Single Time Point Research Articles

Performance of Lung Cancer Prediction Models for Screening-detected, Incidental, and Biopsied Pulmonary Nodules.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally-detected, and bronchoscopically-biopsied pulmonary nodules. Materials and Methods This study retrospectively evaluated promising predictive models for lung cancer prediction in three clinical settings: lung cancer screening with low-dose CT, incidentally, detected pulmonary nodules, and nodules deemed suspicious enough to warrant a biopsy. The area under the receiver operating characteristic curve (AUC) of eight validated models including logistic regressions on clinical variables and radiologist nodule characterizations, artificial intelligence (AI) on chest CTs, longitudinal imaging AI, and multimodal approaches for prediction of lung cancer risk was assessed in 9 cohorts (n = 898, 896, 882, 219, 364, 117, 131, 115, 373) from multiple institutions. Each model was implemented from their published literature, and each cohort was curated from primary data sources collected over periods within 2002 to 2021. Results No single predictive model emerged as the highest-performing model across all cohorts, but certain models performed better in specific clinical contexts. Single timepoint chest CT AI performed well for screening-detected nodules but did not generalize well to other clinical settings. Longitudinal imaging and multimodal models demonstrated comparatively good performance on incidentally-detected nodules. When applied to biopsied nodules, all models showed low performance. Conclusion Eight lung cancer prediction models failed to generalize well across clinical settings and sites outside of their training distributions. ©RSNA, 2025.

THE EVALUATION OF LEADERSHIP STYLES ON EMPLOYEE INNOVATIVE WORK BEHAVIOUR OF PROJECT MANAGERS IN THE HEALTHCARE INDUSTRY: THE MEDIATING ROLE OF EMOTION INTELLIGENCE

Effective leadership plays a pivotal role within an organisation, as inadequate leadership can have adverse effects on both its financial performance and brand reputation. In response to a growing demand for enhanced leadership, this research delves into the impact of different leadership styles, including transformational, laissez-faire, and transactional, on the innovative work behaviour of employees within the healthcare sector of Pakistan. The study also explores how Emotional Intelligence (EI) acts as a mediating factor in this relationship. The research design adopted a cross-sectional approach, collecting data at a single point in time from 417 project managers and healthcare sector employees in Pakistan. The analysis employed Smart PLS 4 software which revealed a positive correlation between transformational leadership and Employee Innovative Work Behaviour (EIWB), while no significant relationships were observed with laissez-faire and transactional leadership styles. However, it is important to note that EI played an indirect but positive role in influencing EIWB.

Postoperative acute pain trajectory and chronic postsurgical pain after abdominal surgery: a prospective cohort study and mediation analysis.

This study aimed to investigate the trajectories of acute postoperative pain intensity during the initial 5days after abdominal surgery, and to analyze their association with the risk of developing chronic postsurgical pain (CPSP). We enrolled patients with elective abdominal surgery with pain measurements taken across postoperative days 1 through 5. Since postoperative pain is often unavoidable and its initial intensity is closely related to the invasiveness of the surgery, focusing on the overall pain trajectory may be more meaningful than evaluating pain at a single time point. Therefore, the primary outcome of this study was to identify distinct pain trajectories. Secondary outcome was the incidence of CPSP between differences pain trajectories. Lastly, mediation analyses were performed to explore the mediating role of the quality of recovery and subacute pain on the studied associations. The final analysis encompassed 1170 patients (36.75% female) with a median age of 55years. Two distinct clusters were identified: with movement (high: 533 [45.56%]; low: 637 [54.44%]) and at rest (high: 363 [31.03%]; low: 807 [68.97%]). Patients in the high pain trajectory group (during movement [odds ratio [OR] 2.04, 95% CI 1.56-2.68] or at rest [OR 1.90, 95% CI 1.44-2.53]) exhibited nearly doubled risk of CPSP. Moreover, these patients exhibited a significantly poorer recovery quality. Mediation analyses revealed that the poor recovery quality at postoperative 5days (17.62%-18.57%) and higher subacute pain at postoperative 1month (29.46%-32.75%) were significant mediators in the association between adverse postoperative acute pain trajectory patterns and CPSP. This study highlights the clinical significance of postoperative pain trajectory profiles in predicting the risk of CPSP, emphasizing postoperative acute pain trajectory as a critical indicator and subacute pain as a significant mediator. The findings underscore the potential for tailored pain management strategies targeting acute pain trajectories to reduce such risk.

