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Alzheimer’s disease (AD) is characterized by profound metabolic dysfunction and disturbances in gut–brain axis signaling. Ketogenic diet (KD) has demonstrated metabolic and cognitive benefits in both preclinical and clinical studies. However, factors that determine individual responsiveness or non-responsiveness to KD interventions remain poorly understood. Emerging evidence suggests that gut microbiome composition plays a critical role in modulating these factors. This study examined how KD responsiveness, determined by fecal microbiota transplantation (FMT) derived from human KD responders (RES) or non-responders (nRES)- influences cognition, gut barrier function, neuroinflammation, and microbial structure in 3xTg-AD mice. We further evaluated whether supplementing KD with a novel Synbiotic Yogurt (SY) formulated by our team could augment or restore responsiveness. We hypothesized that RES microbiota would confer superior KD-driven benefits and that KD-SY would synergistically improve metabolic and neurobiological outcomes, particularly among nRES recipients. Adult 3xTg-AD mice were antibiotic-cleansed and randomized to receive Control-, RES-, or nRES – FMT, while maintained on KD for four weeks. A second cohort received KD supplemented with SY or non-fat milk along with RES- or nRES-FMT. Behavioral tests, gut permeability assay, serum inflammatory markers, brain amyloid beta (Aβ), intestinal morphology, gene expression, and 16S rRNA microbial profiling were measured. RES-FMT recipients showed early improvements in spatial memory (Y-maze and novel object recognition) and consistently lower Aβ accumulation in cortex and hippocampus. They also showed higher synaptophysin and IL-10 expression. In contrast, nRES-FMT mice exhibited distinct microbiome clustering, lower microbial diversity, enrichment of Proteobacteria, and impaired gut barrier function relative to RES-FMT recipients. Functionally, specific taxa like Enterococcus, Enterobacter, and Paenibacillus were associated with greater vulnerability to AD-related pathology, while Akkermansia, Bifidobacterium, and Muribaculum were linked with lower vulnerability. SY supplementation improved metabolic and gut barrier indices across groups characterized by increased circulating ketone levels, lowered fasting glucose and glucose-ketone index, and decreased gut permeability. nRES-SY mice showed the strongest gains in recognition memory and reductions in brain Aβ1–42 burden. SY increased expression of barrier- and inflammation-modulating genes, including occludin, APLP2, and IL-10. Microbiome analysis demonstrated higher microbial diversity and enrichment of beneficial genera such as Paralactobacillus, Eubacterium, and Muribaculum. These findings show that KD responsiveness is strongly determined by gut microbiota composition and that SY supplementation can enhance or rescue metabolic, cognitive, and microbial outcomes, particularly in nonresponders. This supports a precision-microbiome strategy combining metabolic and Synbiotic interventions to improve gut–brain axis function in AD. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Extracellular vesicles (EVs) are lipid-bound vesicles secreted by cells, including exosomes, microvesicles, and apoptotic bodies. Proteomic analyses of EVs, particularly in relation to cancer, reveal specific biomarkers crucial for diagnosis and therapy. However, isolation techniques such as ultracentrifugation, size-exclusion chromatography, and ultrafiltration face challenges regarding purity, contamination, and yield. Contamination from other proteins complicates downstream processing, leading to difficulties in identifying biomarkers and interpreting results. Future research will focus on refining EV characterization for diagnostic and therapeutic applications, improving proteomics tools for greater accuracy, and exploring the use of EVs in drug delivery and regenerative medicine. In this review, we provide a bird’s eye view of various challenges, starting with EV isolation methods, yield, purity, and limitations in the proteome analysis of EVs for identifying protein targets.

Abstract Hemopoietic histocompatibility (Hh) Ag are noncodominantly expressed on bone marrow stem cells and other normal and neoplastic cells of hemopoietic origin. H-2/Hh-1 allogeneic or parental-strain bone marrow grafts are eliminated in a determinant specific manner by NK cells. In inbred mouse strains, seven Hh-1 alleles representing combinations of five different Hh-1 antigenic determinants are described. Each Hh-1 allele maps in the vicinity of H-2D, and the genes that map to Hh-1 are transacting regulatory genes. The expression of a particular determinant depends on the absence of the regulatory gene and the presence of the appropriate structural gene. The primary focus of this study is to ascertain whether the Hh-1 phenotype and the serologic H-2DL typing are always correlated or whether recombinant can separate the two. To achieve this, we used a panel of irradiated hosts that are able to recognize the different Hh-1 determinants on the bone marrow cells of congenic intra-H-2 recombinant donors. We report: 1) the majority of strains show a correlation between Hh-1 and H-2DL: 2) B10.RQDB and B10.WB strains dissociate Hh-1 from Lb: 3) nine H-2S/D interval recombinant strains exhibit no correlation between the H-2DL type and Hh-1 phenotype; and 4) in two strains from this group, B10.D2 (R106) and B10.RSF5, H-2S/D crossovers occurred within Hh-1r, (Hh-1 regulatory). We conclude that Hh-1r is a distinct regulatory locus mapping telomeric of H-2S and centromeric of, although probably closer to, H-2D.

