Freezing of gait (FoG) prediction, combined with rhythmic laser cues, may help Parkinson’s disease (PD) patients overcome FoG episodes. This study aimed to utilize the impaired gait patterns preceding FoG to build a machine-learning-based model for FoG prediction. Acceleration signals were collected using an accelerometer attached to the lower back of 12 PD patients with FoG while they were performing designed FoG-provoking walking tasks. Step-based impaired gait features and conventional FoG detection features were extracted from the signals, based on which two FoG prediction models were built using AdaBoost to validate if the use of the impaired gait features can better predict FoG. For the correct labeling of the gait prior to FoG (pre-FoG), the personalized pre-FoG phase was defined according to the slope of the impaired gait pattern. The impaired gait features were relabeled based on the pre-FoG phase upon which the personalized labeled FoG prediction model was built. This was compared with the model built using unified labeling. Results showed that impaired gait features could better predict FoG than conventional FoG detection features with low time latency, and personalized labeling could further improve the FoG prediction accuracy. Using impaired gait features and personalized labeling, we built a FoG prediction model with 0.93 sec of latency. Compared to using conventional features and unified labeling, our model achieved 5.7% higher accuracy (82.7%) in patient-dependent test and 9.8% higher accuracy (77.9%) in patient-independent test. Therefore, using the impaired gait patterns is a promising approach to accurately predict FoG with low latency.

Poly(ethylene glycol) (PEG)-based hydrogels are promising materials for biomedical applications because of their excellent hydrophilicity and biocompatibility. However, conventional chemically cross-linked PEG hydrogels are brittle under mechanical loading. The mechanical resilience and rapid recovery abilities of hydrogel implants are critical in load-bearing tissues, such as articular cartilage, which are routinely subjected to cyclic loadings of high magnitude and frequency. Here, we report the fabrication of novel supramolecular PEG hydrogels by polymerizing N,N-dimethylacrylamide with supramolecular cross-linkers self-assembled from adamantane-grafted PEG and mono-acrylated β-cyclodextrin. The resultant PEG–ADA supramolecular hydrogels exhibit substantial deformability, excellent capacity to dissipate massive amounts of loading energy, and have a rapid, full recovery during excessive, ultrafast, and non-resting cyclic compression. Furthermore, the energy dissipation capacity of the PEG–ADA (adamantane-grafted Poly(ethylene glycol)) hydrogels can be regulated by changing the concentration, molecular weight and cross-linking density of PEG. According to in vitro cell metabolism and viability tests, the PEG–ADA hydrogels are non-cytotoxic. When placed over a monolayer of myoblasts that were subjected to instantaneous compressive loading, the PEG–ADA hydrogel cushion significantly enhanced cell survival under this deleterious mechanical insult compared with the effects of the conventional PEG hydrogel. Therefore, PEG–ADA hydrogels are promising prosthetic biomaterials for the repair and regeneration of load-bearing tissues.

Both extrinsic and intrinsic tissues contribute to tendon repair, but the origin and molecular functions of extrinsic tissues in tendon repair are not fully understood. Here we show that tendon sheath cells harbor stem/progenitor cell properties and contribute to tendon repair by activating Hedgehog signaling. We found that Osteocalcin (Bglap) can be used as an adult tendon-sheath-specific marker in mice. Lineage tracing experiments show that Bglap-expressing cells in adult sheath tissues possess clonogenic and multipotent properties comparable to those of stem/progenitor cells isolated from tendon fibers. Transplantation of sheath tissues improves tendon repair. Mechanistically, Hh signaling in sheath tissues is necessary and sufficient to promote the proliferation of Mkx-expressing cells in sheath tissues, and its action is mediated through TGFβ/Smad3 signaling. Furthermore, co-localization of GLI1⁺ and MKX⁺ cells is also found in human tendinopathy specimens. Our work reveals the molecular function of Hh signaling in extrinsic sheath tissues for tendon repair.

Arterial baroreceptors are mechanical sensors that detect blood pressure changes. It has long been suggested that the two arterial baroreceptors, aortic and carotid baroreceptors, have different pressure sensitivities. However, there is no consensus as to which of the arterial baroreceptors are more sensitive to changes in blood pressure. In the present study, we employed independent methods to compare the pressure sensitivity of the two arterial baroreceptors. Firstly, pressure-activated action potential firing was measured by whole-cell current clamp with a high-speed pressure clamp system in primary cultured baroreceptor neurons. The results show that aortic depressor neurons possessed a higher percentage of mechano-sensitive neurons. Furthermore, aortic baroreceptor neurons show a lower pressure threshold than that of carotid baroreceptor neurons. Secondly, uniaxial stretching of baroreceptor neurons, that mimics the forces exerted on blood vessels, elicited a larger increase in intracellular Ca2+ rise in aortic baroreceptor neurons than in carotid baroreceptor neurons. Thirdly, the pressure-induced action potential firing in the aortic depressor nerve recorded in vivo was also higher. The present study therefore provides for a basic physiological understanding on the pressure sensitivity of the two baroreceptor neurons and suggests that aortic baroreceptors have a higher pressure sensitivity than carotid baroreceptors.

Ankle sprain is a frequent type of sports injury leading to lateral ligament injury. The anterior talofibular ligament (ATFL) is a primary ligamentous stabilizer of the ankle joint and typically the most vulnerable ligament injured in a lateral ankle sprain (LAS). This study aimed to quantitively investigate the effect of the thickness and elastic modulus of ATFL on anterior ankle joint stiffness (AAJS) by developing nine subject-specific finite element (FE) models under acute injury, chronic injury, and control conditions of ATFL. A 120 N forward force was applied at the posterior calcaneus leading to an anterior translation of the calcaneus and talus to simulate the anterior drawer test (ADT). In the results, the ratio of the forward force to the talar displacement was used to assess the AAJS, which increased by 5.85% in the acute group and decreased by 19.78% in the chronic group, compared to those of the control group. An empirical equation described the relationship between AAJS, thickness, and elastic modulus (R-square 0.98). The equation proposed in this study provided an approach to quantify AAJS and revealed the effect of the thickness and the elastic modulus of ATFL on ankle stability, which may shed light on the potential diagnosis of lateral ligament injury.