Targeting KDM4 family epigenetically triggers antitumour immunity via enhancing tumour-intrinsic innate sensing and immunogenicity.

Despite the remarkable clinical efficacy of cancer immunotherapy, considerable patients fail to benefit from it due to primary or acquired resistance. Tumours frequently hijack diverse epigenetic mechanisms to evade immune detection, thereby highlighting the potential for pharmacologically targeting epigenetic regulators to restore the impaired immunosurveillance and re-sensitise tumours to immunotherapy. Herein, we demonstrated that KDM4-targeting chemotherapeutic drug JIB-04, epigenetically triggered the tumour-intrinsic innate immune responses and immunogenic cell death (ICD), resulting in impressive antitumour effects. Specifically, JIB-04 induced H3K9 hypermethylation through specific inhibition of the KDM4 family (KDM4A-D), leading to impaired DNA repair signalling and subsequent DNA damage. As a result, JIB-04 not only activated the tumour-intrinsic cyclic GMP-AMP synthase (cGAS)-STING pathway via DNA-damage-induced cytosolic DNA accumulation, but also promoted ICD, releasing numerous damage-associated molecular patterns. Furthermore, JIB-04 induced adaptive resistance through the upregulation of programmed death-ligand 1 (PD-L1), which could be overcome with additional PD-L1 blockade. In human tumours, KDM4B expression was negatively correlated with clinical outcomes, type I interferon signatures, and responses to immunotherapy. In conclusion, our results demonstrate that targeting KDM4 family can activate tumour-intrinsic innate sensing and immunogenicity, and synergise with immunotherapy to improve antitumour outcomes.

Large Range of a High-Precision, Independent, Sub-Mirror Three-Dimensional Co-Phase Error Sensing and Correction Method via a Mask and Population Algorithm.

The emergence of segmented mirrors is expected to solve the design, processing, manufacturing, testing, and launching of space telescopes of large apertures. However, with the increase in the number of sub-mirrors, the sensing and correction of co-phase errors in segmented mirrors will be very difficult. In this paper, an independent three-dimensional method for sub-mirror co-phase error sensing and correction method is proposed. The method is based on a wide spectral modulation transfer function (MTF), mask, population optimization algorithm, and online model-free correction. In this method, the sensing and correction process of each sub-mirror co-phase error is independent of each other, so the increase in the number of sub-mirrors will not increase the difficulty of the method. This method can sense and correct the co-phase errors of three dimensions of the sub-mirror, including piston, tip, and tilt, even without modeling the optical system, and has a wide detection range and high precision. And the efficiency is high because the sub-mirrors can be corrected simultaneously in parallel. Simulation results show that the proposed method can effectively sense and correct the co-phase errors of the sub-mirrors in the range [-50λ, 50λ] in three dimensions with high precision. The average RMSE value in 100 experiments of the true co-phase error values and the experimental co-phase error values of one of the six sub-mirrors is 2.358 × 10-7λ.

Caspase-9 inhibition triggers Hsp90-based chemotherapy-mediated tumor intrinsic innate sensing and enhances antitumor immunity.

BACKGROUND: Antineoplastic chemotherapies are dramatically efficient when they provoke immunogenic cell death (ICD), thus inducing an antitumor immune response and even tumor elimination. However, activated caspases, the hallmark of most cancer chemotherapeutic agents, render apoptosis immunologically silent. Whether they are dispensable for chemotherapy-induced cell death and the apoptotic clearance of cells in vivo is still elusive. METHODS: A rational cell-based anticancer drug library screening was performed to explore the immunogenic apoptosis pathway and therapeutic targets under apoptotic caspase inhibition. Based on this screening, the potential of caspase inhibition in enhancing chemotherapy-induced antitumor immunity and the mechanism of actions was investigated by various cells and mouse models. RESULTS: Heat shock protein 90 (Hsp90) inhibition activates caspases in tumor cells to produce abundant genomic and mitochondrial DNA fragments and results in cell apoptosis. Meanwhile, it hijacks Caspase-9 signaling to suppress intrinsic DNA sensing. Pharmacological blockade or genetic deletion of Caspase-9 causes tumor cells to secrete interferon (IFN)-ß via tumor intrinsic mitochondrial DNA/the second messenger cyclic GMP-AMP (cGAS) /stimulator of interferon genes (STING) pathway without impairing Hsp90 inhibition-induced cell death. Importantly, both Caspase-9 and Hsp90 inhibition triggers an ICD, leading to the release of numerous damage-associated molecular patterns such as high-mobility group box protein 1, ATP and type I IFNs in vitro and remarkable antitumor effects in vivo. Moreover, the combination treatment also induces adaptive resistance by upregulating programmed death-ligand 1 (PD-L1). Additional PD-L1 blockade can further overcome this acquired immune resistance and achieve complete tumor regression. CONCLUSIONS: Blockade of Caspase-9 signaling selectively provokes Hsp90-based chemotherapy-mediated tumor innate sensing, leading to CD8+ T cell-dependent tumor control. Our findings implicate that pharmacological modulation of caspase pathway increases the tumor-intrinsic innate sensing and immunogenicity of chemotherapy-induced apoptosis, and synergizes with immunotherapy to overcome adaptive resistance.