Abstract OBJECTIVES: The impact of treatment modifications including replacement of alkylating agents based regimens and improvement in the practices of radiation oncology on the risk of secondary cancers (SCs) in Hodgkin's lymphoma (HL) survivors is unknown in the United States (U.S.). This study analyzed the trends of secondary cancer risks among the survivors of HL in the U.S. METHODS: The HL patients diagnosed during 1973-2014 were identified from the Surveillance, Epidemiology and End results (SEER) database. Due to differences in the treatment practices in HL, the whole cohort was divided into three time-periods: 1973-1986, 1987-2000 and 2001-2014. We compared the risk of SCs in the HL patients with the risk expected in the U.S. general population over the three study periods. RESULTS: With a follow-up of 23,864 HL survivors for 284,730 person-years (PY), 3260 secondary cancers were diagnosed, with standardized incidence ratio (SIR) of 1.97 (95% CI, 1.9-2.04) which resulted in 56.56 excess cancers per 10,000 person-years. SIR for any SCs in women (SIR 2.17; 95% CI 2.06-2.28) was significantly higher than in the men (SIR 1.84; 95% CI 1.75-1.92). The highest SIRs were observed for AML (SIR, 9.9; 95%CI, 8.3-11.9), NHL (SIR, 5.8; 95% CI, 5.3-6.4) and salivary gland tumors (SIR, 6.04; 95% CI, 4-8.8) while lung cancer (23.6%) and breast cancer (27.4%) contributed most to the excess risk in males and females respectively. The SIR for any SCs was maximum in the period after 15 to 20 years from the diagnosis of HL and remained high for more than 20 years after the diagnosis of HL (SIR for ≥ 20 years, 2.34; 95% CI, 2.19 to 2.5). A statistically significant decrease in the overall SIRs of SCs was observed in HL patients diagnosed during 1987-2000 (SIR 1.82 95% CI 1.72-1.93) and 2001-2014 (SIR 1.66 95% CI 1.51-1.82) as compared to the patients diagnosed in 1973-1986 (SIR 2.24 95% CI 2.13-2.35). (Figure 1) The decline in the overall SIR was mostly due to decline in the digestive tract and breast cancers. The SIRs of most of the other solid tumors and hematological malignancies including individual risks for NHL and AML did not decrease in the more recent study periods. Moreover, the decline in the SIRs of solid tumors was noticed only in the patients age below 60 years old. The female patients diagnosed in the most recent period were at lower risk of developing breast cancers (SIR 0.56 95% CI 0.34-0.86) as compared to the general population. The decline in the risk for secondary cancers was observed only after 10 years from the diagnosis of HL. After making adjustments for age, gender and race, patients diagnosed during 1973-1986 were at 12% higher risk of developing SCs (HR 1.12 95% CI 1.03-1.23 p=0.01) as compared to the patients diagnosed during 1987-2000. The hazard ratio for developing SCs in the patients diagnosed during 2001-2014 was not different from the patients diagnosed during 1987-2000 (HR 1.02 95% CI 0.9-1.2 p=0.74). CONCLUSIONS: Although, the overall risk of secondary cancers in patients with Hodgkin's lymphoma has declined after the modifications in Hodgkin's lymphoma treatment, apart from the digestive tract and breast cancers the risk has not changed significantly at most of the individual sites. The risk of secondary cancers is still 70% higher than the general population and is maximum 15-20 years from the diagnosis of Hodgkin's lymphoma. Thus close follow up with active surveillance for secondary cancers is crucial for the long term survivors of Hodgkin's lymphoma. Disclosures Ailawadhi: Novartis: Consultancy, Honoraria; Pharmacyclics: Research Funding; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria.

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.

Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.

