Phylogeny and diversification of genus Sanicula L. (Apiaceae): novel insights from plastid phylogenomic analyses.

BACKGROUND: The genus Sanicula L. is a unique perennial herb that holds important medicinal values. Although the previous studies on Sanicula provided us with a good research basis, its taxonomic system and interspecific relationships have not been satisfactorily resolved, especially for those endemic to China. Moreover, the evolutionary history of this genus also remains inadequately understood. The plastid genomes possessing highly conserved structure and limited evolutionary rate have proved to be an effective tool for studying plant phylogeny and evolution. RESULTS: In the current study, we newly sequenced and assembled fifteen Sanicula complete plastomes. Combined with two previously reported plastomes, we performed comprehensively plastid phylogenomics analyses to gain novel insights into the evolutionary history of this genus. The comparative results indicated that the seventeen plastomes exhibited a high degree of conservation and similarity in terms of their structure, size, GC content, gene order, IR borders, codon bias patterns and SSRs profiles. Such as all of them displayed a typical quadripartite structure, including a large single copy region (LSC: 85,074-86,197 bp), a small single copy region (SSC: 17,047-17,132 bp) separated by a pair of inverted repeat regions (IRs: 26,176-26,334 bp). And the seventeen plastomes had similar IR boundaries and the adjacent genes were identical. The rps19 gene was located at the junction of the LSC/IRa, the IRa/SSC junction region was located between the trnN gene and ndhF gene, the ycf1 gene appeared in the SSC/IRb junction and the IRb/LSC boundary was located between rpl12 gene and trnH gene. Twelve specific mutation hotspots (atpF, cemA, accD, rpl22, rbcL, matK, ycf1, trnH-psbA, ycf4-cemA, rbcL-accD, trnE-trnT and trnG-trnR) were identified that can serve as potential DNA barcodes for species identification within the genus Sanicula. Furthermore, the plastomes data and Internal Transcribed Spacer (ITS) sequences were performed to reconstruct the phylogeny of Sanicula. Although the tree topologies of them were incongruent, both provided strong evidence supporting the monophyly of Saniculoideae and Apioideae. In addition, the sister groups between Saniculoideae and Apioideae were strongly suggested. The Sanicula species involved in this study were clustered into a clade, and the Eryngium species were also clustered together. However, it was clearly observed that the sections of Sanicula involved in the current study were not respectively recovered as monophyletic group. Molecular dating analysis explored that the origin of this genus was occurred during the late Eocene period, approximately 37.84 Ma (95% HPD: 20.33-52.21 Ma) years ago and the diversification of the genus was occurred in early Miocene 18.38 Ma (95% HPD: 10.68-25.28 Ma). CONCLUSION: The plastome-based tree and ITS-based tree generated incongruences, which may be attributed to the event of hybridization/introgression, incomplete lineage sorting (ILS) and chloroplast capture. Our study highlighted the power of plastome data to significantly improve the phylogenetic supports and resolutions, and to efficiently explore the evolutionary history of this genus. Molecular dating analysis explored that the diversification of the genus occurred in the early Miocene, which was largely influenced by the prevalence of the East Asian monsoon and the uplift of the Hengduan Mountains (HDM). In summary, our study provides novel insights into the plastome evolution, phylogenetic relationships, taxonomic framework and evolution of genus Sanicula.

Structure and Functions of Endophytic Bacterial Communities Associated with Sphagnum Mosses and Their Drivers in Two Different Nutrient Types of Peatlands.

