Bioengineering

In vitro fertilization (IVF) laboratories equipped with timelapse incubators generate vast quantities of sequential embryo images, yet the absence of standardized, annotated databases impedes the development of reproducible computational tools for embryo assessment. Here we describe the construction of a standardized time-lapse imaging database comprising 631 normally fertilized zygotes from 218 treatment cycles, integrating timelapse image sequences, patient clinical records, and embryo developmental outcomes. We further present a gradient boosting decision tree (GBDT) ensemble framework that integrates zygote morphokinetic parameters-continuous time-series features extracted via a validated CNN-based segmentation algorithm (US Patent US11210494B2)-with conventional embryo assessment grades (categorical features per the Istanbul consensus). The fusion framework employs equal-weight initialization followed by iterative residual-decreasing training to optimally combine heterogeneous feature types. Ablation analysis demonstrated that the integrated model achieved an AUC of 0.78, significantly outperforming morphokinetics-only (AUC 0.71) and conventional-only (AUC 0.65) models, confirming the complementary value of the two data modalities. The database and fusion framework provide a reproducible foundation for embryo development assessment and are generalizable to other multimodal data integration tasks in reproductive medicine.

Objective: To perform internal and external validation of a gradient-boosted decision tree (GBDT) fusion model that integrates zygote morphokinetic parameters with conventional embryo assessment features for blastocyst prediction, and to compare its discriminative performance against senior embryologists. Methods: This retrospective cohort study included 631 normally fertilized zygotes from 218 treatment cycles. A GBDT fusion model integrating 84 zygote morphokinetic parameters and 8 conventional assessment features was evaluated internally (5-fold cross-validation) and externally on a public dataset of 523 embryos with blastocyst outcomes. Model performance was assessed using area under the ROC curve (AUC), area under the precision-recall curve (AUPRC), F1 score, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was compared with embryologist consensus using the DeLong test; agreement was assessed with Cohen's kappa. Results: The model achieved an internal AUC of 0.78 (95% CI 0.74-0.82), AUPRC 0.72, F1 0.73, sensitivity 0.74, specificity 0.77, PPV 0.72, and NPV 0.79. External validation on the public dataset demonstrated acceptable generalizability (AUC 0.76, 95% CI 0.71-0.81). The model significantly outperformed embryologist consensus (AUC 0.70, P<0.001) with moderate agreement (kappa=0.56). Decision curve analysis confirmed clinical net benefit at threshold probabilities of 0.15-0.55. Conclusions: The GBDT fusion model integrating zygote morphokinetics with conventional assessment demonstrates good discrimination and external generalizability for blastocyst prediction, providing an interpretable decision-support tool for embryo selection in IVF practice.

Background: Pain relief is the principal patient-centered goal of surgery for symptomatic lumbar synovial facet cysts, yet comparative reviews have often emphasized cyst recurrence. Whether adding fusion improves postoperative pain or reduces later surgery remains uncertain. Objective: To compare decompression alone with decompression plus fusion, with postoperative back- and leg-pain outcomes as the primary domain. Methods: PubMed, Embase, Scopus, Web of Science, and the Cochrane Library were searched from inception to 2 June 2026. Comparative cohorts and case series with at least five patients were eligible. Twenty-two studies were re-extracted for VAS/NRS scores, change scores, and persistent or recurrent pain. Random-effects restricted maximum likelihood models with Hartung-Knapp inference were used; clinically distinct pain outcomes were analyzed separately. Results: Twenty-two studies (16 cohorts, 6 case series; 51,899 participants) were included. Two studies provided compatible final VAS data. Fusion did not improve postoperative back pain (MD -0.04, 95% CI -0.17 to 0.10; I2=0%) or leg pain (MD -0.03, 95% CI -0.28 to 0.21; I2=0%). Postoperative back pain (RR 0.58, 95% CI 0.14-2.30) and leg/radicular symptoms (RR 0.75, 95% CI 0.42-1.32) were also not significantly reduced. Fusion decreased confirmed cyst recurrence (RR 0.29, 95% CI 0.15-0.57) but not reoperation or subsequent lumbar surgery (RR 0.80, 95% CI 0.42-1.50). Conclusion: Current comparative evidence does not demonstrate superior postoperative pain control with routine fusion. Fusion reduces cyst recurrence without clearly reducing reoperation, supporting selective use when instability is present or anticipated.

