Somatic KMT2D loss-of-function mutations in lung squamous cell carcinoma: a single-center cohort study.

Background: The significant progress has been made in targeted therapy for lung adenocarcinoma (LUAD) in the past decade. Only few targeted therapeutics have yet been approved for the treatment of lung squamous cell carcinoma (LUSC). Several higher frequency of gene alterations are identified as potentially actionable in LUSC. Our work aimed to explore the complex interplay of multiple genetic alterations and pathways contributing to the pathogenesis of LUSC, with a very low frequency of a single driver molecular alterations to develop more effective therapeutic strategies in the future. Methods: We retrospectively analyzed the targeted next-generation sequencing (NGS) data (approximately 600 genes) of 335 patients initially diagnosed with non-small cell lung cancer (NSCLC) at our institution between January 2019 and March 2023 and explored the somatic genome alteration difference between LUSC and LUAD. Results: We analyzed that the presence of loss-of-function (LoF) mutations (nonsense, frameshift, and splice-site variants) in histone-lysine N-methyltransferase 2D (KMT2D) was much more prevalent in LUSC (11/53, 20.8%) than in LUAD (6/282, 2.1%). Moreover, our data indicated TP53 co-mutated with KMT2D LoF in 90.9% (10/11) LUSC and 33.3% (2/6) LUAD. Notably, the mutation allele fraction (MAF) of KMT2D was very similar to that of TP53 in the co-mutated cases. Genomic profiling of driver gene mutations of NSCLC showed that 81.8% (9/11) of the patients with LUSC with KMT2D LoF mutations had PIK3CA amplification and/or FGFR1 amplification. Conclusions: Our results prompted that somatic LoF mutations of KMT2D occur frequently in LUSC, but are less frequent in LUAD and therefore may potentially contribute to the pathogenesis of LUSC. Concurrent TP53 mutations, FGFR1 amplification, and PIK3CA amplification are very common in LUSC cases with KMT2D LoF mutations. It needs more deeper investigation on the interplay of the genes and pathways and uses larger cohorts in the future.

Lactobacillus melliventris promotes hive productivity and immune functionality in Bombus terrestris performance in the greenhouse.

Bumblebees are important pollinators in agricultural ecosystems, but their abundance is declining globally. There is an urgent need to protect bumblebee health and their pollination services. Bumblebees possess specialized gut microbiota with potential to be used as probiotics to help defend at-risk bumblebee populations. However, evidence for probiotic benefits on bumblebees is lacking. Here, we evaluated how supplementation with Lactobacillus melliventris isolated from bumblebee gut affected the colony development of Bombus terrestris. This native strain colonized robustly and persisted long-term in bumblebees, leading to a significantly higher quality of offspring. Subsequently, the tyrosine pathway was upregulated in the brain and fat body, while the Wnt and mTOR pathways of the gut were downregulated. Notably, the field experiment in the greenhouse revealed the supplementation of L. melliventris led to a 2.5-fold increase in the bumblebee survival rate and a more than 10% increase in the number of flowers visited, indicating a better health condition and pollination ability in field conditions. Our study represents a first screening for the potential use of the native gut member, L. melliventris, as probiotic strains in hive supplement for bumblebee breeding, which may be a practical approach to improve immunity and hive health.

A Pressure and Temperature Dual-Parameter Sensor Based on a Composite Material for Electronic Wearable Devices.

Wearable sensors integrating multiple functionalities are highly desirable in artificial wearable devices, which are of great significance in the field of biomedical research and for human-computer interactions. However, it is still a great challenge to simultaneously perceive multiple external stimuli such as pressure and temperature with one single sensor. Combining the piezoresistive effect with the negative temperature coefficient of resistance, in this paper, we report on a pressure-temperature dual-parameter sensor composed of a polydimethylsiloxane film, carbon nanotube sponge, and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate). The proposed multifunctional sensor can stably monitor pressure signals with a high sensitivity of 16 kPa-1, has a range of up to 2.5 kPa, and also has a fast response time. Meanwhile, the sensor can also respond to temperature changes with an ultrahigh sensitivity rate of 0.84% °C-1 in the range of 20 °C to 80 °C. To validate the applicability of our sensor in practical environments, we conducted real-scene tests, which revealed its capability for monitoring = human motion signals while simultaneously sensing external temperature stimuli, reflecting its great application prospects for electronic wearable devices.

