Accurate acetabular cup placement is essential in total hip arthroplasty (THA). We hypothesized that the newly introduced Computed Tomography (CT)-based portable navigation system would demonstrate accuracy comparable to that of the imageless portable navigation system. The aim of this study was to compare cup placement accuracy between the CT-based and imageless portable navigation systems of the same platform in THA performed in the lateral decubitus position. This retrospective cross-sectional study included 36 patients who underwent primary THA via a direct lateral approach in the lateral decubitus position. In all cases, both imageless and CT-based portable navigation systems were used concurrently. Postoperative cup alignment was evaluated using three-dimensional CT (3D-CT). The primary outcome was the absolute error in cup inclination and anteversion, defined as the difference between intraoperative navigation values and postoperative 3D-CT measurements in the functional. Secondary outcomes included outlier rates and registration success rates. No statistically significant differences were observed between the imageless and CT-based portable navigation systems in the mean absolute error for inclination (2.2 ± 1.8° vs. 2.3 ± 1.8°, p = 0.93) or anteversion (2.3 ± 2.3° vs. 2.6 ± 2.5°, p = 0.41). There were no significant differences in outlier proportions. The registration success rate was 92% (36/39) due to three technical failures. In this preliminary study, the CT-based portable navigation system demonstrated cup placement accuracy comparable to that of the imageless portable navigation system. Although the CT-based system may provide additional spatial information intraoperatively, its impact on clinical outcomes remains unclear and requires further longitudinal investigation.
Humidity levels, like light and temperature, fluctuate daily yet are less predictable; however, whether humidity can entrain circadian clocks and synchronize animal behaviors with environmental variations remains unknown. Here, we investigate the circadian humidity entrainment in various insects across multiple orders. Insect species respond to humidity cycles with distinct patterns, some active during either wet/dry periods or at the arid-humid transition. When the humidity cue is removed, most species continue to show rhythmic activity associated with the previous arid-humid (AH) cycles. Fruit flies shift their activity accordingly when humidity cycles are altered and remain in the new rhythms under the following free-running conditions (FRC; constant humidity, HH). Moreover, Drosophila clock and hygrosensation mutants have lower rhythmic activity during AH and a significant reduction in rhythms after humidity entrainment (FRC with HH), indicating that core clock components and hygrosensors are essential for humidity-dependent circadian entrainment. Our findings provide strong evidence that humidity is likely to serve as a potential zeitgeber for circadian entrainment in most, but not all, insect systems and should have broad applicability and importance across animal systems. While light and temperature act as the primary zeitgebers, understanding the mechanisms of humidity entrainment will help us better interpret the behavioral patterns of terrestrial animals, particularly small insects susceptible to dehydration.
Accurate uplink channel estimation in high-mobility vehicular networks remains challenging due to rapid channel variations and Doppler effects, especially in systems assisted by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Most existing studies focus on limited user scenarios and static or low-mobility conditions, which restricts their applicability to realistic vehicular environments. This work proposes a Kalman-aided channel estimation framework for multi-user uplink vehicular STAR-RIS systems operating under high mobility. The proposed approach integrates least squares (LS) estimation with discrete Fourier transform (DFT)-based orthogonal pilot design to obtain initial channel estimates, followed by a Kalman filter to continuously track time-varying Rician fading channels modeled with Jakes temporal correlation. Path-loss scaling is incorporated to improve composite channel tracking accuracy. The framework effectively mitigates Doppler-induced estimation degradation and supports scalable multi-user operation. Simulation results show that the proposed estimator consistently outperforms conventional methods in high-mobility scenarios. In particular, the normalized mean square error is reduced by up to 25 dB for the time-switching protocol and approximately 22 dB for the energy-splitting protocol compared with the corresponding baseline estimation schemes. These results indicate that the proposed estimation and tracking framework maintains stable accuracy across a wide range of vehicular operating conditions.
This study investigates the climatic sensitivity and long-term performance stability of a semi-transparent photovoltaic (STPV) system operating in a tropical coastal region of Indonesia. Using a decade of daily meteorological data (2012-2022), we developed a multivariate regression-based environmental modelling approach to evaluate the influence of key climatic variables on performance ratio (PR) and energy yield. Three modelling structures were considered, including a full-variable model, a simplified model based on global tilted irradiance (GTI) and ambient temperature, and a constant PR benchmark. The results indicate that GTI and temperature are the dominant climatic drivers, accounting for most of the meaningful variability in PR. The simplified GTI-temperature model achieved predictive performance comparable to the full model, suggesting that a parsimonious formulation can retain most of the explanatory power while reducing data requirements. The estimated PR values ranged between 0.78 and 0.80, consistent with reported values for tropical photovoltaic systems. Despite observable seasonal and interannual climatic variability, the system exhibited relatively stable performance over the study period, with no clear monotonic decline in energy yield. These findings highlight the applicability of simplified environmental models for performance assessment and planning in data-scarce tropical coastal regions.