This study aims to improve the detection performance of age-related macular degeneration (AMD) in low-quality retinal images. BackgroundAMD is a leading cause of vision loss among older adults globally, and accurate detection is crucial for clinical management. However, low-quality optical coherence tomography (OCT) images significantly compromise diagnostic accuracy. ObjectiveTo enhance AMD detection in low-quality images using noise-augmented data augmentation and an improved YOLO deep learning model. MethodsPublic datasets from UCSD and Duke University were utilized; the training dataset comprised 24,980 OCT images (high-quality and noise-augmented low-quality), while the testing dataset included 1,000 images (584 AMD, 416 normal). The model is based on the YOLOv8n framework, integrated with Squeeze-and-Excitation blocks (SEblock) and Adaptive Sparse Self-Attention (ASSA), with an additional 160x160 detection layer for detecting small lesions. Evaluation metrics included accuracy, sensitivity, specificity, and F2-score. ResultsThe proposed model achieved an accuracy of 99.02%, sensitivity of 98.17%, specificity of 100%, and an F2-score of 98.50% on the Duke dataset. Detection rates were significantly improved compared to traditional methods, particularly in low-quality images, with a detection rate of 89.60%, markedly superior to original YOLOv8n (55.10%) and classical models like ResNet50. ConclusionThe enhanced model, employing noise-augmented training data and improved attention mechanisms, demonstrates excellent AMD detection capabilities in low-quality OCT images, showing broad potential for clinical applications.

Background: Vertebroplasty and balloon kyphoplasty are used for symptomatic vertebral hemangiomas, although comparative evidence is limited. We summarized pain relief, cement leakage, and recurrence after vertebral augmentation and assessed whether direct comparison of the two techniques was feasible. Methods: Five databases were searched from inception to January 2, 2026, with an update on July 5, 2026. Because only one small cohort directly compared vertebroplasty with kyphoplasty, outcomes were pooled as single-arm proportions or, for early pain change, as a mean difference using random-effects models. Prespecified subgroup, sensitivity, small-study effect, and influence analyses were performed. Results: Forty-four studies were included: 33 case series, 10 cohort studies, and one randomized trial. Kyphoplasty-specific evidence comprised one dedicated series and one comparative cohort. Any cement leakage occurred in 10.5% of patients (14 studies; 95% CI 5.7-18.4%), while trim-and-fill gave an exploratory adjusted estimate of 20.4%. Early pain reduction averaged 5.13 points on a 0-10 scale (8 studies; 95% CI 4.48-5.77; I2=89.4%). Complete or near-complete pain relief occurred in 79.4% of patients (10 studies), and recurrence, progression, or retreatment occurred in 3.9% (13 studies). Symptomatic cement leakage was uncommon at 0.4%. Conclusion: The available literature, which is mainly retrospective and vertebroplasty-based, supports substantial pain relief with infrequent symptomatic complications. Kyphoplasty data remain insufficient for a reliable technique comparison. Prospective studies with standardized clinical and imaging outcomes are needed.

