Learning to decipher acoustically distorted speech serves as a test case for the study of language-related skill acquisition in persons with developmental dyslexia (DD). Deciphering this type of input is rarely learned explicitly and does not yield conscious insights. Problems in implicit and procedural skill learning have been proposed as possible causes of DD. Here we examined the learning of time-compressed (accelerated) speech and its generalization to novel materials among young adults with DD compared to typical readers (TD). All participants completed a training session that involved judging the semantic plausibility of sentences, during which the level of time-compression was changed using an adaptive (staircase) procedure according to each participant’s performance. In the test, phase learning (test on same items) and generalization (test on new items and same items spoken by a new speaker) were assessed. Both groups showed robust gains after training. Moreover, after training, the initial disadvantage of the DD group was no longer significant. After training, both groups experienced relative difficulties in deciphering learned tokens spoken by a different voice, though participants with DD were less able to generalize the gains to deciphering new tokens. Thus, DD individuals benefited from repeated experience with time-compressed speech no less than typical readers, but their evolving skill was apparently more dependent on the specific characteristics of the tokens. Atypical generalization, which indicates that perceptual learning is contingent on lower-level features of the input though does not necessarily point to impaired learning potential per se, may explain some of the contradictory findings in published studies of speech perception in DD. Although usually transparent to listeners, speech perception is quite a challenging task. In particular, it requires mapping the acoustic input onto stable  representations even though the speech signal itself is variable as a result of between-speaker differences, changes in speech rate  and enviSince speech is rarely learned explicitly and perceptual learning does not yield conscious insights that can be easily communicated, the perceptual learning of speech is a case of implicit learning of skills that are essential to human communication . ImpliciDevelopmental Dyslexia (DD) is one of the most common neurodevelopmental disorders, with prevalence rates estimated at 5%-10% . DespiteAlthough perceptual learning has been examined previously in individuals with DD in both the visual , 36 and Many studies suggest that typically developing individuals can adapt to such speech quite rapidly, especially under favorable learning conditions . Recent Participants were 24 university students (undergraduates or graduate students), among them 12 dyslexics  and 12 typical readers . A similar sample size was sufficient to detect group differences on the same task between native and non-native listeners . ParticiIntelligence was assessed by means of two subtests from the Wechsler Intelligence test for adults . One is Verbal working memory was assessed by the Digit Span subtest from the Wechsler Adult Intelligence Scale . In thisDecoding, reading fluency, and reading comprehension tests were administered, as described in the following sections.Two tests were used to assess decoding skills: One Minute Tests of Words  and of NThe Oral Reading Tests obtained from the reading comprehension subset of the Israeli Psychometric Exam was used to assess reading fluency. In this test, participants were required to read a text of 216 words aloud, as quickly and accurately as possible. The number of words read correctly per minute was calculated.Phonological awareness was assessed by the following tests: Phoneme Deletion, Segmentation and Parsing ) Experiments with speaker variability, speech rate and perceptual learning provide strong evidence for implicit memory for very fine perceptual details of speech . ListenThe reduced ability of people with DD to transfer their robust practice-related gains when new tokens were presented in the trained voice can indicate that the setting of a processing routine is more heavily weighted for specific items repeatedly encountered in training , 79. TheSpeech perception problems have been documented in people with DD . Most studies, however, assessed the end product of learning  , 84 rathS1 File(RAR)Click here for additional data file.


The organosolv lignins recovered from this process were investigated by determination of Klason plus acid-soluble lignin content, of sugars by HPLC analysis, and of ash content. Structural characterizations of these lignins were performed by Fourier-transform infrared (FT-IR) and by 31P NMR. The results of the latter studies indicate that the content of free phenolic groups was more important in bark than in wood lignin. The gel permeation chromatography (GPC) analyses results suggested that the weight-average molecular mass of wood lignin was higher than that of bark lignin. The studied organosolv lignins were used for the preparation of particleboards as recovered and in combination with glyoxal or isocyanate. It was found that sugar maple bark lignin, as such or modified with isocyanate, was a more efficient adhesive than its wood counterpart. On the contrary, it was the organosolv wood lignin combined with glyoxal which was a more efficient adhesive than its bark counterpart. In combination with isocyanate, it was the sugar maple bark organosolv lignin which was determined to have the best adhesive performance of all studied lignins.Organosolv lignins obtained from sugar maple bark and wood were studied as adhesives for wood particleboard production. Organosolv pulping of sugar maple wood and bark was carried out in the presence of Lewis acid FeCl In. In31P NThe major compound in wood lignin revealed a much-condensed unit such as dibenzodioxocin, which was more difficult to solubilize in deuterium solvent for NMR experiments. In accordance to the high molecular weight of wood lignin determined by GPC, a successive depolymerization/repolymerization of this lignin is hypothesized to take place due to the use of ferric chloride at high concentration, which could have catalyzed crosslinking reactions of sugar maple wood lignin.31P NMR experiments (On the other hand, eriments , which reriments , could beriments  20]..31P NMR Compared to our previous work , the higWith glyoxal activation, sugar maple wood organosolv lignin was shown to have a better performance in panel application than bark lignin. Conversely, lignin reaction with isocyanate was more successful with bark lignin than with wood lignin, as determined by particleboard performance. This favorable interaction between bark lignin and isocyanate was also confirmed by the FT-IR analysis in comparison to wood lignin–isocyanate FT-IR spectrum .−1, confirming its reaction and the consumption of isocyanate by bark lignin (−1, decreased in bark lignin after its combination with isocyanate. This could be explained by the reaction of isocyanate and bark lignin, which was completed due to the high aliphatic hydroxyl content of bark lignin, while with wood lignin this reaction was not completed.Compared to wood lignin, bark lignin revealed no cyanate moiety, which appears at 2280 cmk lignin . On the The experimental data obtained in this research demonstrated the significant difference between sugar maple organosolv bark and wood lignin. Direct glyoxalation in lignin under alkaline conditions was more efficient for enhancing the mechanical properties of wood panel when sugar maple organosolv wood lignin was used as resin. On the other hand, the results of the FT-IR analyses seem to indicate that the reaction with isocyanate was more advanced with bark lignin than with wood organosolv lignin. This could confirm the results of the GPC analyses, which demonstrated that bark lignin had lower average molar mass and, consequently, more reactive sites available for reactions taking place during panel curing. The good performance of bark lignin with isocyanate could indicate its applicability as polyols in polyurethane resin formulation for panel production.


Austad and Hoffmann review the current state-of-the-art on what support there is for the theory of antagonistic pleiotropy and what implications this has for modern medicine regarding improving human health and longevity . AlthougThese studies are essential to the discussion on aging biology in general and human health. As a species, we uniquely live well beyond reproductive senescence and thus the potential for costs of such antagonistic variants to express themselves is particularly important to assess. Two studies in 2017 uncovered evidence for antagonistic pleiotropy in genes related to coronary heart disease (CAD) and fitness, and diseases related to ageing.et al. [et al. [The study by Byars et al. , found t [et al. , found eSPATA31 gene has been found under strong positive genomic selection. Long-lived individuals carry fewer SPATA31 copy numbers [ numbers . On the GDF5 gene encodes for a protein important in joints and long bone development. Many people in Europe and Asia have a common variant in GROW1, an enhancer of the gene that causes reduced expression of GDF5. This common variant has been associated with decreased height and has been selected in people living in northern regions, since shorter stature is beneficial in cold environments [APOE gene. This allele is well known for Alzheimer’s disease predisposition after 60 years. Studies exist suggesting cognitive benefits of this risk allele at earlier ages, as young ε4 carriers have been shown to outperform non-carriers in measures of general cognitive ability, memory, attention, cognitive control allocation, verbal fluency, mental arithmetic performance and other brain functions [Another example of an allele that is associated with age-related degenerative disease, but may offer some advantage in younger ages, is ε4 of A study by Voskarides 2018  found thThese studies collectively demonstrate excellent candidate genes bearing the hallmarks of antagonistic pleiotropy. They appear to confer fitness advantages to human populations during the reproductive period, but also specifically increase risk of various common diseases that typically begin to manifest at ages when selection is weak. These genes would have been positively selected for if they improved survival and reproduction in ancestral environments, thereby increasing in frequency over time even if they increased morbidity in old ages. The manifestation of this tradeoff is conflated by the fact that post-reproductive life expectancy of modern humans well exceeds that of our ancestors living a few thousand years ago where age-related diseases would not have been the leading cause of death and therefore such tradeoffs would have been minimal anyway.Further progress in human studies will be crucial to validate recent candidate genes and identify others with such antagonistic pleiotropic effects. It appears that a large percentage of genetic predisposition to age related diseases may have been shaped by evolutionary mechanisms. It may be important that these are considered alongside traditional GWAS disease risk variants and also given their pleiotropy, carefully considered regarding potential non-target effects in drug design or gene therapy.Conflict of interest: None declared.