Obeticholic acid (OCA), a synthetic analog of chenodeoxycholic acid, was approved in 2016 for the treatment of primary biliary cholangitis. Early clinical trials revealed elevated liver biomarkers in healthy subjects receiving supratherapeutic OCA doses (100-250 mg). OCA was also evaluated as a treatment for metabolic dysfunction-associated steatotic liver disease (MASLD) but was not approved by the FDA due to liver safety concerns. In this in silico study, we investigated mechanisms of OCA-associated liver injury in virtual healthy and MASLD populations receiving supratherapeutic and therapeutic (10-25 mg) doses, respectively. OCA and metabolite exposures in plasma, sinusoidal blood, liver, and gut compartments were simulated using a physiologically based pharmacokinetic model. In the virtual MASLD population, exposures were increased 2-, 5-, and 10-fold in plasma, sinusoidal, and/or liver compartments relative to baseline. Mechanistic parameters relevant to OCA-mediated liver injury, including bile acid transporter inhibition and mitochondrial dysfunction, were incorporated into the DILIsym model. Predicted liver injury was reported as evaluation of drug-induced serious hepatotoxicity (eDISH) plots, and elevations in alanine aminotransferase, aspartate aminotransferase, and total hepatic bile acids. DILIsym simulations recapitulated liver biomarker elevations observed at supratherapeutic OCA doses in healthy subjects and predicted biomarker increases in the MASLD population under conditions of 5- and 10-fold increased exposures relevant to this population. Bile acid transporter inhibition alone reproduced simulated biomarker elevations, whereas mitochondrial uncoupling alone predicted increased biomarkers only at the highest exposures. Results suggest that DILIsym modeling would have predicted the liver safety concerns that led to withdrawal of OCA from the US market.
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Night vision goggles (NVGs) enhance vision under scotopic conditions by amplifying near-infrared light and converting it to a wavelength that can be seen by the human visual system. Although significantly more expensive than monocular systems, binocular NVGs provide the user with independent inputs to each eye, and therefore facilitate stereopsis, the ability to discriminate differences in depth from binocular cues. Past work examining stereopsis through NVGs has been mixed, with early-generation systems showing no evidence for stereopsis while more-modern systems show some evidence for (and others against) stereopsis, albeit at levels below that observed under natural photopic viewing conditions. These studies have examined stereopsis through NVGs under ideal conditions that isolate binocular contributions to depth perception. In the present study, stereopsis through NVGs was examined under more realistic conditions and for more operationally relevant tasks. The results show that stereopsis through NVGs persists even under degraded viewing conditions and provides a binocular advantage for real-world tasks where the perception of depth plays an important role. These results show that limitations in stereoacuity through NVGs are not driven by visual acuity limits, as has been previously argued, and more generally a dissociation between visual acuity and stereoacuity.
Rising global meat demand and nutritional awareness have fuelled interest in sustainable, ethical protein sources. Animal agriculture generates greenhouse gas emissions, land degradation, and water scarcity, creating a need for plant-based meat alternatives. While plant sources face drawbacks such as incomplete amino acid profiles, anti-nutritional factors, and land requirements. Algae emerge as a superior option, delivering exceptionally high protein content (up to 70% dry weight), complete essential amino acids, omega-3 fatty acids, vitamins, polysaccharides, and potent antioxidants, surpassing plant sources in nutrient density, bioavailability, and environmental footprint. This review evaluates the nutritional, environmental, and technological potential of key algal species (microalgae and macroalgae) for meat substitute applications. Algal formulations excel over plant-based counterparts with superior protein quality (PDCAAS >0.9 vs. often <0.8 for plants), rapid biomass growth (10-50× faster than plants), and no arable land requirements, enabling scalable, low-water production. The review addresses challenges such as off-flavors, digestibility, and cost through solutions such as strain selection, biorefinery optimization, and hybrid cultivation systems. An overview of key market players highlights the growing role of algae in alternative meats. By integrating nutritional and industrial perspectives, this work reveals trends positioning algae at the forefront for health-conscious consumers, advocating a "best-of-everything" approach with diverse species to revolutionize sustainable food systems.
