The rotator cuff (RC) plays a critical role in stabilizing the glenohumeral joint and generating shoulder forces during elevation, yet the engagement of individual RC muscle subregions during loaded shoulder flexion remains incompletely characterized in vivo. This study used ultrasound shear-wave elastography (SWE) to quantify angle-dependent and depth-dependent engagement of supraspinatus (SSP), infraspinatus (ISP), and anterior deltoid muscle subregions during low-load shoulder flexion. Ten healthy young males performed isometric holds at shoulder flexion angles from 0°-120° while supporting an external load corresponding to 10% of maximal voluntary contraction. SWE-derived muscle modulus, as an inference of activity, was measured in anterior-superficial and anterior-middle SSP subregions, superior and middle ISP subregions, and the anterior deltoid. The anterior deltoid demonstrated a progressive rise from 0° [78.8 (42.1) kPa] to 90° [474.0 (127.2) kPa] (p < 0.001). RC subregions presented earlier engagement, with increased activity evident by 30°. Within the SSP, the anterior-middle and anterior-superficial subregions showed the highest activity at 60° [609.6 (112.4) kPa (p < 0.001) and 330.7 (120.6) kPa (p < 0.001), respectively]. In the ISP, the superior and middle subregions peaked at 60° and 90° [401.2 (149.5) kPa (p < 0.01 vs. 0°) and 312.6 (77.8) kPa (p < 0.001 vs. 0°), respectively]. These findings reveal pronounced depth- and angle-dependent differences in muscle behavior and demonstrate that deeper, capsule-adjacent subregions maintained elevated engagement across wider functional ranges. This study provides mechanistic insight into layered RC function, offering a functional framework relevant to rehabilitation strategies and surgical approaches that consider subregion-specific muscle behavior.

Flexible pressure sensors that simultaneously deliver high sensitivity and a broad detection range are highly desirable for wearable electronics but remain constrained by inherent trade-offs. Here, we present a high-performance flexible piezoresistive pressure sensor with microdome-structured MXene/PDMS composites. The sensing mechanism is elucidated through in-situ optical microscopy combined with finite element analysis, which directly visualizes the progressive evolution of the interfacial contact area during microdome deformation under compression. This progressive contact modulation effectively alleviates the sensitivity-range bottleneck. Consequently, the sensor achieves an exceptional sensitivity of 314 kPa-1 in the low-pressure regime while maintaining robust sensing performance across an extended working range (up to 390 kPa). Furthermore, it exhibits fast response and recovery times (31/34 ms) and superior long-term durability over 3000 loading-unloading cycles. This outstanding electromechanical performance enables comprehensive multiscale physiological monitoring, capable of capturing small pressure variations down to 1 kPa including respiratory patterns and arterial pulses, as well as high-load scenarios such as joint flexion and gait monitoring. Building upon these capabilities, a real-time cervical posture recognition system was implemented as a representative paradigm of intelligent health management. By integrating a logistic regression machine learning classifier, the system attained a classification accuracy of 98.5% on the test set. This work proposes a rational structural engineering strategy, providing a versatile and dependable sensing platform for next-generation intelligent health monitoring and human-machine interfaces.

Despite therapeutic efforts, the majority of individuals post-stroke will experience chronic motor deficits, particularly in the hand. Assistive devices such as hand exoskeletons have the potential to improve hand function, but these instruments must provide sufficient flexibility to support a variety of tasks. This study tests the robustness and utility of a novel device, the Bidirectionally Actuated Cable (BAC)-Glove, which provides independent actuation of each digit. The BAC-Glove supports a variety of control modes, including direct user control through electromyography (EMG). Device capabilities in terms of digit movement and fingertip force production were assessed in 5 neurotypical participants. Kinematics were captured with motion tracking and kinetics were captured with a load cell. Another 10 neurotypical participants completed four training sessions with the BAC-Glove to examine the viability of EMG control. Evaluations were performed at the end of the first and last sessions to examine user performance with the device. The device produced coordinated flexion and extension motions of all three finger joints and peak fingertip forces of 15.1 N in flexion and 9.6 N in extension. Participants improved EMG control of the BAC-Glove over the training sessions, as evidenced by significant improvement on measures of object manipulation with the device, such as the Box and Block test (p < 0.05). BAC-Glove is a robust and potentially useful device for assisting manipulation of objects to perform activities of daily living. The proposed EMG control scheme showed sufficient viability to warrant future examination in clinical populations.