Intent-Bert and Universal Context Encoders: A Framework for Workload and Sensor Agnostic Human Intention Prediction

Determining human intention is a challenging task. Many existing techniques seek to address it by combining many forms of data, such as images, point clouds, poses, and others, creating multi-modal models. However, these techniques still often require significant foreknowledge in the form of known potential activities and objects in the environment, as well as specific types of data to collect. To address these limitations, we propose Intent-BERT and Universal Context Encoders, which combine to form workload-agnostic framework that can be used to predict the next activity that a human performs as an Open Vocabulary Problem and the time until that switch, along with the time the current activity ends. Universal Context Encoders utilize the distances between the embeddings of words to extract relationships between Human-Readable English descriptions of both the current task and the origin of various multi-modal inputs to determine how to weigh the values themselves. We examine the effectiveness of this approach by creating a multi-modal model using it and training it on the InHARD dataset. It is able to return a completely accurate description of the next Action performed by a human working alongside a robot in a manufacturing task in ∼42% of test cases and has a 95% Top-3 accuracy, all from a single time point, outperforming multi-modal gpt4o by about 50% on a token by token basis.

Abstract TP161: Machine Learning to Glean Characteristics of Quantitative Susceptibility Maps in Cerebral Cavernous Angiomas with Symptomatic Hemorrhage

Introduction and Hypothesis: New bleeding in cerebral cavernous malformations (CCM) heralds increased risk of future hemorrhage for several years, yet conventional imaging only detects new bleeding that occurred in the prior weeks. A biomarker of hemorrhage could help identifying high risk lesions. An increase of mean lesional quantitative susceptibility mapping (QSM) ≥6% on MRI has been adjudicated as reflecting new bleeding in CCM during longitudinal follow-up. However, mean lesional QSM from a single acquisition could not diagnose or prognosticate a bleed. We hypothesize that machine learning (ML) may identify diagnostic and prognostic features of bleeding within QSM maps at a single point in time. Material and Methods: Two hundred and sixty-five QSM maps of CCM lesions were acquired in 120 patients enrolled in National Institute of Health (NIH) multisite trial readiness project (NCT03652181). Each map was classified (Yes/No) in association with symptomatic hemorrhage (SH) and/or biomarker event with QSM increase ≥6% in the prior (diagnostic association) and subsequent (prognostic association) year. Twenty-eight features were extracted including 14 texture, 5 first-order statistical, as well as 3 size, shape, and morphological. Five-fold cross-validation was conducted on a support-vector machine (SVM) with linear stepwise kernel for both diagnostic and prognostic associations. Performance of individual features and composite classifiers was evaluated using student t-test ( p <0.05) with Bonferroni-correction and receiver operating characteristic (ROC) analysis, area under the curve (AUC). Results: Lesions with SH in the prior year had lower average values for sum variance (AUC=0.79, p<0.001), variance (AUC=0.79, p<0.001), and correlation (AUC=0.71, p=0.004) as compared to lesions without SH. The SVM classification method tasked with distinguishing lesions with mean QSM increase ≥6% in the prior year included recurrent selection of sum average, mean, sphericity and margin sharpness, yielding an AUC of 0.61 (p=0.02). In the prognostic cohort, no individual feature nor any SVM classification model was able to distinguish cases with a subsequent clinical bleed or biomarker event. Conclusion: This proof-of-concept suggests that ML may assist in deriving features on QSM maps acquired at a single timepoint, which reflect prior hemorrhagic activity in CCM. Further investigation is planned in larger cohorts and in conjunction with clinical trials of bleeding in CCM.

Association of systemic inflammatory markers with white matter hyperintensities and microstructural injury: an analysis of UK Biobank data.

White matter damage is closely associated with cognitive and psychiatric symptoms and is prevalent in cerebral small vessel disease (CSVD); although the pathophysiological mechanisms involved in CSVD remain elusive, inflammation plays a crucial role. We sought to investigate the relationship between systemic inflammation markers and imaging markers of CVSD, namely white matter hyperintensity (WMH) and microstructural injury. We conducted a study involving both cross-sectional and longitudinal data from the UK Biobank Cohort. We performed multiple linear regression analyses, adjusted for potential confounders, to explore the associations between systemic inflammation markers (e.g., systemic immune-inflammation index [SII], neutrophil-to-lymphocyte ratio [NLR], C-reactive protein [CRP] levels, monocyte count, neutrophil count) and macro- and microstructural white matter injury, as markers of CSVD. We performed Mendelian randomization analysis to investigate the genetically predictive effect of monocytes on WMH, as well as mediation analysis to clarify whether inflammatory markers affected cognitive function via white matter injury. We included 36 411 participants (mean age 54.8 ± 7.5 yr, 51.9% female) from the UK Biobank Cohort. We found that SII was significantly associated with both WMH and microstructural injury markers (fractional anisotropy, mean diffusivity, intracellular volume fraction, and isotropic compartment volume fraction [ISOVF]), and the neutrophil-to-lymphocyte ratio was significantly associated with WMH and some markers of microstructural injury (mean diffusivity and ISOVF). Our analysis revealed that the CRP level was significantly associated with WMH and WMH progression but not with microstructural injury. We also demonstrated that monocyte count was significantly associated with WMH and ISOVF, and that neutrophil count was significantly associated with WMH, mean diffusivity, and ISOVF. In 2-sample Mendelian randomization analyses, we found positive associations between genetic determinants of monocytes and WMH. The mediating role of WMH suggested that a higher SII value and monocyte count could contribute to cognitive impairment through white matter injury. Although the study includes both cross-sectional and longitudinal components, the sample size for the longitudinal aspect is limited, and the use of blood biomarkers from a single timepoint is also a limitation of this research. The SII and neutrophil-to-lymphocyte ratio may be early detection markers for white matter damage in patients with CSVD, whereas the CRP level is more closely associated with disease severity and progression. Our findings highlight the clinical relevance of systemic inflammation markers with white matter macro- and microstructural injuries, revealing that systemic inflammation is likely involved in the mechanism of early white matter injury among patients with CSVD.

