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A new analytical method for rapid screening of influenza virus neuraminidase inhibitors was established. The method is based on the principle that, given a certain amount of neuraminidase, the sample and the neuraminidase act in the microplate for a period of time, and the active neuraminidase that is not inhibited by the sample can generate a fluorescence value at a specific wavelength after binding to the substrate, and the rate of inhibition of neuraminidase by the sample can be calculated based on the actual detected fluorescence value. This newly developed method was used to screen and evaluate the in vitro anti-neuraminidase activity of 39 high-purity compounds contained in three traditional Chinese herbal medicines, and finally 25 compounds with strong activity were obtained. The newly established neuraminidase inhibitor analytical method has these advantages of practicality, rapidity, high sensitivity and low cost, and has a good value for promotion and application. This article newly establishes a rapid, sensitive, simple and practical screening method for influenza virus neuraminidase inhibitors, which is a great complement to the existing methods and has a good promotion and application value.

Video stabilization refers to the problem of transforming a shaky video into a visually pleasing one. The question of how to strike a good trade-off between visual quality and computational speed has remained one of the open challenges in video stabilization. Inspired by the analogy between wobbly frames and jigsaw puzzles, we propose an iterative optimization-based learning approach using synthetic datasets for video stabilization, which consists of two interacting submodules: motion trajectory smoothing and full-frame outpainting. First, we develop a two-level (coarse-to-fine) stabilizing algorithm based on the probabilistic flow field. The confidence map associated with the estimated optical flow is exploited to guide the search for shared regions through backpropagation. Second, we take a divide-and-conquer approach and propose a novel multiframe fusion strategy to render full-frame stabilized views. An important new insight brought about by our iterative optimization approach is that the target video can be interpreted as the fixed point of nonlinear mapping for video stabilization. We formulate video stabilization as a problem of minimizing the amount of jerkiness in motion trajectories, which guarantees convergence with the help of fixed-point theory. Extensive experimental results are reported to demonstrate the superiority of the proposed approach in terms of computational speed and visual quality. The code will be available on GitHub., Comment: Accepted by ICCV2023

We introduce the notion of point affiliation into feature upsampling. By abstracting a feature map into non-overlapped semantic clusters formed by points of identical semantic meaning, feature upsampling can be viewed as point affiliation -- designating a semantic cluster for each upsampled point. In the framework of kernel-based dynamic upsampling, we show that an upsampled point can resort to its low-res decoder neighbors and high-res encoder point to reason the affiliation, conditioned on the mutual similarity between them. We therefore present a generic formulation for generating similarity-aware upsampling kernels and prove that such kernels encourage not only semantic smoothness but also boundary sharpness. This formulation constitutes a novel, lightweight, and universal upsampling solution, Similarity-Aware Point Affiliation (SAPA). We show its working mechanism via our preliminary designs with window-shape kernel. After probing the limitations of the designs on object detection, we reveal additional insights for upsampling, leading to SAPA with the dynamic kernel shape. Extensive experiments demonstrate that SAPA outperforms prior upsamplers and invites consistent performance improvements on a number of dense prediction tasks, including semantic segmentation, object detection, instance segmentation, panoptic segmentation, image matting, and depth estimation. Code is made available at: https://github.com/tiny-smart/sapa, 17 pages. Extended version of NeurIPS 2022 paper "SAPA: Similarity-Aware Point Affiliation for Feature Upsampling" at arXiv:2209.12866v1. arXiv admin note: text overlap with arXiv:2209.12866

Here we present a new lake sedimentary dataset from the Heihe River basin in the middle part of the Hexi Corridor, NW China, reconstructing the lake evolution history since the mid Holocene (MH).

