The need for clearer boundaries has been amplified by rapid product innovation. Kratom, derived from the tree Mitragyna speciosa, has long been consumed in Southeast Asia as fresh or dried leaves, including through chewing, brewing and aqueous preparations. Its contemporary US market is more diverse, extending to powders, capsules, tablets, gummies, tea bags, liquid shots and other formulations. The abstract cites an estimated 10 to 16 million US consumers. Surveys describe use for pain, mental health conditions, withdrawal symptoms and general wellness, but these reports are observational and often cannot identify the exact product involved. As a result, they cannot reliably establish which product composition is associated with any particular adverse outcome.

Native kratom leaf is chemically complex, containing alkaloids alongside flavonoids, polyphenolic compounds, triterpenoids, saponins, monoterpenes and secoiridoids. The proposed definition focuses on four principal alkaloids: mitragynine, paynantheine, speciogynine and speciociliatine. Mitragynine is generally the most abundant, representing a reported 51% to 82% of the alkaloid fraction, although it usually remains below 2.5% of total leaf weight. The framework sets an expected mitragynine range of 0.5% to 2.5% by dried leaf weight, with each of the other three major alkaloids at 0.1% to 1.0%. It also proposes a total alkaloid content below 3.0%.

A particularly consequential distinction concerns 7-hydroxymitragynine, or 7-HMG. It was initially considered a naturally occurring leaf constituent but is now recognized as an oxidative metabolite of mitragynine, detectable at trace levels in some post-harvest materials. The authors state that it should not exceed 0.01% by weight under their definition of unaltered leaf. This matters because its pharmacology differs sharply from that of mitragynine. A cited experimental study reported respiratory depression from 7-HMG comparable to morphine that was reversed by naloxone, whereas mitragynine increased respiratory frequency and was unaffected by naloxone. These are experimental findings about the compounds, not evidence that every kratom product produces those effects in users.

Category 1 covers traditional botanical preparations, including teas, decoctions and aqueous or aqueous-ethanol fluidized extracts containing less than 10% alkaloids. Category 2 covers more concentrated material, divided into semi-purified extracts with 10% to 40% alkaloids and purified extracts with 40% to 60%. Category 3 applies to isolates containing more than 60% alkaloids. Category 3a may qualify as a dietary ingredient when an isolate preserves the natural alkaloid ratios and no chemical alteration has occurred. Category 3b comprises isolated fractions or compounds that do not reflect the plant’s natural composition and that the authors recommend treating as novel drugs.

Category 4 covers substances that are not properly described as kratom: synthetic duplicates of natural alkaloids, chemically altered compounds and other novel drug molecules. Examples include semi-synthetic 7-HMG and mitragynine pseudoindoxyl, as well as synthetic alkaloids derived from 7-HMG or other kratom compounds. The authors argue that purity alone does not make an isolate natural. A product can be derived from the plant yet no longer preserve its chemical composition, which places it outside the scope of the traditional botanical. Their distinction also reflects a difference in evidentiary history: isolated pure kratom alkaloids do not have the same history of use in concentrated form as components commonly present in food, such as caffeine or vanilla.

The policy assessment places the proposal within a fragmented legal environment. The US Food and Drug Administration changed its treatment of kratom from an unapproved drug in 2012 to a dietary ingredient and new dietary ingredient in 2013. The Drug Enforcement Administration proposed scheduling mitragynine and 7-HMG in 2016 but later rescinded that action. In July 2025, the FDA recommended restricting 7-HMG products and proposed that the DEA schedule 7-HMG, while leaving kratom leaf products outside that recommendation; the perspective says no federal scheduling action had been taken by publication. State policies vary widely, encompassing bans, age restrictions, alkaloid limits, serving-size rules, labeling requirements and consumer-protection laws.

The authors reject what they describe as two equally inadequate extremes: blanket inaction and an unsupported ban on all kratom. They argue that inaction would leave concentrated, semi-synthetic and synthetic products exposed to consumers without the safety evidence or regulatory controls expected for conventional products. Conversely, they say available preclinical evidence, observational studies, Southeast Asian history of use and human clinical trials do not justify treating properly labeled leaf and traditional preparations as equivalent to Schedule I compounds. They also cite the World Health Organization’s conclusion that evidence was insufficient to recommend international scheduling. This is a policy assessment based on existing evidence, not a new demonstration that kratom is broadly safe or effective for any particular condition.

Manufacturing recommendations draw on the US dietary-supplement framework, including current good manufacturing practice requirements. Manufacturers would need written specifications for identity, purity, strength, composition and contaminants, supported by scientifically valid testing or examination. Required documentation would include test methods, evidence that those methods are suitable and valid, master manufacturing records, batch records and adverse-event collection. For leaf, Category 1 and Category 2 products, the authors also recommend visible serving measurements, limiting the number of servings in solid packages and providing a measured device for liquids. These measures are intended to reduce confusion and exposure from poorly controlled portions, rather than to imply that a standard serving eliminates risk.