Sphagnum mosses are keystone plant species in the peatland ecosystems that play a crucial role in the formation of peat, which shelters a broad diversity of endophytic bacteria with important ecological functions. In particular, methanotrophic and nitrogen-fixing endophytic bacteria benefit Sphagnum moss hosts by providing both carbon and nitrogen. However, the composition and abundance of endophytic bacteria from different species of Sphagnum moss in peatlands of different nutrient statuses and their drivers remain unclear. This study used 16S rRNA gene amplicon sequencing to examine endophytic bacterial communities in Sphagnum mosses and measured the activity of methanotrophic microbial by the 13C-CH4 oxidation rate. According to the results, the endophytic bacterial community structure varied among Sphagnum moss species and Sphagnum capillifolium had the highest endophytic bacterial alpha diversity. Moreover, chlorophyll, phenol oxidase, carbon contents, and water retention capacity strongly shaped the communities of endophytic bacteria. Finally, Sphagnum palustre in Hani (SP) had a higher methane oxidation rate than S. palustre in Taishanmiao. This result is associated with the higher average relative abundance of Methyloferula an obligate methanotroph in SP. In summary, this work highlights the effects of Sphagnum moss characteristics on the endophytic bacteriome. The endophytic bacteriome is important for Sphagnum moss productivity, as well as for carbon and nitrogen cycles in Sphagnum moss peatlands.

Global responses of wetland methane emissions to extreme temperature and precipitation.

As global warming continues, events of extreme heat or heavy precipitation will become more frequent, while events of extreme cold will become less so. How wetlands around the globe will react to these extreme events is unclear yet critical, because they are among the greatest natural sources of methane(CH4). Here we use seven indices of extreme climate and the rate of methane emission from global wetlands(WME) during 2000-2019 simulated by 12 published models as input data. Our analyses suggest that extreme cold (particularly extreme low temperatures) inhibits WME, whereas extreme heat (particularly extreme high temperatures) accelerates WME. Our results also suggest that daily precipitation >10 mm accelerates WME, while much higher daily precipitation levels can slow WME. The correlation of extreme high temperature and precipitation with rate of WME became stronger during the study period, while the correlation between extreme low temperature and WME rate became weaker.

Supervised training models with or without manual lesion delineation outperform clinicians in distinguishing pulmonary cryptococcosis from lung adenocarcinoma on chest CT.

BACKGROUND: The role of artificial intelligence (AI) in the discrimination between pulmonary cryptococcosis (PC) and lung adenocarcinoma (LA) warrants further research. OBJECTIVES: To compare the performances of AI models with clinicians in distinguishing PC from LA on chest CT. METHODS: Patients diagnosed with confirmed PC or LA were retrospectively recruited from three tertiary hospitals in Guangzhou. A deep learning framework was employed to develop two models: an undelineated supervised training (UST) model utilising original CT images, and a delineated supervised training (DST) model utilising CT images with manual lesion annotations provided by physicians. A subset of 20 cases was randomly selected from the entire dataset and reviewed by clinicians through a network questionnaire. The sensitivity, specificity and accuracy of the models and the clinicians were calculated. RESULTS: A total of 395 PC cases and 249 LA cases were included in the final analysis. The internal validation results for the UST model showed a sensitivity of 85.3%, specificity of 81.0%, accuracy of 83.6% and an area under the curve (AUC) of 0.93. Similarly, the DST model exhibited a sensitivity of 88.2%, specificity of 88.1%, accuracy of 88.2% and an AUC of 0.94. The external validation of the two models yielded AUC values of 0.74 and 0.77, respectively. The average sensitivity, specificity and accuracy of 102 clinicians were determined to be 63.1%, 53.7% and 59.3%, respectively. CONCLUSIONS: Both models outperformed the clinicians in distinguishing between PC and LA on chest CT, with the UST model exhibiting comparable performance to the DST model.

Attributes and Predictors of Opinion Leaders on Twitter: COVID-19 Childhood Vaccination Campaign.

Identifying attributes of the COVID-19 childhood vaccine message disseminators is beneficial to health campaign research. This study examines the We Can Do This COVID-19 childhood vaccination health campaign message disseminators on Twitter during 2021-2022. Guided by the diffusion of innovation theory and the theory of the two-step flow communication, we classify the disseminators (n=823) and examine their influence over the two-year period. A manual content analysis and social network analysis were conducted to measure the impact of disseminators on their networks through in-degree centrality assessment. Results revealed that experts in medical fields, industrial professionals, and social media influencers were the top three most common career titles disclosed in Twitter bios among individual accounts, whereas local nonprofit organizations, governments, and companies were the most common organizational accounts. Mann-Whitney U Tests indicated that in both years message disseminators with clinical medicine expertise were more influential than those who did not reveal such expertise. However, only in 2021 were campaign message disseminators with parental expertise more influential within the social network. We discuss the implications of disseminator classification as well as the significance of enhancing health campaigns by identifying who discusses them on social media.