Xin Deng,1,* Xin Zhong,1,* Bin Nie,2 Ruochen Wang,1 Hao Lu,1 Lei Ge,1 Juying Qian,1 Jianying Ma,1 Junbo Ge1 1Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, National Clinical Research Center for Interventional Medicine, Shanghai, People’s Republic of China; 2The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Junbo Ge; Jianying Ma, Email jbge@zs-hospital.sh.cn; ma.jianying@zs-hospital.sh.cnBackground: The septal collateral channel (CC) is the preferred channel in retrograde percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). However, reports on the utilization of the ipsilateral septal CC are limited.Objective: To evaluate the feasibility and safety of the ipsilateral septal CC in retrograde CTO PCI.Methods: Twenty-five patients with successful wire CC tracking via the ipsilateral septal CC in retrograde CTO PCI were retrospectively analyzed. All procedures were performed by experienced CTO operators. Procedures were divided into the left descending coronary artery (LAD)-septal-LAD group and the LAD-septal-left circumflex coronary artery (LCX) group. Procedural complications and in-hospital outcomes were ascertained.Results: Both groups were similar with respect to risk factors and angiographic characteristics of the CTO, except for the collateral tortuosity (86.7% vs 20%, p=0.002). The success rate of microcatheter CC tracking was 96%. Both technical success and procedural success rates were 92%. Procedural complications were found in one case (septal perforation, 4%), which happened in the LAD-septal-LAD group (p=0.250). One postoperative adverse event (Q-wave myocardial infarction, 4%) was observed before discharge.Conclusion: The retrograde approach via the ipsilateral septal CC was feasible, with high success rates and acceptable complications, in the hands of experienced operators.Keywords: percutaneous coronary interventions, chronic total occlusions, ipsilateral septal collateral, left coronary artery

Remote photoplethysmography (rPPG) is an important technique for perceiving human vital signs, which has received extensive attention. For a long time, researchers have focused on supervised methods that rely on large amounts of labeled data. These methods are limited by the requirement for large amounts of data and the difficulty of acquiring ground truth physiological signals. To address these issues, several self-supervised methods based on contrastive learning have been proposed. However, they focus on the contrastive learning between samples, which neglect the inherent self-similar prior in physiological signals and seem to have a limited ability to cope with noisy. In this paper, a linear self-supervised reconstruction task was designed for extracting the inherent self-similar prior in physiological signals. Besides, a specific noise-insensitive strategy was explored for reducing the interference of motion and illumination. The proposed framework in this paper, namely rPPG-MAE, demonstrates excellent performance even on the challenging VIPL-HR dataset. We also evaluate the proposed method on two public datasets, namely PURE and UBFC-rPPG. The results show that our method not only outperforms existing self-supervised methods but also exceeds the state-of-the-art (SOTA) supervised methods. One important observation is that the quality of the dataset seems more important than the size in self-supervised pre-training of rPPG. The source code is released at https://github.com/linuxsino/rPPG-MAE.

In order to search for high energy density materials, various 4,8-dihydrodifurazano[3,4-b,e]pyrazine based energetic materials were designed. Density functional theory was employed to investigate the relationships between the structures and properties. The calculated results indicated that the properties of these designed compounds were influenced by the energetic groups and heterocyclic substituents. The -N3 energetic group was found to be the most effective substituent to improve the heats of formation of the designed compounds while the tetrazole ring/-C(NO2)3 group contributed much to the values of detonation properties. The analysis of bond orders and bond dissociation energies showed that the addition of -NHNH2, -NHNO2, -CH(NO2)3 and -C(NO2)3 groups would decrease the bond dissociation energies remarkably. Compounds A8, B8, C8, D8, E8, and F8 were finally screened as the potential candidates for high energy density materials since these compounds possess excellent detonation properties and acceptable thermal stabilities. Additionally, the electronic structures of the screened compounds were calculated.

Manganese dioxide nanoparticles (MnO2-NPs) have a wide range of applications in biomedicine. Given this widespread usage, it is worth noting that MnO2-NPs are definitely toxic, especially to the brain. However, the damage caused by MnO2-NPs to the choroid plexus (CP) and to the brain after crossing CP epithelial cells has not been elucidated. Therefore, this study aims to investigate these effects and elucidate potential underlying mechanisms through transcriptomics analysis. To achieve this objective, eighteen SD rats were randomly divided into three groups: the control group (control), low-dose exposure group (low-dose) and high-dose exposure group (high-dose). Animals in the two treated groups were administered with two concentrations of MnO2-NPs (200 mg kg−1 BW and 400 mg kg−1 BW) using a noninvasive intratracheal injection method once a week for three months. Finally, the neural behavior of all the animals was tested using a hot plate tester, open-field test and Y-type electric maze. The morphological characteristics of the CP and hippocampus were observed by H&E stain, and the transcriptome of CP tissues was analysed by transcriptome sequencing. The representative differentially expressed genes were quantified by qRT-PCR. We found that treatment with MnO2-NPs could induce learning capacity and memory faculty decline and destroy the structure of hippocampal and CP cells in rats. High doses of MnO2-NPs had a more obvious destructive capacity. For transcriptomic analysis, we found that there were significant differences in the numbers and types of differential genes in CP between the low- and high-dose groups compared to the control. Through GO terms and KEGG analysis, high-dose MnO2-NPs significantly affected the expression of transporters, ion channel proteins, and ribosomal proteins. There were 17 common differentially expressed genes. Most of them were transporter and binding genes on the cell membrane, and some of them had kinase activity. Three genes, Brinp, Synpr and Crmp1, were selected for qRT-PCR to confirm their expression differences among the three groups. In conclusion, high-dose MnO2-NPs exposure induced abnormal neurobehaviour, impaired memory function, destroyed the structure of the CP and changed its transcriptome in rats. The most significant DEGs in the CP were within the transport system.

