Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model

Recently, semi-supervised federated learning (semi-FL) has been proposed to handle the commonly seen real-world scenarios with labeled data on the server and unlabeled data on the clients. However, existing methods face several challenges such as communication costs, data heterogeneity, and training pressure on client devices. To address these challenges, we introduce the powerful diffusion models (DM) into semi-FL and propose FedDISC, a Federated Diffusion-Inspired Semi-supervised Co-training method. Specifically, we first extract prototypes of the labeled server data and use these prototypes to predict pseudo-labels of the client data. For each category, we compute the cluster centroids and domain-specific representations to signify the semantic and stylistic information of their distributions. After adding noise, these representations are sent back to the server, which uses the pre-trained DM to generate synthetic datasets complying with the client distributions and train a global model on it. With the assistance of vast knowledge within DM, the synthetic datasets have comparable quality and diversity to the client images, subsequently enabling the training of global models that achieve performance equivalent to or even surpassing the ceiling of supervised centralized training. FedDISC works within one communication round, does not require any local training, and involves very minimal information uploading, greatly enhancing its practicality. Extensive experiments on three large-scale datasets demonstrate that FedDISC effectively addresses the semi-FL problem on non-IID clients and outperforms the compared SOTA methods. Sufficient visualization experiments also illustrate that the synthetic dataset generated by FedDISC exhibits comparable diversity and quality to the original client dataset, with a neglectable possibility of leaking privacy-sensitive information of the clients

Valence-programmable nanoparticle architectures.

Nanoparticle-based clusters permit the harvesting of collective and emergent properties, with applications ranging from optics and sensing to information processing and catalysis. However, existing approaches to create such architectures are typically system-specific, which limits designability and fabrication. Our work addresses this challenge by demonstrating that cluster architectures can be rationally formed using components with programmable valence. We realize cluster assemblies by employing a three-dimensional (3D) DNA meshframe with high spatial symmetry as a site-programmable scaffold, which can be prescribed with desired valence modes and affinity types. Thus, this meshframe serves as a versatile platform for coordination of nanoparticles into desired cluster architectures. Using the same underlying frame, we show the realization of a variety of preprogrammed designed valence modes, which allows for assembling 3D clusters with complex architectures. The structures of assembled 3D clusters are verified by electron microcopy imaging, cryo-EM tomography and in-situ X-ray scattering methods. We also find a close agreement between structural and optical properties of designed chiral architectures

Potential Mechanisms of the Impact of Hepatocyte Growth Factor Gene-Modified Tendon Stem Cells on Tendon Healing

The therapeutic impact of stem cells is potentially largely attributable to secretion of exosomes and soluble factors. The present study evaluates the impact of hepatocyte growth factor (HGF)–expressing tendon stem cells (TSCs) on tendon healing in a rat model. Patellar tendon TSCs were isolated and underwent transfection with lentiviral vectors containing HGF or green fluorescent protein (GFP) genes. In vivo, immunohistochemistry of tendons sampled 1 week postsurgery demonstrated that all stem cell–treated groups exhibited higher numbers of CD163+ M2 monocytes and IL-10+ cells (anti-inflammatory), and lower numbers of CCR7+ M1 monocytes and IL-6+ as well as COX-2+ cells (pro-inflammatory). Effects were most pronounced in the HGF-expressing TSCs (TSCs + HGF) treated group. Histology ± immunohistochemistry of tendons sampled 4 and 8 weeks postsurgery demonstrated that all stem cell–treated groups exhibited more ordered collagen fiber arrangement and lower levels of COLIII, α-SMA, TGF-β1, and fibronectin (proteins relevant to fibroscarring). Effects were most pronounced in the TSCs + HGF–treated group. For the in vitro study, isolated tendon fibroblasts pretreated with TGF-β1 to mimic the in vivo microenvironment of tendon injury were indirectly cocultured with TSCs, TSCs + GFP, or TSCs + HGF using a transwell system. Western blotting demonstrated that all stem cell types decreased TGF-β1-induced increases in fibroblast levels of COX-2, COLIII, and α-SMA, concomitant with decreased activation of major TGF-β1 signaling pathways (p38 MAPK, ERK1/2, but not Smad2/3). This effect was most pronounced for TSCs + HGF, which also decreased the TGF-β1-induced increase in activation of the Smad2/3 signaling pathway. The presence of specific inhibitors of these pathways during fibroblast TGF-β1 stimulation also attenuated increases in levels of COX-2, COLIII, and α-SMA. In conclusion, TSCs + HGF, which exhibit HGF overexpression, may promoting tendon healing via decreasing inflammation and fibrosis, perhaps partly via inhibiting TGF-β1-induced signaling. These findings identify a novel potential therapeutic strategy for tendon injuries, warranting additional research