Dual Strategies with Anion/Cation Co-Doping and Lithium Carbonate Coating to Enhance the Electrochemical Performance of Lithium-Rich Layered Oxides.

Lithium-rich layered oxides (LLOs, Li1.2 Mn0.54 Ni0.13 Co0.13 O2 ) are widely used as cathode materials for lithium-ion batteries due to its high specific capacity, high operating voltage and low cost. However, the LLOs are faced with rapid decay of charge/discharge capacity and voltage, as well as interface side reactions, which limit its electrochemical performance. Herein, the dual strategies of sulfite/sodium ion co-doping and lithium carbonate coating were used to improve it. It founds that modified LLOs achieve 88.74 % initial coulomb efficiency, 295.3 mAh g-1 first turn discharge capacity, in addition to 216.9 mAh g-1 at 1 C, and 87.23 % capacity retention after 100 cycles. Mechanism research indicated that the excellent electrochemical performance benefits from the doping of both Na+ and SO3 2- , and it could significantly reduce the migration energy barrier of Li+ and promote Li+ migration. Meanwhile, anion and cation are co-doped greatly reduces the band gap of LLOs and increase its electrical conductivity, and its binding effect on Li+ is weakened, making it easier for Li+ to shuttle through the material. In addition, the lithium carbonate coating significantly inhibits the occurrence of interfacial side reactions of LLOs. This work provides a theoretical basis and practical guidance for the further development of LLOs with higher electrochemical performance.

Constructing pH-Responsive and Tunable Azo-Phenol-Based o-Nitrobenzyl Photocages.

Multiple triggered-release strategies are widely utilized to control the release of caged target molecules. Among them, photocages with conditional triggers provide extra layers of control in photorelease. In this work, a series of pH-responsive photocages was designed that could be triggered under irradiation and specific intracellular pH values. pH-sensitive phenolic groups were conjugated with o-nitrobenzyl (oNB) to form azo-phenolic NPX photocages with tunable pKa. These azo-phenol-based oNB photocages showed differentiable photoreleasing profiles at pH 5.0, 7.2 and 9.0. By attaching fluorogenic cargos, it was shown that one of the photocages, NPdiCl, could be used to differentiate between acidic pH 5.0 and neutral pH 7.2 in cells under artificial pH conditions. Finally, NPdiCl was identified as a promising pH-responsive photocage for photoreleasing cargo inside acidic tumor cells.

Development of a New Heteropolyoxotantalate Cluster for Multidimensional Polyoxotantalate Materials.

A unique heteropolyoxotantalate (hetero-POTa) cluster [P2O7Ta5O14]7- (P2Ta5) was first developed using pyrophosphate as a key to open the ultrastable skeleton of the classical Lindqvist-type [Ta6O19]8- precursor. The P2Ta5 cluster can serve as a general and flexible secondary building unit to create a family of brand-new multidimensional POTa architectures. This work not only promotes the limited structural diversity of hetero-POTa but also provides a practical strategy for new extended POTa architectures.

A case of IgG4-related interstitial nephritis with ureteral obstruction: case report and literature review.

