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Cannabis is one of the most common substances used during pregnancy. This study examined motivation to quit cannabis use among pregnant women enrolled in a randomized controlled trial of a technology-delivered brief motivational intervention targeting sexually transmitted infection (STI) risk behaviors, including substance use. Secondary analyses used data from a clinical trial among pregnant adults who screened positive for STI risk behavior (e.g., sexual behavior and alcohol/drug use risk during pregnancy). Four subscales (autonomous, introjected, external, and amotivation) from the Treatment Self-Regulation Questionnaire assessed motivation for not using cannabis and the timeline follow-back assessed cannabis use at baseline, 2-month, and 6-month follow-up during pregnancy. Mixed logistic regression and negative binomial regression investigated the relationship between motivation and cannabis use (Y/N) and cannabis use days, respectively, with a generalized estimating equations approach after adjusting for age and marital status. Of 176 participants (mean age: 30.2 [standard deviation = 5.0]; 26% Black), n = 62 (35.2%) reported cannabis use during pregnancy. Participants with cannabis use during pregnancy were more likely to be younger, Black, and have lower socioeconomic status than those with no cannabis use. Higher autonomous, introjected, and amotivation scores were associated with lower odds of cannabis use (p = 0.0003, p = 0.0033, p = 0.0307, respectively). Higher autonomous, introjected, and external regulation scores were associated with fewer average cannabis use days (p = 0.0013, p = 0.0035, p = 0.005, respectively). Higher levels of motivation are associated with less cannabis use during pregnancy. Given psychosocial barriers to treatment, these findings may support delivery of brief technology-delivered motivational interventions to reduce prenatal cannabis use.

Black men experience a disproportionate burden of lung cancer yet remain underrepresented in screening and smoking cessation programs. Community-based approaches combining culturally relevant information with patient navigation may help address these gaps. This Phase II developmental feasibility study examined a culturally targeted, navigator-led lung health intervention to support knowledge, decision-making, and early engagement with lung cancer screening and cessation resources among Black men who smoke (March 2023-June 2024). Forty participants recruited through barbershop outreach completed three staged sessions-an in-person educational visit with targeted materials and a screening decision aid, followed by brief navigation contacts. Outcomes were assessed at baseline, post-intervention, and 6-week follow-up. Participants demonstrated improvements in lung cancer-related knowledge, decisional clarity, and readiness to consider screening and cessation. Satisfaction with targeted materials and navigator support was high. Nearly half reported contacting healthcare providers regarding screening, and some scheduled low-dose CT examinations, while Quitline engagement remained modest. Findings support the feasibility and acceptability of culturally targeted navigation delivered in barbershops and may strengthen early behavioral engagement along the lung health continuum for Black men. Larger controlled trials with longer follow-up are needed to evaluate sustained behavioral outcomes.

Valsalva retinopathy is a well-recognized cause of sudden, painless visual loss resulting from preretinal hemorrhage following an abrupt increase in intrathoracic or intra-abdominal pressure. It is most commonly associated with activities such as coughing, vomiting, and physical exertion. We report the case of a 23-year-old previously healthy male who presented with acute, painless visual loss in the left eye following khat chewing and brief hanging from a window. Ophthalmic examination revealed a dense premacular hemorrhage associated with marked visual impairment. Optical coherence tomography (OCT) confirmed a subhyaloid hemorrhage, demonstrating a dome-shaped premacular hemorrhagic cavity beneath the posterior hyaloid face. A diagnosis of Valsalva retinopathy was established based on the clinical and imaging findings. The patient underwent Nd laser hyaloidotomy using a Q-switched Nd laser, resulting in successful drainage of the hemorrhage into the vitreous cavity. At one-month follow-up, complete visual recovery (6/6) was achieved, with complete resolution of the hemorrhage and no procedure-related complications. This case highlights an uncommon presentation of Valsalva retinopathy following brief hanging from a window. The hanging episode was considered the most likely precipitating event because of its potential to generate substantial Valsalva stress and a sudden increase in retinal venous pressure. Although khat use has not been established as a direct cause of Valsalva retinopathy, its sympathomimetic cardiovascular effects may have contributed to vascular susceptibility. This report expands the spectrum of atypical triggers associated with Valsalva retinopathy. Valsalva retinopathy should be considered in young patients presenting with sudden visual loss, even when the precipitating event is unconventional. Early treatment with Nd laser hyaloidotomy can result in excellent anatomical and visual outcomes in selected patients with dense premacular hemorrhage.

