Allergic fungal rhinosinusitis linked to other hyper-IgE syndromes through defective TH17 responses.

BACKGROUND: In a gene expression analysis comparing sinus mucosa samples from allergic fungal rhinosinusitis (AFRS) patients with samples from non-AFRS chronic rhinosinusitis with nasal polyp (CRSwNP) patients, the antimicrobial peptide (AMP) histatin 1 (HTN1) was found to be the most differentially downregulated gene in AFRS. OBJECTIVE: We sought to identify the molecular etiology of the downregulated expression of HTN1. METHODS: We used RT-PCR to compare the expression of AMPs and a fungistasis assay to evaluate the antifungal activity of sinus secretions. Using flow cytometry, we characterized the presence of TH17/TH22 cells and signal transducer and activator of transcription (STAT) signaling from AFRS patients, non-AFRS CRSwNP patients, and healthy controls. RESULTS: We confirmed decreased expression of AMPs in AFRS sinus mucosa with concordant decrease in antifungal activity in sinus secretions. IL-22 and IL-22-producing T cells were deficient within sinus mucosa of AFRS patients. In vitro studies demonstrated a defect in IL-6/STAT3 signaling critical for TH17/TH22 differentiation. Epithelial cells from AFRS patients could express AMPs when stimulated with exogenous IL-22/IL-17 and circulating TH17 cell abundance was normal. CONCLUSIONS: Similar to other hyper-IgE syndromes, but distinct from CRSwNP, AFRS patients express a defect in STAT3 activation limited to IL-6-dependent STAT3 phosphorylation that is critical for TH17/TH22 differentiation. This defect leads to a local deficiency of IL-17/IL-22 cytokines and deficient AMP expression within diseased sinus mucosa of AFRS patients. Our findings support evaluation of therapeutic approaches that enhance airway AMP production in AFRS.

PrivFR: Privacy-Enhanced Federated Recommendation With Shared Hash Embedding.

Federated recommender systems (FRSs), with their improved privacy-preserving advantages to jointly train recommendation models from numerous devices while keeping user data distributed, have been widely explored in modern recommender systems (RSs). However, conventional FRSs require transmitting the entire model between the server and clients, which brings a huge carbon footprint for cost-conscious cross-device learning tasks. While several efforts have been dedicated to improving the efficiency of FRSs, it's suboptimal to treat the whole model as the objective of compact design. Besides, current research fails to handle the out-of-vocabulary (OOV) issue in real-world FRSs, where the items only occasionally appear in the testing phase but were not observed during the training process, which is another practical challenge and has not been well studied yet. To this end, we propose a privacy-enhanced federated recommendation framework with shared hash embedding, PrivFR, in cross-device settings, which is an efficient representation mechanism specialized for the embedding parameters without compromising the model capability. Specifically, it represents items in a resource-efficient way by delicately utilizing shared hash embedding and multiple hash functions. As such, it just maintains a small shared pool of hash embedding in local clients, rather than fitting all embedding vectors for each item, which can exactly achieve the dual advantages of conserving resources and handling the OOV issue. What's more, we prove that this mechanism can protect the data privacy of local clients from a theoretical perspective. Extensive experiments show that our method not only effectively reduces storage and communication overheads, but also outperforms state-of-the-art FRSs.

Combating antimicrobial resistance: the silent war.

Once hailed as miraculous solutions, antibiotics no longer hold that status. The excessive use of antibiotics across human healthcare, agriculture, and animal husbandry has given rise to a broad array of multidrug-resistant (MDR) pathogens, posing formidable treatment challenges. Antimicrobial resistance (AMR) has evolved into a pressing global health crisis, linked to elevated mortality rates in the modern medical era. Additionally, the absence of effective antibiotics introduces substantial risks to medical and surgical procedures. The dwindling interest of pharmaceutical industries in developing new antibiotics against MDR pathogens has aggravated the scarcity issue, resulting in an exceedingly limited pipeline of new antibiotics. Given these circumstances, the imperative to devise novel strategies to combat perilous MDR pathogens has become paramount. Contemporary research has unveiled several promising avenues for addressing this challenge. The article provides a comprehensive overview of these innovative therapeutic approaches, highlighting their mechanisms of action, benefits, and drawbacks.

Sources and transport of CO2 in the karst system of Jiguan Cave, Funiu Mountains, China.