BACKGROUND: IgG4-related disease (IgG4-RD) is a newly discovered systemic disease that can affect any organ or tissue in the body. IgG4-related kidney disease (IgG4-RKD) is relatively rare but essential to IgG4-RD. However, there are few reports of IgG4-RD mimicking malignant ureteral tumors leading to hydronephrosis. We report here a rare case of IgG4-RD involving the ureter. CASE PRESENTATION: An 87-year-old man presented to our nephrology department with anorexia, nausea, and acute kidney injury in November 2020. Urinary computed tomography (CT) examination revealed a right lower ureter mass with right renal and ureter hydronephrosis. The serum level of IgG4 was 1890 mg/dL, and the concurrently renal biopsy revealed extensive infiltration of IgG4-positive plasma cells in renal interstitium, which was diagnosed as IgG4-associated tubule-interstitial nephritis(IgG4-TIN). The renal function improved significantly after double-J tube implantation of the right ureter and moderate-dose hormone therapy. The serum IgG4 decreased to the normal range, and the right lower ureter mass almost disappeared after one year of low-dose hormone maintenance therapy. CONCLUSION: IgG4-RD can present as a mass in the renal pelvis and (or) ureter, leading to hydronephrosis. Therefore, early recognition of this disease is significant. Most patients respond well to hormonal therapy to avoid surgical treatment due to misdiagnosis as malignant tumors, causing secondary harm to patients.

Neuroprotective effects of Chrysanthemum morifolium on cerebral ischemia- reperfusion injury contributes to the oxidative stress suppression and related Keap1/Nrf2 pathway.

BACKGROUND: Ischemic stroke, the cause of death and disability worldwide, is closely related to oxidative stress damage. Chrysanthemum has profound antiantioxidant activity. We aimed to verify whether Chrysanthemum morifolium extract (CME) influences brain injury in cerebral ischemia-reperfusion injury (CR/RI) model. METHODS: In vitro, rat hippocampal H19-7 neurons were pretreated with CME, CR/RI was simulated with oxygen glucose deprivation/reoxygenation (OGD/R). The cell viability, apoptosis, lactate dehydrogenase release, reactive oxygen species (ROS) generation, malonaldehyde (MDA) content and superoxide dismutase（SOD） activity were detected. In vivo, middle cerebral artery occlusion (MCAO) model rats were pre-administered with CME, and then behavioral test, triphenyltetrazolium chloride (TTC), hematoxylin-eosin staining (HE), terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL), ROS immunofluorescence, MDA and SOD activity were tested. Furthermore, Keap1/Nrf2 signaling of CME in CI/RI was investigated. RESULTS: In OGD/R induced in H19-7 cells, CME increased OGD/R-induced cell viability and reduced cell apoptosis, which was reversed by siNrf2 transfection . In MCAO rats, CME improved the neurological deficits and alleviated brain injury. However, co-treatment with MLK385 counteracted these neuroprotective effects of CME on MCAO rats. CONCLUSION: CME could significantly reduce oxidative stress and nerve injury in vitro and in vivo models of CI/RI by regulating the Keap1/Nrf2 pathway.

Investigating Substance Use via Reddit: Systematic Scoping Review.

BACKGROUND: Reddit's (Reddit Inc) large user base, diverse communities, and anonymity make it a useful platform for substance use research. Despite a growing body of literature on substance use on Reddit, challenges and limitations must be carefully considered. However, no systematic scoping review has been conducted on the use of Reddit as a data source for substance use research. OBJECTIVE: This review aims to investigate the use of Reddit for studying substance use by examining previous studies' objectives, reasons, limitations, and methods for using Reddit. In addition, we discuss the implications and contributions of previous studies and identify gaps in the literature that require further attention. METHODS: A total of 7 databases were searched using keyword combinations including Reddit and substance-related keywords in April 2022. The initial search resulted in 456 articles, and 227 articles remained after removing duplicates. All included studies were peer reviewed, empirical, available in full text, and pertinent to Reddit and substance use, and they were all written in English. After screening, 60 articles met the eligibility criteria for the review, with 57 articles identified from the initial database search and 3 from the ancestry search. A codebook was developed, and qualitative content analysis was performed to extract relevant evidence related to the research questions. RESULTS: The use of Reddit for studying substance use has grown steadily since 2015, with a sharp increase in 2021. The primary objective was to identify tendencies and patterns in various types of substance use discussions (52/60, 87%). Reddit was also used to explore unique user experiences, propose methodologies, investigate user interactions, and develop interventions. A total of 9 reasons for using Reddit to study substance use were identified, such as the platform's anonymity, its widespread popularity, and the explicit topics of subreddits. However, 7 limitations were noted, including the platform's low representativeness of the general population with substance use and the lack of demographic information. Most studies use application programming interfaces for data collection and quantitative approaches for analysis, with few using qualitative approaches. Machine learning algorithms are commonly used for natural language processing tasks. The theoretical, methodological, and practical implications and contributions of the included articles are summarized and discussed. The most prevalent practical implications are investigating prevailing topics in Reddit discussions, providing recommendations for clinical practices and policies, and comparing Reddit discussions on substance use across various sources. CONCLUSIONS: This systematic scoping review provides an overview of Reddit's use as a data source for substance use research. Although the limitations of Reddit data must be considered, analyzing them can be useful for understanding patterns and user experiences related to substance use. Our review also highlights gaps in the literature and suggests avenues for future research.