Modern sequencing technologies can now capture multiple omic layers from the same biological system, but integrating these views into a coherent model is far from trivial. Graph-based deep learning has become an attractive strategy because it can represent complex molecular interactions and sample relationships in a flexible way. In this review, we survey how graphs are constructed and used in multi-omics deep learning models, organizing methods by node schema, edge semantics, interaction type, integration strategy, graph context, and model architecture across bulk, single-cell, and spatial settings. We summarize the strengths and weaknesses of different design choices in terms of interpretability, data requirements, robustness to noise and missing modalities, and suitability for tasks ranging from prediction to mechanism-oriented discovery. Based on these insights, we outline a general, practical pipeline for constructing, curating, and evaluating graphs that can serve as a starting point for new multi-omics studies.

The Health Foundation ran a £6.7M, six-year programme of work that created a consortium of analytical teams embedded in the health and care system across the United Kingdom. Each year, the teams acquired, linked and analysed health and social care datasets with the goal of being responsive to local analytical needs and producing results more quickly than typical academic research. The teams then coordinated their analyses to allow results to be combined into briefing papers for national policy makers without requiring data to be shared and held in a central location. The programme gave insights on a range of health and social care topics including: care for vulnerable patients during COVID, the evolution of children's mental health care, roadblocks in journeys from hospital into community care, and the role of housing quality in health inequalities. As importantly, the programme provides insight into: stakeholder engagement for impact; using patient expertise to improve analysis; best practices for analytical collaboration with government and NHS; and battling information governance for multi-agency data linkage. Drawing on a range of case studies, we describe how the programme shows that complex and novel data linkages are necessary to provide insights that local service planners can act on, and also highlights a complex set of conditions that need to be met to enable impactful analytics using real-world health and care data. We'll also highlight insights into making the NHS 'AI ready': the UK government's plan to use technology to address the challenges faced by the national healthcare system.

Alcohol use is a leading cause of premature mortality in the US. Despite public health recommendations and insurance coverage mandates, alcohol screening and brief intervention (ASBI) in primary care remains underused. To estimate the population-level impact of expanded ASBI delivery on alcohol use and potential years of life lost (YLL) from major alcohol-related causes of death in US adults through 2030, by sex, race and ethnicity, and educational attainment as a proxy for socioeconomic status. This was a decision analytical study that used a dynamic individual-level microsimulation model of nationally representative of US adults (age ≥18 years) from 2000 to 2030 and considered sociodemographic variables, alcohol use, and mortality risks. Four expansion scenarios increasing the annual number of eligible individuals receiving ASBI from 2025 to 2030: scenario 1, expanding alcohol screening (AS) only; scenario 2, expanding brief intervention (BI) by 4 million; scenario 3, expanding BI by 8 million; and scenario 4, universal ASBI delivery. Scenarios were compared with a no-expansion counterfactual assuming historical trends. Prevalence of hazardous alcohol use (>20 or >40 g of alcohol per day for women and men) and YLL per 100 000 before age 75 years from 5 key alcohol-related causes of death (alcohol use disorder, liver disease and cirrhosis, motor vehicle injuries, other unintentional injuries, and suicide) in 2030. The analysis of the microsimulation model found that scenario 3 (additional 8 million BI) and scenario 4 (universal ASBI) had the strongest impact on alcohol use and mortality, and were projected to reduce annual alcohol-related YLL per 100 000 by -51.3 (95% credible interval [CrI], -73.2 to -32.8) and -68.9 (CrI, -102.2 to -44.8) among men, respectively, and -34.1 (CrI, -54.5 to -16.1) and -52.0 (CrI, -75.0 to -30.2) among women, respectively, by 2030. In scenario 4, the gap in YLL from causes associated with alcohol use between low and high education narrowed by -3.5% (-64.5 YLL per 100 000; 95% CrI, -106.3 to -35.9) among men and -4.9% (-31.4 YLL per 100 000; 95% CrI, -56.2 to -12.4) among women. In decision analytical model expanding ASBI delivery in primary care was projected to reduce premature mortality and may represent an important strategy for improving population health. Substantial expansion had measurable but modest potential to narrow socioeconomic inequalities in premature mortality from causes of death associated with alcohol use.

