Background: The intercondylar notch (ICN) and the anterior cruciate ligament (ACL) are important structures in knee morphometry, with key roles in stabilizing the knee. Aim: To determine the associations between the specific shape of the ICN (A-, W-, or U-shape) and the ACL size in patients with intact ACLs. Methods: Magnetic resonance imaging (MRI) scans were independently analyzed by two experts: one orthopedic surgeon and one imaging physician. In all cases, the following measurements were taken based on the existing definitions: ACL area, anterior ICN (aICN) area, ICN width, lateral trochlear inclination (LTI), and Insall–Salvati index. Results: A total of 65 cases (50.8% male; 33.8 ± 10.2 years mean age at inclusion) were included in the study. The ACL and aICN areas were significantly larger in patients with U-shaped compared with A-shaped and W-shaped ICNs: 0.50 (0.20–0.80) vs. 0.40 (0.20–0.80) vs. 0.40 (0.30–0.80), p = 0.011 and 1.16 (0.57–3.60) vs. 0.47 (0.15–0.95) vs. 0.37 (0.15–0.81), p < 0.001, respectively. Internal meniscal lesions were more common in cases with U-shaped ICNs (64.0%), while external ones were more common in W-shaped ICN cases (35.3%). None of the A-shaped cases had external chondral or meniscal lesions. The ACL area was significantly larger in males and internal meniscal injuries, with no differences between chondral lesions, external meniscal injuries, patellar chondral lesions, patella alta, or trochlear dysplasia. Conclusion: The specific shape of the intercondylar notch was associated with the anterior cruciate ligament–anterior intercondylar notch (ACL–aICN) area size correlation, with a strong correlation between ACL and aICN area when the intercondylar notch was A-shaped or W-shaped, and a low correlation when the notch was U- shaped. The specific shape of the intercondylar notch (A-, W-, or U-shape) was associated with the occurrence of both internal and external meniscal injuries, with the U-shaped intercondylar notch morphometry being more frequent in cases with internal meniscal injuries and the W-shape being more common in cases with external meniscal injuries.

Background: Jones fractures of the 5th metatarsal are frequently associated with nonunion due to limited vascularization and repetitive mechanical stress. The aim of the study was to compare the biomechanical performance of T-plate and bicortical screw fixation using standardized 3D models. Methods: Three-dimensional models of the 5th metatarsal were generated from CT images and printed using PolyJet technology (Stratasys J5 DentaJet) using a rigid-elastic composite with properties similar to cortical and cancellous bone. Jones fractures were fixed with either a locked T-plate or a bicortical screw. The samples were tested under axial and oblique static loads (α = 0°, 90°, 180°) and for three values of interfragmentary distance (d = 0.1–1 mm), in a 3 × 2 factorial design. Results: The T-plate fixation recorded a maximum yield force (Fmax) of 149.78 ± 8.53 N (138–161 N), significantly higher compared to the bicortical screw −98.56 ± 2.58 N (96–101 N), (p < 0.05). The ductility index was higher for the plate, indicating a progressive transition to yield. The α and d factors significantly influenced the mechanical behavior, with the polynomial model explaining over 95% of the total variation. Discussion: The plate fixation demonstrated greater strength and superior biomechanical tolerance in imperfect reduction scenarios. The main limitation is the lack of fatigue testing and the inability of 3D models to reproduce the structural heterogeneity of human bone. Conclusions: Implant selection should be individualized based on fracture stability. 3D models provide a reproducible platform for comparative evaluation of osteosynthesis methods, but future studies should include cyclic loading and biological validation.

Background/Objectives: Avulsion fractures of the fifth metatarsal often require surgical fixation when displacement or instability is present. This study aimed to compare the biomechanical performance of hook-plate and bicortical screw fixation using anatomically accurate 3D-printed metatarsal models analyzed through digital image correlation (DIC). Methods: Multi-material 3D-printed specimens were subjected to simulated gait-phase loading (α = 0°, 90°, 180°), combined with three interfragmentary distances (d = 0.1, 0.5, 1 mm) following a replicated 3 × 3 factorial design (n = 27 per fixation method). Full-field strain and displacement maps were quantified using ARAMIS DIC. Results: Hook-plate fixation consistently produced lower maximum stresses compared with bicortical screws (reductions of 9–36 MPa across conditions). The highest stresses were observed for screw fixation at α = 90° and d = 0.1 mm (100.3 ± 1.5 MPa), while the lowest occurred for hook plates at α = 180° and d = 1 mm (33.3 ± 1.5 MPa). ANOVA confirmed significant α×d interactions (p < 0.01). Conclusions: Hook-plate fixation provided superior angular stability and suggested improved cyclic performance compared to bicortical screws, favoring early mobilization. The combined use of 3D printing and DIC represents a valuable framework for preclinical implant evaluation. These results provide useful insights for selecting the optimal fixation technique in clinical management of fifth metatarsal avulsion fractures.

