The incorporation of siRNA into nanocarriers is mandatory to facilitate its intracellular delivery, as siRNA itself cannot enter cells. However, the incorporation of these nanocarriers into oral, solid dosage forms and their fate in the gastrointestinal environment is yet to be explored. In the present work, the fate of, (i) naked siRNA, (ii) freshly prepared siRNA lipoplexes, and (iii) tableted siRNA lipoplexes, in simulated gastric and intestinal fluids was studied. The siRNA, either released from or protected within the lipoplexes, was quantified by gel electrophoresis and siRNA efficacy was assessed in cell transfection. The freshly prepared lipoplexes kept their siRNA load and transfection efficiency totally preserved during 1 h of incubation in simulated gastric fluid at 37 °C. However, in simulated intestinal fluid, despite no release of siRNA from lipoplexes after 6 h of incubation, gene silencing efficacy was dramatically decreased even after 1 h of exposure. The lipoplexes obtained from tablets efficiently protected siRNA in simulated gastric fluid, thus preserving the gene silencing efficacy, whereas their incubation in simulated intestinal fluid resulted in a marked siRNA release and decreased gene silencing efficacy. These results provided a detailed explanation for understanding the fate of siRNA in gastrointestinal conditions, when simply loaded in lipoplexes or formulated in the form of tablets. The zwiFirstly, the cationic liposomes were prepared by using the lipid film method with the cationic lipid DMAPAP and a zwiterrionic lipid DOPE  as previously reported by our research group ,23,24. Aw/w) in 150 mM NaCl  with an equal volume of a solution containing siRNA (luciferase or control) and sodium alginate  on the formation, stability and gene-silencing efficacy of lipoplexes was assayed in order to determine the best procedure for preparing stable and efficient lipoplexes. For that purpose, the size of the lipoplexes was measured for freshly prepared samples, and after 4 and 24 h of storage at room temperature.Size measurements were performed on a MALVERN Zetasizer Nanoseries Nano ZS using Malvern Zetasizer Software . Particle suspensions were prepared in 100 μL of NaCl 150 mM with a final concentration of siRNA of 334 nM.w/v of trehalose with 1% w/v of mannitol) was added to the lipoplex suspension (9.4 μM siRNA). The resulting suspension (4 mL) was taken in a 50 mL Falcon centrifuge tube  and frozen in liquid nitrogen for 10 min and then it was connected to the drying chamber of a laboratory-scale freeze dryer . A 30 h freeze drying cycle was performed and the process parameters were kept constant during the runs (the condenser chamber temperature was −60 °C and the chamber pressure was 0.1 mbar).The obtained lipoplexes were freeze-dried as described in our previous study . Brieflyw/w) were mixed with Flowlac® (23% w/w), and magnesium stearate (0.5% w/w) to prepare 160 mg of the final mixture. Then, the mixture was compacted with a StylOne Evolution compression simulator , and tooled with bevel-edged Euro B punches (6 mm in diameter). Compaction pressure of 150 MPa was applied using the force-driven mode of Analis software. Various characteristics of the formed tablets, such as apparent densities, thickness, diameter, elastic recovery, and cohesion have already been studied and reported by our group /I(input), while the % of released intact siRNA was given by: 100 × I(band 1′)/I(input), as previously described in Hamoudi et al. .B16-Luc were obtained and transfected as described ,25. Lipop < 0.05 were considered statistically significant.All results were analyzed with the unpaired, nonparametric Mann−Whitney test using two-tailed P-values. Results with Lipoplexes were prepared by mixing a DMAPAP and DOPE liposome suspension with siRNA, sodium alginate and NaCl in aqueous solution as previously reported by our research group ,23,24. TThe uncoated tablets must disintegrate within 15 min to meet the standards of United States pharmacopoeia (USP) and European pharmacopoeia (EP). In this case, all six tablets that were obtained under a compression pressure of 150 MPa were disintegrated within five min, 4 min 54 s and 4 min 46 s precisely in water and SGF, respectively. Therefore, the tablets containing freeze-dried siRNA meet the standards of the USP and EP.Oral administration presents a number of limitations, one of which is the acidic-to-near-neutral pH of the gastrointestinal tract. We first assessed the impact of preparing and incubating siRNA lipoplexes in acidic pH medium on the size of lipoplexes and efficacy of gene silencing.The lipoplexes were prepared at different pH levels, namely 2, 4.5 or 7, and their average size was measured immediately after preparation and after 4 h and 24 h of storage at room temperature following their preparation as well.® 37 mg/mL, magnesium stearate 0.8 mg/mL, trehalose 90 mg/mL, mannitol 36 mg/mL).It was observed that naked siRNA remained stable in NaCl as well as in SGF, even after 1 h incubation at 37 °C, which indicates that the gastric conditions do not degrade naked siRNA A. In NaCNaked siRNA remained stable in NaCl after 6 h incubation at 37 °C. In SIF-treated samples, naked siRNA was completely degraded after 3 h incubation . This shIn the case of NaCl (150 mM)-treated fresh lipoplex samples, no release of siRNA was observed in both nonincubated as well as incubated samples, even after 6 h incubation at 37 °C. However, tableted, freeze-dried siRNA lipoplexes showed a very low release of siRNA after 3 h as well as after 6 h incubation A. In SIFIn the case of tableted lipoplexes, release of siRNA was observed after 1 h incubation in SIF (>25%), which kept increasing after 3 h and remained stable after 6 h incubation, respectively. The amount of intact siRNA present within the tableted lipoplexes was found around 13% after 1 h incubation in SIF, with no intact siRNA recovered from tableted lipoplexes after 3 h incubation B. It canThe percentage of siRNA released from the fresh lipoplexes and the tableted lipoplexes, once submitted to intestinal environment conditions, was found to be different.In order to assess whether this difference was due to the compressive stresses, or the presence of the excipients used for the preparation of the tablets, freshly prepared lipoplexes were incubated in an excipient solution and the effect of this incubation on the release of siRNA was evaluated. It was observed that the presence of excipients did not contribute towards the release of siRNA from the fresh lipoplexes incubated in SGF for 1 h A, nor toAs shown in As with fresh lipoplexes, incubation in SIF completely collapsed their efficacy. In summary, whether the lipoplexes were fresh or resuspended from a tablet, their efficacy was maintained after SGF challenge but a significant loss of activity was observed after SIF challenge.Oral delivery of siRNAs has been considered ever since the Nobel Prize was awarded to RNA interference in 2006 . Since tIn order to assess siRNA stability, we used an original method previously published by our research group that allowed quantification of both siRNA retained inside and released from its nanocarrier by assaying siRNA lipoplexes through gel electrophoresis without or with NaCl-Triton treatment, measuring integrated optical density for each siRNA band, and further calculating the percentages of intact siRNA either released in the medium or remaining in the lipoplex, relative to naked siRNA total load . This meIn our study, the naked siRNA in solution could resist gastric challenges for one hour at physiological temperature, but it was progressively altered in intestinal conditions, with a total degradation at 3 h. When documented in the literature, the stability of naked siRNA in gastric media varied according to the experimental conditions of the assays. Hence, siRNA tested in simulated gastric fluid at pH 1.2 without pepsin was stable for one hour at room temperature , while sSince naked siRNA in itself cannot enter cells to exert RNA interference, its incorporation into nanovectors is mandatory to allow for its intracellular delivery. Several nanosystems of siRNA have been shown to protect, to some extent, siRNA from gastro-intestinal challenge, mainly including polymeric nanoparticles ,16,17,18Currently, the incorporation of siRNA nanovectors in solid oral dosage forms and further determination of their fate in gastrointestinal conditions are scarce. Indeed, to our best knowledge, one single article reported the formulation of cell-penetrating peptides–siRNA nanocomplexes into solid dispersions intended for oral delivery that are stable in simulated gastric conditions . No comp


Moreover, stomatal morphology seemed to have less effect on the initial and final stomatal conductance, and there was a minimal correlation between steady-state and non-steady-state stomatal conductance among different rice genotypes. These results highlight the important role of stomatal morphology in regulating photosynthetic efficiency and plant growth under fluctuating light conditions. To simultaneously enhance leaf iWUE when improving the photosynthetic efficiency under fluctuating light, it may be necessary to take biochemical processes into account in the future.Plants are often confronted with light fluctuations from seconds to minutes due to altering sun angles, mutual shading, and clouds under natural conditions, which causes a massive carbon loss and water waste. The effect of stomatal morphology on the response of leaf gas exchange to fluctuating light remains disputable. In this study, we investigated the differences in leaf stomatal morphology and photosynthetic induction across twelve rice genotypes after a stepwise increase in light intensity. A negative correlation was observed between stomatal size and density across rice genotypes. Smaller and denser stomata contributed to a faster stomatal response under fluctuating light. Plants with faster stomatal opening also showed faster photosynthetic induction and higher biomass accumulation but lower intrinsic water use efficiency ( It is urgent to increase crop productivity to meet the demands of the growing population . Rice isStomatal kinetics is controlled by guard cell turgidity, which is sensitive to light intensity . Still, iWUE) has