Xbp1 promotes odontoblastic differentiation through modulating mitochondrial homeostasis.

Odontoblast differentiation depends on the orderly recruitment of transcriptional factors (TFs) in the transcriptional regulatory network. The depletion of crucial TFs disturbs dynamic alteration of the chromatin landscape and gene expression profile, leading to developmental defects. Our previous studies have revealed that the basic leucine zipper (bZIP) TF family is crucial in odontoblastic differentiation, but the function of bZIP TF family member XBP1 is still unknown. Here, we showed the stage-specific expression patterns of the spliced form Xbp1s during tooth development. Elevated Xbp1 expression and nuclear translocation of XBP1S in mesenchymal stem cells (MSCs) were induced by differentiation medium in vitro. Diminution of Xbp1 expression impaired the odontogenic differentiation potential of MSCs. The further integration of ATAC-seq and RNA-seq identified Hspa9 as a direct downstream target, an essential mitochondrial chaperonin gene that modulated mitochondrial homeostasis. The amelioration of mitochondrial dysfunction rescued the impaired odontogenic differentiation potential of MSCs caused by the diminution of Xbp1. Furthermore, the overexpression of Hspa9 rescued Xbp1-deficient defects in odontoblastic differentiation. Our study illustrates the crucial role of Xbp1 in odontoblastic differentiation via modulating mitochondrial homeostasis and brings evidence to the therapy of mitochondrial diseases caused by genetic defects.

Performance of ATT and UDFF in the diagnosis of non-alcoholic fatty liver: An animal experiment.

Objective: To establish a Bama minipigs model with Non-Alcoholic Fatty Liver (NAFL) induced by a high-fat diet and investigate the application of attenuation coefficient (ATT) and ultrasound-derived fat fraction (UDFF) in the diagnosis of NAFL. Methods: Six-month-old male Bama minipigs were randomly divided into normal control and high-fat groups (n = 3 pigs per group), and fed with a control diet and high-fat diet for 32 weeks. Weight and body length were measured every four weeks, followed by quantitative ultrasound imaging (ATT and UDFF), blood biochemical markers, and liver biopsies on the same day. Using the Non-Alcoholic Fatty Liver Disease (NAFLD) Activity Score (NAS) as a reference, we analyzed the correlation between ATT, UDFF, and their score results. Results: Compared with the normal control group, the body weight, body mass index (BMI), and serum levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the High-fat group were significantly different at Week 12 (P < 0.05). Spearman correlation analysis showed that the ATT value was significantly correlated with NAS score (r = 0.76, P < 0.001), and the UDFF value was significantly correlated with NAS score (r = 0.80, P < 0.001). The optimal cut-off value of ATT and UDFF were 0.59 dB/cm/MHz and 5.5%, respectively. These values are optimal for diagnosis of NAFL in Bama minipig model. Conclusion: ATT and UDFF have a high correlation with steatosis, and can be used as a non-invasive method for early screening of hepatic steatosis, which can dynamically monitor the change of disease course.

Identification of Pancreatic Metastasis Cells and Cell Spheroids by the Organelle-Targeting Sensor Array.

Pancreatic cancer is a highly malignant and metastatic cancer. Pancreatic cancer can lead to liver metastases, gallbladder metastases, and duodenum metastases. The identification of pancreatic cancer cells is essential for the diagnosis of metastatic cancer and exploration of carcinoma in situ. Organelles play an important role in maintaining the function of cells, the various cells show significant differences in organelle microenvironment. Herein, six probes are synthesized for targeting mitochondria, lysosomes, cell membranes, endoplasmic reticulum, Golgi apparatus, and lipid droplets. The six fluorescent probes form an organelles-targeted sensor array (OT-SA) to image pancreatic metastatic cancer cells and cell spheroids. The homology of metastatic cancer cells brings the challenge for identification of these cells. The residual network (ResNet) model has been proven to automatically extract and select image features, which can figure out a subtle difference among similar samples. Hence, OT-SA is developed to identify pancreatic metastasis cells and cell spheroids in combination with ResNet analysis. The identification accuracy for the pancreatic metastasis cells (> 99%) and pancreatic metastasis cell spheroids (> 99%) in the test set is successfully achieved respectively. The organelles-targeting sensor array provides a method for the identification of pancreatic cancer metastasis in cells and cell spheroids.