Class-agnostic counting (CAC) aims to count objects of interest from a query image given few exemplars. This task is typically addressed by extracting the features of query image and exemplars respectively with (un)shared feature extractors and by matching their feature similarity, leading to an extract-\textit{then}-match paradigm. In this work, we show that CAC can be simplified in an extract-\textit{and}-match manner, particularly using a pretrained and plain vision transformer (ViT) where feature extraction and similarity matching are executed simultaneously within the self-attention. We reveal the rationale of such simplification from a decoupled view of the self-attention and point out that the simplification is only made possible if the query and exemplar tokens are concatenated as input. The resulting model, termed CACViT, simplifies the CAC pipeline and unifies the feature spaces between the query image and exemplars. In addition, we find CACViT naturally encodes background information within self-attention, which helps reduce background disturbance. Further, to compensate the loss of the scale and the order-of-magnitude information due to resizing and normalization in ViT, we present two effective strategies for scale and magnitude embedding. Extensive experiments on the FSC147 and the CARPK datasets show that CACViT significantly outperforms state-of-the-art CAC approaches in both effectiveness (23.60% error reduction) and generalization, which suggests CACViT provides a concise and strong baseline for CAC. Code will be available.

Because of the influence of climate change and human activities, an in-depth analysis of land use/cover change (LUCC) and its drivers in Nepal is important for local community forestry management and sustainable development. This paper analyzed the direction, magnitude, and rate of LUCCs and their spatial aggregation, as well as landscape fragmentation in Nepal, from 1995 to 2020 using the ESA/CCI (European Space Agency Climate Change Initiative) dataset. A total of 10 factors including population, socioeconomic development, climate factors, and forest management factors were selected to determine the dominant driving factors affecting LUCC in Nepal by Principal component analysis (PCA) and linear regression analysis. Our study showed that climate change, human activities, and forest management (e.g., community forestry) all influenced LUCC. In Nepal, land use/cover shifted among forest, shrub, grassland, and cropland from 1995 to 2020, mainly from forest to cropland. The most significant LUCC in recent decades has been caused by the expansion of cropland and urbanization. The area of coniferous and broadleaf forests decreased from 1995 to 2001 due to deforestation and forest degradation, and recovered gradually after 2001, which was attributed to the successful practice of community forestry in Nepal. Accelerated urbanization was also found in Nepal, and the significant expansion of construction land came mainly came from cropland. Land fragmentation in Nepal was severe and exhibited spatial aggregation characteristics. Human activities played a greater role in LUCC in Nepal than climate factors. The community forestry, GDP growth, and precipitation were positive driving factors for increases in forest area, while the development of the services sector and rising temperature were negative driving factors.

Colon cancer is one of the most common malignant tumors at present. It was relatively common in western developed countries, and has gradually become one of the common causes of cancer death in developing countries in recent years. With the development of imaging, endoscopic technology and early screening, the mortality rate of colon cancer has decreased significantly, but the prognosis of patients with colon cancer is still poor due to certain recurrence and metastasis risks. The latest research shows that the anoikis gene also has a certain regulatory role in colon cancer. Therefore, this paper studies the screening of related genes and their interaction with immune cells and drugs based on bioinformatics.

