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Pichia pastoris is an established protein expression host mainly applied for the production of biopharmaceuticals and industrial enzymes. This methylotrophic yeast is a distinguished production system for its growth to very high cell densities, for the available strong and tightly regulated promoters, and for the options to produce gram amounts of recombinant protein per litre of culture both intracellularly and in secretory fashion. However, not every protein of interest is produced in or secreted by P. pastoris to such high titres. Frequently, protein yields are clearly lower, particularly if complex proteins are expressed that are hetero-oligomers, membrane-attached or prone to proteolytic degradation. The last few years have been particularly fruitful because of numerous activities in improving the expression of such complex proteins with a focus on either protein engineering or on engineering the protein expression host P. pastoris. This review refers to established tools in protein expression in P. pastoris and highlights novel developments in the areas of expression vector design, host strain engineering and screening for high-level expression strains. Breakthroughs in membrane protein expression are discussed alongside numerous commercial applications of P. pastoris derived proteins.

Dormancy-associated MADS-box (DAM) genes serve as crucial regulators of the endodormancy cycle in rosaceous plants. Although pear DAM genes have been identified previously, the lack of a high-quality reference genome and techniques to study gene function have prevented accurate genome-wide analysis and functional verification of such genes. Additionally, the contribution of other genes to the regulation of endodormancy release remains poorly understood. In this study, a high-quality genome assembly for 'Cuiguan' pear (Pyrus pyrifolia), which is a leading cultivar with a low chilling requirement cultivated in China, was constructed using PacBio and Hi-C technologies. Using this genome sequence, we revealed that pear DAM genes were tandemly clustered on Chr8 and Chr15 and were differentially expressed in the buds between 'Cuiguan' and the high-chilling-requirement cultivar 'Suli' during the dormancy cycle. Using a virus-induced gene silencing system, we determined the repressive effects of DAM genes on bud break. Several novel genes potentially involved in the regulation of endodormancy release were identified by RNA sequencing and H3K4me3 chromatin immunoprecipitation sequencing analyses of 'Suli' buds during artificial chilling using the new reference genome. Our findings enrich the knowledge of the regulatory mechanism underlying endodormancy release and chilling requirements and provide a foundation for the practical regulation of dormancy release in fruit trees as an adaptation to climate change.

Background NAC proteins contribute to diverse plant developmental processes as well as tolerances to biotic and abiotic stresses. The pear genome had been decoded and provided the basis for the genome-wide analysis to find the evolution, duplication, gene structures and predicted functions of PpNAC transcription factors. Results A total of 185 PpNAC genes were found in pear, of which 148 were mapped on chromosomes while 37 were on unanchored scaffolds. Phylogeny split the NAC genes into 6 clades (Group1- Group6) with their sub clades (~ subgroup A to subgroup H) and each group displayed common motifs with no/minor change. The numbers of exons in each group varied from 1 to 12 with an average of 3 while 44 pairs from all groups showed their duplication events. qPCR and RNA-Seq data analyses in different pear cultivars/species revealed some predicted functions of PpNAC genes i.e. PpNACs 37, 61, 70 (2A), 53, 151 (2D), 10, 92, 130 and 154 (3D) were potentially involved in bud endodormancy, PpNACs 61, 70 (2A), 172, 176 and 23 (4E) were associated with fruit pigmentations in blue light, PpNAC s 127 (1E), 46 (1G) and 56 (5A) might be related to early, middle and late fruit developments respectively. Besides, all genes from subgroups 2D and 3D were found to be related with abiotic stress (cold, salt and drought) tolerances by targeting the stress responsive genes in pear. Conclusions The present genome-wide analysis provided valuable information for understanding the classification, motif and gene structure, evolution and predicted functions of NAC gene family in pear as well as in higher plants. NAC TFs play diverse and multifunctional roles in biotic and abiotic stresses, growth and development and fruit ripening and pigmentation through multiple pathways in pear.

