GPR177 Blocking Peptide
- Known as:
- GPR177 Blocking Peptide
- Catalog number:
- 33r-1477
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Fitzgerald industries international
- Gene target:
- GPR177 Blocking Peptide
Related genes to: GPR177 Blocking Peptide
- Gene:
- WLS NIH gene
- Name:
- Wnt ligand secretion mediator
- Previous symbol:
- C1orf139, GPR177
- Synonyms:
- FLJ23091, MRP, wls, EVI, mig-14
- Chromosome:
- 1p31.3
- Locus Type:
- gene with protein product
- Date approved:
- 2005-07-08
- Date modifiied:
- 2018-11-09
Related products to: GPR177 Blocking Peptide
Related articles to: GPR177 Blocking Peptide
- Identify the perceived importance of front-of-package warning labels in purchase decisions of industrialized food products among Mexican adults with self-reported noncommunicable diseases (NCDs). - Source: PubMed
Publication date: 2026/06/18
Sagaceta-Mejía JanineCruz-Casarrubias CarlosMunguía AnaDurán ReginaTolentino-Mayo LizbethBarquera Simón - Ultra-wideband (UWB) localization is widely used in indoor positioning because it provides high temporal resolution and direct geometric range constraints. In complex indoor environments, however, UWB ranging is affected by non-line-of-sight propagation, multipath reflection, heterogeneous measurement quality, and link-dependent persistent bias, producing long-tailed errors and trajectory drift. This paper proposes HBR-PGD, a heteroscedastic bias-robust projected gradient descent framework for UWB-only indoor localization. Its central idea is a role-separated error-source formulation that assigns packet-level quality degradation, anchor-channel persistent bias, and sparse instantaneous NLOS anomalies to different roles in a unified constrained residual model. Packet-level quality features are mapped to heteroscedastic uncertainty scales, robust loss shape parameters, and non-negative NLOS correction priors; anchor-channel soft gating limits residual-correction freedom; and target trajectories and bounded structural bias states are jointly estimated in overlapping sliding windows. Experiments on a public indoor UWB dataset show that HBR-PGD achieves RMSE values of 0.107 m, 0.068 m, and 0.204 m in residential-apartment, small-apartment, and workshop/industrial environments, respectively. Compared with WLS, MCC-VC-TOA, SR-MCC, and AR-PNN, HBR-PGD consistently improves overall accuracy and high-percentile robustness, with the largest gain in the workshop/industrial environment. Ablation results verify the contributions of heteroscedastic weighting, structural-bias estimation, gated correction, and information-weighted fusion. These results suggest that HBR-PGD is a practical UWB-only localization framework for complex indoor environments with heterogeneous measurement quality, persistent link bias, and sparse NLOS anomalies. - Source: PubMed
Publication date: 2026/07/19
Yu ZhongyangLiu QinghuaQian Yong - : Accurate prediction of surgical duration is essential for efficient operating room management. Spine surgery frequently shows discrepancies between estimated and actual surgical duration, which can disrupt surgical scheduling and resource allocation. The aim of this study was to develop and compare machine learning (ML) algorithms for predicting spine surgery duration and identify the most effective approach. : Electronic medical records of 3376 patients who underwent spine surgery were retrospectively analyzed at a single center. The dataset was divided into training (80%, = 2700) and internal test (20%, = 676) sets using stratified random sampling based on surgical duration quintiles. To match the intended use at the time of operating room scheduling, four models (Random Forest, XGBoost, multilayer perceptron [MLP], and weighted least squares [WLS] regression) were developed using only predictors available at scheduling and evaluated on the independent internal test set; a full-information model that additionally included intraoperatively recorded variables was examined for comparison. : XGBoost demonstrated the best predictive performance, achieving a mean squared error (MSE) of 3014.6 min (equivalent to a root mean squared error [RMSE] of 54.9 min; 95% CI for MSE, 2558.3-3556.0) and an R of 0.622 (95% CI, 0.566-0.675). The other ML models showed comparable performance, whereas WLS regression performed less favorably; the full-information model performed equivalently (R 0.622). Compared with