STFormer: Spatial-Temporal-Aware Transformer for Video Instance Segmentation.

Video instance segmentation (VIS) is a challenging task, requiring handling object classification, segmentation, and tracking in videos. Existing Transformer-based VIS approaches have shown remarkable success, combining encoded features and instance queries as decoder inputs. However, their decoder inputs are low-resolution due to computational cost, resulting in a loss of fine-grained information, sensitivity to background interference, and poor handling of small objects.

Integrins in cancer stem cells.

Integrins are a class of adhesion receptors on cell membranes, consisting of α and β subunits. By binding to the extracellular matrix, integrins activate intracellular signaling pathways, participating in every step of cancer initiation and progression. Tumor stem cells possess self-renewal and self-differentiation abilities, along with strong tumorigenic potential.

MotionTrack: Learning motion predictor for multiple object tracking.

Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accurately tracking objects in scenarios with homogeneous appearance and heterogeneous motion remains a challenge. This challenge arises from two main factors: the insufficient discriminability of ReID features and the predominant utilization of linear motion models in MOT.

TransConv: Transformer Meets Contextual Convolution for Unsupervised Domain Adaptation.

Unsupervised domain adaptation (UDA) aims to reapply the classifier to be ever-trained on a labeled source domain to a related unlabeled target domain. Recent progress in this line has evolved with the advance of network architectures from convolutional neural networks (CNNs) to transformers or both hybrids. However, this advance has to pay the cost of high computational overheads or complex training processes.

MTCH2 in Metabolic Diseases, Neurodegenerative Diseases, Cancers, Embryonic Development and Reproduction.

Mitochondrial carrier homolog 2 (MTCH2) is a member of the solute carrier 25 family, located on the outer mitochondrial membrane. MTCH2 was first identified in 2000. The development in MTCH2 research is rapidly increasing.

HCL: A Hierarchical Contrastive Learning Framework for Zero-Shot Relation Extraction.

Zero-shot relation extraction (ZSRE) is shown to become more significant in the current information extraction system, which aims at predicting relation classes that lack annotations or have just never appeared during training. Previous works focus on projecting sentences with their corresponding relation descriptions to an intermediate semantic space and searching the nearest semantic for predicting unseen classes. Though these methods can achieve sound performance, they only obtain inferior semantic information via a trivial distance metric and neglect the interaction in the instance representations.

Unusual case of retroperitoneal hematoma and duodenal ulcerative bleeding after nephrectomy: Case report.

Rationale: Retroperitoneal hematomas are relatively common in patients undergoing nephrectomy. Herein, we report an unusual case involving a giant retroperitoneal hematoma and subsequent duodenal ulcerative bleeding following a radical nephrectomy.

Patient Concerns: A 77-year-old woman was admitted to our hospital for lower back pain, and she had severe right hydronephrosis and a urinary tract infection.

IoUformer: Pseudo-IoU prediction with transformer for visual tracking.

Siamese tracking has witnessed tremendous progress in tracking paradigm. However, its default box estimation pipeline still faces a crucial inconsistency issue, namely, the bounding box decided by its classification score is not always best overlapped with the ground truth, thus harming performance. To this end, we explore a novel simple tracking paradigm based on the intersection over union (IoU) value prediction.

Sparse Low-Rank Multi-View Subspace Clustering With Consensus Anchors and Unified Bipartite Graph.

Anchor technology is popularly employed in multi-view subspace clustering (MVSC) to reduce the complexity cost. However, due to the sampling operation being performed on each individual view independently and not considering the distribution of samples in all views, the produced anchors are usually slightly distinguishable, failing to characterize the whole data. Moreover, it is necessary to fuse multiple separated graphs into one, which leads to the final clustering performance heavily subject to the fusion algorithm adopted.

SiamDF: Tracking training data-free siamese tracker.

Much progress has been made in siamese tracking, primarily benefiting from increasing huge training data. However, very little attention has been really paid to the role of huge training data in learning an effective siamese tracker. In this study, we undertake an in-depth analysis of this issue from a novel optimization perspective, and observe that training data is particularly adept at background suppression, thereby refining target representation.

Non-coding RNAs in renal cell carcinoma: Implications for drug resistance.

Renal cell carcinoma (RCC) represents a malignant tumor of the urinary system. Individuals with early-stage RCC could be cured by surgical treatment, but a considerable number of cases of advanced RCC progress to drug resistance. Recently, numerous reports have demonstrated that a variety of non-coding RNAs (ncRNAs) contribute to tumor occurrence and development.

Spatiotemporally resolved metabolomics and isotope tracing reveal CNS drug targets.

Deconvolution of potential drug targets of the central nervous system (CNS) is particularly challenging because of the complicated structure and function of the brain. Here, a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging. This strategy can map various substances including exogenous drugs, isotopically labeled metabolites, and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways.

A Closer Look at the Joint Training of Object Detection and Re-identification in Multi-Object Tracking.