Case report: Rechallenge with EGFR-TKIs after immunotherapy in EGFR-mutated non-small cell lung cancer with leptomeningeal metastasis.

Rechallenge of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) after PD-1 blockade failure was an effective therapy for non-small cell lung cancer (NSCLC) patients with resistance to EGFR-TKIs. The third-generation TKIs, like osimertinib and furmonertinib, can reach higher concentration in the cerebrospinal fluid (CSF) than other TKIs, and exhibit a beneficial effect in NSCLC patients with leptomeningeal metastases (LM) harboring sensitive EGFR mutation. Here, we report that two-stage IV pulmonary adenocarcinoma patients with LM harboring an EGFR L858R mutation benefit from the third-generation EGFR-TKIs rechallenge after immune checkpoint inhibitor (ICI) and anti-angiogenic agent combination therapy. Complete response (CR) to partial response (PR) of central nervous system (CNS) response was achieved immediately after the administration of furmonertinib and osimertinib. We conducted next-generation sequencing (NGS) and IHC to elucidate the evolution of driver mutations and the immune microenvironment. In conclusion, these two cases might provide a therapeutic strategy for further clinical practice. More research was needed to elucidate the resistance mechanisms and improve current treatment strategies in EGFR-mutated patients with LM.

Double Fano Resonance and Independent Regulation Characteristics in a Rectangular-like Nanotetramer Metasurface Structure.

Fano resonance, which is based on a plasmonic metasurface, has many potential applications in various fields, such as biochemical sensors, slow light effect, and integrated optical circuits. In this study, a rectangular-like nanotetramer metasurface structure composed of four round-head nanorods was designed. The transmission spectrum, surface charge, and electrical field distributions of the proposed structure were simulated using the finite element method. A double Fano resonance profile was observed in the transmission spectrum. One of the Fano resonances was caused by the symmetry breaking and plasmon hybridization between the horizontal double rods, whereas the other resonance was due to the plasmonic modes' hybridization among four nanorods. These resonances could be independently tuned because of different formation mechanisms. The number of Fano resonances could be adjusted by changing the coupling distance between the horizontal and vertical rods. The results contributed to designing the highly sensitive sensors based on the plasmonic metasurface.

Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction.

Learned optimization algorithms are promising approaches to inverse problems by leveraging advanced numerical optimization schemes and deep neural network techniques in machine learning. In this paper, we propose a novel deep neural network architecture imitating an extra proximal gradient algorithm to solve a general class of inverse problems with a focus on applications in image reconstruction. The proposed network features learned regularization that incorporates adaptive sparsification mappings, robust shrinkage selections, and nonlocal operators to improve solution quality. Numerical results demonstrate the improved efficiency and accuracy of the proposed network over several state-of-the-art methods on a variety of test problems.

An investigation of integrating the finite element method (FEM) with grey system theory for geotechnical problems.

Numerical simulation is very important to solve geotechnical problems. However, it is difficult to obtain required comprehensive and accurate information such as parameters, boundary conditions, and etc. In this paper, a grey distributed parameter model, which integrates the finite element method (FEM) with the grey system theory, was proposed to address the issue. The analysis of grey properties on rock and soil system was performed. The equilibrium equations, geometric equations, physics equations and related differential equations were obtained, each of the equations contains grey parameters and variables. And the discretization and solution methods of the FEM with the grey variables were discussed. An example of deep-buried circular mining tunnel was applied to test the proposed model. The calculation results were compared with those of the exact solution (analytical solution) and the classical FEM, respectively, through which the rationality of the proposed model was demonstrated. For the first time, grey variables and grey parameters are defined in geotechnical numerical simulation. The expressions of basic equations with grey variables are given respectively. A grey distributed parameter model which integrates the FEM with the grey system theory is proposed to solve geotechnical problems, and the optimal solution to the proposed model is determined through calculation and comparison of an application example. The proposed numerical model with grey variables not only has the advantage of grey system theory, but also greatly improves the adaptability and application effect of the model, which contributes to the prediction and evaluation problems in geological engineering, geotechnical engineering, water conservancy engineering and civil engineering with complex structures.

