PITPNB Antibody (C-term) Blocking Peptides
- Known as:
- PITPNB Antibody (C-terminus) Blocking Peptides
- Catalog number:
- BP12982b
- Product Quantity:
- 2
- Category:
- -
- Supplier:
- Abgen
- Gene target:
- PITPNB Antibody (C-term) Blocking Peptides
Related genes to: PITPNB Antibody (C-term) Blocking Peptides
- Gene:
- PITPNB NIH gene
- Name:
- phosphatidylinositol transfer protein beta
- Previous symbol:
- -
- Synonyms:
- VIB1B
- Chromosome:
- 22q12.1
- Locus Type:
- gene with protein product
- Date approved:
- 1999-10-29
- Date modifiied:
- 2015-11-20
Related products to: PITPNB Antibody (C-term) Blocking Peptides
Related articles to: PITPNB Antibody (C-term) Blocking Peptides
- Seminal plasma (SP) is a complex immune modulator within the female reproductive tract of several species. In sheep, it can restore the fertility of cryopreserved sperm and is necessary for the fertility of epididymal sperm following cervical artificial insemination. We have also shown it capable of protecting cryopreserved sperm from polymorphonuclear leukocyte (PMN) binding . Thus, we hypothesize SP, and its components confer immune protection to sperm following deposition in the ovine cervix and that sperm cryopreservation disrupts this delicate sperm-female interaction. To delineate the contributions of soluble and extracellular vesicle (EV) associated SP components, frozen-thawed ram spermatozoa were incubated with whole SP, EV-depleted SP (DSP) and enriched EVs. All SP treatments significantly reduced binding (FTSP: 20.7 ± 3.39%; FTDSP: 24.3 ± 3.64%; FTEV: 19.8 ± 3.63%) compared to the control (36.3 ± 3.63%; p < 0.0001), with no differences between treated groups. To further isolate inhibitory factors, FT was incubated with SP fractionated into 5 molecular weight treatments (F1; <10, 10-30, 30-50, 50-100, >100 kDa). Two fractions, F3 (300kDa) and F5 (>100kDa) reduced PMN binding (22.44 ± 2.18%, 21.67 ± 1.85%, respectively) compared to the control (FT: 58.83 ± 4.54%; p < 0.0001) and similar to whole SP (20.67 ± 1.65%; p>0.05), indicating these fractions contain key immunoregulatory factors. Proteomic analysis identified 2,161 proteins in whole SP, with SP-EVs contributing 795 unique proteins. Among protective fractions (SP, DSP, EV, F3, F5), 588 proteins were shared, including a core signature of PITPNB, RPLP2, SLC9A3R1, PTTG1IP, CKAP4, and FKBP11, absent in non-protective fractions. Complement regulators (CD46, CD59, CFH, CLU) and glycocalyx-associated proteins (CRISPs, DEFB124) were enriched in protective fractions, supporting layered immunomodulation via both soluble and vesicular delivery. Functional analyses demonstrated that SP modulates PMN binding and activation while maintaining sperm viability, highlighting a structured, multi-layered immunoregulatory system. These findings provide the most comprehensive characterization of ram SP and SP-EVs to date, integrating functional assays with proteomic profiling, and reveal conserved protein signatures that underpin sperm immune tolerance. This work establishes a foundation for future studies targeting EV-mediated delivery and glycocalyx-associated immunoregulators to improve fertility outcomes and assisted reproductive technologies. - Source: PubMed
Publication date: 2026/09/03
Warr SophieMikhael LydiaTorres-Arce ElizabethSchjenken JohnPini Taylorde Graaf Simon PRickard Jessica P - Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning approach to identify a gene expression signature predicting pathological complete response (pCR) versus residual disease (RD) using bulk RNA-sequencing data from GSE163882 (138 RD, 80 pCR). We employed TMM normalization with differential expression analysis (250 genes, FDR < 0.05, |log2FC| ≥ 1), ensemble feature selection across five classifiers (Random Forest, Gradient Boosting, SVM, k-NN, and Neural Network) with 10-fold repeated cross-validation, and stacked ensemble development. Consensus selection identified a 17-gene signature consistently ranked across algorithms. The stacked ensemble achieved 0.97 AUC post-testing on hold-out test data. External validation on the independent GSE240671 cohort (37 pCR, 25 RD) following ComBat batch correction achieved ROC AUC of 0.78 and PR AUC of 0.85 with isotonic calibration, demonstrating balanced accuracy of 0.71 and 0.86 sensitivity for pCR detection. Pathway enrichment revealed associations with cell cycle regulation (E2F3, MKI67), DNA repair (BRCA2), and transcriptional control (MED1), with six priority genes (MED1, BRCA2, E2F3, PITPNB, H1-1, and FARP2) showing established breast cancer relevance. This externally validated 17-gene signature provides a biologically grounded tool for NAC response prediction in precision oncology. - Source: PubMed
Publication date: 2026/01/16
Lamprou SteliosGeorgiou StylianaStylianopoulos TriantafyllosVoutouri Chrysovalantis - Moyamoya disease (MMD) is a chronic, progressive occlusive cerebrovascular disease. It causes recurrent cerebrovascular stroke due to vascular closure and proliferation. An unclear pathophysiological mechanism is the most significant obstacle in the diagnosis and treatment of MMD. - Source: PubMed