Labeling proposals call for a supplement-facts panel showing the amount of each ingredient per serving and the percent daily value, with “no daily value established” displayed where appropriate for kratom. Labels should list ingredients in descending order of predominance and identify “kratom” in the ingredient list. Additional requested information includes serving size, daily serving recommendations, use instructions and duration, expiration date, a complete ingredient list, mitragynine percentage by weight and lot number. Products should also disclose 7-HMG content per serving or the method’s limit of detection. Suggested warnings cover pregnancy, breastfeeding, medical conditions, medication use, oral-only use, combining the product with alcohol or other drugs, possible physical dependence and discontinuation if adverse effects occur.

For properly prepared leaf and traditional Category 1 products, the perspective derives a recommended maximum of 40 mg mitragynine per serving and no more than two servings, or 80 mg, in 24 hours. The authors say this limit has reasonable assurance of safety when the products are prepared traditionally and used as directed, while stressing that it cannot automatically be applied to concentrated or altered products. For Category 2 extracts, they recommend that manufacturers demonstrate no chemical alteration during processing, obtain ingredient safety data and file the required new-dietary-ingredient notification. Absent such evidence, the same 40 mg limit may be considered only when mitragynine exceeds 40% of total alkaloids and 7-HMG remains below 0.01% on a dry-weight basis. No scientifically supported serving limits are proposed for Category 3b or Category 4 products, which the paper says should be regulated as unapproved drugs.

Subject of Research: Evidence-based product classification and regulation for kratom, extracts and synthetic alkaloid products in the United States

Article Title: Defining kratom: evidence-based policy guidelines for a rapidly evolving market

Article References: Berthold, E., Brown, P. N., Chan, M., Grundmann, O., McCurdy, C. R., Sharma, A., & Singh, D. (2026). Defining kratom: evidence-based policy guidelines for a rapidly evolving market. Frontiers in Pharmacology, 17, 1925809. https://doi.org/10.3389/fphar.2026.1925809

Image Credits: AI Generated

DOI: 10.3389/fphar.2026.1925809

Keywords: kratom, Mitragyna speciosa, mitragynine, 7-hydroxymitragynine, product regulation, dietary supplements, novel drugs, public health, adulteration, United States, Defining, evidence-based

The findings identify social and functional experiences as potentially important correlates of depression among cancer survivors, but the study does not establish that these factors cause depression. The analysis was led by Philip Baiden of the University of Texas at Arlington, with colleagues from institutions including the University of Texas at Rio Grande Valley, and was published in PLOS One on October 21, 2026. The researchers analyzed data from the 2023 and 2024 Behavioral Risk Factor Surveillance System involving adult cancer survivors in the United States.

Among those included, 21.8% reported receiving a diagnosis of depressive disorder at some time in their life. In other words, slightly more than one in five participants reported a lifetime diagnosis, while the remaining participants did not report such a diagnosis. The study focused on the relationship between that self-reported history and an expanding set of demographic, socioeconomic, health, behavioral, functional and psychosocial factors.

Previous work discussed by the authors had linked functional limitations, loneliness and inadequate social or emotional support to depression among cancer survivors, but the researchers said earlier studies were generally small and often grouped these factors together. Grouping can make it difficult to determine whether the different experiences contribute distinct associations with depression. This analysis therefore examined loneliness, functional limitations and social and emotional support separately and considered their relationships with a lifetime depressive-disorder diagnosis alongside other participant characteristics.

The study did not directly measure whether depression began before or after cancer, nor did it evaluate how the severity of a participant’s depressive disorder related to any of the included factors. To analyze the data, the team constructed a series of hierarchical logistic regression models. Model 1 included sociodemographic factors, and Model 2 added socioeconomic status.

Model 3 incorporated physical health status and health behaviors, while Model 4 was the fully adjusted model and also included functional limitations, social and emotional support, and loneliness. Receiver operating characteristic curves were presented for the four models, along with the variables included at each stage of adjustment. These models estimated associations between the measured characteristics and the self-reported lifetime diagnosis; they did not test an intervention, establish a causal sequence or determine what would happen if loneliness or another factor were reduced.

Loneliness produced the largest observed association among the psychosocial and functional variables in the fully adjusted analysis. The adjusted odds ratio of 2.72 means that survivors reporting loneliness had 2.72 times the odds of reporting a lifetime depressive-disorder diagnosis than those not reporting loneliness, with the estimate obtained after accounting for the other variables in Model 4. It does not mean that 2.72 times as many survivors were depressed, nor does it mean that every lonely survivor had a diagnosis.

Functional limitations carried an adjusted odds ratio of 2.05, while lack of social and emotional support was associated with an adjusted odds ratio of 1.43. These separate estimates show which measured characteristics remained associated with the reported outcome after adjustment, rather than proving that the factors are interchangeable or that changing them would change depression risk. Health behaviors were included in the analysis alongside the psychosocial and functional measures.

Physical exercise was associated with a decreased likelihood of reporting a lifetime diagnosis of depressive disorder. The supplied study report does not give a specific adjusted effect estimate for that association, and it should not be interpreted as evidence that exercise caused fewer diagnoses. Because the research was observational and the outcome and other variables were self-reported, the finding establishes a statistical relationship rather than a causal effect.

The analysis also cannot determine whether exercise preceded the depressive-disorder diagnosis or whether other factors included in the models contributed to the observed association. The scope and size of the dataset distinguish this investigation from the smaller studies highlighted by the authors. That scale does not eliminate the constraints of observational research, however.