We describe various surgical options for correction of myopia, the advantages and disadvantages of the procedures, current practices and emerging trends.Over the last few decades, refractive surgery for treatment of myopia has gained popularity as both a cosmetic procedure to avoid spectacles and as a means of complying with occupational vision standards. Refractive surgery procedures include:Incisional refractive surgeryExcimer laser refractive surgery andIntraocular surgeryth century, when SchiotzThe first report of using an incision to alter the shape of the human cornea was in the 19Photorefractive keratectomy (PRK)Laser subepithelial keratectomy (LASEK) andEpithelial laser in situ keratomileusis In PRK, the epithelium is removed either mechanically by scraping it with a blade or chemically by using a diluted solution of ethanol. In the latter approach the epithelial sheet is not repositioned after laser ablation.In LASEK the epithelial flap is repositioned gently over the ablated tissue.Comparative studies of surface ablation techniques (PRK versus LASEK) have shown similar refractive outcomes. These procedures work best for myopia up to 6.0 D (dioptres). Laser surface ablation is a better option than LASIK in patients with epithelial irregularities, dry eye syndrome, thin corneas, possible risk of post LASIK flap dislocation and possible risk of keratectasia.LASIK is currently the most popular surgical option for myopia correction. It is superior to PRK in terms of patient comfort, visual stabilisations and stromal haze formation. It was first popularised by PallikarisAs with any other surgery, LASIK also has its own share of complications; these include free flaps, buttonhole flaps, irregular flaps and post LASIK traumatic flap displacement; epithelial ingrowth and dry eye syndrome also need to be kept in mind.Recently, Wavefront-guided LASIK is being used to preserve the asphericity of the cornea, thus inducing less spherical aberration compared with standard LASIK  and B.For very high degrees of myopia (more than minus 10.0 D), LASIK is unpredictable and runs a risk of regression and ectasia. Refractive lens exchange (RLE), also known as clear lens extraction, was first described by Fukala in 1890, as one of the options to treat high myopia .4 The avThese days, Femtosecond lasersThe most recent addition to this list is that of Small incision lenticule extraction (ReLEx® SMILE) which is a minimally invasive procedure, and combines the advantage of both PRK and LASIK that is flapless and fast recovery.Surgical options for refractive errors have come a long way since 1990. In a field like ophthalmology, which is dependent on technology, we can only expect that treatment options will become more sophisticated and patient-friendly in the coming years.


Vaccines can be extremely cost-effective public health measures. Unfortunately the research and development (R&D) of novel vaccines is suffering from rising costs and declining success rates. Because many vaccines target low- and middle income markets (LMIC), output needs to be maintained at a constrained budget. In addition, scientific neglect and political uncertainty around reimbursement decisions make it an unattractive arena for private investors. The vaccine development pipeline for LMIC thus is in need for a different, sustainable, and cost-effective development model. In conventional vaccine development, objectives for every clinical development phase have been predefined. However, given the scarcity of resources, the most efficient clinical development path should identify vaccine candidates with the highest potential impact as soon as possible. We argue for a custom-made question-based development path based on the scientific questions, success probabilities and investments required. One question can be addressed by several studies and one study can provide partial answers to multiple questions. An example of a question-based approach is the implementation of a controlled human malaria infection model (CHMI). Malaria vaccine R&D faces major scientific challenges and has limited resources. Therefore, early preliminary efficacy data needs to be obtained in order to reallocate resources as efficiently as possible and reduce clinical development costs. To meet this demand, novel malaria vaccines are tested for efficacy in so-called CHMI trials in which small groups of healthy volunteers are vaccinated and subsequently infected with malaria. Early evaluation studies of critical questions, such as CHMI, are highly rewarding, since they prevent expenditures on projects that are unlikely to succeed. Each set of estimated probabilities and costs  will have its own optimal priority sequence of questions to address. Algorithms can be designed to determine the optimal order in which questions should be addressed. Experimental infections of healthy volunteers is an example of how a question-based approach to vaccine development can be implemented and has the potential to change the arena of clinical vaccine development. Vaccines are one of the world's most important and cost-effective public health measures and have proven to generate vast socio-economic benefits . The eliInitially, investors perceived vaccine development to be riskier than other products, but this view has changed over the past years . UnfortuBecause the global viral, bacterial, and parasitic infectious disease burden nowadays is primarily borne by low- and middle- income countries (LMIC), novel vaccines need to target LMIC markets. The limited financial capacity of such nations puts constraints on the vaccine market prices. Advanced scientific technologies in areas such as immunology, chemistry and molecular biology have accelerated vaccine development through, for example, increased understanding of population differences in vaccine efficacy  or identPredicting vaccine demand in the LMIC countries is difficult because the infrastructure needed to provide necessary epidemiological data and information on immunization coverage and wastage is sometimes lacking. In addition, vaccine uptake in the Global Alliance for Vaccines and Immunization (GAVI)-eligible countries may lag behind demand forecasts . The polGiven the current vaccine development landscape, the market-driven business model will need to be revisited in order to provide a feasible, sustainable, and cost- effective structure for a global population.Global recognition of the challenges in vaccine development for LMIC has increased the support of donors for vaccine research, particularly from the Bill and Melinda Gates Foundation . These aAlternatively, market-based “pull” mechanisms—where donors stimulate demand for new technologies through purchase commitments and volume guarantees—incentivize vaccine research and development by fuelling the business case from the revenue side. Similarly, effort is put into defining target product profiles for new vaccines early in the development process, aiming to reduce risks of late failures by being explicit about the requirements for novel category vaccines . HoweverIn conclusion, managing costs and risks of vaccines for LMIC is challenging. Providing early proof-of-concept of these vaccines is essential in order to prioritize and ensure donor enthusiasm, raise funds from private investors or fuel collaborations with companies. Obviously, any product will have intrinsic development risks which are technical in nature. However, additional uncertainty may be introduced by the lack of scientific insights which need to be valued within the vaccine portfolio. Unfortunately, investment decisions on R&D projects in life sciences are frequently based on Net Present Value (NPV) calculations that depend heavily on assumptions of technical risks, costs and future profits while scientific considerations are not taken into account. NPV analysis just indicates that such evaluation studies cost time and money and disregards the increases in knowledge which is obtained when scientific questions are adequately addressed. Particularly in vaccine development for LMIC scientific advances are fundamental to game-changing novel technologies.Phase 1: Research using small groups of healthy volunteers. Traditionally, this phase mainly focuses on vaccine safety, may explore its immunogenicity, and targets to finding a dose where the level of tolerance is acceptable. In general, this phase takes about 1–2 years.Phase 2: Clinical trials are larger and the first proof for immunogenicity is established. More characteristics of the vaccine are determined and a safe and well-tolerated dose is determined where the drug is immunogenic.Phase 3: The potential new vaccine is tested on thousands of patients in an endemic setting to investigate its safety in more detail. Furthermore, the efficacy of the vaccine at the determined dose is determined. Further research is conducted to investigate possible side effects after long-term treatment and development of the drug for different indications is investigated.Phase 4: The registered and introduced vaccine is monitored closely to examine the occurrence of unexpected side-effects and interactions with other vaccines.Classically, the clinical development program of a vaccine is divided in four phases:The description of these phases is typically process oriented and contains very little information about which scientific aspects are actually covered during the clinical development. Alternatively, the clinical vaccine development pipeline can be centered around key scientific questions which need to be addressed in the most optimal order applicable to the individual investigational vaccine Figure . ExampleDoes the vaccine formulation induce an immune response (“Immunogenicity”)?This main generic question contains several issues that need to be addressed such as the route and site of vaccine administration. Not only