A 31-year-old man presented with an acute, ligamentous perilunate dislocation and paresthesia in the median nerve distribution after a dirt bike accident and underwent closed reduction. The following morning, he was treated with carpal tunnel release and open reduction and internal fixation using a 4-anchor suture tape internal bracing treatment technique through a dorsal carpal approach. The construct consisted of a series of internal braces dunked into four carpal anchors to reinforce/recreate the scapholunate interosseous ligament, lunotriquetral interosseous ligament, and dorsal intercarpal ligament without Kirschner wire retention, with an additional limb used to resist excess scaphoid flexion. The patient was immobilized in a short arm cast for six weeks before initiating full range-of-motion and hand therapy. Full weight bearing and strengthening were allowed at 12 weeks. At six months, the patient reported minimal to no pain, was able to form a full composite fist, and could tolerate a dart thrower's motion. He demonstrated a wrist flexion-extension arc of 90o (25o flexion/65o extension) and reported complete resolution of paresthesia since surgery. No radiographic evidence of carpal instability, fracture, or peri-implant failure was observed, and the Quick Disability of the Arm, Shoulder, and Hand (Quick DASH) score obtained through telephone was 14 out of 100 at 32 months postoperatively.

Robotic total knee arthroplasty (TKA) enables repeated intraoperative quantification of preoperative alignment, flexion deformity, and medial and lateral compartment gaps in extension and at 90° flexion before component positioning, but the preoperative patterns guiding functional-alignment planning remain incompletely characterized. This study aimed to derive a pragmatic driver-based classification from preoperative robotic data and evaluate its internal coherence across the surgical workflow. We analyzed 68 consecutive primary functionally aligned robotic TKAs performed by a single surgeon using a CT-based robotic-arm platform. Preoperative variables included hip-knee-ankle angle (HKA), flexion deformity, and independent medial and lateral gaps in extension and at 90° flexion. A 10-case formative series informed concept generation; the finalized hierarchy was then applied to all cases using preoperative variables only. Four phenotypes were derived: bone-driven, ligament-driven, flexion-dominant, and mixed/complex (defined as the co-occurrence of two or more severe deformity drivers). Internal coherence was assessed through release escalation, corrected-state behavior, plan-to-final HKA fidelity, and mechanical and functional-alignment balance. Inter-observer reliability was tested by having five independent surgeons classify all cases blinded, with agreement quantified by Fleiss' and Cohen's kappa. All knees were classified: bone-driven, 40/68 (58.8%); ligament-driven, 6/68 (8.8%); flexion-dominant, 10/68 (14.7%); and mixed/complex, 12/68 (17.6%). Release escalation occurred in 1/68 (1.5%), with no posterior capsulotomy. Overall, 58/63 (92.1%) finished within ± 2° of planned HKA; strict mechanical balance was achieved in 58/62 (93.5%) and functional-alignment balance in 61/62 (98.4%). Flexion-dominant knees showed lower coronal fidelity but complete final balance, suggesting a coronal-sagittal trade-off during functional planning. Inter-observer agreement among the five surgeons was almost perfect (Fleiss' kappa 0.88, 95% CI 0.81-0.93; 92.4% overall agreement). Preoperative HKA, sagittal deformity, and medial-lateral gap asymmetry revealed recurring patterns organized into a four-phenotype driver framework. This classification is best interpreted as an internally coherent derivation framework that showed almost perfect inter-observer reliability (Fleiss' kappa 0.88) but still requires external, multicenter validation and threshold-sensitivity analysis before its clinical utility can be established.

AI models are increasingly explored for radiographic assessment of knee osteoarthritis, but their reliability as an experimental model for KL grading remains uncertain. This study evaluated ChatGPT-5 agreement with expert consensus for KL grading and compared its performance with a secondary AI model. This controlled cross-sectional observer agreement analysis used 630 hand-compiled synthetic posteroanterior fixed flexion knee radiographs selected for technical adequacy, anatomical suitability, and interpretability. Three experienced clinicians, one orthopedic surgeon and two rheumatologists, independently graded all images, and a three-rater majority-consensus expert reference standard was established. ChatGPT-5 assessed the same images using a standardized prompt and image-level protocol. Gemini 2.5 Flash assessed a 112-image subset. Agreement was analyzed using weighted Cohen's κ, Gwet's AC2, and mean absolute error (MAE). Binary classification behavior was evaluated at the KL ≥ 2 threshold. Inter-rater agreement before consensus formation was high: Fleiss' κ was 0.884, Gwet's AC2 was 0.921, and pairwise weighted κ ranged from 0.902 to 0.929. Complete three-rater agreement was observed in 520 radiographs (82.5%), and only 14 cases (2.2%) required adjudication. Compared with the expert reference standard, ChatGPT-5 showed moderate-to-substantial agreement, with weighted κ = 0.680 (95% CI 0.616-0.737), MAE = 0.589, and 60.9% exact five-grade agreement. Exact agreement was highest for KL 0 (81.5%) and KL 4 (66.9%) and lower for intermediate grades. For binary KL ≥ 2 classification, ChatGPT-5 correctly classified 513/630 radiographs, with 81.4% accuracy (95% CI 78.2-84.3), 82.1% sensitivity, 80.3% specificity, 87.6% PPV, and 72.6% NPV. A small but significant shift toward higher grading was observed (p = 0.013), with up-grading more frequent in KL 0-1 and down-grading more frequent in KL 3-4. In the 112-image exploratory subset, Gemini 2.5 Flash showed limited agreement with the expert reference standard (weighted κ = 0.23, MAE = 0.66, exact agreement = 50.0%) and poor agreement with ChatGPT-5 (weighted κ = 0.06). For KL ≥ 2 classification, Gemini achieved 87.5% accuracy, 100% sensitivity, 0% specificity, and 87.5% PPV; NPV was not estimable because no KL < 2 classifications were generated. In this controlled synthetic radiograph study, ChatGPT-5 showed moderate-to-substantial agreement with expert consensus under standardized experimental conditions. However, the curated synthetic dataset, limited technical reproducibility of web-based inference, systematic grading tendencies, exploratory nature of the secondary-model analysis, and limited ecological validity preclude any inference of clinical readiness or real-world diagnostic performance without validation on real-world, multicenter, prevalence-based knee radiograph datasets.