Background: Artificial intelligence (AI) systems for glaucoma diagnosis and prognostication from visual fields (VF) are under active development, yet do not audit for vertical-meridian-respecting field loss - known sequelae of stroke, hemorrhage, and neoplasm. We developed a self-supervised encoder of automated perimetry that learns anatomically interpretable VF structure without labels, and evaluated its capacity to identify suspected neurologic VF patterns in an independent public glaucoma dataset. Methods: We pretrained a 128-dimensional masked autoencoder on 23,223 unlabeled Humphrey VFs (patient-grouped training split of 28,943 fields from 3,871 patients; UWHVF, all-comers perimetry), using monocular pattern-deviation input. A supervised linear classifier over vertical-midline latent dimensions was trained on per-eye expert neurological/non-neurological labels and assessed under hard-negative cross-validation, with specificity evaluated on 100 held-out, structurally separated UWHVF controls. External evaluation used the Harvard-Glaucoma Fairness dataset (Harvard-GF; 3,300 patients with paired VF and optical coherence tomography [OCT] from a single academic center), which contributed no data at any training stage. Results: Masked reconstruction recovered structure concordant with retinal neuroanatomy: 50 of 128 latent dimensions emerged spatially specialized, versus 23 for the total-deviation encoder. The classifier achieved cross-validated balanced accuracy 0.78 (95% CI, 0.75-0.82) and AUC 0.85 (95% CI, 0.82-0.89), with no false positives among the 100 held-out controls. Applied to Harvard-GF without fine-tuning, it identified a top-20 of 1,748 glaucoma-labeled patients (1.1%) with morphology inconsistent with glaucoma; all 20 were positive on the rule-based Neurological Hemifield Test (mean score 62.4), and OCT showed preserved superior (Cohen d = +0.68; P < .001) and inferior (d = +0.63; P = .003) retinal nerve fiber layer versus severity-matched controls. Conclusions: A self-supervised VF encoder learned anatomically interpretable visual field structure from unlabeled data and identified suspected neurological cases in a curated glaucoma dataset, with expert, rule-based, and OCT corroboration. Visual field datasets used to train glaucoma AI may benefit from neurological screening before model training; the encoder reported here supports such audits and provides a foundation for neuro-ophthalmic AI beyond fundus photography and OCT.

Conventional transfemoral amputation disrupts native neuromuscular pathways, limiting prosthetic joint control, sensory feedback, and the perception of the prosthesis as part of the body. To ameliorate these pathologies, we restored the agonist-antagonist relationship of residual muscles in two individuals with above-knee amputation through an interventional surgical revision. Participants trained with a bionic knee prosthesis before and after the surgical revision while generating neuromuscular, cortical, functional, and affective data. Both individuals demonstrated improvements after the revision that could not readily be attributed to training effects, including: 1) increased proprioceptive afferents and stronger activation in cortical regions associated with sensorimotor integration of their missing joints, 2) improved control of the bionic knee during functional tasks including sit-to-stand and stair ascent, and 3) generally greater prosthesis embodiment, proprioception, and phantom limb definition as assessed through questionnaires and interviews. In contrast, training outcomes were more participant-specific and more variably correlated with amount of exposure, especially before the revision. These pilot findings suggest that revisional augmentation of residual neuromuscular tissues to restore agonist-antagonist dynamics may promote sensorimotor coherence and enhance both functional and perceptual integration with a bionic prosthesis, and remaining participant-specific heterogeneities may be attributable to inter-individual difference in residual limbs neuromuscular system, amputation history, and personal beliefs about prosthesis usage.

Static force plates (FP) are the gold standard for measuring ground reaction forces (GRF) and computing joint moments through inverse dynamics in gait analysis. However, they are restricted to controlled environments, and the number of steps analyzed is limited by the plates embedded in the floor. To address these limitations, portable solutions such as sensorized insoles, socks, or shoes have emerged. Yet, creating wearable systems capable of measuring three-dimensional GRF in real-world conditions remains challenging. Current sensorized shoes often incorporate thick sensors (up to 2 cm), reducing usability and limiting their application in pathological populations or dynamic tasks like running. This study evaluates the usability of ShokacShoes, a novel sensorized shoe integrating three thin, three-dimensional force sensors, and explores its potential as a Wearable Force Plate (WFP). Eight healthy participants performed slow, natural, and fast walking using two insole configurations. Force and temporal metrics were derived from WFP and FP data. Results indicate that WFP enables accurate step segmentation and detects significant effects of speed and insole type on temporal and force metrics, confirming its reliability under different walking conditions. Comparisons with FP revealed differences in force metrics and signal morphology, though temporal parameters remained consistent. These results are likely due to sensor quantity and positioning. Thereby, ShokacShoes represent a valid solution capable of measuring three-dimensional forces within commercial footwear. Future work will focus on validating the applicability of a new version of ShokacShoes against gold-standard FP in a comprehensive validation study involving diverse real-world scenarios and pathological conditions.