Neoadjuvant camrelizumab plus chemotherapy for resectable, locally advanced esophageal squamous cell carcinoma (NIC-ESCC2019): A multicenter, phase 2 study.

Optimal treatment for resectable esophageal squamous cell carcinoma (ESCC) is controversial, especially in the context of potential benefit of combining PD-1 blockade with neoadjuvant therapy. This phase 2 study aimed to assess neoadjuvant camrelizumab plus chemotherapy in this population. Patients (clinical stage II-IVA) received two cycles of neoadjuvant chemoimmunotherapy (NIC) with camrelizumab (200 mg on day 1) plus nab-paclitaxel (260 mg/m2 in total on day 1 and day 8) and cisplatin (75 mg/m2 in total on days 1-3) of each 21-day cycle. Surgery was performed approximately 6 weeks after completion of NIC. Primary endpoint was complete pathologic response (CPR) rate in primary tumor. Secondary endpoints were objective response rate (ORR) per RECIST v1.1, 2-year progression-free survival (PFS) rate after surgery, PFS, overall survival (OS) and safety during NIC and perioperative period. Between 17 January 2020 and 8 December 2020, 56 patients were enrolled, and 51 received esophagectomy. Data cutoff date was 25 August 2021. The CPR rate was 35.3% (95% CI, 21.7%-48.9%). NIC had an ORR of 66.7% (95% CI, 40.0%-70.4%) and treatment-related adverse events (TRAEs) of low severity (grade 1-2, 75.0%; grade 3, 10.7%; grade 4-5, no). No perioperative mortality occurred. Three (5.9%) patients had tumor recurrence and one (2.0%) patient died. The 2-year PFS rate, median PFS and median OS had not been reached yet. Camrelizumab plus neoadjuvant chemotherapy in resectable ESCC demonstrates promising efficacy with acceptable toxicity, providing a feasible and effective option. Study is ongoing for long-term survival analyses.

Omega-3 fatty acids impair miR-1-3p-dependent Notch3 down-regulation and alleviate sepsis-induced intestinal injury.

BACKGROUND: Sepsis is a troublesome syndrome that can cause intestinal injury and even high mortality rates. Omega-3 fatty acids (FAs) are known to protect against intestinal damage. Accordingly, the current study set out to explore if omega-3 FAs could affect sepsis-induced intestinal injury with the involvement of the microRNA (miR)-1-3p/Notch3-Smad axis. METHODS: First, cecal ligation and perforation (CLP) was performed to establish septic mouse models in C57BL/6J mice, and mouse intestinal epithelial MODE-K cells were induced by lipopolysaccharide (LPS) to establish sepsis cell models. The CLP-induced septic mice or LPS-exposed cells were subjected to treatment with Omega-3 FAs and activin (Smad signaling activator), miR-1-3p inhibitor and over-expressed/short hairpin RNA (oe-/sh)-Notch3 to explore their roles in inflammation, intestinal oxidative stress and cell apoptosis. A dual-luciferase reporter gene assay was further performed to verify the regulatory relationship between miR-1-3p and Notch3. RESULTS: Omega-3 FAs inhibited CLP-induced intestinal injury and ameliorated LPS-induced intestinal epithelial cell injury by down-regulating miR-1-3p, as evidenced by decreased levels of tumor necrosis factor-α, interleukin-1ß (IL-1ß) and IL-6, in addition to diminished levels of reactive oxygen species, malondialdehyde levels and superoxide dismutase activity. Furthermore, miR-1-3p could down-regulate Notch3, which inactivated the Smad pathway. CONCLUSION: Collectively, our findings indicated that omega-3 FAs elevate the expression of Notch3 by down-regulating miR-1-3p, and then blocking the Smad pathway to alleviate intestinal epithelial inflammation and oxidative stress injury caused by sepsis.