Retinopathy as a predictive indicator for significant hepatic fibrosis according to T2DM status: A cross-sectional study based on the national health and nutrition examination survey data.

INTRODUCTION AND OBJECTIVES: Type 2 Diabetes Mellitus (T2DM), a prevalent metabolic disorder, often coexists with a range of complications, with retinopathy being particularly common. Recent studies have shed light on a potential connection between diabetic retinopathy (DR) and hepatic fibrosis, indicating a possible shared pathophysiological foundation in T2DM. This study investigates the correlation between retinopathy and hepatic fibrosis among individuals with T2DM, as well as evaluates the diagnostic value of DR for significant hepatic fibrosis. MATERIALS AND METHODS: Our cross-sectional analysis incorporated 5413 participants from the National Health and Nutrition Examination Survey (NHANES) 2005-2008. The Fibrosis-4 score (FIB-4) classified hepatic fibrosis into different grades (F0-F4), with significant hepatic fibrosis marked as F2 or higher. Retinopathy severity was determined using retinal imaging and categorized into four levels. The analysis of variance or Chi-square tests facilitated group comparisons. Additionally, the receiver operating characteristic (ROC) analysis appraised the predictive accuracy of retinopathy for significant hepatic fibrosis in the T2DM population. RESULTS: Among 5413 participants, the mean age was 59.56 ± 12.41, with 50.2% male. And 20.6% were diagnosed with T2DM. Hepatic fibrosis grading was positively associated with retinopathy severity (OR [odds ratio]: 1.521, 95%CI [confidence interval]: 1.152-2.008, P = 0.003) across the entire population. The association was amplified in the T2DM population according to Pearson's analysis results. The ROC curve demonstrated retinopathy's diagnostic capacity for significant hepatic fibrosis in the T2DM population (AUC [area under curve] = 0.72, 95%CI: 0.651-0.793, P < 0.001). CONCLUSIONS: Retinopathy could serve as an independent predictor of significant hepatic fibrosis in T2DM population. Ophthalmologists are advised to closely monitor T2DM patients with retinopathy.

Bright Nonblinking Photoluminescence with Blinking Lifetime from a Nanocavity-Coupled Quantum Dot.

Colloidal quantum dots (QDs) are excellent luminescent nanomaterials for many optoelectronic applications. However, photoluminescence blinking has limited their practical use. Coupling QDs to plasmonic nanostructures shows potential in suppressing blinking. However, the underlying mechanism remains unclear and debated, hampering the development of bright nonblinking dots. Here, by deterministically coupling a QD to a plasmonic nanocavity, we clarify the mechanism and demonstrate unprecedented single-QD brightness. In particular, we report for the first time that a blinking QD could obtain nonblinking photoluminescence with a blinking lifetime through coupling to the nanocavity. We show that the plasmon-enhanced radiative decay outcompetes the nonradiative Auger process, enabling similar quantum yields for charged and neutral excitons in the same dot. Meanwhile, we demonstrate a record photon detection rate of 17 MHz from a colloidal QD, indicating an experimental photon generation rate of more than 500 MHz. These findings pave the way for ultrabright nonblinking QDs, benefiting diverse QD-based applications.

A time-continuous land surface temperature (LST) data fusion approach based on deep learning with microwave remote sensing and high-density ground truth observations.

