Stable blue phosphorescent organic LEDs that use polariton-enhanced Purcell effects.

Phosphorescent organic light-emitting diodes (PHOLEDs) feature high efficiency1,2, brightness and colour tunability suitable for both display and lighting applications3. However, overcoming the short operational lifetime of blue PHOLEDs remains one of the most challenging high-value problems in the field of organic electronics. Their short lifetimes originate from the annihilation of high-energy, long-lived blue triplets that leads to molecular dissociation4-7. The Purcell effect, the enhancement of the radiative decay rate in a microcavity, can reduce the triplet density and, hence, the probability of destructive high-energy triplet-polaron annihilation (TPA)5,6 and triplet-triplet annihilation (TTA) events4,5,7,8. Here we introduce the polariton-enhanced Purcell effect in blue PHOLEDs. We find that plasmon-exciton polaritons9 (PEPs) substantially increase the strength of the Purcell effect and achieve an average Purcell factor (PF) of 2.4 ± 0.2 over a 50-nm-thick emission layer (EML) in a blue PHOLED. A 5.3-fold improvement in LT90 (the time for the PHOLED luminance to decay to 90% of its initial value) of a cyan-emitting Ir-complex device is achieved compared with its use in a conventional PHOLED. Shifting the chromaticity coordinates to (0.14, 0.14) and (0.15, 0.20) into the deep blue, the Purcell-enhanced devices achieve 10-14 times improvement over similarly deep-blue PHOLEDs, with one structure reaching the longest Ir-complex device lifetime of LT90 = 140 ± 20 h reported so far10-21. The polariton-enhanced Purcell effect and microcavity engineering provide new possibilities for extending deep-blue PHOLED lifetimes.

SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. Addressing this biological complexity requires innovative and accurate tools for trait prediction. In response to this challenge, we have developed SoyDNGP, a deep learning-based model that offers significant advancements in the field of soybean trait prediction. Compared to existing methods, such as DeepGS and DNNGP, SoyDNGP boasts a distinct advantage due to its minimal increase in parameter volume and superior predictive accuracy. Through rigorous performance comparison, including prediction accuracy and model complexity, SoyDNGP represents improved performance to its counterparts. Furthermore, it effectively predicted complex traits with remarkable precision, demonstrating robust performance across different sample sizes and trait complexities. We also tested the versatility of SoyDNGP across multiple crop species, including cotton, maize, rice and tomato. Our results showed its consistent and comparable performance, emphasizing SoyDNGP's potential as a versatile tool for genomic prediction across a broad range of crops. To enhance its accessibility to users without extensive programming experience, we designed a user-friendly web server, available at http://xtlab.hzau.edu.cn/SoyDNGP. The server provides two features: 'Trait Lookup', offering users the ability to access pre-existing trait predictions for over 500 soybean accessions, and 'Trait Prediction', allowing for the upload of VCF files for trait estimation. By providing a high-performing, accessible tool for trait prediction, SoyDNGP opens up new possibilities in the quest for optimized soybean breeding.

PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.

N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, is involved in gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A modification is important for understanding its molecular mechanisms in different biological contexts. However, most existing models have limited range of application and are species-centric. Here we present PEA-m6A, a unified, modularized and parameterized framework that can streamline m6A-Seq data analysis for predicting m6A-modified regions in plant genomes. The PEA-m6A framework builds ensemble learning-based m6A prediction models with statistic-based and deep learning-driven features, achieving superior performance with an improvement of 6.7% to 23.3% in the area under precision-recall curve compared with state-of-the-art regional-scale m6A predictor WeakRM in 12 plant species. Especially, PEA-m6A is capable of leveraging knowledge from pretrained models via transfer learning, representing an innovation in that it can improve prediction accuracy of m6A modifications under small-sample training tasks. PEA-m6A also has a strong capability for generalization, making it suitable for application in within- and cross-species m6A prediction. Overall, this study presents a promising m6A prediction tool, PEA-m6A, with outstanding performance in terms of its accuracy, flexibility, transferability, and generalization ability. PEA-m6A has been packaged using Galaxy and Docker technologies for ease of use and is publicly available at https://github.com/cma2015/PEA-m6A.

