlapping phases: Exploration; Design; Development; Implementation; and Sustainment and Dissemination. These phases are aligned with the Exploration, Preparation, Implementation, and Sustainment (EPIS) implementation science framework,Exploration consists of inception, prioritization, and resourcing. The ReImagine EHR Steering Committee prioritizes projects and allocates operational resources based on the principles outlined in Design involves proposing a technology-facilitated solution to address user needs. ReImagine EHR uses an iterative, user-centered design process. Functional requirements are defined early based on an understanding of the nature of the clinical problem to be addressed. Both formal methods  and informal methods  may be used to assess user needs.Development is conducted using the agile software development model. A typical “sprint” to develop additional functionality lasts 2 weeks, and all software updates undergo comprehensive testing prior to clinical deployment. Interoperability standards used include the Health Level Seven International (HL7) SMART standard for integrating the user interface, the HL7 US Core FHIR standard for data integration,Implementation involves operational use, refinement, and evaluation at initial clinical implementation sites. Typically, the application is first rolled out to pilot users to identify and address any major issues. A wider rollout then follows, with the system monitored and maintained to ensure proper functioning and updates being implemented as needed. The use, usability, efficiency, effectiveness, and impact of the system are formally or informally evaluated.The Sustainment and Dissemination phase involves providing long-term support for innovations and extending reach and impact beyond the initial healthcare system. Most ReImagine EHR innovations are designed and developed with a goal of such dissemination. Dissemination may be conducted through EHR app stores or via institutional partnerships.ReImagine EHR is supported by both our health system and external funding. There are significant synergies between operations and research: innovations can be initially motivated by scientific questions and funded through research grants, then later evolve to support clinical operations. Likewise, innovations can be initially developed for clinical operations then lead to research projects, for example to further enhance a tool or to evaluate it through a multi-site trial. Regardless of the initial funding source, individual innovations must demonstrate sufficient clinical value to justify long-term operational support and maintenance. For projects supported by external funding, it is important to demonstrate clinical value during the project period if ongoing operational support is desired.ReImagine EHR was launched at UUH in January 2016. Below we describe enabling infrastructure developed through the initiative, 5 representative innovations, and return on investment to date.We have encountered and resolved several challenges, many of which are technical in nature. This supportive infrastructure has been iteratively developed to address challenges encountered in the pursuit of individual innovations, including those described in the section “Representative Innovations.” Some of these challenges impact most projects, including the need for value set specification, the need for EHR data mapping, and the need for rigorous testing and evaluation. Other challenges affect only a subset of projects, such as native EHR FHIR APIs lacking support for desired interfaces or transmitting unnecessary data to third-party applications hosted outside the enterprise firewall.ReImagine EHR has engaged in the design, development, and implementation of over 10 applications to date. To illustrate how patient care and the provider experience across the care continuum can be improved through such innovations, 5 representative innovations are described below in terms of the problem addressed, the solution developed, the outcomes to date, and collaborating partners.Problem: Elevated bilirubin levels in newborns can cause brain damage. While a clinical guideline is available for neonatal bilirubin management,Solution: The SMART on FHIR Bilirubin App  and enter the data into the calculator in a time-consuming and potentially error-prone process.Solution: MDCalc Connect, an EHR-integrated version of MDCalc, a leading clinical calculator platform historically available as Web and mobile apps  was used to predict the medications most likely to be effective for individual patients to reach a patient-specific hemoglobin A1c goal. The application provides these predictions as well as information on relevant side effects and associated costs  (irs (VA) .Outcomes: An AHRQ-funded clinical trial at UUH is underway.Partners: University of Michigan, Ann Arbor VA Center for Clinical Management Research, Salt Lake City VA Center for Informatics Decision Enhancement and Surveillance (IDEAS), UUH Community Physicians Group, UUH Department of Radiology.Problem: Chronic diseases affect most adults, with many adults having multiple chronic conditions such as hypertension, diabetes, and chronic lung disease.,Solution: A Disease Manager was developed to serve as a one-stop-shop in ambulatory care for chronic disease management and health maintenance. Initial modules supported include hypertension, diabetes, chronic obstructive pulmonary disease (COPD), and health maintenance , reduced time spent per task, and reduced user frustration.Partners: UUH primary care and specialist providers.Annual institutional investment in ReImagine EHR has been in the range of approximately $500 000 to $1 million, with almost all of the funds used to support the salaries of informaticists, software engineers, sociotechnical experts, and trainees. The return on this investment has