The existence of bladder cancer stem cells (BCSC) has been suggested to underlie bladder tumor initiation and recurrence. Sonic Hedgehog (SHH) signaling has been implicated in promoting cancer stem cell (CSC) self-renewal and is activated in bladder cancer, but its impact on BCSC maintenance is unclear. In this study, we generated a mAb (BCMab1) against CD44+ human bladder cancer cells that recognizes aberrantly glycosylated integrin α3β1. The combination of BCMab1 with an anti-CD44 antibody identified a BCMab1+CD44+ cell subpopulation as BCSCs with stem cell–like properties. Gene expression analysis revealed that the hedgehog pathway was activated in the BCMab1+CD44+ subpopulation and was required for BCSC self-renewal. Furthermore, the glycotransferase GALNT1 was highly expressed in BCMab1+CD44+ cells and correlated with clinicopathologic features of bladder cancers. Mechanistically, GALNT1 mediated O-linked glycosylation of SHH to promote its activation, which was essential for the self-renewal maintenance of BCSCs and bladder tumorigenesis. Finally, intravesical instillation of GALNT1 siRNA and the SHH inhibitor cyclopamine exerted potent antitumor activity against bladder tumor growth. Taken together, our findings identify a BCSC subpopulation in human bladder tumors that appears to be responsive to the inhibition of GALNT1 and SHH signaling, and thus highlight a potential strategy for preventing the rapid recurrence typical in patients with bladder cancer. Cancer Res; 76(5); 1273–83. ©2015 AACR.

Supplementary Figures 1-3 and Supplementary Table 1. Supplementary Figure 1. GALNT1-mediated SHH processing is related to Gli1 expression in BCSCs. Supplementary Figure 2. O-linked glycosylation sites of SHH were predicted by NetOGlyc 3.1 Server tool. Supplementary Figure 3. SHH and its mutants were detected by ELLA. Supplementary Table 1. Primer oligonucleotides for qPCR

Supplementary Figure Legends

Supplementary Figure 3 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Methods and Materials, Figure Legends 1-7 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 7 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

High expression of Notch-1 and Jagged-1 mRNA correlates with poor prognosis in breast cancer. Elucidating the cross-talk between Notch and other major breast cancer pathways is necessary to determine which patients may benefit from Notch inhibitors, which agents should be combined with them, and which biomarkers indicate Notch activity in vivo. We explored expression of Notch receptors and ligands in clinical specimens, as well as activity, regulation, and effectors of Notch signaling using cell lines and xenografts. Ductal and lobular carcinomas commonly expressed Notch-1, Notch-4, and Jagged-1 at variable levels. However, in breast cancer cell lines, Notch-induced transcriptional activity did not correlate with Notch receptor levels and was highest in estrogen receptor α–negative (ERα−), Her2/Neu nonoverexpressing cells. In ERα+ cells, estradiol inhibited Notch activity and Notch-1IC nuclear levels and affected Notch-1 cellular distribution. Tamoxifen and raloxifene blocked this effect, reactivating Notch. Notch-1 induced Notch-4. Notch-4 expression in clinical specimens correlated with proliferation (Ki67). In MDA-MB231 (ERα−) cells, Notch-1 knockdown or γ-secretase inhibition decreased cyclins A and B1, causing G2 arrest, p53-independent induction of NOXA, and death. In T47D:A18 (ERα+) cells, the same targets were affected, and Notch inhibition potentiated the effects of tamoxifen. In vivo, γ-secretase inhibitor treatment arrested the growth of MDA-MB231 tumors and, in combination with tamoxifen, caused regression of T47D:A18 tumors. Our data indicate that combinations of antiestrogens and Notch inhibitors may be effective in ERα+ breast cancers and that Notch signaling is a potential therapeutic target in ERα− breast cancers. [Cancer Res 2008;68(13):5226–35]

Supplementary Table 1 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 2 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 4 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 6 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 5 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Supplementary Figure 1 from Cross-talk between Notch and the Estrogen Receptor in Breast Cancer Suggests Novel Therapeutic Approaches

Point cloud segmentation is a fundamental task in 3D vision that serves a wide range of applications. Although great progresses have been made these years, its practical usability is still limited by the availability of training data. Existing approaches cannot make full use of multiple datasets on hand due to the label mismatch among different datasets. In this paper, we propose a principled approach that supports learning from heterogeneous datasets with different label sets. Our idea is to utilize a pre-trained language model to embed discrete labels to a continuous latent space with the help of their label names. This unifies all labels of different datasets, so that joint training is doable. Meanwhile, classifying points in the continuous 3D space by their vocabulary tokens significantly increase the generalization ability of the model in comparison with existing approaches that have fixed decoder architecture. Besides, we also integrate prompt learning in our framework to alleviate data shifts among different data sources. Extensive experiments demonstrate that our model outperforms the state-of-the-art by a large margin., 11 pages, 5 figures