Formal theories translate verbal theories into a mathematical representation, such as a coupled differential equation or other dynamical systems, intending to strengthen the deductive power of (clinical) theories and to formulate testable and novel hypotheses. Work in clinical formal theories mainly relies on simulations, which is an intuitive method for evaluating overall model performance, but may fall short of establishing a precise link between the mathematical properties of the model and the dynamic properties of its outcome. Moreover, when the model's outcome contradicts clinical observations, it is unclear where the discrepancy lies and how to improve the model. In this article, we introduce formal mathematical techniques for graphical model analysis, including phase plane analysis, which allows identifying a system's stable and unstable equilibria, and bifurcation analysis, a framework to delineate parameter regimes corresponding to qualitatively different dynamical outcomes for a model. Using two formal dynamic models in psychology (one for panic disorder and one for suicidal ideation), we illustrate those methods through an easy-to-use R package, deBif, with a graphical user interface. These examples demonstrate the importance of using graphical tools to investigate the hypothesized mechanisms of psychological systems.
Sudden infant death syndrome (SIDS) occurs predominantly during sleep between 2 and 6 months of age, suggesting impaired maturation of arousal pathways. The neurobiological mechanisms involved remain unclear. We investigated the role of wake-promoting Orexin (Ox) and Histamine (HA) neurons in SIDS. Cerebrospinal fluid (CSF) Ox levels were measured in 61 living controls and 70 Sudden Unexpected Death Infants (SUDI: 38 SIDS, 32 explained deaths (ED)). HA and tele-methylhistamine (t-MeHA) were analyzed in an additional 46 SUDI (34 SIDS, 12 ED) and 42 controls. Immunohistochemistry was performed on hypothalamic tissue from 11 SIDS and 8 ED cases to quantify Ox and HA neuron numbers. CSF Ox levels did not differ overall between groups but were higher in SUDI infants aged 2-6 months. HA and t-MeHA levels were elevated in SUDI, likely reflecting postmortem release. Ox neuron numbers were increased in rostral hypothalamic region in SIDS compared with EDs, whereas HA neuron numbers were unchanged. SIDS is associated with increased Ox neuronal activity during the peak risk period, possibly reflecting a homeostatic upregulation in response to arousal deficit or repeated stress or hypoxia, while the role of HA system remains to be clarified with more sensitive biomarkers. First study evaluating orexin and histamine systems in SIDS using CSF and postmortem brain tissue. Identifies elevated orexin activity in SIDS infants, particularly in the 2-6 month risk window. No evidence to date for direct histamine involvement; need for more sensitive biomarkers. Suggests orexin system as a potential biomarker for SIDS risk stratification. Highlights the importance of combined neurobiological approaches for prevention.
Global health cooperation is undergoing recalibration. The 2025 America First Global Health Strategy does not introduce entirely new governance instruments but more explicitly prioritizes bilateral agreements, co-financing requirements, and performance-based partnerships within global health cooperation. This commentary examines how the strategy formalizes and intensifies existing dynamics of strategic bilateralism and analyses its implications for low- and middle-income countries. We argue that the significance of the strategy lies less in new governance mechanisms than in the scale, visibility, and political framing of existing ones. While this approach may strengthen domestic ownership and programme integration, it may also reshape bargaining dynamics, fiscal responsibilities, and coordination structures within global health systems.
Aerobic exercise is beneficial in managing Parkinson disease (PD), yet its potential remains less clear in early stages. This study investigates the impact of long-term aerobic exercise habits in individuals with early-stage PD compared with healthy controls. Cross-sectional study. To evaluate whether long-term exposure to moderate- to high-intensity exercise was associated with more favorable physical, cognitive, and patient-reported outcomes in early PD, by comparing "highly active" individuals (self-reported moderate- to high-intensity aerobic exercise ≥ twice weekly for >3 months) with "low-active" individuals (self-reported moderate- to high-intensity aerobic exercise ≤ twice weekly for >3 months) and healthy controls. University. Seventy low-active individuals with PD, 35 highly active individuals with PD, and 35 healthy controls were included. Not applicable. Assessments included Timed Up and Go Test, Six Spot Step Test, 6-Minute Walk Test, Mini Balance Evaluation Systems Test, Lower Extremity Muscle Peak Power, Aerobic Capacity, Physical Activity, Montreal Cognitive Assessment, Symbol Digit Modalities Test, Parkinson's Disease Questionnaire, Non-Motor Symptoms Questionnaire, Falls Efficacy Scale-International, European Quality of Life Questionnaire, Beck Depression Inventory-II, and Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale. Highly active individuals with PD outperformed low-active individuals with PD (p < .05) in physical function outcomes, motor symptom severity, physical activity levels, and nonmotor symptoms, while showing comparable results to healthy controls across several tests covering physical and cognitive function and physical activity level. Low-active participants showed impairments in several physical function and activity outcomes relative to healthy controls (p < .05). Cognitive function outcomes were comparable across the PD groups, but healthy controls performed better in processing speed (p < .05). No significant differences were found between participant groups in quality of life or depressive symptoms. Regular engagement in moderate- to high-intensity aerobic exercise in early PD may preserve physical function, suggesting a potential role in limiting disease-related motor decline. These findings support the consideration of early, high-intensity aerobic exercise interventions as part of a comprehensive management strategy for PD.