always been an important issue with increasing demand to improve crop yield and the amount of carbon assimilation per unit of water used  the effect of stomatal morphology on the dynamic response of stomatal conductance and photosynthetic rate, (2) the relationship between the steady-state and non-steady-state gas exchange, and (3) the effect of stomatal kinetics on plant growth and Twelve rice genotypes, including T1 (4X), A1 (4X), WH (4X), Yangdao6 (4X), Yongyou12, Yangdao6 (2x), N22, WH (2x), Huanghuazhan (HHZ), Yangliangyou6 (YLY6), Guangzhan63 (GCA), and Guangchangai (GCA), were chosen in this study . T1 (4X)2 concentration was maintained at 400 μmol mol–1; the IRGA flow rate was set at 500 μmol s–1; the chamber temperature was kept at 28°C; and the leaf-to-air vapor-pressure deficit (VPDleaf–air) was maintained at 1.3 ± 0.2. All measurements were conducted using the youngest fully expanded leaf from 9:00 a.m. to 16:00 p.m. in April 2018.All gas exchange parameters were recorded using a Li-Cor 6400XT portable gas exchange system  in the open air on sunny days. A 2 cm × 3 cm chamber was used, and a LED 6400-02B lamp served as the light source. Throughout the measurement, the reference infrared gas analyzer (IRGA) CO–2 s–1 until the photosynthetic rate (A) and stomatal conductance (gs) reached a steady state. Then, the PPFD was increased to 1,500 μmol m–2 s–1 until 600 s of light induction for A and gs. The data were recorded every 4 s. To estimate the response of stomatal opening to a stepwise increase in light intensity, P50g and P90g were calculated, which represent the time required for gs to reach 50 and 90% of the difference between the initial and final stomatal conductance (gsi and gsf) after switching to high light conditions. Similarly, the response rate of photosynthesis to a stepwise increase in light intensity was obtained by calculating the time required for A to reach 50 and 90% (P50A and P90A) of the difference between the initial and final photosynthetic rate (Ai and Af)  of 100 μmol m and Af) .Cg) and Carbon loss (Cl) represent the integrated amount of CO2 uptake and loss during light induction, which were calculated as follows:Carbon gain  solution. The abaxial surface of the leaf was obtained by gently scratching the adaxial surface using blades. Afterward, the transparent epidermis was kept in clean water. The epidermal impressions were placed on the microscope slides and analyzed using an optical microscope equipped with a digital camera. In each treatment, five slides from three plants were used for determination. Stomatal density and number were determined using ImageJ. Five stomata were randomly selected from each slide to determine the stomatal size, which was calculated by multiplying stomatal length and width.Once all gas exchange and stomatal morphology measurements were accomplished, one plant was sampled per pot to estimate the plant growth. The plants were then separated into leaves and stems. A leaf area meter  was used to determine the total leaf area. Besides, the number of stems per plant was recorded. Finally, to determine the total dry weight of the aboveground part, leaves and stems were oven-dried at 80°C to constant weight.One-way ANOVA and the least-significant difference (LSD) test were used to assess the measured parameters using SPSS 21.0 . Linear regression was analyzed to test the correlations between the measured parameters using SigmaPlot 12.5 .50g and P90g among twelve rice genotypes  and YD6 (4x) than for WH (2x), and YD6 (2x), and it was the same case for P50g and P50A. Leaf carbon gain (Cg) and carbon loss (Cl) significantly varied among twelve rice genotypes during 600 s of light induction  and photosynthetic rate (Ai and Af) among rice genotypes (gsf and Af than WH (2x) and YD6 (2x) (Wi and Wf) also significantly varied among rice genotypes  . The inienotypes . Signifiand P90g . Howeverobserved . Leaf iWng light .2 and from 252 to 730 mm–2, respectively (50g and P90g (50g and P90g (Cg)  .The natural variations of plant growth were further explored within twelve rice genotypes, including the number of tillers, total leaf area, leaf mass per area (LMA), and biomass . Similargs) is known to be determined by stomatal morphology and aperture. Generally, there are significant negative correlations between stomatal size and density across or within species (gs and photosynthetic rate (A) under constant light conditions  and promote the initial response of stomatal conductance and photosynthetic rate to fluctuating light  and stomatal conductance (gsi and gsf), which again indicates that excessively higher gs will decrease the iWUE (Stomata are micropores composed of pairs of guard cells on the epidermis of leaves, which control the balance of CO in iWUE . This aswer iWUE . Also, wthe iWUE .iWUE. Further evidence is still needed to evaluate the relationship between steady-state and non-steady-state gas exchange. This study mainly highlights the important role of stomatal morphology in regulating leaf photosynthetic induction and plant growth. To simultaneously improve photosynthetic efficiency and iWUE, it may be necessary to take biochemical processes into account in the future.This study also shows that genotypes with larger stomatal sizes generally have a lower stomatal density. A higher density of smaller stomata will contribute to faster stomatal kinetics and, thereafter, higher biomass accumulation but reduce the leaf The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.ZX and JH planned and designed the experiment and analyzed the data and wrote the manuscript. ZX and ZD performed the plant propagation and leaf gas exchange experiments. YW and DY performed the stomatal anatomy experiment. All authors revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Picobirnaviruses (PBVs) have been detected in several species of animals worldwide; however, data pertaining to their presence in Australian wild and domestic animals are limited. Although PBVs are mostly found in faecal samples, their detection in blood and respiratory tract samples raises questions concerning their tropism and pathogenicity. We report here PBV detection in wild deer and cattle from southeastern Australia. Through metagenomics, the presence of PBV genogroups I (GI) and II (GII) were detected in deer serum and plasma. Molecular epidemiology studies targeting the partial RNA-dependent RNA polymerase gene were performed in a wide range of specimens  collected from wild deer and cattle, with PCR amplification obtained in all specimen types except lung and spleen. Our results reveal the predominance of GI and concomitant detection of both genogroups in wild deer and cattle. In concordance with other studies, the detected GI sequences displayed high genetic diversity, however in contrast, GII sequences clustered into three distinct clades. Detection of both genogroups in the upper respiratory tract  of deer in the present study gives more evidence about the respiratory tract tropism of PBV. Although much remains unknown about the epidemiology and tropism of PBVs, our study suggests a wide distribution of these viruses in southeastern Australia. Picobirnaviruses (PBVs) are members of the family Picobirnaviridae and have a non-enveloped bi-segmented double-stranded RNA (dsRNA) genome measuring 35–40 nm in diameter. The genome of a PBV consists of two segments: segment 1 (~2.4–2.7 kb in size) containing the capsid gene and an additional open reading frame, which encodes a putative protein of an unknown function; and segment 2 (~1.7–1.9 kb in size), containing the RNA-dependent RNA polymerase (RdRp) gene [Capreolus capreolus) in Slovenia tested positive for PBV GI by polymerase chain reaction (PCR) [Oryctolagus cuniculus) [Sarcophilus harrisii) [PBVs were initially discovered in a small number of faecal specimens during the investigation of gastroenteritis in children in 1988 . Since ton (PCR) . In Auston (PCR) , wild bion (PCR) ,8, Europarrisii) .Macaca mulatta and Macaca fascicularis) [Although PBVs have been detected in faeces/gut contents of humans and various animal species with diarrhoea, the role of PBV as a causative agent of diarrhoea is still controversial. Indeed, its presence has also been reported in asymptomatic hosts, leading to the assumption that PBVs may be opportunistic enteric pathogens ,2,4,11. cularis) , and in cularis)  and domecularis) , suggestTo date, the difference in frequency and distribution between GI and GII is considerable, with a higher prevalence of GI ,15,18,19The aims of the present study were: (i) to detect novel RNA viruses in serum and plasma samples collected in wild deer from southeastern Australia, and (ii) to expand our knowledge on the epidemiology of PBV by investigating their presence and quantifying their genetic diversity in wild deer and cattle from southeastern Australia. These objectives were achieved by high-throughput sequencing and RT-PCR coupled with Sanger sequencing. This study reports for the first time the presence, molecular characterisation, and genotypic differentiation of PBVs in a wide range of samples from wild deer and cattle.Dama dama) in the Liverpool Plains and rusa deer (Rusa timorensis) at Wollongong, New South Wales (g). Three serum and two plasma samples were selected for this analysis. All samples were stored at −80 °C until next-generation sequencing was carried out.This study used samples collected as part of a disease investigation in Australian wild deer . Brieflyth Wales . Blood wg for 1 min. Filtrates were then nuclease treated using benzonase and micrococcal nuclease and incubated at 37 °C for 2 h, followed by nucleic acid extraction using the QIAamp Viral RNA mini kit  without adding any carrier RNA. This approach enabled both DNA and RNA virus nucleic acids to be extracted using this kit.In order to remove impurities such as host cells and bacteria, viral enrichment was conducted as per published protocols with minor modifications ,31. Brie® SV Gel and PCR Clean-Up kit  and quantified using a Qubit dsDNA high sensitivity assay kit with Qubit Fluorometer v3.0 .cDNA synthesis and amplification were performed using the Whole Transcriptome Amplification Kit . WTA2 PCR products were then purified using the WizardSequencing libraries were constructed using the Nextera XT Flexi DNA Library kit  according to the manufacturer’s instructions. Libraries were then pooled and sequenced with the Illumina Hiseq2500 platform and using a 2 × 150 PE high-output flow cell at the Australian Genome Research Facility, Melbourne, Australia.