BackgroundDiversion colitis (DC) is nonspecific inflammation of the distal intestinal mucosa following disruption of colonic continuity with colonic dysfunction. The colonscopic score is a good tool for differentiating the severity of patients with DC. At present, no studies have analyzed the pathogenesis of DC from the perspective of the diversity and and differences of intestinal flora.MethodsRetrospective study: Clinical information were collected from patients with low rectal cancer admitted to the Department of Anorectal Surgery, Changzheng Hospital, from April 2017 to April 2019. These patients underwent laparoscopic low anterior resection (LAR) combined with terminal ileum enterostomy (dual-chamber). We used chi-square test to comparethe clinical baseline information, clinical symptoms, and colonscopic characteristics between different severity of DC. Propsective oberservational study: We recruited 40 patients with laparoscopic anterior low resection combined with terminal ileum enterostomy and they were further classified into mild group and severe group according to the scores of colonscopic examinations for DC. 16s-rDNA sequencing was carried out to analyze the diversity and and differences of intestinal flora in the intestinal lavage fluid of the two groups.ResultsIn retrospective study, we found that age, BMI, history of diabetes, and symptoms associated with the stoma state were the independent risk factors that affect DC severity (PP<0.05), which was consistent with our results of differentiating the severity of DC under endoscopy; In propsective oberservational study, 40 patients with low rectal cancer recruited by sample size calculation, 23 were in the mild group and 17 in the severe group. The results of 16s-rDNA sequencing showed that intestinal flora with high enrichment values primarily consisted of Bifidobacteriales and Prevotella in mild group, whereas that in the severe group consisted of Providencia and Dorea. The functional predictions on such two types of intestinal flora were mainly focused on lipid synthesis, glycan synthesis, metabolism, and amino acid metabolism pathways.ConclusionAfter ileostomy closure surgery, a series of severe clinical symptoms might appear in DC patients. There are significant differences in local and systemic inflammatory responses, composition of intestinal flora between DC patients with different colonscopic scores, which provide a basis for the clinical interventional treatment for DC in patients with permanent stoma.

Remote photoplethysmography (rPPG) technology has drawn increasing attention in recent years. It can extract Blood Volume Pulse (BVP) from facial videos, making many applications like health monitoring and emotional analysis more accessible. However, as the BVP signal is easily affected by environmental changes, existing methods struggle to generalize well for unseen domains. In this paper, we systematically address the domain shift problem in the rPPG measurement task. We show that most domain generalization methods do not work well in this problem, as domain labels are ambiguous in complicated environmental changes. In light of this, we propose a domain-label-free approach called NEuron STructure modeling (NEST). NEST improves the generalization capacity by maximizing the coverage of feature space during training, which reduces the chance for under-optimized feature activation during inference. Besides, NEST can also enrich and enhance domain invariant features across multi-domain. We create and benchmark a large-scale domain generalization protocol for the rPPG measurement task. Extensive experiments show that our approach outperforms the state-of-the-art methods on both cross-dataset and intra-dataset settings., Accepted by CVPR2023

Steatorrhea, a sign of severe pancreatic exocrine insufficiency (PEI), is related to consequences caused by pancreatitis. This study aimed to identify predictors and to construct a nomogram for steatorrhea in idiopathic chronic pancreatitis (ICP).ICP patients admitted to our hospital from January 2000 to December 2013 were enrolled in this retrospective-prospective cohort study and randomly assigned to the training and validation cohorts. The cumulative rate of steatorrhea was calculated. A Cox proportional hazard regression model was used to identify predictors for steatorrhea and construct the nomogram. Internal and external validation of the nomogram was then performed.There were 1633 ICP patients enrolled, with a median follow-up duration of 9.8 years and 20.8% (339/1633) of patients developed steatorrhea following onset of ICP. Steatorrhea was observed in 93, 115, and 133 patients at 1, 3, and 5 years following diagnosis of CP, with a cumulative rate of 6.5% (95% confidence interval [CI] 5.1%-7.9%), 8.0% (95% CI 6.2%-9.8%), and 9.3% (95% CI 6.6%-12.0%), respectively. Male sex (hazard ratio [HR] 2.479, P 0.001), diabetes mellitus at/before diagnosis of ICP (HR 2.274, P = 0.003), and aged less than 18 years at onset of ICP (HR 0.095, P 0.001) were identified risk factors for steatorrhea. Initial manifestations were associated with development of steatorrhea. The nomogram was proven to have good concordance indexes.We identified predictors and developed a nomogram for predicting steatorrhea in ICP. It was recommended that high-risk populations be followed up closely, which might contribute to the early diagnosis and treatment of PEI.