Clinical efficacy and safety of neuroendoscopic surgery for severe thalamic hemorrhage with ventricle encroachment.

To summarize and analyze the clinical efficacy and safety of neuroendoscopic surgery (NES) in the treatment of patients for severe thalamic hemorrhage with ventricle encroachment (THVE). Eighty-three patients with severe THVE were treated in the Neurosurgery Department of Anqing Hospital Affiliated to Anhui Medical University from July 2019 to August 2021. Our study was approved by the ethics committee. The patients were randomly divided into NES group and extraventricular drainage (EVD) group. The hospital stay, Glasgow coma scale (GCS) scores on the 1st and 14th days postoperatively, the incidence of intracranial infections, and the clearance of postoperative hematomas were compared and analyzed between the two groups. The patients had follow-up evaluations 6 months postoperatively. The prognosis was evaluated based on the activity of daily living (ADL) score. A head CT or MRI was obtained to determine whether there was hydrocephalus, cerebral infarction, or other related complications. Eighty-three patients were randomly divided into 41 cases of NES group and 42 cases of EVD group. The length of postoperative hospital stay was 17.42 ± 1.53 days, the GCS scores were 6.56 ± 0.21, and 10.83 ± 0.36 on days 1 and 14, respectively; intracranial infections occurred in 3 patients (7.31%) and the hematoma clearance rate was 83.6 ± 5.18% in the NES group, all of which were significantly better than the EVD group (P < 0.05). After 6 months of follow-up, 28 patients (68.29%) had a good prognosis, 5 patients (12.19%) died, and 4 patients (9.75%) had hydrocephalus in the NES group. In the EVD group, the prognosis was good in 15 patients (35.71%), 12 patients (28.57%) died, and 17 patients (40.47%) had hydrocephalus. The prognosis, mortality rate, and incidence of hydrocephalus in the NES group were significantly better than the EVD group (P < 0.05). Compared to traditional EVD, NES for severe THVE had a higher hematoma clearance rate, and fewer intracranial infections and patients with hydrocephalus, which together improve the clinical prognosis and is thus recommended for clinical use.

Avian influenza viruses suppress innate immunity by inducing trans-transcriptional readthrough via SSU72.

Innate immunity plays critical antiviral roles. The highly virulent avian influenza viruses (AIVs) H5N1, H7N9, and H5N6 can better escape host innate immune responses than the less virulent seasonal H1N1 virus. Here, we report a mechanism by which transcriptional readthrough (TRT)-mediated suppression of innate immunity occurs post AIV infection. By using cell lines, mouse lungs, and patient PBMCs, we showed that genes on the complementary strand ("trans" genes) influenced by TRT were involved in the disruption of host antiviral responses during AIV infection. The trans-TRT enhanced viral lethality, and TRT abolishment increased cell viability and STAT1/2 expression. The viral NS1 protein directly bound to SSU72, and degradation of SSU72 induced TRT. SSU72 overexpression reduced TRT and alleviated mouse lung injury. Our results suggest that AIVs infection induce TRT by reducing SSU72 expression, thereby impairing host immune responses, a molecular mechanism acting through the NS1-SSU72-trans-TRT-STAT1/2 axis. Thus, restoration of SSU72 expression might be a potential strategy for preventing AIV pandemics.

An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset.