−5 to remove potential false positives. All contigs that returned blast hits were filtered to remove non-viral reads that likely correspond to fungal or bacterial species. Virus contigs of interest (>500 nucleotides and query cover >50%) were imported in Geneious software , and putative ORFs were predicted using the same software. Multiple alignment with reference sequences was performed using MAFFT (version 7) [The raw data were demultiplexed, and Trim_Galore v0.4.5 was used for quality control of the reads, with the minimum sequence length set to 50 bp and Phred Quality of 25. Host genome reads were filtered out by mapping the reads to deer RefSeq genome (GenBank GCF_002102435.1) using bwa v0.7.17, samtools v1.6, and bedtools v2.26. The cleaned reads were de novo assembled using SPAdes v3.10.1  with parrsion 7) . Phylogersion 7) , using tg). Lung, trachea, and spleen samples were collected from each carcass and treated with homemade RNA and DNA preservation solution consisting of 7.44 g of EDTA, 7.35 g of sodium citrate trisodium salt dihydrate, and 700 g of ammonium sulfate in 1 L of water [Deer culled for other reasons were opportunistically sampled during field necropsies with the assistance of recreational and professional hunters during August 2019 and October 2020 in New South Wales and Victoria . Samplinw/v) suspensions in phosphate-buffered saline (PBS pH 7.2) for RNA extraction. A total of 0.1 g of thawed sample was suspended in 1 mL of PBS. The suspension was stored overnight at −80 °C, then centrifuged at 4000× g for 15 min at 4 °C. RNA was extracted from serum, transport media , and 10% faecal suspensions using a QIAamp® Viral RNA Mini Kit , according to the manufacturer’s instructions. The RNA was eluted in 50 µL of resuspension buffer and used as the template for cDNA synthesis.Aliquots of 100 mg (0.1 g) of spleen, lung, and trachea specimens were used for RNA extraction using 1 mL TRIsure™ , and following the manufacturer’s instructions. After drying, the RNA pellet was resuspended in 30 μL of DEPC-treated water and used as the template for cDNA synthesis. Faecal specimens were converted to 10%  according to the manufacturer’s instructions. Nucleotide sequencing was performed by Sanger sequencing at the Australian Genome Research Facility, Melbourne, Australia. Sequences were deposited in GenBank under accession numbers MZ048540-MZ048585 (genogroup I) and MZ048586-MZ048608 (genogroup II).The viral RNA was reverse transcribed using Tetro cDNA Synthesis Kit  with random hexamers, following the manufacturer’s instructions. The cDNA was used as a template for the PCRs to detect the two PBV genogroups . All primers amplified PCR product fragments of different sizes of segment 2’s RdRp gene. To detect genogroup I, primers AACCCAAATTCACAGTGTCTTGG and AGAGGATGGTACTTCACATTCTC  were useTo avoid contamination of our results, we took a number of precautions, including the use of a laminar flow cabinet equipped with a UV lamp for aliquoting and preparing samples. Additionally, RNA extraction, PCR preparation, and PCR were performed in physically separated rooms, and filter pipette tips were used for all pipetting. Extraction of RNA-negative samples (nuclease-free water) was also included for each extraction round and as negative controls in every PCR run.Nucleotide sequences were edited using Geneious software , and the final sequences were compared with PBV sequences deposited in the NCBI GenBank database, using the BLAST server . Some GIThe geographic dynamics of the PBV GII detected in the present study were analysed under the structured coalescent model  in BEASTIllumina sequencing of five deer sample libraries was initially performed to investigate the presence of novel RNA viruses in a sub-section of deer serum samples. Sequencing generated a total of 205,614,103 paired-end (PE) reads with library size ranges of 38,934,907 to 47,809,012 PE reads. After trimming, 93% of the reads (191 million) were retained, with 60% of these retained trimmed reads (115 million) not mapping to published host DNA. In each of the libraries, phages made up at least 80% of the total number of viral contigs. Further analysis of eukaryotic viral contigs revealed sequences identified as picobirnaviruses segment 2 (or RdRp) in four deer samples with lengths ranging from 881 to 1719 nucleotides .Marmota himalayana), and Tibetan antelope (Pantholops hodgsonii)  .Rusa unicolor), were sampled in Outer Melbourne, Yellingbo, and Bunyip  were tested by RT-PCR. Serum and faeces samples were collected from 71 deer , includid Bunyip . From 15d Bunyip . Of the d Bunyip . A totald Bunyip .n = 7) or GII (n = 3), sourced across multiple specimen types. For PBV genogroup I, the most frequent multi-specimen detection was faeces/serum, with one deer testing positive in three different specimens (There were 36 deer samples that tested positive for either PBV GI (pecimens . Converspecimens . Interespecimens .Macaca spp.), and humans derived from GenBank. The 4 GA-91 strain (AF246940) was used in the phylogenetic analysis as an outgroup.To determine genetic relationships between deer PBV GI samples and cognate PBVs , a phylogenetic tree was constructed based on a partial fragment of the RdRP gene, as has been performed previously . NucleotThe phylogenetic tree  revealedThe high nucleotide identities obtained in some groups suggest the presence of the same PBV clone across samples. Although nucleotide identities >95% and a high bootstrap value of 99% were observed in most of the PBVs detected in different specimens sourced from the same animal , the disThe animal PBV sequence most closely related to both deer and cattle PBVs was the porcine PBV KM361930) with 93.7% nucleotide identity compared to V92 faeces and 92% with LV7, LV10, and LV12. To determine genetic relationships between deer PBV GII sequences with cognate PBVs, a phylogenetic tree was constructed based on a 193 bp fragment of the RdRP gene, as has been performed previously  Figure . In tota930 with Phylogenetic analysis demonstrated that the GII samples were distributed between eight separate branches, with three highly supported groups , suggesting relationships between the GII circulating in these areas . High nuIdentical sequences and monophyletic clustering were obtained in PBV GII sourced from different specimens in deer N329 and N331 . The dis−5–0.49). Migration rate from NSW to VIC was median 71.77, 95% HPD 7.6 × 10−7–613.34) and from VIC to NSW was median 0.93 (95% HPD 2.21 × 10−7–48.36). The location of most recent common ancestor of the PBV GII detected in the present study was in Victoria, with a relatively high posterior probability (83%)  .Australia’s wild deer populations have increased in abundance and distribution during recent decades , and theTo our knowledge, this study reports for the first time: (i) the presence, molecular characterisation, and phylogenetic relationship of PBVs infecting deer and cattle in Australia, and (ii) the screening of PBVs in a wide range of sample types  from the same animal. To date, only two reports have detected PBV in blood ,17 by hiOur findings describe the existence of PBV GI and GII in deer and livestock in Australia. Both genogroups were detected in the same animal, suggesting that they can co-infect one single host simultaneously. Notably, similar to other reports in the literature ,4, PBV GNo amplification of PBV sequences was detected in the lung or spleen, suggesting the absence of chronic systemic infection in the wild deer sampled for this study. Since PBVs have been mostly detected in faeces/gut contents of animals and humans with or without diarrhoea, they were considered as opportunistic enteric pathogens of mammals ,28. In fA structured Bayesian coalescent model was used to infer PBV GII dynamics between the southern (Victoria) and northern  sampling locations. The maximum clade credibility Bayesian tree was broadly congruent with the tree from the maximum likelihood (ML) analysis. The Bayesian analysis pointed to the possible role of Victoria as a PBV GII distribution source for the southeast of Australia. Indeed, the analyses identified Victoria as the location of origin for this group of viruses with more than 80% confidence. Similarly, the PBV GII virus population size in Victoria would also appear to be larger. While these results provide a first insight into the PBV GII dynamics, we acknowledge that the accuracy of the population size parameters in our analysis was limited, as reflected by the wide HPD. The same applies to the estimation of the migration rates between subpopulations, in which case the uncertainty of the estimates was particularly high. This is not surprising as it is well known that it is difficult to accurately estimate these parameters (more so with non-informative priors as it was in our case) especially when the sample size is relatively small as it was in this study . This isTo better understand the epidemiology of PBVs GII in deer and to define whether transmission to domestic animals occurs, there is a need to conduct a more intensive PBV surveillance in deer and cattle, possibly also including other geographical regions of Australia. However, whether GI and/or GII can also play a causal role in respiratory diseases remains to be determined. The lack of a suitable mammalian cell culture system and/or gnotobiotic animal models where PBVs are successfully propagated makes it difficult to determine the tissue tropism and pathogenesis of PBVs in mammals. This study illustrates how novel molecular techniques can provide a new understanding of viral epidemiology and evolution. Future studies will be necessary to understand the dynamics of virus circulation. Although much remains to be understood regarding the epidemiology of PBV, our study suggests that PBV may be widely distributed in deer and cattle in southeastern Australia. In conclusion, this first phylogenetic survey provides new knowledge and understanding of the putative host range and tropism of PBVs and confirms the high genetic diversity of GI.