included the positive impact of individual projects on patient care and the provider experience, grant funding, scientific outputs, and commercialization. To date, the initiative has helped to bring in over $35 million in external grants and contracts. Digital innovations that extend native EHR capabilities have immense potential for improving health and health care. ReImagine EHR was among the first large-scale initiatives at an academic health system to embrace this approach to digital innovation. Key aspects of ReImagine EHR include a commitment to collaboration, a focus on delivering value, investment in human capital and infrastructure, the embrace of interoperability standards such as SMART on FHIR, and a high degree of synergy achieved across research and operations. As the healthcare community increasingly embraces digital innovation enabled by interoperability standards, we believe that our experiences can help guide future progress. Key lessons learned are described below.By many metrics, ReImagine EHR has been a successful initiative: many innovative EHR add-on apps have been developed and implemented; long-term institutional funding has been sustained; substantial grant funding and corporate partnerships have been secured; and formal evaluations have demonstrated high user satisfaction and positive clinical impact.In some cases, valuable digital health innovations can be implemented across health systems using only the US Core FHIR APIsThere may be cases where APIs natively supported by the EHR are inadequate for meeting user needs. For example, for the bilirubin app, custom APIs were needed to support critical data such as the baby’s gestational age and phototherapy orders.As described in Critical to achieving wide uptake and impact is a systematic and iterative approach to user-centered design. With the help of experts in cognitive psychology, we elicit user needs, design our solutions to meet those needs and associated workflows, and make iterative enhancements based on user feedback. Key user needs that we strive to meet include (1) a clear value proposition such as time savings; (2) a coherent user and team experience spanning both the digital innovation and the native EHR; (3) a self-explanatory user interface that requires minimal training; and (4) easy access to the innovation within usual workflows. In-depth user needs analyses sometimes uncover unanticipated ways in which the tool can provide additional value, such as by supporting resident education, patient education, or shared decision-making with patients.In addition to user-centered design, adoption of innovations can be increased through implementation support. Approaches we employ include (1) user education through laminated quick reference guides, brief presentations at staff or faculty meetings, and short videos by clinical champions; (2) monitoring and encouraging adoption; (3) tailoring implementation strategies based on the results of user needs assessments; (4) soliciting user feedback through an in-app widget that captures user comments along with a snapshot of the application state; and (5) making every effort to address user feedback in a timely fashion. Another potential approach to increasing adoption is through alerts or non-interruptive reminders recommending use; while potentially effective, this approach should be used with caution due to the potential for alert fatigue.,Evaluation is critical across the project lifecycle. In our experience, however, evaluation is often under-resourced outside of grant-funded initiatives due to never-ending demands for developing new functionality. This problem is compounded by the expertise needed to conduct rigorous evaluations, including for biostatistics, economics, informatics, clinical medicine, and cognitive psychology. We are continuing to refine our roadmap and supportive tooling for conducting such evaluations. In many cases, a rigorous evaluation may require effort comparable to the development of the technology itself, such as when complex clinical decision support logic needs to be replicated for impact assessment. ReImagine EHR has taken some initial steps through the assembly of highly trained evaluation experts and the conduct of several rigorous evaluation studies. However, much more rigorous evaluations are needed to comprehensively assess impact, unintended consequences, and areas for improvement. Ideally, digital innovations should be evaluated through randomized controlled trials conducted across multiple sites and guided by implementation science frameworks.Just as an increasing use of alerts in the EHR led to alert fatigue,Effective execution of a digital innovation initiative such as ReImagine EHR requires interdisciplinary, cross-institutional, and cross-sector partnerships. As demonstrated by the representative innovations described above, successful projects often require contributions from multiple stakeholders. ReImagine EHR relies on interdisciplinary partnerships across diverse domains including clinical medicine, patient engagement, user-centered design, cognitive psychology, standards and interoperability, data science, AI, business, and software engineering. Moreover, since practice patterns and the technology infrastructure may differ significantly across health systems, it is often necessary to engage external institutional partners. Furthermore, industry partners can bring unique resources and expertise. Thus, we believe both internal and external partnerships are essential to maximize impact.The healthcare community is still in the early stages of applying FHIR-based digital innovations to improve care. There are many exciting, untapped areas for future innovation. Exciting areas for future research and development include direct patient engagement through patient-facing SMART on FHIR applications such