A randomized phase 2 study of an individualized neoantigen-targeting immunotherapy in patients with newly diagnosed metastatic microsatellite stable colorectal cancer (MSS-CRC).

LBA13 Background: Neoantigen-targeting immunotherapy aims to provide therapeutic benefit to patients by generating potent neoantigen-specific T cells. GRANITE is an immunotherapy regimen that uses chimpanzee adenovirus and self-amplifying mRNA vaccines encoding patient-specific neoantigens in combination with immune checkpoint inhibitors. Preliminary efficacy was noted in MSS-CRC (Palmer et al Nature Medicine 2022) and this regimen is being assessed in a randomized Phase 2 study in 1L metastatic MSS-CRC (NCT05141721). Methods: Patients (pts) with 20 neoantigens based on the EDGEÔ prediction model were randomized 1:1 to receive the GRANITE regimen in addition to 1L standard of care (SOC) (GRANITE vaccine arm), or 1L SOC alone (control arm). Results: Baseline demographics and disease characteristics were balanced between arms. As of 15 Oct 2024, GRANITE pts had an improvement in PFS relative to control pts (HR=0.73, 90% CI [0.44, 1.21]). In this study, high and low disease burden groups were identified using baseline ctDNA assessed by Gritstone’s validated, highly sensitive, tumor-informed assay. Patients with low disease burden benefited more than those with high disease burden, consistent with emerging data suggesting neoantigen-targeting immunotherapy having greater activity in minimal disease settings (e.g., adjuvant setting). Furthermore, in the low disease burden group at the most recent study visit, more patients were free of progression with very low ctDNA levels (ie, below the limit of quantification of the assay) in the GRANITE arm, 41% (7/17), versus the control arm, 21% (3/14). The greater proportion of GRANITE patients both free of progression and with very low ctDNA, suggests potential further separation of PFS cuves with additional follow up. Neoantigen-specific T cell responses were observed in 100% of patients in the GRANITE arm with evaluable PBMC samples (17/17 assessed by ex vivo and in vitro stimulation ELISpots). Molecular responses based on a reduction in ctDNA at a single timepoint was similar between arms (39% in GRANITE and 40% in control arms). Most common (≥20%) treatment-related adverse events (TRAE) included pyrexia and influenza like illness and no pts discontinued due to a TRAE. Conclusion: This randomized study shows GRANITE may benefit patients, especially those with low burden disease, in this front line setting of metastatic MSS-CRC that has not benefitted from immunotherapy. Updated analysis will be presented. Clinical trial information: NCT05141721 .

