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BackgroundPredicting which patients will respond to PD-1 blockade and identifying the relevant underlying mechanisms are major challenges in immuno-oncology. Emerging data suggest that the frequency of cancer-specific T-cells in blood can predict anti-PD-1 response,1 2 but identifying these cells in most cancers is not routinely feasible. Prior studies have identified gene signatures shared by cancer-specific T cells within tumors, however, these cannot be applied to blood samples because gene expression patterns are strikingly different between cancer-specific T-cells in tumors versus blood. If gene signatures could be developed to identify cancer-specific T cells in blood, this could enable prediction of response. We leveraged the small antigenic space of Merkel cell polyomavirus (MCPyV) oncoproteins and our existing suite of reagents to identify and characterize cancer-specific T-cells in blood from patients with Merkel cell carcinoma (MCC).MethodsSingle-cell RNA sequencing was performed on 17 pre-anti-PD-(L)1 blood from patients with advanced MCC. MCPyV-specific CD8 T cells were identified using a panel of 19 HLA multimer reagents. Differential gene expression was used to analyze transcripts enriched in MCPyV multimer-binding cells relative to other non-naïve CD8 T-cells.ResultsWe identified a 27-gene signature that was enriched in MCPyV-specific CD8 T cells across 17 patients. An independent validation cohort of 8 virus-driven MCC patients revealed that this gene signature was able to identify peripheral MCC-associated CD8 T cells with a sensitivity of 69% and a specificity of 90% (figure 1A). We determined if this gene signature could also identify T cells from a cohort of 17 Epstein Barr Virus-driven nasopharyngeal carcinoma (NPC) patients. NPC-associated CD8 T cells were identified using a previously determined protein signature.3 Indeed, the gene signature was able to identify peripheral NPC-associated CD8 T-cells with a sensitivity of 72% and a specificity of 75% (figure 1B).ConclusionsThe tumor-specific T-cell gene signature generated via one cohort of MCC patients robustly identified tumor-specific T cells in two other cohorts (one composed of MCC patients and one of NPC patients) with comparable accuracy. Taken together, our data indicate that, compared to other non-naïve peripheral CD8 T-cells, tumor-specific CD8 T-cells have a distinct gene expression profile. It is plausible that this gene expression profile could also identify cancer-specific CD8 T-cells in mutationally driven cancers. This would allow us to gain important insights into the mechanisms of response and resistance to T-cell-based immunotherapies and enable clinically feasible identification of TCRs for transgenic T cell therapies for most cancers.Trial RegistrationThis abstract includes patient samples collected on NCT02267603.ReferencesPulliam T, Jani S, Jing L, Zhang J, Kulikauskas R, Church C, Garnett-Benson C, Paulson K, Smith K, Pardoll A, et al. 50 Merkel cell polyomavirus-specific CD8 T cells in blood, but not in tumors, correlate with immunotherapy response in merkel cell carcinoma. Journal for ImmunoTherapy of Cancer 2022;10:A53-A53. 10.1136/jitc-2022-SITC2022.0050.Ryu H, Bi T, Sarkar K, Church C, Ramchurren N, Pulliam T, Fling S, Nghiem P, Newell E. 1045 High dimensional profiling of merkel cell polyomavirus-specific T cells in response to anti-PD-1 immunotherapy. Journal for ImmunoTherapy of Cancer 2022;10:A1087-A1087. 10.1136/jitc-2022-SITC2022.1045.Kumar N, MacMillan H, Yeong JPS, Chua M, Jain A, Newell E. 1035 High-dimensional immune profiling of peripheral epstein-barr virus-specific T cells in nasopharyngeal carcinoma. Journal for ImmunoTherapy of Cancer 2022;10:A1077-A1077. 10.1136/jitc-2022-SITC2022.1035.Ethics ApprovalAll patients represented here participated with written informed consent. Training cohort samples were provided by Cancer Immunotherapy Trails Network (trial registration: ClinicalTrials.gov NCT02267603) and analyzed with approval by the Fred Hutchinson Cancer Center‘s Institutional Review Board (FH 6585). MCC validation cohort samples were collected and analyzed with approval by the Fred Hutchinson Cancer Center‘s Institutional Review Board (FH 6585). NPC validation cohort samples were obtained from the National Cancer Centre Singapore, and de-identified patient information from this cohort was obtained with approval by the institutional review board at the Fred Hutchinson Cancer Research Center (IR File#: 6007–1053).Abstract 1018 Figure 1Receiver operating characteristic (ROC) curve demonstrating performance of the tumor-specific gene expression signature in independent validation cohorts from MCC (A) and NPC (B).

