Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM

The central problem in cryo-electron microscopy (cryo-EM) is to recover the 3D structure from noisy 2D projection images which requires estimating the missing projection angles (poses). Recent methods attempted to solve the 3D reconstruction problem with the autoencoder architecture, which suffers from the latent vector space sampling problem and frequently produces suboptimal pose inferences and inferior 3D reconstructions. Here we present an improved autoencoder architecture called ACE (Asymmetric Complementary autoEncoder), based on which we designed the ACE-EM method for cryo-EM 3D reconstructions. Compared to previous methods, ACE-EM reached higher pose space coverage within the same training time and boosted the reconstruction performance regardless of the choice of decoders. With this method, the Nyquist resolution (highest possible resolution) was reached for 3D reconstructions of both simulated and experimental cryo-EM datasets. Furthermore, ACE-EM is the only amortized inference method that reached the Nyquist resolution

Light Multi-segment Activation for Model Compression

Model compression has become necessary when applying neural networks (NN) into many real application tasks that can accept slightly-reduced model accuracy with strict tolerance to model complexity. Recently, Knowledge Distillation, which distills the knowledge from well-trained and highly complex teacher model into a compact student model, has been widely used for model compression. However, under the strict requirement on the resource cost, it is quite challenging to achieve comparable performance with the teacher model, essentially due to the drastically-reduced expressiveness ability of the compact student model. Inspired by the nature of the expressiveness ability in Neural Networks, we propose to use multi-segment activation, which can significantly improve the expressiveness ability with very little cost, in the compact student model. Specifically, we propose a highly efficient multi-segment activation, called Light Multi-segment Activation (LMA), which can rapidly produce multiple linear regions with very few parameters by leveraging the statistical information. With using LMA, the compact student model is capable of achieving much better performance effectively and efficiently, than the ReLU-equipped one with same model scale. Furthermore, the proposed method is compatible with other model compression techniques, such as quantization, which means they can be used jointly for better compression performance. Experiments on state-of-the-art NN architectures over the real-world tasks demonstrate the effectiveness and extensibility of the LMA

Cell patterning using a dielectrophoretic–hydrodynamic trap

The paper presents a dielectrophoretic method for cell patterning using dielectrophoretic–hydrodynamic trap. A distinctive characteristic of the device is that the dielectrophoretic (DEP) force is generated using a structure that combines conventional electrode-based DEP (eDEP) with insulator-based DEP method (iDEP). The conventional eDEP force is generated across the microfluidic channel between a top plate indium tin oxide electrode and a thin CrAu electrode. Meantime, an isolating cage built from SU8 photoresist around the thin electrode modifies the electric field generating an iDEP force. The cells that are flowing through a microfluidic channel are trapped in the SU8 cage by the total DEP force. As a result, according to the cell dimension and the thickness of the SU8 layer, different cell patterns can be achieved. If the cell’s size is sensitively smaller than the dimensions of the hydrodynamic trap, due to the dipole–dipole interaction, the cell can be organized in 3D structures. The trapping method can be used for conducting genetic, biochemical or physiological studies on cells

Pre-concentration and determination of trace uranium (VI) in environments using ion-imprinted chitosan resin via solid phase extraction

The uranyl-ion-imprinted and non-imprinted cross-linked chitosan resins possessing quinoline-8-ol moiety have been prepared. In all the cases, a significant imprinting effect was noticed on comparing percent extraction of uranium (VI). The resulting ion-imprinted resin was used for solid phase extractive preconcentration of uranium (VI) prior to its determination by spectrophotometry. Experimental variables that influence the quantitative extraction of uranium (VI) were optimized by both static and column methods. The retention capacity found for uranium (VI) was 218 mg g-1 of resin which is higher than the corresponding non-imprinted resins and other solid phase extraction sorbents possessing quinoline-8-ol moiety. The optimum pH range was 4.5-7.0. Uranium adsorbed was easily and quantitatively eluted with 1 mol L-1 HCl (10 mL) at a flow rate of 2 mL min-1. Interference studies showed a high tolerance of diverse ions and electrolyte species. The limit of detection was 2 µg L-1 and the dynamic linear range was 5-100 µg L-1. The accuracy of the developed method was tested with one uranium ore standard reference material. Furthermore, the proposed method was successfully applied for the determination of uranium in contaminated soil and sediment samples

Virome and metagenomic analysis reveal the distinct distribution of microbiota in human fetal gut during gestation