Black adolescents face disproportionate behavioral health and substance use risks amplified by structural racism and discrimination, yet access to culturally grounded, family-centered preventive interventions remains exceedingly rare. Telehealth may advance prevention equity by eliminating geographic and logistical access barriers. A randomized controlled trial enrolled 170 families with Black adolescents (ages 11-12) assigned to T-SAAF-a telehealth adaptation of the evidence-based Strong African American Families program-or a no-treatment control. At 2 year follow-up, 145 families (85%) completed assessments. Youth-reported conduct problems and substance use onset were analyzed using ANCOVA and binary logistic regression, adjusting for baseline scores, age, sex, time between assessments, and caregiver educational attainment. T-SAAF participants reported significantly fewer conduct problems at 2 year follow-up (M = 1.51, 95% CI [1.35, 1.67]) than controls (M = 1.77, 95% CI [1.59, 1.94]; F[1,137] = 4.49, p = 0.036, η2 = 0.032). T-SAAF did not significantly reduce odds of substance use onset (OR = 1.22, 95% CI [0.48, 3.09], p = 0.68). A brief, culturally grounded telehealth family intervention reduced conduct problems among Black adolescents at a 2 year follow-up, relative to a no-treatment control. Substance use onset did not differ between conditions. These findings position digitally delivered, family-centered prevention as a promising, equity-focused strategy for extending evidence-based programming to underserved Black families. Trial Registration ClinicalTrials.gov NCT05253235; registered February 22, 2022.

Postpartum depression (PPD) is a mood disorder affecting women during pregnancy or after childbirth, characterized by persistent sadness, anxiety, and difficulty bonding with the newborn. Symptoms range from mild emotional disturbances to severe depressive episodes requiring urgent clinical intervention. Despite the availability of treatments, PPD often remains underdiagnosed and undertreated. This study demonstrates an efficient method to predict the Edinburgh Postnatal Depression Scale (EPDS) scores based on combined acoustic and linguistic features extracted from speech. Pregnant and postpartum women aged 18 years or older were recruited for a structured screening study conducted between 2023 and 2024 (n = 275). Each participant completed the full EPDS questionnaire and provided a single open-ended audio response recorded via a smartphone application. A multimodal approach combining linguistic and acoustic features was used to predict EPDS scores, capturing both semantic content and paralinguistic markers, such as vocal pitch, speech rate, and prosody, reflective of mood and affect. Features from both modalities were combined using a regressor to produce a numeric EPDS score ranging from 0 to 30. The model achieved a sensitivity of 84.4% (95% confidence interval [CI]: 77.5-89.5) and a specificity of 76.9% (95% CI: 69.0-82.2) at the ≥10 screening threshold, with an area under the curve of 0.886 (95% CI: 0.845-0.922). Regression performance demonstrated a Pearson correlation of R = 0.749 (95% CI: 0.69-0.80) and a mean absolute error of 3.42 compared with the ground-truth EPDS scores. This model demonstrates strong screening performance for identifying PPD risk from brief video responses and can augment clinical workflows by prioritizing follow-up evaluation when elevated EPDS risk is detected.

