Divalent cations activate TRPV1 through promoting conformational change of the extracellular region

Divalent cations Mg and Ba selectively and directly potentiate transient receptor potential vanilloid type 1 heat activation by lowering the activation threshold into the room temperature range. We found that Mg potentiates channel activation only from the extracellular side; on the intracellular side, Mg inhibits channel current. By dividing the extracellularly accessible region of the channel protein into small segments and perturbing the structure of each segment with sequence replacement mutations, we observed that the S1-S2 linker, the S3-S4 linker, and the pore turret are all required for Mg potentiation. Sequence replacements at these regions substantially reduced or eliminated Mg-induced activation at room temperature while sparing capsaicin activation. Heat activation was affected by many, but not all, of these structural alternations. These observations indicate that extracellular linkers and the turret may interact with each other. Site-directed fluorescence resonance energy transfer measurements further revealed that, like heat, Mg also induces structural changes in the pore turret. Interestingly, turret movement induced by Mg precedes channel activation, suggesting that Mg-induced conformational change in the extracellular region most likely serves as the cause of channel activation instead of a coincidental or accommodating structural adjustment

Morphological and Comparative Transcriptome Analysis of Three Species of Five-Needle Pines: Insights Into Phenotypic Evolution and Phylogeny

Pinus koraiensis, Pinus sibirica, and Pinus pumila are the major five-needle pines in northeast China, with substantial economic and ecological values. The phenotypic variation, environmental adaptability and evolutionary relationships of these three five-needle pines remain largely undecided. It is therefore important to study their genetic differentiation and evolutionary history. To obtain more genetic information, the needle transcriptomes of the three five-needle pines were sequenced and assembled. To explore the relationship of sequence information and adaptation to a high mountain environment, data on needle morphological traits [needle length (NL), needle width (NW), needle thickness (NT), and fascicle width (FW)] and 19 climatic variables describing the patterns and intensity of temperature and precipitation at six natural populations were recorded. Geographic coordinates of altitude, latitude, and longitude were also obtained. The needle morphological data was combined with transcriptome information, location, and climate data, for a comparative analysis of the three five-needle pines. We found significant differences for needle traits among the populations of the three five-needle pine species. Transcriptome analysis showed that the phenotypic variation and environmental adaptation of the needles of P. koraiensis, P. sibirica, and P. pumila were related to photosynthesis, respiration, and metabolites. Analysis of orthologs from 11 Pinus species indicated a closer genetic relationship between P. koraiensis and P. sibirica compared to P. pumila. Our study lays a foundation for genetic improvement of these five-needle pines and provides insights into the adaptation and evolution of Pinus species

Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys

The performance of advanced materials for extreme environments is underpinned by their microstructure, such as the size and distribution of nano- to micro-sized reinforcing phase(s). Chromium-based superalloys are a recently proposed alternative to conventional face-centred-cubic superalloys for high-temperature applications, e.g., Concentrated Solar Power. Their development requires the determination of precipitate volume fraction and size distribution using Electron Microscopy (EM), as these properties are crucial for the thermal stability and mechanical properties of chromium superalloys. Traditional approaches to EM image processing utilise filtering with a fixed contrast threshold, leads to weak robustness to background noise and poor generalisability to different materials. It also requires an enormous amount of time for manual object measurements on large datasets. Efficient and accurate object detection and segmentation are therefore highly desired to accelerate the development of novel materials like chromium-based superalloys. To address these bottlenecks, based on YOLOv5 and SegFormer structures, this study proposes an end-to-end, two-stage deep learning scheme, DT-SegNet, to perform object detection and segmentation for EM images. The proposed approach can thus benefit from the training efficiency of CNNs at the detection stage (i.e., a small number of training images required) and the accuracy of the ViT at the segmentation stage. Extensive numerical experiments demonstrate that the proposed DT-SegNet significantly outperforms the state-of-the-art segmentation tools offered by Weka and ilastik regarding a large number of metrics, including accuracy, precision, recall and F1-score. This model forms a useful tool to aid alloy development microstructure examinations, and offers significant advantages to address the large datasets associated with highthroughput alloy development approaches

Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys

The performance of advanced materials for extreme environments is underpinned by their microstructure, such as the size and distribution of nano- to micro-sized reinforcing phase(s). Chromium-based superalloys are a recently proposed alternative to conventional face-centred-cubic superalloys for high-temperature applications, e.g., Concentrated Solar Power. Their development requires the determination of precipitate volume fraction and size distribution using Electron Microscopy (EM), as these properties are crucial for the thermal stability and mechanical properties of chromium superalloys. Traditional approaches to EM image processing utilise filtering with a fixed contrast threshold, leads to weak robustness to background noise and poor generalisability to different materials. It also requires an enormous amount of time for manual object measurements on large datasets. Efficient and accurate object detection and segmentation are therefore highly desired to accelerate the development of novel materials like chromium-based superalloys. To address these bottlenecks, based on YOLOv5 and SegFormer structures, this study proposes an end-to-end, two-stage deep learning scheme, DT-SegNet, to perform object detection and segmentation for EM images. The proposed approach can thus benefit from the training efficiency of CNNs at the detection stage (i.e., a small number of training images required) and the accuracy of the ViT at the segmentation stage. Extensive numerical experiments demonstrate that the proposed DT-SegNet significantly outperforms the state-of-the-art segmentation tools offered by Weka and ilastik regarding a large number of metrics, including accuracy, precision, recall and F1-score. This model forms a useful tool to aid alloy development microstructure examinations, and offers significant advantages to address the large datasets associated with high-throughput alloy development approaches