Predators have evolved sophisticated behavioral patterns that enable efficient prey capture. The scale-eating cichlid Perissodus microlepis exhibits pronounced morphological asymmetry in mouth-opening direction, corresponding to behavioral laterality in attack direction. Given that recognizing and tracking the flank of prey are crucial for successful predation, we hypothesized that the morphological asymmetry also influences their spatial positioning relative to prey during attack initiation. To test this idea, we simultaneously tracked predator and prey movements using DeepLabCut and analyzed the predatory sequence. Not only strike direction but also the lateralized approach initiation position was correlated with mouth asymmetry. Additionally, trajectory analyses revealed two distinct predation strategies based on the predator's relative position to the prey at the start of the approach: a rear approach, whereby predators move in from behind and strike at close range with strong body flexion, and a side approach, whereby predators initiate from lateral positions at shorter distances and rush forward. Although rear and side attacks differ in their kinematics and strike timing, both strategies achieve high predation success by applying strong forces to the prey's flank. Overall, this study advances our understanding of the predation strategies of scale-eating cichlids, providing insights into their evolutionary significance.

Background Patellar tendon rupture is an uncommon but functionally debilitating injury requiring prompt surgical repair to restore the knee extensor mechanism. Evidence regarding the effect of short in-hospital delays to surgery on postoperative outcomes remains limited. This study evaluated short-term clinical outcomes following acute patellar tendon repair at a tertiary trauma centre over a 16-year period. Methods A retrospective case series was conducted using a prospectively maintained trauma registry from a tertiary hospital in the East Midlands, United Kingdom (2008-2024). Clinical records, operative notes, and follow-up documentation were reviewed. Data collected included patient demographics, injury characteristics, imaging modality, repair technique, surgeon grade, time to surgery (TTS), postoperative range of motion (ROM), follow-up duration, and complications. The primary outcome was postoperative knee flexion ROM at discharge. Statistical analysis included Pearson correlation and Spearman's correlation for non-parametric analysis, independent-samples t-tests, and one-way ANOVA. Results Thirty-four patients underwent operative repair of acute patellar tendon rupture. The cohort had a male-to-female ratio of 7.5:1, with a mean age of 50.7 years. Mean TTS was 2.5 days, and mean postoperative ROM at discharge was 105.4°. All patients with documented range-of-motion data achieved at least 85° of knee flexion, recorded at the final outpatient review. Complications occurred in nine (26.5%) patients, although most were minor and managed non-operatively. There was no significant association between TTS and postoperative ROM at discharge (r = -0.11, p = 0.59), suggesting that short in-hospital delays within the observed acute treatment window were not statistically associated with ROM at discharge. No statistically significant differences in short-term outcomes were observed between consultant-led and supervised registrar-led procedures, although this comparison was exploratory and unadjusted. Additional preoperative imaging was not associated with a statistically significant increase in TTS. Conclusion Primary repair of acute patellar tendon rupture produced satisfactory short-term functional outcomes with a low rate of major complications. Within the observed acute treatment window (0-9 days), no association was identified between time to surgery and knee flexion ROM at discharge, although the study was underpowered to exclude small-to-moderate effects. Supervised trainee-led surgery was associated with short-term outcomes similar to those of consultant-led procedures, although case allocation was not randomised. These findings are exploratory and confined to short-term outcomes. Larger prospective studies incorporating validated patient-reported outcome measures are required to better define prognostic factors following acute patellar tendon repair.