Mouse Monoclonal to CD105 / Endoglin, Clone MEM-229, Isotype IgG2aApplication FC, WB, IHC(F), ICC Concentration 1 mg/ml
- Known as:
- Mouse Monoclonal CD105 / Endoglin, Clone MEM-229, Isotype IgG2aApplication FC, Western Blot, Immunohistochemistry(F), ICC Concentration 1 mg/milliliter
- Catalog number:
- 1B-453-C100
- Product Quantity:
- 0.1 mg
- Category:
- -
- Supplier:
- Exbio
- Gene target:
- Mouse Monoclonal CD105 / Endoglin Clone MEM-229 Isotype IgG2aApplication IHC() ICC Concentration 1
Related genes to: Mouse Monoclonal to CD105 / Endoglin, Clone MEM-229, Isotype IgG2aApplication FC, WB, IHC(F), ICC Concentration 1 mg/ml
- Gene:
- BIRC3 NIH gene
- Name:
- baculoviral IAP repeat containing 3
- Previous symbol:
- API2
- Synonyms:
- cIAP2, hiap-1, MIHC, RNF49, MALT2, c-IAP2
- Chromosome:
- 11q22.2
- Locus Type:
- gene with protein product
- Date approved:
- 1998-06-10
- Date modifiied:
- 2016-10-05
- Gene:
- ENG NIH gene
- Name:
- endoglin
- Previous symbol:
- ORW1, ORW
- Synonyms:
- END, HHT1, CD105
- Chromosome:
- 9q34.11
- Locus Type:
- gene with protein product
- Date approved:
- 1993-03-03
- Date modifiied:
- 2019-04-23
- Gene:
- GIHCG NIH gene
- Name:
- GIHCG inhibitor of miR-200b/200a/429 expression
- Previous symbol:
- -
- Synonyms:
- lncRNA-GIHCG
- Chromosome:
- 12q14.1
- Locus Type:
- RNA, long non-coding
- Date approved:
- 2018-07-25
- Date modifiied:
- 2019-01-25
Related products to: Mouse Monoclonal to CD105 / Endoglin, Clone MEM-229, Isotype IgG2aApplication FC, WB, IHC(F), ICC Concentration 1 mg/ml
Related articles to: Mouse Monoclonal to CD105 / Endoglin, Clone MEM-229, Isotype IgG2aApplication FC, WB, IHC(F), ICC Concentration 1 mg/ml
- This paper presents a numerical model for damage problems in soft biological tissues with random fields, integrating the advantages of the modified stochastic perturbation method (MSPM) and quadtree scaled boundary finite element method (quadtree SBFEM). The anisotropic hyperelastic constitutive model is used, and the damage behavior is described by a gradient-enhanced damage model without mesh dependence. The deterministic problem is formulated by the quadtree SBFEM with the benefit of convenient mesh regeneration directly from images. In order to describe spatial heterogeneous soft biological tissues, the constitutive parameters are assumed by the random field model, which is given by Karhunen-Loève (K-L) expansion. The stochastic responses of structures are solved by MSPM, for which the derivatives of the system matrices are not required. Numerical examples are conducted to verify the accuracy and efficiency of the proposed approaches and to obtain the mean values and standard deviations of the random response of spatial heterogeneous soft biological tissues damage problems, including the calculation of the probability of failure (PoF) of arterial wall during atherosclerosis in angioplasty. - Source: PubMed
Dong XingcongYang HaitianWu FengHe Yiqian - Online adaptive radiotherapy (ART) requires fast and accurate delineation of targets and organs at risk on cone-beam computed tomography (CBCT). Although deep learning (DL)-based CBCT auto-segmentation methods have been proposed, their clinical generalizability remains insufficiently validated. This study aimed to externally evaluate a pretrained DL model for lung tumor and esophagus segmentation on CBCT. Originally trained using C-arm linac CBCT images, the model was directly applied to an independent cohort of 12 lung cancer patients, each with 5 CBCT images acquired at a separate institution on an O-ring linac. Rigid propagation of planning CT contours served as a minimal baseline to determine whether the model matched or outperformed conventional rigid registration for gross tumor volume (GTV) and esophagus segmentation using geometric and dosimetric measures. Compared with rigid contour propagation, the model significantly improved GTV segmentation accuracy, with mean Dice similarity coefficient (DSC) increasing from 0.66 to 0.76. Significant differences in GTV D98% were observed between the model-generated contours and the reference contours (50.69 vs. 53.58 Gy). The model showed a statistically non-significant decrease in performance compared with previously reported results on its original testing dataset (mean DSC = 0.84), which shared the same distribution as the training dataset. For esophagus segmentation, evaluation of 26 scans from 6 patients showed that the model achieved geometric accuracy within peri-target contour rings comparable to rigid propagation, with mean DSC of 0.72 and 0.70, respectively. Similar esophagus V32Gy values were observed between the model-generated and reference contours (0.06 vs. 0.06 cc). Significantly reduced accuracy was observed compared with previously reported results, with mean DSC decreasing from 0.79 to 0.72. These findings highlight that DL-based CBCT auto-segmentation may suffer performance degradation under domain shifts across patient populations, clinical workflows, and imaging systems, emphasizing the necessity of external evaluation beyond the original development environment. - Source: PubMed
Publication date: 2026/10/02