Purpose: To validate an automated pipeline to detect and quantify focal retinal and choroidal pulsation areas that are synchronous with the cardiac cycle in video indocyanine green angiography (ICGA). Design: Retrospective, observational, hypothesis-generating validation study Subjects, Participants: Consecutive patients with a diagnosis of central serous chorioretinopathy (CSCR) in one or both eyes. Methods: Videos were acquired on Heidelberg HRA+OCT. The pipeline consisted of three steps: signal extraction, foci detection, and quantification. After registration of the constituent frames, each pixel's intensity signal was analyzed at the presumed cardiac frequency (tested from a sample of three detectable frequencies). A synchrony score combining local phase coherence with oscillation amplitude was then derived and computed using a standard deviation ({sigma}) above each video's background oscillation value. Two masked graders marked the retinal and choroidal pulsation areas twice. We compared detection of the pulsation areas against grader consensus using a receiver operating characteristic curve (using multiple grid sizes to divide the scan area) and, separately, using a signal-based area-reduction method to obtain an optimum {sigma} value. Main Outcome Measures: Agreement between the automated algorithm and human graders in detection of pulsation foci, and the optimum threshold multiplier ({sigma}). Results: We studied 20 ICGA videos from 20 eyes. At the 16-pixel grid size, the pipeline achieved a mean area under the curve (AUC) of 0.914, sensitivity of 0.86, and specificity of 0.80. Grader agreement improved with larger grid size, reaching substantial-to-strong levels for choroidal annotations. The two independent validation methods demonstrated similar {sigma} values that differed by 0.62{sigma}, supporting {sigma}=4.0 as the optimum value. Conclusions: We report the first automated method to quantify retinal and choroidal vascular pulsation on video ICGA. It measures pixels that oscillate over time with the presumed cardiac cycle and works reliably at the spatial scale (grid level) where experts agree. Pulsatile hemodynamics may add a new vascular biomarker for glaucoma, diabetes, hypertension, and pachychoroid diseases.

Physiological mirror activity (pMA) is the increase in involuntary muscle activity observed on the contralateral side during unilateral voluntary movement in neurologically healthy participants. This cross-sectional study aimed to explore the relationship between pMA and corticomuscular coherence (CMC) during finger dexterity tasks in young and older adults. Thirty-one right-handed young adults and 24 older adults performed a left-hand finger dexterity task. Electroencephalogram (EEG) signals were recorded from C3 and C4, and electromyogram (EMG) signals were collected from bilateral finger flexors and extensors. pMA was quantified as the change in right-hand EMG from rest to task. Gamma-band CMC was calculated from task-related EEG-EMG pairs, and its association with pMA was analyzed. In young adults, greater pMA was associated with lower CMC (C3- and C4-right flexors), whereas in older adults, greater pMA was associated with higher CMC (C3-left flexor). Young adults may suppress pMA emergence by appropriately monitoring and inhibiting activity, in the hand not performing the task. Conversely, in older adults, the mobilization of the ipsilateral motor cortex may have contributed to pMA emergence. This study suggests that the neuromuscular mechanisms involved in pMA during finger dexterity tasks differ between young and older adults.