Background: Survival of patients with MM has improved significantly over recent years due to therapeutic advancements. Population-level data has shown that a substantial proportion of MM patients may die early after their diagnosis and real-world evidence regarding early mortality (≤6 months after MM diagnosis) has been conflicting. We evaluated the trends, causes and predictors of early mortality among newly diagnosed MM (NDMM) patients in the real world. Methods: We used Surveillance Epidemiology and End Results (SEER) database, to identify all adult patients (age ≥ 18 years) who were diagnosed of MM from 1975 to 2015. Data on age, gender, geographical regions, year of diagnosis, survival time, vital status at 6 months after diagnosis and cause of death (COD) were extracted. Ages were categorized as quartiles while period of diagnosis for multivariate analysis were categorized by running a joinpoint analysis separately for the all-cause and myeloma-specific mortality. To look at trends in early mortality, we estimated proportion of deaths for each year and plotted it as a scatterplot against the year of diagnosis and fitted it in the join point regression model by applying the NCI's Join point Regression Program, Version 4.5.0.1. By this method we identified the year(s) when a trend change was produced, calculated the annual percentage change (APC) in rates between trend-change points, and the average annual percentage change (AAPC) in the whole period studied. To correct for known errors with COD attribution, we applied a special COD variable which has been recently developed by the SEER program to indicate if the death was due to the primary cancer diagnosis or other causes. A multivariate analysis was conducted to analyze the predictors of all-cause and myeloma-specific mortality within 6 months by fitting into logistic regression model. Results: Of 90,975 NDMM patients, early mortality due to any cause was noted in 18,810 (20.7%). For the whole cohort, median age was 68 years, majority of the patients were males (53.1%), of non-Hispanic white (NHW) race/ethnicity (65.5%) and were diagnosed in SEER registries in the western region (53.9%). An overall survival (OS) of ≤6 months was seen for approximately 22% of NHW but 18% of non-Hispanic blacks (NHB) and Hispanics. OS of ≤6 months was seen in 10% of patients in the first quartile of age (<60 years) as compared to 36% of patients in the 4th quartile (≥78 years). By geographical regions, 23.3% of MM patients in the Midwest had ≤6-month OS as compared to only 18.4% in the Northeast. The most common early mortality COD was MM in 74.7% of the patients, followed by cardiovascular (11.9%), other (8.8%) and infectious causes (3.1%). The overall pattern of COD at 6 months was similar to COD at any time in the whole cohort. Joinpoint regression analysis of trends data resulted in 1 joinpoint for all-cause 6-month mortality while 2 joinpoints were noticed for myeloma-specific mortality (Figure 1). A steep decline in mortality was noticed in the more recent time periods for both, all-cause (2006-2015) and myeloma-specific (2003-2015) mortality rates with an AAPC of 3.93 (95%CI p<0.001) for all-cause and 3.95 (95%CI p<0.001) for myeloma-specific mortality. Prior to 2006, the decrease in all-cause mortality was only modest whereas decrease in myeloma-specific mortality witnessed a sharp decline from 1975-1987 as well. On MVA, advanced age (p<0.001), NHW race/ethnicity and Midwest geographic region (p<0.001) were associated with higher likelihood of mortality while female gender (p<0.001), more recent period of diagnosis (p<0.001), and "other" races (not NHW, NHB or Hispanics) (p<0.001) were associated with lower risk of mortality. Conclusion: Our results show that early mortality due to MM remains high despite therapeutic improvements and there are significant gender, racial and geographic disparities for this phenomenon. However, significant declines in all-cause and MM-specific early mortality in the more recent times are promising. The risk of early mortality is higher among men, older patients, NHW and Midwest region. A focus on interventions to reduce early mortality, including early diagnosis, use of efficacious anti-MM therapy and aggressive supportive care should be directed at groups with high-risk for early mortality from MM. Disclosures Chanan-Khan: Millennium: Research Funding; Ascentage: Research Funding; AbbVie: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment. Ailawadhi:Celgene: Consultancy; Pharmacyclics: Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy; Cellectar: Research Funding; Janssen: Consultancy, Research Funding.

Multiple myeloma (MM) treatment has advanced significantly over the last 2 decades. In most patients, the disease course has been altered from early fatality to chronic morbidity with multiple lines of treatment. The MM treatment paradigm has shifted toward treating patients before end-organ damage occurs. Thus, timeliness of treatment initiation in this era might improve patient outcomes. This is the first report to our knowledge analyzing disparities and trends in treatment timeliness of patients with MM using the National Cancer Database. Multiple factors affected the timing of treatment initiation in MM and disparities were found. We noted that initiation of treatment was delayed in women (odds ratio [OR], 1.15; 95% CI, 1.1 to 1.2) and blacks (OR, 1.21; 95% CI, 1.14 to 1.28; reference, whites) and in patients diagnosed in more recent years (2012-2015; OR, 1.15; 95% CI, 1.1 to 1.22; reference, 2004-2007). Patients were likely to start treatment earlier if they were age ≥ 80 years (OR, 0.83; 95% CI, 0.76 to 0.9; reference, age < 60 years), were uninsured (OR, 0.81; 95% CI, 0.72 to 0.91; reference, private insurance), had Medicaid (OR, 0.87; 95% CI, 0.79 to 0.95; reference, private insurance), were treated in a comprehensive community cancer program (OR, 0.7; 95% CI, 0.65 to 0.77; reference, community cancer program), lived in a location other than the US Northeast, or had a higher Charlson comorbidity score. Patient education and income levels did not affect time to treatment initiation. Particular aspects of these disparities could be explained by our current health care system and insurance rules, whereas others need to be investigated more deeply.