Background: Life for women drastically altered after the 2021 US-NATO military withdrawal from Afghanistan. Methods: Applying a gendered general strain theory (GGST) model, this paper presents mixed-method findings from a 2023 semi-structured digital survey of 29 Afghan women, identifying key shared hardships concerning the daily lives of Afghan women (ages 18–65) and psychosocial stress. Results: A thematic analysis of their responses indicates that support for the Taliban’s return to power ranges among women; however, respondents experience diminished quality-of-life (DQOL) factors like persistent food insecurity that affect their views of the current government and affect their psychosocial health. Furthermore, most struggle with financial insecurity and growing governmental restrictions, particularly gender discrimination policies (GDP), further increasing their stress as they try to acclimate to the new political environment. Additionally, we triangulate the key qualitative findings with a statistical analysis to help illustrate emerging patterns between DQOL factors, GDP experiences, and psychosocial stress (PSS). Conclusions: This study is one of the first known semi-structured surveys conducted within the country of Afghanistan after the Taliban reseized control, offering crucial insights into life of Afghan women through their own intimate experiences and perspectives.

Official data on birth is important to monitor the specific targets of SDGs. About 2.7 million children under age five years do not have official birth registration document in India. Unavailability of birth registration document may deprive the children from access to government-aided essential services such as fixed years of formal education, healthcare, and legal protection. This study examines the effect of socioeconomic, demographic and health care factors on birth registration in India. We also examined the spatial pattern of completeness of birth registration that could be useful for district level intervention. We used data from the National Family Health Survey (NFHS-4), 2015-16. We carried out the descriptive statistics and bivariate analysis. Besides, we used multilevel binary logistic regression to identify significant covariates of birth registration at the individual, district, and state levels. We used GIS software to do spatial mapping of completeness of birth registration at district level. The birth registration level was lower than national average (80.21%) in the 254 districts. In Uttar Pradesh, 12 out of 71 districts recorded lower than 50% birth registration. Also, some districts from Arunachal Pradesh, J&K, and Rajasthan recorded lower than 50% birth registration. We also found a lower proportion of children are registered among children of birth order three and above (62.83%) and rural resident (76.62%). Children of mothers with no formal education, no media exposure, poorest wealth quintile, OBC and muslims religion have lower level of birth registration. Multilevel regression result showed 25 percent variation in birth registration lie between states while the remaining 75 percent variation lie within states. Moreover, children among illiterate mother (AOR = 0.57, CI [0.54, 0.61], p<0.001), Muslims households (AOR = 0.90, CI [0.87, 0.94], p<0.001), and poorest wealth quintile (AOR = 0.38, CI [0.36, 0.41], p<0.001) showed lower odds for child's birth registration. We strongly suggest linking the birth registration facilities with health institutions.

India contributes the highest global share of deaths among the under-fives. Continuous monitoring of the reduction in the under-five mortality rate (U5MR) at local level is thus essential to set priorities for policy-makers and health professionals. In this study, we aimed to provide an update on district-level disparities in the neonatal mortality rate (NMR) and the U5MR with special reference to Sustainable Development Goal 3 (SDG3) on preventable deaths among new-borns and children under five. We used recently released population-based cross-sectional data from the National Family Health Survey (NFHS) conducted in 2015-2016. We used the synthetic cohort probability approach to analyze the full birth history information of women aged 15-49 to estimate the NMR and U5MR for the ten years preceding the survey. Both the NMR and U5MR vary enormously across Indian districts. With respect to the SDG3 target for 2030 for the NMR and the U5MR, the estimated NMR for India for the period studied is about 2.4 times higher, while the estimated U5MR is about double. At district level, while 9% of the districts have already reached the NMR targeted in SDG3, nearly half (315 districts) are not likely to achieve the 2030 target even if they realize the NMR reductions achieved by their own states between the last two rounds of National Family Health Survey of India. Similarly, less than one-third of the districts (177) of India are unlikely to achieve the SDG3 target on the U5MR by 2030. While the majority of high-risk districts for the NMR and U5MR are located in the poorer states of north-central and eastern India, a few high-risk districts for NMR also fall in the rich and advanced states. About 97% of districts from Chhattisgarh and Uttar Pradesh, for example, are unlikely to meet the SDG3 target for preventable deaths among new-borns and children under age five, irrespective of gender. To achieve the SDG3 target on preventable deaths by 2030, the majority of Indian districts clearly need to make a giant leap to reduce their NMR and U5MR.