The result concerns cancer survivors included in the 2023 and 2024 Behavioral Risk Factor Surveillance System data and their self-reported experiences, rather than every person who has received a cancer diagnosis. The outcome was also a reported history of diagnosis, not a contemporaneous clinical assessment of current depression. Lead author Baiden said the results show that cancer survivorship involves psychological and social challenges as well as physical recovery.

“Our study of more than 70,000 US cancer survivors found that approximately one in five reported having received a depression diagnosis during their lifetime,” he said. “These findings remind us that cancer survivorship involves much more than physical recovery.” He added that, as advances in cancer treatment allow more people to survive the disease, long-term mental health and overall quality of life require greater attention. These statements frame the implications of the observed associations; the research itself did not measure treatment advances or evaluate whether any survivorship program improved mental-health outcomes.

The authors also emphasized support from relationships outside formal healthcare. “Our findings reinforce the importance of social and emotional support in the lives of cancer survivors,” Baiden said, adding that support from family members, friends and communities matters alongside care from healthcare providers. Co-author Batholomew Chireh described the loneliness association as particularly striking because it remained after accounting for demographic, socioeconomic and health-related characteristics.

Chireh said the result suggests that addressing loneliness should be a priority in efforts to improve the well-being of cancer survivors. That is an implication of the finding rather than evidence from a tested loneliness intervention, and the study did not determine whether changing social circumstances alters the likelihood of a depression diagnosis. Co-author Judith S. Anagbonu said the results point to an opportunity for healthcare providers to assess loneliness, emotional support and functional limitations during cancer-survivorship care.

She said routine assessments could help identify survivors who may benefit from additional mental-health services and suggested that psychosocial screening, counseling, rehabilitation and community-based support could be integrated into follow-up care where appropriate. None of these services was tested in the analysis, so the study cannot establish that such a program would prevent or treat depression. Taken together, the results offer a large-sample view of factors associated with a reported lifetime depressive-disorder diagnosis among US cancer survivors: loneliness had the strongest measured relationship, functional limitations and insufficient social or emotional support were also associated with the outcome, and physical exercise was associated with a lower likelihood of reporting the diagnosis.

The central conclusion is one of association. Loneliness stood out even in the most fully adjusted model, but the observational evidence cannot establish causation, clarify the timing of depression relative to cancer, or show that interventions targeting these factors would change mental-health outcomes.

Subject of Research: Associations of loneliness, functional limitations and social support with lifetime depression diagnosis among US cancer survivors

Article Title: Modifiable psychosocial factors linked to depression among US cancer survivors

Article References: Modifiable psychosocial factors linked to depression among US cancer survivors. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: cancer survivors, loneliness, depression, mental health, psychosocial factors, functional limitations, social support, BRFSS, United States, Modifiable, psychosocial, factors

The underlying datasets have provided a foundation for numerous wildfire studies in the continental United States over the past two decades, but discrepancies among their records can complicate efforts to determine how many individual fires occurred and how large they were. Kasischke and French began by mining information from the three national sources, then combined it with regional reports, regional datasets and information found through searches of the world wide web. Fires not represented in the original national datasets were added when the broader search identified them as distinct events. The resulting inventory is intended to improve the information available for quantifying annual area burned and changes in extreme wildfire activity at different spatial scales.

Much of the work focused on records whose descriptions or measurements did not align. The researchers developed specific approaches for cases in which the same fire appeared with substantially different reported sizes, fires were labeled as complexes, several fires were contained within a larger event, smaller events merged into a larger one, events later joined, sizes were reported incorrectly or records were duplicated. These are consequential distinctions for event-based inventories because the treatment of a complex incident affects both the number assigned to a fire and the area attributed to it. The database seeks to reconcile these cases before researchers aggregate individual records into annual, regional or national totals.

Calculations using the integrated database increase total burned area for all United States regions. They also yield more extreme wildfires—defined in the study’s short summary as events larger than 5,000 hectares—and a larger area burned by events above that threshold. The authors present these results as differences between measurements generated from the new event database and those obtained from the records currently used by the fire-science community, rather than as projections of future wildfire activity. The comparison illustrates how the number, size and classification of recorded events can shape estimates of burned area and the prevalence of extreme fires across the full 1992–2021 inventory.

The work is a preprint and has not yet completed the journal’s review process. The supplied record states that the manuscript was received on 23 August 2026 and entered discussion on 21 October 2026, with a supplement also available from the preprint record. Its geographic scope is the continental United States, and its temporal scope is the three decades from 1992 to 2021. The database also depends on the quality and consistency of the national, regional and web-based information used to construct and reconcile it. Within those limits, the study’s central contribution is methodological: it provides a harmonized inventory of individual wildfire events designed to reduce uncertainties in the counts, areas and extreme-event measurements used in fire-science research.

Subject of Research: An integrated event database for measuring wildfires across the continental United States from 1992 to 2021

Article Title: An integrated wildfire event database for improved fire science research for the continental United States, 1992–2021

Article References: Kasischke, E. S., & French, N. H. (2026). An integrated wildfire event database for improved fire science research for the continental United States, 1992–2021. https://doi.org/10.5194/essd-2026-660

Image Credits: AI Generated

DOI: 10.5194/essd-2026-660

Keywords: wildfire database, burned area, extreme wildfires, United States, fire records, data reconciliation, event classification, 1992–2021, wildfire science, preprint, integrated, wildfire

The database contained 490,211 presence records and 441,012 absence records; 38,744 records from state or federal surveyors met the establishment criterion of at least two living insects or one egg mass. Analyses used biological years, which turned over on 1 May. By 2023, established populations extended from 35.63 to 43.21 degrees north and to 87.64 degrees west.