Background: Prolonging ambulation is an important treatment goal in children with Duchenne muscular dystrophy (DMD). Clinical management targets 'actionable' (i.e., modifiable) impairments, such as progressive muscle weakness and contractures, that underlie gait pathology. Gait classification may improve clinical decision-making, but the utility of gait classification in clinical practice depends on understanding how underlying, actionable impairments contribute to distinct gait patterns, which remains insufficiently understood. The research questions were: (1) Can DMD gait patterns be accurately classified from actionable impairments? and (2) Can the model's predictions be explained, and do these explanations provide clinical utility and increase trust in the model? Methods: A retrospective dataset of 274 lower-limb observations from 137 assessments in 30 boys with DMD was analyzed, including 3D gait analysis, instrumented strength assessment, and clinical examination (manual muscle testing, goniometry and clinical stiffness scale). Observations were classified into the mildly affected, tiptoeing, or flexion gait pattern. Ten predictors representing actionable impairments were included: nine predictors related to muscle weakness and contractures, and body mass index (BMI). A balanced random forest classifier was evaluated with leave-one-group-out cross-validation. Model interpretability was explored using SHapley Additive exPlanations to generate global and local explanations. An interview with a clinical expert assessed the utility of the explanations as the primary outcome, with trust in and expectations of both the model and the explanations as secondary outcomes. Results: The model achieved an accuracy of 74.5%. Global explanations identified hip and knee weakness, gastrocnemius-soleus contractures, and BMI as the most important predictors across gait patterns. Local explanations illustrated how patient-specific impairments informed individual predictions. The user study demonstrated the clinical utility of the explanations, as they were perceived as interpretable, provided useful insights, and these insights were actionable. The explanations largely aligned with the expectations and increased self-reported trust in the model. Conclusions: Gait patterns in DMD can be predicted from clinically actionable impairments, and explainable artificial intelligence can translate model outputs into meaningful clinical insights. This approach is promising for supporting both general and personalized rehabilitation and orthopedic strategies aimed at prolonging ambulation in DMD. Further validation in larger, multi-center cohorts is needed.

Background and purpose: Patellofemoral pain syndrome (PFPS) is a multifaceted condition where proximal, local, and distal factors may contribute to symptoms and limitations. How these factors collectively contribute to PFPS remains poorly understood. Therefore, this study compared proximal, local, and distal mechanical characteristics between individuals with and without PFPS and investigated their association with pain intensity and functional disability. Methods: Eighty participants were included: 40 individuals with unilateral or bilateral PFPS, 40 healthy controls. Isometric muscle strength of hip, trunk, and ankle was assessed using a handheld dynamometer. Joint alignment (Q-angle, rearfoot angle, pelvic tilt) and muscle flexibility (iliotibial band, hamstrings, quadriceps, gastrocnemius, and soleus) were measured using standard clinical techniques. Pain severity was assessed using a visual analog scale (VAS), and functional disability was evaluated using the Kujala score. Results: Individuals with PFPS showed reduced iliotibial band flexibility, decreased hamstring and soleus length, lower hip abductor strength, and greater anterior and lateral pelvic tilt (all p < 0.02). Multivariate analysis identified reduced iliotibial band flexibility (OR = 7.48) and greater anterior pelvic tilt (OR = 11.75) as independent associates of PFPS. Anterior pelvic tilt predicted pain severity, while anterior trunk muscle strength and Q-angle predicted disability. Discussion: Reduced iliotibial band flexibility and increased anterior pelvic tilt were independently associated with PFPS, while anterior pelvic tilt predicted pain severity and anterior trunk muscle strength and Q-angle predicted functional disability. Clinical assessment and rehabilitation of PFPS should therefore extend beyond the knee to include iliotibial band flexibility, pelvic alignment, and trunk muscle strength.