the immunogenicity of the vaccine antigen, but also any possible adjuvants, vectors or conjugates could be included in answering this question.Does the vaccine formulation induce a disease correlate of protection (“Disease correlate”)?Answering this question includes the demonstration of the immunological mechanism of action for the investigational vaccine. As stated previously, R&D investments into mechanisms of disease and correlates of protection are essential to help answer this question and as such the associated development risks in this area may vary considerably. Addressing this question may be very instrumental in addressing the other questions also. In diseases where a correlate of protection is lacking, e.g., malaria or HIV, protective efficacy trials bear substantial risks which have impeded vaccine development.Does the vaccine formulation confer protective efficacy to the target disease (“Protective efficacy”)?This question reflects the need to establish beneficial effects on the incidence or prevalence disease but also the alteration of other physiological systems resulting in clinical side effects. Depending on the infection incidence, these trials can be particularly large in vaccine development in order to achieve sufficient power to detect efficacy.What is the lowest dose and number of doses at which the vaccine which still induces protective immunity (“Therapeutic window”)?The therapeutic window of each investigational vaccine needs to be established in order to select the optimal dose that is clinically optimally efficacious at well tolerated levels. This question includes important sub-questions: how many vaccine doses need to be given at what interval? Can vaccine formulation decrease the need for booster doses?How do the sources of variability in vaccine response in the target population affect the development of the product (“Target population”)?This question should include: Are there any specific factors in the target population that may affect immunogenicity? Particularly in vaccine development for LMIC this can be a significant hurdle given the generally decreased efficacy of vaccines in resource-poor settings . Co-infeThe abovementioned questions can be ranked based on their risk profile and examined in different sequence orders. For example, if we examine the clinical development path for a hypothetical malaria vaccine using overall probability of success of 5%, development costs of 90 €M and revenues of 800 €M. Equal distribution of the risks and costs over the five proposed questions would amount to a 55% probability of success and 18 M€ costs for each question. The resulting question-based decision tree Figure  reflectsBecause it is unlikely that all five questions would contribute evenly to the overall risks, we now unevenly distribute risks and costs in our example Figure . DespiteFurthermore, the question-based approach illustrates how the project value can increase by performing an additional early phase evaluation study that helps to adequately answer a critical question. If an additional 1 M€ costs and a 5% increased probability of successfully answering the “Disease correlate” question is added, the overall project value increases by more than 50% Figure , despiteBy defining the costs and probabilities of success and constructing the decision tree for every new vaccine, the bottleneck in the development of each individual vaccine will be identified. Presumably for most vaccines the “Disease correlate” and “Protective efficacy” questions will have the lowest probability of success. As explained earlier, the increasing recognition of this critical bottleneck in vaccine development has led to a demand for proof-of-concept clinical trials showing early efficacy for the candidate vaccine technology. In the next section, we will take the example of malaria vaccine development to illustrate how question-based product development has changed malaria vaccine development and fostered novel technology development in this field.Plasmodium falciparum (Pf). This organism displays extracellular and intracellular developmental stages and transforms within the human host, creating a challenge for the immune system and therefore also a scientific challenge for malaria vaccine development. Because there are no prior registered vaccines for parasitic diseases, malaria vaccine development cannot draw on experience from other disease areas. In addition, despite decades of vaccine research, there are no correlates of protection for Pf malaria. Lastly, Pf strains worldwide display considerable genetic variability which may affect local vaccine efficacy. As a consequence, the probability of successful market entry for malaria vaccines is extremely low even after 7–8 years of clinical development  endpoint, addressing a claim in the vaccine target product profile, such as diarrhea in the case of cholera CHI  or feverIn addition, the vaccine antigen(s) should be sufficiently present in the CHI model to measure protective effects. For example, in the malaria case, a liver-stage malaria vaccine can be tested for its preliminary efficacy by a mosquito-bite CHMI. However, for blood stage malaria vaccines, this model is less suitable because blood stage parasitemia will be limited to only a very short (3–4 day) timeframe in a mosquito bite CHMI . TherefoGenerally, CHI trials are performed in healthy adult volunteers which do not necessarily reflect the target population, which is typically much more heterogeneous. In order to overcome these differences, CHI trials can also be performed in more susceptible (target) populations such as COPD patients for rhinovirus  or malarPf CHI (Given the invasive nature of the CHI trial, regulatory authorities will often demand strictly controlled production of challenge material. In addition to the fact that such processes may be difficult, expensive and time-consuming, the process itself may render the challenge material less representative of microbes circulating in the field. For example, passage of virus strains through well-characterized cell lines to produce Good Manufacturing Practice compliant strains, will unequivocally alter the genetic makeup of the virus. Alternatively, the well-characterized laboratory strains such as the Quailes strain used for typhoid CHI  or the NPf CHI  may not Depending on the scientific and clinical details of the CHI model mentioned above, the CHI model can be used as a tool to answer one or multiple questions in the product development pipeline. Determining the most optimal order in which these questions should be addressed, will aid in positioning the CHI model in the pipeline. Because CHI models often address high-risk clinical development questions, they are optimally performed early in clinical development. Previously, this has led to hesitancy by vaccine developers, who fear that negative results will result in a “no-go” decision for a vaccine which may actually be efficacious in later trials. However, as in any other model, the results of the model system should be valued for its merits within the scientific question which it addresses. For example, a CHMI trial may enable identification of an immunological correlate of protection in a trial which shows only partial efficacy. The correlate will de-risk other clinical development questions. Depending on the outcome of the trial, these need to be reassessed and risks adjusted to come up with the then optimal order based on the required investments and updated probability of success.Increasing familiarity of CHI models by regulators as well as vaccine developers increases acceptance of these trials as part of the regulatory package which is submitted for licensure. However, given the restrictions of CHI models, continuous education of regulators, and vaccine developers to increase the scientific understanding of these models is essential to ensure that data from these trials are interpreted appropriately. In the end, regulation follows science, not the other way around. The malaria example shows how a well-designed CHI trial early in clinical development can dramatically improve the business case of the experimental vaccine and ultimately lead to registration of a LMIC vaccine with global impact.In conclusion, global vaccine development faces major challenges, particularly for LMIC settings. Initiatives to improve the business case for vaccine development including so-called “pull” mechanisms to ensure pricing and guarantee demand are needed but will not provide the ultimate solution. A question-based clinical development approach can provide the insights on critical steps in the development path for novel vaccines and will help display the priorities within the program. Controlled human infections, if well designed, are an excellent example of how question based product development has led to adjustments to the product development pipeline and the way to prioritize vaccine candidates, accelerate novel vaccines, reallocate resources and foster novel technologies. During development, the estimations in the question based approach require constant evaluation and adjustment in order to keep development on the optimal path. Ultimately, this approach has the potential to more quickly improve global health and hopefully increase the appetite for private investors to enter the arena of clinical vaccine development and work together with public funders to target low income markets despite small profit margins. In addition, it will foster scientific advances which are needed to turn the tide on the development of vaccines for neglected infections of global importance, increase enthusiasm for public investments and the public pressure needed to stimulate societal corporate responsibility.MR drafted the manuscript. IK and SdV reviewed and finalized the manuscript.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.