Patients and Methods. We retrospectively evaluated the medical records of 12 children with IMD requiring PICU stay between January 2018 and July 2019.  Invasive meningococcal disease (IMD) is a serious infectious disease requiring stay in a pediatric intensive care unit (PICU) that continues to be associated with high morbidity and mortality rates. Prompt recognition, early antibiotic therapy, and aggressive supportive therapies can reduce mortality. We aimed to assess the clinical and laboratory characteristics of children with IMD.  We followed up 12 patients  with IMD  in PICU. All children were previously healthy and have not received meningococcal vaccines. Their pediatric risk of mortality (PRISM) scores varies between 5 and 37, four of the patients required mechanical ventilation, and the predicted mortality was 39% at admission. Seven patients had catecholamine refractory septic shock and disseminated intravascular coagulation (DIC). Three of the patients required extracorporeal treatment. The predominant serogroup is Men B (5/12). The mortality rate was 16.6% with early use of antibiotics, fluids, and other interventions.  Mortality related to IMD is higher among children with severe meningococcemia despite early interventions in PICU. Routine use of meningococcal vaccines during childhood would be a better strategy for controlling IMD in both developing and developed countries. Neisseria meningitidis is an important cause of morbidity and mortality in children worldwide [N. meningitides are classified into 12 serogroups according to the antigenic variability of their capsules, and among them, serogroups A, B, C, Y, W, and X are clinically important [Invasive meningococcal disease (IMD) due to orldwide . N. menimportant . While tmportant .Meningococcemia is a sudden onset, fulminant contagious disease requiring stay in an intensive care unit . DespiteN. meningitides with culture and/or the polymerase chain reaction (PCR) method in cerebrospinal fluid (CSF) and/or blood samples. Patient's age, gender, presence of underlying disease, and vaccination status were recorded. Complete blood count, peripheral blood smears, serum C reactive protein (CRP) and procalcitonin levels, arterial blood gas analysis, phrothrombin time (PT), activated partial thromboplastin time (aPTT), fibrinogen, D-dimer, and blood culture results were noted from medical records. CSF workup results were recorded for patients who were eligible for a lumbar puncture. Patients were diagnosed as disseminated intravascular coagulation (DIC) if they met the criteria for at least one of the following: platelet count <150000/mm3, fibrinogen level <250 mg/dL, D-dimer level >500 U/L, long PT, and PTT  [μg/kg/min) + dobutamine dose (μg/kg/min) + 100 × adrenaline dose (μg/ kg/ min) + 100 × noradrenaline dose (μg/kg/min) + 10 × milrinone dose (μg/kg/min) + 10,000 × vasopressin dose (U/kg/min). Prognosis of the patients has been classified as “died” or “discharged.”Patients who were admitted to the pediatric intensive care unit (PICU) of Sanliurfa Training and Research Hospital between January 2018 and June 2019 with a diagnosis of IMD were included. Diagnosis of IMD was confirmed by the detection of ctively) . Septic ctively) . PediatrTwelve children (five girls and seven boys) aged between 5 and 168 months with IMD were enrolled. All patients were reported to healthcare authorities, and all of the persons with a history of close contact were started on prophylactic treatment by the Local Public Health Department. The clinical, demographical, and laboratory findings of the children are summarized in Tables Three patients were diagnosed with meningococcemia , while the remaining nine were diagnosed with meningococcemia and meningitis. Four of the patients in our study were younger than one year of age (33.3%), three were aged between 1 to 5 years, and five (41.6%) were older than five years. One child was a member of a Syrian refugee family. None of the patients had been previously vaccinated with meningococcal vaccines. Two of the patients (cases 4 and 10) had no history of other childhood routine immunizations.PRISM scores vary between 5 and 37, and predicted mortality according to PRISM scores was between 1.7 and 94.2% . The higFever was the common presenting symptom for all the patients. The period time between the onset of symptoms and presentation varied between 12 and 72 hours, and all of the patients were referred because of fever and petechiae/purpuric lesions. Cases 3, 6, 11, and 12 presented with petechiae and purpuric lesions on extremities, case 7 had purpuric lesions only in the anal region, and the rest of the cases had lesions disseminated over the entire body.rd percentile) and a history of being treated for a symptom of fever within the previous two days. The patient presented with a history of extension posturing and convulsions at home, and purpuric lesions appeared within two hours of admittance. Purpura fulminans developed within hours, and the patient died on the fifth day of PICU admission.Five out of 12 patients had IMD due to serogroup B, and one case was due to serogroup W. All of the patients were given fluid resuscitation and antibiotic treatment of ceftriaxone (100 mg/kg/day 2 times or cefotaxime 200 mg/kg/day 4 times). The first dose of antibiotic treatment was given at the first hour of admission to the pediatric emergency care unit. Vancomycin was empirically given to case 4 due to suspected toxic shock syndrome until the causative bacteria had been identified . Seven pIMD continues to be an important public health issue that results in high rates of mortality and morbidity in childhood. Beginning treatment promptly and extensive therapy protocols are life-saving in these critically ill patients , 2, 8, 9Recognition of symptoms is of critical importance in diagnosing IMD. IMD should be in the differential diagnosis in every pediatric case presenting with fever and petechiae . DefinitN. meningitidis has become the most important target agent of vaccine studies after successful implementation of vaccines, resulting in decreased prevalence of the other two most common agents causing meningitis, Haemophilus influenzae tip B, and Streptococcus pneumoniae [eumoniae . None ofeumoniae . Meningoeumoniae . Serogroeumoniae . IMD andOur study has some limitations. This is a retrospective, short-term interval, single-center experience and includes only children requiring PICU. We did not show the serogroup in six out of 12 cases. However, we report 12 cases with IMD from the city with the largest birth cohort, and our study results highlight the severity of the infection among previously healthy children. We underline the importance of early antibiotic treatment accompanied by early and intense supportive therapy in PICU, and these interventions could decrease the predicted mortality rate at admission. Routine use of meningococcal vaccines during childhood would be a better strategy for controlling IMD in both developing and developed countries.


Supplemental Digital Content is available in the text This study aims to introduce a morphological classification of hyperextension tibial plateau fractures based on CT scans and to reveal the correlation between the anterior compression and posterior tension fractures.From January 2015 to January 2019, 37 patients with hyperextension tibial plateau fractures were studied retrospectively. Based on this classification, the fractures were divided into 2 groups: group A had anterolateral or anteromedial compression fractures while group B had both. Three observers classified the fractures and recorded the morphology and incidences of posterior plateau fractures and proximal fibular fractures.P < .05). However, there was no significant difference between the incidence of proximal fibular avulsion fractures in the 2 groups or the combined and non-combined type fractures in group B (P > .05).All 37 fractures were allocated to group A  and B . Of the posterior tibial plateau fractures, 10 (27%) fractures were defined as partial and 27 (73%) as total. Of the 37 fractures, 18 (49%) proximal fibular avulsion fractures were observed. There was a significant difference between groups A and B regarding the incidence of total posterior tibial plateau fractures (Hyperextension tibial plateau fractures with a decreased posterior slope angle always involve both the anteromedial and anterolateral plateaus. This CT-based classification may improve the understanding of fracture features and is helpful for planning treatment. Moreover, coronal deformity is evaluated through anteroposterior radiographs, inhibiting the detailed analysis of fracture features on the joint surface of the tibial plateau. Hence, a comprehensive, detailed hyperextension TPF classification based on CT is urgently needed.Of all the tibial plateau fractures (TPFs), hyperextension TPFs are a relatively rare subtype  and are often combined with multiple soft tissue injuries. first showed the fracture pattern caused by hyperextension varus injury and that these fractures have a high incidence of associated ligament injuries. Bennett et al and Conesa et al described the formative mechanism of anterior small and large type compression fractures, respectively. These studies focused more on the relationship between anteromedial compression fractures and posterolateral ligament injuries but did not refer to concurrent posterior TPFs. Bicondylar varus hyperextension TPFs were first depicted by Firoozabadi et al, who summarized the radiographic hallmarks of this fracture. Gonzalez et al further expanded bicondylar TPFs into pure, varus and valgus types. However, “bicondylar” merely demonstrates that medial and lateral columns are involved and cannot show accurate fracture locations in anteroposterior direction. Few studies referred to the fracture morphology of posterior plateaus at all or briefly mentioned it as “simple.” Meanwhile, being an important risk factor for accelerated knee osteoarthritis, it is rational to classify the fractures based on coronal deformities, but rotational force is another issue requiring consideration. Currently, because of a lack of a commonly accepted classification system based on anatomic fracture morphology, some confusing terms are used to indicate fracture subtypes caused by hyperextension injuries, such as “reverse Segond” fractures and non-dislocated hyperextension TPFs.In 2001, Chiba et alThe purpose of this retrospective study, therefore, is to introduce a new systematic classification for hyperextension TPFs based on CT images and to illustrate the correlation between anterior compression fractures, posterior tension fractures and proximal fibular avulsion fractures (PFAFs).2 All patients gave their informed consent prior to their inclusion in the study.Ethical approval was obtained by the ethics committee of the Third Hospital of Hebei Medical University. All procedures were performed in accordance with the tenets of the Declaration of Helsinki.From January 2015 to January 2019, a total of 37 patients  with unilateral hyperextension TPF were selected from 543 potential TPF patients. The mean age of the patient was 51.0 ± 8.9, with a range from 23 to 63 years old. The causes of the injuries included falling from a height (n = 14), vehicle accident (n = 13), motorbike or electric motorbike accident (n = 7), and sports-related injuries (n = 3).Diagnosis was established based on the previously described definition by Gonzalez et al1.anteromedial or/and anterolateral compression fractures,2.tension failure of partial or total posterior cortex, or proximal fibular avulsion fractures,3.posterior tibial slope angle (PTSA) less than 11°.The inclusion criteria were patients aged between 18 and 65 years with a complete collection of radiographs and CT images. The exclusion criteria included:1.patients aged below 18 years because of their immature bones,2.patients older than 65 because of the possible existence of osteoporosis,3.pathologic fractures,4.early fractures or knee arthritis with the abnormal alignment of lower extremities,5.other fractures occurring on the same lower extremity such as femur and patella fractures.2.1 study  are allocated to group B. Chiba et al divide the anterolateral or anteromedial compression fractures into a small or large type based on the fragment size  quadrants including anteromedian plateau . 