This work aims at developing a generalizable Magnetic Resonance Imaging (MRI) reconstruction method in the meta-learning framework. Specifically, we develop a deep reconstruction network induced by a learnable optimization algorithm (LOA) to solve the nonconvex nonsmooth variational model of MRI image reconstruction. In this model, the nonconvex nonsmooth regularization term is parameterized as a structured deep network where the network parameters can be learned from data. We partition these network parameters into two parts: a task-invariant part for the common feature encoder component of the regularization, and a task-specific part to account for the variations in the heterogeneous training and testing data. We train the regularization parameters in a bilevel optimization framework which significantly improves the robustness of the training process and the generalization ability of the network. We conduct a series of numerical experiments using heterogeneous MRI data sets with various undersampling patterns, ratios, and acquisition settings. The experimental results show that our network yields greatly improved reconstruction quality over existing methods and can generalize well to new reconstruction problems whose undersampling patterns/trajectories are not present during training.

Ifenprodil and Flavopiridol Identified by Genomewide RNA Interference Screening as Effective Drugs To Ameliorate Murine Acute Lung Injury after Influenza A H5N1 Virus Infection.

Due to the limitations of effective treatments, avian influenza A H5N1 virus is the most lethal influenza virus strain that causes severe acute lung injury (ALI). To develop effective drugs ameliorating H5N1-induced ALI, we explore an RNA interference (RNAi) screening method to monitor changes in cell death induced by H5N1 infection. We performed RNAi screening on 19,424 genes in A549 lung epithelial cells and examined cell death induced by H5N1 infection. These screens identified 1,137 host genes for which knockdown altered cell viability by over 20%. DrugBank searches of these 1,137 host genes identified 146 validated druggable target genes with 372 drug candidates. We obtained 104 commercially available drugs with 65 validated target genes and examined their improvement of cell viability following H5N1 infection. We identified 28 drugs that could significantly recover cell viability following H5N1 infection and tested 10 in an H5N1-induced-ALI mouse model. The neurological drug ifenprodil and the anticancer drug flavopiridol markedly decreased leukocyte infiltration and lung injury scores in infected mouse lungs, significantly ameliorated edema in infected mouse lung tissues, and significantly improved the survival of H5N1-infected mice. Ifenprodil is an antagonist of the N-methyl-d-aspartate (NMDA) receptor, which is linked to inflammation and lung injury. Flavopiridol is an inhibitor of cyclin-dependent kinase 4 (CDK4), which is linked to leukocyte migration and lung injury. These results suggest that ifenprodil and flavopiridol represent novel remedies against potential H5N1 epidemics in addition to their proven indications. Furthermore, our strategy for identifying repurposable drugs could be a general approach for other diseases.IMPORTANCE Drug repurposing is a quick and economical strategy for developing new therapies with approved drugs. H5N1 is a highly pathogenic avian influenza virus subtype that can cause severe acute lung injury (ALI) and a high mortality rate due to limited treatments. The use of RNA interference (RNAi) is a reliable approach to identify essential genes in diseases. In most genomewide RNAi screenings, virus replication is the readout of interference. Since H5N1 virus infection could induce significant cell death and the percentage of cell death is associated with virus lethality, we designed a genomewide RNAi screening method to identify repurposable drugs against H5N1 virus with cell death as the readout. We discovered that the neurological drug ifenprodil and the anticancer drug flavopiridol could effectively ameliorate murine ALI after influenza A H5N1 virus infection, suggesting that they might be novel remedies for H5N1 virus-induced ALI in addition to the traditional indications.

Clinical and Immunological Characteristics of Human Infections With H5N6 Avian Influenza Virus.