Security Implications of AI Chatbots in Health Care.

Artificial intelligence (AI) chatbots like ChatGPT and Google Bard are computer programs that use AI and natural language processing to understand customer questions and generate natural, fluid, dialogue-like responses to their inputs. ChatGPT, an AI chatbot created by OpenAI, has rapidly become a widely used tool on the internet. AI chatbots have the potential to improve patient care and public health. However, they are trained on massive amounts of people's data, which may include sensitive patient data and business information. The increased use of chatbots introduces data security issues, which should be handled yet remain understudied. This paper aims to identify the most important security problems of AI chatbots and propose guidelines for protecting sensitive health information. It explores the impact of using ChatGPT in health care. It also identifies the principal security risks of ChatGPT and suggests key considerations for security risk mitigation. It concludes by discussing the policy implications of using AI chatbots in health care.

Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions—a pilot study / La secuenciación metagenómica revela comunidades microbianas de pulmón porcino y genomas ensamblados en metagenoma asociados con lesiones pulmonares: un estudio piloto

Low microbial biomass in the lungs, high host-DNA contamination and sampling difficulty limit the study on lung microbiome. Therefore, little is still known about lung microbial communities and their functions. Here, we perform a preliminary exploratory study to investigate the composition of swine lung microbial community using shotgun metagenomic sequencing and compare the microbial communities between healthy and severe-lesion lungs. We collected ten lavage-fluid samples from swine lungs (five from healthy lungs and five from severe-lesion lungs), and obtained their metagenomes by shotgun metagenomic sequencing. After filtering host genomic DNA contamination (93.5% ± 1.2%) in the lung metagenomic data, we annotated swine lung microbial communities ranging from four domains to 645 species. Compared with previous taxonomic annotation of the same samples by the 16S rRNA gene amplicon sequencing, it annotated the same number of family taxa but more genera and species. We next performed an association analysis between lung microbiome and host lung-lesion phenotype. We found three species (Mycoplasma hyopneumoniae, Ureaplasma diversum, and Mycoplasma hyorhinis) were associated with lung lesions, suggesting they might be the key species causing swine lung lesions. Furthermore, we successfully reconstructed the metagenome-assembled genomes (MAGs) of these three species using metagenomic binning. This pilot study showed us the feasibility and relevant limitations of shotgun metagenomic sequencing for the characterization of swine lung microbiome using lung lavage-fluid samples. The findings provided an enhanced understanding of the swine lung microbiome and its role in maintaining lung health and/or causing lung lesions.(AU)

Dissecting the tumour immune microenvironment in merkel cell carcinoma based on a machine learning framework.

Merkel cell carcinoma (MCC) is a primary cutaneous neoplasm of neuroendocrine carcinoma of the skin, which is characterized by molecular heterogeneity with diverse tumour microenvironment (TME). However, we are still lack knowledge of the cellular states and ecosystems in MCC. Here, we systematically identified and characterized the landscape of cellular states and ecotypes in MCC based on a machine learning framework. We obtained 30 distinct cellular states from 9 immune cell types and investigated the B cell, CD8 T cell, fibroblast, and monocytes/macrophage cellular states in detail. The functional profiling of cellular states were investigated and found the genes highly expressed in cellular states were significantly enriched in immune- and cancer hallmark-related pathways. In addition, four ecotypes were further identified which were with different patient compositions. Transcriptional regulation analysis revealed the critical transcription factors (i.e. E2F1, E2F3 and E2F7), which play important roles in regulating the TME of MCC. In summary, the findings of this study may provide rich knowledge to understand the intrinsic subtypes of MCCs and the pathways involved in distinct subtype oncogenesis, and will further advance the knowledge in developing a specific therapeutic strategy for these MCC subtypes.

Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition.

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer.

Mass spectrometry (MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Data-independent acquisition (DIA) mode is considered to perform better than data-dependent acquisition (DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft (MiniPDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients. Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases. Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer (CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and MiniPDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.

The intratumor mycobiome promotes lung cancer progression via myeloid-derived suppressor cells.