The main invasion covered large parts of Pennsylvania, New Jersey, Delaware and Maryland, with outlying populations established in several other states. Researchers delineated invaded areas at multiple spatial scales using square grids and α-convex hulls. A grid cell counted as invaded if it contained an established population in the focal year or any earlier year.

For the hulls, the researchers tested 19 α′ values from 1 to 100 kilometres, plus 1,000 kilometres to approximate the minimum convex hull. The tested scales ranged from much finer than county scale to much coarser, although county sizes vary geographically. Spread was estimated by converting delineated area to an effective range radius and fitting both simple linear regressions and logistic curves against time.

Model fit was compared using the small-sample corrected Akaike Information Criterion, or AICc. Logistic curves generally fitted better, consistent with a slow-fast-slow temporal pattern, but their changing slopes meant that a single spread-rate estimate was not appropriate. Across the tested grid scales, maximum logistic-model rates rose from 9.6 kilometres per year with 1-kilometre cells to 57.6 kilometres per year with 100-kilometre cells.

Corresponding α-convex hull estimates increased from 2.4 to 39.9 kilometres per year. Coarser scales also shifted the estimated peak from 2018 to 2020. Five-fold cross-validation was used to compare how well each boundary method separated presence from absence records.

Performance was assessed with precision, recall and Fβ scores, with β controlling the relative emphasis placed on recall. α-convex hulls generally outperformed grids when precision and recall received equal weight; the methods were more comparable at higher β values. The researchers selected α′ = 35 kilometres for subsequent satellite analyses from pooled cross-validation results at β = 2, which placed greater weight on capturing presence records and reducing the risk of omitting outlying populations. Using the 35-kilometre hulls, the researchers identified 153 distinct satellite populations during the invasion.

Of these, 46 remained separate from the primary invasion for at least one year. Only 29 one-year-old epicentres met the study’s sampling criterion of at least 20 recorded absences within a 5-kilometre buffer around their margins in both observed years. Median boundary displacement in the first year ranged from 0 to 10.6 kilometres and was generally larger in the second year, ranging from 0 to 15.4 kilometres.

Most satellite populations had first-year median displacement below 1.5 kilometres, compared with more than 20 kilometres annually around the primary invasion three to five years after detection. Direct measurements around the primary epicentre in Berks County, Pennsylvania, showed median boundary displacement of 20.7 kilometres in 2017, 20.3 kilometres in 2018 and 20.5 kilometres in 2019. The respective interquartile ranges were 14.5–30.9, 12.0–31.3 and 13.1–31.1 kilometres.

Boundary displacement slowed from 2020 through 2023, but the cause remains unclear. During that period, the invasion reached the eastern shoreline and extended outside Pennsylvania for the first time, state agencies used different sampling plans, and survey effort was reduced by the COVID-19 pandemic and associated shutdowns. The authors proposed climatic conditions, accumulating natural enemies and more frequent small populations near the invasion margin as possible explanations for the slowdown, but the study did not establish their causal contributions.

The analysis also has important limitations. Recorded absences may reflect failed detection rather than true absence, and public reports may include false positives. Boundaries were drawn from state and federal presence records, with absences used for evaluation rather than boundary construction.

Satellite estimates were based on relatively few sufficiently sampled epicentres, and the cross-validation did not test sensitivity to the proportion or spatial arrangement of withheld records. Overall, the findings show that spatial aggregation can substantially alter measured invasion rates and estimated boundary locations, making scale selection an essential part of spread analysis. The authors recommend examining land cover, transport flows and environmental conditions, incorporating temperature-dependent population dynamics, and improving estimates of detection and false-positive rates in future analyses.

They also argue that the observed pattern of slower initial expansion around satellite populations provides a historical basis for surveillance and early action.

Subject of Research: Temporal and spatial-scale analysis of spotted lanternfly spread in the United States

Article Title: Leveraging spatial scale and temporal variation to track the spread rate of invasive spotted lanternflies ( Lycorma delicatula )

Article References: Keller, J., De Bona, S., & Helmus, M. R. (2026). Leveraging spatial scale and temporal variation to track the spread rate of invasive spotted lanternflies (Lycorma delicatula). NeoBiota, 106, 287-307. https://doi.org/10.3897/neobiota.106.177041

Image Credits: AI Generated

DOI: 10.3897/neobiota.106.177041

Keywords: spotted lanternfly, Lycorma delicatula, invasive species, invasion spread, spatial scale, boundary displacement, cross-validation, surveillance, United States, Leveraging, spatial, scale

The analysis did not directly count individuals’ FGM/C status. Instead, it combined population and prevalence data to estimate how many people were likely to have undergone the practice and how many remained potentially at risk. Population estimates came from the 2015–2019 American Community Survey Public Use Microdata Sample. Unlike earlier US studies that primarily selected people by place of birth, the study selected its population primarily by ancestry.