Conveyance and modification of carbon-isotope signals within the karst system remain difficult to constrain, due to the complexity of interactions between multiple components, including precipitation, bedrock, soil, atmosphere, and biota. Cave monitoring is thus critical to understanding both their transport in the karst system and dependence on local hydroclimatic conditions. Jiguan Cave, located in Funiu Mountain in central China, is representative of karst tourist caves with relatively thin epikarst zone. We conducted a comprehensive monitoring program of cave climate from 2018 to 2021 and measured δ13C during 2021 in monthly and heavy-rainfall samples of soil CO2, cave CO2, cave water (drip water and underground river), and underground river outlet. Our results demonstrate synchronous variations between CO2 concentration and δ13CCO2 in both soil and cave air on seasonal time scales. Cave pCO2 and carbon-isotope composition further exhibited a high sensitivity to human respiration with fluctuations of ~2000-3000 ppm within 4 days during the cave closure period in July 2021 without tourists. 13C-depleted isotopic signal of cave air in summer is the mixture of human respiration and soil CO2 which varies as a function of regional hydrological conditions of the summer monsoon during the rainy season with high temperatures and humidity. However, respired CO2 from the overlying soil was expected to be the only principal source of the cave CO2 when the anthropogenic CO2 source was removed. The high seasonal amplitude of cave air δ13CCO2 reflects ventilation dynamics, which leads to a prominent contribution from the external atmosphere during winter. Intriguingly, although the δ13C signal reflects complex vertical processes in the vertical karst profile, a heavy summer rainfall event was related to anomalously high δ13C values of cave water that can be utilized to interpret rainfall intensity and regional hydroclimate.

RN486, a Bruton's Tyrosine Kinase inhibitor, antagonizes multidrug resistance in ABCG2-overexpressing cancer cells.

Background and Objectives: Overcoming ATP-binding cassette subfamily G member 2 (ABCG2)-mediated multidrug resistance (MDR) has attracted the attention of scientists because one of the critical factors resulting in MDR in cancer is the overexpression of ABCG2. RN486, a Bruton's Tyrosine Kinase (BTK) inhibitor, was discovered to potentially reverse ABCB1-mediated MDR. However, there is still uncertainty about whether RN486 has a reversal off-target impact on ABCG2-mediated MDR. Methods: MTT assay was used to detect the reversal effect of RN486 on ABCG2-overexpressing cancer cells. The ABCG2 expression level and subcellular localization were examined by Western blotting and immunofluorescence. Drug accumulation and eflux assay and ATPase assay were performed to analyze the ABCG2 transporter function and ATPase activity. Molecular modeling predicted the binding between RN486 and ABCG2 protein. Results: Non-toxic concentrations of RN486 remarkably increased the sensitivity of ABCG2-overexpressing cancer cells to conventional anticancer drugs mitoxantrone and topotecan. The reversal mechanistic studies showed that RN486 elevated the drug accumulation because of reducing the eflux of ABCG2 substrate drug in ABCG2-overexpressing cancer cells. In addition, the inhibitory efect of RN486 on ABCG2-associated ATPase activity was also verified. Molecular docking study implied a strong binding afinity between RN486 and ABCG2 transporter. Meanwhile, the ABCG2 subcellular localization was not altered by the treatment of RN486, but the expression level of ABCG2 was down-regulated. Conclusions: Our studies propose that RN486 can antagonize ABCG2-mediated MDR in cancer cells via down-regulating the expression level of ABCG2 protein, reducing ATPase activity of ABCG2 transporter, and inhibiting the transporting function. RN486 could be potentially used in conjunction with chemotherapy to alleviate MDR mediated by ABCG2 in cancer.

SASAN: Shape-Adaptive Set Abstraction Network for Point-Voxel 3D Object Detection.

Point-voxel 3D object detectors have achieved impressive performance in complex traffic scenes. However, they utilize the 3D sparse convolution (spconv) layers with fixed receptive fields, such as voxel-based detectors, and inherit the fixed sphere radius from point-based methods for generating the features of keypoints, which make them weak in adaptively modeling various geometrical deformations and sizes of real objects. To tackle this issue, we propose a shape-adaptive set abstraction network (SASAN) for point-voxel 3D object detection. First, the proposal and offset generation module is adopted to learn the coordinates and confidences of 3D proposals and shape-adaptive offsets of the certain number of offset points for each voxel. Meanwhile, an extra offset supervision task is employed to guide the learning of shifting values of offset points, aiming at motivating the predicted offsets to preferably adapt to the various shapes of objects. Then, the shape-adaptive set abstraction module is proposed to extract multiscale keypoints features by grouping the neighboring offset points' features, as well as features learned from adjacent raw points and the 2-D bird-view map. Finally, the region of interest (RoI)-grid proposal refinement module is used to aggregate the keypoints features for further proposal refinement and confidence prediction. Extensive experiments on the competitive KITTI 3D detection benchmark demonstrate that the proposed SASAN gains superior performance as compared with state-of-the-art methods.