3D reconstructive images were reconstructed using MIMICS software . In order to visualize the articular surface of the reconstructed tibial plateau, we removed the femur and patella. All the radiographs, CT scans and 3D images of the selected fractures were reviewed by 3 senior orthopaedic surgeons. They first independently evaluated the images and then worked together to reach a consensus about the new classification, and all of the fractures were classified. Then, they observed the morphological characteristics of posterior TPFs. According to the size of fragments lost from the posterior tibial metaphysis, the posterior TPFs were allocated as partial or total, and then they were further divided into separated and intact subtypes Fig. . The inc2.2P value of less than .05 was considered statistically significant.The categorical data were compared with two-tailed Fisher exact tests to assess the correlation between anterior and posterior TPFs, as well as PFAFs. Analyses were performed using SPSSfor windows statistical software . A 3Based on our new classification, all 37 fractures were allocated to group A  or group B . Of the 37 fractures, 10 (27%) were defined as partial and 27 (73%) were defined as total. In our series, PFAFs were found in 18 (49%) fractures.In group A, there were partial (n = 10) and total (n = 5) fractures . In the large type of group A, 6 out of 7 fractures involved anterolateral quadrants associated with intact medial column fractures.In group B, there were partial (n = 2) and total (n = 20) fractures . Of the 22 group B fractures, 11 were categorized as combined fractures, and of these, PFAFs were found in 9 (82%) cases.P = .006). Regarding the incidence of PFAFs, there was no significant difference between group A and B (P = .092) (Table P = .08).There was a significant difference between groups A and B regarding the incidence of total posterior TPFs (2) Table , and als4This new CT-based classification of hyperextension TPFs clarifies the relationship between the subtypes and the incidence of related fractures. We found that the hyperextension TPFs with a decreased PTSA which involved anterior quadrants were common and often associated with total posterior fractures. Meanwhile, the small type of anterior compression fractures tended to be found with intact posterior TPFs, and the large type of anterolateral compression fractures was always connected with intact medial column fractures. found the agreement with the pre-operation plan increased from 58% to 71% with an additional CT scan which enhanced the reliability of different classifications, but whether 3D-CT can improve the reliability of characterization and classification of TPFs is still debatable.,18Utilizing CT scans has opened a new chapter in TPF classification. Chan et al found 3D-CT could minimize measurement deviations because it could overcome the influence of the orientation of the patient's legs at the time of the CT scan and the width of the CT slices. By mesuring 10-case 3D reconstructed TPF models, Assink et al concluded that 3D-CT could show the exact fracture characteristics such as step-off and displacemet of articular fractures. Therefore, 3D-CT reconstruction has advantages over ordianary CT scans, and it was applied in this study.In a comparative study including 30 knees, Hirschmann et al found only 16 fractures abided by the diagnostic criteria of hyperextension TPFs, and up to 13 fractures involved both anterior quadrants. Of these 13 fractures, it was observed that all of the posterior tension TPFs were intact, contrasting with our observations. Xie et al adopted a 3D fracture mapping technique to analyze the correlation between injury mechanism and fracture morphology and found that the varus and valgus hyperextension TPFs constituted 13% and 3% of the 353 TPFs in their case series, respectively. Of the 47 varus fractures, 24 fractures were combined with PFAFs and the size of medial plateau fragments was varied. Luo et al innovatively viewed the posterior tibial plateau as a single column. In a case series of 74 bicondylar TPFs, Streubel et al found 68% of the fractures had an average of over 5°difference of PTSAs between posterolateral and posteromedial fragments and concluded that ignoring the posterior TPFs might lead to inappropriate utilization of treatment techniques and poor outcomes.Concern has been given to injury mechanisms and related soft tissue injuries. Through a retrospective analysis of 514 TPFs, Hua et alvarus or valgus force might be the main factor; while total posterior TPFs were always associated with group B fractures that were highly likely to result from high-energy trauma, and hyperextension force plays an more important role than varus or valgus force, leading to relatively more severe posterior fractures. In addition, based on the correlation between intact posterior fractures and small type fractures in Group B, this fracture pattern may be caused by an axial force on the over-hyperextension knee, and further leaded to both the intact posterior shear fractures and anterior compressed fractures quadrants, or servere posterior soft tissue injury, such as posterior capsule disruption, anterior and posterior cruciate ligament injuries, without definite posterior fractures. If a fracture cannot be classified into any type of our classification in clinical practice, extra attention should be paid for latent soft tissue injury. Therefore, a reasonable fixation process can be made due to the principal reduction and fixation through the converse injury mechanism based on this classification in clinical practice.Subtypes in our classification showed a close relationship with injury mechanism, which can help us to understand fracture charcteristics. Partial posterior TPFs were often related to group A fractures, which might often caused by low-energy trauma such as sport-related injury, and ,14,27 have proposed the hypothesis that knee rotation might play a role in hyperextension TPFs, but no study has yet proved it with concrete evidence. According to our classification, the combined type fractures can indicate knee rotation because the different sizes of anterolateral and anteromedial fragments show the relative location between the femur and tibia when an injury occurs. Regarding the concurrent PFAFs, there was no significant difference between combined type fractures and other type fractures in group B, which means hyperextension force might play a more important role than rotation force. However, the combined type fractures had a high incidence of concurrent PFAFs (82%), which is likely to have resulted from both knee rotation and hyperextension forces during the injury process because of the rotation-resisting and hyperextension-resisting function of ligaments attached to the proximal part of the fibula. Therefore, it is necessary to fix the concurrent PFAFs or lateral collateral ligaments if the injured knee instability still exists after tibial fracture fixation .Many studies showed good intraobserver and interobserver reliability, the mean Kappa value was 0.939 and 0.955, respectively. Second, it may facilitate hyperextensive TPF research because it contains all of the hyperextension TPF patterns reported in previous literature,6,10,23 and each fracture pattern only matches 1 certain type. Finally, it helps us choose suitable operative approaches for fracture fixation. Before fixing anterior fragments, the reduction of posterior TPFs should be considered first, and an additional posterior approach may be needed for separated posterior TPFs. Regarding group A fractures, 1 anterolateral or anteromedial surgical exposure is straightforward based on the location of anterior fragments, but except for those little posterior fragaments with a stable knee joint, another posterior incision is always necessary in the diagonal direction of the anterior fractures. Anteromedial compression fractures in group A often combine with PFAFs, which need to be fixed through an additional lateral approach; generally, the anterolateral and medial incisions are adopted when anterolateral compression fractures combined with intact medial plateau fractures . Moreover, this fracture pattern should be concerning because they resemble Wahlquist type C fractures, which have a high possibility of severe concurrent complications, such as compartment syndrome and neurovascular injures. Regarding the majority of group B fractures, the anterolateral and posteromedial approaches are recommended,30 , but for small type fractures of group B, the modified anterior middle approach is suggested.The advantages of our classification include: first, it is a comprehensive and detailed classification based on the fracture morphology of 4 quadrants of tibial plateau. This anatomically oriented classification including 2 columns and 4 quadrants can be easily remembered and used, and previous literatureHowever, our classification has several weaknesses, one of which is that the anteromedial or/and anterolateral compression fractures without posterior TPFs or PFAFs, potentially associated with multiple ligament injuries, were not selected in our study. These are, however, also created by hyperextension injuries. In light of this, an MRI scan is necessary for evaluating the related ligament injuries. The second weakness is how to accurately and quantitatively measure the knee rotation angles of different types in our classification. The authors suggest conducting a large multi-center study to overcome these drawbacks.The limitations of the study are as follows. First, the statistical sample size was small, which reduced the validity of the study and increased the margin of error. Second, the inherent features of the retrospective study, as well as the observers’ preference, experience, and ability may have influenced the classification of the fractures. Third, ligament injuries may also affect the clinical outcomes, but assessing these injuries was impossible because MRI was not performed in this study.5The hyperextension TPFs with a decreased PTSA tend to involve both anterior quadrants which are frequently combined with total posterior TPFs. Our classification focuses on the morphological characteristics of and correlation between anterior compression fractures and related posterior tension fractures, which may enhance our understanding of hyperextension TPFs and help us make more accurate pre-operative planning.Grateful acknowledgement is made to my three colleagues Professor Xu Zhang, Xinzhong Shao, and Yadong Yu who voluntarily classified the selected fractures using their deep clinical experience and precious time. We also sincerely appreciate Tom Speed who helped us to proofread the article.Conceptualization: Aqin Peng.Data curation: Xiao Zhang, Xiaochen Tian.Formal analysis: Shuai Wang, Yaning Hu, Shuo Pan.Investigation: Xiaochen Tian, Shuo Pan.Project administration: Xiao Zhang.Resources: Xiaochen Tian.Software: Shuai Wang, Yaning Hu.Supervision: Aqin Peng.Writing – original draft: Xiao Zhang.Writing – review & editing: Xiao Zhang.