Photoexcited organic dye-catalyzed synthesis of sulfenyl amides through a direct sulfenylation of C(sp3)–H bonds using thiosulfonates as a sulfur source at room temperature.

Automatic image cropping algorithms aim to recompose images like human-being photographers by generating the cropping boxes with improved composition quality. Cropping box regression approaches learn the beauty of composition from annotated cropping boxes. However, the bias of annotations leads to quasi-trivial recomposing results, which has an obvious tendency to the average location of training samples. The crux of this predicament is that the task is naively treated as a box regression problem, where rare samples might be dominated by normal samples, and the composition patterns of rare samples are not well exploited. Observing that similar composition patterns tend to be shared by the cropping boundaries annotated nearly, we argue to find the beauty of composition from the rare samples by clustering the samples with similar cropping boundary annotations, ie, similar composition patterns. We propose a novel Contrastive Composition Clustering (C2C) to regularize the composition features by contrasting dynamically established similar and dissimilar pairs. In this way, common composition patterns of multiple images can be better summarized, which especially benefits the rare samples and endows our model with better generalizability to render nontrivial results. Extensive experimental results show the superiority of our model compared with prior arts. We also illustrate the philosophy of our design with an interesting analytical visualization., Accepted to AAAI 2023 (Oral); 9 pages, 6 figures

The NF-κB signaling pathway is overactivated in tumor cells, and the activation of the NF-κB signaling pathway releases a large number of inflammatory factors, which enhance tumor immunosuppression and promote tumor metastasis. The cytochrome P450 (CYP450) system consists of important metabolic enzymes present in different tissues and progressive tumors, which may lead to changes in the pharmacological action of drugs in inflammatory diseases such as tumors. In this study, the anticancer effect of tetrahydrocurcumin (THC), an active metabolite of curcumin, on breast cancer cells and the underlying mechanism were investigated. Result showed that THC selectively inhibited proliferation and triggered apoptosis in breast cancer cells in a concentration- and time-dependent manner. Moreover, THC-induced cell apoptosis via a mitochondria-mediated pathway, as indicated by the upregulated ratio of Bax/Bcl-2 and reactive oxygen species (ROS) induction. In addition, THC could affect the CYP450 enzyme metabolic pathway and inhibit the expression of CYP1A1 and activation of the NF-κB pathway, thereby inhibiting the migration and invasion of breast cancer cells. Furthermore, after overexpression of CYP1A1, the inhibitory effects of THC on the proliferation, metastasis, and induction of apoptosis in breast cancer cells were weakened. The knockdown of CYP1A1 significantly enhanced the inhibitory effect of THC on the proliferation, metastasis, and apoptosis induction of breast cancer cells. Notably, THC exhibited a significant tumor growth inhibition and anti-pulmonary metastasis effect in a tumor mouse model of MCF-7 and 4T1 cells by regulating the tumor immunosuppressive microenvironment. Collectively, these results showed that TH could effectively trigger apoptosis and inhibit the migration of breast cancer cells via the CYP1A1/NF-κB signaling pathway, indicating that THC serves as a potential candidate drug for the treatment of breast cancer.

Pkhd1l1 is predicted to encode a very large type-I transmembrane protein, but its function has largely remained obscure. Recently, it was shown that Pkhdl1l1 is a component of the coat that decorates stereocilia of outer hair cells in the mouse ear. Consistent with this localization, conditional deletion of Pkhd1l1 specifically from hair cells, was associated with progressive hearing loss. In the zebrafish, there are two paralogous pkhd1l1 genes - pkhd1l1α and pkhd1l1β. Using CRISPR-Cas9 mediated gene editing, we generated loss-of-function alleles for both and show that the double mutants exhibit nonsense-mediated-decay (NMD) of the RNAs. With behavioural assays, we demonstrate that zebrafish pkhd1l1 genes also regulate hearing; however, in contrast to Pkhd1l1 mutant mice, which develop progressive hearing loss, the double mutant zebrafish exhibited statistically significant hearing loss even from the larval stage. Our data highlight a conserved function of Pkhd1l1 in hearing and based on these findings from animal models, we postulate that PKHD1L1 could be a candidate gene for sensorineural hearing loss (SNHL) in humans.