Publication date: 2025/07/28
Zhou ZhenyuNiu HongchuanXu ShaoqiZhang JunzeLiu YutongLei ChengxuHe ShihaoZhao Yuanli - BACKGROUND: The Holstein Friesian (HF) cattle breed is the most dominant breed in commercial dairy farming worldwide and managed in more than 150 countries. These countries span diverse agro-climatic zones, ranging from tropical to cold regions. The introduction of HF animals in these regions occurred at different moments in the past which are poorly recorded and continued through importation of live animal and frozen semen. We hypothesize that the HF cattle populations in these regions underwent early forms of adaptation to these specific local environments. However, the detection of genetic variation associated with this adaptation remains poorly documented. RESULTS: This study investigates genetic relationship and potential early selection signatures in HF populations from three African countries (Egypt, South Africa, Uganda) and three European countries (Finland, Portugal, The Netherlands), considering five animals per country. Approximately 16.0 million single nucleotide polymorphisms (SNPs) were detected in the 30 HF animals and used for further analyses. Across all countries, we identified dispersed regions totaling 3.3 megabase of ecosystem-specific genomic regions (43 genes), indicative of early selection signatures based on fixation indices (F-statistic, Fst). Furthermore, comparing variants between tropical (Egypt and Uganda) and cold regions (Finland and The Netherlands) by Fst, nucleotide diversity (θπ ratio), and extended haplotype homozygosity (XP-EHH), we identified a total of 10 candidate regions, comprising 12 genes within a 0.57 megabase size. The regions were enriched with genes involved in signaling pathways associated directly or indirectly with adaptation, including the immune system (PGLYRP4,PGLYRP3, PAG1, CD48, SLAMF1, DYSF,and LOC615223), organ development and reproduction (LDB3, ADAMTSL4, TPRN, CCDC40, OR2AG1G, and OR8B3), thermogenic activation (TBC1D16), phospholipid metabolism (PLPPR4 and PITPNB), thermos-tolerance (ZNF423), and stimulus response (NCOA7, CYP2C85, and ARFGEF3). CONCLUSION: This study provides new insights into early forms of genetic plasticity of animals adapted to very diverse ecosystems. Our findings highlight candidate genes related to immune response, organ development, reproduction, metabolism, and thermo-tolerance, hypothesizing their role in facilitating adaptation to different environments. - Source: PubMed
Publication date: 2025/07/01
Gao JunxinGonzalez-Prendes RaynerLiu YingKantanen JuhaGinja CatarinaGhanem NasserKugonza Donald RugiraMakgahlela MahlakoBovenhuis HenkGroenen Martien A MCrooijmans Richard P M A - Previous studies have indicated a significantly higher prevalence of breast cancer (BC) among female patients with meningioma compared to the general female population. Therefore, this study aimed to assess the causal relationship between BC and meningioma at the genetic level. Genetic instrumental variables (IVs) for BC were identified from the Breast Cancer Association Consortium (BCAC), the Discovery Biology and Risk of Inherited Variants in Breast Cancer Consortium (DRIVE), the Collaborative Oncological Gene-environment Study (iCOGS), and 11 other BC genome-wide association studies (GWAS). Meningioma GWAS data were obtained from the FinnGen consortium and were further divided into intracranial and spinal meningioma groups for analysis. The primary analysis employed the inverse-variance weighted (IVW) method, supported by sensitivity analysis to address pleiotropy and enhance robustness. Next, linkage disequilibrium score regression (LDSC) was used to assess the genetic correlation between BC and meningioma. Finally, we applied the Functional Mapping and Annotation (FUMA) platform to conduct an in-depth analysis of the GWAS data. After rigorous screening and Mendelian randomization (MR) tests, genetically predicted overall BC (OR: 1.17, P = 0.0045) and ER(estrogen receptors) + BC (OR: 1.21, P = 0.0006) showed a potential causal association with intracranial meningioma. No causal relationships were found between intracranial meningioma and three BC subtypes. No bidirectional causal relationships were found between spinal meningioma and any BC subtype. The LDSC results suggested a modest positive genetic correlation between overall BC (rg: 0.152, SE: 0.077, P = 0.048), ER + BC (rg: 0.181, SE: 0.086, P = 0.035), and intracranial meningioma. FUMA analysis identified PITPNB, TTC28, and CHEK2 as shared risk genes between overall BC, ER + BC, and intracranial meningioma. These findings suggest that BC, especially ER + BC, may be a risk factor for intracranial meningioma. ER-related signaling pathways and the regulation of DNA damage may play a critical role in the pathogenesis of both diseases. - Source: PubMed
Publication date: 2025/02/04
Ding LuChen BoZhou ZhouMei ZhaojunCao KanLu XinyuChen Wei