Fluvial facies are excellent reservoirs for fluids, critical for both carbon sequestration and hydrocarbon exploration. This study focuses on the Lower Jurassic fluvial deposits on the eastern flank of the Chepaizi Uplift in the Junggar Basin, addressing two key questions: (1) How to reconstruct the morphology of ancient river channels? (2) How to calculate the parameters of these channels (widths, lengths, and distribution ranges)? To achieve these objectives, we developed a quantitative paleodrainage reconstruction model guided by seismic sedimentology and GIS analyses, integrating 3D seismic data and a modern fluvial analog from Daqing Mountain region in Inner Mongolia. Using this method, we reconstructed the Lower Jurassic paleodrainage system and estimated key paleochannel parameters. Key results include: (1) V-shaped valleys are associated with fluvial erosion and high-energy depositional environments, whereas U-shaped and W-shaped valleys develop in low-energy settings. (2) The Lower Jurassic strata are divided into source, transport, and sink units, further subdivided into four sub-source-to-sink zones (P1-P4). (3) Quantitative analysis reveals that the widths of the paleochannels in the study area range from 330 to 1520 m, with lengths ranging from 2 to 9 km. The southern system features wider paleochannels and a greater sediment transport capacity. The areas of the piedmont alluvial fans in P1-P4 are 25.63 km2, 37.69 km2, 17.79 km2, and 41.43 km2, respectively. U-shaped or W-shaped channels are associated with larger depositional areas in these alluvial fans. This study provides practical guidance for hydrocarbon exploration in unexplored Jurassic areas of the Chepaizi Uplift. Meanwhile, the methodology can be applied to reconstructing paleodrainage systems in other terrestrial basins.
Mind‑body practices, such as meditation and yoga, involve paying attention to breathing sensations. During these practices, individuals report "interoceptive lapses," moments when attention drifts away from internal bodily sensations. While lapses in attention to the external world have been widely studied, little is known about the physiological and neural mechanisms of interoceptive lapses. Interoceptive lapses may share markers with exteroceptive lapses-such as reaction time variability and default-mode network (DMN) connectivity-but may also depend on distinct brain systems and breathing physiology. We examined behavioral, physiological, and neural signals preceding lapses in a sample of 93 adolescents enriched for GAD and depression symptoms. Participants performed a 20-min breath counting task in the fMRI scanner with simultaneous breath recordings. Lapses were defined as moments when counting errors occurred. The sample was split into training and validation sets to test machine learning models predicting attentional lapses. The strongest predictors were timing and variability of button responses (AUCs > 0.75). Breathing variability and breathing-behavior synchronization showed smaller but generalizable predictive value (AUCs < 0.65). Whole-brain connectivity models also predicted lapses (AUC ≈ 0.65), incorporating the DMN, dorsal and ventral attention, and somatomotor networks. Furthermore, models that included brain connectivity marginally outperformed behavior-only models. Comparisons to previous exteroceptive findings indicate some common markers (e.g., reaction time variability) and some unique markers (e.g., selective perceptual coupling with attentional networks). Although limited by the clinical sample and lack of a control task, these results highlight brain-body markers of interoceptive attention that may inform real-time monitoring during mind-body interventions.