Methane emissions may be driven by hydrogenotrophic methanogens inhabiting the stem tissues of poplar.

Living trees in forests emit methane (CH4 ) from their stems. However, the magnitudes, patterns, drivers, origins, and biogeochemical pathways of these emissions remain poorly understood. We measured in situ CH4 fluxes in poplar stems and soils using static chambers and investigated the microbial communities of heartwood and sapwood by sequencing bacterial 16S, archaeal 16S, and fungal ITS rRNA genes. Methane emissions from poplar stems occurred throughout the sampling period. The mean CH4 emission rate was 2.7 mg m-2 stem d-1 . Stem CH4 emission rate increased significantly with air temperature, humidity, soil water content, and soil CH4 fluxes, but decreased with increasing sampling height. The CO2 reduction and methylotrophic methanogenesis were the major methanogenic pathways in wood tissues. The dominant methanogen groups detected in stem tissues were Methanobacterium, Methanobrevibacter, Rice Cluster I, Methanosarcina, Methanomassiliicoccus, Methanoculleus, and Methanomethylophilaceae. In addition, three methanotrophic genera were identified in the heartwood and sapwood - Methylocystis, Methylobacterium, and Paracoccus. Overall, stem CH4 emissions can originate directly from the internal tissues or co-occur from soils and stems. The co-existence of methanogens and methanotrophs within heartwood and sapwood highlights a need for future research in the microbial mechanisms underlying stem CH4 exchange with the atmosphere.

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.

KI-Catalyzed Oxidative Cyclization of Enamines and tBuONO to Access Functional Imidazole-4-Carboxylic Derivatives.

A simple protocol for the noble-metal-free oxidative cyclization of enamines and tBuONO has been developed. This KI-mediated formal [4 + 1] cycloamination reaction provides a practical strategy for the synthesis of imidazole-4-carboxylic derivatives using tBuONO both as an aminating reagent and oxidant. The reaction features wide substrate scope and good functional tolerance for enamine compounds, even the unactivated ones.

Homogeneous selection is stronger for fungi in deeper peat than in shallow peat in the low-temperature fens of China.

Peatlands have accumulated enormous amounts of carbon over millennia, and climate changes threatens the release of this carbon into the atmosphere. Fungi are crucial drivers of global carbon cycling because they are the principal decomposer of organic matter in peatlands. However, the fungal community composition and ecological preferences in peat remain unclear, which restricts our ability to evaluate the role of the fungal community in peat biogeochemical functions. We investigated 54 soils from 6 low-temperature peatlands across China to fill this knowledge gap. The peat was divided into above-water table (AWT) and below-water table (BWT) layers based on the water table fluctuation. We investigated fungal community assembly processes and drivers for each peat layer. The results showed that fungal communities differed significantly among peat layers. The relative abundance of symbiotrophs was significantly higher in the AWT (17.4%) than in the BWT (9.0%), while the abundances of yeast and litter saprotrophs were obviously lower in the AWT than in the BWT. Our results revealed that the assemblage of both fungal taxonomic and phylogenetic communities was mainly governed by stochastic processes in both AWT (87.8%) and BWT (58.6%) layers. However, in the BWT, the relative importance of deterministic processes (28.4%) significantly increased, indicating a potential deterministic environmental selection induced by permanently anaerobic condition. Mean annual precipitation and mean annual temperature were the most critical drives for the assemblage of the fungal community in the BWT. These observations collectively indicate that fungal community assembly is depth-dependent, implying different community assembly mechanisms and ecological functions along the peat profile. These findings highlight the importance of climate driven deep peat fungal community composition assemblages and suggest the potential to project the changes in fungal diversity with ongoing climate change.