as Apple HealthEHR-integrated digital innovation initiatives can be key enterprise assets for improving users’ experience with the EHR, enhancing patient care, and helping address provider burnout. ReImagine EHR provides a case study of how health systems can begin to seize this opportunity.This work was supported by the University of Utah, the Agency for Healthcare Research and Quality (R18HS026198 and U18HS027099), the National Cancer Institute of the National Institutes of Health (U24CA204800 and U01CA232826), the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (R18DK123372), the National Center for Advancing Translational Sciences of the National Institutes of Health (3UL1TR002538-03S4), the Office of the National Coordinator for Health Information Technology (90AX0013), the Patient Centered Outcomes Research Institute (PCS-2017C2-7613), the Centers for Medicare & Medicaid Services and the Utah Department of Health (HITECH IAPD 182700537), the Centers for Disease Control and Prevention (NU58DP006770), Hitachi, Ltd., and MD Aware, LLC.Co-author TJC is supported by a Career Development Award from VA HSR&D (CDA 16-151) and a grant from the VA QUERI National Program (PrOVE QUERI). TR and KLM were supported by the National Library of Medicine of the National Institutes of Health (T15LM007124). Some of the research reported in this publication utilized the Genetic Counseling Shared Resource at Huntsman Cancer Institute at the University of Utah and was supported by the National Cancer Institute of the National Institutes of Health (P30CA042014).The funding organizations had no role in the conceptualization, design, data collection, analysis, decision to publish, or manuscript preparation for this case study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the organizations involved.Each author made substantial contributions to (1) the conception or design of the ReImagine EHR initiative or one of the described projects ; (2) the acquisition, analysis, or interpretation of data ; (3) the creation of new software used in the work ; or (4) the drafting or substantial revision of the manuscript . All authors also approved the manuscript for submission and agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated, resolved, and documented in the literature.


An accurate assessment of potential pathologic complete response(pCR) following neoadjuvant chemoradiotherapy(NCRT) is important for the appropriate treatment of rectal cancer. However, the factors that predict the response to neoadjuvant chemoradiotherapy have not been well defined. Therefore, this study analyzed the predictive factors on the development of pCR after neoadjuvant chemoradiation for rectal cancer.  From January 2008 to January 2018, a total of 432 consecutive patients from a single institution patients who underwent a long-course neoadjuvant chemoradiotherapy were reviewed in this study. The clinicopathological features were analyzed to identify predictive factors for pathologic complete response in rectal cancer after neoadjuvant chemoradiation. The rate of pathologic complete response in rectal cancer after neoadjuvant chemoradiation was 20.8%, patients were divided into the pCR and non-pCR groups. The two groups were well balanced in terms of age, gender, body mass index, ASA score, tumor stage, tumor differentiation, tumor location, surgical procedure, chemotherapy regimen and radiation dose. The multivariate analysis revealed that a pretreatment carcinoembryonic antigen (CEA) level of ≤5 ng/mL and an interval of ≥8 weeks between the completion of chemoradiation and surgical resection were independent risk factors of an increased rate of pCR.  Pretreatment carcinoembryonic antigen (CEA) level of ≤5 ng/mL and an interval of ≥8 weeks between the completion of chemoradiation and surgical resection are predictive factors for pathologic complete response in rectal cancer after neoadjuvant chemoradiation. Using these predictive factors, we can predict the prognosis of patients and develop adaptive treatment strategies. A wait-and-see policy might be possible in highly selective cases. Neoadjuvant chemoradiotherapy (NCRT) and total mesorectal excision (TME) have been shown to significantly decrease the local recurrence rate and improve the overall survival (OS) rate , which have become the standard of care for patients with clinical stages II and III rectal cancer . Neoadjuvant chemoradiotherapy also can increases the rate of sphincter preservation . Most patients respond to neoadjuvant chemoradiotherapy. After neoadjuvant chemoradiotherapy, about 10%-30% of the patients get complete pathological response, and there is no viable tumor cells in the surgical specimens . However, some patients did not respond to neoadjuvant chemoradiotherapy. Recent studies have shown that the prognosis of rectal cancer patients with pathological complete response after neoadjuvant chemoradiotherapy is better than that without pathological complete response . A wait-and-see policy might be a consideration in rectal cancer patients treated with neoadjuvant chemoradiotherapy and who have already clinical complete responded to treatment .Patients with ypT0N0 rectal cancer are a subgroup that responds well to neoadjuvant chemoradiotherapy and have favorable oncological prognosis, with a 5-year disease-free survival (DFS) rate reaching 83%-95% . So, the ability to predict the efficacy of neoadjuvant chemoradiotherapy for rectal cancer has important clinical significance. However, it is very difficult to predict the pathological complete response of rectal cancer after neoadjuvant chemoradiotherapy, and the relevant research is limited. The present retrospective study was designed to evaluate the clinical factors that can be predicted pathologic complete response to neoadjuvant chemoradiotherapy for rectal cancer.Patients