Age-disaggregated prevalence estimates were derived from Multiple Indicator Cluster Surveys, Demographic and Health Surveys and other nationally representative surveys using methods developed in earlier work by Callaghan. The included survey samples were described as nationally representative at the 95% confidence level, with reported FGM/C error margins between 0.2% and 1.78%.

Earlier US estimates used relatively simple calculations. Jones and colleagues multiplied the relevant population by an average prevalence measure, while Goldberg and colleagues used age-based prevalence assumptions. European studies frequently applied an additional adjustment for migration and acculturation, commonly estimating that native-born girls had half the risk of foreign-born girls. Callaghan’s model aimed to represent variation that could be concealed by combining these elements into a single adjustment and by assuming a common risk boundary for all communities.

The new model incorporated a coefficient for socio-economic selective migration, drawing on differences between national prevalence and prevalence among more educated, wealthier or urban groups. It also introduced an Ethno-religious Loading Factor for Nigerian and Egyptian populations. This factor was used in sensitivity analyses to illustrate how ethnic and religious selection might affect estimates, rather than to claim an exact measured effect, and results were presented both with and without it.

Three approaches were used to estimate the proportion of FGM/C risk occurring before migration, after migration and in the future. The first used a universal risk boundary of age 19, consistent with an earlier framework. The second replaced that boundary with an age above which FGM/C was considered rare in each relevant community. The third fitted a generalised gamma distribution to age-of-cutting data, providing a continuous probability curve for estimating risk at individual ages. All fitted quartiles were within the 90% confidence level of the original quartiles, and 95.2% were within the 95% confidence level.

The third approach assumed that the age distribution of FGM/C was unimodal, although this may be less suitable for Liberia, where survey data suggested a bimodal distribution. The model also did not include the possible effects of long-term residence in refugee camps before migration, transnational travel or acculturation. The Ethno-religious Loading Factor values for Nigeria and Egypt were explicitly described by the author as speculative and intended to demonstrate a mechanism’s potential impact rather than predict its exact scale.

All three migration-timing approaches produced the same total estimate of 587,386 women and girls in the affected population. However, the more detailed methods classified more people as already living with FGM/C and fewer as remaining at risk. Relative to the age-19 approach, the generalised gamma model reclassified 85,512 women and girls from the at-risk category to the living-with category, representing a 66.8% reduction in the estimated number considered at risk.

Under the hypothesised deterrence scenario, represented by a Prevention Impact Factor of 0.25 and incorporating the hypothetical effect of ethnic and religious selective migration, the model estimated that the Jones method had overstated the overall impacted population by 12.9%, or 79,817 people, while the Goldberg method had overstated it by 6.3%, or 36,388. In the generalised gamma results, 94.1% of the estimated affected population, or 508,953 people, were classified as likely already living with FGM/C; 5.9%, or 31,826, were classified as potentially at risk. These figures describe a model-based population classification rather than a direct prevalence survey. The findings change the composition of the modelled population rather than its total size, and should not be interpreted as proof that earlier studies directly misclassified individual women’s status.

Subject of Research: Modelling migration-related FGM/C prevalence and risk among US immigrant and diaspora populations

Article Title: Modelling the impact of migration on FGM/C prevalence and risk in immigrant and diaspora populations

Article References: Callaghan, S. (2026). Modelling the impact of migration on FGM/C prevalence and risk in immigrant and diaspora populations. PLOS One, 21(10), e0360038. https://doi.org/10.1371/journal.pone.0360038

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360038

Keywords: female genital mutilation, FGM/C, migration, diaspora populations, United States, selective migration, age of cutting, prevalence modelling, acculturation, American Community Survey, Modelling, impact

Researchers analyzed 2021 data from the Behavioral Risk Factor Surveillance System. The study included 88,319 men, of whom 3,702 self-identified as gay or bisexual. Health-related quality of life was assessed through three outcomes: physical-distress days, mental-distress days, and activity-limitation days during the previous 30 days. The researchers compared these outcomes between sexual-minority and heterosexual men and examined sociodemographic and behavioral correlates of quality of life among the gay and bisexual men.

Sexual-minority men reported an average of 6.82 mental-distress days in the previous 30 days, compared with 3.19 among heterosexual men. They also reported 5.42 activity-limitation days, compared with 4.92, while physical-distress days were 3.65 and 3.44, respectively. Within the sexual-minority group, age and employment status were strongly associated with the measured quality-of-life outcomes. Compared with retired men, men unable to work reported substantially more physical-distress, mental-distress, and activity-limitation days.

Leisure-time physical activity was associated with fewer unhealthy days across all three outcomes, while current smoking was associated with more mental-distress days among gay and bisexual men. The group also reported higher levels of both health-promoting behaviors and risk behaviors, including smoking and binge or heavy drinking. These findings are based on the study abstract, which does not report confidence intervals, model estimates, response rates, or other methodological details needed for fuller assessment of precision and generalizability. The observational associations do not establish that the measured behaviors caused differences in health-related quality of life.