P < 0.05, respectively, were uncovered. After PPI network construction, the top five hub genes associated with UA were extracted, including APP, MAPK3, MMP9, CD40 and CD40LG, whereas those associated with MI were PPARG, MAPK1, MMP9, AGT, and TGFB1. The establishment of the aforementioned candidate key genes, as well as the enriched signaling cascades, provides promising molecular marker for OSA-related ACS, which will to provide a certain predictive value for the occurrence of ACS in OSA patients in the future.Although obstructive sleep apnea (OSA) has been clinically reported to be associated with acute coronary syndrome (ACS), the pathogenesis between the two is unclear. Herein, we analyzed and screened out the prospective molecular marker. To explore the candidate genes, as well as signaling cascades involved in ACS related to OSA, we extracted the integrated differentially expressed genes (DEGs) from the intersection of genes from the Gene Expression Omnibus (GEO) cohorts and text mining, followed by enrichment of the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein–protein interaction (PPI) network and the matching hub gene. A total of 17 and 56 integrated human DEGs in unstable angina (UA) and myocardial infarction (MI) group associated with OSAs that met the criteria of |log2 fold change (FC)|≥ 1, adjusted  Obstructive sleep apnea (OSA) is highly prevalent in patients with cardiovascular diseases8. Increasing evidence indicates that OSA is associated with incidence and progression of coronary artery disease11 and cerebrovascular disease12. Compared with the general population, prevalence of OSA is higher in acute coronary syndrome (ACS) patients and ranges from 36 to 63% across various ethnicities13. Notably, among patients with coronary artery disease, those with ACS represent a high-risk subset and generally have higher mortality than patients with stable angina14. In addition, observational studies have examined whether OSA significantly increased the risk of recurrent cardiovascular events in patients with ACS and/or undergoing percutaneous coronary intervention (PCI)18. Despite the huge advancements in ACS research, the prognosis of ACS treatment is still poor. With the onset age of ACS patients gradually getting younger, it is imperative to establish the etiology, as well as the molecular features, of ACS disease. Therefore, we explore the molecular biomarkers by studying the correlation between OSA and ACS disease to provide evidence for early diagnosis, prevention, and treatment of this disease.Obstructive sleep apnea (OSA) represents a severely underdiagnosed (~ 80%) form of sleep-disordered breathing19. Though the pathogenesis of OSA has been found to be related to ACS recently, its pathogenesis, as well as the molecular mechanism remain unknown. Hence, we need to utilize the gene expression chip in the bulletin database and analyze its data through modern software to find new diagnostic markers and therapeutic targets20.At present, high-throughput sequencing techniques such as molecular diagnosis, prognosis estimation, as well as drug target discovery , are gradually considered to have important clinical significance in disease research. The Integrated Gene Expression Database (GEO), a publicly available website supported by the National Center for Biotechnology Information (NCBI), harbors dozens of basic experimental disease gene expression patterns and is extensively employed to explore key genes and prospective mechanisms of disease onset and development22. Then, the genes related to obstructive sleep apnea were obtained by text mining. We use the online tool Venny to analyze the intersection of DEG and text mining gene sets to obtain common genes, and we further used different bioinformatics methods to perform gene ontology, signal pathway enrichment annotations, protein and protein interactions for these common genes the study. In this article, we have studied candidate genes and signal pathways involved in ACS related to OSA, which will help provide a certain predictive value for the occurrence of ACS in OSA patients in the future.In this study, we retrieved human unstable angina (UA) and myocardial infarction (MI) gene expression patterns GSE60993 and GSE24519 from the GEO website. After that, the R software (version 3.6.3) was used to screen for differentially expressed genes (DEG)https://www.ncbi.nlm.nih.gov/geo/)23. The GSE60993 cohort contains seven normal control and nine UA samples, while the GSE24519 dataset includes four normal control and four MI samples.We abstracted the gene expression chip data GSE60993 and GSE24519 from the NCBI Gene Expression Comprehensive (GEO) web resource (P < 0.05), and we selected the remarkable DEGs for downstream analyses24. In order to further investigate DEGs, we selected 10 up-regulated and 10 down-regulated mRNAs with the most fold change as the candidate DEGs for subsequent studies |≥ 1, adjusted http://pubmed2ensembl.ls.manchester.ac.uk/). When manipulated, pubmed2ensembl retrieves all the gene names found in the existing literature relevant to the search topic. We searched for the concept of “obstructive sleep apnea”. We then screened all the genes associated with the topic from the results. Finally, we used the gene set obtained by text mining and the previously obtained differential gene set for the next step of analysis after the intersection.We carried out the text mining based on the pubmed2ensembl public tool (https://david.ncifcrf.gov/). The GO annotation and KEGG pathway enrichment were carried out using the web resource27, which provided a sequence of functional annotation tools for systematic analysis of biological significance of gene lists. The above gene tables were analyzed with P < 0.05 as the significant threshold.The obtained DEGs were imported to David V. 6.8  data encoded by DEGhttps://hiplot.com.cn/basic).In order to further analyze whether the differentially expressed target mRNA related to prognosis has diagnostic value, subject receiver operating characteristic curve (ROC) analysis uses the open-source network tool Hiplot , 15 cell component terms (CC), and 8 molecular function terms (MF) were uncovered in the DEGs integrated by UA. The KEGG enrichment assessment demonstrated that the integrated DEGs were remarkably enriched in the KEGG cascade Toxoplasmosis, Asthma and Primary immunodeficiency in UA group Fig. B and ProBased on the 17 UA group genes and the 56 MI group genes, the Cytoscape publicly available platform and the STRING resource were employed to develop the PPI network, perform module analysis, and visualization. Consequently, we developed a PPI network bearing 24 crosstalk based on 15 integrated DEGs related to UA  is Aβ, which aggregates into Aβ plaques. According to the amyloid cascade hypothesis, it is these plaques that are responsible for AD pathology55. In Antoniades et al. 's study, CD40 was found to be involved in the immune pathogenesis of ACS 56 due to its bi-cellular activation through the signaling pathways C-Jun, NF-κB and ERK 1/2, resulting in the secretion of inflammatory cytokines, adhesion molecules, and platelet activation55. However, soluble forms of CD40 and CD40L were significantly associated with adverse cardiovascular events in patients with ACS58, suggesting that they are potential targets for therapeutic agents 56. A recent study found that the soluble CD40 ligand (sCD40L) level of OSA patients is significantly increased, and it can be improved by continuous positive airway pressure therapy59. This means that OSA seems to have a clear correlation with the pre-atherosclerotic state, and this state can be continuously monitored by measuring the level of sCD40L.CD40 is a costimulatory molecule in the constitutive expression of B lymphocytes and is expressed in a variety of cells, such as endothelial cells (ECs), monocytes, macrophages and smooth muscle cells (SMCs)60. MMPs are a family of zinc-dependent proteinases capable of degrading various structural components of ECM, thus leading to ECM destruction and plaque rupture61. At the same time, MMP9 has been found in a number of autoimmune diseases and biological processes, such as pulmonary inflammation, hemorrhage, infection and cancer63. Therefore, we believe that MMP9 may have a certain relationship with OSA.MMP9 has been shown in many studies to be significantly associated with cardiovascular disease. Moreover, it was also confirmed in our results that MMP9 was highly expressed in both datasets. MMP9 is a protease of the MMP family that is capable of degrading a broad spectrum of extracellular matrix components and is held responsible for vascular remodeling and breakdown of the fibrous cap of atherosclerotic lesions leading to plaque vulnerability64. Many previous studies have demonstrated that MAPK1 plays an important role in atherosclerotic lesions or processes67. Furthermore, MAPK1 were both up-regulated in coronary heart disease (CAD)68. At the same time, MAPK pathway also plays a role in stroke progression70.MAPK1 is mostly concentrated in the cytoplasm, and activated MAPK1 translocates to the nucleus and activates the expression of target genes in tumor tissuesIn addition to the genes described above that are known to be associated with OSA and ACS, we also found four potential targeted genes that have not been clearly reported in the literature.73. The extracellular, as well as intracellular, mitogenic stimuli activate the MAPK3 cascade, which has pivotal functions in cellular differentiation, proliferation and survival74. The study of colorectal cancer by Schmitz et al. showed that the expression of MAPK3 is related to poor prognosis75.MAPK3, referred to as the mitogen-activated protein kinase 3, is a MAP kinase family member and participates in an extensive array of biological processes, including cell proliferation, as well as angiogenesis. MAPK3 may serve as the intrafollicular mediator that triggers the expansion of the cumulus cell-oocyte complex (COC), as well as the maturation of the oocytes79.Angiotensin (AGT), a plasma globulin of the silk fibroin family, is converted to angiotensin I by renin. Angiotensin converting enzyme (ACE) cleaves angiotensin I and converts to angiotensin II. Angiotensin II then causes increased arterial pressure by participating in intravascular fluid volume elevation and vasoconstriction. Finally, angiotensin II functions through angiotensin receptor type 1 (AGTR1) and angiotensin receptor type 2 (AGTR2)85, TGFβ1 is secreted by a variety of cells, such as peripheral blood monocytes, macrophages, platelets, vascular smooth muscle cells (VSMCs), and renal cells. Its regulatory function on the vessel wall is directed at VSMC, endothelial cells and extracellular matrix. Although there is a significant correlation between TGFβ1 and the pathogenesis of atherosclerosis, the relationship between plasma TGFβ1 levels and the risk of ACS remains unclear88. This is because the exact mechanism of TGFβ1 signaling in the vascular system is still not fully understood89.According to previous reports90. Notably, dinucleotide microsatellite with cytosine-adenine (CA) repeats in the CD40LG 3-untranslated region (3-UTR) described as highly polymorphisms have been found to be associated with multiple diseases, such as multiple sclerosis (MS), systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA)93.The CD40L gene consists of five exons and four introns. Studies have shown that if CD40L expression is low or it is not expressed, impaired immunoglobulin class-switching while mice overexpressing CD40L have chronic inflammationBy employing a sequence of bioinformatics tools for gene expression profiling, we established the core function of candidate key genes, and the enriched signaling cascades constituting the “FoxO signaling pathway” in the molecular modulation network of ACS via integrated bioinformatic analysis. This provides a possible target for the prediction and clinical treatment of ACS in OSA patients in the future. However, in vitro, as well as in vivo studies, should be conducted to verify our findings.