Abstract Introduction Intrauterine fetal death (IUFD) beyond 24 weeks of gestation, particularly when accompanied by an unfavourable cervix, poses a distinct obstetric challenge in achieving safe and timely vaginal delivery while minimising maternal distress. Mifepristone priming followed by misoprostol and intracervical Foley's catheter combined with misoprostol are both established approaches for cervical ripening and induction of labour in this setting, but direct comparative data especially from Indian tertiary care populations remain limited. Methods This prospective comparative study was conducted in the Department of Obstetrics and Gynaecology, Kamla Raja Hospital, Gajra Raja Medical College (GRMC), Gwalior, Madhya Pradesh, India, over a two-year period (November 2020 - October 2022). One hundred and fourteen women with ultrasonography-confirmed IUFD beyond 24 weeks of gestation were alternately allocated to Group A (n=57; oral mifepristone 200 mg followed by gestational-age-adjusted vaginal misoprostol) or Group B (n=57; intracervical 16F Foley's catheter followed by gestational-age-adjusted vaginal misoprostol). Outcomes assessed included pre- and post-induction Bishop score, induction-to-delivery interval, misoprostol dose requirement, need for oxytocin augmentation, mode of delivery, blood loss, maternal complications, pain (visual analogue scale, VAS), and patient satisfaction. Results Baseline age, parity, gestational age, and pre-induction Bishop score were comparable between groups (p>0.05). The mean post-induction (24-hour) Bishop score was significantly higher in Group A (7.39+/- 2.07) than Group B (6.37+/-1.89; p=0.007). The mean induction-to-delivery interval was significantly shorter in Group A (25.43+/- 6.84 hours) than Group B (29.26+/- 5.54 hours; p=0.0014), and the median misoprostol dose requirement was significantly lower in Group A (50 mcg) than Group B (100 mcg; p<0.01). Mode of delivery, blood loss, oxytocin augmentation requirement, and overall maternal complication rates did not differ significantly between groups (all p>0.05). Pain scores were significantly lower in Group A (VAS 2.83+/- 1.16) than Group B (VAS 6.18+/- 1.69; p<0.0001), while patient satisfaction was comparable between groups (96.5% vs. 91.23%; p=0.244). Conclusions Both mifepristone-misoprostol and Foley's catheter-misoprostol regimens are safe and effective methods for induction of labour following IUFD beyond 24 weeks of gestation with an unfavourable cervix. Mifepristone priming achieved a shorter induction-to-delivery interval, lower total misoprostol requirement, and substantially less procedural pain, making it an attractive first-line option where available, while Foley's catheter remains a safe, low-cost, and widely accessible alternative, notwithstanding lower patient comfort.

Three-dimensional (3D) mural cell morphology is heterogeneous and coupled to vessel geometry, however, measurements from two-dimensional (2D) maximum intensity projections (MIP) obscure overlapping processes and cell-vessel contacts. Accordingly, we developed Mural-VISTA, a semi-automated Python workflow for mural cell-vessel interaction and single-cell topo-morphology analysis of reconstructed surface meshes. This workflow integrates mesh pretreatment, interactive centerline extraction, hierarchical segmentation of cell soma, main axis and secondary processes (branches), and extraction of 36 multiscale (cell process segment level, process level, and whole cell level) topo-morphological and vessel-referenced metrics. Mural-VISTA identified morphological changes in pericytes and vascular smooth muscle cells (vSMCs) with altered RhoA activity. Constitutive active RhoA (RhoA CA) over-expression reduced branch complexity and increased process alignment in both cell types, while increased whole-cell and branch solidity only in vSMCs. Dominant negative RhoA (RhoA DN) over-expression increased branch abundance and reduced branch solidity in pericytes but not vSMCs, suggesting cell-type specific effect of reduced RhoA activity. In conclusion, Mural-VISTA enables quantitative 3D profiling of mural cell architecture and its spatial relationship with the vessel.

Breast cancer survivors frequently experience upper-limb impairments, making continuous monitoring essential for effective rehabilitation. We propose REINA (Recognize-Then-Infer Wearable-to-App AI Framework), a two-stage deep-learning approach for remote monitoring of motor function during breast cancer rehabilitation using wearable-device data. Inertial measurement unit (IMU) signals from wearable devices are first used to recognize physical activities via supervised learning, followed by an activity-specific recurrent neural network (RNN) to infer corresponding electromyography (EMG) signals. REINA establishes reliable inference of neuromuscular activity from wearable IMU data, enabling real-time, cost-effective assessment of motor function recovery in real-world settings.