Subject of Research: Associations between health behaviors and health-related quality of life among U.S. gay and bisexual men

Article Title: Association between health-related quality of life and health behaviors among men who have sex with men in the United States: a nationwide population-based study

Article References: Chan, A. S. W., Tam, H. L., Leung, I. S. H., Asiamah, N., Li, S., & Mo, P. K. H. (2026). Association between health-related quality of life and health behaviors among men who have sex with men in the United States: a nationwide population-based study. BMC Psychology. https://doi.org/10.1186/s40359-026-05634-8

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05634-8

Keywords: health-related quality of life, gay and bisexual men, mental distress, physical activity, smoking, alcohol use, employment status, population-based study, United States, Association, between, health-related

For the expanded BRICS grouping, the researchers applied Bayesian hierarchical methods to improve inference stability in the presence of multicollinearity and parameter uncertainty. The authors describe this as the first Bayesian hierarchical application of the neo-Schumpeterian diffusion model. The supplied evidence consists of the study abstract, so the full methods, results and limitations cannot be assessed here.

The abstract identifies several factors associated with technological growth. Innovative human capital is linked to both imitation and domestic innovation, while institutional quality, tacit knowledge transfer, foreign direct investment attraction and information and communication technology diffusion are reported as significant drivers. The estimated effects of research and development intensity, digital investment, financial development and education investment are described as contingent on governance quality and absorptive capacity, indicating that financial inputs alone were not sufficient in the model without supportive institutions and capabilities.

These results are estimates from an observational modeling framework rather than direct experimental findings. The abstract reports convergence toward the frontier and identifies associated determinants, but it does not establish that individual factors caused the estimated technological changes. Its scope is limited to the specified BRICS groupings and the 1996–2022 period, and the supplied material does not provide country-level effect sizes, uncertainty intervals or details of robustness tests.

Subject of Research: Bayesian modeling of technology diffusion and convergence in BRICS economies

Article Title: Bayesian hierarchical modeling reveals how Schumpeterian technology diffusion drives BRICS convergence toward the United States frontier

Article References: Pham, K. X., & Thach, N. N. (2026). Bayesian hierarchical modeling reveals how Schumpeterian technology diffusion drives BRICS convergence toward the United States frontier. Discover Sustainability. https://doi.org/10.1007/s43621-026-04848-5

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04848-5

Keywords: BRICS, technological convergence, Bayesian hierarchical models, technology diffusion, domestic innovation, absorptive capacity, institutional quality, human capital, United States, Bayesian, hierarchical, modeling

The study used administrative medical and pharmacy claims from the Komodo Research Database for January 2017 through September 2023. Adults were included if claims showed a neurologist-confirmed myasthenia gravis diagnosis after at least 12 months of continuous insurance eligibility and if they had at least 12 months of continuous eligibility after diagnosis for follow-up. The database draws from more than 150 payers and represents more than 160 million patients across the United States, including people with commercial, Medicare Advantage and Medicaid coverage.

The analytic cohort had a mean age of 61.1 years, and 49.1% were female. Most participants were White, lived in the South and had commercial insurance. Common physical comorbidities included hypertension, obesity and diabetes. A multivariable Cox proportional hazards model examined associations between baseline characteristics and the first claims-defined exacerbation or crisis while adjusting for the other variables included in the model. Because the claims did not contain standardized severity measures such as MG-Activities of Daily Living scores, baseline symptoms were used as proxies for disease severity.

During follow-up, 3,045 patients had a first clinical event, with a mean time of 5.4 months from the index date to the event. Of these events, 98.2% were classified as myasthenic exacerbations and 1.8% as crises. Baseline factors associated with a higher event hazard included immunoglobulin use (hazard ratio, 1.54), dysarthria (1.45), general or other muscle-specific weakness (1.38), use of non-steroidal immunosuppressants (1.37), dysphagia (1.28), weight loss (1.27), dyspnea (1.23) and ptosis (1.20). Absence of another neurological condition was associated with a hazard ratio of 1.20, absence of another autoimmune disorder with 1.18, and male sex with 1.15. All of these associations had p-values below 0.05 and do not establish causation.

For the burden analysis, the researchers formed a clinical-event cohort of 2,657 patients and a no-event cohort of 3,092 patients, each with at least 12 months of follow-up after its index date. The index date was the first event for the clinical-event cohort and a random date with a medical visit for the no-event cohort. Entropy balancing reweighted the no-event group on age, sex, race and ethnicity, geographic region, payer, index year, time since initial myasthenia gravis evidence and baseline diagnosis.

After balancing, patients with an event had 6.02 times the rate of all-cause inpatient admissions, 1.91 times the rate of emergency-department visits and 1.58 times the rate of outpatient visits during the 12 months after indexing; all reported p-values were below 0.05. They also had 5.82 times as many inpatient days: 9.01 days compared with 1.55. For myasthenia gravis-related utilization, the corresponding rate ratios were 16.09 for inpatient admissions, 12.23 for emergency-department visits and 3.96 for outpatient visits.

Mean all-cause total healthcare costs per patient per year were $95,821 in the clinical-event cohort and $25,029 in the no-event cohort, a mean difference of $70,792 (p<0.001). Pharmacy and medical costs each accounted for roughly half of that difference. The $18,103 difference in immunoglobulin costs represented 51.3% of the pharmacy-cost gap. Inpatient costs contributed $25,271, or 71.1%, of the medical-cost difference. Mean myasthenia gravis-related annual costs were $73,641 with an event and $6,469 without one, a difference of $67,172 (p<0.001). Monthly all-cause costs among event patients rose from $5,786 before the event to $19,325 in the following month and remained between $6,626 and $7,268 in subsequent months.