Since the beginning of the current conflicts in Southwest Asia, more than 2 million service members have deployed in support of Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) Sharkey . ServiceDespite considerable media coverage and anecdotal reports from concerned service members, epidemiologic evidence of adverse health effects from burn pits exposure has been lacking until recently. For example, as recently as 2014, Abraham et al. noted that “no study has identified an association between burn pit emissions exposure and post deployment chronic lung conditions.” Similarly, the Institute of Medicine concluded in 2011 that there was insufficient evidence to develop firm conclusions about what long-term health effects might be seen in service members exposed to burn pits.Several factors suggest that this situation is likely to change. First, the number of veterans who have participated in the Airborne Hazards and Open Burn Pit Registry has steadily increased, making it feasible to conduct registry-based epidemiologic studies . A publiSecondly, two recent epidemiologic studies have found that exposure to burn pits and deployment to Kabul, Afghanistan is associated with chronic respiratory conditions . Liu et Thirdly, because of the increasing time elapsed since exposure to burn pits during combat, the latency period may be approaching that sufficient to detect associations with emphysema in epidemiologic studies. It may also be feasible to conduct epidemiologic studies to examine associations with malignancies and pulmonary conditions that are infrequent in the general population  . A propoIn addition to additional population-based and registry-based epidemiologic studies of chronic health conditions among veterans exposed to toxic fumes from burn pits, longitudinal studies are needed that include serial measurements of pulmonary function and novel biological markers of exposure to polychlorinated dibeno-p-dioxins/dibenzofurans . Individ


Refractory and relapsed cancer patients often develop resistance mechanisms associated with an immunosuppressive tumor microenvironment (TME). Indeed, the TME is critically involved not only in tumor growth, invasion and dissemination, but in immune editing and resistance to different therapies both conventional and biological. Innate myeloid cells such as monocytes, macrophages, neutrophils, and a diverse set of cells, sometime called myeloid derived suppressor cells (MDSCs) may drive both local and systemic immunosuppression. These cells, however, possess novel molecules and functions that could be targeted to fight against cancer making them potential candidates for development of second-generation immunotherapy approaches. The aim of this article collection is to provide a comprehensive overview of the different myeloid subsets in the TME, and to describe recent developments and approaches targeting myeloid cells to enhance anti-tumor immunity and the clinical efficacy of standard-of-care cancer drugs.Jeong et al. summarizes the regulation of neutrophils that determines the reciprocal dynamics between them and tumor cells. This continuous interaction has expanded to a formidably complicated network, including tumor types, tumor stages, subtypes of neutrophils, various signaling molecules mediating crosstalk, and spatial-temporal interactions with other cell types. This ever-growing complexity as reviewed by Jeong et al. has revealed how much more there is still to be learned to be able to achieve effective and consistent therapeutic effects based upon targeting neutrophils. This diversity is a point emphasized in the mini-review by Granot who suggests that simple binary classifications are insufficient and that the context defines neutrophil types and functions. Mackey et al. in their minireview address a particular aspect of the contextual regulation of neutrophils in the TME, i.e. neutrophil maturation outside the bone marrow. This atypical maturation and notably the promotion of immature neutrophils by tumors underlie many of the different responses of neutrophils to cancer.Neutrophils exhibit diverse and sometimes contradictory roles in the TME. The review by Canè et al. support the notion of a “monocyte continuum” instead of classification of stepwise differences between the different subtypes. They also maintain that monocytes are more than precursors of macrophages and dendritic cells but also make a direct contribution to cancer development themselves. An additional feature of this review is the summary of current monocyte-targeting drugs and their mechanisms of actions. Along these lines, Mengos et al. describes the documented clinical findings on a CD14+HLA-DRlo/neg monocyte population that has emerged as an important mediator of tumor-induced immunosuppression. Different from MDSCs, these cells arise from the regular circulating monocyte pool, which lose HLA-DR expression and get deactivated after an acute or chronic inflammatory trigger leading to immune paralysis. The immunosuppressive monocytes can negatively affect responses to immune checkpoint inhibitors and could be potentially used as biomarkers to understand disparate responses to immune activating drugs, in addition to their potential targeting to increase immunotherapy responses.Similar to neutrophils, monocytes also show significant diversity in the TME. In their review, Laviron et al. examine the pros and cons of intravital imaging as compared to other approaches, such as cell sorting and sequencing, and suggest that an integrative approach offers the most valuable information.Cellular processes as analyzed by tissue sections at a certain time point may be missed, impossible to obtain or even misinterpreted. With new technologies, intravital optical imaging is providing an unprecedented opportunity to look at cancer cells and stromal cells in their native environment and thus yields arguably the most reliable results in interpreting the TME. Tanita et al. shed light on the mode of action of bexarotene, a third-generation retinoid that has been used for decades in the treatment of both early and advanced cutaneous T-cell lymphomas (CTCL). The authors show that bexarotene decreases CCL22 production by CD163+ macrophages in CTCL patients. Since CCL22 attracts CCR4+ lymphocytes, such as Tregs, Th2 cells, and also CTCL cells to support tumor progression, this study proposes the potential of targeting tumor associated macrophages (TAMs) in CTCL for improved patient outcome The mode of action of several FDA approved drugs such as bisphosphonates, trabectedin, imatinib, and sunitinib has been shown to involve the modulation of macrophage functions in addition to their respective targets. Whether their macrophage targeting effects are significantly contributing to drug efficacy remains to be investigated. In their article Willebrand et al. where they studied the effect of high salt intake on the functional modulation of MDSCs in the TME. Excess salt intake has been previously shown to balance various innate and adaptive immune cells toward a pro-inflammatory state, and believed to be associated with several autoimmune disorders. Therefore, an interesting question that the authors raised was whether high salt conditions can promote anti-tumor immunity to inhibit tumor growth? Surprisingly, the authors find that, while high-salt diet altered T cell populations, the delay in tumor growth was largely mediated by an impairment in MDSC suppressive functions  Thus, high salt-induced molecular changes could be potentially utilized during immunotherapy.Another interesting concept is reported by Hua and Bergers focus on two common components in these two intricately related processes—blood vessels and immune cells. They explain how tumor cells hijack the immunosuppressive and angiogenic programs that occur during the resolution phase of wound healing toward their own ends. The authors thus suggest targeting both myeloid cells and angiogenesis to revert the hijacked wound-healing process.As a general assumption, macrophages are mostly considered to have an unfavorable role in cancer since they are effective suppressors of anti-tumor immune responses and can contribute to tumor progression in multiple ways. Tumor growth is often compared to the wound healing process and is metaphorically described as a “wound that does not heal.” Bercovici et al. discuss the plasticity of macrophages and focus on macrophage regulated intratumoral T cell migration and activation. The authors emphasize that T cell focused treatments should be systematically replaced by rational combination treatments stimulating both innate and adaptive arms of the immune system. When appropriately stimulated macrophages can effectively induce anti-tumor responses in cooperation with T cells. To date, only a few myeloid cell targeting strategies under clinical development have yielded promising results and many have been terminated due to toxicities. In their review Jahchan et al., indicate the potential of targeting TAMs in cancer immunotherapy. They make a persuasive case for such approaches through the targeting of particular functions of TAMs or by altering their differentiation to anti-tumoral responses either directly or through the enhancement of immunotherapy. They also provide an authoritative update of all current clinical trials using these approaches.In a mini review As shown by this collection of articles, a tremendous diversity of myeloid cells orchestrate tumor-stromal and stromal-stromal interactions to regulate the final outcome of the disease. Elucidation of the detailed mechanisms and systemic rational evaluation of therapeutic targeting of these cells may be the key to fighting cancer.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


Measurements of population activity in alert animals have demonstrated that the intrinsic response state of the cortex has profound effects on the neuronal representation of sensory inputs, raising the possibility that cortical state could influence the behavioral performance in perceptual learning (PL). PL is a process by which sensory experience leads to gradual and semi-permanent improvements in perceptual judgment, and it is generally agreed that these improvements are modulated by sensory cortical areas. Although the precise neural mechanisms underlying the improved perceptual judgment remain unclear, cortical state has been shown to impact the behavioral outcome of PL. We discuss several ways in which cortical state might influence PL based on the recent evidence for state-dependent modulation of sensory encoding. Conversely, training in a certain perceptual task feeds back to modulate cortical state, suggesting a bi-directional relationship between cortical state and behavioral outcomes of PL. We highlight the recent studies that shed light on the mechanism of the interplay between cortical state and PL. Figure 1; Cortical state classically refers to the dynamics of neuronal population activity in a cortical network . TransitHow these cortical states are orchestrated to modulate neural and behavioral plasticity during learning is a fundamental question in neuroscience. Recent findings of functional MRI (fMRI) studies in human subjects show that cortical state, measured as the resting state network activity of the brain has a significant impact on the performance in perceptual learning (PL) . Here, wCortical state has been defined operationally on different spatial scales (from a specific area to the entire cortex) and temporal scales (tens of milliseconds to seconds) even in the awake brain. At the neuronal level, shifts in cortical state manifest as a transition between up (depolarized) and down (hyperpolarized) phases of membrane potential, which arises from fluctuations in the synaptic input. Cortical state has also been defined based on population-level fluctuations in synchrony or the LFP power during spontaneous activity . SimultaPerceptual learning is a form of implicit learning and distinct from declarative learning that requires the use of the medial temporal lobe . PL is cNeural mechanisms that underlie behavioral improvement associated with PL remain undefined. Depending on the task design, species and sensory modality, different mechanisms have been put forward. In tasks that require discrimination or detection of primary features of stimulus, the performance improvement has been associated with enhanced representation of the relevant features. On the other hand, tasks that are based on emergent properties of cortex such as context-specific sensory coding, remarkable changes in the top-down influence have been observed while the neural plasticity at the level of individual sensory neurons appeared to be modest . AnotherAn intuitive way by which cortical state might affect PL is through modulating neural activity in the cortical area that encodes task-relevant features. Typical PL involves training subjects to discriminate perceptually demanding stimuli that are repeatedly presented for extended periods of time. Neuronal responses to repetitive sensory stimuli are not static but dynamically modulated by the ongoing spontaneous activity. Recent studies using population recording techniques have revealed that spontaneous activity is structured in spatial and temporal domains. The amplitude and variability of sensory-evoked responses are correlated with the intrinsic response state in the sensory cortex to such an extent that the evoked responses can be predicted from the pre-stimulus on-going activity . StimuluIn vivo measurements in different cortical areas show that the pairwise correlated variability is on average about 0.1–0.2, although it can vary significantly depending on internal cortical state  causes perceptual improvement, interaction between different cortical areas is likely to be critical for PL. Therefore, studies examining the impact of cortical state on PL and vice versa should consider the long-range pathways that connect different cortical areas. To this end, genetic tools for directly manipulating specific long-range pathways may be combined with recording of cortical state during perceptual tasks. Advances in multi-areal, single-neuron imaging in behaving animals would allow us to define how cortical state transitions are coordinated across brain areas and whether a specific coordination is important for PL.SK wrote the paper.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data. Sequential sampling models have been widely embraced in contemporary decision neuroscience. The models come in many forms that, despite containing fundamentally different algorithmic elements, can make highly similar predictions for behaviour. Consequently, it can be difficult to definitively adjudicate between alternative models based solely on quantitative fits to behaviour.The discovery of brain signals that reflect key neural computations underpinning decision-making is opening new avenues for empirically testing and refining model predictions.Neurophysiological research is highlighting the multilayered neural architecture for implementing even the most elementary sensorimotor decisions. We do not yet know how many processing layers are required nor what distinct computations are performed at each layer. The term ‘decision-making’ often calls to mind scenarios such as voting in an election or selecting a course of study. Yet, even simply perceiving our sensory environment relies on a continuous stream of elementary judgments, known as ‘perceptual decisions’. In some cases, perceptual decisions can be as consequential as those requiring more abstract judgements . In the highly complex and dynamic environment that we inhabit, making accurate and timely decisions is a considerable challenge for the brain, since the information it receives is almost always to some degree unreliable. Understanding how the brain overcomes the challenges associated with perceptual decision-making could also illuminate broader principles of computation that extend to a range of cognitive operations evidence accumulation  and variance Δt, is accumulated until the cumulant reaches an upper or lower bound. The drift rate scales with stimulus strength and the bounds are set to achieve a balance between speed and accuracy demands. The subject’s overall response time is modelled as a sum of the time it takes this diffusion process to reach the bound, and a ‘nondecision’ time accounting for additional delays associated with encoding, routing Both simpler and more complex versions of this model have been developed, and the choice among these depends on research goals. In general, cognitive modelling is primarily concerned with forging abstract mathematical accounts of behaviour, the parameters of which serve as mechanistically interpretable metrics of task performance. Unlike neural or biophysical modelling, cognitive models do not generally strive to represent details of neurophysiological implementation Toward the more complex end, the leaky competing accumulator model of Usher and McClelland Alt-text: Box 1Many model variants exist because there are many alternative implementations of a decision process based on sequential sampling . In manyIn the most widely subscribed models Establishing the relative prominence of these alternative mechanisms in choice behaviour has consequences beyond matters of preference in model-fitting approaches. These alternative accounts reflect fundamentally different algorithmic elements and, therefore, adjudicating between them has important implications for our understanding of normal and abnormal decision-making. For example, there has been an increasing application of sequential sampling models in studies seeking to better understand decision-making deficits observed in psychiatric populations et al.model parsimony. The authors found that most data sets were better explained by a constant bound model with drift rate variability. Of note, however, in this comparison, collapsing bound models also included drift rate variability in addition to several parameters describing the collapse (nonlinear functions of time). As a result, the collapsing bound models were at a disadvantage, since BIC metrics penalise for complexity. In an attempt to address this, a second main comparison was made with a collapsing bound model contrived to have the same number of parameters as the constant bound model. Again, the data favoured constant bounds, but again questions remain, since the parameters that were omitted from the collapsing bound model were ones that account for qualitatively distinct and often significant aspects of behavioural data . The simplest way to implement a collapsing bound  was not considered. By contrast, a more recent study that did use such a linear implementation showed an improved BIC for a model that included collapsing bounds alongside drift rate variability In behavioural model comparisons between two mechanisms that produce the same qualitative behavioural pattern, the outcome can greatly depend on the number and nature of the parameters used to implement those mechanisms. To take an example relevant to the above debate, Hawkins Box 2Significant advances in isolating decision signals from non-invasive human brain recordings open possibilities for translating the detailed characterisations of decision mechanisms wrought from nonhuman neurophysiology to the human brain in both health and disease. Moreover, global brain recording techniques, such as electro- and/or magneto-encephalography (EEG/MEG) and fMRI can complement intracranial investigations by offering a wider systems-level view of decision-related processes. However, a challenge is that non-invasive assays suffer from limited spatial or temporal resolution. In EEG/MEG, signals at the scalp reflect the sum of concurrently active components of neural activity. Several approaches have been used to disentangle the components specifically with a role in decision-making. One approach is to design paradigms that, by their nature, produce signals related to the core ingredients of a decision  while minimising decision-irrelevant neural activity components. For example, decisions based on gradual changes in the intensity of flickering visual or auditory stimuli readily furnish sensory evidence signals through steady-state flicker-response amplitudes and eliminate irrelevant early sensory-evoked potentials normally evoked by sudden intensity transients Other approaches have used signal-analytic methods to extract decision-relevant signals during more complex tasks involving higher-order categorisations. For example, using a task requiring accumulation of orientation information varying stochastically over discrete sequential samples, sample-by-sample regression analyses can furnish distinct signal components related to decision-irrelevant sensory changes and relevant decision-update processes For the abovementioned non-invasive neurophysiology approaches, the ability to take measurements of dynamic decision signals at multiple hierarchical levels in the decision architecture has been demonstrated, yet the potential to use such measurements in neurally informed, or even neurally constrained, modelling is only beginning to be realised Alt-text: Box 2Discrepancies such as the one discussed above highlight the difficulties that can arise when adjudicating between alternative models based on behavioural data alone. One approach to break such impasses is to additionally consider the ability of a model to capture key observable aspects of the biological implementation of the decision process et al.urgency signal rose more steeply under speed pressure  for motion decisions, where autocorrelation levels are, in fact, low and have short (on the order of <100 ms) timescales Drift rate variability is an undeniably convenient feature of abstract decision models for quantitative fitting of behaviour et al.In general, there are many different ways in which observations of decision-related neural signal dynamics can inform psychological process modelling and thereby help to converge on a computational account of the brain’s decision mechanisms neurally informed modelling in relying on the additional constraints brought by neural data to allow models to take on levels of complexity closer to the neural reality. Alternatively, in cases where behavioural data alone provide sufficient constraints for a reasonable fit, a ‘two-step’ approach can be taken, where behavioural fits are used to simulate dynamics for comparison with neural dynamics in a separate step. For example, in a recent study of rapid, value-biased sensorimotor decisions in humans One effective approach that is beginning to be used is to quantitatively fit a given model to both the neural signatures of decision formation and behavioural data combined in a single step Neural signal analyses could similarly have a critical role in the application of models in research involving group comparisons. For example, consider the choice of ‘scaling parameter’, a parameter whose value is fixed, to anchor the model fit and to set the arbitrary scale on which all other parameters are measured (hence the name). A common choice in abstract decision models  is to set within-trial noise to a fixed value Box 3Much research effort in decision neuroscience has focused on recordings from area LIP, and this work has yielded insights into the computational mechanisms by which the brain accommodates speed–accuracy demands Alt-text: Box 3An obvious caveat should be noted in relation to any of the above approaches: it must be taken into account how confident we are that the signals in question are indeed tracing the core neural computations that give rise to decisions Neurophysiological evidence from rodents, monkeys, and humans is increasingly highlighting the multilevel nature of the neural architecture of the brain for implementing even the most elementary decisions In many cases, however, there are clear limits to the ability to localise effects among hierarchical processing levels using behavioural analysis alone. Several key parameters of sequential sampling models are likely subject to influences at