Protein function prediction is essential and fundamental for drug discovery and disease treatment. In recent years, deep learning methods have achieved notable improvements by exploiting either protein sequence or structural features. Specifically, Convolutional Neural Networks often fail to apprehend global protein topologies due to restricted receptive fields, while Graph Convolutional Networks excel at processing graph-structured data, a singular network paradigm fundamentally lacks the capacity to fully integrate diverse, multimodal features. Furthermore, combining modalities via static feature aggregation frequently limits model efficacy and causes modality interference. To resolve these challenges, we propose the Structure-Sequence Adaptive Synergy network (SSAS-GO), which employs a Multi-Scale Motif Block to extract localized sequence semantic anchors, alongside a parallel Dual-Stream Graph Encoder to capture spatial topologies. Subsequently, these representations are fed into a Task-Adaptive Cross-Modal gating mechanism. This core module dynamically recalibrates the weights of sequence and structural features. On the PDBch test set, SSAS-GO leverages native topologies to achieve state-of-the-art Area Under the Precision-Recall Curve (AUPR) scores of 0.463 for Biological Process and 0.559 for Cellular Component. Remarkably, on the AFch test set, the model achieves a substantial 17.7% relative AUPR improvement for Molecular Function tasks.

We sought to evaluate preliminary efficacy and implementation outcomes of an e-cigarette and tobacco cessation intervention for hospitalised youth in the USA. We conducted a pilot randomised controlled trial at a paediatric hospital with 3-month follow-up from August 2023 to December 2024. Hospitalised youth (14-21 years) with self-reported past 30-day e-cigarette use were eligible. Exclusions included severe medical/psychiatric illness, cognitive impairment and inability to communicate in English. Intervention entailed health education, motivational interviewing counselling, quit planning, nicotine replacement therapy (NRT) and phone booster sessions. Control entailed brief advice and quit programme referral. The primary outcome was self-reported past 30-day e-cigarette abstinence at 3 months with biochemical confirmation with intention-to-treat (ITT) sensitivity analysis. Implementation outcomes included acceptability, feasibility and fidelity. In 144 hospitalised youth enrolled, the mean age was 16.2 years (SD: 1.3) and 62% were female. At 3 months there was no difference in past 30-day e-cigarette abstinence between arms (intervention 43% vs control 42%; p=0.91). In ITT analysis we found the OR of abstinence was OR 0.77 (95% CI 0.27 to 2.19, p=0.62) in the intervention versus control. Mean fidelity score was 43 (SD: 3; out of 50). All intervention participants (n=96) completed the initial in-person intervention, 49% made a quit plan, of those 23% were prescribed NRT. Most (89%) were somewhat/very satisfied with the intervention. Our study is among the first to demonstrate promising implementation but not efficacy of an e-cigarette cessation intervention in hospitalised youth. Future work is needed to enhance intervention efficacy in this population. NCT05936099.

Pancreatic cancer (PC) is a highly lethal malignancy. 4-10% are linked to inherited mutations in genes such as BRCA1/2, PALB2, ATM and mismatch repair (MMR) genes. Germline testing is essential to guide treatment decisions, yet delays remain common. Genetic testing models without pre-test assessment in a Hereditary Cancer Unit (HCU), have emerged as a strategy to improve earlier clinical decision-making. A retrospective, observational and descriptive study was conducted on 223 PC patients (55% male; average age 64 years) who underwent rapid germline genetic testing at Hospital General Universitario Gregorio Marañón (Madrid, Spain) between April 2019 and May 2024. Tests were ordered by oncologists with brief pre-test counseling, followed by a nurse-facilitated consent and peripheral blood collection. Post-test counseling in an HCU was offered for patients with variants of unknown significance (VUS) and pathogenic/likely pathogenic variants (PV), or upon physician or patient request. PV and VUS were identified in 32 (14.3%) and 82 (36.7%) patients, respectively. 50% of PV carriers did not meet familial PC criteria. Actionable mutations were detected in 14 (43.7%) of PV carriers, involving BRCA2 (6/32), PALB2 (1/32) and ATM (7/32). Treatment modifications occurred in 7/223 patients (3%), including PARP inhibitors or platinum-based regimens. Median time from the genetic test request to the results was 48 days (95% CI, 44-52). Mainstream genetic testing in PC is a viable approach to expedite results and facilitate precision oncology. Further studies are needed to evaluate long-term outcomes, cost-effectiveness and the psychosocial impact compared to traditional genetic counseling pathways.

