453 research outputs found
Unsupervised Prototype Adapter for Vision-Language Models
Recently, large-scale pre-trained vision-language models (e.g. CLIP and
ALIGN) have demonstrated remarkable effectiveness in acquiring transferable
visual representations. To leverage the valuable knowledge encoded within these
models for downstream tasks, several fine-tuning approaches, including prompt
tuning methods and adapter-based methods, have been developed to adapt
vision-language models effectively with supervision. However, these methods
rely on the availability of annotated samples, which can be labor-intensive and
time-consuming to acquire, thus limiting scalability. To address this issue, in
this work, we design an unsupervised fine-tuning approach for vision-language
models called Unsupervised Prototype Adapter (UP-Adapter). Specifically, for
the unannotated target datasets, we leverage the text-image aligning capability
of CLIP to automatically select the most confident samples for each class.
Utilizing these selected samples, we generate class prototypes, which serve as
the initialization for the learnable prototype model. After fine-tuning, the
prototype model prediction is combined with the original CLIP's prediction by a
residual connection to perform downstream recognition tasks. Our extensive
experimental results on image recognition and domain generalization show that
the proposed unsupervised method outperforms 8-shot CoOp, 8-shot Tip-Adapter,
and also the state-of-the-art UPL method by large margins.Comment: Accepted by PRCV 202
An overview of the effect of sodium glucose cotransporter 2 inhibitor monotherapy on glycemic and other clinical laboratory parameters in type 2 diabetes patients
Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation
Pre-trained Vision-Language Models (VLMs), such as CLIP, have shown enhanced
performance across a range of tasks that involve the integration of visual and
linguistic modalities. When CLIP is used for depth estimation tasks, the
patches, divided from the input images, can be combined with a series of
semantic descriptions of the depth information to obtain similarity results.
The coarse estimation of depth is then achieved by weighting and summing the
depth values, called depth bins, corresponding to the predefined semantic
descriptions. The zero-shot approach circumvents the computational and
time-intensive nature of traditional fully-supervised depth estimation methods.
However, this method, utilizing fixed depth bins, may not effectively
generalize as images from different scenes may exhibit distinct depth
distributions. To address this challenge, we propose a few-shot-based method
which learns to adapt the VLMs for monocular depth estimation to balance
training costs and generalization capabilities. Specifically, it assigns
different depth bins for different scenes, which can be selected by the model
during inference. Additionally, we incorporate learnable prompts to preprocess
the input text to convert the easily human-understood text into easily
model-understood vectors and further enhance the performance. With only one
image per scene for training, our extensive experiment results on the NYU V2
and KITTI dataset demonstrate that our method outperforms the previous
state-of-the-art method by up to 10.6\% in terms of MARE.Comment: Accepted by WACV 202
Identifying potential prognosis markers in hepatocellular carcinoma via integrated bioinformatics analysis and biological experiments
Background: Hepatocellular carcinoma is one kind of clinical common malignant tumor with a poor prognosis, and its pathogenesis remains to be clarified urgently. This study was performed to elucidate key genes involving HCC by bioinformatics analysis and experimental evaluation.Methods: We identified common differentially expressed genes (DEGs) based on gene expression profile data of GSE60502 and GSE84402 from the Gene Expression Omnibus (GEO) database. Gene Ontology enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, REACTOME pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used to analyze functions of these genes. The protein-protein interaction (PPI) network was constructed using Cytoscape software based on the STRING database, and Molecular Complex Detection (MCODE) was used to pick out two significant modules. Hub genes, screened by the CytoHubba plug-in, were validated by Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) database. Then, the correlation between hub genes expression and immune cell infiltration was evaluated by Tumor IMmune Estimation Resource (TIMER) database, and