Land surface temperature (LST) is a crucial parameter in the circulation of water, exchange of land-atmosphere energy, and turbulence. Currently, most LST products rely heavily on thermal infrared remote sensing, which is susceptible to cloud and rain interference, leading to inferior temporal continuity. Microwave remote sensing has the advantage of being available "all-weather" due to strong penetration capability, which provides the possibility to simulate time-continuous LST data. In addition, the continuous increase in high-density station observations (>10,000 stations) provides reliable measured data for the remote sensing monitoring of LST in China. This study aims to adopt the "Earth big data" generated from high-density station observation and microwave remote sensing data to monitor LST based on deep learning (U-Net family) for the first time. Given the significant spatial and temporal variability of LST and its sensitivity to various factors according to radiation transmission equations, this study incorporated climatic, anthropogenic, geographical, and vegetation datasets to facilitate a multi-source data fusion approach for LST estimation. The results showed that the U-Net++ model with modified skip connections better minimized the semantic discrepancy between the feature maps of the encoder and decoder subnetworks for 0.1° daily LST mapping across China than the U-Net and U2-Net deep learning models. The accuracy of the LST simulation exhibited favorable outcomes in the spatial and temporal dimensions. The station density met the requirements of monitoring air-ground integration monitoring in China. Additionally, the temporal change in the simulation accuracy fluctuated in a W-shape owing to the limited simulation capability of deep learning in extreme scenarios. Anthropogenic factors had the largest influence on LST changes in China, followed by climate, geography, and vegetation. This study highlighted the application of deep learning in remote sensing monitoring against the background of "big data" and provided a scientific foundation for the response of climate change to human activities, ecological environmental protection, and sustainable social and economic development.

Research status and prospect on the mechanisms of acupuncture and moxibustion treatment for constipation of Parkinson's disease. / é’ˆç¸æ²»ç–—å¸•é‡‘æ£®ç— ä¾¿ç§˜çš„æœºåˆ¶ç ”ç©¶çŽ°çŠ¶åŠå±•æœ›.

Constipation may accelerate the progression of Parkinson's disease (PD). The quality of life in PD patients can be significantly improved when constipation is treated, hence the disease progression may be delayed. At present, the mechanism research is still at the initial stage for acupuncture in treatment of PD, focusing on neurohumoral factors, intestinal flora, bacterial fermentation products and intestinal inflammation； and there are the problems such as single intervention, thinking limitation and insufficient cooperation among disciplines. This paper systematically reviews the mechanism research progress of acupuncture for the treatment of constipation in PD so as to provide the references for the subsequent studies.

A novel similarity measurement for triangular cloud models based on dual consideration of shape and distance.

It is important to be able to measure the similarity between two uncertain concepts for many real-life AI applications, such as image retrieval, collaborative filtering, risk assessment, and data clustering. Cloud models are important cognitive computing models that show promise in measuring the similarity of uncertain concepts. Here, we aim to address the shortcomings of existing cloud model similarity measurement algorithms, such as poor discrimination ability and unstable measurement results. We propose an EPTCM algorithm based on the triangular fuzzy number EW-type closeness and cloud drop variance, considering the shape and distance similarities of existing cloud models. The experimental results show that the EPTCM algorithm has good recognition and classification accuracy and is more accurate than the existing Likeness comparing method (LICM), overlap-based expectation curve (OECM), fuzzy distance-based similarity (FDCM) and multidimensional similarity cloud model (MSCM) methods. The experimental results also demonstrate that the EPTCM algorithm has successfully overcome the shortcomings of existing algorithms. In summary, the EPTCM method proposed here is effective and feasible to implement.

Handedness anomaly in a non-collinear antiferromagnet under spin-orbit torque.

