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In this work, molecular dynamics (MD) simulations are applied to investigate the dependence of the Wenzel–Cassie transition on water droplet size. During the Wenzel–Cassie transition, the critical water droplet and corresponding critical roughness may be expected, which are respectively described as the critical radius (RDroplet,c) and wetting parameter (WRoughness,c). From the work, RDroplet,c may be termed as the smallest droplet size at which the Cassie state is expected for the corresponding WRoughness,c. In combination with the structural study of water, it is due to the structural competition between interfacial and bulk water. Additionally, RDroplet,c may be dependent on the WRoughness,c. It is found that the RDroplet,c is influenced by the distribution and geometric characteristics of surface roughness. A denser distribution of roughness is expected to result in a lower RDroplet,c. Consequently, superhydrophobicity may be influenced by the characteristics of surface roughness and the size of the water droplet. The Cassie state is achieved when the wetting parameter of roughness is less than the WRoughness,c and the water droplet is larger than the RDroplet,c.

Biomimetic superhydrophobic surfaces have become a focal point of recent research, driven by their promise in diverse applications. Among these, the lotus and rose effects are of particular interest due to their contrasting adhesion characteristics. Given that superhydrophobicity is closely related to the hierarchical structures of these surfaces, investigating the effects of two-level roughness on superhydrophobicity is crucial. In our previous work, we introduced a wetting parameter (WRoughness), strongly correlated with the geometric characteristics of surface roughness, to elucidate the superhydrophobic behavior of solid surfaces. This parameter predicts the existence of a critical wetting parameter (WRoughness,c) during the Wenzel–Cassie transition. For two-level surface roughness composed of primary and secondary roughness, the WRoughness of the two-level surface is influenced by the geometric characteristics of both primary and secondary roughness. Furthermore, when secondary roughness is added to a primary roughness surface in the Wenzel state, the resulting two-level roughness can exhibit various superhydrophobic states, such as the Wenzel state, Wenzel–Cassie transition, or Cassie state, depending on the characteristics of the secondary roughness. To further investigate the influence of two-level roughness on superhydrophobicity, molecular dynamics (MD) simulations were also conducted.

Organoids are three-dimensional (3D) miniature structures cultured in vitro produced from either human pluripotent stem cells (hPSCs) or adult stem cells (AdSCs) derived from healthy individuals or patients that recapitulate the cellular heterogeneity, structure, and functions of human organs. The advent of human 3D organoid systems is now possible to allow remarkably detailed observation of stem cell morphogens, maintenance and differentiation resemble primary tissues, enhancing the potential to study both human physiology and developmental stage. As they are similar to their original organs and carry human genetic information, organoids derived from patient hold great promise for biomedical research and preclinical drug testing and is currently used for personalized, regenerative medicine, gene repair and transplantation therapy. In recent decades, researchers have succeeded in generating various types of organoids mimicking in vivo organs. Herein, we provide an update on current in vitro differentiation technologies of brain, retinal, kidney, liver, lung, gastrointestinal, cardiac, vascularized and multi-lineage organoids, discuss the differences between PSC- and AdSC-derived organoids, summarize the potential applications of stem cell-derived organoids systems in the laboratory and clinic, and outline the current challenges for the application of organoids, which would deepen the understanding of mechanisms of human development and enhance further utility of organoids in basic research and clinical studies.

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. Reorganization and classification of complex histologic patterns of RCC on biopsy and surgical resection slides under a microscope remains a heavily specialized, error-prone, and time-consuming task for pathologists. In this study, we developed a deep neural network model that can accurately classify digitized surgical resection slides and biopsy slides into five related classes: clear cell RCC, papillary RCC, chromophobe RCC, renal oncocytoma, and normal. In addition to the whole-slide classification pipeline, we visualized the identified indicative regions and features on slides for classification by reprocessing patch-level classification results to ensure the explainability of our diagnostic model. We evaluated our model on independent test sets of 78 surgical resection whole slides and 79 biopsy slides from our tertiary medical institution, and 917 surgical resection slides from The Cancer Genome Atlas (TCGA) database. The average area under the curve (AUC) of our classifier on the internal resection slides, internal biopsy slides, and external TCGA slides is 0.98 (95% confidence interval (CI): 0.97–1.00), 0.98 (95% CI: 0.96–1.00) and 0.97 (95% CI: 0.96–0.98), respectively. Our results suggest that the high generalizability of our approach across different data sources and specimen types. More importantly, our model has the potential to assist pathologists by (1) automatically pre-screening slides to reduce false-negative cases, (2) highlighting regions of importance on digitized slides to accelerate diagnosis, and (3) providing objective and accurate diagnosis as the second opinion.