While the gender disparity in health and mortality in various stages of life in India is well documented, there is limited evidence on female disadvantage in health-care expenditure (HCE). Examine the gender difference in HCE in short-term and major morbidity in India, and understand the role of factors underlying the difference. Using two rounds of nationally representative panel data-the India Human Development Survey (IHDS) 2004-2005 and 2011-2012 (IHDS I & II)-we calculate morbidity prevalence rate and mean HCE by gender, and examine the adjusted effect of gender on major morbidity-related HCE by using a two-part regression model. Further, we performed Oaxaca-Blinder decomposition of the gender gap in HCE in major morbidity to understand the contribution of demographic and socio-economic factors. Health-care expenditure on females was systematically lower than on males across all demographic and socio-economic groups. Multivariate analysis confirms that female HCE is significantly lower than male HCE even after controlling demographic and socio-economic factors (β = -0.148, p = 0.000, CI:-0.206-0.091). For both short-term and major morbidity, a female disadvantage on HCE increased from IHDS I to IHDS II. For instance, the male-female gap in major morbidity related expenditure increased from INR 1298 to INR 4172. A decomposition analysis of gender gap in HCE demonstrates that about 48% of the gap is attributable to differences in demographic and socio-economic factors (endowment effect), whereas 50% of the gap is due to the differential effect of the determinants (coefficient effect). Indians spend less on female health care than on male health care. Most of the gender gap in HCE is not due to differential distribution of factors affecting HCE.

Background Rural Indians have higher mortality rates than urban Indians. However, the rural-urban gap in under-five mortality has changed is less researched. This paper aims to assess 1) whether the rural-urban gap in under-five mortality has reduced over time 2) Whether rural children are still experiencing a higher likelihood of death after eliminating the role of other socioeconomic factors 3) What factors are responsible for India’s rural-urban gap in under-five mortality. Methods We used all rounds for National Family Health Survey data for understanding the trend of rural-urban gap in under-five mortality. Using NFHS-2019-21 data, we carried out a binary logistic regression analysis to examine the factors associated with under-five mortality. Fairlie’s decomposition technique was applied to understand the relative contribution of different covariates to the rural–urban gap in under-five mortality. Results India has witnessed a more than 50% reduction in under-five mortality rate between 1992 and 93 and 2019–21. From 1992 to 93 to 2019–21, the annual decrease in rural and urban under-five mortality is 1.6% and 2.7%, respectively. Yet, rural population still contributes a higher proportion of the under-five deaths. The rural-urban gap in under-five mortality has reduced from 44 per thousand live births in 1992–1993 to 30 per thousand in 2004–2005 which further decreased to 14 per thousand in 2019–2021. There is no disadvantage for the rural children due to their place of residence if they belong to economically well-off household or their mothers are educated. It is wealth index rather than place of residence which determines the under-five mortality. Economic (50.82% contribution) and educational differential (28.57% contribution) are the main reasons for rural-urban under-five mortality gaps. Conclusion The existing rural-urban gap in under-five mortality suggests that the social and health policies need to be need to reach rural children from poor families and uneducated mothers. This call for attention to ensure that the future programme must emphasize mothers from economically and educationally disadvantaged sections. While there should be more emphasis on equal access to health care facilities by the rural population, there should also be an effort to strengthen the rural economy and quality of education.

Wetlands protect downstream waters by filtering excess nitrogen (N) generated from agricultural and urban activities. Many small ephemeral wetlands, also known as geographically isolated wetlands (GIWs), are hotspots of N retention but have received fewer legal protections due to their apparent isolation from jurisdictional waters. Here, we hypothesize that the isolation of the GIWs make them more efficient N filters, especially when considering transient hydrologic dynamics. We use a reduced complexity model with 30 years of remotely sensed monthly wetland inundation levels in 3700 GIWs across eight wetlandscapes in the US to show how consideration of transient hydrologic dynamics can increase N retention estimates by up to 130%, with greater retention magnification for the smaller wetlands. This effect is more pronounced in semi-arid systems such as the prairies in North Dakota, where transient assumptions lead to 1.8 times more retention, compared to humid landscapes like the North Carolina Pocosins where transient assumptions only lead to 1.4 times more retention. Our results highlight how GIWs have an outsized role in retaining nutrients, and this service is enhanced due to their hydrologic disconnectivity which must be protected to maintain the integrity of downstream waters.