573. CD388, a Novel Drug-Fc Conjugate (DFC), Demonstrates Prophylactic Activity in an Influenza Human Challenge Model

Abstract Background Influenza is a significant cause of morbidity and mortality globally. CD388 is a multivalent conjugate of a dimeric zanamivir stably linked to a proprietary human IgG1 Fc fragment engineered for extended half-life. In preclinical and two Phase 1 studies CD388 has been shown to be safe. Here we describe a post-hoc analysis of prophylactic activity of CD388 against influenza disease in a Phase 2a human challenge study. Methods Healthy participants (18-55 yrs) were randomized to receive subcutaneous (SQ) CD388 or placebo. CD388 was administered 5 days before intranasal challenge with A/Perth/16/2009 (H3N2). A hemagglutinin inhibition assay (HAI) was performed at the onset of quarantine, on Day 0 (prior to inoculation) and on Day 28. A 4-fold increase in Day 28 HAI titer with respect to Day 0 titer was considered as confirmation of influenza infection. Participants completed a graded symptom scoring system 3 x daily. Symptomatic infection was defined as RT-PCR-confirmed (2 quantifiable measurements on ≥ 2 independent samples over 2 days) or culture confirmed (1 quantifiable TCID50 measurement) influenza infection from Day 1 (pm) to Day 8 (am) AND fever or ≥ 2 symptoms at a single time point or any symptom of grade ≥ 2 at a single time point. Prophylactic efficacy was assessed among participants who experienced a 4-fold increase in HAI titer. Results 28 participants received 150 mg of CD388 and 28 received placebo. 17 participants in the CD388 arm (60.7%) and 15 participants in the placebo arm (53.6%) had a 4-fold increase in the HAI titer on Day 28 (Table 1). Although these end-points were not powered, of those with the 4-fold change in HAI, the number of symptomatic participants was significantly lower in the CD388 arm (3/17, 17.6%) compared to placebo (9/15, 60%; p= 0.017), and among these symptomatic participants the median AUC TCID50 (log TCID50/mL x number of days) was significantly lower in the CD388 arm (6.1, min 3.3, max 9.7) compared to placebo (10.8, min 5.7, max 17; p=0.008, Table 1). Conclusion A single SQ dose of CD388 administered 5 days prior to influenza challenge was effective in preventing symptomatic disease. A Phase 2b clinical influenza prevention study for CD388 will begin in the Fall of 2024. Disclosures Ozlem Equils, MD, Cidara Therapeutics: Employee|Cidara Therapeutics: Stocks/Bonds (Public Company) Shawn Flanagan, PhD, Cidara Therapeutics: Salaried Employee|Cidara Therapeutics: Employee|Cidara Therapeutics: Stocks/Bonds (Public Company)|Cidara Therapeutics: Stocks/Bonds (Public Company) Sy-Shi Wang, Ph.D., Janssen Research & Development LLC: Employee|Janssen Research & Development LLC: Stocks/Bonds (Public Company) Johan Vingerhoets, PhD, Janssen Pharmaceutica NV: Stocks/Bonds (Public Company) Wilbert van Duijnhoven, n/a, Janssen Pharmaceutica NV: Employee|Janssen Pharmaceutica NV: Stocks/Bonds (Public Company) Alex James Mann, MSc, hVIVO: Employee Roxana E. Rojas, M.D., Ph.D., Janssen Research & Development LLC: Employee|Janssen Research & Development LLC: Stocks/Bonds (Public Company)|Johnson and Johnson: Stocks/Bonds (Public Company) Taylor Sandison, MD, MPH, Cidara Therapeutics Inc: Employee|Cidara Therapeutics Inc: Stocks/Bonds (Public Company)

Learning spellings and meanings: Longitudinal relations to reading

BackgroundProminent theories of reading make the prediction that individual differences in children's word learning capacity determine the pace of their acquisition of reading skill. Despite the developmental nature of some of these theories, most empirical research to date has explored the relation between word learning capacity and reading at a single time point. The present study extends this research base by investigating whether earlier learning of the spelling and meaning of words is associated with later core aspects of reading: orthographic representations, word reading and reading comprehension.MethodsParticipants were 120 English‐speaking children followed longitudinally from Grade 3 to Grade 4 (i.e., from 8 to 9 years of age on average). At Grade 3, children read stories containing new words and answered questions about the spelling and meaning of these new words, evaluating orthographic and semantic learning, respectively. Children also completed outcome measures of orthographic representations (with a choice task targeting the spelling of existing words), word reading and reading comprehension (with standardised tasks) at Grades 3 and 4. We conducted regression analyses controlling for age, nonverbal reasoning, working memory, vocabulary and phonological awareness.ResultsWe found that each of orthographic and semantic learning predicted gains in orthographic representations from Grade 3 to Grade 4. Furthermore, orthographic learning at Grade 3 predicted word reading at Grade 4, while semantic learning at Grade 3 predicted reading comprehension at Grade 4.ConclusionsThese longitudinal associations between orthographic and semantic learning and core aspects of reading strengthen the evidence in support of the hypothesis that children's word learning capacity plays a key role in reading development.

Within- and Between-Person Differences in Activity Factor Structure: Results from an Ecological Momentary Assessment Study.

Studies using ecological momentary assessment (EMA) of activity participation rely on items tapping domains informed by factor analyses based on single time points. Analyses from a single time point focus on differences between participants and provide little insight into how activities cluster together within a person across moments or days. The present study compared the factor structure in activity participation between- and within-persons using an expanded set of momentary activity items in middle and older adulthood. Using tablets, 81 adults aged 41 to 94 years reported activities completed in the past 3-4 hours five times per day for 14 days. The most common activities during the day involved social interactions, reading, and computer work. Watching TV or videos was the most common evening activity. Multilevel factor analysis simultaneously computed both intra-individual factors (within-person) and inter-individual factors (between-person). Four within-person and 4 between-person factors provided the best model fit, with three common factors: cognitive (read, computer); social (events, mentoring, providing care); and passive (TV, games) factors. There were notable differences in the fourth factor. Although three common activity factors were found between individuals and within persons from day to day, the divergence between the fourth intra- and inter-individual factors provides insight into how activity engagement operates at different timescales and likely reflect daily demands versus long-term goals. EMA provides a window into engagement throughout and across days, but researchers who commonly use retrospective reports of between-person activity engagement may find distinctly different results from factor analyses.

P-2052. Pre-existing Humoral Immunity to Seasonal Coronaviruses and Effect on SARS-CoV-2 Antibody Responses on SARS-CoV-2 Vaccination and Infection

Abstract Background High homology and potential cross-reactive immune responses between SARS-CoV-2 and seasonal human coronaviruses (HCoVs) have been described by several studies. However, the role of pre-existing immunity to HCoVs in the outcome of SARS-CoV-2 infection and vaccination is still unclear. Anti-spike IgG titers against human coronavirus (HCoV)-229E, -HKU1, -NL63, and -OC43 by age of participants N=1,675 serum samples were collected from participants aged 2 to 95 years (median 44). anti-spike IgG titers against HCoV-229E, -HKU1, -NL63, and -OC43 were quantified by electrochemiluminescent immunoassay. Each dot represents the anti-HCoV spike IgG titer and age of the participant. Methods Pediatric and adult participants were enrolled. We collected demographic data and vaccination status, as well as serum samples at a single time point between August 2020 and August 2023. Anti-spike IgG titers against SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 were quantified by electrochemiluminescent immunoassay. SARS-CoV-2 infection status was determined by the presence of anti-SARS-CoV-2 nucleocapsid antibodies. Correlations were assessed by two-sided Spearman rank-correlation tests. Correlations between SARS-CoV-2 and hCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 unvaccinated participants To evaluate the effect of immunity against HCoVs on SARS-CoV-2 infection, correlations between SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 unvaccinated participants are shown (N=380). Each dot represents individual participants. Solid and dotted lines respectively indicate linear regression and 95% confidence interval. Correlations were assessed by two-sided Spearman rank-correlation tests. Results Sera were collected from N=1,675 participants of which 5.7% were ≤10 years (age range: 2-95 yrs, median: 44 yrs). HCoV titers rapidly increased in early childhood and the majority of adults had immunity against HCoVs. We first analyzed N=380 sera from SARS-CoV-2 unvaccinated participants. SARS-CoV-2 titers positively correlated with HCoV-OC43, -HKU1, and -NL63 titers. Furthermore, HCoV-OC43 titers were significantly higher in participants post-SARS-CoV-2 infection, determined by the presence of SARS-CoV-2 nucleocapsid antibodies, as compared to non-infected participants (geometric mean, 49,256 vs 29,613; P< 0.01). Next, to evaluate the correlation between HCoV immunity and SARS-CoV-2 titers on vaccination, sera from N=1,059 SARS-CoV-2 non-infected participants were analyzed. Notably, positive correlations between SARS-CoV-2 and HCoV-OC43, and -HKU1 anti-spike IgG titers were demonstrated (r=0.43 and 0.27; both P< 0.0001). Although higher numbers of SARS-CoV-2 vaccinations were associated with more SARS-CoV-2 antibodies, HCoV-OC43 titers did not show a correlation. Correlations between SARS-CoV-2 and hCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants To evaluate the effect of immunity against HCoVs on SARS-CoV-2 vaccination, correlations between SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants, determined by the absence of SARS-CoV-2 nucleocapsid antibodies, are shown (N=1,059). Each dot represents individual participants. Solid and dotted lines respectively indicate linear regression and 95% confidence intervals. Correlations were assessed by two-sided Spearman rank-correlation tests. Conclusion HCoVs immunity was acquired in early childhood. HCoV-OC43 titers were higher in SARS-CoV-2 infected participants compared to non-infected. In SARS-CoV-2 non-infected participants, positive correlations were seen between SARS-CoV-2 and HCoV-OC43 and -HKU1 titers. Our data indicates that immunity against HCoVs may enhance SARS-CoV-2 immune responses on infection and vaccination. Anti-spike IgG titers against SARS-CoV-2 and HCoVs by numbers of previous SARS-CoV-2 vaccines SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants, determined by the absence of SARS-CoV-2 nucleocapsid antibodies, are shown by numbers of previous SARS-CoV-2 vaccination (N=780). Geometric mean titers are listed. Data were analyzed by Kruskal–Wallis test. ** P<0.01. Disclosures Julia Upton, MD, ALK Abello: Advisor/Consultant|ALK Abello: Grant/Research Support|Bausch Health: Advisor/Consultant|DBV Technologies: Grant/Research Support|Pfizer: Advisor/Consultant|Pharming: Advisor/Consultant|Regeneron: Grant/Research Support|Sanofi: Grant/Research Support

Comparative analysis of salivary cytokine profiles in newly diagnosed pediatric patients with cancer and healthy children

Salivary cytokines have the potential to serve as biomarkers for evaluating cancer progression and treatment response in specific cancer types. This study explored salivary cytokine profiles in pediatric cancer patients and healthy controls, examining changes during chemotherapy. We conducted a prospective study involving newly diagnosed cancer patients and healthy controls under 19 years old. Saliva samples were collected at diagnosis, and three and six months post-diagnosis for cancer patients, while healthy controls provided samples at a single time point. Cytokine levels were analyzed using Luminex technology. Our study included 19 cancer patients (10 with leukemia, 5 with lymphoma, and 4 with solid tumors) and 128 healthy controls aged 4 to 18 years. At diagnosis, patients with leukemia and solid tumors showed elevated levels of interferon-γ, interleukin (IL)-1α, IL-1β, IL-4, IL-5, IL-8, IL-10, and tumor necrosis factor. After three months, IL-6, IL-10, and inducible protein-10 levels significantly increased, while IL-1α, IL-1β, and IL-8 rose by six months. These findings indicate that salivary cytokines are elevated at diagnosis and during initial treatment phases in pediatric cancer patients, highlighting saliva’s potential as a noninvasive medium for early detection of systemic diseases in children.

Screening for comprehensive social needs in patients with cancer: a narrative review.

Patients with cancer who report social needs have worse quality of life, lower healthcare access, and suboptimal health outcomes. However, screening for social needs does not happen systematically and successful screening tools, strategies, and workflows have seldom been described. The downstream effects of screening including resource navigation have also not been well characterized. This objective of this narrative review was to fill these gaps. Two investigators searched Pubmed and Embase for studies that implemented a patient-facing social screening tool among patients with cancer between 2008-2023 using search terms including "social screening," "social needs," and "cancer." We identified 19 articles that met study inclusion criteria. The most common tool used was the validated Health Leads Social Toolkit. Most often, screening tools were administered electronically, sent directly to patients, and captured needs at a single time point during a patient's diagnosis. Screening response rates ranged between 10-60%. Less than half of the studies described downstream resource navigation for patients who screened positive for social needs Only one study evaluated the impact of screening on clinical outcomes and quality of life. Screening for patients who do not speak English or who belong to historically racial, ethnic, and gender minority groups was limited. Screening for social needs has been shown to be feasible across delivery systems with numerous validated tools available. However, gaps remain in generalizability to diverse patient populations. Future work must identify how screening workflows can be successfully incorporated into routine clinical workflows.

No microorganism was detected in amniotic fluid of healthy pregnancies from the second trimester to the delivery

BackgroundThe early colonization and establishment of the microbiome in newborns is a crucial step in the development of the immune system and host metabolism. However, the exact timing of initial microbial colonization remains a subject of ongoing debate. While numerous studies have attempted to determine the presence or absence of intrauterine bacteria, the majority of them have drawn conclusions based on sequencing data from maternal or infant samples taken at a single time point. In this study, we aimed to investigate the microbial population in amniotic fluid (AF) from the second trimester until the time of delivery using multiple microbiological methods.MethodsAF samples were collected during the second trimester (19–21 gestational weeks) and at the time of delivery. Cohort 1 included 51 women who underwent the term and elective cesarean section, with both their second trimester and delivery AF samples (n = 55, respectively) analyzed. Cohort 2 contained 22 women who experienced infection-related adverse pregnancy outcomes (including preterm birth, histological chorioamnionitis, and stillbirth), with only their second trimester AF samples (n = 24) examined. Additionally, multiple procedural negative controls and technical positive controls were applied to this study to remove potential contamination. Microbial profiles were assessed through cultivation, quantitative real-time polymerase chain reaction, 16S ribosomal RNA gene sequencing, and cytokine analysis.ResultsIn cohort 1, the bacterial load and community structure in the second trimester AF samples were indistinguishable from negative controls. Although marginally higher bacterial loads and different bacterial communities were observed in the delivery AF samples compared to negative controls, these bacterial DNA were not considered biologically functional due to the absence of maternal inflammatory responses. In cohort 2, the bacterial load and community structure of the second trimester AF samples differed significantly from those of negative controls, with Ureaplasma and Lactobacillus identified as the most prevalent genera against negative controls.ConclusionsOur study demonstrates that no microorganisms were detected in the AF of healthy pregnancies from the second trimester to the delivery. The presence of Ureaplasma and Lactobacillus in the second trimester AF may be associated with infection-related adverse pregnancy outcomes.6irEaCsybXVfgvknzcqbk-Video