and methods Patients and evaluation before the treatmentThis retrospective study was conducted at the Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. The study was performed in accordance with the ethical standards of our institutional research committee, and the principles of the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from each individual participant included in the study. The data of 432 consecutive patients with rectal cancer who received neoadjuvant chemoradiotherapy in our hospital from January 2008 to January 2018 were retrospectively analyzed. The criteria for neoadjuvant chemoradiotherapy were as follows: (I) low or middle rectal carcinoma ; (II) pretreatment clinical stage was II and III; (III) no obvious distant metastasis; (IV) postoperative pathological results showed R0 resection. The exclusion criteria were: (I) other malignant tumors present ; (II) a history of malignant tumor or relapse; (III) managed by a watch-and-wait strategy after neoadjuvant chemoradiotherapy.All patients underwent colonoscopy with biopsy and were histologically diagnosed with adenocarcinoma. Preoperative clinical staging was determined by abdominal and pelvic computed tomography (CT), transrectal ultrasonography, pelvic magnetic resonance imaging, or a combination of these. Postoperative specimens were examined by at least two pathologists specialized in colorectal cancer. The specimens were examined grossly and microscopically. pCR was defined as the absence of viable tumor cells in the surgical specimen, including lymph nodes. Patients without pCR were grouped into the non-pCR cohort. Clinicopathological classification and staging were based on the American Joint Committee on Cancer tumor-node-metastasis (TNM) staging system.Treatment2 per day for 35 days, without weekend breaks, or oral capecitabine at a dose of 1,650 mg/m2 per day for 35 days plus intravenous oxaliplatin at a dose of 50 mg/m2 once weekly for 5 weeks. Surgical resection was planned for 6-8weeks after the completion of neoadjuvant chemoradiotherapy, irrespective of the response to chemoradiotherapy. All patients underwent radical total mesorectal excision (TME).All of the patients received intensity-modulated radiation therapy with concurrent oral administration of capecitabine: the total dosage was 50Gy . One of the two chemotherapeutic regimens was delivered concurrently with radiotherapy as follows: oral capecitabine at a dose of 1,650 mg/mThe clinicopathological and operative data were documented, including age, gender, body mass index, ASA score, tumor stage, tumor differentiation, tumor location, surgical procedure, pretreatment serum CEA level, chemotherapy regimen, the interval between neoadjuvant chemoradiotherapy and surgery, and radiation dose. Data of last follow-up and vital status were collected on all patients. Each patient was followed-up every three months for the first two years, every six months for the next three years, and once a year thereafter. Digital rectal examination was performed and the levels of carcinoembryonic antigen (CEA) and carbohydrate antigen (CA) 19-9 were determined at every follow-up visit. Chest computed tomography, magnetic resonance imaging, or computed tomography with intravenous contrast of the liver and pelvis, and full colonoscopy were regularly undertaken. Statistical analysisNonparametric variables are presented as the median and range, and categorical variables are presented as the frequency with percentages. Continuous variables were analyzed with the Mann–Whitney U test, and categorical variables were analyzed with the Chisquare test or Fisher’s exact test, when appropriate. univariate and multivariate analyses were performed by using logistic regression and Cox proportional hazard ratios to identify factors that predict pCR. P<0.05 was considered statistically significant. Data were analyzed by Statistical Package for the Social Science (SPSS) for Windows . Patient demographics and tumor characteristics are shown in For the univariate and multivariate analyses, the variables were analyzed as discrete categorical variables. On multivariate analysis, a pretreatment CEA level of ≤5 ng/mL  and an interval from the completion of neoadjuvant chemoradiotherapy to surgery of ≥8 weeks  were identified as independent predictors for achieving a pCR .For clinical stages II and III rectal cancer, the standard treatment is neoadjuvant chemoradiotherapy and surgery. Compared with surgical resection alone or postoperative chemoradiotherapy, neoadjuvant chemoradiotherapy improves local control. The prognosis of patients with tumor regression and T or N downstaging after neoadjuvant chemoradiotherapy for rectal cancer has been shown to improve significantly. It has been well documented that patients who achieved pCR had better long-term outcomes than those without pCR. However, the factors that predict patient response to neoadjuvant chemoradiotherapy for rectal cancer have not been well defined. Some studies have evaluated clinical factors associated with complete response to preoperative chemoradiotherapy for rectal cancer . Armstrong et al., (2015) found that lower pretreatment CEA level, proximity to anal verge, and statin use were predictors of pCR after evaluating the clinical factors of 885 patients. Das et al., (2007a) identified that the circumferential tumor extent was the only factor that was significantly associated with pCR in a large sample size retrospective review of 562 patients. Kalady et al., (2009a) evaluated the predictors of pCR in 242 patients and found that an interval of >8 weeks between the completion of preoperative chemoradiotherapy and surgical resection was the only factor that was significantly associated with pCR. Garland et al., (2014b) found that the tumor size and pretreatment clinical N category were independent predictors