Although polymorphic microbiomes have emerged as hallmarks of cancer, far less is known about the role of the intratumor mycobiome as living microorganisms in cancer progression. Here, using fungi-enriched DNA extraction and deep shotgun metagenomic sequencing, we have identified enriched tumor-resident Aspergillus sydowii in patients with lung adenocarcinoma (LUAD). By three different syngeneic lung cancer mice models, we find that A. sydowii promotes lung tumor progression via IL-1ß-mediated expansion and activation of MDSCs, resulting in suppressed activity of cytotoxic T lymphocyte cells and accumulation of PD-1+ CD8+ T cells. This is mediated by IL-1ß secretion via ß-glucan/Dectin-1/CARD9 pathway. Analysis of human samples confirms that enriched A. sydowii is associated with immunosuppression and poor patient outcome. Our findings suggest that intratumor mycobiome, albeit at low biomass, promotes lung cancer progression and could be targeted at the strain level to improve patients with LUAD outcome.

Characterization of the pig lower respiratory tract antibiotic resistome.

Respiratory diseases and its treatments are highly concerned in both the pig industry and human health. However, the composition and distribution of antibiotic resistance genes (ARGs) in swine lower respiratory tract microbiome remain unknown. The relationships of ARGs with mobile genetic elements (MGEs) and lung health are unclear. Here, we characterize antibiotic resistomes of the swine lower respiratory tract microbiome containing 1228 open reading frames belonging to 372 ARGs using 745 metagenomes from 675 experimental pigs. Twelve ARGs conferring resistance to tetracycline are related to an MGE Tn916 family, and multiple types of ARGs are related to a transposase gene tnpA. Most of the linkage complexes between ARGs and MGEs (the Tn916 family and tnpA) are also observed in pig gut microbiomes and human lung microbiomes, suggesting the high risk of these MGEs mediating ARG transfer to both human and pig health. Gammaproteobacteria are the major ARG carriers, within which Escherichia coli harbored >50 ARGs and >10 MGEs. Although the microbial compositions structure the compositions of ARGs, we identify 73 ARGs whose relative abundances are significantly associated with the severity of lung lesions. Our results provide the first overview of ARG profiles in the swine lower respiratory tract microbiome.

Vemurafenib inhibits necroptosis in normal and pathological conditions as a RIPK1 antagonist.

Necroptosis, a programmed cell death with necrotic-like morphology, has been recognized as an important driver in various inflammatory diseases. Inhibition of necroptosis has shown potential promise in the therapy of multiple human diseases. However, very few necroptosis inhibitors are available for clinical use as yet. Here, we identified an FDA-approved anti-cancer drug, Vemurafenib, as a potent inhibitor of necroptosis. Through direct binding, Vemurafenib blocked the kinase activity of receptor-interacting protein kinases 1 (RIPK1), impeded the downstream signaling and necrosome complex assembly, and inhibited necroptosis. Compared with Necrostain-1, Vemurafenib stabilized RIPK1 in an inactive DLG-out conformation by occupying a distinct allosteric hydrophobic pocket. Furthermore, pretreatment with Vemurafenib provided strong protection against necroptosis-associated diseases in vivo. Altogether, our results demonstrate that Vemurafenib is an effective RIPK1 antagonist and provide rationale and preclinical evidence for the potential application of approved drug in necroptosis-related diseases.

Channel Modeling and Characteristics Analysis under Different 3D Dynamic Trajectories for UAV-Assisted Emergency Communications.

This study involved channel modeling and characteristics analysis of unmanned aerial vehicles (UAVs) according to different operating trajectories. Based on the idea of standardized channel modeling, air-to-ground (AG) channel modeling of a UAV was carried out, taking into consideration that both the receiver (Rx) and the transmitter (Tx) ran along different types of trajectories. In addition, based on Markov chains and a smooth-turn (ST) mobility model, the influences of different operation trajectories on typical channel characteristics-including time-variant power delay profile (PDP), stationary interval, temporal autocorrelation function (ACF), root mean square (RMS) delay spread (DS), and spatial cross-correlation function (CCF)-were studied. The multi-mobility multi-trajectory UAV channel model matched well with actual operation scenarios, and the characteristics of the UAV AG channel could be analyzed more accurately, thus providing a reference for future system design and sensor network deployment of sixth-generation (6G) UAV-assisted emergency communications.

Cadmium promotes colorectal cancer metastasis through EGFR/Akt/mTOR signaling cascade and dynamics.