Silicon-based transient electronics: principles, devices and applications.

Recent advances in materials science, device designs and advanced fabrication technologies have enabled the rapid development of transient electronics, which represents a class of devices or systems that their functionalities and constitutions can be partially/completely degraded via chemical reaction or physical disintegration over a stable operation. Therefore, numerous potentials, including zero/reduced waste electronics, bioresorbable electronic implants, hardware security, and others, are expected. In particular, transient electronics with biocompatible and bioresorbable properties could completely eliminate the secondary retrieval surgical procedure after their in-body operation, thus offering significant potentials for biomedical applications. In terms of material strategies for the manufacturing of transient electronics, silicon nanomembranes (SiNMs) are of great interest because of their good physical/chemical properties, modest mechanical flexibility (depending on their dimensions), robust and outstanding device performances, and state-of-the-art manufacturing technologies. As a result, continuous efforts have been made to develop silicon-based transient electronics, mainly focusing on designing manufacturing strategies, fabricating various devices with different functionalities, investigating degradation or failure mechanisms, and exploring their applications. In this review, we will summarize the recent progresses of silicon-based transient electronics, with an emphasis on the manufacturing of SiNMs, devices, as well as their applications. After a brief introduction, strategies and basics for utilizing SiNMs for transient electronics will be discussed. Then, various silicon-based transient electronic devices with different functionalities are described. After that, several examples regarding on the applications, with an emphasis on the biomedical engineering, of silicon-based transient electronics are presented. Finally, summary and perspectives on transient electronics are exhibited.

Parkinson's disease patients combined with constipation tend to have higher serum expression of microRNA 29c, prominent neuropsychiatric disorders, possible RBD conversion, and a substandard quality of life.

INTRODUCTION: The symptom of constipation has been confirmed as an early diagnose criteria for Parkinson's disease (PD). Furthermore, evidences suggest that pathogenesis of PD initiates in gut, rather than brain. If so, identifying biomarkers for constipation in PD might have potentials to assist early diagnosis and initial treatment. METHOD: We first identified that microRNA 29c (miR-29c) was dysregulated both in PD and constipation patients through bioinformatics analysis. Then, serological analysis of the expression of miR-29c in 67 PD patients with constipation (PD-C), 51 PD patients without constipation (PD-NC), and 50 healthy controls (HC) was carried out by qPCR. Demographic and clinical features were also compared. Patients in PD-C group were further classified into two groups: those with prodromal stage constipation (PD-C-Pro) (n = 36) and those with clinical stage constipation (PD-C-Clinic) (n = 31), to explore their different characteristics. RESULTS: The levels of miR-29c in PD-C group were higher than that in PD-NC group, both higher than HC group. PD-C-Pro group's miR-29c levels were statistically higher compared with PD-C-Clinic group's. What is more, PD-C group had higher scores of MDS-UPDRS-I, NMSS, NMSS3, NMSS4, NMSS6, NMSS9, SCOPA-AUT, HAMD, HAMA, RBDSQ, CSS, and PACQOL compared with PD-NC party. Relative to the PD-C-Clinic, patients in PD-C-Pro group had higher MDS-UPDRS-I, NMSS, NMSS3, HAMD, and HAMA scores, and were more likely to have RBD. CONCLUSION: Our results indicated that miR-29c seems to be an underlying cause for developing constipation in patients with PD and PD-C identifies a group of patients with more severe non-motor impairment, prominent neuropsychiatric disorders, and possible RBD conversion as well as a substandard quality of life. We further confirmed that there is a close relationship between symptoms representing the same pathological origin, especially constipation and RBD.

Identifying the potential role of serum miR-20a as a biomarker for olfactory dysfunction in patients with Parkinson's disease.