Non-collinear antiferromagnets are an emerging family of spintronic materials because they not only possess the general advantages of antiferromagnets but also enable more advanced functionalities. Recently, in an intriguing non-collinear antiferromagnet Mn3Sn, where the octupole moment is defined as the collective magnetic order parameter, spin-orbit torque (SOT) switching has been achieved in seemingly the same protocol as in ferromagnets. Nevertheless, it is fundamentally important to explore the unknown octupole moment dynamics and contrast it with the magnetization vector of ferromagnets. Here we report a handedness anomaly in the SOT-driven dynamics of Mn3Sn: when spin current is injected, the octupole moment rotates in the opposite direction to the individual moments, leading to a SOT switching polarity distinct from ferromagnets. By using second-harmonic and d.c. magnetometry, we track the SOT effect onto the octupole moment during its rotation and reveal that the handedness anomaly stems from the interactions between the injected spin and the unique chiral-spin structure of Mn3Sn. We further establish the torque balancing equation of the magnetic octupole moment and quantify the SOT efficiency. Our finding provides a guideline for understanding and implementing the electrical manipulation of non-collinear antiferromagnets, which in nature differs from the well-established collinear magnets.

A new method to identifying optimal adjustment strategy when the car cockpit is uncomfortable: optimal state distance method.

With the rapid development of the automobile industry, the comfort of the cockpit has become the standard for judging the quality of the car. People have also put forward higher requirements for cockpit comfort. In the process of driving, the cockpit environment will constantly change, and the comfort will also change. When the comprehensive comfort level of the cockpit decreases and the occupants feel uncomfortable, the cockpit comfort should be adjusted. In this article, a cockpit comfort evaluation model is established to realize the evaluation of cockpit comfort. In addition, we elaborate the theory of optimal state distance, where the numerical magnitude of the optimal state distance is used to reflect the extent to which an indicator deviates from its optimal state. Also, a cockpit optimal adjustment strategy identification model is established based on the theory, which can obtain the optimal adjustment strategy in a certain cockpit operating environment, facilitate the timely adjustment of the corresponding actuator, and realize the dynamic monitoring and adjustment of cockpit comfort. This project provides a reference direction for cockpit comfort adjustment, which is of great significance for future research and development of automotive cockpit comfort.

Early Circulating Tumor DNA Dynamics Predict Neoadjuvant Therapy Response and Recurrence in Colorectal Liver Metastases: A Prospective Study.

BACKGROUND: For patients with colorectal liver metastases (CRLM) who receive neoadjuvant therapy (NAT), reliable indicators that can early and accurately predict treatment response are lacking. This study was conducted to prospectively investigate the potential of early circulating tumor DNA (ctDNA) dynamics as a precise predictor of NAT response and recurrence in CRLM. METHODS: This study prospectively enrolled 34 patients with CRLM who received NAT, with blood samples collected and subjected to deep targeted panel sequencing at two time points: 1 day before the first and the second cycles of NAT. Correlations of ctDNA mean variant allele frequency (mVAF) dynamics and treatment response were assessed. The performance of early ctDNA dynamics in predicting treatment response was assessed and compared with those of carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA19-9). RESULTS: The baseline ctDNA mVAF was significantly associated with pre-NAT tumor diameter (r = 0.65; P < 0.0001). After one cycle of NAT, the ctDNA mVAF declined remarkably (P < 0.0001). The dynamic change in ctDNA mVAF of 50% or more was significantly correlated with better NAT responses. The discriminatory capacity of ctDNA mVAF changes was superior to that of CEA or CA19-9 in predicting radiologic response (area under the curve [AUC], 0.90 vs 0.71 vs 0.61) and pathologic tumor regression grade (AUC, 0.83 vs 0.64 vs 0.67). The early changes in ctDNA mVAF but not CEA or CA19-9 were an independent indicator of recurrence-free survival (RFS) (hazard ratio, 4.0; P = 0.023). CONCLUSIONS: For CRLM patients receiving NAT, an early ctDNA change is a superior predictor of treatment response and recurrence compared with conventional tumor markers.

An evaluation model for automobile intelligent cockpit comfort based on improved combination weighting-cloud model.

