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Background: The clinical strategy of oral supplementation of Vitamin D (VD) as a preventive and therapeutic measure for warts needs further exploration. Methods: The clinical data of patients with skin diseases who visited the Children's Hospital affiliated with Chongqing Medical University from February 2018 to June 2024 were collected. The serum VD levels in patients with warts (common warts, flat warts, and plantar warts) and patients with other common skin diseases (atopic dermatitis, psoriasis, alopecia areata, vitiligo, and chronic urticaria) were compared. Two‐sample bidirectional Mendelian randomization (MR) analysis was performed to investigate potential causal associations between VD and warts. Results: The average serum VD level of children with warts was 23.27 ± 7.07 ng/mL, which showed no statistically significant difference compared to children with other common skin diseases. The inverse variance weighted (IVW) method analysis indicated a positive causal relationship between VD and warts (Odds Ratio [OR] = 1.86, [95% CI: 1.19−2.92], p = 0.007). Sensitivity analysis did not show any indication of horizontal pleiotropy or heterogeneity. The MR‐PRESSO method did not identify any outliers. Conclusion: The levels of serum VD in children with warts do not significantly decrease compared to children with other common skin conditions. The evidence from the MR analysis indicates a positive causal relationship between VD and warts, suggesting caution in supplementing VD for children with warts who have normal or elevated serum VD levels. Further clinical studies are needed for validation in the future. [ABSTRACT FROM AUTHOR]

Purpose: Osteosarcoma is a primary bone tumor lacking optimal clinical treatment options. Tumor-associated macrophages in the tumor microenvironment are closely associated with tumor development and metastasis. Studies have identified the macrophage receptor with collagenous structure (MARCO) as a specific receptor expressed in macrophages. This study aimed to investigate whether anti-MARCO mAb treatment can induce macrophage polarization in the tumor microenvironment and elicit anti-tumor effects. Methods: THP-1 cells were treated with 20 ng/mL phorbol 12-myristate 13-acetate and 80 ng/mL interleukin-4 for 48 h to induce macrophage polarization to alternatively activated macrophages (M2). Enzyme-linked immunosorbent assay, real-time quantitative polymerase chain reaction, flow cytometry, and bioinformatic analyses were performed to evaluate macrophage polarization. The co-culture groups included a blank group, an M2 macrophage and U2OS co-culture group, and an anti-MARCO mAb-treated M2 macrophage group. Cell viability assays, cell scratch tests, apoptosis, and cell cycle analyses were performed to determine the effects of anti-MARCO mAb-treated macrophages on osteosarcoma cells. Results: It was demonstrated that anti-MARCO mAb can drive macrophages toward classically activated macrophage (M1) polarization. Anti-MARCO mAb promoted the secretion of pro-inflammatory factors by macrophages, including tumor necrosis factor-alpha (TNF-α), interleukin-1beta, interleukin-6 and interleukin-23. Studies on in vitro co-culture models have revealed that macrophages treated with anti-MARCO mAb can suppress the growth and migration of osteosarcoma cells, induce cell apoptosis, and inhibit cell cycle progression of osteosarcoma cells through M1 polarization of macrophages in vitro. Conclusion: Anti-MARCO mAb treatment exerts anti-osteosarcoma effects by affecting macrophage polarization toward M1 macrophages, offering a potential new therapeutic approach for treating osteosarcoma. [ABSTRACT FROM AUTHOR]