C-repeat binding factor/dehydration-responsive element (CBF/DRE) transcription factors (TFs) participate in a variety of adaptive mechanisms, and are involved in molecular signaling and abiotic stress tolerance in plants. In pear (Pyrus pyrifolia) and other rosaceous crops, the independent evolution of CBF subfamily members requires investigation to understand the possible divergent functions of these proteins. In this study, phylogenetic analysis divided six PpyCBFs from the Asian pear genome into three clades/subtypes, and collinearity and phylogenetic analyses suggested that PpyCBF3 was the mother CBF. All PpyCBFs were found to be highly expressed in response to low temperature, salt, drought, and abscisic acid (ABA) as well as bud endodormancy, similar to PpyCORs (PpyCOR47, PpyCOR15A, PpyRD29A, and PpyKIN). Transcript levels of clade II PpyCBFs during low temperature and ABA treatments were higher than those of clades I and III. Ectopic expression of PpyCBF2 and PpyCBF3 in Arabidopsis enhanced its tolerance against abiotic stresses, especially to low temperature in the first case and salt and drought stresses in the latter, and resulted in lower reactive oxygen species (ROS) and antioxidant gene activities compared with the wild type. The increased expression of endogenous ABA-dependent and -independent genes during normal conditions in PpyCBF2- and PpyCBF3-overexpressing Arabidopsis lines suggested that PpyCBFs were involved in both ABA-dependent and -independent pathways. All PpyCBFs, especially the mother CBF, had high transactivation activities with 6XCCGAC binding elements. Luciferase and Y1H assays revealed the existence of phylogenetically and promoter-dependent conserved CBF–COR cascades in the pear. The presence of a previously identified CCGA binding site, combined with the results of mutagenesis of the CGACA binding site of the PpyCOR15A promoter, indicated that CGA was a core binding element of PpyCBFs. In conclusion, PpyCBF TFs might operate redundantly via both ABA-dependent and -independent pathways, and are strongly linked to abiotic stress signaling and responses in the Asian pear.

Nowadays, electric load forecasting through a data analytic approach has become one of the most active and emerging research areas. It provides future consumption patterns of electric load. Since there are large fluctuations in both electricity production and use, it is a difficult task to achieve a balance between electric load and demand. By analyzing past electric consumption records to estimate the upcoming electricity load, the issue of fluctuating behavior can be resolved. In this study, a framework for feature selection, extraction, and regression is put forward to carry out the electric load prediction. The feature selection phase uses a combination of extreme gradient boosting (XGB) and random forest (RF) to determine the significance of each feature. Redundant features in the feature extraction approach are removed by applying recursive feature elimination (RFE). We propose an enhanced support vector machine (ESVM) and an enhanced convolutional neural network (ECNN) for the regression component. Hyperparameters of both the proposed approaches are set using the random search (RS) technique. To illustrate the effectiveness of our proposed strategies, a comparison is also performed between the state-of-the-art approaches and our proposed techniques. In addition, we perform statistical analyses to prove the significance of our proposed approaches. Simulation findings illustrate that our proposed approaches ECNN and ESVM achieve higher accuracies of 98.83% and 98.7%, respectively.

Background Thaumatin-like proteins (TLPs) are crucial pathogenesis-related proteins that significantly contribute to plant defense rection. Fusarium oxysporum f. sp. cubense ( Foc ) causes Fusarium wilt of bananas, a serious threat to global production. However, the role of TLPs in disease resistance remains unclear. Results This study identified 49 TLP genes in banana, predominantly localized in the extracellular space, and distributed across 11 chromosomes. The ancestor–descendant relationship was explained, six genes remained remarkably conserved across species could represent the ancestral genes of the TLP gene family. Promoter regions, transcriptome and qRT-PCR analysis suggested that MaTLP16 might be involved in disease resistance. Furthermore, transcriptional silencing of MaTLP16 resulted in more severe leaf damage compared to the control, indicating that MaTLP16 is an important Foc resistance-related gene. Conclusion This study conducted a comprehensive genome-wide identification and systematic analysis of the TLP gene family in bananas. Our findings establish a foundation for further functional studies of MaTLP genes and highlight MaTLP16 as a strong candidate for use in breeding programs aimed at enhancing resistance to Musa diseases.