Agriculture in hilly regions holds significant potential but is often undervalued in the context of food production due to the distinct terrain, microclimate, and subsistence farming practices. This study explores long-term water and energy fluxes across the years 2017-2021, over a rainfed rice-wheat system using the eddy covariance technique to evaluate evapotranspiration (ET) dynamics. Seasonal variation in ET during rice and wheat growing seasons closely follows the daily magnitude of available net energy, relative canopy cover and the supply of soil moisture. The total ET during the rice and wheat growing seasons ranged from 319.39-403.82 mm and 341.81-458.29 mm, respectively, with maximum daily ET values of 7.21 mm day-1 for rice and 6.79 mm day-1 for wheat. Path analysis was used to examine the direct and indirect effects of environmental and biophysical factors on ET, including net radiation (Rn), air temperature (Tair), vapor pressure deficit (VPD), soil water content (SWC), stomatal conductance (Gs), and leaf area index (LAI). VPD was the dominant driver of ET during the rice season, while both VPD and Rn significantly influenced ET during the wheat season. Gs was also a key factor, with stronger control during the wheat season. Notably, VPD had a negative impact on ET through Gs in both seasons. Overall, this study highlights how ET ET in rainfed rice-wheat systems interacts with environmental and biophysical factors, providing insights into crop-water relations and land-atmosphere interactions.
Which infertility treatment pathway is most cost-effective for women with polycystic ovary syndrome (PCOS)-related infertility in centres with expertise in oocyte in vitro maturation (IVM)? Cost-effectiveness analysis of treatment pathways for PCOS-related infertility using a Markov decision-analytic model. Real-life data from 517 anovulatory PCOS patients treated between January 2018 and January 2023 at a Belgian tertiary infertility clinic informed model parameters and defined the treatment-as-usual (TAU) strategy. Five pathways including incremental cycles of letrozole, low-dose gonadotropins, assisted reproductive technology (ART) after conventional ovarian stimulation (COS) or IVM were modelled and compared to TAU. Patients transitioned between treatment cycles, resulting in ongoing pregnancy or drop-out over a 24-month horizon. Costs were assessed from healthcare and societal perspectives, including direct and indirect costs. Incremental cost-effectiveness ratios (ICERs) were calculated, with sensitivity analyses performed. Ongoing pregnancy rates (OPR) after the first, fourth, and sixth letrozole cycles were 16.1%, 41.6%, and 45.7%, with minimal gain beyond 4 cycles. Deterministic analysis identified two cost-effective pathways: (a) 4 cycles of letrozole followed by 2 cycles of low-dose gonadotropins and COS, and (b) 4 cycles of letrozole followed by 2 cycles of low-dose gonadotropins, 1 cycle of IVM, and COS, with ICERs of -€8174 and -€10,805 from the healthcare perspective, and -€11,494 and -€14,083 from the societal perspective, respectively. Incorporating IVM as second-line would require a 25.7% relative OPR increase from IVM, to become the most cost-effective pathway. Probabilistic sensitivity analyses confirmed robustness. This model highlights the role of IVM as a valuable component of PCOS infertility treatment in centres of expertise, with potential for greater impact as culture systems advance.
Policy Points Chronic absence should be recognized as a public health indicator and early warning sign that systems are failing to meet the developmental, social, and health needs of students. Improving student attendance requires cross-sector policy action across education, health, and public health to address the structural and social determinants of chronic absence. A prevention-oriented public health approach is essential, focusing on root causes that schools cannot address alone such as poor health, housing instability, and unreliable transportation. Chronic absence, defined as missing more than 10% of time in school, has risen sharply in the United States following the COVID-19 pandemic and now affects more than one in four students. It reflects unmet health and social needs and is patterned by deep structural inequalities. Both short- and long-term consequences include adverse impacts on educational attainment, health, and social outcomes. Despite this, chronic absence remains largely framed and addressed as an education-sector problem, limiting the scope and effectiveness of current responses. This perspective synthesizes interdisciplinary evidence from education, public health, and child development literature, drawing on ecological and life course frameworks to reconceptualize chronic absence as a public health issue. We develop a conceptual model integrating multilevel determinants of attendance across individual, family, school, community, and structural domains, and identify implications for policy and cross-sector action. Viewing chronic absence through a public health lens reframes it from a purely educational outcome to a signal of unmet need and a multidimensional indicator of system performance. Attendance patterns reflect the interaction of health, social, and structural factors that lie largely outside of the control of schools. Current approaches often emphasize individual responsibility, while overlooking the broader conditions that shape attendance. Reframing chronic absence in this way underscores the need for coordinated cross-sector interventions that address underlying determinants. Positioning chronic absence as a public health priority enables a more coherent response. We propose three principles to guide action: (1) use school attendance data as a vital sign of student and system well-being; (2) develop strategic partnerships to align goals and drive progress; and (3) develop strengths-based policies and programs to prevent chronic absence. Without this shift, efforts to reduce chronic absence are likely to remain fragmented and insufficient to achieve equitable improvements in child health and educational outcomes.