of pCR after evaluating the clinical factors of 297 patients. In this analysis of a consecutive series of rectal cancer patients who underwent neoadjuvant chemoradiotherapy and radical resection from a single institution, the rate of postoperative pathologic complete response(pCR) was 20.8%, and we found that a pretreatment CEA level of ≤5 ng/mL and an interval from the completion of neoadjuvant chemoradiotherapy to surgery of ≥8 weeks were independent predictors of pCR. Carcinoembryonic antigen (CEA) is a tumor associated antigen, CEA has important clinical value in the condition monitoring and curative effect evaluation of colorectal cancer . In colon cancer, CEA levels have been shown to be an important prognostic factor in node-negative disease, with an increase of the preoperative serum CEA level associated with an increased risk of recurrence . Consistent with our findings, Yeo et al., (2013) also showed that CEA level before treatment was an important predictive factor of pCR in a cohort of 609 patients who received preoperative chemoradiotherapy. Riesterer et al., (2007) found that tumor cells which have a high density of CEA may resist radiation. Garland et al., (2014c) found the pretreatment serum CEA levels and a decrease in the pre- to post-treatment serum CEA level were independent risk factors of pCR. Another recent study confirmed the value of CEA level before treatment on pCR, but found that the predictive value was limited to patients who were nonsmokers . We found that the CEA level was significantly higher in the non-pCR group than in the pCR group, and a normal pretreatment CEA level was significantly associated with pCR in both univariate and multivariate analyses.In 1999, François et al., (1999)  advocated the adoption of an interval between chemoradiation and surgery of 6 to 8 weeks. This was based on a statistically nonsignificant improvement in sphincter preservation rates without changes in perioperative complications, compared to an interval of 2-3 weeks. Based on these equivocal findings, an interval between chemoradiation and surgery of 6 to 8 weeks has become part of the standard protocol for the treatment of rectal cancer in the USA. Radiation-induced necrosis and subsequent tumor regression is a time-dependent phenomenon in which a longer interval between the completion of chemoradiotherapy and surgery may increase the rate of pCR . Therefore, the persistent effects of neoadjuvant treatment would continue to cause cell death over time, and consequently, waiting longer before surgery could yield less viable carcinoma at the time of surgery. In this study, we found that a time interval between chemoradiation and surgery ≥8 weeks was the independent predictor of pCR. Similarly, Kalady et al. reported that an interval of >8 weeks was an independent predictor for pCR  . Wolthuis et al., (2012) reported that an interval of >7 weeks was associated with increased pCR , and the 5-year cancer-specific survival rate was higher in the long-interval group than in the short-interval group . de Campos-Lobato et al., (2011a) has demonstrated that a prolonged interval between chemoradiation and surgery was an independent predictor of achieving a pCR, and this study shows that a longer interval is safe for patients as it does not increase peri or postoperative morbidity. Furthermore, an interval of greater than or equal to 8 weeks resulted in a decreased rate of local recurrence.Despite attempts to improve tumor response by varying chemotherapy regimens, no significant impact on oncologic outcomes has been made. To improve the response, some randomized trials have added oxaliplatin or targeted drugs into the currently widely used fluorinated, pyrimidine-based preoperative chemotherapy regimen . However, none of these studies reported an increased pCR rate. Our study found that the addition of oxaliplatin did not increase the pCR rate.Due to the retrospective nature of this study, it is subject to potential bias and certain limitations. Firstly, this is a single-center, retrospective study. Besides, there were fewer patients in the pCR group than in the non-pCR group, there may be bias. Secondly, Since the study was not prospectively designed, the time interval between chemoradiation and surgery was decided according to the individual surgeon preference. To solve these controversial factors, randomized clinical trials should be performed in the future and identify the predictors for pCR and elucidate its potential mechanisms. Patients who are considered good responders to neoadjuvant chemoradiotherapy may benefit little from TME, and their optimal treatment may involve nonoperative management or local excision.In conclusion, this large, retrospective study demonstrated that a pretreatment CEA level of ≤5 ng/mL and an interval from the completion of neoadjuvant chemoradiotherapy to surgery of ≥8 weeks were independent clinical predictors for achieving pCR. These findings may help clinicians predict the prognosis of patients and develop individualized treatment strategies.Zheng Wang and Qi Zhang contributed the conceiving and designing the study. Jianwei Liang and Jianan Chen did the collecting of data. Shiwen Mei did the analyzing and interpreting of data. Qi Zhang and Zheng Wang did the writing of the article. Zheng Wang approved the final version of the article.