The Kaladawan iron deposit is located in the North Altyn Tagh and exhibits occurrences of iron ore bodies at the contact zone between Ordovician magmatic rocks (basalts, rhyolite, and granodiorite) and marble. However, controversy persists regarding the genetic classification and metallogenic mechanism of this deposit. Through a field investigation, single mineral in situ geochemical analysis, whole-rock geochemical analysis, and Fe isotope determination, the following conclusions are made: (1) Ti-(Ni/Cr) and (V/Ti)-Fe diagrams indicate that the magnetite from all studied rocks underwent hydrothermal metasomatism, while (Ni/(Cr + Mn))-(Ti + V) and (Ca + Al + Mn)-(Ti + V) diagrams suggest a skarn origin for these magnetites. Therefore, it can be inferred that the Kaladawan iron deposit is skarn-type. (2) The iron ore exhibits similar rare-earth-element characteristics to the altered basalt. Additionally, the altered basalts (δ56Fe = 0.024~0.100‰) are more enriched in light Fe isotopes than the unaltered basalts (δ56Fe = 0.129~0.197‰) at the same location, indicating that the ore-forming materials of the Kaladawan iron ore are mainly derived from basaltic rocks. (3) According to the law of mass conservation and the intermediate Fe isotopic composition of the iron ore between the granodiorite and basalt, the hydrothermal fluid for the formation of iron ores was inferred to be derived from the late intrusive granodiorite. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer, which is highly aggressive and incurable. Here, we proposed an ultrasound activatable bromodomain-containing protein 4 (BRD4) proteolysis targeting chimera (PROTAC) release strategy for the first time for precisely controlled protein degradation in preclinical TNBC model. Through combination of PROTAC and ultrasound-targeted microbubble destruction (UTMD) technology, the present strategy also aims to concurrently solve the major limitations of poor loading capacity of microbubbles and undesirable targeting and membrane permeability of PROTAC. PROTAC (ARV-825)-encapsulated microbubbles, ARV-MBs, were developed for the efficacious treatment of TNBC in vitro and in vivo. The microbubbles we synthesized showed ultrasound-responsive drug release ability, which could effectively promote the penetration of PROTAC into tumor site and tumor cell. Under ultrasound, ARV-MBs could play an effective antitumor effect by potentiating the ubiquitination and degradation of BRD4 in tumor. The current study may provide a new idea for promoting clinical translation of drug-loaded microbubbles and PROTAC, and offer a new efficacious therapeutic modality for TNBC., Competing Interests: Competing interests: The authors declare that they have no competing interests., (Copyright © 2024 Hongye He et al.)

Glycosylation is the most structurally diverse form of post-translational modification (PTM) of proteins that affects a myriad of cellular processes. As a pivotal regulator of protein homeostasis, glycosylation notably impacts the function of proteins, spanning from protein localization and stability to protein-protein interactions. Aberrant glycosylation is a hallmark of cancer, and extensive studies have revealed the multifaceted roles of glycosylation in tumor growth, migration, invasion and immune escape Over the past decade, glycosylation has emerged as an immune regulator in the tumor microenvironment (TME). Here, we summarize the intricate interplay between glycosylation and the immune system documented in recent literature, which orchestrates the regulation of the tumor immune response through endogenous lectins, immune checkpoints and the extracellular matrix (ECM) in the TME. In addition, we discuss the latest progress in glycan-based cancer immunotherapy. This review provides a basic understanding of glycosylation in the tumor immune response and a theoretical framework for tumor immunotherapy.

As a pivotal subfield within the domain of time series forecasting, runoff forecasting plays a crucial role in water resource management and scheduling. Recent advancements in the application of artificial neural networks (ANNs) and attention mechanisms have markedly enhanced the accuracy of runoff forecasting models. This article introduces an innovative hybrid model, ResTCN-DAM, which synergizes the strengths of deep residual network (ResNet), temporal convolutional networks (TCNs), and dual attention mechanisms (DAMs). The proposed ResTCN-DAM is designed to leverage the unique attributes of these three modules: TCN has outstanding capability to process time series data in parallel. By combining with modified ResNet, multiple TCN layers can be densely stacked to capture more hidden information in the temporal dimension. DAM module adeptly captures the interdependencies within both temporal and feature dimensions, adeptly accentuating relevant time steps/features while diminishing less significant ones with minimal computational cost. Furthermore, the snapshot ensemble method is able to obtain the effect of training multiple models through one single training process, which ensures the accuracy and robustness of the forecasts. The deep integration and collaborative cooperation of these modules comprehensively enhance the model's forecasting capability from various perspectives. Ablation studies conducted validate the efficacy of each module, and through multiple sets of comparative experiments, it is shown that the proposed ResTCN-DAM has exceptional and consistent performance across varying lead times. We also employ visualization techniques to display heatmaps of the model's weights, thereby enhancing the interpretability of the model. When compared with the prevailing neural network-based runoff forecasting models, ResTCN-DAM exhibits state-of-the-art accuracy, temporal robustness, and interpretability, positioning it at the forefront of contemporary research.