Aiming at the comfort evaluation of automobile intelligent cockpit, an evaluation model based on improved combination weighting-cloud model is established. By consulting relevant literature, 4 first-class indexes and 15 second-class indexes, including noise and vibration, light environment, thermal environment and human-computer interaction, are selected to establish a comfort evaluation system. Later the subjective and objective weights obtained by improved Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) are combined by Game Theory. Considering the fuzziness and randomness of the index system, the combination weights obtained by Game Theory are combined with the cloud model. The floating cloud algorithms is used to determine the first-class and second-class index clouds and the comprehensive evaluation cloud parameters. Improvements were made in two commonly used similarity calculation methods, the expectation curve method (ECM) and the maximum boundary curve method (MCM). A new similarity calculation method is defined to optimize the evaluation results and determine the final comfort evaluation grade. Lastly, a 2021 Audi intelligent car under a certain working condition was selected to verify the correctness and rationality of the model using the fuzzy evaluation method. The results show that the cockpit comfort evaluation model based on the improved combination weighting-cloud model can better reflect the comprehensive comfort of automobile cockpit.

Coherent antiferromagnetic spintronics.

Antiferromagnets have attracted extensive interest as a material platform in spintronics. So far, antiferromagnet-enabled spin-orbitronics, spin-transfer electronics and spin caloritronics have formed the bases of antiferromagnetic spintronics. Spin transport and manipulation based on coherent antiferromagnetic dynamics have recently emerged, pushing the developing field of antiferromagnetic spintronics towards a new stage distinguished by the features of spin coherence. In this Review, we categorize and analyse the critical effects that harness the coherence of antiferromagnets for spintronic applications, including spin pumping from monochromatic antiferromagnetic magnons, spin transmission via phase-correlated antiferromagnetic magnons, electrically induced spin rotation and ultrafast spin-orbit effects in antiferromagnets. We also discuss future opportunities in research and applications stimulated by the principles, materials and phenomena of coherent antiferromagnetic spintronics.

Localization and density of tertiary lymphoid structures associate with molecular subtype and clinical outcome in colorectal cancer liver metastases.

BACKGROUND: Tertiary lymphoid structures (TLSs) have been proposed to assess the prognosis of patients with cancer. Here, we investigated the prognostic value and relevant mechanisms of TLSs in colorectal cancer liver metastases (CRCLM). METHODS: 603 patients with CRCLM treated by surgical resection from three cancer centers were included. The TLSs were categorized according to their anatomic subregions and quantified, and a TLS scoring system was established for intratumor region (T score) and peritumor region (P score). Differences in relapse-free survival (RFS) and overall survival (OS) between groups were determined. Multiplex immunohistochemical staining (mIHC) was used to determine the cellular composition of TLSs in 40 CRCLM patients. RESULTS: T score positively correlated with superior prognosis, while P score negatively associated with poor survival (all p<0.05). Meanwhile, T score was positively associated with specific mutation subtype of KRAS. Furthermore, TLSs enrichment gene expression was significantly associated with survival and transcriptomic subtypes of CRCLM. Subsequently, mIHC showed that the densities of Treg cells, M2 macrophages and Tfh cells were significantly higher in intratumor TLSs than in peritumor TLSs (p=0.029, p=0.047 and p=0.041, respectively), and the frequencies of Treg cells and M2 macrophages were positively correlated with P score, while the frequencies of Tfh cells were positively associated with T scores in intratumor TLSs (all p<0.05). Next, based on the distribution and abundance of TLSs, an Immune Score combining T score and P score was established which categorized CRCLM patients into four immune classes with different prognosis (all p<0.05). Among them, patients with higher immune class have more favorable prognoses. The C-index of Immune Class for RFS and OS was higher than Clinical Risk Score statistically. These results were also confirmed by the other two validation cohorts. CONCLUSIONS: The distribution and abundance of TLSs is significantly associated with RFS and OS of CRCLM patients, and a novel immune class was proposed for predicting the prognosis of CRCLM patients.

Phosphorylation of ATF2 promotes odontoblastic differentiation via intrinsic HAT activity.