FKBP5, the coding gene of FKBP51, with antidepressant treatment resistance and MDD susceptibility.The identification of single-nucleotide polymorphisms (SNPs) in genes putatively related to pathophysiological processes in major depressive disorder (MDD) might improve both diagnosis and personalized treatment strategies eventually leading to more effective interventions. Considering the important role of the glucocorticoid receptor and the related FK506 binding protein 51 (FKBP51) in the pathophysiology of MDD, we aimed to investigate putative associations between variants of FKBP5 gene prioritized based on location and, putative or known functions were genotyped in Han Chinese population, including MDD patients with or without antidepressant-treatment resistance and healthy controls. Associations of FKBP5 SNPs with MDD susceptibility and treatment response were examined in the whole group of MDD patients, as well as in subgroups stratified by antidepressant treatment resistance, compared with healthy controls.Nine common SNPs of the r2 > 0.8, P = .040) and haplotype block with SNPs in moderate LD  between the haplotype distributions of patients with antidepressant treatment resistance (n = 81) and healthy controls, but both significances did not survive multiple testing correction. Furthermore, no specific haplotype could be observed causing a significant difference in any combination between all comparisons.In total, 181 Han Chinese patients with MDD and 80 healthy controls were recruited. No significant SNP or haplotype associations were observed in the whole patient group. There were nominal significant differences both for the haplotype block with SNPs in strong LD . A follow-up study will need larger, better phenotyped, and more homogeneous samples to draw a definitive conclusion regarding the involvement of this gene in MDD.No associations were observed of  Moreover, lifetime suicide risk for MDD is 2.2% to 15% making the development of more effective treatment strategies an urgent matter. Indeed 30% to 50% of the MDD patients do not respond satisfactorily to antidepressant drugs even after sufficient forms of treatment, eventually falling in the category of treatment-resistant depression.Major depressive disorder (MDD) is a widespread mental illness that affects approximately 350 million people worldwide. and that this may also contribute to antidepressant treatment resistance. Furthermore, a dysregulated hypothalamic-pituitary-adrenal (HPA) axis is a key characteristic of depression, which can be endorsed by inflammatory cytokines.,7 In this regard, a dysfunction of HPA axis could also be an important factor with antidepressant treatment resistance. The FK506-binding protein 51 (FKBP51) is a chaperon protein supporting glucocorticoid receptor (GR) maturation and thus plays an important role in regulating GR activity. Under physiological conditions FKBP51 is part of a negative feedback loop attenuating stress-induced increases of plasma cortisol; however, FKBP51 hyperactivity may result in an increased GR resistance. It has also been shown that FKBP51 can work as a scaffolding protein leading to the dephosphorylation of Akt. This decrease of Akt signaling activity may result in decreased neurogenesis, which might also be involved in treatment resistance.,15 In addition, FKBP51 has been reported to reduce inflammatory responses through a reduction of transcriptional factor NF-κB (p50/p65) nucleus translocation.The considerable individual variation in antidepressant treatment response attracted a lot of attention for the underlying mechanisms of treatment resistance. Earlier studies have suggested that a dysregulated inflammatory system is involved in the pathophysiology of MDD,FKBP5, the gene encoding the FKBP51 protein, may be involved in the pathophysiology of MDD. For instance, a meta-analysis showed that the SNPs rs1360780 and rs3800373 in the FKBP5 gene increased the risk of developing MDD and were also associated with the risk of suicidal behavior in whites. Furthermore, a case–control study in 202 Korean demonstrated that the T allele of FKBP5 rs1360780 was associated with significant volume reductions in mood-related cortical and subcortical regions in MDD patients compared to controls. In addition, a study within STAR∗D demonstrated that rs352428 significantly decreased the gene's transcriptional activity resulting in reduced protein expression, which was significantly associated with an insufficient response to selective serotonin reuptake inhibitors. So for the relation between FKBP5 polymorphisms and antidepressant treatment response has only be studied in Caucasians and it remains unclear whether the observed effects can be generalized to other ethnicities. Finally, Cattaneo et al reported a 11% reduction in leukocyte FKBP51 RNA expression in MDD patients responding to 8-week antidepressant treatment , whereas no such change was found in nonresponders. Because of its key role in glucocorticoid pathways, neurogenesis, and inflammation. FKBP51 is a promising target to investigate the underlying mechanisms of antidepressant treatment resistance.The identification of single-nucleotide polymorphisms (SNPs) relating to treatment response could help to understand the varying responses to antidepressant treatment and aid the development of better treatment strategies. Several lines of evidence have shown that SNPs in  However, thus far GWAS of depression were far less successful, which may be partly attributed to the heterogeneous study population collected from many different sites to increase sample size,–24 based on the current diagnostic classification. The CONVERGE study detected two loci for MDD in 11,670 Han Chinese with only a tenth of the estimated sample size, through increasing homogeneity of studying population by stringent criteria and deep phenotyping, which would indicate that population homogeneity is critical for the detection of genetic associations of MDD. Therefore, in this study, we focused on a homogeneous population of Han Chinese patients with antidepressant treatment resistance and increased inflammatory activity (we will refer to this group of patients as TRDI in the following text). We compared this subgroup of patients with Han Chinese MDD patients without treatment resistance (MDNTR in the following text) and healthy controls . The aim of this study was to investigate the role of FKBP5 genetic polymorphisms in MDD vulnerability and antidepressant treatment response. In this explorative study, we hypothesized that FKBP5 polymorphisms, including allele, genotype and haplotype distributions, are contributable to increased MDD susceptibility and antidepressant treatment resistance in Han Chinese population, particularly in TRDI patients.Technological innovations like genome-wide association studies (GWAS) have substantially aided in the discovery of genetic risk factors for  hereditary diseases.22.1This study recruited 3 groups of participants, including TRDI patients, MDNTR patients, and healthy controls. The TRDI patients (n = 81) were recruited from the inpatient and outpatient departments of Tianjin Anding Hospital between September 2015 and October 2018, and took part in the clinical study registered on “ClinicalTrials.gov” with protocol ID “NAC-2015-TJAH” and ClinicalTrials.gov ID “NCT02972398”. The TRDI patients were called back for blood sampling. Inclusion criteria were: a current episode of MDD diagnosed according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) with Structured Clinical Interview for DSM-IV; age between 18 and 65 years; a total score of 17 items Hamilton Depression Rating Scale (HAMD-17) ≥17; a C-reactive protein level between 0.85 and 10 mg/L; insufficient response to ≥1 antidepressants given for at least 6 weeks and in an adequate dose during the current episode. Exclusion criteria were: a history of manic episode; use of mood stabilizer; use of antipsychotic medication with more than half of the maximum dosage suggested in the instruction; history of substance abuse or dependence; an allergic reaction to NAC or any component of the preparation; severe somatic diseases that might interfere with regular antidepressant treatment including conditions such as kidney and liver failure, uncontrolled hypertension, cardiovascular, cerebrovascular and pulmonary disease, thyroid disease, diabetes, epilepsy and asthma; use of anti-inflammatory medication for >7 days in the last 2 months preceding the trial; use of immunosuppressive medication such as oral steroid hormones; history of chronic infection, such as tuberculosis, AIDS, hepatitis; C-reactive protein value >10 mg/L; women in pregnancy or lactation period. More detailed information on study procedures has been described elsewhere.The data of MDNTR patients n = 100) and healthy controls (n = 80) came from the inpatient and outpatient departments of Tianjin Anding Hospital and Tianjin General Hospital during November 2009 and July 2010. The inclusion criteria for MDNTR patients were: diagnosed MDD with DSM-IV, first episode or recurrent; no resistance to anti-depressant treatments, that is, defined the present episode as a relapse from the efficacious antidepressant treatment because of drug withdrawal for first-episode patients or a recurrence with a history of effective antidepressant treatments for recurrent patients; no history of manic or hypomanic episodes; total score of HAMD-17 ≥17. Patients were excluded if the current depressive disorder was not idiopathic but secondary to other conditions, like substance abuse, medical diseases, and so on; current or historic episode of any mental disorder regardless of depressive disorders; women in menstruation, pregnancy, or lactation period. To be clarified, the MDNTR patients were not assessed for inflammatory activity. The healthy controls had to have no history or family history of any mental disorders and no medical diseases. Medical diseases included severe somatic diseases such as kidney and liver failure, uncontrolled hypertension, cardiovascular, cerebrovascular and pulmonary disease, thyroid disease, diabetes, epilepsy and asthma. Both studies were evaluated by the Medical Ethical Board of the Tianjin Anding Hospital  and all patients provided written informed consent. Please see the Figure 00 and he2.2FKBP5 gene were prioritized for location and, putative or known functions, based on NCBI dbSNP and earlier reports on their associations with clinical phenotypes.