As a part of modeling the production process of activated biocarbon from barley straw, a model of the initial pyrolysis or carbonization stage was developed. Material samples were divided into five particle size ranges and pyrolyzed in a thermobalance at 900 °C under a nitrogen atmosphere with five different constant heating rates. For the modeling, after a brief review of the possible strategies, the Distributed Activation Energy Model (DAEM) was chosen as the most adequate. In particular, the distribution-free variant proposed by Miura and Maki was applied, allowing the activation energy distribution and the pre-exponential factor to be directly derived from experimental data without assuming a predefined analytical form for the energy distribution. The model implementation incorporates a new approximation for the temperature integral and uses five heating rates instead of the customary three. All this results in greater accuracy and detailed characterization, previously unavailable, of a widespread biomass material. A full description of the model hypotheses and procedures is given, and the results are discussed in detail, showing good agreement between experimental data and model predictions. Perspectives for the generalized use of the model, e.g., in CFD contexts, are also discussed, highlighting its robustness and computational efficiency for engineering applications.

Improving overground walking in people with chronic, incomplete spinal cord injury (iSCI) is especially important for older adults, who now represent more than 40% of the SCI population. Age and injury appear to interact to limit neuroplasticity in spared pathways, constraining gains from gait training. Brief episodes of low oxygen breathing (therapeutic acute intermittent hypoxia [tAIH]) may function as a plasticity-promoting primer to enhance the effects of transcutaneous spinal stimulation-augmented gait training (WALKtSTIM), particularly in older individuals. This multicenter, age-stratified, placebo-controlled clinical trial will examine dose- and age-dependent effects of tAIH+WALKtSTIM on walking recovery in 60 adults with chronic (>1 year) iSCI. After an eight-session WALK prewash phase, participants are randomized within age strata (18-49 and 50-80 years) to tAIH+WALKtSTIM or Placebo+WALKtSTIM. The active intervention delivers daily tAIH or Placebo immediately before a 45-min WALKtSTIM session, 4 days per week for 4 weeks. Primary outcomes are walking speed (10-Meter Walk Test), endurance (6-Minute Walk Test), and balance (Timed Up-and-Go), assessed at baseline, during intervention weeks, and 1, 4, and 8 weeks post intervention. Safety and mechanistic measures include lower extremity strength, spasticity, pain, cardiopulmonary function, cognition, autonomic events, and serum testosterone. Findings will determine whether tAIH priming augments WALKtSTIM relative to Placebo, whether extending pretreatment from 2 to 4 weeks (in pooled analyses with BO2ST-I) yields larger or more durable walking gains, and whether age and hormone levels modify responsiveness. These results will inform age-appropriate tAIH dosing strategies and support the development of personalized neuromodulatory rehabilitation for an aging SCI population.