Ecologists and fisheries managers are interested in monitoring economically important marine fish species and using this data to inform management strategies. Determining environmental factors that best predict changes in these populations, particularly under rapid climate change, are a priority. I illustrate the application of the least squares-based spline estimation and group LASSO (LSSGLASSO) procedure for selection of coefficient functions in single index varying coefficient models (SIVCMs) on an ecological data set that includes spatiotemporal environmental covariates suspected to play a role in the catches and weights of six groundfish species. Temporal trends in variable selection were apparent, though the selection of variables was largely unrelated to common North Pacific climate indices. These results indicate that the strength of an environmental variable’s effect on a groundfish population may change over time, and not necessarily in-step with known low-frequency patterns of ocean-climate variability commonly attributable to large-scale regime shifts in the North Pacific. My application of the LSSGLASSO procedure for SIVCMs to deep water species using environmental data from various sources illustrates how variable selection with a flexible model structure can produce informative inference for remote and hard-to-reach animal populations. Groundfish populations in the northeastern Pacific Ocean followed the six- to 12-year warming and cooling periods of the El Niño-Southern Oscillation (ENSO)2. Sea surface temperature and pressure changes in the North Pacific are captured by the Pacific Decadal Oscillation (PDO), which is separate from ENSO behavior in the region3. A third climate cycle described more recently and termed the Northeast Pacific Gyre Oscillation (NPGO) follows variations in ocean nutrient cycling and phytoplankton abundance and plays a role in the larger system of climate variability with ENSO and PDO5.The northern Pacific system is controlled by multiple interdecadal patterns of climate variability that stem from different physical sources7. This switching of regimes makes it difficult to identify which specific patterns are culprits in affecting distinct marine populations9. Many studies on fisheries systems continue to focus on these interdecadal climate modes as primary sources of population variability of marine fishes. However, climate modes alone are insufficient to accurately describe variability found in many commercially valuable marine populations on multi-year scales10. Other sources of oceanic variability not captured by climate modes exist and should be considered when attempting to create accurate models to describe and predict changes in marine populations, even in areas that appear to be dominated by shifts in climate regimes. The complicated interplay of ocean-climate systems in the North Pacific region makes it difficult to identify which and how specific indices are culprits in affecting distinct marine populations.Dramatic, permanent changes in marine species compositions in response to shifts in climate modes, commonly referred to as regime shifts, such as the strong one observed in 1976-1977 in the northern Pacific Ocean may be the convergence of several climate patterns switching phases within the same time period13. Several of these populations are managed by international or regional fishing commissions to control commercial harvests and monitor population health16. These organizations are becoming more concerned about the role climate plays in maintaining healthy fish populations, especially as marine fishes do not recover from population collapses as quickly as previously believed17. Fishing activities are increasingly concentrated on deeper-dwelling species19. While focus on the effect of various climate modes has dominated ecological research on fishes in the North Pacific region, relationships between the marine environment and atmospheric trends are nuanced and may involve complex lagged effects, particularly for deepwater populations20. Organisms that inhabit the deep ocean are also problematic to study, as they are not adapted to surface-level conditions and prove difficult to sample and keep alive, making experiments in laboratory conditions impossible or prohibitively expensive. Determining which specific environmental variables contribute to fluctuations in the populations of these species from observational data would represent major progress in discerning the impact of climate variability on marine ecosystem health and how those changes affect the economy and food security. A model structure able to accommodate a suite of environmental variables that vary spatiotemporally would be necessary to examine effects of many environmental covariates on deepwater marine populations simultaneously.Many of the marine fishes in the northern Pacific Ocean are commercially important species that contribute significantly to the economy of the United States and are important sources of food both domestically and internationally21. By setting Z to longitude, latitude, and time triplets, the SIVCM is a convenient structure for incorporating spatiotemporal effects for multiple environmental predictors in X. Spatiotemporal variation among values is incorporated through three-dimensional functions based on spline smoothing27, accounting for spatial and temporal autocorrelation and improving prediction and inference29. Similar structures have been widely used in the related spatially-varying coefficient models31 and temporally-varying coefficient models32, including applications in forestry33, ecology34, and economics36. Spline-based methods, which are often used to estimate 38, are more robust for spatially correlated data and do not require the spatial variation to be specified by a functional form40.Consider the single index varying coefficient model (SIVCM) of the formX is typically of interest. Forward selection, backwards elimination, and stepwise selection methods are unstable for models with many predictors and even with advancements to the algorithms, these methods are considered sub-optimal for variable selection, particularly for high-dimensional models41. Penalty-based regression procedures, such as ridge regression and least absolute shrinkage and selection operator (LASSO) estimation, penalize large