Ovarian cancer is a gynecological malignancy associated with high mortality and poses significant clinical challenges in early diagnosis and precision treatment. Although the rapid advancement of artificial intelligence (AI) has introduced novel approaches to this field, a comprehensive bibliometric overview remains lacking. This study aims to fill this gap by providing a systematic bibliometric analysis of this rapidly evolving domain. In this study, the Web of Science Core Collection (WoSCC) was used to retrieve literature on AI applications in ovarian cancer research published from 2006 to the search date (November 19, 2025). Using CiteSpace and VOSviewer, we conducted visual and quantitative analyses of publication trends, countries/regions, institutions, authors, journals, highly cited papers, and keywords. A total of 786 publications were included in the analysis. The annual publication output showed pronounced exponential growth, with a marked acceleration after 2019. China, the United States, and the United Kingdom were the leading contributing countries. Research hotspots centered on AI-assisted diagnosis, prognostic prediction models, radiomics, and biomarker discovery. The evolution of keywords indicated that frontier research has shifted from basic classification toward more advanced areas, including high-grade serous ovarian carcinoma, multimodal learning, and explainable AI. Research on AI in ovarian cancer has progressed rapidly, with international collaboration concentrated among leading contributors such as China, the USA, and the UK. Future efforts should prioritize the development of explainable and robust clinical AI systems, deeper integration of multimodal data, closer collaboration between clinicians and AI researchers, and high-quality data sharing to facilitate the translation of research findings into precise clinical practice.
Fungal infections, especially in people with weakened immune systems, are a significant global health burden. Accurate identification of fungal morphology from microscopic images is a critical step in guiding timely antifungal treatment decisions. However, manual morphological assessment remains highly dependent on expert mycologists and is prone to inter-observer variability. In this study, we propose a hybrid deep learning framework that integrates the ConvNeXtV2-Base architecture with a Multi-Head Attention-based Multiple Instance Learning module for automated classification of microscopic fungal morphology images. The framework was evaluated on the open-access DeFungi dataset, consisting of 3696 microscopic images representing five clinically meaningful fungal morphology classes. In comparative experiments, classical vision transformer (ViT) models achieved 91.20% accuracy, while MIL-enhanced ViT models reached 93.99%. The proposed ConvNeXtV2-Base + MIL hybrid method outperformed all evaluated architectures, achieving 98.90% classification accuracy. These results establish a new benchmark for automated fungal morphology classification and highlight the potential of AI-assisted decision-support tools to aid expert mycologists in morphology-based assessment workflows.
While post-exposure prophylaxis (PEP) is considered a gate way to pre-exposure prophylaxis (PrEP), prospective evidence remains limited. This study aimed to investigate the association between PEP experience and subsequent PrEP initiation. A nested case-control study was conducted within a prospective cohort of men who have sex with men (MSM) in Qingdao, China. Cases were participants newly initiating PrEP, matched to four controls selected from participants who were at risk of initiating PrEP at the exact time the case occurred. The primary exposure was self-reported baseline PEP use, classified as never, ever, or recent use. Supplementary analyses examined PEP use at the visit immediately preceding PrEP initiation. A dichotomous exposure categorization grouping strategy was also applied across the above analysis (combining ever and recent users). Conditional Logistic regression estimated associations between PEP and PrEP initiation. Subgroup analyses were performed to assess the potential effect modification. A total of 59 cases and 234 matched controls were included. Baseline PEP experience was not significantly associated with subsequent PrEP initiation (ever use: aOR = 1.79, 95%CI: 0.86-3.69, P = 0.117; recent use: aOR = 1.52, 95%CI: 0.46-4.99, P = 0.488). This lack of a significant association persisted when ever and recent PEP users were combined into a single "prior use" category (aOR = 1.72, 95%CI: 0.88-3.35, P = 0.110). However, subgroup analyses showed that among participants who report recent recreational drug use, those with a history of PEP use were more likely to initiate PrEP (aOR = 2.25, 95%CI: 1.09-4.64, P = 0.029). These findings suggest that to effectively leverage PEP encounters as a gateway to sustained prevention, health systems should prioritize and intensify linkage interventions for high-risk groups identified during the PEP consultation, particularly individuals who use substances. Transforming PEP encounters into opportunities for tailored intervention can strengthen the HIV prevention cascade for those most in need.