This study examined whether the Brief Observation of Social Communication Change (BOSCC) yields consistent scores when administered by parents versus professionals within the same home environment. Forty-one toddlers (73% male; mean age 28.2 months) at elevated likelihood for autism spectrum disorder completed two BOSCC sessions at home: one parent-led and one professional-led, following identical procedures. The domains, Social Communication (SC), Restricted and Repetitive Behaviours (RRB), and Other Abnormal Behaviours (OAB), were scored by independent coders. Scores were compared using paired t-tests or Wilcoxon signed-rank tests, and consistency was assessed with correlations. No significant differences were observed between parent- and professional-led sessions for Total BOSCC scores or the SC, RRB, or OAB domains (all p > .19; Cohen's d&#x2009;<&#x2009;0.15). Correlations were strong for Total (&#x3c1;&#x2009;=&#x2009;0.90), SC (&#x3c1;&#x2009;=&#x2009;0.83), and RRB (r&#x2009;=&#x2009;.78) scores, indicating high consistency. OAB scores exhibited only moderate correlation (&#x3c1;&#x2009;=&#x2009;0.33), which became non-significant following outlier exclusion. BOSCC reliably captures core autism-related behaviours (SC and RRB) irrespective of whether the session is led by a parent or a professional. Parent-led administration in the home is a valid and scalable approach for naturalistic behavioural monitoring and intervention assessment.

Computational models of visual system function are largely based on the mammalian visual hierarchy, as the exemplar of a large complex visual system. However, the cephalopod visual system provides an intriguing alternative model for vision; it is relatively similar in size, complexity, and acuity to that of mammals, but has a fundamentally different neural architecture. While this system has been largely overlooked relative to more standard model species, renewed interest in the diversity of neural computations across species, along with technical developments allowing for further investigation, have led to insights into this evolutionarily distinct visual system. Here we provide a brief overview of the unique architecture of the cephalopod visual system, and review recent advances in understanding its neural circuitry, visual coding, and potential computational mechanisms. Throughout, we highlight how investigating cephalopod visual processing provides the opportunity to identify both shared and novel principles for visual computations and their neural implementation.

Maternal cardiac arrest is a life-threatening event with both obstetric and non-obstetric causes, requiring rapid, pregnancy-specific resuscitation. Physiological changes in pregnancy reduce the effectiveness of standard Cardiopulmonary resuscitation, necessitating modifications to advanced cardiac life support (ACLS). This review aims to highlight key causes, resuscitation adaptations, and the critical role of perimortem cesarean delivery (PMCD) in improving maternal and fetal outcomes. A structured literature search was conducted across PubMed, Scopus, Google Scholar, and Web of Science using relevant keywords. Studies were screened by title/abstract followed by full-text review, and articles focusing on clinical aspects, techniques, outcomes, and guidelines of PMCD were included, with emphasis on recent high-quality evidence. The literature search included peer-reviewed publications from 2000 to 2025, comprising original research articles, case reports, and guideline documents. Resuscitation follows standard American Heart Association (AHA) basic life support (BLS)/ ACLS with key modifications: provide left uterine displacement (LUD) (15-30&#xb0; tilt) after 20 weeks to relieve aortocaval compression; secure airway early due to difficult airway and rapid desaturation; perform chest compressions slightly higher on the sternum; use upper-extremity/central venous access; and apply standard defibrillation and drug protocols. If PMCD is performed within 5 min of cardiac arrest, it significantly improves maternal return of spontaneous circulation (ROSC) and increases the likelihood of favorable fetal survival and neurological outcomes. Maternal cardiac arrest requires prompt, pregnancy-specific modifications to standard resuscitation to optimize outcomes. Early uterine displacement, effective airway management, and adherence to ACLS protocols are critical, while timely PMCD within 4-5 min significantly improves maternal hemodynamics and enhances both maternal and fetal survival.