There has been an outbreak of lung injury associated with e-cigarettes and vaping in the United States since early 2019. We present two cases who were admitted to the hospital with shortness of breath and cough. Chest imaging showed they had interstitial changes. They were diagnosed with e-cigarette and vaping product use-associated lung injury (EVALI) and treated with steroids and supportive management. With an improvement in symptoms, they were discharged home. On follow-up in the clinic, both patients were asymptomatic and had complete resolution of radiographic abnormalities. However, pulmonary function testing showed reduced diffusion capacity for carbon monoxide (DLCO). Total lung capacity (TLC), forced vital capacity (FVC), forced expiratory volume in the first one second (FEV-1), and the FEV-1/FVC ratio were normal.

After an outbreak in December 2019 in Wuhan, Hubei Province of China, coronavirus disease 2019 (COVID-19) has rapidly become a pandemic. The 2019 novel coronavirus (2019 nCov), now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causes a wide spectrum of illness and patients with underlying comorbidities have a high mortality. Here we present a 49-year-old male patient with comorbid conditions who presented with fever, cough, myalgia and shortness of breath for five days with likely exposure to a COVID-19 contact. A computed tomography scan of the thorax revealed multifocal bilateral ground-glass lung opacities with areas of subpleural sparing. He tested positive for SARS-CoV-2 by nucleic acid amplification. Hydroxychloroquine therapy was started, and the patient responded favorably with improvement of symptoms. Early diagnosis and self-isolation or quarantine remain key to stemming the tide of the contagion as there is a real risk of the healthcare system being overwhelmed.

Extracellular vesicles (EVs) produced by Fusarium oxysporum f. sp. cubense (Foc) play vital roles in plant–pathogen interactions; however, the isolation of purified Foc TR4-EVs and their pathogenicity and proteomic profiles are not well studied. This study aims to isolate and characterize purified Foc TR4-EVs and compare their pathogenic effects and protein profiles with crude TR4-EVs. Foc TR4-EVs were isolated using ultracentrifugation and purified by iodixanol gradient centrifugation. After characterization and evaluation of the pathogenicity effects on banana leaves, LC-MS/MS was performed to conduct the proteomics assay. Results indicated that Fraction 2 EVs exhibited clearer spherical structures (TEM), excessive abundance (1.70 × 109 particles/mL), greater intensity (400 a.u), mean size (154.5 nm), moderate protein content (333.16 ng/µL), and protein profile (25–77 kDa), which were superior to Fractions 1, 3, and crude EVs. Crude EVs displayed significant background interference with EV structures (TEM), highest abundance (2.11 × 109 particles/mL), lower intensity (7.0 a.u), higher protein content (528.33 ng/µL), and higher molecular weight proteins (55–70 kDa) compared to gradient EVs. A non-significant biocontrol effect of Foc-EVs on the growth of TR4 spores was observed. Pathogenicity assays revealed that crude EVs caused the largest (2.805 cm2), while Fraction 2 (1.386 cm2) and Fraction 3 (1.255 cm2) resulted in moderate lesions on banana leaves. Proteomic analysis identified 807 unique proteins in Fraction 2, enriched in pathways related to EV trafficking and signaling. In comparison, crude EVs contained 179 unique non-EV proteins related to metabolism and secondary metabolites, indicating that non-EV proteins of crude EVs also influence the pathogenicity observed in banana leaves. This study emphasizes the importance of EV purification, with Fraction 2 being a critical focus for future research on Foc EV pathogenicity.

Many healthcare centers are deploying advanced Internet of Things (IoT) based on Software-Defined Networks (SDNs). Transmission Control Protocol (TCP) was developed to control the data transmission in wide range of networks and provides reliable communication by using many caching and congestion control schemes. TCP is predestined to always increase and decrease its congestion window size to make changes in traffic. Nowadays, about 50% IoT based SDN traffic is controlled by TCP CUBIC, which is the default congestion control scheme in Linux operating system. The aim of this research is to develop a new content-caching based congestion control scheme for advanced IoT enabled SDN networks to achieve better performance in healthcare infrastructure network environments. In this research, Congestion Control Module for Loss Event (CCM-LE) is proposed to enhance the performance of TCP CUBIC in advanced IoT based on SDN. Network Simulator 2 (NS-2) is used to simulate the experiments of CCM-LE and state-of-the-art schemes. Results show that the performance of CCM-LE outperforms by 19% as compared to state-of-the-art schemes.