The findings support the value of early risk stratification but remain observational. The claims algorithm may have included some patients with ocular rather than generalized disease because the relevant diagnostic codes do not distinguish those forms. Exacerbations and crises could also have been misclassified, and the analysis did not exclude encounters involving concurrent conditions such as infection. Standardized clinical severity measures and unmeasured factors such as socioeconomic status were unavailable. The study period overlapped the COVID-19 pandemic, and results may not apply to uninsured people or those covered by payer types outside the database. Consequently, the study identifies associations and resource use, rather than demonstrating that any treatment or clinical action prevents events.

Subject of Research: Clinical-event predictors and healthcare costs associated with generalized myasthenia gravis in the United States

Article Title: Exacerbations and crises in generalized myasthenia gravis: predictors and associated economic burden in the United States

Article References: Grover, K., Cloutier, M., Coteur, G., Boonmak, P., El Khoury, A. C., Zhdanava, M., Tardif-Samson, A., Wang, Y., & Gandhi, K. (2026). Exacerbations and crises in generalized myasthenia gravis: predictors and associated economic burden in the United States. Frontiers in Neurology, 17, Article 1919726. https://doi.org/10.3389/fneur.2026.1919726

Image Credits: AI Generated

DOI: 10.3389/fneur.2026.1919726

Keywords: generalized myasthenia gravis, myasthenic exacerbation, myasthenic crisis, healthcare resource use, healthcare costs, claims analysis, United States, Exacerbations, crises, generalized, myasthenia, gravis

The researchers developed separate habitat and bioclimatic suitability models for the spotted lanternfly, Lycorma delicatula, and combined their probability maps to identify locations meeting broad-scale climatic and local environmental requirements. Models were calibrated principally with records from the species’ native range in mainland China rather than with occurrences from invaded regions, where populations may still be expanding or may have been introduced into unsuitable environments. The habitat model incorporated elevation, land cover, built-up areas, cultivated vegetation, natural vegetation and a composite layer representing numerous potential host plants. The bioclimatic model used temperature and precipitation variables at a broader geographic scale.

Performance was strong for both components. The best habitat models had area-under-the-curve values of 0.870 to 0.900 and true skill statistic values of 0.585 to 0.697, while the strongest bioclimatic models reached area-under-the-curve values of 0.971 to 0.985 and true skill statistic values of 0.855 to 0.898. The combined map achieved a Boyce index of 1 in the native-range calibration area and again in the eastern United States, indicating that occurrence records were strongly concentrated in locations the model rated as suitable. By contrast, the value of −0.133 for South Korea indicated a marked mismatch between predicted suitability and the scattered locations where the insect has been recorded.

Host plants were the most influential habitat variable, with an importance value of 0.542, followed by built-up land at 0.358. Cultivated and managed vegetation, herbaceous cover and elevation made smaller contributions. The model associated the highest occurrence probability with lowlands to mid-mountain areas, with an optimum near 750 metres above sea level. For climate, the mean temperature of the coldest quarter was the dominant predictor, with an importance value of 0.591 and apparent optimal conditions around 0 °C, chiefly between −5 and +2 °C. The minimum temperature of the warmest month and mean diurnal temperature range also influenced the fitted responses. The authors note that host distributions and land cover are themselves shaped by climate, so the habitat layer indirectly captures some climatic influence as well as local habitat availability.

Globally, the model identified eastern China as the most favorable part of the native range, the central-eastern United States as the largest continuous suitable region outside Asia, and nearly all of Japan as highly suitable. Additional potentially suitable areas were scattered across Europe, mostly south of 55 degrees north. In Europe, the mapped zone extended across central-eastern France, Switzerland, the Benelux countries and Germany, as well as northern Italy, Slovenia, Croatia, the Danube basin, parts of southeastern Ukraine and the Northern Caucasus. California was not identified as a critical invasion area; the researchers interpreted reported detections there as likely adventive occurrences sustained by transport rather than evidence of expanding populations.

To estimate movement rather than merely identify favorable habitat, the team analyzed 11,326 occurrence records from the eastern United States, where the invasion has been closely documented. Distances between the closest records in consecutive years produced a bootstrapped median of 1,720 metres, with a 95% confidence interval of 1,680 to 1,766 metres. The bootstrapped 99th percentile was 25,418 metres, with a 95% confidence interval of 18,479 to 37,038 metres. This upper estimate was treated as the maximum annual dispersal distance, and records lying beyond it were classified as likely human-mediated introductions rather than ordinary expansion from the initial population.

The researchers then converted predicted environmental suitability into landscape resistance and tested whether linear or nonlinear logistic resistance best reproduced the observed eastern United States expansion. The best-fitting configuration used a logistic function with a midpoint parameter of 0.5, a steepness value of 15 and a cumulative resistance threshold of 1,200. Under this model, the estimated invaded area increased from 1,797 square kilometres in 2015 to 8,611 in 2016, 35,724 in 2018, 72,511 in 2020 and 127,721 in 2024. The model’s year-by-year boundaries captured occurrences consistent with spread from the first introduction, but overlapping records also revealed secondary invasion hotspots that transport had apparently helped create.