Mouse dental papilla cells (mDPCs) are cranial neural crest-derived dental mesenchymal cells that give rise to dentin-secreting odontoblasts after the bell stage during odontogenesis. The odontoblastic differentiation of mDPCs is spatiotemporally regulated by transcription factors (TFs). Our previous work reveals that chromatin accessibility was correlated with the occupation of the basic leucine zipper TF family during odontoblastic differentiation. However, the detailed mechanism by which TFs regulate the initiation of odontoblastic differentiation remains elusive. Here, we report that phosphorylation of ATF2 (p-ATF2) is particularly increased during odontoblastic differentiation in vivo and in vitro. ATAC-seq and p-ATF2 CUT&Tag experiments further demonstrate a high correlation between p-ATF2 localization and increased chromatin accessibility of regions near mineralization-related genes. Knockdown of Atf2 inhibits the odontoblastic differentiation of mDPCs, while overexpression of p-ATF2 promotes odontoblastic differentiation. ATAC-seq after overexpression of p-ATF2 reveals that p-ATF2 increases the chromatin accessibility of regions adjacent to genes associated with matrix mineralization. Furthermore, we find that p-ATF2 physically interacts with and promotes H2BK12 acetylation. Taken together, our findings reveal a mechanism that p-ATF2 promotes odontoblastic differentiation at initiation via remodeling chromatin accessibility and emphasize the role of the phosphoswitch model of TFs in cell fate transitions.

The prognostic significance of clinicopathological characteristics in early-onset versus late-onset colorectal cancer liver metastases.

PURPOSE: This study aimed to explore the prognostic significance of clinicopathological characteristics in early-onset versus late-onset colorectal liver metastases (CRLM). METHODS: The data of CRLM patients who underwent hepatectomy from September 2010 to September 2020 were retrospectively analyzed. According to the age of primary cancer diagnosis, patients were divided into early-onset CRLM (EOCRLM) and late-onset CRLM (LOCRLM) groups. Clinicopathological parameters were compared between the two groups. Cox regression model and Kaplan-Meier method were used to analyze the effect of clinicopathological parameters on overall survival (OS) and recurrence-free survival (RFS). RESULTS: In total, 431 CRLM patients were identified, 130 with EOCRLM and 301 with LOCRLM. Compared with LOCRLM patients, EOCRLM patients had lower American Society of Anesthesia (ASA) grade and longer operation time (204 vs. 179 min). More aggressive features were presented in EOCRLM patients including synchronous liver metastases (76.9% vs. 61.1%) and bilobar involvement (43.8% vs. 33.2%). No significant difference in OS or RFS was found between the two groups. Multivariate analysis of EOCRLM group showed that preoperative CA19-9 level and RAS/BRAF status were predictive of OS, while bilobar involvement and preoperative CEA level were associated with RFS. In LOCRLM group, the number of CRLM, preoperative CA19-9 level, and BRAF status were associated with OS, while the number of CRLM was associated with RFS. CONCLUSIONS: The preoperative CA19-9 level, RAS/BRAF status, bilobar involvement, and preoperative CEA level were predictive of EOCRLM patient prognosis, while the number of CRLM, preoperative CA19-9 level, and BRAF status were predictive of LOCRLM patient prognosis.

Dual immune checkpoint inhibitors or combined with anti-VEGF agents in advanced, unresectable hepatocellular carcinoma.