Adolescent idiopathic scoliosis (AIS) alters spinal geometry and may influence the biomechanical response of the spine during functional postures. However, posture-dependent changes in spinal loading and paraspinal muscle forces in AIS remain poorly understood. This study investigated the effects of trunk posture on intervertebral loading and paraspinal muscle forces using a subject-specific musculoskeletal model of an adolescent with AIS. The spinal deformity was reconstructed from biplanar radiographs and incorporated into a full-body musculoskeletal model. Flexion, extension, lateral bending, and axial rotation were simulated at three incremental magnitudes, with motion distributed across the thoracolumbar spine. Intervertebral compressive and lateral forces around the curve apex and forces in the erector spinae (ES) and multifidus (MF) muscles were evaluated. Trunk flexion produced the greatest compressive loading, reaching 337 N at the curve apex and 372 N two levels below the apex at 30{degrees} flexion. Lateral bending produced pronounced direction-dependent loading: concave-side bending increased lateral forces, whereas convex-side bending increased compressive forces. Axial rotation produced similar but smaller direction-dependent changes. Paraspinal muscle forces were consistently asymmetric, with concave-side dominance of the ES and convex-side dominance of the MF. Flexion and convex-sided movements generally produced greater muscle imbalance, while increasing posture magnitude amplified spinal loading and muscle forces. These findings demonstrate that trunk posture, movement direction, and magnitude substantially influence the biomechanical environment of the scoliotic spine and should be considered when evaluating spinal mechanics in AIS.

Background: Early access to pregnancy assessment units now detects many tubal ectopic pregnancies (TEP) at a stage when they could resolve spontaneously, creating a management dilemma. Methods: We performed a hypothesis-generating exploratory analysis in a retrospective study to assess whether serum progesterone (P4) levels in women with TEP are associated with management outcome. Results: Ninety-one cases of TEP managed in a single centre over three years were analysed. Receiver operating characteristic (ROC) curve analysis was used to explore serum levels of progesterone (P4), first human chorionic gonadotropin (hCG) and peak hCG (alone and in combination) in relation with successful completion of expectant management. Decision-tree analysis using first hCG and P4 was additionally performed to explore clinical sequential risk stratification. 23% (n=21) successfully completed expectant management. P4 concentrations in the expectant management group (median 3 nmol/L, IQR 2.00 to 8.50) were significantly lower than in those requiring surgical or medical management (median 17 nmol/L, IQR 5.75 to 29.25; p=0.0002). Area under the ROC curve (AUC) values for P4, log10 first hCG, log10 peak hCG and P4 with log10 first hCG were 0.766, 0.814, 0.811 and 0.835, respectively, for predicting successful expectant management. However, hCG was not significantly outperformed. Nonetheless, Youden optimised thresholds for hCG and P4 are reported, alongside decision-tree analysis that identified sequential first hCG and P4 thresholds associated with successful expectant management. Conclusion: Lower P4 levels are associated with successful expectant management of TEP but they do not outperform hCG either alone or as an adjunctive marker.

Electrostatic actuation is an emerging technology for generating tactile sensations on capacitive touchscreens through voltage-induced attractive forces between a fingertip and the surface. However, accurate control of electrostatic attraction during natural touchscreen interactions remains challenging because the applied normal force and sliding speed continuously vary, and their effects on the fingertip-screen contact and resulting actuation strength are not fully characterized. Here, we show how normal force and sliding speed systematically alter fingertip- screen contact area and electrical impedance, and use these measured changes to estimate electrostatic attraction during sliding. Contact area, interaction forces, and electrical impedance were measured simultaneously as participants slid their fingertips across an electrostatic surface under systematically varied normal forces and sliding speeds. These measurements revealed condition-dependent changes in fingertip contact, electrical interaction impedance, effective capacitance, derived effective gap thickness, and electrostatic attraction. We then incorporated these measured contact quantities into a physics-informed, data-driven model based on parallel-plate capacitor theory, in which effective capacitance, apparent contact area, and effective voltage determine the estimated electrostatic attraction. The resulting model links force- and speed-dependent changes in these quantities to electrostatic attraction while accounting for inter-participant variability through a participant-specific scaling factor. These findings provide experimentally grounded guidance for designing electrostatic surface-haptic feedback and future adaptive control strategies under realistic touch conditions.