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment.

There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19. COVID-MTL learns different COVID-19 tasks in parallel through our novel random-weighted loss function, which assigns learning weights under Dirichlet distribution to prevent task dominance; our new 3D real-time augmentation algorithm (Shift3D) introduces space variances for 3D CNN components by shifting low-level feature representations of volumetric inputs in three dimensions; thereby, the MTL framework is able to accelerate convergence and improve joint learning performance compared to single-task models. By only using chest CT scans, COVID-MTL was trained on 930 CT scans and tested on separate 399 cases. COVID-MTL achieved AUCs of 0.939 and 0.846, and accuracies of 90.23% and 79.20% for detection of COVID-19 against radiology and NAT, respectively, which outperformed the state-of-the-art models. Meanwhile, COVID-MTL yielded AUC of 0.800 ± 0.020 and 0.813 ± 0.021 (with transfer learning) for classifying control/suspected, mild/regular, and severe/critically-ill cases. To decipher the recognition mechanism, we also identified high-throughput lung features that were significantly related (P < 0.001) to the positivity and severity of COVID-19.

[Transcriptome analysis in fetal lungs of SRC1/SRC2 double-knockout mice].

Steroid receptor coactivators (SRCs) significantly increase the transcriptional activity of various steroid hormone receptors, and play an important regulatory role in a variety of physiological functions such as food intake, sleep, stress response and reproduction. Previous studies have found that pregnant mice carrying fetuses with SRC1/2 double-knockout (dKO) manifested delayed labor, partly due to the hypoplasia of fetal lungs and the decreased secretion of pulmonary surfactant protein-A (SP-A) and platelet activating factor (PAF). However, there is still a lack of systematic analysis of the changes in gene expression at the whole transcriptome level in the fetal lungs of SRC1/2 dKO mice. In this study, the SRC1KO, SRC2KO, SRC1/2 dKO and wild-type (WT) mouse fetal lung samples were collected at 18.5 days post coitus. The Illumina platform was employed for transcriptome mRNA sequencing, and then the differentially expressed genes (DEGs) were annotated and analyzed by GO and KEGG analysis. The results showed that the proportion of quality score of the sequencing data above Q30 in all samples was more than 92% and passed the quality control. Compared with WT fetal lungs, SRC1KO and SRC2KO fetal lungs had 61 and 32 DEGs, respectively; SRC1/2 dKO fetal lungs had 480, 11 and 901 DEGs compared with WT, SRC1KO and SRC2KO fetal lungs, respectively. Among these genes, Aspg, Crispld2, Eln, Ntsr2, Slc10a6 and Vgll3 were the unique DEGs of SRC1/2 dKO fetal lungs compared with other genotype mice. Real-time PCR and Western blotting verified the reliability of transcriptome sequencing results. The GO analysis of the DEGs between SRC1/2 dKO and WT mouse fetal lungs showed that the DEGs were significantly enriched in the extracellular space, extracellular region, and extracellular matrix in terms of cellular component. In the biological process, they were significantly enriched in the term of development of multiple organs. KEGG pathway analysis showed that the DEGs were mainly enriched in signaling pathways such as the complement system, extracellular matrix-receptor interactions, and protein digestion and absorption. In summary, this study comprehensively revealed the changes of gene expression in the fetal lungs of SRC1/2 dKO mice at the transcriptome level, which provides a new theoretical basis for the study of the developmental regulatory mechanism of the fetal lung during pregnancy, and the fetus-derived signals that affect the initiation of labor.