Physiological Reports

Objectives To examine the acute effects of a single bout of high-intensity interval training (HIIT) on fetal blood flow distribution during the third trimester of pregnancy. Methods Thirty-four healthy pregnant participants (mean age 31.6 years, standard deviation (SD) 4.1; gestational week 33.8 (SD 0.4) completed eight 30-second high-intensity cycling work-bouts interspersed with 2-minute rest periods. Fetal heart rate (FHR), maternal blood pressure, and Doppler-derived blood flow indices in the middle cerebral artery, umbilical artery and vein, and ductus venosus were assessed before and after exercise. We estimated fetal liver blood flow and the ratio of umbilical vein flow to ductus venosus. Maternal heart rate (HR) and FHR were recorded throughout exercise. Paired t-tests compared pre- and post-exercise values. Results No significant changes were observed in fetal blood flow indices or distribution following exercise. Average maternal HR and FHR during the work-bouts were 158 bpm (SD 16) and 152 bpm (SD 12), respectively. Following HIIT, maternal systolic blood pressure increased by 5 mmHg (95% CI 1 to 8, p=.014), maternal HR by 22 bpm (95% CI 15 to 28, p<.001), and FHR by 13 bpm (95% CI 10 to 17, p<.001). We recorded 16 instances of FHR above normal range during HIIT. Conclusion A single HIIT session in late pregnancy increased maternal blood pressure and HR and transiently elevated FHR but did not affect fetal blood flow indices or distribution. Brief episodes of fetal tachycardia were observed but appeared to be clinically insignificant. Future research should investigate the effects of repeated HIIT exposure during pregnancy.

This study examined the utility of HRV detrended fluctuation analysis alpha-1 (DFA1) to assess readiness-to-train and exercise durability under varying acute training loads. Nineteen trained cyclists completed two 20-minute time-trials (TT) under rested and fatigued conditions. DFA1 was measured during a standardized warm-up (WU), 20-min TT, and standardized cool-down (CD). Power output (PO) and DFA1 responses were compared across conditions, and associations with performance and fitness (W/kg) were examined. DFA1 values declined with increasing WU and CD exercise intensity (p<0.001) and were significantly attenuated following the 20-min TT (p<0.001). While DFA1 profiles did not differ significantly between rested and fatigued conditions, lower pre-TT DFA1 was associated with reduced TT performance (p=0.022; r=0.55), suggesting relevance to training readiness. Additionally, an 18% decline in DFA1 between 10- and 20-min during the TT (p=0.031), and lower post-TT values at matched intensities were observed (p<0.001), indicating physiological perturbation from the 20-min TT. Fitter participants exhibited lower DFA1 values during the 20-min TT (p<0.001; r=-0.77), suggesting a greater capacity to sustain physiological stress. While DFA1 is responsive to exercise intensity and stress, offering potential to assess training readiness and durability, more robust fatigue protocols are needed to validate DFA1 as training load monitoring tool.

Abstract Purpose: MyotonPRO (MTP) and time-harmonic elastography (THE) are increasingly used to assess muscle mechanical properties, yet they operate on fundamentally different physical principles. MTP measures composite MTP stiffness (N/m) through surface oscillations, while THE quantifies intrinsic shear modulus (THE stiffness, kPa) via propagating shear waves. This study aimed at systematically compare MTP and THE measurements in the vastus lateralis muscle across different contraction intensities and examine how the skin layer and subcutaneous fat (SLSF) thickness influence their relationship. Methods: Twenty-six healthy adults (15 males, 11 females; age 25 [SD 4] years) underwent MTP and THE measurements of the vastus lateralis at rest and during isometric contractions at 15% and 30% maximal voluntary contraction (MVC). Effects of contraction intensities on tissue properties were assessed using univariate analyses of variance with repeated measures. Associations between the different outcomes of THE and MTP technologies were explored using Pearson's correlations and partial correlation coefficients separately for each contraction intensity with adjustment of the SLSF thickness of participants. Results: Both technologies detected contraction intensity-dependent stiffening across all outcomes (p < 0.001). THE stiffness increased from 5.3 [1.2] kPa at rest to 15.6 [6.1] kPa at 30% MVC; THE wave attenuation increased from 0.83 [0.19] to 1.42 [0.36] s/m while MTP stiffness increased from 337.3 [49.3] N/m at rest to 529.4 [160.7] N/m at 30% MVC. Correlations between modalities were weak and condition-dependent. THE wave attenuation did not significantly correlate with any MTP outcome across conditions. Conclusion: MTP and THE detect contraction-induced stiffening through fundamentally different physical mechanisms and should not be regarded as interchangeable. Their correlation is modest at rest and breaks down (or reverses) during active contraction, with subcutaneous fat as a key modifying factor. Clinical trial number: Not applicable.