Osteochondral repair requires restoration of zonally organised articular cartilage and subchondral bone, yet translatable implants rarely reproduce this spatial complexity. Here, we developed an off-the-shelf, cell-free multilayer scaffold comprising a superficial 2% (w/v) articular cartilage extracellular matrix (AC-ECM) phase, an intermediate 5% AC-ECM phase and a basal 6% bone ECM (BN-ECM) phase. The scaffold formed continuous interfaces, displayed regionally distinct pore sizes and resisted permanent deformation during cyclic compression. In vitro, constructs seeded with caprine mesenchymal stromal and articular cartilage progenitor cells supported cell expansion and the accumulation of sulfated glycosaminoglycan- and collagen-rich matrix, with regional differences in collagen I, II and X deposition. Following eight weeks of subcutaneous implantation, cell-seeded scaffolds contained more collagenous matrix than unseeded controls, while vascularisation preferentially localised to the BN-ECM phase. The scaffold was then evaluated against empty defects in a caprine osteochondral model for six months. Scaffold treatment significantly improved macroscopic and histological repair, increased chondral tissue fill (~60% versus ~40%), limited cartilage-like tissue extension into the subchondral region and generated a more native-like superficial collagen organisation. Repair tissue further exhibited greater collagen II immunoreactivity, increased ACAN and COL2A1 expression and reduced COL1A2 expression relative to empty defects, although deeper bone repair was not significantly improved. These findings demonstrate that tissue-specific ECM layering can spatially guide endogenous repair and substantially improve cartilage restoration without exogenous cells or growth factors in a clinically relevant large-animal model, while identifying subchondral bone regeneration as the remaining design challenge for complete osteochondral repair.

Background: Newly available arm angle data offers a new dimension to understand rising rates of arm injury in MLB pitchers. Purpose: To evaluate the relationship between arm angle, pitch characteristics, and elbow and forearm injury in MLB pitchers.<br><br> Study Design: Retrospective cohort study; Level of evidence, 3 Methods: Statcast data from 2020 to 2025 and MLB injured list (IL) data were used to evaluate arm angle and pitch characteristics in relation to elbow and forearm injuries. Results are presented with and without requirements on prior season workload and for same-season and next-season injury incidence. A generalized additive model (GAM) was used to capture non-linear dependence and interactions between selected features and injury incidence to the elbow or forearm. Average marginal effect (AME) odds ratios are reported for main effect terms. Results: N = 3,812 pitcher-seasons were included. 29% pitchers who underwent UCLR did so in the same season as a forearm injury (tmean=44, tmedian=27 days to surgery). Arm angle, fastball usage, and their interaction were the three most predictive features. Arm angle was positively related to incidence of injury (ORmeanAME=1.014), fastball usage was inversely related to incidence of injury (ORmeanAME=0.243), and arm angle moderated the effect fastball usage at high arm angle, where increased usage was no longer protective. Slider velocity (ORmeanAME=1.072), spin rate (ORmeanAME=1.001), and usage (ORmeanAME=2.039) also significantly predicted injury risk. Fastball velocity was not significant in any fit, with ORmeanAME=0.999 across all fits. Fit-level Nagelkerke R2 values ranged from .019 to .052. Conclusion: Fastball usage and arm angle, not velocity, predicted elbow and forearm injury risk among MLB pitchers, and arm angle was the single most predictive feature. The heterogeneity of risk factors as a function of arm angle, and the novelty of MLB arm angle data, may explain why fastball usage has been previously underexplored as a risk factor. Keywords: baseball; arm angle; fastball velocity; fastball usage; spin rate; UCL; ulnar collateral ligament; elbow injury; forearm injury; Statcast