multiple processing levels, and these influences often cannot be disentangled. For example, changes in the ‘nondecision time’ parameter (which accounts for delays due to processes not directly associated with evidence accumulation) could stem from altered delays at the outset of the decision process  and/or at the end of it . There is also ambiguity in the dependence of a parameter on changes at a single processing level versus in the transmission of information between levels; for example, drift rate is dependent not only on the strength and reliability of sensory representations themselves, but also on the weighting or reference values used in casting those representations as an input to the accumulation process  activity and its relationship to multiunit spiking forms an important bridge to scalp EEG, which is thought to primarily reflect postsynaptic activity Biophysically based computational modelling represents a complementary approach to integrating across levels of description while also specifying mechanisms of decision formation. For instance, spiking neuronal network models have successfully captured aspects of spiking dynamics and behavioural data during decision-making Despite this progress, recurrent neural networks come with issues relating to stability and ease of interpretation with respect to decision algorithms of lower complexity. One means to bridge from spiking neuronal network models to simpler firing-rate, population-based models is through theoretical mean-field approximations Alt-text: Box 4This discovery not only builds on longstanding assertions that the brain must house abstract-level mechanisms to afford flexibility in mapping sensations to appropriate actions Although we may lack a complete picture of the essential computational layers for decision-making, studies that have recorded neural activity at multiple processing levels during the same task have already furnished insights that are beyond the reach of behavioural modelling alone. For example, recording from both MT and LIP during training on a motion direction discrimination task revealed that improvements in behavioural sensitivity with learning were attributable to changes in the motion-driven response of LIP neurons in the absence of any change in the evidence-encoding MT neurons, suggesting that learning changes the read-out but not the sensory representations themselves In certain instances, multiple levels of processing can be examined within a single brain area. For example, in the context of visual search decisions, salience-encoding visual FEF neurons provide the evidence that is accumulated by movement neurons, and these signals have also been used to directly constrain mathematical models Combining computational modelling with neural recordings probing multiple processing levels  will be central to resolving a range of outstanding questions in the field. For example, thus far, much of the neurophysiological research on decision-making has focussed on activity in neural circuits situated close to the motor output end of the sensorimotor hierarchy. Therefore, we have a fairly refined picture of how key factors such as speed pressure, prior probability, and payoff information affect decision-making at this neurophysiological level, but a more limited picture on earlier processing stages. Of note, research on attention Outstanding QuestionsVarious factors are known to influence decision-making behaviour, among them: prior information, conflicting information, redundant information, energetic costs, spatial attention, perceptual learning, and value assignment. Processing of many of these factors is dysregulated in brain disorders. Do sequential sampling models provide accurate accounts of the essential neurocomputational adjustments through which these factors influence decision-making, and can neural signal analyses be used to determine whether that is the case? In addition to dominant criteria adjustments, are there modulations exerted at the sensory level that model fitting alone cannot detect?The versatility of popular sequential sampling model variants is partly owed to the inclusion of certain parameters  that render the models flexible and enable them to account for different behavioural patterns. What predictions do these parameters make regarding neural activity, and how can these predictions be tested? Can neural signatures of such processes be identified?Build-to-threshold decision signals have been observed in a variety of brain areas. What distinct computations do these signals and areas perform during decision formation?What are the precise roles of abstract evidence accumulation signals in decision formation? What is the relationship between decision-related signals recorded non-invasively  and those observed in single-unit recordings (primarily in nonhuman primates and rodents)?Sequential sampling models have provided a common, principled foundation to diverse investigations into decision-making. Behavioural fits of the models have long been used to furnish quantitative, mechanistically defined metrics to aid in understanding differences in how decisions are forged across stimulus conditions, task contexts, and clinical groups. However, the field has been grappling with several debates regarding key algorithmic elements of these models that are difficult to resolve based solely on quantitative fits to behavioural data. The ability to observe neural signal dynamics underpinning the decision process provides a means of guiding model development further. Recent studies demonstrate the unique insights that can be acquired by examining correspondences between abstract mathematical models and neural signals that have been independently verified to reflect elements of decision formation. It is now increasingly possible to construct models that are neurally constrained , neurally informed , or at least neurally cognisant . With the ongoing development of techniques and paradigms for measuring decision-relevant neural processes, we can expect to see increasing adoption of such approaches that integrate neural evidence into computational accounts of decision-making (see Outstanding Questions). Adapting cognitive models to reflect the critical neural dynamics governing decision formation can also help substantially in establishing much needed linkages between the parameters and mechanisms of cognitive models and biophysically based neural circuit models, which are rarely brought into direct contact


Suicide is a preventable public health problem. Zero Suicide (ZS) is a suicide prevention framework currently being evaluated by Mental Health Research Network investigators embedded in six Health Care Systems Research Network (HCSRN) member health systems implementing ZS. This paper describes ongoing collaboration to develop population-based process improvement metrics for use in, and comparison across, these and other health systems. Robust process improvement metrics are sorely needed by the hundreds of health systems across the country preparing to implement their own best practices in suicide care. Here we articulate three examples of challenges in using health system data to assess suicide prevention activities, each in ascending order of complexity: 1) Mapping and reconciling different versions of suicide risk assessment instruments across health systems; 2) Deciding what should count as adequate suicide prevention follow-up care and how to count it in different health systems with different care processes; and 3) Trying to determine whether a safety planning discussion took place between a clinician and a patient, and if so, what actually happened. To develop broadly applicable metrics, we have advocated for standardization of care processes and their documentation, encouraged standardized screening tools and urged they be recorded as discrete electronic health record (EHR) variables, and engaged with our clinical partners and health system data architects to identify all relevant care processes and the ways they are recorded in the EHR so we are not systematically missing important data. Serving as embedded research partners in our local ZS implementation teams has facilitated this work. The age-adjusted suicide rate in the United States increased 28 percent between 1999 and 2016 when nearly 45,000 Americans died by suicide .In 2012, the National Action Alliance for Suicide Prevention (Action Alliance) and the U.S. Surgeon General published the National Strategy for Suicide Prevention (NSSP) . A call www.zerosuicide.com), an active e-list with over 2000 members, a workforce survey, and an organizational self-study. Implementation strategies are meant to be tailored to each health system’s unique population and local context. Therefore, ZS is not a one-size-fits-all, manualized intervention. Rather, it is a set of recommendations, best practices and customizable tools to improve the quality of suicide prevention efforts.The NSSP promotes the adoption of “zero suicides” as an aspirational goal for health systems serving defined populations (Objective 8.1) . One sysZS promotes several evidence-based suicide prevention interventions developed in the past decade and is based on the Henry Ford Health System (HFHS) Perfect Depression Care program that resulted in a near 80 percent reduction in the suicide death rate among patients receiving behavioral health care 11121314,1112131213Currently, investigators within the Mental Health Research Network (MHRN)  are condBecause of their relationships to the health systems and their roles as embedded researchers, the MHRN investigators are also able to accurately identify and describe suicide care processes and measure quality improvements. The health systems participate together in a Zero Suicide national learning collaborative where they share approaches, decisions, and lessons learned as they design a unique implementation strategy for their individual systems. The systems are also working together with MHRN researchers to compare and evaluate specific components of ZS. Health system and clinical leaders with responsibility for ZS implementation and health system data analysts are partners in the research; the project aims to demonstrate a ‘Learning Healthcare System for Suicide Prevention.’Because each of the health systems are implementing different ZS components in different settings  at different times, certain sites will serve as ‘intervention’ sites for specific ZS components while others serve as ‘controls’ allowing a pragmatic interrupted time-series analysis of suicide outcomes that overcomes the costs and impracticalities of a randomized controlled trial. This kind of evaluation, using EHR data to measure ZS processes and outcomes across multiple diverse health systems implementing varied suicide prevention approaches within defined, large populations sufficiently powered to test suicide outcomes, could only be conducted within the HCSRN. One practical goal of this project is to develop EHR-based tools for implementation and evaluation that can be replicated in other health systems using EHR data.This paper describes the work our team is doing to develop population-based suicide prevention metrics for use in, and comparison across, the health systems. While measuring suicide outcomes is important and comes with its own unique set of challenges 19, here ZS emphasizes the importance of using an evidence-based, scorable risk assessment tool. For the purposes of population risk management, ideally that tool would be easily be embedded in the EHR with discrete data fields, so the data can be easily identified and harvested for quality improvement monitoring. Most health systems participating in the ZS evaluation study use the Patient Health Questionnaire (PHQ-9)  item 9 tIn contrast, the Columbia Suicide Severity Rating Scale (C-SSRS) , used toDespite the aforementioned challenges, suicide risk screening involves a relatively standardized care process, unlike follow-up care once risk is identified, which could include many different interventions at varying levels of care