P1317 Oral microbiota is linked to the propensity for mucosal healing: A prospective oral-gut-stool microbiome analysis in IBD

Abstract Background The oral cavity is the second most complex human microbial niche and is the conduit through which initial gut microbial colonisation occurs during early life. While the gut microbiome is implicated in the pathogenesis of inflammatory bowel disease (IBD), the role of the oral microbiome remains underexplored. We aimed to characterise the oral-gut microbiome in IBD and its association with disease activity and complete mucosal healing (CMH), a key prognostic marker for long-term remission. Methods All patients with Crohn’s disease (CD) and Ulcerative Colitis (UC) were prospectively recruited via www.musicstudy.uk. We conducted a 3-stage experimental approach. (1) We profiled the oral microbiota in IBD vs healthy controls (HC) (CD = 34, UC = 24 and HC = 25). (2) We carried out trans-anatomical oral-ileal-stool microbial source tracking1 within the same patients at a single time-point (CD = 23; inflamed vs. non-inflamed mucosal samples), alongside longitudinal oral-stool sampling (CD = 32, UC = 17). (3) Our machine learning (ML) modelling integrated stool microbiota taxonomic profiles (CD = 53, UC = 11; sampled at 0, 3, and 6 months) with ~80 clinical variables to classify CMH using random forest, AdaBoost, XGBoost, logistic regression, and neural networks. Results 16S rRNA sequencing revealed significant divergence between IBD and HC oral microbiota (PCoA, Bray-Curtis; PERMANOVA, p=0.003). Active disease also differed from remission (PCoA, Bray-Curtis; PERMANOVA, p=0.01). Higher oral Veillonella abundances were associated with IBD; bacteria commonly enriched in the IBD gut. We determined within patient oral microbiota abundances in gut samples and found no difference between inflamed ileal mucosa compared to non-inflamed (p=0.52). Patients who did not achieve CMH exhibited significantly higher oral microbiota abundances in stool compared to those with CMH (β = 0.046, p=0.022, linear mixed-effects model). Oral microbiota abundances in stool correlated with clinical markers of disease activity, calprotectin (r = 0.23, p=0.009) and albumin (r = –0.28, p=0.002; Benjamini-Hochberg adjusted). ML models integrating stool microbiota taxonomic profiles and clinical variables outperformed clinical markers alone in predicting CMH (AUC: 0.79 vs. 0.55), indicating that the inclusion of stool microbiota features could be valuable in predicting CMH in the clinical setting. Conclusion Our data show distinct oral microbiota taxonomic profiles in IBD and active disease, with higher oral microbiota abundances in stool associated with lack of CMH. These findings highlight the oral microbiome as a potential upstream regulator of microbial-immune crosstalk from the site of IBD-inflammation.

Enterprise Risk Management and IT Resources impact on Sustainable Competitive Advantage through mediating role of Knowledge Management Capability

Purpose – This study seeks to determine impact of enterprise risk management (ERM) and information technology resources (ITR) on sustainable competitive advantage (SCA) through mediating role of knowledge management capability (KMC). Methodology – An investigation based on empirical research was carried out on 183 software companies in Lahore, Rawalpindi, Islamabad and Karachi, Pakistan. A self-administered survey was conducted to obtain the data from software companies. The study employed stratified random sampling for participant selection and data were analyzed through partial least squares structural equation modelling (PLS-SEM). Findings – Results revealed ERM and KMC significantly contribute to SCA. However, ITR did not directly impact SCA, yet it showed an important mediated effect on SCA through KMC. Also, KMC mediates relationship between ERM and SCA. Implications – The outcomes of this study contribute to resource based view (RBV) theory by demonstrating that ERM, ITR and KMC play pivotal roles in achieving SCA within the IT industry. Policymakers and industry leaders are encouraged to support these areas to help companies anticipate risks, optimize resources and thrive in global markets. Limitations – This study focused exclusively on private software companies located in four cities (Islamabad, Rawalpindi, Lahore and Karachi) within Pakistan. Additionally, the cross-sectional, survey-based methodology captured data only at a single point in time. Originality – The novelty of this article lies in fact that it addresses the gap in existing research through exploring effect of ERM and ITR on SCA through mediating role of KMC in Pakistani private software companies.

Neighbourhood Effects Across Generations and the Reproduction of Inequality.

This paper analyses the enduring impact of neighbourhood deprivation on youth development, exploring multigenerational aspects often overlooked in existing research. I investigate how neighbourhood environments experienced across two generations impact youth outcomes, focussing on cognitive skills and socio-emotional behaviour. Using data from the 1958 National Child Development Study in the UK, this study employs a Regression with Residuals (RWR) design to comprehensively assess any long-lasting effects. The results point to an enduring impact of neighbourhood deprivation on both outcomes, revealing that sustained exposure to disadvantage drives persistently different developmental trajectories. I find evidence for a transmission mechanism, indicating that exposure to neighbourhood deprivation during parental own formative years affects their offspring's outcomes, directly and indirectly. While parental formative neighbourhood environments significantly shape cognitive development through mechanisms related to education and income, socio-emotional outcomes are also influenced by the legacy of neighbourhood context across generations. While conventional approaches focus on a single point in time, this study contributes to neighbourhood effects literature by taking a lengthier perspective and acknowledging the protracted and influential role that neighbourhoods as social institutions may play in shaping individual opportunities and inequality dynamics over time.

Parental Separation and Children’s Education—Changes Over Time?

The association between parental separation and children’s education has been widely studied, but mainly at a single time point and for marital dissolution only. We examine whether the (generally negative) association has changed across cohorts for several educational outcomes and whether the association differs by parental union type (marriage, cohabitation) and socioeconomic family background (parental education).We use Finnish total population register data. We focus on child cohorts born between 1987 and 2003 (N = 967,242) and analyse grade point averages, secondary education and tertiary education using linear regression and linear probability models with standard errors clustered within families.The association between parental separation and educational achievement is negative and has remained similar across the birth cohorts. Differences according to parental union type and socioeconomic family background are rather small. The stability of the association over time suggests that the consequences of parental separation on children’s education have not changed over time, and they do not depend much on parental union type or family background.

Maternal Serum Catestatin Levels in Gestational Diabetes Mellitus: A Potential Biomarker for Risk Assessment and Diagnosis.

Background/Objectives: Gestational diabetes mellitus (GDM) presents significant risks for both maternal and neonatal health, affecting fetal growth and increasing the likelihood of future diabetes mellitus (DM) development in affected women. The dysregulation of metabolic biomarkers, including catestatin, has been implicated in GDM pathophysiology. However, the clinical significance of catestatin in GDM remains poorly understood, particularly in the context of different therapeutic approaches. Methods: This observational, prospective, and cross-sectional study was conducted to evaluate maternal serum catestatin levels in gestational diabetes mellitus (GDM) patients and healthy controls. Data were collected at a single time point during the second trimester of pregnancy (24 to 28 weeks). Participants were categorized based on their glucose tolerance and GDM management strategies (diet regulation or insulin therapy). Results: Receiver Operating Characteristic (ROC) analysis demonstrated the diagnostic significance of serum catestatin levels in GDM, suggesting a cut-off value of >9.61 ng/mL for discriminating between women with and without GDM. However, further research is needed to elucidate the mechanistic role of catestatin in GDM and its utility in guiding therapeutic interventions. Conclusions: Our study highlights the potential of catestatin as a biomarker for GDM risk stratification and monitoring, complementing existing diagnostic tools. Integrating metabolic biomarkers like catestatin into clinical management approaches may optimize maternal and neonatal health outcomes in GDM. However, the limitations of our study, including its cross-sectional design and sample size, underscore the need for future multicenter studies to validate our findings comprehensively.

Lead time trajectory of blood-based protein biomarkers for detection of pancreatic cancer based on repeat testing.

In the current study, we assessed whether repeated measurements of a panel of protein biomarkers with relevance to pancreatic ductal adenocarcinoma (PDAC) improves lead time performance for earlier detection over a single timepoint measurement. Specifically, CA125, CEA, LRG1, REG3A, THBS2, TIMP1, TNRFSF1A as well as CA19-9 were assayed in serially collected pre-diagnostic plasma from 242 PDAC cases and 242 age- and sex-matched non-case control participants in the PLCO cohort. We compared performance estimates of a parametric empirical Bayes (PEB) algorithm, which incorporates participant biomarker history, to that of a single-threshold (ST) method. We demonstrated improvements in AUC estimates (2-13%) for all biomarkers when considering the PEB approach compared to ST. For CA19-9, the PEBCA19-9 yielded an AUC of 0.88 when at least one repeat measurement was within 3 years of clinical diagnosis. At a specificity of 98.5%, the PEBCA19-9 identified 15 of the 41 PDAC cases and signaled positive at an average lead-time of 1.09 years whereas the ST approach captured 11 of the 41 PDAC cases with an average positive signal at 0.48 years. Among CA19-9 low individuals, a PEB algorithm based on repeat measurements of TIMP1 yielded an additional 14% sensitivity at 98.5% specificity. An adaptive algorithm that considers repeated CA19-9 measurements improves sensitivity and lead-time detection of PDAC compared to a single-threshold method. Additional protein biomarkers may improve sensitivity for earlier detection of PDAC among cases with low CA19-9.