Effects of radial extracorporeal shock wave therapy on flexor spasticity of the upper limb in post-stroke patients: A randomized controlled trial.

OBJECTIVE: This study aimed to assess the efficacy of radial extracorporeal shock wave therapy in treating upper limb spasticity after a stroke. DESIGN: Randomized controlled trial. SETTING: Zhujiang Hospital of Southern Medical University. SUBJECTS: This study included 95 people with stroke. INTERVENTION: The active (n = 47) and sham-placebo (n = 48) radial extracorporeal shockwave therapy groups received three treatment sessions (every third day). MAIN MEASURES: The Modified Ashworth Scale, Hmax/Mmax ratio, root mean square, co-contraction ratio, mechanical parameters of the muscle and temperature were measured at baseline and days 2, 5 and 8. RESULTS: Among the 135 potential participants screened, 100 were enrolled and allocated randomly, with 95 participants ultimately being included in the intent-to-treat analysis dataset. The active group showed significantly better improvements in upper limb spasticity and muscle function than did the sham-placebo group. Greater improvements in the Modified Ashworth Scale were observed in the active group than in the sham-placebo group (difference, -0.45; 95% CI, -0.69 to -0.22; P < 0.001). Moreover, significant differences in root mean square, co-contraction ratio and Hmax/Mmax ratio were observed between the two groups (all P < 0.001). The mechanical parameters of the biceps muscle were significantly better in the active group than in the sham-placebo group (P < 0.001). The active group had a higher temperature than the sham-placebo group, although the difference was not significant (P = 0.070). CONCLUSIONS: This study revealed that the treatment with extracorporeal shockwave therapy can relieve upper limb spasticity in people with stroke.

Tailored Supramolecular Interactions in Host-Guest Complexation for Efficient and Stable Perovskite Solar Cells and Modules.

Host-guest complexation offers a promising approach for mitigating surface defects in perovskite solar cells (PSCs). Crown ethers are the most widely used macrocyclic hosts for complexing perovskite surfaces, yet their supramolecular interactions and functional implications require further understanding. Here we show that the dipole moment of crown ethers serves as an indicator of supramolecular interactions with both perovskites and precursor salts. A larger dipole moment, achieved through the substitution of heteroatoms, correlates with enhanced coordination with lead cations. Perovskite films incorporating aza-crown ethers as additives exhibited improved morphology, reduced defect densities, and better energy-level alignment compared to those using native crown ethers. We report power-conversion efficiencies (PCEs) exceeding 25% for PSCs, which show enhanced long-term stability, and a record PCE of 21.5% for host-guest complexation-based perovskite solar modules with an active area of 14.0 cm2.

Sub-Second Long Lifetime Triplet Exciton Reservoir for Highly Efficient and Stable Organic Light-Emitting Diode.

In organic light-emitting diode (OLED), achieving high efficiency requires effective triplet exciton confinement by carrier-transporting materials, which typically have higher triplet energy (ET) than the emitter, leading to poor stability. Here, an electron-transporting material (ETM), whose ET is 0.32 eV lower than that of the emitter is reported. In devices, it surprisingly exhibits strong confinement effect and generates excellent efficiency. Additionally, the device operational lifetime is 4.9 times longer than the device with a standard ETM, 1,3,5-tri(1-phenyl-1H-benzo[d]imidazol-2-yl) phenyl (whose ET 0.36 eV is higher than the emitter). This anomalous finding is ascribed to the exceptionally long triplet state lifetime (≈0.2 s) of the ETM. It is named as long-lifetime triplet exciton reservoir effect. The systematic analysis reveals that the long triplet lifetime of ETM can compensate the requirement for high ET with the help of endothermic energy transfer. Such combination of low ET and long lifetime provides equivalent exciton confinement effect and high molecular stability simultaneously. It offers a novel molecular design paradigm for breaking the dilemma between high efficiency and prolonged operational lifetime in OLEDs.

A crystal capping layer for formation of black-phase FAPbI3 perovskite in humid air.

Black-phase formamidinium lead iodide (α-FAPbI3) perovskites are the desired phase for photovoltaic applications, but water can trigger formation of photoinactive impurity phases such as δ-FAPbI3. We show that the classic solvent system for perovskite fabrication exacerbates this reproducibility challenge. The conventional coordinative solvent dimethyl sulfoxide (DMSO) promoted δ-FAPbI3 formation under high relative humidity (RH) conditions because of its hygroscopic nature. We introduced chlorine-containing organic molecules to form a capping layer that blocked moisture penetration while preserving DMSO-based complexes to regulate crystal growth. We report power conversion efficiencies of >24.5% for perovskite solar cells fabricated across an RH range of 20 to 60%, and 23.4% at 80% RH. The unencapsulated device retained 96% of its initial performance in air (with 40 to 60% RH) after 500-hour maximum power point operation.

CsAGP: Detecting Alzheimer's disease from multimodal images via dual-transformer with cross-attention and graph pooling.

Alzheimer's disease (AD) is a terrible and degenerative disease commonly occurring in the elderly. Early detection can prevent patients from further damage, which is crucial in treating AD. Over the past few decades, it has been demonstrated that neuroimaging can be a critical diagnostic tool for AD, and the feature fusion of different neuroimaging modalities can enhance diagnostic performance. Most previous studies in multimodal feature fusion have only concatenated the high-level features extracted by neural networks from various neuroimaging images simply. However, a major problem of these studies is over-looking the low-level feature interactions between modalities in the feature extraction stage, resulting in suboptimal performance in AD diagnosis. In this paper, we develop a dual-branch vision transformer with cross-attention and graph pooling, namely CsAGP, which enables multi-level feature interactions between the inputs to learn a shared feature representation. Specifically, we first construct a brand-new cross-attention fusion module (CAFM), which processes MRI and PET images by two independent branches of differing computational complexity. These features are fused merely by the cross-attention mechanism to enhance each other. After that, a concise graph pooling algorithm-based Reshape-Pooling-Reshape (RPR) framework is developed for token selection to reduce token redundancy in the proposed model. Extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrated that the suggested method obtains 99.04%, 97.43%, 98.57%, and 98.72% accuracy for the classification of AD vs. CN, AD vs. MCI, CN vs. MCI, and AD vs. CN vs. MCI, respectively.