Zhang ZhehaoHobbis DeanJiang JueRangnekar AneeshChoi Chloe Min SeoWaters MichaelVeeraraghavan HariniHugo Geoffrey D - Nanoparticles encapsulating therapeutic RNA have emerged as a transformative strategy in precision medicine, enabling a wide range of applications such as gene therapy for rare diseases, the silencing of toxic gene products, and the mobilization of the immune system to induce specific responses ranging from immune tolerance to fighting tumors. However, most current preclinical and clinical efforts rely on non-targeted delivery systems, limiting their safety, therapeutic efficacy, and selectivity. To enhance the therapeutic index of RNA-based therapeutic systems, we report on the design of a novel Clec9A-targeted polymeric nanoparticle aimed at exploring strategies to enhance delivery toward CLEC9A-expressing immune cells as a proof of concept in the field of mRNA vaccination. We began by evaluating in silico the binding potential of the previously reported 12-amino-acid WH peptide, known for its high affinity to mouse Clec9A, the human ortholog. Using computational tools, we designed and screened truncated variants of the peptide and identified promising candidates with retained, or even enhanced, binding capacity to human Clec9A. These optimized short peptides were synthesized and covalently conjugated to our proprietary poly(beta-amino ester) (pBAE) polymers. We evaluated the impact of the conjugation site on receptor targeting by comparing terminal versus lateral chain attachment. We show that peptide orientation significantly influences transfection efficiency in human THP-1 cells, used as a monocytic robust in vitro model. Additionally, we computationally generated and validated shorter mutant peptide variants with improved Clec9A affinity over the original sequences. Our findings demonstrate that rationally engineered short peptides improve transfection in a human monocytic cell model, which is consistent with the proposed Clec9A-targeting strategy suggested by computational modeling. This strategy lays the groundwork for the next generation of targeted RNA-based (immune)therapeutics, offering improved selectivity and consequent therapeutic potential. - Source: PubMed
Publication date: 2026/10/02
Stamenković VladimirBrajković MislavGarcia-Fernandez CoralBorrós SalvadorBiarnés XeviFornaguera Cristina - Tetracycline resistance genes (TRGs) in wastewater pose environmental and public health risks through antimicrobial resistance dissemination. However, the global development of wastewater surveillance for TRG monitoring remains insufficiently characterized. Scopus-indexed TRG wastewater surveillance research (2001-2025) was analyzed using bibliometric methods, yielding 700 articles after screening. Data were cleaned using biblioMagika and OpenRefine, with VOSviewer used for keyword co-occurrence analysis. Temporal trends were assessed using the Mann-Kendall test, Sen's slope estimator, and Hamed-Rao correction for serial autocorrelation. Publication output increased significantly (τ = 0.891, = 1.15 × 10; Sen's slope ≈ 3.84 publications/year) and remained significant after autocorrelation correction (N/N* ≈ 3.16, = 6.16 × 10). China and the United States led publication output (370 and 99 publications, respectively), while publication volume was not significantly associated with normalized citation impact ( = 0.163, = 0.436). Environmental science and microbiology dominated. Six thematic clusters centered on antibiotic resistance genes, horizontal gene transfer, metagenomics, and wastewater treatment. TRG wastewater surveillance research is expanding rapidly, highlighting the need for international collaboration, methodological standardization, and capacity building within a One Health framework. - Source: PubMed
Publication date: 2026/10/02
Abubakar Tirmizhi MunkailaMohd Zain Nor Azimah - Rupture of intracranial aneurysms is a major cause of subarachnoid hemorrhage, making accurate segmentation important for aneurysm assessment and treatment planning. However, automated segmentation in computed tomography angiography (CTA) remains challenging because of small lesion size, complex morphology, and ambiguous boundaries between aneurysms and adjacent vessels. To address these challenges, we propose HSF-Net, a Swin UNETR-based segmentation network that integrates a Hybrid-Scale Fusion (HSF) module and the Convolutional Block Attention Module (CBAM) into the decoder. Unlike conventional decoders that mainly rely on simple feature concatenation, HSF-Net follows a "fuse first, refine later" strategy, in which HSF performs input-dependent multi-scale feature fusion and CBAM subsequently refines the fused features through channel and spatial attention. On the internal independent test set, HSF-Net achieved a mean patient-level Dice score of 83.4%, outperforming the Swin UNETR baseline and obtaining the highest Dice score among the evaluated methods under the same evaluation protocol. Ablation studies confirmed the complementary contributions of HSF and CBAM. Evaluation on an independent external cohort provided preliminary evidence of its cross-center applicability. These results suggest that HSF-Net provides an effective approach for automated intracranial aneurysm segmentation in CTA images. - Source: PubMed
Publication date: 2026/10/02
Yang ShuwenWang PeipeiYe MingquanLiu LeleLi YajieZhou Yunfeng