Efficacy and safety of immunotherapy combined with single-agent chemotherapy as second- or later-line therapy for metastatic non-small cell lung cancer

ObjectiveThis study sought to assess the efficacy and safety of immunotherapy combined with single-agent chemotherapy as a second- or later-line setting for metastatic non-small cell lung cancer (NSCLC) and to provide clinical evidence for this treatment regimen. The predictive value of extracellular vesicle (EV) membrane proteins was explored in patients who underwent this treatment.MethodsClinical data from patients diagnosed with metastatic NSCLC who received immunotherapy plus single-agent chemotherapy as a second- or later-line setting were retrospectively collected between March 2019 and January 2022. A total of 30 patients met the inclusion criteria, and all were pathologically confirmed to have NSCLC. Short-term efficacy, progression-free survival (PFS), EV markers for response prediction, and adverse events were assessed.ResultsEfficacy data were available for all 30 patients and included a partial response in 5 patients, stable disease in 18 patients, and disease progression in 7 patients. The objective response rate was 16.7%, the disease control rate was 76.7%, and the median PFS was 3.2 months. Univariate analysis showed that PFS was not associated with sex, age, smoking status, treatment lines, prior use of immunotherapy, or prior use of antiangiogenic drugs. The EV membrane proteins MET proto-oncogene, receptor tyrosine kinase (c-MET), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor receptor 2 (VEGFR2) at baseline were associated with poor prognosis and correlated with the efficacy of immunotherapy plus chemotherapy. According to the receiver operating characteristics and Kaplan–Meier curve analyses, patients with high c-MET, EGFR, and VEGFR2 expression at baseline had significantly shorter PFS than those with low expression. In addition, VEGFR2 expression was increased after combined immunotherapy in responders, which was decreased in non-responders. The most common grade 2 or higher adverse events were neutropenia, gastrointestinal reactions, and thyroid dysfunction, all of which were tolerated.ConclusionsImmunotherapy plus single-agent chemotherapy as a second- or later-line treatment is safe, effective, and tolerable for metastatic NSCLC. EV markers can be used as predictive markers of efficacy in patients with metastatic NSCLC treated with immunotherapy plus chemotherapy to help monitor treatment efficacy and guide treatment decisions

Urbanization affects spatial variation and species similarity of bird diversity distribution

Although cities are human-dominated systems, they provide habitat for many other species. Because of the lack of long-term observation data, it is challenging to assess the impacts of rapid urbanization on biodiversity in Global South countries. Using multisource data, we provided the first analysis of the impacts of urbanization on bird distribution at the continental scale and found that the distributional hot spots of threatened birds overlapped greatly with urbanized areas, with only 3.90% of the threatened birds’ preferred land cover type in urban built-up areas. Bird ranges are being reshaped differently because of their different adaptations to urbanization. While green infrastructure can improve local bird diversity, the homogeneous urban environment also leads to species compositions being more similar across regions. More attention should be paid to narrow-range species for the formulation of biodiversity conservation strategies, and conservation actions should be further coordinated among cities from a global perspective

Simulation of Mushroom Nanostructures with Ag Nanoparticles for Broadband and Wide-Angle Superabsorption

Metal nanoparticles (NPs) concentrate the energy of incident photons through plasmon resonance excitation, which allows scattering into a substrate with a high refractive index, and the radiated energy from this excitation significantly increases the optical absorption of the substrate. In this work, the effect of Ag NPs on the absorption capacity of mushroom-nanostructured Si metasurfaces was analyzed using the finite-difference time-domain method. It was observed that the absorbance in the metasurfaces with Ag NPs increased from 90.8% to 98.7% compared with nanostructured Si metasurface without NPs. It was shown that the plasmon resonance effect of Ag NPs enlarged the range of the FP cavity by about 10 times, and the electric field strength E2 increased by about four times through the combination of Ag NP and Si absorbers. Meanwhile, the effect of randomly distributed nanostructures on the absorption properties of Si metasurfaces was simulated. Additionally, the nanostructured surface with Ag NPs was insensitive to angle, which encourages the design of broadband and wide-angle superabsorption nanostructures