Background/Objectives: Suicide remains a major public health concern, with over 700,000 deaths annually worldwide. Current risk assessment is limited by the tendency of at-risk patients to deny suicidal ideation, with denial rates of approximately 50% among ideators and up to 78% among inpatient suicide decedents. Methods: This proof-of-concept study investigated whether deep learning applied to patient speech could distinguish psychiatric inpatients admitted following a recent suicide attempt from patients with severe depression without documented suicidal ideation. A multi-scale two-dimensional convolutional neural network with residual connections and spatial attention (Multi-Scale CNN) was trained on mel-spectrograms generated exclusively from patient speech extracted by automatic speaker diarization followed by manual verification. The dataset comprised recordings from 88 psychiatric inpatients (59 suicide attempters and 29 patients with severe depression without suicidal ideation). Model performance was evaluated using repeated patient-level stratified five-fold cross-validation, ensuring complete separation of participants between folds. Additional female-only, exploratory male-only, and repeated sex-matched analyses were performed to evaluate the potential influence of sex imbalance. Results: Repeated patient-level five-fold cross-validation yielded a mean classification accuracy of 72.7 ± 6.4% with a mean ROC-AUC of 0.824 ± 0.054, a sensitivity of 88.3 ± 9.5%, and a specificity of 41.3 ± 25.0%. Female-only analysis maintained good discriminative performance (ROC-AUC 0.866 ± 0.123), whereas repeated sex-matched analyses produced lower performance (ROC-AUC 0.621 ± 0.156), indicating that sex imbalance contributed to, but did not fully explain, the observed discrimination. The male-only analysis was considered exploratory because of the limited number of male patients in the depression group. Conclusions: These findings support the feasibility of voice-based patient-level analysis as a complementary objective approach for suicide risk assessment. Although the study remains exploratory because of the limited sample size and the absence of external validation, the revised validation strategy and sex-controlled analyses provide a substantially more robust estimate of model performance. Further multicenter prospective studies are required before clinical implementation.

Myoelectric exoprostheses serve to aid in the everyday activities of patients with forearm or hand amputations. While electrical signals are known key factors controlling exoprosthesis, little is known about how we can improve their transmission strength from the forearm muscles as to obtain better sEMG. The purpose of this study is to evaluate the role of the forearm fascial layer in transmitting myoelectrical current. We examined the sEMG signals in three individual muscles, each from six healthy forearms (Group 1) and six amputation stumps (Group 2), along with their complete biometric characteristics. Following the tests, one patient underwent a circumferential osteoneuromuscular stump revision surgery (CONM) that also involved partial removal of fascia and subcutaneous fat in the amputation stump, with re-testing after complete healing. In group 1, we obtained a stronger sEMG signal than in Group 2. In the CONM case, after surgery, the patient’s data suggest that the removal of fascia, alongside the fibrotic and subcutaneous fat tissue, generates a stronger sEMG signal. Therefore, a reduction in the fascial layer, especially if accompanied by a reduction of the subcutaneous fat layer may prove significant for improving the strength of sEMG signals used in the control of modern exoprosthetics.

The development of implantable neural interfaces is essential for enabling bidirectional communication between the nervous system and prosthetic devices, yet their evaluation still relies primarily on in vivo models which are costly, variable, and ethically constrained. Here, we report a bio-inspired artificial nerve simulator engineered as a reproducible ex vivo platform for pre-implantation testing of plug-type electrodes. The simulator is fabricated from a conductive hydrogel composite based on reduced graphene oxide (rGO), polyaniline (PANI), agarose, sucrose, and sodium chloride, with embedded conductive channels that replicate the fascicular organization and conductivity of peripheral nerves. The resulting construct exhibits impedance values of ~2.4–2.9 kΩ between electrode needles at 1 kHz, closely matching in vivo measurements (~2 kΩ) obtained in Sus scrofa domesticus nerve tissue. Its structural and electrical fidelity enables systematic evaluation of electrode–nerve contact properties, signal transmission, and insertion behavior under controlled conditions, while reducing reliance on animal experiments. This bio-inspired simulator offers a scalable and physiologically relevant testbed that bridges materials engineering and translational neuroprosthetics, accelerating the development of next-generation implantable neural interfaces.