Background: MM is associated with significant morbidity even at the time of presentation and there is ample data to support that MM treatment improves overall survival (OS) as well as quality of life (QoL) due to effective symptom control. Patient refusal to recommended cancer treatment is not common in clinical practice but has been reported in certain cancers. There is no data on characteristics of MM patients who refuse treatment despite physician recommendation and outcomes of such patients. Methods: We used the National Cancer Database (NCDB) from 2004-2015 to extract data on adult MM patients who refused any systemic therapy as part of their initial care despite physician recommendation. Information on patient age, gender, race/ethnicity, education, year of diagnosis, income, geographical location, comorbidities, systemic treatment, survival time and vital status was obtained. Average annual percent change (AAPC) and average percent change (APC) were calculated to analyze the trends, and periods with similar APC were compared for statistically significant changes by applying join point regression. Multivariate models were employed to identify factors predicting refusal to therapy and to assess its impact on OS. Results: Of 75,734 eligible patients who were recommended treatment for MM (chemotherapy and or immunotherapy), 2138 (2.8%) patients did not receive any treatment due to refusal. Significantly higher number of females, patients in older age groups (age groups 60-79 and ³ 80 years), Medicare recipients and with ≥2 comorbidities refused treatment recommendation. On multivariate analysis, advanced age groups 60-79 years (OR = 1.47; 95% CI 1.27-1.31 p&lt;0.001) and ³80 years (OR = 5.02; 95% CI 4.23-5.96, p&lt;0.001), female gender (OR =1.16 ; 95% CI 1.05-1.27, p&lt;0.001), patients with certain primary payor types including Medicaid (OR = 1.59; 95% CI 1.28-1.98, p&lt;0.001), Medicare (OR = 1.63; 95% CI 1.43-1.87, p&lt;0.001) and uninsured (OR = 1.81; 95% CI 1.38-2.38, p&lt;0.001), and presence of ³2 comorbidities (OR = 1.39; 95% CI 1.2-1.61, p&lt;0.001) were the independent factors associated with higher likelihood of refusing treatment. Whereas being seen at academic research programs (OR = 0.7; 95% CI 0.6-0.8, p&lt;0.001), higher education (OR =0.81 ; 95% CI 0.67-0.98, p=0.03), geographical location (Midwest OR =0.87 ; 95% CI 0.76-0.99, p=0.04), longer distance to facility being at 3rd quartile (10.1-26.2 miles: OR =0.78 ; 95% CI 0.68-0.89, p&lt;0.001) or 4th quartile (&gt;26.2 miles: OR = 0.59; 95% CI 0.51-0.68, p&lt;0.001) were associated with lower likelihood of refusing treatment. The overall rate of refusing treatment by MM patients was quite stable during 2004-2015 with an AAPC of 1.1 (95% CI -1.1-3.3 p=0.3). However, on fitting scatter plot into Joinpoint regression model, a concerning trend in the more recent years was noted. While the rate of refusing recommended treatment decreased during 2004-2008, a rising trend was observed during the period 2008-2015 with an APC of 3.8 (95% CI 1.3-6.4, p≤0.001) (Fig 1a). Patients who were recommended treatment but refused had significantly worse survival than those who received treatment (median survival 17.7 vs 52.9 months, Cox hazard ratio 1.21; CI 1.17-1.24, p&lt;0.001) (Fig 1b). Conclusions: The percentage of MM patients refusing any systemic treatment as a part of their initial care despite physician recommendation appears to be increasing in recent years and this needs to be systematically addressed. Disparities in refusal to recommended treatment are independently associated with several variables including age, gender, comorbidities, geographical location, facility and insurance type. These need to be addressed urgently since there are several effective and well-tolerated anti-MM treatments which can potentially benefit patients in case the initial socioeconomic, clinical and psychosocial barriers are overcome. Disclosures Chanan-Khan: Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; AbbVie: Research Funding. Ailawadhi:Pharmacyclics: Research Funding; Celgene: Consultancy; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy.