Characterization of a novel thermophilic cyanobacterium within Trichocoleusaceae, Trichothermofontia sichuanensis gen. et sp. nov., and its CO2-concentrating mechanism

Thermophiles from extreme thermal environments have shown tremendous potential regarding ecological and biotechnological applications. Nevertheless, thermophilic cyanobacteria remain largely untapped and are rarely characterized. Herein, a polyphasic approach was used to characterize a thermophilic strain, PKUAC-SCTB231 (hereafter B231), isolated from a hot spring (pH 6.62, 55.5°C) in Zhonggu village, China. The analyses of 16S rRNA phylogeny, secondary structures of 16S-23S ITS and morphology strongly supported strain B231 as a novel genus within Trichocoleusaceae. Phylogenomic inference and three genome-based indices further verified the genus delineation. Based on the botanical code, the isolate is herein delineated as Trichothermofontia sichuanensis gen. et sp. nov., a genus closely related to a validly described genus Trichocoleus. In addition, our results suggest that Pinocchia currently classified to belong to the family Leptolyngbyaceae may require revision and assignment to the family Trichocoleusaceae. Furthermore, the complete genome of Trichothermofontia B231 facilitated the elucidation of the genetic basis regarding genes related to its carbon-concentrating mechanism (CCM). The strain belongs to β-cyanobacteria according to its β-carboxysome shell protein and 1B form of Ribulose bisphosphate Carboxylase-Oxygenase (RubisCO). Compared to other thermophilic strains, strain B231contains a relatively low diversity of bicarbonate transporters (only BicA for HCO3− transport) but a higher abundance of different types of carbonic anhydrase (CA), β-CA (ccaA) and γ-CA (ccmM). The BCT1 transporter consistently possessed by freshwater cyanobacteria was absent in strain B231. Similar situation was occasionally observed in freshwater thermal Thermoleptolyngbya and Thermosynechococcus strains. Moreover, strain B231 shows a similar composition of carboxysome shell proteins (ccmK1-4, ccmL, -M, -N, -O, and -P) to mesophilic cyanobacteria, the diversity of which was higher than many thermophilic strains lacking at least one of the four ccmK genes. The genomic distribution of CCM-related genes suggests that the expression of some components is regulated as an operon and others in an independently controlled satellite locus. The current study also offers fundamental information for future taxogenomics, ecogenomics and geogenomic studies on distribution and significance of thermophilic cyanobacteria in the global ecosystem

Transcriptome and network analyses reveal key pathways and genes involved in response to carotenoid deposition in scallop muscle

Carotenoids are essential nutrients for humans and animals, and carotenoid content has become an important trait to evaluate the nutritional value of many cultured animals. Marine animals provide humans with diverse carotenoids, and developing carotenoid-enriched varieties has been the focus of marine animal breeding. Understanding the molecular mechanism of carotenoid deposition could benefit marine animal breeding for carotenoid content improvement. In the present study, transcriptomic analysis of adductor muscle was performed between Yesso scallop (Patinopecten yessoensis) with white muscle (WM) and carotenoid-enriched orange muscle (OM). A total of 683 differentially expressed genes (DEGs) were identified, with 302 and 381 genes being up- and down-regulated in OM scallop. Gene co-expression network analysis identified four carotenoid accumulation−related modules, including three up-regulated modules and one down-regulated module. The genes in up-regulated modules mainly participate in the pathways of translation and transcription (MEgreen), immune system (MElightyellow), and lipid metabolism (MEpink), while the down-regulated module is mainly enriched with genes involved in various metabolic pathways (MEturquoise). As the causal gene responsible for muscle coloration in scallop, PyBCO-like 1 is the hub gene of MEturquoise and showed strong connectivity with NR2F1A, a transcriptional factor involved in the regulation of retinoic acid. In addition, the up-regulated DEGs, including WDR3, RPP29, TBL3, RIOK2, and NOB1 from “ribosome biogenesis”, HSP70s and HSP702Bs from “antigen processing and presentation”, and ACOX1 from “PPAR signaling pathway” were identified as hub genes, indicating the potential regulatory role of these genes and pathways in response to carotenoid accumulation. Our data contribute to a deeper understanding of the regulatory and response mechanisms of carotenoid accumulation in marine animals

Design and Optimize the Performance of Self-Powered Photodetector Based on PbS/TiS3 Heterostructure by SCAPS-1D

Titanium trisulphide (TiS3) has been widely used in the field of optoelectronics owing to its superb optical and electronic characteristics. In this work, a self-powered photodetector using bulk PbS/TiS3 p-n heterojunction is numerically investigated and analyzed by a Solar Cell Capacitance Simulator in one-Dimension (SCAPS-1D) software. The energy bands, electron-holes generation or recombination rate, current density-voltage (J-V), and spectral response properties have been investigated by SCAPS-1D. To improve the performance of photodetectors, the influence of thickness, shallow acceptor or donor density, and defect density are investigated. By optimization, the optimal thickness of the TiS3 layer and PbS layer are determined to be 2.5 μm and 700 nm, respectively. The density of the superior shallow acceptor (donor) is 1015 (1022) cm−3. High quality TiS3 film is required with the defect density of about 1014 cm−3. For the PbS layer, the maximum defect density is 1017 cm−3. As a result, the photodetector based on the heterojunction with optimal parameters exhibits a good photoresponse from 300 nm to 1300 nm. Under the air mass 1.5 global tilt (AM 1.5G) illuminations, the optimal short-circuit current reaches 35.57 mA/cm2 and the open circuit voltage is about 870 mV. The responsivity (R) and a detectivity (D*) of the simulated photodetector are 0.36 A W−1 and 3.9 × 1013 Jones, respectively. The simulation result provides a promising research direction to further broaden the TiS3-based optoelectronic device

Design and Optimize the Performance of Self-Powered Photodetector Based on PbS/TiS₃ Heterostructure by SCAPS-1D

Titanium trisulphide (TiS3) has been widely used in the field of optoelectronics owing to its superb optical and electronic characteristics. In this work, a self-powered photodetector using bulk PbS/TiS3 p-n heterojunction is numerically investigated and analyzed by a Solar Cell Capacitance Simulator in one-Dimension (SCAPS-1D) software. The energy bands, electron-holes generation or recombination rate, current density-voltage (J-V), and spectral response properties have been investigated by SCAPS-1D. To improve the performance of photodetectors, the influence of thickness, shallow acceptor or donor density, and defect density are investigated. By optimization, the optimal thickness of the TiS3 layer and PbS layer are determined to be 2.5 μm and 700 nm, respectively. The density of the superior shallow acceptor (donor) is 1015 (1022) cm−3. High quality TiS3 film is required with the defect density of about 1014 cm−3. For the PbS layer, the maximum defect density is 1017 cm−3. As a result, the photodetector based on the heterojunction with optimal parameters exhibits a good photoresponse from 300 nm to 1300 nm. Under the air mass 1.5 global tilt (AM 1.5G) illuminations, the optimal short-circuit current reaches 35.57 mA/cm2 and the open circuit voltage is about 870 mV. The responsivity (R) and a detectivity (D*) of the simulated photodetector are 0.36 A W−1 and 3.9 × 1013 Jones, respectively. The simulation result provides a promising research direction to further broaden the TiS3-based optoelectronic device

Theoretical Studies on Selectivity of HPK1/JAK1 Inhibitors by Molecular Dynamics Simulations and Free Energy Calculations

Hematopoietic progenitor kinase 1 (HPK1) is a negative regulator of T cell receptor, which has been regarded as a potential target for immunotherapy. Yu et al. observed the off-target effect of the high-throughput screening HPK1 kinase inhibitor hits on JAK1 kinase. The off-target effect is usually due to the lack of specificity of the drug, resulting in toxic side effects. Therefore, exploring the mechanisms to selectively inhibit HPK1 is critical for developing effective and safe inhibitors. In this study, two indazole compounds as HPK1 inhibitors with different selectivity towards JAK1 were used to investigate the selectivity mechanism using multiple computational methods, including conventional molecular dynamics simulations, binding free energy calculations and umbrella sampling simulations. The results indicate that the salt bridge between the inhibitor and residue Asp101 of HPK1 favors their selectivity towards HPK1 over JAK1. Information obtained from this study can be used to discover and design more potent and selective HPK1 inhibitors for immunotherapy

Active learning with sampling by uncertainty and density for word sense disambiguation and text classification

This paper addresses two issues of active learning. Firstly, to solve a problem of uncertainty sampling that it often fails by selecting outliers, this paper presents a new selective sampling technique, sampling by uncertainty and density (SUD), in which a k-Nearest-Neighbor-based density measure is adopted to determine whether an unlabeled example is an outlier. Secondly, a technique of sampling by clustering (SBC) is applied to build a representative initial training data set for active learning. Finally, we implement a new algorithm of active learning with SUD and SBC techniques. The experimental results from three real-world data sets show that our method outperforms competing methods, particularly at the early stages of active learning.