Background: Post-operative hypotension and vasoplegia are well recognised following cardiac surgery but remain poorly characterised after major non-cardiac surgery, despite associations with acute kidney injury (AKI), cardiovascular complications, and increased mortality. Dysregulation of the renin angiotensin aldosterone system (RAAS) may underpin haemodynamic instability in this setting, yet data in abdominal surgery are limited. Objectives: The POLECAT (Perioperative delta Renin) study aims to determine whether changes in circulating renin concentration (delta renin) from pre-operative baseline to the early post-operative period are associated with post-operative vasoplegia in patients undergoing major abdominal surgery requiring intensive care admission. Methods: POLECAT is a single-centre, prospective observational study conducted at a UK tertiary referral hospital. Adult patients undergoing planned or emergency abdominopelvic surgery with anticipated intensive care admission are enrolled. Blood samples are obtained pre-operatively, within four hours post-operatively, and on post-operative day one to measure renin and a panel of endothelial, renal, and immune biomarkers. The primary outcome is post-operative vasoplegia, defined as the requirement for a vasopressor infusion at 08:00 on post-operative day one. Secondary outcomes include alternative vasoplegia definitions, AKI (KDIGO criteria), vasopressor burden, organ dysfunction, cardiovascular complications, length of stay, and mortality. Multivariable regression, receiver operating characteristic analyses, and predefined subgroup analyses will be performed, with sensitivity analyses addressing missing data. Conclusions: This study will clarify the relationship between peri-operative RAAS dysfunction and vasoplegia following major abdominal surgery. Findings may support biomarker-guided risk stratification and inform future interventional trials targeting haemodynamic instability in this high-risk population.

Background: Quadriceps strength and landing mechanics are two modifiable factors associated with anterior cruciate ligament (ACL) injury risk. Collecting detailed biomechanical data is an arduous task. Identifying a relationship using more easily measured variables, such as quadriceps strength, would offer value for athlete counseling and injury prevention programs. Although quadriceps weakness has been associated with altered landing strategies in ACL-reconstructed (ACLR) individuals, this relationship is less clear in healthy athletes. Purpose: To investigate the association between isokinetic quadriceps strength and peak knee flexion angle during a vertical drop jump in healthy adolescent athletes. Study Design: Secondary analysis of previously collected data. Methods: Healthy adolescent athletes had their dominant leg quadriceps strength measured using an isokinetic dynamometer at 60{degrees}/s from 0-90{degrees} of knee flexion. Landing mechanics were assessed during a vertical drop jump using three-dimensional motion capture synchronized with force plates. Pearson correlation was used to evaluate the association between quadriceps strength and peak knee flexion angle during landing, with statistical significance defined as p < .05. Results: There was a weak negative correlation between quadriceps strength and peak knee flexion angle (p = .017, R = -.22 [-.04, -.38]), suggesting that stronger athletes achieved greater knee flexion angles. Discussion: Greater quadriceps strength was associated with increased peak knee flexion angles during landing; however, the weak correlation suggests that strength explains only a small portion of the variability in landing mechanics. These findings deviate slightly from prior literature in healthy populations but are consistent with studies demonstrating that greater quadriceps strength is associated with achieving greater peak knee flexion in ACLR patients. Accordingly, quadriceps strengthening should remain a key component of multifactorial ACL injury prevention programs.

Purpose: To identify, through iterative user-centered design, the auditory biofeedback requirements and sound preferences supporting gait training in children with cerebral palsy (CP), and to determine which feedback variables, sound mappings, and sound types yield clinically viable and movement-interpretable paradigms. Methods: The iterative process spanned two prototype phases. Prototype A comprised seven paradigms demonstrated to two experienced physiotherapists (Workshop 1A). Two of these were subsequently discarded owing to poor sound-movement interpretability and two were modified. Six paradigms were added to Prototype B, demonstrated to four children, five parents, and one therapist (Workshop 1B) and two therapists (Workshop 2B). Data were analyzed using systematic text condensation. Results: Within-child sound preferences varied with energy level and sensory state on a given day. Sound-movement interpretability tended to suffer for paradigms with greater acoustic complexity (e.g. computer-generated music). Therapists endorsed a repertoire spanning both movement quality and movement quantity targets. Participants independently proposed paradigms rewarding restrained and controlled movement, a feedback category absent from the current prototype. Conclusions: Session-level calibration is preferable to fixed sound profiles, requiring real-time interface support for paradigm adjustment. Acoustic complexity must remain subordinate to movement-sound interpretability. Paradigms targeting movement restraint are a development priority unaddressed in the literature.