regression coefficients to reduce overfitting. LASSO additionally performs variable selection by penalizing small regression coefficients to zero, effectively removing these coefficients from the model42. LASSO works particularly well for models with many predictors because it shrinks large coefficients to zero rather than minimizing them, and it is computationally efficient43. Group LASSO incorporates information about groupings of variables into the penalty function, which is particularly important for categorical predictor variables44. While selection for varying coefficient models (VCMs), a lower-order relative of the SIVCM, have built on both the smoothly clipped absolute deviation (SCAD) and LASSO approaches48, selection procedures of the single-index direction coefficients or the functions in SIVCMs have primarily used SCAD penalties51. SCAD procedures are unbiased, but they are sensitive to initial estimation and parameter tuning48. LASSO procedures are typically simpler to implement than SCAD, and group LASSO correctly selects important variables for VCMs where the number of dimensions far exceeds the number of observations52. In this analysis, I used a combination of least squared-based spline estimation and group LASSO (LSSGLASSO) proposed by Sun et al.53 to select coefficient functions and estimate the index parameters in a SIVCM of spatiotemporally-varying environmental covariates potentially contributing to changes in groundfish populations in the North Pacific Ocean. With this application, I aimed to establish relevant environmental factors that influence populations of focal groundfish species in this region.For such models, selection of important predictor variables in 55. The six groundfish species of focus in this analysis were Pacific cod , Pacific halibut (Hippoglossus stenolepis), sablefish (Anoplopoma fimbria), rougheye rockfish , shortraker rockfish , and shortspine thornyhead . Air temperature in degrees Celsius (ATMP), sea level pressure in hPa (PRES), wind speed in meters per second averaged over eight-minute periods (WSPD), sea surface temperature in degrees Celsius (WTMP), and the average height in meters of the highest one-third of all waves in 20-minute sampling periods (WVHT) measured daily from buoys in the Gulf of Alaska were obtained from the National Data Buoy Center and summarized by monthly means56. Temperature in degrees Celsius measured at the sea floor (hereafter bottom temperature) was obtained from the AFSC Resource Assessment and Conservation Engineering (RACE) Division’s bottom trawl surveys57. Zooplankton biomass volume given in number per cubic meter (hereafter plankton) were obtained from the NOAA’s Coastal and Oceanic Plankton Ecology, Production, and Observation Database58. Alkalinity (Alk), chlorophyll (Chl), nitrate (NO3), dissolved oxygen (Oxy), phosphate (Phos), and silicate (Sil) concentrations at depths of 75, 400, and 900 meters were obtained from the NOAA’s World Ocean Database59.Annual surveys of several groundfish species are taken at established locations in the waters along the coast of Alaska by the Alaska Fisheries Science Center (AFSC), a division of the National Oceanic and Atmospheric Administration (NOAA). Catch per unit effort (CPUE), also referred to as catch rate, and mean weight in kilograms of six groundfish species determined at each location for each survey year were obtained for years 1979–2013i was calculated as i regressed against all other explanatory variables. VIFs for all explanatory variables were computed, and the variable with largest VIF that exceeded a value of 5 was removed61. The process was repeated after each removed variable, until no variables had a Since environmental data can include hundreds of predictor variables with potential multi-collinearity, a practical method for reducing variables before performing group LASSO is necessary for the LSSGLASSO procedure to be computationally feasible. Therefore, backward variable elimination of explanatory environmental variables using computed variance inflation factors (VIF) was performed. The VIF for explanatory variable 63. For all environmental variables, a seasonal amplitude was then calculated for each survey year for all locations. For physical variables ATMP, PRES, WSPD, WTMP, WVHT and bottom temperature, seasonal amplitude was defined as the mean of June, July, and August averages minus the mean of December, January, and February averages. This was owing to the fact that temperatures maximize in the summer and minimize in winter and winter storms enable strong mixing of ocean nutrients65. Seasonal amplitudes for chemical and biological variables including plankton, Chl, Alk, NO3, Oxy, Phos, Sal, and Sil were calculated as the mean of August, September, and October averages minus the mean of March, April, and May averages. Zooplankton biomass increases in May after winter vertical mixing of deepwater nutrients and benefits from spring phytoplankton blooms but has not yet been depleted by grazing from summer-migrating pelagic fishes and cephalopods67. Therefore nutrients are generally maximal in the spring and minimal in fall after depletion by phytoplankton, whereas zooplankton and chlorophyll would be maximal in fall after nutrient consumption and growth over the summer in the North Pacific region70.Measurements of environmental variables were not recorded at the exact same locations across all years for which groundfish surveys were performed, thus spatiotemporal interpolation via inverse distance weighting was used to obtain monthly environmental measures for 1979–2013 at the precise locations where MESA surveys were conducted55, and groundfish recruitment is related to the effects of physical and biological variables on early life stages71. Therefore, all environmental predictors were lagged based on the sexual maturity