Unifying object detection and re-identification (ReID) into a single network enables faster multi-object tracking (MOT), while this multi-task setting poses challenges for training. In this work, we dissect the joint training of detection and ReID from two dimensions: label assignment and loss function. We find previous works generally overlook them and directly borrow the practices from object detection, inevitably causing inferior performance.

Facile synthesis of lipase-loaded starch nanoparticles as recyclable biocatalyst in Pickering interfacial systems.

To develop recyclable biocatalyst used in Pickering interfacial systems, the pH-responsive monomer [2-(dimethylamine)ethyl methacrylate] (DMAEMA) was grafted onto the maize starch molecule via free radical polymerization. Subsequently, combined with the gelatinization-ethanol precipitation and lipase (Candida rugosa) absorption process, an enzyme-loaded starch nanoparticle with DMAEMA grafting (D-SNP@CRL) was tailor-made, showing a nanometer size and regular sphere. X-ray photoelectron spectroscopy and confocal laser scanning microscopy confirmed a concentration-induced enzyme distribution within D-SNP@CRL, thereof the outside-to-inside enzyme distribution was proved to be optimum in achieving the highest catalytic efficiency.

Improving Multiple Pedestrian Tracking in Crowded Scenes with Hierarchical Association.

Recently, advances in detection and re-identification techniques have significantly boosted tracking-by-detection-based multi-pedestrian tracking (MPT) methods and made MPT a great success in most easy scenes. Several very recent works point out that the two-step scheme of first detection and then tracking is problematic and propose using the bounding box regression head of an object detector to realize data association. In this tracking-by-regression paradigm, the regressor directly predicts each pedestrian's location in the current frame according to its previous position.

circ_0001274 Competitively Binds miR-143-3p to Upregulate VWF Expression to Improve Acute Traumatic Coagulopathy.

Accumulating evidence has noted the circRNA-microRNA- (circRNA-miRNA-) mRNA competing endogenous RNA (ceRNA) regulatory network in disease development and progression. The current study explored the ceRNA network in acute traumatic coagulopathy (ATC). Potential ATC-related genes were screened, and upstream miRNAs and circRNAs of VWF (the candidate target) were assayed through database searching and high-throughput sequencing technology.

Synthesis and antibacterial activity of novel 2‑fluoro ketolide antibiotics with 11,12‑quinoylalkyl side chains.

A series of novel 2‑fluoro ketolide antibiotics with 11,12‑quinoylalkyl side chains derived from telithromycin and cethromycin were designed and synthesized. The corresponding targets 2a-o were tested for their in vitro activities against a series of macrolide-sensitive and macrolide-resistant pathogens. Some of them showed a similar antibacterial spectrum and comparable or slightly better activity to telithromycin.

Target recognition initiated self-dissociation based DNA nanomachine for sensitive and accurate MicroRNA (miRNA) detection.

As a valuable biomarker for various tumor, sensitive and reliable quantitative determination of microRNA (miRNA) is crucial for both disease diagnosis and cancer treatment. Herein, we depict a novel simple and sensitive miRNA detection approach by exploiting an elegantly designed target recognition initiated self-dissociation based DNA nanomachine. In this nanomachine, target recognition assists the formation of active DNAzyme secondary conformation, and the active DNAzyme generates a nicking site in H probe, initiating the self-assembly of H probe.

Designed Synthesis of Compartmented Bienzyme Biocatalysts Based on Core-Shell Zeolitic Imidazole Framework Nanostructures.

For complex cascade biocatalysis, multienzyme compartmentalization helps to optimize substrate transport channels and promote the orderly and tunable progress of step reactions. Herein, a simple and general synthesis strategy is proposed for the construction of a multienzyme biocatalyst by compartmentalizing glucose oxidase and horseradish peroxidase (GOx and HRP) within core-shell zeolite imidazole frameworks (ZIF)-8@ZIF-8 nanostructures. Owing to the combined effects of biomimetic mineralization and the fine regulation of the ZIF-8 growth process, the uniform shell encloses the seed (core) surface by epitaxial growth, and the bienzyme system is accurately localized in a controlled manner.

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed -SNE of Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions.

Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning.

Currently, most Graph Structure Learning (GSL) methods, as a means of learning graph structure, improve the robustness of GNN merely from a local view by considering the local information related to each edge and indiscriminately applying the mechanism across edges, which may suffer from the local structure heterogeneity of the graph (i.e., the uneven distribution of inter-class connections over nodes).

Screening and Preclinical Evaluation of Novel Radiolabeled Anti-Fibroblast Activation Protein-α Recombinant Antibodies.

Fibroblast activation protein-α (FAPα) is selectively overexpressed in tumor-associated fibroblasts in more than 90% of epithelial tumors, and may be a good target for anticancer treatment, for example, using an anti-FAPα recombinant antibody (rAb) labeled with radionuclides. In the present report, the radiolabeling and preclinical evaluation of novel anti-FAPα rAbs were investigated. Two novel anti-FAPα VHHs (AMS002-1 and AMS002-2) with high binding affinity to FAPα were selected from an antibody phage library.