Background: Accurate early identification of sepsis remains a major clinical challenge due to its heterogeneous presentation and overlap of clinical signs with the non-infectious systemic inflammatory response syndrome (SIRS). Timely differentiation is crucial for improving patient outcomes, meeting sepsis bundle requirements and reducing inappropriate antimicrobial use. We hypothesized that clinical and laboratory data available within the first 3 hours of patient presentation could be used to identify patients with sepsis to an actionable level of accuracy, in lieu of traditional microbiology results which would not become available until at least 12-24 hours. Data from two independent studies were used to quantify the diagnostic value of demographic, vital, clinical-laboratory, and microbiological data available at three time points for distinguishing retrospectively diagnosed critically ill patients with either sepsis or non-infectious SIRS. A particular focus of this work was an assessment of the utility of SeptiCyte RAPID (Immunexpress Inc., Seattle, Washington, USA) as an aid to sepsis diagnosis, producing actionable data within 1 hour. Methods: Data from two independent study cohorts were analysed. The 510k cohort consisted of 419 adult patients in intensive care (ICU) (MARS, VENUS, and NEPTUNE trials). The Andalusian cohort consisted of 353 ICU patients from the PANGEA study. Logistic regression models, selected by a greedy search algorithm and validated by repeated cross-validation, were used to determine the contributions of different variables to diagnostic accuracy. Diagnostic performance was quantified by area under the receiver operating characteristic curve (AUC). Results: For the 510k cohort, a baseline AUC of 0.69-0.73 was observed using 5-7 vital and demographic variables assessed immediately upon presentation (time T1). The addition of clinical-laboratory variables, in particular SeptiCyte RAPID, within 1-3 hours post-presentation (time T2) increased the AUC to 0.83-0.85). Finally, the addition of microbiological data 12-24 hours post-presentation (time T3) further improved the AUC to 0.90-0.91. Similar results were obtained for the Andalusian cohort. AUC values at the three time points were as follows: At time T1, AUC = 0.67 based solely on vital signs and demographics; at time T2, AUC = 0.87 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data; at time T3, AUC = 0.93 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data + microbiology results). For both cohorts, the most significant variables included temperature, mean arterial pressure, respiratory rate, suspected infection site; SeptiCyte RAPID, procalcitonin, confirmed bacterial infection and positive blood culture confirmation. Conclusions: Accuracy of identification of sepsis increases markedly as demographics and vital signs are supplemented with clinical-laboratory information, and ultimately with microbiological culture results. The fastest improvement occurs within the first 3 hours when laboratory data, and in particular SeptiCyte RAPID results, become available. Integrating rapid host-response testing with SeptiCyte RAPID into time-based diagnostic frameworks may enhance early sepsis recognition, improve antimicrobial stewardship, and support guideline-driven clinical decisions.

Introduction: Menstrual cycle phase has been proposed as a source of intra-individual variability in resting energy expenditure and the thermic effect of food in premenopausal females, yet studies examining the thermic effect of food across menstrual cycle phases report conflicting findings. Methods: This protocol describes a secondary analysis of prespecified outcomes from a non-randomized, two-period crossover trial primarily designed to assess postprandial plasma triglyceride concentrations across menstrual cycle phases (ClinicalTrials.gov: NCT07459465) in 12 premenopausal females aged 18-30 years, free of chronic disease and hormonal contraceptive use, recruited in Ottawa, Canada. Participants complete two experimental sessions: one in the early follicular phase and one in the mid-luteal phase, each involving consumption of a high-fat meal. Eleven secondary outcomes will be reported: fasting resting energy expenditure, thermic effect of food, respiratory exchange ratio, carbohydrate oxidation rate, lipid oxidation rate, desire to eat, hunger, fullness, prospective food consumption, serum beta-estradiol, and serum progesterone. Masked outcome analyses are performed using linear mixed-effects models. Results: Recruitment began on 26 March 2026; results will be reported in the Stage 2 manuscript. Discussion: Findings from this trial may help clarify whether menstrual cycle phase constitutes a meaningful source of intra-individual variability in energy metabolism, with implications for the design of metabolic research in premenopausal females.

Objective: To characterize genome-wide DNA methylation patterns associated with sepsis using the Infinium Methylation EPIC v2.0 platform and to evaluate the feasibility of pooled methylation profiling in a pilot critical care cohort. Design: Single-center pilot epigenome-wide association study using pooled whole-blood genomic DNA and pool-level bioinformatic analysis. Setting: Academic medical center. Patients: Fifty critically ill adults enrolled within 48 hours of illness onset and 20 healthy controls. Interventions: None. Measurements and Main Results: Critically ill patients required mechanical ventilation and/or vasopressor support. Sepsis was defined according to Sepsis-3 criteria. Seventy individual samples were organized into 14 intended pools of 5 individuals each: 7 sepsis pools, 3 critically ill non-septic pools, and 4 healthy-control pools. One critically ill non-septic pool was excluded because of poor DNA quality, yielding 13 analyzable pools. For the primary pooled comparison, 7 sepsis pools were compared with 6 non-sepsis comparator pools comprising 2 critically ill non-septic and 4 healthy-control pools. After quality control and preprocessing with SeSAMe, 876,094 CpG sites were retained. The initial pool-level screen identified 170,897 candidate differentially methylated regions. Application of stringent secondary filters (false discovery rate <= 1%, absolute delta-beta >= 7.5%, and >= 5 CpGs per region) yielded a high-confidence subset with marked directional skewing, including 155 hypomethylated and 32 hypermethylated regions in sepsis. Differentially methylated region-associated genes were enriched in myeloid leukocyte activation, myeloid leukocyte-mediated immunity, defense response to bacterium, neutrophil granule biology, and hematopoietic cell lineage pathways. Additional signals involved microRNA-associated targets, ribosome biogenesis, RNA processing, long noncoding RNAs, and previously uncharacterized loci. Conclusions: In this pilot pooled EPIC v2.0 study, sepsis was associated with a biologically coherent, predominantly hypomethylated methylation signature enriched in myeloid and host-defense pathways. These findings support the feasibility of pooled methylation profiling for discovery-oriented sepsis biobank studies but should be interpreted as hypothesis-generating given the pool-level design, limited effective sample size, heterogeneous comparator group, and lack of direct validation against individual-level methylation profiles.

Abstract Background: Mean platelet volume (MPV) is a simple, low-cost biomarker that reflects platelet activation. Its prognostic value in septic shock remains controversial. We aimed to determine whether MPV at intensive care unit (ICU) admission is associated with hospital mortality in patients with septic shock. Methods: Retrospective cohort study of consecutive adults with septic shock (Sepsis-3 criteria) admitted to a single ICU. MPV, severity scores (SOFA, APACHE II, SAPS II), procalcitonin, and clinical data were collected. The primary outcome was in-hospital mortality. Spearman correlation, univariate and multivariate logistic regression (with Firth's correction), ROC curves, and subgroup analyses were performed. Results: Fifty-eight patients were included; mortality was 58.6%. MPV did not differ between non-survivors and survivors (13.09 {+/-} 1.37 vs. 12.66 {+/-} 1.45 fL, p = 0.259). MPV showed a weak correlation with procalcitonin ({rho} = 0.394, p = 0.002) but not with severity scores. In multivariate analysis adjusting for age, sex, SOFA and comorbidity count, MPV was not an independent predictor of mortality (OR 1.075, 95% CI 0.682-1.755, p = 0.749). The area under the ROC curve for MPV was 0.598 (95% CI 0.444-0.752), significantly lower than that of SOFA (0.837) and procalcitonin (0.836). Subgroup analyses showed no significant association between MPV and mortality in any stratum. Conclusions: In this cohort of septic shock patients, MPV at ICU admission was not associated with hospital mortality and had poor discriminative ability. Widely used severity scores and procalcitonin remain superior prognostic markers. MPV should not be used as a prognostic tool in septic shock. Keywords: Septic shock, Mean platelet volume, Mortality, SOFA, Procalcitonin, Biomarker

Overview: SeptiCyte RAPID is an FDA-cleared gene expression test that quantifies host immune response to aid in the diagnosis of sepsis. The test yields a score (the SeptiScore) ranging from 0-15, distributed across four bands (1-4) based on increased likelihood of sepsis. Each band can be characterized by average positive and negative likelihood ratios (LR+, LR- respectively) for the discrimination of sepsis versus the non-infectious systemic inflammatory response syndrome (SIRS). Methods: A retrospective analysis of prospectively collected data from a combined cohort of critically ill patients suspected of sepsis (N=889), recruited across 19 hospitals in the USA and Europe. The analysis quantified the LR+ and LR- parameters as a function of SeptiScore, for discrimination of sepsis vs. SIRS in patients admitted to ICU. Hypotheses: (1) The likelihood ratio (LR) framework provides a clinically useful interpretive approach that complements the previously used SeptiScore banding scheme; (2) Low Band 1 SeptiScores are associated with sufficiently small LR- to support the use of SeptiCyte RAPID as a rule-out test for sepsis; (3) High Band 4 SeptiScores are associated with sufficiently large LR+ to support the use of SeptiCyte RAPID as a rule-in test for sepsis; and (4) SeptiScore-derived LR+ and LR- values can be combined with estimates of pre-test probability (derived from patient characteristics and/or other diagnostic tests) to generate individualized, patient-specific post-test probabilities of sepsis. Results: The SeptiCyte RAPID test demonstrates strong diagnostic performance in distinguishing sepsis from SIRS. The likelihood ratios across different score bands provide clear clinical utility: the median LR+ was 3.26 (range 2.57-4.24) for Band 3, and 6.97 (range 4.35-15.57) for Band 4 providing evidence toward ruling in sepsis at high SeptiScores. Conversely, the median LR- was 0.16 (range 0.14-0.20) for Band 2 and 0.085 (range 0.014-0.16) for Band 1, providing evidence toward ruling out sepsis at low SeptiScores. A higher-resolution analysis of SeptiCyte RAPID performance confirmed these trends by evaluating LR+ and LR- at specific values within each band. The sepsis group was further stratified according to whether patients were classified as blood-culture positive (BC+) or blood culture negative (BC-), and the detailed LR+ and LR- analyses were repeated. A monotonic increase in likelihood ratio with increasing SeptiScore was consistently observed, independent of whether sepsis patients were culture-positive, culture-negative, or unstratified with respect to blood culture status. Conclusion: High SeptiScores have correspondingly high LR+ values, and low SeptiScores have correspondingly low LR- values, both of which may have clinical utility. High likelihood ratios for band 4 SeptiScores, which precede traditional microbiology results, may provide clinicians with early confidence of a sepsis diagnosis and microbiology diagnostic stewardship. Low likelihood ratios for band 1 SeptiScores may prompt clinicians to consider an alternate diagnosis to sepsis. Such results, obtained early in the diagnostic workup process, may lead to fewer missed diagnoses and more efficient use of hospital resources.

Background: Accurate evaluation of fine motor abilities is a key aspect of neurological rehabilitation. However, conventional approaches like goniometry are limited by variations among raters and their difficulty in detecting active movement. On the other hand, computer vision-based software delivers non-invasive and quantitative analysis of hand movements. An innovative computer-vision-based software tool, F.A.I.R. Chance(C), was developed to track and analyze individual finger joint movements on a camera-equipped laptop and give real-time numerical feedback. However, its metrics require validation in a healthy population before the tool can be used for clinical purposes. Objective: To assess the reliability and validity of finger movement assessment by the F.A.I.R. Chance computer vision-based tool in healthy adult participants. Methods: An observational cross-sectional study was done at MGM School of Physiotherapy, comprising 30 healthy participants between 18 and 60 years of age. Finger movements like flexion, extension, abduction, and adduction were measured with a standard handheld goniometer. These same finger movements were then measured with the tool at two time points separated by a 30-minute interval to determine the test-retest reliability. The tool's measurements were compared with the goniometric measurements to determine its concurrent validity. Test retest reliability was checked by the Intra-class Correlation Coefficient ICC (2,1), while concurrent validity was tested through Pearson's correlation coefficients. Results: Metacarpophalangeal and proximal interphalangeal joint motions demonstrated moderate to good test-retest reliability (ICC: 0.716-0.953) for the F.A.I.R. Chance tool. However, distal interphalangeal joint movements had lower consistency. Good reliability (ICC: 0.754-0.908) was seen for movements of abduction and adduction in the fingers. Strong concurrent validity for extension movements of the metacarpophalangeal joints (r=0.760-0.914) and moderate concurrent validity for flexion movements of the metacarpophalangeal joints (r=0.427-0.604) was demonstrated for all fingers for the F.A.I.R. Chance tool. Concurrent validity for adduction and abduction movements demonstrated a low to fair correlation with goniometric measurements (r=0.210-0.440). This is consistent with previous research showing poor agreement between goniometry and adduction-abduction movements of the fingers. Conclusion: The F.A.I.R. Chance tool shows good reliability and acceptable concurrent validity to assess fine motor movements in the healthy adult population. This sets a basis for further clinical study of the tool in the target population with fine motor impairments. Keywords: artificial intelligence; assistive technology; computer vision; fine motor evaluation; hand function;

Background: Severe cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) are major dose-limiting toxicities of chimeric antigen receptor (CAR) T-cell therapy. Existing pre-infusion biomarkers offer modest discrimination, motivating non-invasive alternatives. Methods: We prospectively enrolled 26 patients with relapsed/refractory large B-cell lymphoma receiving axicabtagene ciloleucel. Pre-infusion (day -1) exhaled breath samples were analyzed by gas chromatography-mass spectrometry for 40 volatile organic compounds (VOCs). Candidates with univariate AUC > 0.65 for severe (grade >=2) CRS or ICANS were carried forward to sensitivity-maximization-at-given-specificity with LASSO regularization (SMAGS-LASSO), which selected separate panels for each outcome. Model performance was assessed by leave-one-out cross-validation with permutation p-values and Harrell bootstrap optimism correction. Results: The 4-VOC CRS panel (heptanal, benzaldehyde, 2-butanone, ethylbenzene) achieved LOOCV AUC 82.5% (80% sensitivity at 88% specificity) and the 3-VOC ICANS panel (nonanal, allyl methyl sulfide, levomenthol) achieved AUC 86.3% (67% sensitivity at 86% specificity). By tertile, severe CRS occurred in 8/9 (89%) high-risk versus 2/9 (22%) low-risk patients (Cox HR 6.82, 95% CI 1.41-32.9, p=0.017) and severe ICANS occurred in 8/9 (89%) versus 2/9 (22%) (HR 8.28, 95% CI 1.73-39.6, p=0.008). Each 1-SD score increase corresponded to a 3.80-fold higher hazard of severe CRS (p<0.001) and 4.36-fold higher hazard of severe ICANS (p<0.001). In head-to-head comparison, the 3-VOC ICANS panel outperformed the modified Endothelial Activation and Stress Index (mEASIX) (delta-AUC +0.36, DeLong 1-sided p=0.008). The 4-VOC CRS panel had numerically higher AUC than mEASIX (delta-AUC +0.19, p=0.150). Conclusions: Pre-infusion exhaled breath VOC panels stratify CAR T-cell recipients by severity and timing of severe CRS and ICANS, providing a non-invasive complement to existing serum biomarkers. Multi-institutional validation is warranted.

Background: Generative AI tools can support data-intensive research by writing code, drafting prose, searching analytical possibilities, and stress-testing claims. They can also produce false citations, drift between statistical specifications, and lose continuity across long investigations. This paper describes a practical workflow for using AI systems in empirical research while keeping discovery, verification, and accountability inspectable. Methods: We developed and applied a three-phase human-AI workflow to a case study of 14 elite Ethiopian distance runners. The dataset contained 22,605 GPS-segments collected across 97 consecutive days in late 2025, supplemented by venue and athlete metadata collected in the field. Phase 1 used an autonomous data-exploration tool to pre-filter the hypothesis space across five seeded research questions. Phase 2 used an AI system under direct human guidance to construct candidate findings into numerical claims, verification scripts, and draft text. Phase 3 used an independent AI system in an adversarial role to stress-test methods, statistics, prose, figures, and citations. The workflow was informed by Pearl's distinction between association, intervention, and counterfactual reasoning, with human judgement retained for research direction, interpretation, and final claims. Results: The workflow produced three empirical analyses and a documented correction process. The analyses estimated an altitude-to-sea-level pace correction of +0.10 min/km per 1,000 m at matched heart rate, showed why pooled altitude-surface regression was not identifiable within this venue system, documented method-dependence in heart-rate-based intensity classification, characterised within-venue route variation as a 64/36 path-fixed-to-trail-variable split with the Sululta label resolving into two functionally distinct sub-venues, and reframed the cohort's training through a 3x3x3 prescription lattice grounded in Ethiopian coaching practice. The adversarial phase identified several hallucinated citations, a terminology error between HC1 and cluster-robust standard errors, and several inconsistencies between prose, figures, and computed results. Verification scripts re-derived nearly all numerical claims from the cleaned lap-level data. Conclusions: The case study shows how researchers can organise AI-assisted empirical work so that candidate discovery, claim construction, independent stress-testing, and final accountability remain separated. The workflow did not remove the need for domain expertise or human judgement. Its value was in making the route from candidate finding to manuscript claim explicit, reproducible, and open to challenge. Trial registration: Not applicable.

Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation, and bronchial remodeling occur in OLD and eventually result in the unique respiratory sounds. Despite its subjective and having low reproducibility, still traditional auscultation using a manual stethoscope is the main method used to identify the lung sounds. Nevertheless, the combination of recent advancements in digital stethoscopes and AI (Artificial Intelligence) has permitted the objective measurement of lung sounds. Nevertheless, there is a lack of standardized, region-specific databases for AI training and validation. Even though lung sound classification is an emerging aspect in research and telerehabilitation the lobar wise acoustic pattern is still novel due to lack of prevailing database to train AI models. Identifying this gap this study aims to develop an acoustic repository and analyze the data using segmental lung sounds from patients with OLDs and healthy controls through an electronic stethoscope. Methods and analysis This is a cross sectional observational study involving 120 participants (60 OLD patients and 60 healthy controls). Lobar wise acoustic signals will be captured using an electronic stethoscope in healthy and diseases population. The data will be analyzed using Audacity software for annotations and then it will be used for feature extraction and statistical analysis. The acoustic features extracted through Audacity, will include frequency, intensity, pitch, and root mean square (RMS) energy. Repeated measures ANOVA will be applied to compare mean sound intensities across lung segments while Pearson correlation will be used to assess associations with body composition parameters. The data will then be standardized for AI-based diagnostic applications. Ethics and dissemination The study is being reviewed from the Ethics Review Committee, Faculty of Medicine, University of Peradeniya (2025/EC/87) will be sought. Informed consent will be obtained in writing. The dissemination of results will take place through peer-reviewed publications and the creation of a public database containing lung sounds from the region.

Objectives: The aim of mammographic screening is the early detection of invasive cancers. In the era of artificial intelligence (AI), this tool may improve diagnosis of earlier stages. The purpose of this study was to assess the impact on selected quality indicators retrospectively. Method: The data source was the Breast Cancer Screening Registry using data from one Screening Unit that currently uses AI routinely. The indicators of the cancer detection rate (CDR), further assessment rate (FAR), and recall rate (RR) in the year 2023, when AI was used, and the year 2022, without AI, in women aged 45-69 were compared. The statistical evaluation used the chi-square test and logistic regression adjusting for the effects of age, a woman's risk level, and the screening round at a 5% significance level. Results: In 2022, without AI, 4,034 women aged 45-69 were included, compared with 4,049 women in 2023 when AI was used. This study showed a non-significant increase in CDR from 5.0 breast cancers detected per 1,000 women (non-AI assessment) to 5.2 (AI-assisted assessment), p = 0.919; OR (95% CI): 1.034 (0.542-1.974), a significant decrease in the FAR from 5.2% to 3.9%, p < 0.001; OR (95% CI): 0.665 (0.529-0.836), and a decrease in RR from 2.4% to 1.9%, p = 0.083; OR (95% CI): 0.754 (0.548-1.037). Conclusion: AI has the potential to be a useful tool in the early detection of breast cancer by improving quality through a decrease in FAR and RR, while probably maintaining CDR.

Background: Periodontitis is defined by cumulative, irreversible tissue destruction, yet population-based measurement typically relies on cross-sectional indicators derived from retained teeth. Destruction that occurred earlier in life, particularly disease severe enough to result in tooth loss, is structurally excluded from these measures, potentially leading to systematic underestimation of lifetime periodontal burden. Objective: To develop and evaluate a measurement framework that estimates lifetime periodontal burden from cross-sectional data by explicitly incorporating informative tooth loss under etiological uncertainty. Methods: Data were drawn from 10,324 adults aged [&ge;]30 years participating in the 20090-2016 National Health and Nutrition Examination Survey (NHANES) who completed full-mouth periodontal examination and glycated hemoglobin (HbA1c) testing. Lifetime periodontal burden was estimated by combining observed clinical attachment loss in retained teeth with probabilistic contributions from missing teeth, using three alternative age-stratified attribution schedules derived from epidemiological studies of periodontal extraction. Performance was compared with conventional measures of periodontal severity and extent using distributional analyses, correlations with HbA1c, discrimination of diabetes status, and relative importance analysis. Age-adjusted models were treated as sensitivity analyses. Results: Estimated lifetime periodontal burden exhibited strong, monotonic age gradients across glycemic categories, in contrast to more attenuated patterns observed for severity and extent. Across attribution schedules, lifetime burden showed stronger correlations with HbA1c ({rho} = 0.30-0.32) than conventional measures. In multivariable models including all indices, lifetime burden retained an independent association with HbA1c, whereas severity and extent contributed little unique information. Discriminative performance for diabetes status was consistently higher for lifetime burden than for conventional measures and remained stable across attribution schedules. Conclusions: Lifetime periodontal burden can be estimated from cross-sectional data by explicitly modelling informative tooth loss rather than restricting measurement to retained teeth. Incorporating historical tissue loss under uncertainty yields a more coherent representation of cumulative periodontal destruction than snapshot-based measures and provides a methodological basis for life-course-oriented periodontal epidemiology.