Glioblastoma (GBM) as the most malicious primary brain tumor is infiltrative and often unresectable, which coupled with a profoundly immunosuppressive tumor microenvironment (TME) lead to a poor prognosis for patients. Here, we developed a golden vesicular nanoadjuvant (Au/TLR3-V) comprising gold nanoclusters and TLR3 agonist poly(I:C), formulated within an injectable hydrogel (Au/TLR3-V@gel) for locoregional photothermal-immunotherapy of large orthotopic GBM. Upon near-infrared (NIR) irradiation, Au/TLR3-V generated a potent photothermal response that induced immunogenic cell death and promoted dendritic cell (DC) activation. In TME&#x2011;mimicking systems, Au/TLR3-V pre-treated GL261 cells activated DCs accompanied by the upregulation of T&#x2011;cell&#x2011;recruiting chemokines. In murine models of advanced orthotopic GBM, a single intratumoral injection of Au/TLR3-V@gel followed by a brief NIR irradiation orchestrated a two-stage therapeutic process: localized thermal ablation of the tumor bulk (physical reduction) and subsequent release of Au/TLR3-V to facilitate DCs' capture of tumor-derived antigens and subsequently amplify DC activation (biological sweeping). When combined with anti&#x2011;CTLA&#x2011;4 blockade, this therapy achieved an 33% complete cure rate and established potent systemic anti-GBM immunity. By transforming an unresectable and immunologically "cold" tumor into a locally confined immunogenic "hotspot" using a soft, brain-compliant depot, this work provides a promising locoregional approach for unresectable GBM. STATEMENT OF SIGNIFICANCE: The treatment of unresectable glioblastoma is limited by the lack of biomaterials that can simultaneously provide safe intracranial retention, local tumor ablation, and immune activation. This study presents a brain-mimetic injectable hydrogel incorporating a golden vesicular nanoadjuvant (Au/TLR3&#x2011;V@gel) for locoregional photothermal-immunotherapy. The hydrogel offers mechanical compliance with brain tissue and sustained retention, while the released nanoadjuvant amplifies dendritic cell activation in response to tumor antigens generated by photothermal ablation. By coupling local cytoreduction with immune remodeling and further combination with anti-CTLA-4 blockade, this platform achieves durable survival benefits in orthotopic glioblastoma. These findings establish a promising biomaterials-based strategy for intracranial immunotherapy of unresectable brain tumors.

This brief report outlines the history of rabies incidence and its control in animals within the Czech Republic. Furthermore, it provides information on laboratory diagnostic options for post-mortem examination of brain tissue to detect the rabies virus, which are available in the Czech Republic. It also summarizes the recommended procedures to be followed when a laboratory investigation of the central nervous system for rabies is indicated in an animal. Keywords: bat rabies, immunofluorescence test, RT-PCR, transport of samples to the laboratory, State Veterinary Institute.

Despite a wealth of information provided by face perception research, the neural processes by which unfamiliar faces become familiar - particularly via passive exposure - remain poorly understood. Here, we introduce a novel fast periodic visual stimulation electroencephalography (FPVS-EEG) paradigm designed to objectively track neural familiarization Specifically, our paradigm measures the emergence of implicit face identity familiarity during brief, passive repetition learning, without requiring explicit recognition or task engagement. The paradigm uses ecologically valid stimuli incorporating image variations characteristic of forensic material. We tested 28 (18 females) healthy human volunteers including neurotypical civilians and law enforcement professionals, all with typical face processing abilities. Neural responses were measured to a 1 Hz tagged oddball identity embedded within a 6 Hz stream of changing base images, using high-quality mugshot and CCTV-like stimuli. Results showed that neural signatures of implicit familiarity can emerge rapidly within minutes of passive exposure, but only when high-quality mugshot images are used. These familiarity-related responses were characterized by concurrent neural suppression and enhancement, likely to reflect the co-occurrence of repetition detection and identity learning processes. The FPVS-EEG approach reported here provides an objective and quantifiable measure of implicit, early face learning that could complement behavioral assessments and inform future research on individual differences and applied contexts.Significance Statement While there is ample research highlighting differences in the processing of unfamiliar and familiar faces, much less is known about how unfamiliar faces become familiar, particularly at the neural level. Here, we developed a novel paradigm based on Fast Periodic Visual Stimulation to probe face learning implicitly via passive exposure, without explicit recognition decisions. We demonstrated that neural signals of familiarity emerged within 4 minutes of exposure to high-quality mugshots, but not degraded CCTV-like images, for individuals with typical face-processing abilities. Our study offers novel neural measures that can objectively track the earliest stages of familiarization, potentially advancing the study of individual differences in face processing and its applied contexts.