with distinct clinicians. Considerable effort has been made to coordinate staff, organize workflows, and bolster services that will address additional risk uncovered by more comprehensive risk screening. Many health systems have developed monitoring and outreach programs but the way those programs are organized and how patient contacts are documented varies widely across health systems, making measurement of risk mitigation exceedingly complicated. There is also the issue of whether health systems are implementing core ZS components with fidelity. Local adaptation is necessary as long as it does not compromise fidelity. Both measuring how ZS is implemented and what is being implemented are important quality improvement goals. One challenge for developing generalizable suicide prevention metrics is determining what efforts should be measured; a secondary challenge is determining how those efforts can be measured using EHR data across different systems.Returning to the example of our systems’ relative advantage of using easily retrievable PHQ-9 data, if a health system process improvement initiative is, for example, to administer the PHQ-9 at all mental health specialty visits for patients 13 and older, the measurement question is straightforward: “How often is a PHQ-9 recorded during these visits?” In systems with robust capture of well-organized PHQ-9 data this is an uncomplicated metric to produce. However, if a follow-up care process improvement initiative is to administer the C-SSRS for all mental health specialty patients scoring 2 or 3 on PHQ-9 item 9, and the measurement question is “How often is the C-SSRS recorded during these visits?” then it becomes necessary to identify all sources of C-SSRS scores (see above) and specify what counts as a qualifying C-SSRS. For example, if the clinician administers the C-SSRS but records the result in the narrative section of the progress note only, rather than in the C-SSRS flowsheet (where the data can be easily retrieved), will that C-SSRS score be captured and counted? Further, if the first C-SSRS item, “Have you wished you were dead or wished you could go to sleep and not wake up?” is not endorsed by the patient and no further questions are administered, does that C-SSRS administration still count?As another example, if a process improvement initiative is to schedule a follow-up visit within two weeks for every patient scoring ≥3 on the C-SSRS, should any subsequent visit count? Does the visit need to be in-person or would video visits, phone encounters, or secure message exchanges also satisfy the requirement? Does the visit need to be with the same clinician? Should the visit be with a behavioral health clinician or would a visit with an accompanying diagnostic code in any department by any clinician count? Does there need to be some kind of documentation that suicide risk was acknowledged? If the intent of the visit is to follow up on the elevated suicide risk, should there be some standard for visits that do and do not count? And if so, what should that standard be? There is insufficient evidence to guide these decisions, but these are empirical questions that we can address in the ZS evaluation project. Once specifications of what counts are determined then the challenge is to operationalize the metrics across different health systems with varying capture and documentation of follow-up visits.Finally, many variables of interest represent clinical processes that are not discretely captured and easily retrievable in the EHR or claims data. For example, safety planning is a recommended engagement intervention in ZS. A safety plan recognizes that individuals may have chronic or intermittent suicidal thoughts and, as the name implies, the goal is to prepare for how to respond to those thoughts. Safety planning is intended to be a tangible process that is often recorded on paper by the patient in collaboration with the clinician. As such, it can be difficult to identify when safety planning has occurred because paper plans are not always documented in the EHR. Furthermore, unlike the PHQ-9 or the C-SSRS that have discrete response categories, safety plans are unique to each patient and the majority of safety plan components require an open, unstructured response format. Text is often embedded in clinical progress notes and rarely in a discrete, retrievable field. Therefore, apart from time-intensive manual chart review, it can be difficult to determine whether and how many specific safety plan components  were completed.To address some of these challenges, all of the participating health systems are working together to build standardized EHR-based safety planning tools. While the health systems have agreed to use a core set of safety planning components (in most cases modeled after the Stanley-Brown template ), each rThe scope of the evaluation project does not include examining the quality of safety plans to better understand what actually happened in the safety planning exchange between the clinician and the patient. However, a subset of a few sites participating in the larger project have received supplemental funding to develop an advanced method using natural language processing (NLP) to determine when lethal means assessment and safety planning have been documented in the narrative, open-text sections of progress notes in the chart or in the electronic safety plan templates linked to smart data elements. Simple programs can give an indication of quality such as whether all sections of the safety plan were completed, whether phone numbers and crisis contacts were provided, or whether a minimum of three coping skills were documented. More advanced methods using NLP could include more sensitive content evaluation such as: whether there was inclusion of proper names of informal contacts, references to feelings or behaviors documented in the warning signs, and whether a plan for lethal means removal was documented when appropriate.This paper details the challenges of conducting a large-scale, multi-site suicide prevention evaluation and creating generalizable suicide prevention metrics using health system data. Specifically, we highlight the early experiences of our health systems as they have adopted ZS, demonstrated by three progressively more difficult challenges in measuring process improvements. First, mapping and reconciling suicide risk assessments involves a relatively standard care process (PHQ-9 or C-SSRS) that’s usually recorded as discrete data elements (responses to specific PHQ-9 or C-SSRS questions). There is some variability in PHQ-9 or C-SSRS versions across systems, but the number of variations is finite and relatively small. Then assessing adequate outreach and follow-up involves much more variable care processes (many routes for and types of outreach contacts) and more variability in how contacts are recorded. The number of variations is finite, but much larger. Finally, assessing adequacy of safety plans involves an infinitely variable care process (a highly variable interaction between two human beings) that can be recorded in an infinite number of ways (mostly in free text). This is the most challenging problem to overcome.To address each of these problems, our team has followed a similar approach. Whenever possible, when we have been engaged early in the cycle of care improvement, we have recommended that health system leaders standardize care processes and their documentation. We have advocated for using standardized screening tools and encouraged that measures be recorded in the EHR  or be universally retrievable . Serving as embedded researchers in our local ZS implementation teams and in the multi-system ZS learning collaborative has facilitated this partnership. When care improvement processes have been in place and we could not influence their design, we have engaged first with our clinical partners to identify all the relevant care processes and then with our health system data architects to identify the ways those processes are recorded in the EHR so we are not systematically missing important data.The challenges described herein are generalizable beyond suicide prevention work. The challenge of aligning process and outcome measures for comparison across health systems with differing source data is longstanding and universal. The challenge of deciding what should count as adequate and appropriate follow-up care has beset national quality improvement measures when well-intended metrics fail to specify qualifying services or do so in ways that exclude important care processes or include extraneous and irrelevant visits. The challenge of assessing safety planning is similar to the challenge of using EHR records to assess whether shared decision-making about treatment alternatives actually happened—where the presence of an indicator of shared decision-making is probably insufficient to conclude that meaningful patient engagement actually occurred. These are problems that deserve attention. In the context of this pragmatic evaluation, we resolve to address these issues as we seek to create generalizable process improvement metrics for broad use.


This review provides a brief overview of and commentary on currently available technology for the surgical treatment of obstructive benign prostatic hyperplasia causing lower urinary tract symptoms. This review provides references relevant to review and understand current technology that is clinically available. These developments reflect the ongoing needs to still perfect this surgical approach. The most recent advancement is aquablation, the first non-thermal technology to resect prostate tissue; studies demonstrate efficacy and safety at least equivalent to those of transurethral resection of the prostate (TURP) in glands up to 150 mL and improved outcomes in retrograde ejaculation9. In the past, most studies-based superiority of procedures on efficacy outcome parameters such as International Prostate Symptom Score and urodynamic parameters assessing obstruction relief as well as intraoperative and perioperative safety parameters such as bleeding, lengths of hospital stay, and infections. However, with the increased availability of novel and minimally invasive procedures, there is an increasing perception/awareness of these therapies as viable alternatives to medical therapy. Studies such as the BPH-6 studies in which a combination of quality-of-life parameters have increased the importance in outcome parameters that affect procedure choice such as retrograde ejaculation, need for catheterization, and recovery time have made what were technically less efficacious procedures more “superior” in these studies10. As such, many novel and minimally invasive procedures, including various prostatic stents and new technologies to resect prostate tissue or relieve prostatic outlet resistance, are still being aggressively developed. Many of these novel techniques, such as prostatic urethral lift and vapor ablation, are also designed to be used in an outpatient or office setting with minimal or local anesthesia.As intermediate options to medical therapy and TURP, both prostatic urethral lift and vapor ablation are generally office procedures that demonstrate superior safety profiles, especially in regard to sexual function, and that have acceptable efficacy compared with TURP14. The open prostatectomy has also evolved to be incorporated in many robotic prostatectomy procedures, although its overall complication rate and hospital stay are still much higher than those of many transurethral procedures17. The well-known laser-assisted enucleation of the prostate, holmium laser enucleation of the prostate (HoLEP), is one of the most well-studied procedures, demonstrating efficacy and safety superior to those of traditional open prostatectomy and TURP. However, its high learning curve has limited its widespread acceptance and utility20. Despite being initially limited to centers of excellence, it has undergone growing popularity due to the increasing number of trainees who have come from these centers of excellence