Objective To examine the effects of combined oral contraceptive (OC) use on clinical markers of ovarian reserve by comparing Anti-Muellerian Hormone (AMH), antral follicle count (AFC), and ovarian volume (OV) before and after starting or stopping OC. Methods This analysis is based on data from a prospective cohort study conducted at the University Hospital Tubingen, Germany, as part of the IRTG-2804 project. A total of 54 healthy women were included and categorized into three groups based on their OC use status: OC starters (n = 12), stoppers (n = 16), and long-term OC-users (n = 26). Each participant underwent a transvaginal ultrasound (including AFC and OV) and serum sampling (including AMH) at two time points (S1 and S2), three to six months apart. OC starters were assessed first during the early follicular phase (day 1-7) and then during active OC intake (day 8-21), while stoppers were assessed in the reverse order. Long-term users were assessed twice during active OC intake. Results OC stoppers showed significant within-group increases in all ovarian reserve markers, including AMH ({Delta} = 2.57 ng/mL, p < .001), AFC ({Delta} = 3.88, p = .004), and OV, which almost doubled (1.94-fold increase; 95% CI [1.35, 2.80], p < .001). In contrast, OC starters exhibited a significant decline in AMH ({Delta} = -1.25 ng/mL, p = .013), but no changes in AFC or OV. No significant longitudinal changes were observed among long-term OC users. Conclusion AMH levels decrease after starting OC use whereas AFC and OV are not affected. In contrast, AMH, AFC, and OV recover within three to six months after stopping OC, suggesting a reversible suppression of ovarian reserve markers during OC use. These findings are clinically relevant for fertility counseling and for the interpretation of ovarian reserve markers in women using hormonal contraception.

Background: Immune-oncology has revolutionized cancer treatment, but some patients fail to benefit due to primary resistance and tumour-immune evasion. Extracellular vesicles (EVs) are secreted by both tumour and immune cells and mediate communication between cancer cells and the immune system. Our study used proteomic profiling of circulating EVs collected from NSCLC patients treated with immune checkpoint inhibitors (ICI) to identify predictive biomarkers of response as well as immune evasion mechanisms related to treatment resistance. Methods: EVs were isolated from plasma collected prior to ICI treatment using peptide-affinity purification and high-throughput proteomics was performed using Proximal Extension Assay. Differentially expressed EV proteins between durable (DR) and non-durable responders (NDR) were identified and evaluated using Cox proportional hazards regression, survival analysis, sex-stratified analysis, as well as pathway and network analysis. Results: Proteomics analysis identified 116 differentially expressed EV proteins between DR and NDR. NDR was characterized by enrichment of inflammatory, angiogenic, and immune-suppressive EV proteins, such as IL1RL1, TFRC, IL6ST, galectins, TNF superfamily death receptors, chemokines, and PCSK9. Pathway analysis revealed enrichment of angiogenesis, chemotaxis, ECM remodeling, and neutrophil degranulation associated with poor progression-free survival (PFS). In contrast, DR to ICI treatment was associated with EV proteins related to T- and B-cell activation and adaptive immunity. Sex-related differences in abundance and association with PFS was observed for certain EV proteins, including IL1RL1 and TFRC. A six protein EV model (IL1RL1, TFRC, ERI1, CCN5, IGFBPL1, and TNFRSF13C) demonstrated good prognostic performance for identifying NDR (AUC = 0.907) and stratified patients into three discrete risk groups. Conclusions: High-plex EV proteomics revealed biologically coherent tumour-immune signaling programs that are associated with ICI treatment resistance. Profiling circulating EVs may improve our understanding of EV-mediated immune evasion mechanisms and identify protein signatures that reflect the tumour immune microenvironment and predict response to immune checkpoint blockade.

Objective: To address the need for improved measurement of the ways contraception impacts the baseline menstrual cycle (i.e., contraceptive-induced menstrual changes; CIMCs) by assembling an interdisciplinary, global research collective to rigorously develop a person-centered measure for CIMCs in multiple languages. As the first step, this paper reports on our conceptual model development, which is the foundation for ongoing measure development. Study design: We conducted 18 focus groups with 106 people experiencing CIMCs while using hormonal or intrauterine contraception in Durban, South Africa, Santo Domingo, Dominican Republic, and Portland Oregon, United States. We used a virtual affinity mapping approach to analyze qualitative data, which was the basis of our conceptual model along with relevant theory and related models in the literature. Results: The conceptual model of experiences with CIMCs depicts the baseline menstrual cycle, including CIMCs and conceptually-linked effects and the impacts and perceptions of those CIMCs. We found key domains of changes in pain, bleeding volume, bleeding patterns, and characteristics of blood. Conclusion: Our CIMC conceptual model will inform development of a measure with evidence of validation across three language and global contexts. Adoption of a person-centered, standardized CIMC measurement across trials will improve knowledge and decision-making between methods.