BACKGROUND: H5N6 avian influenza virus (AIV) has caused sporadic, recurring outbreaks in China and Southeast Asia since 2013, with 19 human infections and 13 deaths. Seventeen of these infections occurred since December 2015, indicating a recent rise in the frequency of H5N6 cases. METHODS: To assess the relative threat of H5N6 virus to humans, we summarized and compared clinical data from patients infected with H5N6 (n = 19) against data from 2 subtypes of major public health concern, H5N1 (n = 53) and H7N9 (n = 160). To assess immune responses indicative of prognosis, we compared concentrations of serum cytokines/chemokines in patients infected with H5N6, H5N1, H7N9, and 2009 pandemic H1N1 and characterized specific immune responses from 1 surviving and 2 nonsurviving H5N6 patients. RESULTS: H5N6 patients were found to have higher incidences of lymphopenia and elevated alanine aminotransferase and lactate dehydrogenase levels compared with H5N1 and H7N9 patients. Hypercytokinemia was detected at substantially higher frequencies from H5N6 patients compared to those infected with other AIV subtypes. Evaluation of adaptive immunity showed that both humoral and cellular responses could be detected in the H5N6-infected survivor, but cellular responses were absent in the nonsurvivors. In addition, the surviving patient had lower concentrations of both pro- and anti-inflammatory cytokines/chemokines compared to the nonsurvivors. CONCLUSIONS: Our results support that H5N6 virus could potentially be a major public health threat, and suggest it is possible that the earlier acquisition of cellular immunity and lower concentrations of cytokines/chemokines contributed to survival in our patient. Analysis of more patient samples will be needed to draw concrete conclusions.

The first imported case of Rift Valley fever in China reveals a genetic reassortment of different viral lineages.

We report the first imported case of Rift Valley fever (RVF) in China. The patient returned from Angola, a non-epidemic country, with an infection of a new reassortant from different lineages of Rift Valley fever viruses (RVFVs). The patient developed multiorgan dysfunction and gradually recovered with continuous renal replacement therapy and a short regimen of methylprednisolone treatment. The disordered cytokines and chemokines in the plasma of the patient revealed hypercytokinemia, but the levels of protective cytokines were low upon admission and fluctuated as the disease improved. Whole-genome sequencing and phylogenetic analysis revealed that the imported strain was a reassortant comprising the L and M genes from lineage E and the S gene from lineage A. This case highlights that RVFV had undergone genetic reassortment, which could potentially alter its biological properties, cause large outbreaks and pose a serious threat to global public health as well as the livestock breeding industry.

FAT10 Is Critical in Influenza A Virus Replication by Inhibiting Type I IFN.

The H5N1 avian influenza virus causes severe disease and high mortality, making it a major public health concern worldwide. The virus uses the host cellular machinery for several steps of its life cycle. In this report, we observed overexpression of the ubiquitin-like protein FAT10 following live H5N1 virus infection in BALB/c mice and in the human respiratory epithelial cell lines A549 and BEAS-2B. Further experiments demonstrated that FAT10 increased H5N1 virus replication and decreased the viability of infected cells. Total RNA extracted from H5N1 virus-infected cells, but not other H5N1 viral components, upregulated FAT10, and this process was mediated by the retinoic acid-induced protein I-NF-κB signaling pathway. FAT10 knockdown in A549 cells upregulated type I IFN mRNA expression and enhanced STAT1 phosphorylation during live H5N1 virus infection. Taken together, our data suggest that FAT10 was upregulated via retinoic acid-induced protein I and NF-κB during H5N1 avian influenza virus infection. And the upregulated FAT10 promoted H5N1 viral replication by inhibiting type I IFN.

Fault location of two-parallel transmission line for double phase-to-earth fault using one-terminal data.

An accurate algorithm for fault location of double phase-to-earth fault on transmission line of direct ground neutral system is presented. The algorithm, which employs the faulted phase network and zero-sequence network as fault-location model in which the source impedance at the remote end is not involved, effectively eliminates the effect of load flow and fault resistance on the accuracy of fault location. The algorithm achieves accurate location by measuring only one local end data and is used in a procedure that provides automatic determination of faulted types and phases, and does not require the engineer to specify them. Simulation results showed the effectiveness of the algorithm under the condition of double phase-to-earth fault.