Anti-CD33 monoclonal antibody (CABT-ZC1102)


Host Species
Antibody Isotype
Species Reactivity
Full length human recombinant protein of human CD33 produced in HEK293T cell.


Application Notes
ELISA: 1:250-1:1000
We recommend the following for sandwich ELISA (Capture - Detection):
CABT-ZC1107 - CABT-ZC1102
*Suggested working dilutions are given as a guide only. It is recommended that the user titrates the product for use in their own experiment using appropriate negative and positive controls.


Alternative Names
Entrez Gene ID
UniProt ID


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Research advances in nanomedicine, immunotherapy, and combination therapy for leukemia


Authors: Wan, Zhuoya; Sun, Runzi; Moharil, Pearl; Chen, Jing; Liu, Yuzhe; Song, Xu; Ao, Qiang

In the past decade, clinical and laboratory studies have led to important new insights into the biology of leukemia and its treatment. This review describes the progress of leukemia research in the United States in recent years. Whereas the traditional method of treatment is chemotherapy, it is nonselective and could induce systemic toxicities. Thus, in parallel with research on new chemotherapies, great emphasis has been placed on developing immunotherapies. Here, we will review the current immunotherapies available in research and development that overcome current challenges, specifically looking in the field of chimeric antigen receptor T-cell (CAR-T) therapies, checkpoint inhibitors, and antibody-drug conjugates. With about 100 clinical trials for CAR-T therapies and 30 in checkpoint inhibitors for leukemia treatment, scientists are trying to make these technologies cheaper, faster, and more feasible. Further describing the delivery of these therapeutics, we look at the current progress, clinical, and preclinical status of nano-based medicines such as liposomes, polymeric micelles, and metal nanoparticles. Taking advantage of their physicochemical and biologic properties, nanoparticles have been shown to increase the efficacy of commonly administered chemotherapies with reduced adverse effects.

Whole-exome sequencing of the BDR cohort: evidence to support the role of the PILRA gene in Alzheimer's disease


Authors: Patel, T.; Brookes, K. J.; Turton, J.; Chaudhury, S.; Guetta-Baranes, T.; Guerreiro, R.; Bras, J.; Hernandez, D.; Singleton, A.; Francis, P. T.; Hardy, J.; Morgan, K.

Aim: Late-onset Alzheimer's disease (LOAD) accounts for 95% of all Alzheimer's cases and is genetically complex in nature. Overlapping clinical and neuropathological features between AD, FTD and Parkinson's disease highlight the potential role of genetic pleiotropy across diseases. Recent genome-wide association studies (GWASs) have uncovered 20 new loci for AD risk; however, these exhibit small effect sizes. Using NGS, here we perform association analyses using exome-wide and candidate-gene-driven approaches. Methods: Whole-exome sequencing was performed on 132 AD cases and 53 control samples. Exome-wide single-variant association and gene burden tests were performed for 76 640 non-singleton variants. Samples were also screened for known causative mutations in familial genes in AD and other dementias. Single-variant association and burden analysis was also carried out on variants in known AD and other neurological dementia genes. Results: Tentative single-variant and burden associations were seen in several genes with kinase and protease activity. Exome-wide burden analysis also revealed significant burden of variants in PILRA (P = 3.4 X 10(-5)), which has previously been linked to AD via GWAS, hit ZCWPW1. Screening for causative mutations in familial AD and other dementia genes revealed no pathogenic variants. Variants identified in ABCA7, SLC24A4, CD33 and LRRK2 were nominally associated with disease (P < 0.05) but did not withstand correction for multiple testing. APOE (P = 0.02) and CLU (P = 0.04) variants showed significant burden on AD. Conclusions: In addition, polygenic risk scores (PRS) were able to distinguish between cases and controls with 83.8% accuracy using 3268 variants, sex, age at death and APOE epsilon 4 and epsilon 2 status as predictors.

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