Reevaluation of <i>Parasynechococcus</i>-like Strains and Genomic Analysis of Their Microsatellites and Compound Microsatellites

Morphologically similar to Synechococcus, a large number of Parasynechococcus strains were misclassified, resulting in extreme underestimation of their genetic diversity. In this study, 80 Synechococcus-like strains were reevaluated using a combination of 16S rRNA phylogeny and genomic approach, identifying 54 strains as Parasynechococcus-like strains and showing considerably intragenus genetic divergence among the subclades identified. Further, bioinformatics analysis disclosed diversified patterns of distribution, abundance, density, and diversity of microsatellites (SSRs) and compound microsatellites (CSSRs) in genomes of these Parasynechococcus-like strains. Variations of SSRs and CSSRs were observed amongst phylotypes and subclades. Both SSRs and CSSRs were in particular unequally distributed among genomes. Dinucleotide SSRs were the most widespread, while the genomes showed two patterns in the second most abundant repeat type (mononucleotide or trinucleotide SSRs). Both SSRs and CSSRs were predominantly observed in coding regions. These two types of microsatellites showed positive correlation with genome size (p p n, (AG)n and (AGC)n was a major one in the corresponding category. Meanwhile, distinctive motifs of CSSRs were found in 39 genomes. This study characterizes SSRs and CSSRs in genomes of Parasynechococcus-like strains and will be useful as a prerequisite for future studies regarding their distribution, function, and evolution. Moreover, the identified SSRs may facilitate fast acclimation of Parasynechococcus-like strains to fluctuating environments and contribute to the extensive distribution of Parasynechococcus species in global marine environments

Saprophytic <i>Bacillus</i> Accelerates the Release of Effective Components in Agarwood by Degrading Cellulose

The value of Agarwood increases with time due to the gradual release of its major components, but the mechanism behind this remains unclear. Herein we reveal that the potential driving force of this process is the degradation of cellulose in Agarwood by its saprophytic Bacillus subtilis. We selected 10-year-old Agarwood from different places and then isolated the saprophytic bacteria. We confirmed these bacteria from different sources are all Bacillus and confirmed they can degrade cellulose, and the highest cellulase activity reached 0.22 U/mL. By co-cultivation of the bacterium and Agarwood powder, we found that three of the strains could release the effective components of Agarwood, while they had little effect in increasing the same components in living Aquilaria sinensis. Finally, we demonstrated that these saprophytic Bacillus subtilis have similar effects on Zanthoxylum bungeanum Maxim and Dalbergiaod orifera T. Chen, but not on Illicium verum Hook. f, Cinnamomum cassia Presl and Phellodendron chinense Schneid. In conclusion, our experiment revealed that the saprophytic Bacillus release the effective components of Agarwood by degrading cellulose, and we provide a promising way to accelerate this process by using this bacterial agent

Distinct Molecular Patterns of Two-Component Signal Transduction Systems in Thermophilic Cyanobacteria as Revealed by Genomic Identification

Two-component systems (TCSs) play crucial roles in sensing and responding to environmental signals, facilitating the acclimation of cyanobacteria to hostile niches. To date, there is limited information on the TCSs of thermophilic cyanobacteria. Here, genome-based approaches were used to gain insights into the structure and architecture of the TCS in 17 well-described thermophilic cyanobacteria, namely strains from the genus Leptodesmis, Leptolyngbya, Leptothermofonsia, Thermoleptolyngbya, Thermostichus, and Thermosynechococcus. The results revealed a fascinating complexity and diversity of the TCSs. A distinct composition of TCS genes existed among these thermophilic cyanobacteria. A majority of TCS genes were classified as orphan, followed by the paired and complex cluster. A high proportion of histidine kinases (HKs) were predicted to be cytosolic subcellular localizations. Further analyses suggested diversified domain architectures of HK and response regulators (RRs), putatively in association with various functions. Comparative and evolutionary genomic analyses indicated that the horizontal gene transfer, as well as duplications events, might be involved in the evolutionary history of TCS genes in Thermostichus and Thermosynechococcus strains. A comparative analysis between thermophilic and mesophilic cyanobacteria indicated that one HK cluster and one RR cluster were uniquely shared by all the thermophilic cyanobacteria studied, while two HK clusters and one RR cluster were common to all the filamentous thermophilic cyanobacteria. These results suggested that these thermophile-unique clusters may be related to thermal characters and morphology. Collectively, this study shed light on the TCSs of thermophilic cyanobacteria, which may confer the necessary regulatory flexibility; these findings highlight that the genomes of thermophilic cyanobacteria have a broad potential for acclimations to environmental fluctuations