BACKGROUND: Immune checkpoint inhibitor monotherapy did not show superiority of survival over standard therapy in advanced hepatocellular carcinoma. The combination immunotherapy including dual immune checkpoint inhibitors or combined with anti-VEGF agents have become a trend, but not fully evaluated. This study aimed to evaluate and compare distinct combination immunotherapy on efficacy in advanced hepatocellular carcinoma. METHODS: PubMed, Embase, Web of Science and Cochrane databases were systematically searched from inception to January 31, 2022. The primary endpoints were overall objective response rate (ORR), disease control rate (DCR), six-month progression-free survival rate (PFSR6m) and one-year overall survival rate (OSR1y). RESULTS: 11 studies with 16 independent cohorts and 3342 patients were included in the meta-analysis. Compared with first-line sorafenib, combination immunotherapy resulted in a significant improvement in ORR (RR, 2.74; 95%CI, 1.55-4.85; p = 0.0006), PFS (HR, 0.57; 95%CI, 0.49-0.65; p<0.0001) and OS (HR, 0.65; 95%CI, 0.52-0.82; p = 0.0002). Based on RECIST 1.1, the pooled ORR, PFSR6m and OSR1y for combination immunotherapy were 24.6% (95%CI: 20.3%-29.6%), 42.0% (95%CI: 34.2%-50.3%) and 61.8% (95%CI: 57.7%-65.7%), respectively. In distinct combination regimens, PD-1/L1 inhibitors plus anti-VEGF agents showed a significant superiority of clinical benefit than PD-1/L1 inhibitors plus CTLA-4 inhibitors (ORR: 25.2% vs 23.4%, p = 0.033; PFSR6m: 47.4% vs 23.2%, p<0.001; OSR1y: 65.1% vs 55.0%, p = 0.001). CONCLUSIONS: This study was the first meta-analysis to demonstrate the better survival benefit and tolerable toxicity of combination immunotherapy than standard therapy in advanced hepatocellular carcinoma. Compared with PD-1/L1 inhibitors plus CTLA-4 inhibitors, the regimens of PD-1/L1 inhibitors plus anti-VEGF agents may be associated with a significantly better clinical benefit. The difference in long-term survival and response population between two distinct combination regimens required further exploration.

Si-rhodamine fluorescent probe for monitoring of hypochlorous acid in the brains of mice afflicted with neuroinflammation.

Neuroinflammation leads to a persistent oxidative stress in the brain, and is closely related to the pathology of various neurological disorders. Hypochlorous acid (HClO) is a reactive oxygen species (ROS) that, at high levels, can cause brain tissue damage and neurogenic apoptosis. Herein, we designed and synthesized a silicon-rhodamine (SiR)-based formohydrazide (FH)-containing fluorescent probe, denoted as SiR-FH, for sensing HClO. This probe showed good selectivity, rapid response and high sensitivity. SiR-FH was successfully used to detect endogenous and exogenous HClO in living cells. Moreover, SiR-FH realized real-time monitoring of change in HClO flux in the brains of mice with LPS-induced neuroinflammation. The probe provides a practical tool for the monitoring of oxidative stress related to neuroinflammation.

Chromatin conformation of human oral epithelium can identify orofacial cleft missing functional variants.

Genome-wide association studies (GWASs) are the most widely used method to identify genetic risk loci associated with orofacial clefts (OFC). However, despite the increasing size of cohort, GWASs are still insufficient to detect all the heritability, suggesting there are more associations under the current stringent statistical threshold. In this study, we obtained an integrated epigenomic dataset based on the chromatin conformation of a human oral epithelial cell line (HIOEC) using RNA-seq, ATAC-seq, H3K27ac ChIP-seq, and DLO Hi-C. Presumably, this epigenomic dataset could reveal the missing functional variants located in the oral epithelial cell active enhancers/promoters along with their risk target genes, despite relatively less-stringent statistical association with OFC. Taken a non-syndromic cleft palate only (NSCPO) GWAS data of the Chinese Han population as an example, 3664 SNPs that cannot reach the strict significance threshold were subjected to this functional identification pipeline. In total, 254 potential risk SNPs residing in active cis-regulatory elements interacting with 1 718 promoters of oral epithelium-expressed genes were screened. Gapped k-mer machine learning based on enhancers interacting with epithelium-expressed genes along with in vivo and in vitro reporter assays were employed as functional validation. Among all the potential SNPs, we chose and confirmed that the risk alleles of rs560789 and rs174570 reduced the epithelial-specific enhancer activity by preventing the binding of transcription factors related to epithelial development. In summary, we established chromatin conformation datasets of human oral epithelial cells and provided a framework for testing and understanding how regulatory variants impart risk for clefts.