The extant literature on gender differentials in health in developed countries suggests that women outlive men at all ages, but women report poorer health than men. It is well established that Indian women live longer than men, but few studies have been conducted to understand the gender dimension in self-rated health and self-reported disability. The present study investigates gender differentials in self-rated health (SRH) and self-reported disability (SRD) among adults in India, using a nationally representative data. Using data on 10,736 respondents aged 18 and older in the 2007 WHO Study on Global Ageing and Adult Health in India, prevalence estimates of SRH are calculated separately for men and women by socio-economic and demographic characteristics. The association of SRH with gender is tested using a multinomial logistic regression method. SRD is assessed using 20 activities of daily living (ADL). Further, gender differences in total life expectancy (TLE), disability life expectancy (DLE) and the proportion of life spent with a disability at various adult ages are measured. The relative risk of reporting poor health by women was significantly higher than men (relative risk ratio: 1.660; 95% confidence Interval (CI): 1.430-1.927) after adjusting for socio-economic and demographic characteristics. Women reported higher prevalence of severe and extreme disability than men in 14 measures out of a total20 ADL measures. Women aged less than 60 years reported two times more than men in SRD ≥ 5 ADLs. Finally, both DLE and proportion of life spent with a disability were substantially higher for women irrespective of their ages. Indian women live longer but report poorer health than men. A substantial gender differential is found in self-reported disability. This makes for an urgent call to health researchers and policy makers for gender-sensitive programs.

To investigate coverage and factors associated with death registration in India. We used data from the Indian National Family Health Survey 2019-2021. Based on responses of eligible household members, we estimated death registration in 84 390 deaths in all age groups across the country. We used multilevel logistic regression analysis to determine sociodemographic variables associated with death registration at state, district and individual levels. Nationally, 70.8% (59 748/84 390) of deaths were registered. Of 707 districts in our study period, 122 and 53 districts had death registration levels less than 40% in females and males, respectively. The likelihood of death registration was significantly lower for females than males (adjusted odds ratios, aOR: 0.61; 95% confidence interval, CI: 0.59-0.64). Death registration increased significantly with age of the deceased person, with the highest odds in 35-49-year-olds (aOR: 5.05; 95% CI: 4.58-5.57) compared with 0-4-year-olds. Death registration was less likely among rural households, disadvantaged castes, the poorest wealth quintile, Muslims and households without a below poverty level card. Higher education was associated with higher death registration with the greatest likelihood of registration in households with a member with post-secondary school education (aOR: 1.54; 95% CI: 1.42-1.66). District-level factors were not significantly associated with death registration. Sociodemographic characteristics of the deceased person were significantly associated with death registration. Strategies to raise awareness of death registration procedures among disadvantaged population groups and the introduction of a mobile telephone application for death registration are recommended to improve death registration in India.

The high-altitude alpine regions are characterized by highly variable and harsh environmental conditions. However, relatively little is known about the diverse mechanisms adopted by alpine plants to adapt to these stressful conditions. Here, we studied variation in transcriptome and physiological adjustments occurring across the year at high elevation environments in the leaf tissue of Rhododendron anthopogon , an evergreen shrub of Himalaya. The samples were collected at 12 different time-points, from August until snowfall in November 2017, and then from June to September 2018. It was observed that with a drop in both ambient air temperature and photoperiod towards onset of winter, the freezing resistance of plants increased, resulting in ‘cold acclimation’. Further, ‘de-acclimation’ was associated with a decrease in freezing resistance and increase in photosynthetic efficiency of leaves during spring. A considerable amount of variation was observed in the transcriptome in a time-dependent sequential manner, with a total of 9,881 differentially expressed genes. Based on gene expression profiles, the time-points could be segregated into four clusters directly correlating with the distinct phases of acclimation: non-acclimation (22-August-2017, 14-August-2018, 31-August-2018), early cold acclimation (12-September-2017, 29-September-2017), late cold acclimation (11-October-2017, 23-October-2017, 04-November-2017, 18-September-2018) and de-acclimation (15-June-2018, 28-June-2018, 14-July-2018). Cold acclimation was a gradual process, as indicated by presence of an intermediate stage (early acclimation). However, the plants can by-pass this stage when sudden decrease in temperature is encountered. The maximum variation in expression levels of genes occurred during the transition to de-acclimation, hence was ‘transcriptionally’ the most active phase. The similar or higher expression levels of genes during de-acclimation in comparison to non-acclimation suggested that molecular functionality is re-initiated after passing through the harsh winter conditions.