the prognostic values were analyzed by Kaplan-Meier plotter. Finally, biological experiments were performed to illustrate the functions of RRM2.Results: Through integrated bioinformatics analysis, we found that the upregulated DEGs were related to cell cycle and cell division, while the downregulated DEGs were associated with various metabolic processes and complement cascade. RRM2, MAD2L1, MELK, NCAPG, and ASPM, selected as hub genes, were all correlated with poor overall prognosis in HCC. The novel RRM2 inhibitor osalmid had anti-tumor activity, including inhibiting proliferation and migration, promoting cell apoptosis, blocking cell cycle, and inducing DNA damage of HCC cells.Conclusion: The critical pathways and hub genes in HCC progression were screened out, and targeting RRM2 contributed to developing new therapeutic strategies for HCC
Stratospheric PULSE–continental cold air outbreak coupling relationships: Interannual and interdecadal changes
Stratospheric processes and their role in weather and climate have attracted increasing interests. The correspondence between the occurrence of pulse-like, stronger stratospheric poleward warm airmass transport (PULSE) events and the continental-scale cold air outbreak (CAO) events in northern hemispheric winter is found to be unstable from year to year. This increases the difficulties in utilizing the more predictable stratospheric variability in the sub-seasonal forecasts of CAOs, which can cause cold hazards. Using the ERA5 reanalysis data covering 37 winters (November–March) in the period 1979–2015, this study categorizes the CAO events over mid-latitudes of Eurasia (CAO_EA) and those over North America (CAO_NA) into two groups: those coupled with and those decoupled with the PULSE events. The coupled CAOs are further categorized into events that are, respectively, lead-coupled and lag-coupled with PULSEs. The intensity and affected area of extremely cold temperatures tend to be larger during CAOs that are coupled with PULSEs, particularly during the CAO_NA events that are lag-coupled with PULSEs and the CAO_EA events that are lead-coupled with PULSEs. Remarkable interannual and interdecadal variations are observed in the percentage of CAOs that are coupled with PULSEs for each winter, which is an important reference for determining the window of opportunity for skillful sub-seasonal forecasts of CAO by using the stratospheric signals. At both interdecadal and interannual timescales, a warm phase of the El Niño–Southern Oscillation (ENSO) in winter is favorable for the higher lag-coupling rate of CAO_NA and the lead-coupling rate of CAO_EA, and vice versa. The ENSO signals related to the interdecadal changes of the CAO coupling rate in winter can be traced back to the previous winter, while an ENSO phase transition from the previous winter to the current winter is closely related to the interannual changes of the CAO coupling rate
MicroRNA-212-5p Prevents Dopaminergic Neuron Death by Inhibiting SIRT2 in MPTP-Induced Mouse Model of Parkinson’s Disease
Recently, emerging evidences show that sirtuins (SIRTs) modulate aging progress and affect neurodegenerative diseases. For example, inhibition of SIRT2 has been recognized to exert neuroprotective effects in Parkinson’s disease (PD). However, current SIRT2 inhibitors are lack of selective property distinguished from its homolog. In this study, we found that SIRT2 protein level was highly increased in PD model, which was negatively regulated by miR-212-5p. In detail, miR-212-5p transfection reduced SIRT2 expression and inhibited SIRT2 activity. In vivo study, miR-212-5p treatment prevented dopaminergic neuron loss and DAT reduction by targeting SIRT2, which means miR-212-5p shows neuroprotective effect in PD. Mechanismly, we found nuclear acetylated p53 was up-regulation according to p53 is a major deacetylation substrate of SIRT2. Furthermore, decreased cytoplasmic p53 promoted autophagy in PD model, which was showed as autophagosomes, autophagic flux, LC3 B and p62 expression. Meanwhile, we also found miR-212-5p treatment somehow alleviated apoptosis in PD model, which might have some underlying mechanisms. In conclusions, our study provides a direct link between miR-212-5p and SIRT2-mediated p53-dependent programmed cell death in the pathogenesis of PD. These findings will give us an insight into the development of highly specifically SIRT2 inhibitor of opening up novel therapeutic avenues for PD
Common Co-activation of AXL and CDCP1 in EGFR-mutation-positive Non-smallcell Lung Cancer Associated With Poor Prognosis.