INTRODUCTION: Olfactory dysfunction (OD), one of the most common non-motor symptoms in Parkinson's disease (PD), is a cardinal prodromal symptom that can appear years before the onset of motor symptoms. Ongoing studies have demonstrated that microRNAs (miRNAs) are suitable biomarkers for PD, while there is a lack of robust miRNAs that can serve as markers for OD in PD. METHODS: The concordantly differentially expressed miRNAs (DE miRNAs) in the damaged olfactory system were first identified in 2 OD-related Gene Expression Omnibus (GEO) datasets. Then, they were verified in another PD-related GEO dataset and only one miRNA (miR-20a) was found to be significantly altered. Serum levels of miR-20a were further measured by qPCR in 79 PD patients with OD (PD-OD), 52 PD patients without OD (PD-NOD), and 52 healthy controls (HC). Objective measure of OD was defined by 16-item Sniffin' Sticks odor identification test. All the participants underwent a demographic and comprehensive PD-related clinical assessment. RESULTS: Our results proved that miR-20a was significantly downregulated in PD-OD compared with PD-NOD and the area under curve (AUC) for OD detection by miR-20a was 0.803 (95% confidence interval, 0.724-0.883). In addition, PD-OD had higher scores of Movement Disorder Society-Unified Parkinson's Disease Rating Scale (UPDRS) II, Hoehn and Yahr stage (H-Y), Non-Motor Symptoms Scale (NMSS) 3, NMSS 5, NMSS 9, Hamilton Rating Scale for Depression (HAMD), Hamilton Anxiety Scale (HAMA), Activity of Daily Living (ADL), and lower scores of Mini-Mental State Examination (MMSE) and 39-item PD Quality of Life Questionnaire (PDQ-39) than PD-NOD. Binary regression model further presented that lower expressions of miR-20a and poorer cognitive function acted as promoting factors in the development of OD. CONCLUSION: Our results suggest that miR-20a could be a novel biomarker for OD in PD and PD-OD patients tend to have higher disease stage, poorer motor aspects of experiences of daily living, worse cognitive scores, and inferior quality of life, and were more likely to have mental disorders. Cognitive function, in particular, is strongly associated with OD in PD patients.

A Lightweight Recognition Method for Rice Growth Period Based on Improved YOLOv5s.

The identification of the growth and development period of rice is of great significance to achieve high-yield and high-quality rice. However, the acquisition of rice growth period information mainly relies on manual observation, which has problems such as low efficiency and strong subjectivity. In order to solve these problems, a lightweight recognition method is proposed to automatically identify the growth period of rice: Small-YOLOv5, which is based on improved YOLOv5s. Firstly, the new backbone feature extraction network MobileNetV3 was used to replace the YOLOv5s backbone network to reduce the model size and the number of model parameters, thus improving the detection speed of the model. Secondly, in the feature fusion stage of YOLOv5s, we introduced a more lightweight convolution method, GsConv, to replace the standard convolution. The computational cost of GsConv is about 60-70% of the standard convolution, but its contribution to the model learning ability is no less than that of the standard convolution. Based on GsConv, we built a lightweight neck network to reduce the complexity of the network model while maintaining accuracy. To verify the performance of Small-YOLOv5s, we tested it on a self-built dataset of rice growth period. The results show that compared with YOLOv5s (5.0) on the self-built dataset, the number of the model parameter was reduced by 82.4%, GFLOPS decreased by 85.9%, and the volume reduced by 86.0%. The mAP (0.5) value of the improved model was 98.7%, only 0.8% lower than that of the original YOLOv5s model. Compared with the mainstream lightweight model YOLOV5s- MobileNetV3-Small, the number of the model parameter was decreased by 10.0%, the volume reduced by 9.6%, and the mAP (0.5:0.95) improved by 5.0%-reaching 94.7%-and the recall rate improved by 1.5%-reaching 98.9%. Based on experimental comparisons, the effectiveness and superiority of the model have been verified.

Improved volume variable cluster model method for crystal-lattice optimization: effect on isotope fractionation factor.

The isotopic fractionation factor and element partition coefficient can be calculated only after the geometric optimization of the molecular clusters is completed. Optimization directly affects the accuracy of some parameters, such as the average bond length, molecular volume, harmonic vibrational frequency, and other thermodynamic parameters. Here, we used the improved volume variable cluster model (VVCM) method to optimize the molecular clusters of a typical oxide, quartz. We documented the average bond length and relative volume change. Finally, we extracted the harmonic vibrational frequencies and calculated the equilibrium fractionation factor of the silicon and oxygen isotopes. Given its performance in geometrical optimization and isotope fractionation factor calculation, we further applied the improved VVCM method to calculate isotope equilibrium fractionation factors of Cd and Zn between the hydroxide (Zn-Al layered double hydroxide), carbonate (cadmium-containing calcite) and their aqueous solutions under superficial conditions. We summarized a detailed procedure and used it to re-evaluate published theoretical results for cadmium-containing hydroxyapatite, emphasizing the relative volume change for all clusters and confirming the optimal point charge arrangement (PCA). The results showed that the average bond length and isotope fractionation factor are consistent with those published in previous studies, and the relative volume changes are considerably lower than the results calculated using the periodic boundary method. Specifically, the average Si-O bond length of quartz was 1.63 Å, and the relative volume change of quartz centered on silicon atoms was  - 0.39%. The average Zn-O bond length in the Zn-Al-layered double hydroxide was 2.10 Å, with a relative volume change of 1.96%. Cadmium-containing calcite had an average Cd-O bond length of 2.28 Å, with a relative volume change of 0.45%. At 298 K, the equilibrium fractionation factors between quartz, Zn-Al-layered double hydroxide, cadmium-containing calcite, and their corresponding aqueous solutions were [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] respectively. These results strongly support the reliability of the improved VVCM method for geometric optimization of molecular clusters.

miR-152-3p impedes the malignant phenotypes of hepatocellular carcinoma by repressing roundabout guidance receptor 1.

BACKGROUND: miR-152-3p functions as a tumour suppressor in the progression of hepatic tumorigenesis. Herein, we further discussed the prognostic significance and immune infiltration of miR-152-3p and its potential gene target in hepatocellular carcinoma (HCC). METHODS: The Cancer Genome Atlas (TCGA), Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), Human Protein Atlas (HPA) and Kaplan-Meier Plotter databases were used to evaluate miR-152-3p and roundabout guidance receptor 1 (ROBO1) expression, prognosis and immune infiltration. In vitro cell experiments, including cell proliferation and apoptosis, were evaluated using Cell Counting Kit 8 (CCK8) and terminal-deoxynucleotidyl transferase-mediated nick end labelling (TUNEL) assays. RESULTS: Up-regulation of ROBO1 functioned as an oncogene associated with poor prognosis, immune cell enrichment and cell proliferation in HCC. ROBO1 was significantly positively correlated with the enrichment of multiple immune cells and their biomarkers. Enrichment of type-2 T-helper (Th2) cells is an unfavourable biomarker of HCC prognosis. GSEA revealed that ROBO1 correlated with apoptosis, mitosis and carcinogenic signalling pathways. Suppression of cell proliferation and the enhancement of cell apoptosis by miR-152-3p mimics were counteracted by overexpression of ROBO1 in HCC cells. CONCLUSION: ROBO1 expression is positively correlated with multiple immune checkpoint molecules, suggesting that ROBO1 may be a potential drug target to enhance the potency of immunotherapy. The miR-152-3p/ROBO1 signalling axis contributes to malignant progression and provides a prospective immunotherapeutic target for HCC.

Synthesis of 4-dimethylaminobenzyl chrysin ester-Zn fluorescent chemical sensor for the determination of Cr(VI) in water.

Cr(VI) is a type of dangerous effluent that has caused great harm to human health and the environment. Recognition and perception of Cr(VI) by artificial receptors has attracted extensive attention. A novel fluorescent chemical sensor based on the 5,7-dihydroxyflavone skeleton was designed and synthesized for the selective recognition of Cr(VI). As confirmed by fluorescence technology, the fluorescent probe 4-dimethylaminobenzyl chrysin ester-Zn (DBC-Zn) showed high sensitivity and selectivity for dichromate and a fast response (less than 30 sec) recognition. The fluorescence intensity of DBC-Zn varies linearly with the concentration of Cr(VI) in the range 0.1-1 µM. The detection limit of Cr2 O7 2- by DBC-Zn is 2.3 nM, which is far lower than the national safe drinking water standard stipulated by the US Environmental Protection Agency (1.9 µM). The quenching mechanism of the probe can be attributed to the interaction of the dynamic quenching effect and the fluorescence internal filtration effect. In addition, the probe has good stability in both neutral and alkaline environments, and the accuracy of quantitative analysis of Cr2 O7 2- in lake water or tap water is more than 80%. The test paper based on DBC-Zn can effectively detect Cr2 O7 2- at the concentration of 100 ppb. This shows that the probe has a certain practical application value.

Nanoscale Mapping of Morphology of Organic Thin Films.

We determine precise nanoscale information about the morphologies of several organic thin film structures using Fourier plane imaging microscopy (FIM). We used FIM microscopy to detect the orientation of molecular transition dipole moments from an extremely low density of luminescent dye molecules, which we call "morphology sensors". The orientation of the sensor molecules is driven by the local film structure and thus can be used to determine details of the host morphology without influencing it. We use symmetric planar phosphorescent dye molecules as the sensors that are deposited into the bulk of organic film hosts during the growth. We demonstrate morphological mapping with a depth resolution to a few Ångstroms that is limited by the ability to determine thickness during deposition, along with an in-plane resolution limited by optical diffraction. Furthermore, we monitor morphological changes arising from thermal annealing of metastable organic films that are commonly employed in photonic devices.

Enhanced Anti-Atherosclerotic Efficacy of pH-Responsively Releasable Ganglioside GM3 Delivered by Reconstituted High-Density Lipoprotein.

Recently, the atheroprotective role of endogenous GM3 and an atherogenesis-inhibiting effect of exogenous GM3 suggested a possibility of exogenous GM3 being recruited as an anti-atherosclerotic drug. This study seeks to endow exogenous GM3 with atherosclerotic targetability via reconstituted high-density lipoprotein (rHDL), an atherosclerotic targeting drug nanocarrier. Unloaded rHDL, rHDL loaded with exogenous GM3 at a low concentration (GM3L-rHDL), and rHDL carrying GM3 at a relatively high concentration (GM3H-rHDL) were prepared and characterized. The inhibitory effect of GM3-rHDL on lipid deposition in macrophages was confirmed, and GM3-rHDL did not affect the survival of red blood cells. In vivo experiments using ApoE-/- mice fed a high fat diet further confirmed the anti-atherosclerotic efficacy of exogenous GM3 and demonstrated that GM3 packed in HDL nanoparticles (GM3-rHDL) has an enhanced anti-atherosclerotic efficacy and a reduced effective dose of GM3. Then, the macrophage- and atherosclerotic plaque-targeting abilities of GM3-rHD, most likely via the interaction of ApoA-I on GM3-rHDL with its receptors (e.g., SR-B1) on cells, were certified via a microsphere-based method and an aortic fragment-based method, respectively. Moreover, we found that solution acidification enhanced GM3 release from GM3-rHDL nanoparticles, implying the pH-responsive GM3 release when GM3-rHDL enters the acidic atherosclerotic plaques from the neutral blood. The rHDL-mediated atherosclerotic targetability and pH-responsive GM3 release of GM3-rHDL enhanced the anti-atherosclerotic efficacy of exogenous GM3. The development of the GM3-rHDL nanoparticle may help with the application of exogenous GM3 as a clinical drug. Moreover, the data imply that the GM3-rHDL nanoparticle has the potential of being recruited as a drug nanocarrier with atherosclerotic targetability and enhanced anti-atherosclerotic efficacy.

Iron-Catalyzed Regioselective Alkenylboration of Olefins.

The first examples of an iron-catalyzed three-component synthesis of homoallylic boronates from regioselective union of bis(pinacolato)diboron, an alkenyl halide (bromide, chloride or fluoride), and an olefin are disclosed. Products that bear tertiary or quaternary carbon centers could be generated in up to 87 % yield as single regioisomers with complete retention of the olefin stereochemistry. With cyclopropylidene-containing substrates, ring cleavage leading to trisubstituted E-alkenylboronates were selectively obtained. Mechanistic studies revealed reaction attributes that are distinct from previously reported alkene carboboration pathways.

Iron-Catalyzed Tunable and Site-Selective Olefin Transposition.

The catalytic isomerization of C-C double bonds is an indispensable chemical transformation used to deliver higher-value analogues and has important utility in the chemical industry. Notwithstanding the advances reported in this field, there is compelling demand for a general catalytic solution that enables precise control of the C═C bond migration position, in both cyclic and acyclic systems, to furnish disubstituted and trisubstituted alkenes. Here, we show that catalytic amounts of an appropriate earth-abundant iron-based complex, a base and a boryl compound, promote efficient and controllable alkene transposition. Mechanistic investigations reveal that these processes likely involve in situ formation of an iron-hydride species which promotes olefin isomerization through sequential olefin insertion/ß-hydride elimination. Through this strategy, regiodivergent access to different products from one substrate can be facilitated, isomeric olefin mixtures commonly found in petroleum-derived feedstock can be transformed to a single alkene product, and unsaturated moieties embedded within linear and heterocyclic biologically active entities can be obtained.

Chiral Bidentate Boryl Ligand Enabled Iridium-Catalyzed Asymmetric C(sp2)-H Borylation of Diarylmethylamines.

Optically active organoboronic acids and their derivatives are an important family of target compounds in organic chemistry, catalysis, and medicinal chemistry. Yet there are rare asymmetric catalytic examples reported for the synthesis of these compounds via atom and step economic ways. Herein, we report a chelate-directed iridium-catalyzed asymmetric C(sp2)-H borylation of aromatic C-H bonds directed by free amine groups. The success of these transformations relies on a novel family of chiral bidentate boryl ligands (L). They can be synthesized straightforwardly in three steps starting from readily available ( S, S)-1,2-diphenyl-1,2-ethanediamie (( S, S)-DPEN). The Ir-catalyzed C(sp2)-H borylation comprises two parts. The first part is desymmetrization of prochiral diarylmethylamines. In the presence of L3/Ir, a vast array of corresponding borylated products were obtained with high regioselectivity and good to excellent enantioselectivities (26 examples, up to 96% ee). The second part, kinetic resolution of racemic diarylmethylamines, was also conducted. Good selectivity values (up to 68%, 11 examples) were obtained when L8 was used. We also demonstrated the synthetic utility of the current method on gram-scale reaction for several transformations. The C-B bonds of borylated products could be converted to a variety of functionalities including C-O, C-C, C-C, C-Br, and C-P bonds. Finally, we performed DFT calculations of desymmetrization to understand its reaction pathways.

Transition-metal-free synthesis of 1,1-diboronate esters with a fully substituted benzylic center via diborylation of lithiated carbamates.

A transition-metal-free lithiation-borylation method has been developed to access a variety of 1,1-diboronate esters with a fully substituted benzylic center from readily available secondary benzylic N,N-diisopropyl carbamates. The method is applicable to scale-up synthesis of 1,1-diboron compounds. Furthermore, the current method is also applicable to synthesizing optically active 1,1-silylboronate esters.

Dynamic constitutive identification of concrete based on improved dung beetle algorithm to optimize long short-term memory model.

In order to improve the accuracy of concrete dynamic principal identification, a concrete dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) optimized Long Short-Term Memory (LSTM) network is proposed. Firstly, the apparent stress-strain curves of concrete containing damage evolution were measured by Split Hopkinson Pressure Bar (SHPB) test to decouple and separate the damage and rheology, and this system was modeled by using LSTM network. Secondly, for the problem of low convergence accuracy and easy to fall into local optimum of Dung Beetle Algorithm (DBO), the greedy lens imaging reverse learning initialization population strategy, the embedded curve adaptive weighting factor and the PID control optimal solution perturbation strategy are introduced, and the superiority of IDBO algorithm is proved through the comparison of optimization test with DBO, Harris Hawk Optimization Algorithm, Gray Wolf Algorithm, and Fruit Fly Algorithm and the combination of LSTM is built to construct the IDBO-LSTM dynamic homeostasis identification model. The final results show that the IDBO-LSTM model can recognize the concrete material damage without considering the damage; in the case of considering the damage, the IDBO-LSTM prediction curves basically match the SHPB test curves, which proves the feasibility and excellence of the proposed method.

Role of BcSfb3, the subunit of COPII vesicles, in fungal development and pathogenicity, ER-phagy and autophagy in the gray mold fungus Botrytis cinerea.

Cytoplasmic coat protein complex II (COPII) plays a multifunctional role in the transport of newly synthesized proteins, autophagosome formation, and endoplasmic reticulum (ER)-ER-phagy. However, the molecular mechanisms of the COPII subunit in ER-phagy in plant pathogens remain unknown. Here, we identified the subunit of COPII vesicles (BcSfb3) and explored the importance of BcSfb3 in Botrytis cinerea. BcSfb3 deletion affected vegetative growth, conidiation, conidial morphology, and plasma membrane integrity. We confirmed that the increase in infectious hyphal growth was delayed in the ΔBcSfb3 mutant, reducing its pathogenicity in the host plant. Furthermore, the ΔBcSfb3 mutant was sensitive to ER stress, which caused massive ER expansion and induced the formation of ER whorls that were taken up into the vacuole. Further examination demonstrated that BcSfb3 deletion caused ER stress initiated by unfolded protein response, and which led to the promotion of ER-phagy and autophagy that participate in sclerotia formation. In conclusion, these results demonstrate that BcSfb3 plays an important role in fungal development, pathogenesis, ER-phagy and autophagy in B. cinerea.

Primary Budd-Chiari syndrome versus sinusoidal obstruction syndrome: a review.

Budd-Chiari syndrome (BCS) and sinusoidal obstruction syndrome (SOS) are two major vascular disorders of the liver, of which both can cause portal hypertension related complications, but their locations of obstruction are different. BCS refers to the obstruction from the hepatic vein to the junction between the inferior vena cava and right atrium, which is the major etiology of post-sinusoidal portal hypertension; by comparison, SOS is characterized as the obstruction at the level of hepatic sinusoids and terminal venulae, which is a cause of sinusoidal portal hypertension. Both of them can cause hepatic congestion with life-threatening complications, especially acute liver failure and chronic portal hypertension, and share some similar features in terms of imaging and clinical presentations, but they have heterogeneous risk factors, management strategy, and prognosis. Herein, this paper reviews the current evidence and then summarizes the difference between primary BCS and SOS in terms of risk factors, clinical features, diagnosis, and treatment.

Whole-transcriptome sequencing revealed the role of noncoding RNAs in susceptibility and resistance of Pekin ducks to DHAV-3.

As the most prevalent pathogen of duck viral hepatitis (DVH), duck hepatitis A virus genotype 3 (DHAV-3) has caused huge economic losses to the duck industry in China. Herein, we obtained whole-transcriptome sequencing data of susceptible (S) and resistant (R) Pekin duckling samples at 0 h, 12 h, and 24 h after DHAV-3 infection. We found that DHAV-3 infection induces 5,396 differentially expressed genes (DEGs), 85 differentially expressed miRNAs (DEMs), and 727 differentially expressed lncRNAs (DELs) at 24 hpi in S vs. R ducks, those upregulated genes were enriched in inflammation and cell communications pathways and downregulated genes were related to metabolic processes. Upregulated genes showed high connectivity with the miR-33, miR-193, and miR-11591, and downregulated genes were mainly regulated by miR-2954, miR-125, and miR-146b. With the construction of lncRNA-miRNA-mRNA axis, we further identified a few aberrantly expressed lncRNAs (e.g., MSTRG.36194.1, MSTRG.50601.1, MSTRG.34328.7, and MSTRG.29445.1) that regulate expression of hub genes (e.g., THBD, CLIC2, IL8, ACOX2, GPHN, SMLR1, and HAO1) by sponging those highly connected miRNAs. Altogether, our findings defined a dual role of ncRNAs in immune and metabolic regulation during DHAV-3 infection, suggesting potential new targets for treating DHAV-3 infected ducks.