Ten-year scenarios beginning from the species’ current distribution suggested two major fronts in the United States. One lies east of the Appalachian Mountains toward the Atlantic coast, where much of the suitable landscape has already been colonized. The second extends inland, west of the Appalachians and south of the Great Lakes, where the model projected movement toward the continental interior and near-complete occupation of the most suitable areas by the end of the period. Populations in California, the central-western states and Florida were considered less likely to develop into expanding invasions. South Korean expansion was projected to concentrate along the southwestern coast, but the interpretation remains uncertain because scattered records appear to reflect repeated human transport. In Japan, where environmental suitability is high, populations could spread rapidly across central and southern Honshu, without fully saturating suitable northern areas within ten years.

European simulations showed that a successful invasion would depend on establishment in suitable terrain rather than an isolated detection alone. The single iNaturalist record from Madrid was treated as a possible occurrence, but the surrounding area was modeled as too unsuitable to support substantial subsequent expansion from that point. Hypothetical introductions at Milan Malpensa Airport, Paris Charles de Gaulle Airport and Hamburg Port were more consequential because they were situated in highly suitable areas. The authors therefore interpret the European map as a conditional risk scenario: establishment at favorable entry points could enable rapid spread, whereas a population in a marginal environment may not. The projections did not include future human-mediated translocations, which the researchers say could accelerate expansion beyond the modeled trajectories.

The findings provide a map-based assessment rather than a measured ten-year outcome. They distinguish broad physiological limits imposed by climate from finer-scale filters involving host plants, urban habitat and local land cover, and they treat natural spread separately from transport-assisted establishment. South Korea’s poor model agreement and the uncertain status of scattered records in other invaded areas demonstrate the limits of predicting an insect whose distribution is being shaped by both ecological dispersal and human movement. Even so, the study identifies regions where establishment appears most consequential and where rapid expansion would be plausible. It also shows why records of introduction cannot automatically be interpreted as evidence that a species has occupied the full range of suitable habitat.

Subject of Research: Global habitat suitability and invasion scenarios for the spotted lanternfly

Article Title: Predicting the global distribution and invasion scenarios of the Spotted Lanternfly, Lycorma delicatula (White, 1845) ( Hemiptera , Fulgoridae )

Article References: Ruzzier, E., Scaccini, D., Tirozzi, P., Orioli, V., Dondina, O., Di Giulio, A., Pozzebon, A., & Bani, L. (2025). Predicting the global distribution and invasion scenarios of the Spotted Lanternfly, Lycorma delicatula (White, 1845) (Hemiptera, Fulgoridae). NeoBiota, 103, 267-298. https://doi.org/10.3897/neobiota.103.154246

Image Credits: AI Generated

DOI: 10.3897/neobiota.103.154246

Keywords: spotted lanternfly, species distribution modelling, biological invasion, climate suitability, habitat suitability, range expansion, dispersal modelling, grapevine pest, Europe, United States, Japan, South Korea

Following Joanna Briggs Institute methodology and reporting under PRISMA-ScR guidance, the authors searched PubMed, PsycINFO and Web of Science for publications issued from January 2015 through October 2025. Eligible findings were then synthesised thematically. Twenty-one articles reached full-text assessment, but three met the inclusion criteria.

These studies represented three different national settings: the United States, India and the Netherlands. Across the included reports, exchange programmes were associated by their participants with greater awareness of both shared clinical problems and differences among settings. Participants also recognised more clearly how culture and the organisation of mental health care interact with clinical practice.

Professional development emerged as a third major theme in the thematic synthesis. These results describe the benefits reported in a small set of pilot studies rather than a demonstrated effect on care. The review does not establish that cross-national exchanges improve treatment decisions, service delivery or health outcomes for children and adolescents.

Nor can its three included studies identify a universally preferable programme design or determine which exchange format works best for particular participants or settings. The findings are also constrained by the limited number and geographic scope of eligible publications, which prevents strong conclusions about the reach or consistency of the observed themes. The authors recommend further research to assess the added value and cost-effectiveness of cross-national exchange formats and to examine which approaches suit which participants and settings.

The review was preregistered on the Open Science Framework, and its authors state that additional evidence is needed to clarify the value of the programmes. In its current form, the evidence supports a cautious conclusion: cross-national clinical exchange in child psychiatry can raise awareness of cultural and health-system differences and contribute to professional learning, but the review does not demonstrate downstream clinical benefits.

Subject of Research: Scoping review of cross-national clinical exchange in child and adolescent psychiatry

Article Title: Cross-national clinical exchange in child psychiatry across cultural contexts and mental health systems: a scoping review

Article References: de Veen, B. T. H., Bringmann, K. F., Herpers, P. C. M., Staal, W. G., Scholte, R. H. J., van Dongen-Boomsma, M., & Deschamps, P. (2026). Cross-national clinical exchange in child psychiatry across cultural contexts and mental health systems: a scoping review. BMC Medical Education. https://doi.org/10.1186/s12909-026-10356-x

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10356-x

Keywords: child psychiatry, cross-national exchange, scoping review, cultural context, mental health systems, clinical education, professional development, United States, India, Netherlands, Cross-national, clinical