On electronic structure of polymer-derived amorphous silicon carbide ceramics

The electronic structure of polymer-derived amorphous silicon carbide ceramics was studied by combining measurements of temperature-dependent conductivity and optical absorption. By comparing the experimental results to theoretical models, electronic structure was constructed for a carbon-rich amorphous silicon carbide, which revealed several unique features, such as deep defect energy level, wide band-tail band, and overlap between the band-tail band and defect level. These unique features were discussed in terms of the microstructure of the material and used to explain the electric behavior

Cellular immunotherapy as maintenance therapy prolongs the survival of the patients with small cell lung cancer in extensive stage

AbstractBackgroundSmall cell lung cancer (SCLC) is the most devastating type of human lung cancer. Patients usually present with disseminated disease to many organs (extensive stage). This study was to investigate the efficacy and safety of cellular immunotherapy (CIT) with autologous natural killer (NK), γδT, and cytokine-induced killer (CIK) cells as maintenance therapy for extensive-stage SCLC (ES-SCLC) patients.MethodsA pilot prospective cohort study was conducted with ES-SCLC patients who had responded to initial chemotherapy. Patients received either CIT as maintenance therapy (CIT group), or no treatment (control group). Progression-free survival (PFS), overall survival (OS), and adverse effects were compared.ResultsForty-nine patients were recruited in this study, with 19 patients in the CIT group and 30 patients in the control group. The patient characteristics of the 2 groups were comparable except for age, as patients in the CIT group were older than those in the control group (P < 0.05). PFS in the CIT group was superior to the control group (5 vs. 3.1 months, P = 0.020; HR, 0.489, 95% CI, 0.264–0.909, P = 0.024). OS of the CIT group was also longer than that of the control group (13.3 vs. 8.2 months, P = 0.044; HR, 0.528, 95% CI, 0.280–0.996, P = 0.048, respectively). No significant adverse reactions occurred in patients undergoing CIT.ConclusionsCIT maintenance therapy in ES-SCLC prolonged survival with only minimal side effects. Integrating CIT into the current treatment may be a novel strategy for ES-SCLC patients, although further multi-center randomized trials are needed

Production of Transgenic Pigs with an Introduced Missense Mutation of the Bone Morphogenetic Protein Receptor Type IB Gene Related to Prolificacy

In the last few decades, transgenic animal technology has witnessed an increasingly wide application in animal breeding. Reproductive traits are economically important to the pig industry. It has been shown that the bone morphogenetic protein receptor type IB (BMPR1B) A746G polymorphism is responsible for the fertility in sheep. However, this causal mutation exits exclusively in sheep and goat. In this study, we attempted to create transgenic pigs by introducing this mutation with the aim to improve reproductive traits in pigs. We successfully constructed a vector containing porcine BMPR1B coding sequence (CDS) with the mutant G allele of A746G mutation. In total, we obtained 24 cloned male piglets using handmade cloning (HMC) technique, and 12 individuals survived till maturation. A set of polymerase chain reactions indicated that 11 of 12 matured boars were transgene-positive individuals, and that the transgenic vector was most likely disrupted during cloning. Of 11 positive pigs, one (No. 11) lost a part of the terminator region but had the intact promoter and the CDS regions. cDNA sequencing showed that the introduced allele (746G) was expressed in multiple tissues of transgene-positive offspring of No.11. Western blot analysis revealed that BMPR1B protein expression in multiple tissues of transgene-positive F1 piglets was 0.5 to 2-fold higher than that in the transgene-negative siblings. The No. 11 boar showed normal litter size performance as normal pigs from the same breed. Transgene-positive F1 boars produced by No. 11 had higher semen volume, sperm concentration and total sperm per ejaculate than the negative siblings, although the differences did not reached statistical significance. Transgene-positive F1 sows had similar litter size performance to the negative siblings, and more data are needed to adequately assess the litter size performance. In conclusion, we obtained 24 cloned transgenic pigs with the modified porcine BMPR1B CDS using HMC. cDNA sequencing and western blot indicated that the exogenous BMPR1B CDS was successfully expressed in host pigs. The transgenic pigs showed normal litter size performance. However, no significant differences in litter size were found between transgene-positive and negative sows. Our study provides new insight into producing cloned transgenic livestock related to reproductive traits

Resistance to autosomal dominant Alzheimer's disease in an APOE3 Christchurch homozygote: a case report.

We identified a PSEN1 (presenilin 1) mutation carrier from the world's largest autosomal dominant Alzheimer's disease kindred, who did not develop mild cognitive impairment until her seventies, three decades after the expected age of clinical onset. The individual had two copies of the APOE3 Christchurch (R136S) mutation, unusually high brain amyloid levels and limited tau and neurodegenerative measurements. Our findings have implications for the role of APOE in the pathogenesis, treatment and prevention of Alzheimer's disease