Construction of Recurrence Risk Prediction Model for Diabetic Foot Ulcer on the Basis of Logistic Regression, Support Vector Machine and BP Neural Network Model

Background The rates of first and multiple recurrence of diabetic foot ulcers (DFUs) are increasing annually worldwide, and the risk of early recurrence is higher than the distant recurrence. There are numerous risk factors for DFUs recurrence, and there is a lack of systematic screening. Therefore, there is a need to explore the risk factors for DFUs recurrence in order to identify high-risk population of recurrence at an early stage. Objective To explore the predictive value of Logistic regression (LR), support vector machine (SVM), BP neural network model (BPNN) in the recurrence risk of DFUs. Methods From January 2020 to October 2021, a total of patients with DFUs attending the Department of Burn Plastic Surgery, Endocrinology and Wound Ostomy Outpatient Department in General Hospital of Ningxia Medical University were selected as the research objects and divided into the recurrence group (n=116, 29.7%) and non-recurrence group (n=274, 70.3%) according to the recurrence of DFUs within 1 year after discharge. General information was collected and compared between the two groups of patients, including sociodemographic characteristics, medical history assessment and clinical case information. The Diabetes Foot Self-care Behavior Scale (DFSBS) was used to assess the self-management behavior of diabetes foot in patients and chronic diseases risk perception questionnaire was used to assess the risk perception level of DFUs among patients. Multivariable Logistic regression analysis was used to explore the influencing factors of DFUs recurrence in patients within 1 year after discharge. The patients were divided into training and test sets according to the ratio of 7 to 3, the LR, SVM and BPNN recurrence risk prediction models were developed based on Logistic regression variable screening strategy. The receiver operating characteristic (ROC) curves of each model were plotted to predict the recurrence risk of DFUs. Results There were significant differences in BMI, living alone, duration of diabetes, history of smoking, history of alcohol consumption, history of involved toe amputation, classification of diabetic foot ulcers, ankle-brachial index, glycated hemoglobin, sole ulcer, toe involvement, walking impairment, osteomyelitis, multidrug-resistant bacteria infection, diabetic peripheral neuropathy, lower limb atherosclerosis, self-management behavior of diabetes foot, level of risk perception in both groups of DFUs patients (P&lt;0.05). Multivariable Logistic regression analysis showed that BMI〔OR=0.394, 95%CI (0.285, 0.546), P&lt;0.001〕, duration of diabetes〔OR=1.635, 95%CI (1.303, 2.051), P&lt;0.001〕, history of smoking〔OR=0.186, 95%CI (0.080, 0.434), P&lt;0.001〕, classification of diabetic foot ulcers〔OR=2.139, 95%CI (1.133, 4.038), P=0.019〕, glycated hemoglobin〔OR=2.289, 95%CI (1.485, 3.528), P&lt;0.001〕, sole ulcer〔OR=3.148, 95%CI (1.344, 7.373), P=0.008〕, self-management behavior of diabetes foot〔OR=0.744, 95%CI (0.673, 0.822), P&lt;0.001〕and level of risk perception〔OR=0.892, 95%CI (0.845, 0.942), P&lt;0.001〕were influencing factors of the recurrence of DFUs within 1 year (P&lt;0.05). The accuracy rates of LR, SVM and BPNN models to predict the recurrence risk of DFUs in the test sets were 82.43%, 94.87% and 87.17%, with AUCs of 0.843, 0.937 and 0.820, respectively. There were significant differences in AUC of ROC curves of LR, SVM and BPNN recurrence risk prediction models of DFUs (Z=2.741, P&lt;0.05) ; the AUC of ROC curve of SVM recurrence risk prediction model was higher than the LR and BPNN models (Z=5.937, P=0.013; Z=3.946, P&lt;0.001) . Conclusion SVM model can predict the recurrence risk of DFUs patients within 1 year after discharge with good accuracy rate, sensitivity, specificity, AUC and other indicators, which is the relative optimal model. It is recommended to further promote and apply the prediction model to verify its effectiveness