Numerous studies have used human pluripotent stem cell-derived cerebral organoids to elucidate the mystery of human brain development and model neurological diseases in vitro, but the potential for grafted organoid-based therapy in vivo remains unknown. Here, we optimized a culturing protocol capable of efficiently generating small human cerebral organoids. After transplantation into the mouse medial prefrontal cortex, the grafted human cerebral organoids survived and extended projections over 4.5 mm in length to basal brain regions within 1 month. The transplanted cerebral organoids generated human glutamatergic neurons that acquired electrophysiological maturity in the mouse brain. Importantly, the grafted human cerebral organoids functionally integrated into pre-existing neural circuits by forming bidirectional synaptic connections with the mouse host neurons. Furthermore, compared to control mice, the mice transplanted with cerebral organoids showed an increase in freezing time in response to auditory conditioned stimuli, suggesting the potentiation of the startle fear response. Our study showed that subcortical projections can be established by microtransplantation and may provide crucial insights into the therapeutic potential of human cerebral organoids for neurological diseases.

Bamboo, with a high cellulose content comparable to that of wood, is a potential feedstock for biofuel and nanocellulose production. Mechanically isolated bamboo fibers and parenchyma cells exhibited remarkable differences in enzymatic hydrolysis efficiency as reported in a recent comparative study. It was assumed that cellulose microfibrils in bamboo fibers and parenchyma cells differ in their supramolecular structures. In the present study, X-ray diffraction and solid-state CP/MAS13C NMR studies indicated that, the two types of cells showed similar cellulose crystallinity index. The cellulose from bamboo fibers and parenchyma cells also exhibited differences in microfibril sizes, with lateral sizes of ca. 26.0–41.3 Å and ca. 22.7–39.3 Å for bamboo fibers and parenchyma cells respectively. It was further found that cellulose chains in bamboo fibers were more closely packed, supported by its smaller d-spacing than that of parenchyma cell cellulose. In addition, FT-IR and NMR spectroscopy revealed that there was a higher Iβ content in fibers than parenchyma cells. These differences in the crystalline structure of cellulose should be related to the lower recalcitrance to chemical degradation of parenchyma cells compared to bamboo fibers.Graphic abstractThese differences in the crystalline structure of cellulose should be related to the lower recalcitrance to chemical degradation of parenchyma cells compared to bamboo fibers.

Transformers, the dominant architecture for natural language processing, have also recently attracted much attention from computational visual media researchers due to their capacity for long-range representation and high performance. Transformers are sequence-to-sequence models, which use a self-attention mechanism rather than the RNN sequential structure. Thus, such models can be trained in parallel and can represent global information. This study comprehensively surveys recent visual transformer works. We categorize them according to task scenario: backbone design, high-level vision, low-level vision and generation, and multimodal learning. Their key ideas are also analyzed. Differing from previous surveys, we mainly focus on visual transformer methods in low-level vision and generation. The latest works on backbone design are also reviewed in detail. For ease of understanding, we precisely describe the main contributions of the latest works in the form of tables. As well as giving quantitative comparisons, we also present image results for low-level vision and generation tasks. Computational costs and source code links for various important works are also given in this survey to assist further development.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has resulted in tremendous loss worldwide. Although viral spike (S) protein binding of angiotensin-converting enzyme 2 (ACE2) has been established, the functional consequences of the initial receptor binding and the stepwise fusion process are not clear. By utilizing a cell–cell fusion system, in complement with a pseudoviral infection model, we found that the spike engagement of ACE2 primed the generation of S2′ fragments in target cells, a key proteolytic event coupled with spike-mediated membrane fusion. Mutagenesis of an S2′ cleavage site at the arginine (R) 815, but not an S2 cleavage site at arginine 685, was sufficient to prevent subsequent syncytia formation and infection in a variety of cell lines and primary cells isolated from human ACE2 knock-in mice. The requirement for S2′ cleavage at the R815 site was also broadly shared by other SARS-CoV-2 spike variants, such as the Alpha, Beta, and Delta variants of concern. Thus, our study highlights an essential role for host receptor engagement and the key residue of spike for proteolytic activation, and uncovers a targetable mechanism for host cell infection by SARS-CoV-2.