of the focal groundfish. Sablefish and Pacific cod female maturity is reached around 5 years old73. Average age of Pacific halibut females that have reached sexual maturity is 12 years, while for males reaching maturity the average age is 8 years74. Rockfish sexual maturity is typically attained from 3 to 7 years of age75. Therefore, lags of 5 years were used for environmental variables in models with sablefish, rockfish, or Pacific cod CPUEs and weights as responses. Lags of 10 years were used for environmental variables in models with responses of Pacific halibut CPUE and weight. These lags were also supported by the findings of Sun et al.53.The AFSC groundfish surveys sample only adults53. The choice of knots for the B-spline approximation of the coefficient functions and the optimization of the tuning parameter in the LSSGLASSO procesure are covered in detail in Sun et al.53 The optimal tuning parameter was chosen using a BIC-type selection criterion, while the number of knots was fixed at eight. The number of knots can be chosen using a selection criterion such as GCV or BIC, but since basis expansion was only used for selection of the coefficient functions and every function was re-estimated using local linear regression, the choice of the number of knots does not affect the results53. The performance of the group LASSO procedure was tested against procedures where the group LASSO penalty was replaced by either a group LASSO with ridge penalty or a group SCAD with ridge penalty, and there were no appreciable differences between the three selection procedures. Heat maps were used to visualize selection of variables for each groundfish species. After selection, the SIVCM for all years of sablefish CPUE was refit with scaled A SIVCM of the form given in  was fit,78. Seasonal amplitude for climate indices was defined for each year as the mean of June, July, and August minus the mean of December, January, and February, since climate indices typically describe physical environmental conditions that contribute to temperature and pressure changes affecting ocean nutrient mixing80. Logistic regression was then used to fit the model k lagged by 5 years when considering the responses of all groundfish except those of Pacific halibut, which were lagged 10 years; and P-values from the Chi-square test were adjusted within groundfish response to control for the false discovery rate (FDR) of multiple testing using the Benjamini-Hochberg procedure81.To further explore if regional climate conditions influenced the selection of variables each year, I considered potential relationships between the selection of a variable over time and three climate indices that influence environmental systems in the North Pacific region. The Pacific Decadal Oscillation (PDO) monthly index, multivariate El Niño/Southern Oscillation bi-monthly index (MEI), and North Pacific Gyre Oscillation (NPGO) monthly index were obtained for 1979–201326. Relationships of climate to groundfish responses cannot be assumed to be linear84. Therefore, the GAM structure was preferred over a generalized linear model, because it permits nonlinear relationships between predictors and the expected response. P-values were estimated for each smooth predictor in each model and plotted in a heatmap for efficient visualization.Finally, it was necessary to determine whether PDO, MEI, or NPGO were good predictors of groundfish catches and weights and if the effect of a climate index on the selection of variables was related to that index’s direct relationship to the groundfish populations. I fit generalized additive models (GAMs) of the formVariables consistently selected by LSSGLASSO as important to Pacific cod CPUE were WVHT, Alk 900m, Chl 400m, Oxy 900m, Sil 900m, PRES, plankton, Alk 400m, NO3 75m, and Oxy 75m, which usually were in years 1986, 1990, 1992, 1995, 2006, and 2010 . Since rockfish are viviparous, exposure to near-surface environment during development is eliminated. Rougheye rockfish CPUE was best predicted by NPGO seasonal amplitudes, while chlorophyll, dissolved oxygen, and silicate were all important for rougheye rockfish CPUE over all years. NPGO describes variations in salinity, nitrate, phosphate, silicate, oxygen, and chlorophyll, capturing important interannual and decadal biological patterns112. While large-scale climate indices are often favored when studying populations affected by regime shifts of the northern Pacific marine system, the specific pathways of their effects on a population or community are often difficult to disentangle. Most groundfish responses had a large array of environmental variables selected for specific years, indicating that the strength of environmental effects on groundfish may vary over time. Selection of environmental variables appeared to be unrelated to seasonal amplitudes of the PDO, MEI, and NPGO climate indices for most groundfish. Large-scale climate patterns are associated with groundfish responses2, however my results highlight the insufficiency of climate modes alone to accurately describe variability found in many commercially valuable marine populations on decadal scales10. These results indicate the existence of several pathways of climate and other environmental effects on groundfish responses. Ecological variability in these marine systems are therefore likely driven by gradual spatial and temporal climate variability that reduces resilience, with abrupt changes in climate modes precipitating permanent changes in vulnerable systems8.Selection of important variables related to groundfish catch and weight using LSSGLASSO for SIVCMs provided important confirmation of previous findings and new avenues of research for large populations of groundfish in the North Pacific over an extended time period during which several large-scale regime shifts have been reported