Cadmium (Cd) is a hazardous environmental heavy metal with a prolonged biological half-life. Due to the main route of foodborne exposure, the intestinal tract is particularly vulnerable to Cd-induced toxicity. However, the chronic toxicity and underlying mechanisms of Cd in intestinal diseases, including colorectal cancer (CRC), still remain vague. Herein, we aim to investigate the long-term effects of Cd exposure on CRC development and the key signaling event. Our findings indicate that chronic and low-dose exposure to Cd promoted the invasion and metastasis capability of CRC cells in vitro and in mice, with a marginal increase in cell growth. The expression of cell junction-related genes was down-regulated while those molecules that facilitate cell mobility were significantly increased by Cd exposure. Epidermal growth factor receptor (EGFR) signaling was identified to play the dominant role in Cd-promoted CRC metastasis. Interestingly, Cd activated EGFR in a non-canonical manner that exhibited distinct signaling dynamics from the canonical ligand. In contrast to EGF, which induced transient EGFR signaling and ERK activation, Cd promoted sustained EGFR signaling to trigger Akt/mTOR cascade. The unique signaling dynamics of EGFR induced by Cd provoked responses that preferably enhanced the metastatic capacity rather than the growth. Furthermore, blockade of EGFR abrogated the promoting effects of Cd on the liver metastasis of CRC cells. In conclusion, this study provides a better understanding of the long-term influences of environmental Cd on CRC metastasis and reveals the unique EGFR signaling dynamics induced by Cd exposure.

Spatio-temporal variation in water quality and phytoplankton community structure in Changwang, Meishe, and Wuyuan Rivers in Hainan Island, China.

For the first time, this study explored spatio-temporal variation in water quality and phytoplankton community structure in Changwang, Meishe, and Wuyuan Rivers in tropical Hainan Island, China. Phytoplankton samples and water were collected between March and December 2019 and analyzed using standard methods. Two-way ANOVA revealed significant spatial and seasonal variation in physico-chemical parameters (p < 0.05). Wuyuan had high TP (0.06 ± 0.04 mg L-1), TN (1.14 ± 0.71 mg L-1), NH4+-N (0.07 ± 0.09 mg L-1), Secchi depth (2.28 ± 3.79 m), salinity (3.60±5.50 ppt), and EC (332.50 ± 219.10 µS cm-1). At the same time, Meishe had high TP (0.07 ± 0.03 mg L-1), TN (1.04 ± 0.74 mg L-1), NH4+-N (0.07 ± 0.10 mg L-1), EC (327.61 ± 63.22 µS cm-1), and turbidity (40.25 ± 21.16 NTU). In terms of seasons, spring recorded high average TP, TN, NH4+-N, COD, and DO, while summer had a high temperature, Chl-a, salinity, and EC. Generally, the physico-chemical parameters met the China water quality standard limits (GB 3838-2002). Overall, 197 phytoplankton species belonging to Cyanophyta, Chlorophyta, Cryptophyta, Bacillariophyta, Pyrrophyta, Euglenophyta, Xanthophyta, and Chrysophyta were identified, with Cyanophyta being dominant. Phytoplankton density showed spatial changes varying from 18 × 106 cell L-1 to 84 × 106 cell L-1. The phytoplankton diversity ranged from 1.86 to 2.41, indicating a mesotrophic state. One-way ANOSIM showed no significant spatial dissimilarity in phytoplankton composition (R = 0.042, p = 0.771) but indicated a significant seasonal difference (R = 0.265, p = 0.001). Therefore, SIMPER analysis revealed that Lyngbya attenuata, Merismopedia tenuissima, Cyclotella sp., Merismopedia glauca, Merismopedia elegans, and Phormidium tenue contributed to the seasonal differences. Furthermore, CCA demonstrated that TP, TN, NH4+-N, COD, Chl-a, and Secchi depth greatly influenced the phytoplankton community. This study shows the spatio-temporal variation in water quality and phytoplankton communities, useful for managing riverine quality.

Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios.

Regarding the new demands and challenges of sixth-generation (6G) mobile communications, wireless networks are undergoing a significant shift from traditional terrestrial networks to space-air-ground-sea-integrated networks. Unmanned aerial vehicle (UAV) communications in complicated mountainous scenarios are typical applications and have practical implications, especially in emergency communications. In this paper, the ray-tracing (RT) method was applied to reconstruct the propagation scenario and then acquire the wireless channel data. Channel measurements are also conducted in real mountainous scenarios for verification. By setting different flight positions, trajectories, and altitudes, channel data in the millimeter wave (mmWave) band was obtained. Important statistical properties, such as the power delay profile (PDP), Rician K-factor, path loss (PL), root mean square (RMS) delay spread (DS), RMS angular spreads (ASs), and channel capacity were compared and analyzed. The effects of different frequency bands on channel characteristics at 3.5 GHz, 4.9 GHz, 28 GHz, and 38 GHz bands in mountainous scenarios were considered. Furthermore, the effects of extreme weather, especially different precipitation, on the channel characteristics were analyzed. The related results can provide fundamental support for the design and performance evaluation of future 6G UAV-assisted sensor networks in complicated mountainous scenarios.