surgeon-estimated duration alone, XGBoost reduced mean absolute error by approximately 20 min (paired ΔMAE -20.1 min; 95% CI, -23.7 to -16.5) and improved prediction accuracy within 60 min by 14.0 percentage points. SHapley Additive exPlanations (SHAP) analysis identified surgeon identity as the most influential predictor across all models (24.7-41.9%), followed by procedure type and surgeon-estimated duration. : Machine learning models substantially improved prediction of spine surgery duration compared with conventional approaches, with XGBoost showing the highest predictive accuracy. Surgeon identity emerged as the most important predictor of surgical duration. Implementation of such models may improve operating room scheduling efficiency and resource allocation but requires prospective evaluation of clinical and workflow outcomes. - Source: PubMed
Publication date: 2026/07/06
Ko MyungjinLee Hyung ChulLee Hyun SeongLee ByeongcheolLee Min WooKim Yu JeongPark Jae Hong - Forecast reconciliation has become the standard for ensuring coherence in hierarchical time series. However, state-of-the-art methods like Minimum Trace (MinT) prioritize the minimization of error variance, often at the expense of distorting the temporal morphology of the forecast. This paper reframes forecast reconciliation as a multi-objective problem, showing that variance-optimal coherence is insufficient for operational decision-making, and proposing a shape-aware reconciler that explicitly encodes temporal structure. We introduce Shape-Preserving Minimum Trace (SP-MinT), a novel framework that regularizes the optimization process with domain-informed priors constructed from historical day-of-week profiles. We validate the method using a rigorous rolling cross-validation on real-world electricity demand data from Victoria, Australia. The results demonstrate that SP-MinT outperforms the standard MinT-WLS benchmark by reducing the Root Mean Squared Error (RMSE) by 31.94% and the Shape Error (Dynamic Time Warping) by 43.16%. By bridging the gap between statistical optimality and morphological fidelity, SP-MinT offers grid operators hierarchically coherent forecasts that respect physical ramping constraints. - Source: PubMed
Publication date: 2026/07/19
Gonzalez-Sierra MauroVélez Jorge IArango-Manrique Adriana - The aims of this study were 1) to determine how ligature-induced periodontitis (LIP) disrupts barrier functions of the junctional epithelium (JE); 2) to determine, using a genetic approach, the necessity of Wnt signaling for JE barrier functions; and 3) to test, using a biochemical strategy, whether a WNT therapeutic is sufficient to improve barrier functions of a pocket epithelium. In a murine model of LIP, quantitative analyses performed at multiple time points assessed epithelial apoptosis; expression of attachment proteins laminin 5 and β4 integrin, inflammation, and bone resorption. mice were used to evaluate how LIP impacted Wnt-responsive cells and their progeny, and mice were used to determine whether Wnt signaling was required for JE barrier functions. In some cases, LIP was followed by a recovery period to assess molecular changes in pocket epithelium, and in a subset of these mice, a liposomal formulation of human WNT3A protein (L-WNT3A) was tested for its effects on early repair dynamics in pocket epithelium. LIP triggered apoptosis, significantly reduced expression of laminin 5 and β4 integrin in the JE, and disrupted the Wnt-responsive compartment; these epithelial changes were accompanied by inflammation and alveolar bone resorption. Reepithelialization occurred even with a ligature present, but this pocket epithelium had compromised barrier functions. Wntless (Wls) deletion was sufficient to convert a JE into pocket epithelium, while topical L-WNT3A treatment was sufficient to increase hemidesmosomal protein expression in pocket epithelium and reduce inflammation at early time points. LIP destroys barrier functions and thus converts a JE into pocket epithelium. Deletion of epithelial demonstrates that this conversion is a Wnt-dependent event. L-WNT3A restores some early barrier features to pocket epithelium; future studies will focus on the durability of these effects. - Source: PubMed
Publication date: 2026/07/18
Aellos FChang EJeong ELiu BYuan XNazari RHermans FTorabi M MOchweri P CCuevas PRao SAlccayhuaman K A ApazaSandoval ACoyac B RLambrichts IHelms J A