Epidermal growth factor receptor (EGFR)-mutation-positive non-smallcell lung cancer (NSCLC) is incurable, despite high rates of response to EGFR tyrosine kinase inhibitors (TKIs). We investigated receptor tyrosine kinases (RTKs), Src family kinases and focal adhesion kinase (FAK) as genetic modifiers of innate resistance in EGFR-mutation-positive NSCLC. We performed gene expression analysis in two cohorts (Cohort 1 and Cohort 2) of EGFR-mutation-positive NSCLC patients treated with EGFR TKI. We evaluated the efficacy of gefitinib or osimertinib with the Src/FAK/Janus kinase 2 (JAK2) inhibitor, TPX0005 in vitro and in vivo. In Cohort 1, CUB domain-containing protein-1 (CDCP1) was an independent negative prognostic factor for progression-free survival (hazard ratio of 1.79, p=0.0407) and overall survival (hazard ratio of 2.23, p=0.0192). A two-gene model based on AXL and CDCP1 expression was strongly associated with the clinical outcome to EGFR TKIs, in both cohorts of patients. Our preclinical experiments revealed that several RTKs and non-RTKs, were up-regulated at baseline or after treatment with gefitinib or osimertinib. TPX-0005 plus EGFR TKI suppressed expression and activation of RTKs and downstream signaling intermediates. Co-expression of CDCP1 and AXL is often observed in EGFR-mutation-positive tumors, limiting the efficacy of EGFR TKIs. Co-treatment with EGFR TKI and TPX-0005 warrants testing
Yupingfeng Pulvis Regulates the Balance of T Cell Subsets in Asthma Mice
Background. Yupingfeng Pulvis (HFBP) had played an active role in many diseases, especially respiratory tract infections. Exploring the possible prevention mechanism of HFBP may provide new ideas in clinical applications for this well-known herbal formula. Purpose. To study the possible mechanisms of therapy effect of HFBP on asthma mice via regulating the balance of Tregs and Th17 cells. Method. The female BALB/c mice were divided into five groups: control group, model group, prednisone (5.5 mg/kg) group, and 22 g/kg HFBP and 44 g/kg HFBP groups. Ovalbumin was used to make the asthma model of mice; the drug was ig administered daily after atomization for consecutive 15 d. The mice were killed after the last administration. The paraffin-embedded tissue sections of the lungs were stained by H&E. Tregs and Th17 cells in bronchoalveolar lavage fluid were detected by flow cytometry. IL-4, TGF-β, and TNF-α in the serum were detected by ELISA assay. Results. HFBP could alleviate the inflammation in the lung tissue of mice, decrease the proportion of Th17 cells, and increase the proportion of Treg cells in bronchoalveolar lavage fluid. HFBP could decrease IL-4 and TNF-α level and increase TGF-β level in blood. Conclusion. HFBP could treat the asthma through impacting the balance of Th17 cells and Treg cells as well as the levels of related inflammatory cytokines in asthma mice
The comparison of manual and mechanical anastomosis after total pharyngolaryngoesophagectomy
BackgroundTotal pharyngolaryngoesophagectomy (TPLE) is considered as a curative treatment for hypopharynx cancer and cervical esophageal carcinomas (HPCECs). Traditional pharyngo-gastric anastomosis is usually performed manually, and postoperative complications are common. The aim of this study was to introduce a new technique for mechanical anastomosis and to evaluate perioperative outcomes and prognosis.MethodsFrom May 1995 to Nov 2021, a series of 75 consecutive patients who received TPLE for a pathological diagnosis of HPCECs at Sun Yat-sen Memorial Hospital were evaluated. Mechanical anastomosis was performed in 28 cases and manual anastomosis was performed in 47 cases. The data from these patients were retrospectively analyzed.ResultsThe mean age was 57.6 years, and 20% of the patients were female. The rate of anastomotic fistula and wound infection in the mechanical group were significantly lower than that in the manual group. The operation time, intraoperative blood loss and postoperative hospital stays were significantly higher in the manual group than that in the mechanical group. The R0 resection rate and the tumor characteristics were not significantly different between groups. There was no significant difference in overall survival and disease-free survival between the two groups.ConclusionThe mechanical anastomosis technology adopted by this study was shown to be a safer and more effective procedure with similar survival comparable to that of manual anastomosis for the HPCECs patients
- …