Ultrafast extraction of uranium from seawater using photosensitized biohybrid system with bioinspired cascaded strategy.

The highly effective utilization of uranium resources in global seawater is a viable method to satisfy the rising demands for fueling nuclear energy industry. Herein, inspired by the multi-mechanisms of the marine bacteria for uranium immobilization, CdS nanoparticles are deposited on the cell of marine bacterial strain Bacillus velezensis UUS-1 to create a photosensitized biohybrid system UUS-1/CdS. This system achieves high uranium extraction efficiency using a cascaded strategy, where the bacterial cells guarantee high extraction selectivity and the photosensitive CdS nanoparticles realize cascading photoreduction of high soluble U(VI) to low soluble U(IV) to enhance extraction capacity. As one of the fastest-acting adsorbents in natural seawater, a high extraction capacity for uranium of 7.03 mg g-1 is achieved with an ultrafast extraction speed of 4.69 mg g-1 d-1. The cascaded strategy promisingly improves uranium extraction performance and pioneers a new direction for the design of adsorbents to extract uranium from seawater.

Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study.

Low microbial biomass in the lungs, high host-DNA contamination and sampling difficulty limit the study on lung microbiome. Therefore, little is still known about lung microbial communities and their functions. Here, we perform a preliminary exploratory study to investigate the composition of swine lung microbial community using shotgun metagenomic sequencing and compare the microbial communities between healthy and severe-lesion lungs. We collected ten lavage-fluid samples from swine lungs (five from healthy lungs and five from severe-lesion lungs), and obtained their metagenomes by shotgun metagenomic sequencing. After filtering host genomic DNA contamination (93.5% ± 1.2%) in the lung metagenomic data, we annotated swine lung microbial communities ranging from four domains to 645 species. Compared with previous taxonomic annotation of the same samples by the 16S rRNA gene amplicon sequencing, it annotated the same number of family taxa but more genera and species. We next performed an association analysis between lung microbiome and host lung-lesion phenotype. We found three species (Mycoplasma hyopneumoniae, Ureaplasma diversum, and Mycoplasma hyorhinis) were associated with lung lesions, suggesting they might be the key species causing swine lung lesions. Furthermore, we successfully reconstructed the metagenome-assembled genomes (MAGs) of these three species using metagenomic binning. This pilot study showed us the feasibility and relevant limitations of shotgun metagenomic sequencing for the characterization of swine lung microbiome using lung lavage-fluid samples. The findings provided an enhanced understanding of the swine lung microbiome and its role in maintaining lung health and/or causing lung lesions.

Nano-Econazole Enhanced PD-L1 Checkpoint Blockade for Synergistic Antitumor Immunotherapy against Pancreatic Ductal Adenocarcinoma.

Insufficienct T lymphocyte infiltration and unresponsiveness to immune checkpoint blockade therapy are still major difficulties for the clinical treatment of pancreatic ductal adenocarcinoma (PDAC). Although econazole has shown promise in inhibiting PDAC growth, its poor bioavailability and water solubility limit its potential as a clinical therapy for PDAC. Furthermore, the synergistic role of econazole and biliverdin in immune checkpoint blockade therapy in PDAC remains elusive and challenging. Herein, a chemo-phototherapy nanoplatform is designed by which econazole and biliverdin can be co-assembled (defined as FBE NPs), which significantly improve the poor water solubility of econazole and enhance the efficacy of PD-L1 checkpoint blockade therapy against PDAC. Mechanistically, econazole and biliverdin are directly released into the acidic cancer microenvironment, to activate immunogenic cell death via biliverdin-induced PTT/PDT and boost the immunotherapeutic response of PD-L1 blockade. In addition, econazole simultaneously enhances PD-L1 expression to sensitize anti-PD-L1 therapy, leading to suppression of distant tumors, long-term immune memory effects, improved dendritic cell maturation, and tumor infiltration of CD8+ T lymphocytes. The combined FBE NPs and α-PDL1 show synergistic antitumor efficacy. Collectively, FBE NPs show excellent biosafety and antitumor efficacy by combining chemo-phototherapy with PD-L1 blockade, which has promising potential in a precision medicine approach as a PDAC treatment strategy.