Studies have shown that fetal immune cell activation may result from potential exposure to microbes, although the presence of microbes in fetus has been a controversial topic. Here, we combined metagenomic and virome techniques to investigate the presence of bacteria and viruses in fetal tissues (small intestine, cecum, and rectum). We found that the fetal gut is not a sterile environment and has a low abundance but metabolically rich microbiome. Specifically, Proteobacteria and Actinobacteria were the dominant bacteria phyla of fetal gut. In total, 700 species viruses were detected, and Human betaherpesvirus 5 was the most abundant eukaryotic viruses. Especially, we first identified Methanobrevibacter smithii in fetal gut. Through the comparison with adults’ gut microbiota we found that Firmicutes and Bacteroidetes gradually became the main force of gut microbiota during the process of growth and development. Interestingly, 6 antibiotic resistance genes were shared by the fetus and adults. Our results indicate the presence of microbes in the fetal gut and demonstrate the diversity of bacteria, archaea and viruses, which provide support for the studies related to early fetal immunity. This study further explores the specific composition of viruses in the fetal gut and the similarities between fetal and adults’ gut microbiota, which is valuable for understanding human fetal immunity development during gestation

Comprehending the cuproptosis and cancer-immunity cycle network: delving into the immune landscape and its predictive role in breast cancer immunotherapy responses and clinical endpoints

BackgroundThe role of cuproptosis, a phenomenon associated with tumor metabolism and immunological identification, remains underexplored, particularly in relation to the cancer-immunity cycle (CIC) network. This study aims to rigorously examine the impact of the cuproptosis-CIC nexus on immune reactions and prognostic outcomes in patients with breast cancer (BC), striving to establish a comprehensive prognostic model.MethodsIn the study, we segregated data obtained from TCGA, GEO, and ICGC using CICs retrieved from the TIP database. We constructed a genetic prognostic framework using the LASSO-Cox model, followed by its validation through Cox proportional hazards regression. This framework’s validity was further confirmed with data from ICGC and GEO. Explorations of the tumor microenvironment were carried out through the application of ESTIMATE and CIBERSORT algorithms, as well as machine learning techniques, to identify potential treatment strategies. Single-cell sequencing methods were utilized to delineate the spatial distribution of key genes within the various cell types in the tumor milieu. To explore the critical role of the identified CICs, experiments were conducted focusing on cell survival and migration abilities.ResultsIn our research, we identified a set of 4 crucial cuproptosis-CICs that have a profound impact on patient longevity and their response to immunotherapy. By leveraging these identified CICs, we constructed a predictive model that efficiently estimates patient prognoses. Detailed analyses at the single-cell level showed that the significance of CICs. Experimental approaches, including CCK-8, Transwell, and wound healing assays, revealed that the protein HSPA9 restricts the growth and movement of breast cancer cells. Furthermore, our studies using immunofluorescence techniques demonstrated that suppressing HSPA9 leads to a notable increase in ceramide levels.ConclusionThis research outlines a network of cuproptosis-CICs and constructs a predictive nomogram. Our model holds great promise for healthcare professionals to personalize treatment approaches for individuals with breast cancer. The work provides insights into the complex relationship between the cuproptosis-CIC network and the cancer immune microenvironment, setting the stage for novel approaches to cancer immunotherapy. By focusing on the essential gene HSPA9 within the cancer-immunity cycle, this strategy has the potential to significantly improve the efficacy of treatments against breast cancer

Liver-targeting MRI contrast agent based on galactose functionalized o-carboxymethyl chitosan

Commercial gadolinium (Gd)-based contrast agents (GBCAs) play important role in clinical diagnostic of hepatocellular carcinoma, but their diagnostic efficacy remained improved. As small molecules, the imaging contrast and window of GBCAs is limited by low liver targeting and retention. Herein, we developed a liver-targeting gadolinium (Ⅲ) chelated macromolecular MRI contrast agent based on galactose functionalized o-carboxymethyl chitosan, namely, CS-Ga-(Gd-DTPA)n, to improve hepatocyte uptake and liver retention. Compared to Gd-DTPA and non-specific macromolecular agent CS-(Gd-DTPA)n, CS-Ga-(Gd-DTPA)n showed higher hepatocyte uptake, excellent cell and blood biocompatibility in vitro. Furthermore, CS-Ga-(Gd-DTPA)n also exhibited higher relaxivity in vitro, prolonged retention and better T1-weighted signal enhancement in liver. At 10 days post-injection of CS-Ga-(Gd-DTPA)n at a dose of 0.03 mM Gd/Kg, Gd had a little accumulation in liver with no liver function damage. The good performance of CS-Ga-(Gd-DTPA)n gives great confidence in developing liver-specifc MRI contrast agents for clinical translation