as well as the improved technology of morcellation and instrumentation. The procedure has been in use since its initial introduction 20 years ago. However, laser procedures did not undergo durable popularity and widespread clinical utility until the introduction of high-power 532-nm laser technology, or “GreenLight” laser. Initially known as photoselective vaporization (PVP) and introduced as a viable technology with the first multicenter article in 200422, it is now the most common laser procedure in the world as a pure laser vaporization procedure. This technology has also evolved from an 80-Watt technology to a 180-Watt technology capable of vaporizing prostate tissue more efficiently and faster23. Many studies have demonstrated the laser’s clear superior safety profile in anticoagulated patients, high risk patients (high American Society of Anaesthesiologists score or Charlson index) and in large prostates28. Whereas most “GreenLight” procedures use pure vaporization techniques for glands up at about 80 g, vapoenucleations techniques have been applied to glands up to 376 mL29. Although there are many competing laser technologies, none has yet to compare in terms of ease of use, widespread utility, and short learning curve with a high safety profile.Not surprisingly, many currently used technologies, including many traditional therapies, have evolved. Because it removes the risk of dilutional hyponatremia by using normal saline as an irrigant, the standard TURP is now performed with bipolar technologies with equal efficacy and improved safety parameters33. The vaporization enucleation technique with GreenLight has allowed enucleation and completion of prostatectomy without a mechanical morcellator with outcomes superior to those of standard PVP techniques, especially in larger glands29.Over the last decade, the superior outcome efficacy and durability of HoLEP in comparison with open prostatectomy have suggested a modification in technique to incorporate enucleation with various technologies. Not surprisingly, laser enucleation of the prostate with GreenLight has evolved to demonstrate better efficacy with a maintained safety profile, especially in very large glands. The enucleation technique has expanded to include thulium laser technology as well as bipolar electrovaporization technology34.With the goal of preserving sexual function, the preservation of antegrade ejaculation has become an area of focus and interest with current evolving technologies. Studies with prostatic urethral lift and vapor ablation and aquablation incorporate ejaculation outcomes and demonstrate increased preservation of antegrade ejaculation compared with traditional techniques. Although preservation of bladder neck structures is often associated with preservation of antegrade ejaculation, especially in those with large intravesical middle lobes, the current modern approach is the preservation of paracollicular structures in laser, aquablation, and bipolar electrosurgical prostatectomy techniques


Identification of a biomarker for disease activity in eosinophilic granulomatosis with polyangiitis  remains an unmet need. This study examined the value of serum periostin, a marker of type 2 inflammation, as a measure of disease activity in patients with EGPA.Participants enrolled in a multicenter, prospective cohort of patients with EGPA were included in this study if they had disease activity (defined as Birmingham Vasculitis Activity Score [BVAS] > 0) during follow-up. Serum levels of periostin were measured at flare visit as well as two pre- and two post-flare visits, if available. The outcome of disease activity was assessed either with BVAS or Physician Global Assessment (PGA). Mixed-effect models were used to examine the association between periostin levels and disease activity. Comparisons were made with a historical cohort of healthy individuals and patients with asthma.In the 49 patients included in the study, the median periostin level was 60 ng/ml (IQR 50 to 73) in all visits and did not significantly change across visits. Multivariate analyses found no association between periostin level and presence or absence of flare according to the BVAS  but an increase in periostin level was significantly associated with greater disease severity during a flare according to the PGA . Periostin levels in EGPA were significantly higher than previously studied healthy controls and patients with asthma.In EGPA serum periostin level is modestly associated with greater disease severity during a flare but does not discriminate active from inactive disease. Periostin levels in EGPA are higher than in other previously studied cohorts, including healthy populations and patients with asthma, and are relatively stable over time. Eosinophilic granulomatosis with polyangiitis  is a multi-organ inflammatory disorder with common manifestations of asthma, rhinosinusitis, and peripheral blood eosinophilia. Other pWhile therapeutic management has improved outcomes in EGPA, relapses remain a significant issue. In particular, distinguishing other disease activity from EGPA versus an isolated asthma exacerbation or infection is challenging and has important ramifications, including the escalation of potentially toxic immunosuppressive treatment. Similarly, differentiating active inflammation from permanent damage caused by prior disease is often difficult. Commonly used laboratory markers, such as blood eosinophil count, serum immunoglobulin E (IgE), erythrocyte sedimentation rate (ESR), or C-reactive protein (CRP), do not reliably discriminate active disease in EGPA from non-EGPA disease or damage, and are unpredictably influenced by glucocorticoids and other immunosuppressive therapies.Serum periostin is a matricellular protein secreted by airway epithelial cells in response to stimulation by IL-13 and IL-4 and facilitates eosinophil-mediated type 2 inflammation and fibrosis, which are processes involved in EGPA. The rolThe objective of this study was to examine the role of serum periostin as a biomarker in patients with EGPA.Patients enrolled in the Vasculitis Clinical Research Consortium (VCRC) Longitudinal Study of EGPA were eligible for this study. The VCRC is comprised of over 15 international academic medical centers dedicated to conducting clinical and translational research in vasculitis. The Longitudinal Study of EGPA is an observational prospective cohort that collects clinical, laboratory, and blood samples of patients with EGPA at regular intervals  at 8 VCRC Centers in the United States and Canada. Patients are eligible to be enrolled in the cohort if they meet the American College of Rheumatology classification criteria for Churg-Strauss Syndrome  and do not have any other inflammatory or autoimmune conditions. This stFor this study, disease activity was defined according to a validated disease activity index, the Birmingham Vasculitis Activity Score (BVAS) with BVA® Periostin assay  which has been developed for clinical use and demonstrated to have high precision and reliability, p < 0.01). At the flare visit patients with an increase in periostin level also had a higher PGA score and were less likely to be receiving azathioprine or inhaled glucocorticoids.Among the subgroup of 20 patients who had an increase in serum periostin level between the pre-flare and flare visit, patients who experienced an increase in serum periostin had a higher median serum periostin level and blood eosinophil count at the time of the flare compared to those without a rise in periostin . As expeIn EGPA, identifying active disease is often challenging especially when non-specific symptoms occur, such as worsening of asthma or rhinosinusitis. The development of predictive or diagnostic biomarkers would greatly improve the ability to determine who will or is currently relapsing. This study aimed to investigate the utility of serum periostin, which has been found to be elevated in other eosinophilic syndromes. This study found that while serum periostin does not discriminate active from inactive disease in EGPA, based on the standard disease activity index (BVAS), a higher periostin level is modestly associated with greater disease severity according to physician assessment. Furthermore, periostin levels are higher in EGPA compared to previously-studied cohorts of healthy populations and patients with asthma, 20.Interestingly, two different measurements of disease activity yielded different results in this study. The BVAS is a useful tool which enumerates disease manifestations within the past 28 days while PGA is a summation measure based on the physician’s judgment. Therefore, it is possible, for example, that 2 patients with lung infiltrates will have the same BVAS but have different PGA scores if one patient has more severe symptoms and lung involvement than the other. The significant albeit modest association between periostin level and PGA but not BVAS suggests that periostin levels are sensitive to gradations in disease severity determined by the physician and no organ-specific involvement. In addition, the BVAS incorporates all manifestations within the past 28 days while the PGA score used in this study only evaluated disease activity on the day of the visit; thus, the use of immunosuppressive therapy  since the onset of symptoms may have mitigated expected changes in periostin level.While a statistically significant association was seen between PGA and periostin, the strength of the association was modest. This may be due in part to the mild severity of flares which may have contributed to less pronounced changes in periostin levels. As discussed previously, the large majority of patients in this cohort were receiving inhaled or oral immunosuppressive therapies which may also have affected results. Prior studies demonstrated that inhaled glucocorticoids affect serum periostin levels in asthma and the Notably, while the periostin levels were fairly stable across visits, they were overall much higher than previously-described cohorts, including patients with asthma, despite the concurrent use of immunosuppressive therapy. The use of periostin in distinguishing EGPA from other eosinophilic syndromes, including isolated asthma, deserves further exploration.There were several limitations to this study. Asthma and sinusitis, which in isolation are not considered to be features of active disease in EGPA, were poorly characterized and may have been important confounders in the analysis. Disease activity measurements relied in part on investigator judgment and may have been less sensitive to subclinical or low levels of disease activity. Lastly, as discussed above, the majority of patients were receiving immunosuppressive therapy during the flare visit which may further have dampened the performance of the biomarker. Dosage of immunosuppressive therapies was not available to further understand effects of medications on periostin level. However, this study closely resembled a real-world setting and, therefore, more accurately characterizes the effectiveness of periostin as a biomarker.Despite these limitations, the major strength of this study was its use of a fairly large, prospective longitudinal cohort of patients with this rare disease and with assessment and data collection performed by experts in EGPA. Standardized forms were used to collect data such as disease activity, medications, and laboratory values. Serum periostin in all samples was measured with a validated assay that was developed for clinical use.In conclusion, serum periostin level is modestly associated with severity of disease activity during flare according to the PGA score but does not discriminate active from inactive disease. Periostin is significantly higher in EGPA compared to healthy populations and patients with asthma. Further investigation in the utility of periostin as a biomarker in severe EGPA and differentiation of EGPA from other eosinophilic syndromes is warranted, perhaps in combination with other biomarkers or clinical variables.S1 Dataset(XLS)Click here for additional data file.