–30 Furthermore, the SNPs were considered for those above 15% in Han Chinese population according to minor allele frequency (MAF: 0.15∼0.26). These SNPs included rs1043805 , rs3800373 , rs9296158 , rs7748266 , rs1360780 , rs2766537 , rs9394309 , rs9470080 , and rs2817035 , and the chromosome positions are based on hg38.Nine SNPs of the 2.3 which was stored and processed at the Tianjin Anding Hospital or the Molecular or Population Genetic Center of Tianjin Medical University. For MDNTR patients and healthy controls, their samples had been storing at minus 80°C, which were unfreezed in 4°C refrigerator before genotyping. Genotyping was performed by matrix-assisted laser desorption time-of-flight mass spectrometry, which is a high-throughput blood group genotyping method. After inputting to the AssayDesigner3.1 software for the design of the target SNPs, primers were confirmed and synthesized. Polymerase chain reaction amplification, Shrimp Alkaline Phosphatase purification reaction, extension reaction, resin purification and detection on sequenom were performed on the Sequenom MassArrays platform. Ten percent of samples were used for re-genotyping randomly for quality control, to check the concordance rate. Genotype calling was done blinded to the participants’ clinical data.Genomic DNA was extracted from 5 mL venous blood sample using the high-salt method,P value. SNPs were excluded if the call rate was <90% or the HWE P value among the healthy controls was <.05/9 = 5.5 × 10–3.The quality of the SNPs was checked by determining the call rate and the Hardy-Weinberg equilibrium (HWE) 2.4χ2 test was used to compare the genotype frequency between cases (TRDI patient and MDNTR patient groups) versus healthy controls, TRDI versus healthy controls, MDNTR versus healthy controls, and also stratified patient groups by treatment response phenotype (treatment-resistant depression vs MDNTR). Analyses correcting for age and sex were performed using logistic regression with covariates. To define haplotype blocks, PLINK v1.9 was used to determine linkage disequilibrium (LD) between markers within 1Mb. For each chromosomal region haplotype blocks were next constructed using a lenient r2 threshold of 0.1 and using a stringent r2 threshold of 0.8. Haplotype frequencies within each haplotype block were then determined for cases and controls separately and compared using a permutation test as implemented in PHASE 2.1.1. In this permutation test case–control status was permuted over the individuals 10,000 times and the P value was determined as the proportion of tests from the permuted data with a P value smaller than that when using the original case and control datasets.The allele and genotype frequency, call rate, HWE, and odds ratios were evaluated using PLINK v1.9. The  The significance threshold in this study was 2.5 × 10–3, .To avoid false-positive findings upon the multiple testing, a multiple testing correction was applied. Spectral decomposition of the genotype data was used to determine the number of independent test.http://zzz.bwh.harvard.edu/gpc/cc2.html)The power analysis was performed using “Genetic Power Calculator” online (33.1P = .003) and sex . See Table A total of 261 Han Chinese participants was recruited, including a TRDI patient group (n = 81), a MDNTR patient group (n = 100), and a healthy control group (n = 80). The distributions of age and sex in the 3 groups are significantly different . Comparing the allele or genotype frequencies of cases and controls, we found no significant associations between any of the alleles or genotypes with MDD . The SNP rs9394309 was not in HWE in the healthy controls . We tested each haplotype for frequency differences in relation to depression and treatment response.We studied 2 haplotype blocks: one including SNPs rs1043805, rs3800373, rs9296158, rs7748266, rs136078, rs9470080, and rs2817035, which were all in at least moderate LD with a lenient 3.3.1r2 threshold , and also not between MDNTR and healthy controls (P = .59/.61). When comparing the haplotype distribution between TRDI patients and healthy controls, there were nominal significant differences both in the stringent r2 threshold haplotype block (P = .04) and the lenient r2 threshold haplotype block (P = .0147). However, both significances did not survive multiple testing correction. Furthermore, no specific haplotypes revealed significant differences in any of the analyses. The details of the haplotype analyses comparing cases to controls are shown in Table The results demonstrated that there were no statistical differences in haplotype distribution between cases and healthy controls neither for the haplotype with the lenient nor for the one with the stringent ck P = .0 and the 3.3.2r2 threshold haplotype block and the lenient r2 threshold haplotype block . The combinations of A-C and A-A-G-C-C-C-G were the dominant haplotypes both in the MDNTR patients and the TRDI patients. All results are shown in Table When comparing the haplotype distribution between TRDI patients and MDNTR patients we did not find significant differences both with the stringent 3.4Given the sample size this study had limited power. Post-hoc power analyses showed that the power to detect the observed odds ratios for MDD cases versus healthy controls ranged from 0.192 to 0.645. For MDNTR cases versus healthy controls it was between 0.105 and 0.593 and for TRDI cases versus healthy controls between 0.113 and 0.752. The power to detect differences between TRDI and MDNTR cases ranged from 0.100 to 0.250.4 In the present study we combined both approaches to investigate the role of FKBP5 gene variants in MDD susceptibility and their usefulness as markers for predicting treatment response. We hypothesized that FKBP5 polymorphisms could play an important role in increased MDD susceptibility and antidepressant treatment resistance, and in particular we wanted to test whether this association is more pronounced in TRDI patients. However, we did not find any significant difference in the distributions of alleles, genotypes, and haplotypes between cases and healthy controls or between TRDI patients and MDNTR patients, after correction for multiple testing.Candidate gene SNP association analysis is a commonly used method to delineate the role of genetic factors in the pathophysiology of MDD but also in pharmacogenomic approaches in predicting treatment response.–38 but thus far little genome-wide significance has been reported,,23,39 even though MDD has a strong genetic background with heritability estimates ranging from 31% to 42%. However, it also is known that MDD is a highly heterogeneous disorder. It is therefore important to note that in order to increase the sample size many GWAS have combined data from multiple sites. This will likely increase heterogeneity of the samples, which could partly explain the thus far disappointing results in MDD. In the present study the distribution of haplotype frequencies of rs1043805, rs3800373, rs9296158, rs7748266, rs1360780, rs9470080, and rs2817035 was significantly different between TRDI cases and healthy controls, but not between MDD cases and healthy controls or MDNTR cases and healthy controls. This might suggest a role of this haplotype block in the vulnerability for MDD, although significance did not survive multiple testing correction and no specific haplotype could be identified. The negative outcome when comparing the larger MDD sample with healthy controls might hint at a less homogeneous character of the combined sample. Furthermore, the comparison between TRDI patients and MDNTR patients for treatment response phenotype did not show any significance, which suggests that none of the investigated SNPs or haplotypes is involved in the resistance to antidepressant treatments.Many GWAS for MDD have been carried out,FKBP5 has been considered as a candidate gene for depression because of the role of the encoded protein in the HPA axis response to stress and its inhibition of inflammatory responses. First, recent studies have reported an association of FKBP5 SNPs with treatment response in affective disorders. One study of 93 patients with bipolar disorder reported that SNPs rs1360789, rs9296158, and rs7748266, were associated with lithium response, whereas the TT genotype of rs1360789 was shown to be associated the response to antidepressant treatments in a STAR∗D cohort. Secondly, some variants of the FKBP5 gene were also shown to be associated with the susceptibility for depression. For example, a cross-sectional study of 4639 samples reported that all minor alleles of rs9394309, rs9470080, rs7748266, and rs1360780 were not only associated with decreased levels of cortisol, but also with an increased likelihood of depressive symptoms. This circumstantial evidence suggests that FKBP5 SNPs hold some promise as candidate markers for the pathophysiology of depression. In the present study, however, we could not demonstrate significant differences with any comparisons for SNPs and haplotype combinations of the FKBP5 gene in relation to the depression and treatment response phenotypes, even in the homogeneous TRDI group. An important factor with our negative findings might relate to genetic differences between the Caucasians in the aforementioned studies and the Han Chinese in ours. This is corroborated by the CONVERGE project, which could not demonstrate a significant association of MDD with FKNP5 gene in a homogenous population of Han Chinese. Furthermore, a study with an independent replication should be conducted to validate the findings.,45 Power ranged only from 0.100 to 0.752. Enlarging the sample by including MDNTR patients and combining them with the TRDI patients may have negatively influenced the outcome, despite the increase in power, because of increased heterogeneity in the phenotype. Furthermore, the distribution of age and sex in the three groups are significantly different, which could affect the genetic association analysis even after correcting. Finally, genetic data were derived from 2 separately conducted studies both lacking detailed information necessary to adjust for confounding factors such as the antidepressants used, course of the disease and the number of episodes. It is clear that these confounding factors have no influence on the genetics, but they will influence the phenotype and thus potentially increase the heterogeneity of the samples.The main limitation of our study is its relatively small sample size, although it was comparable with some recent MDD studies on treatment response.FKBP5 SNPs  and haplotypes were not associated with the susceptibility of MDD and treatment response to antidepressants in Han Chinese. There are many factors influencing MDD, such as presumable a high number of loci, their frequencies, their effect sizes, interactions with other genetic loci, but also environmental factors and interactions between them and genes. Without a proper understanding of the influence of these factors on MDD, the only practical way to improve the reliability of the results may be found in an increase of the sample size on the condition that homogeneity is not compromised.In conclusion, we reported here, for the first time, that the 4.1The 2 studies protocol were approved by the medical ethics committee of Tianjin Anding Hospital and conformed to “Declaration of Helsinki”. All participants had signed informed consent about the content and extent of the planned study before the participations. The patients’ guardians signed the informed consent on behalf of the participants when the capacity of participants to consent was compromised.Each author's individual contributions had been listed as following: Shen Li, Chenghao Yang, and Jie Li contributed to the conceptualization of this study; Fokko Bosker and Jie Li contributed to the planning; Yanyan Ma, Bing Chen, Meijuan Li, Chenghao Yang, and Shen Li conducted the implementation of experiments; Ilja Nolte worked out the data analysis; Chenghao Yang, Ilja Nolte, Fokko Bosker, and Jie Li contributed to the manuscript preparation.Conceptualization: Chenghao Yang, Shen Li, Jie Li.Data curtain: Ilja M. Nolte.Formal analysis: Ilja M. Nolte.Funding acquisition: Jie Li.Investigation: Chenghao Yang, Shen Li, Yanyan Ma, Bing Chen, Meijuan Li.Supervision: Jie Li.Writing – original draft: Chenghao Yang, Fokko J. Bosker.Writing – review & editing: Chenghao Yang, Fokko J. Bosker, Jie Li, Ilja M. Nolte.