Multiomics comparison among populations of three plant sources of Amomi Fructus

Amomi Fructus(Sharen,AF)is a traditional Chinese medicine(TCM)from three source species(or varieties),including Wurfbainia villosa var.villosa(WVV),W.villosa var.xanthioides(WVX),or W.longiligularis(WL).Among them,WVV has been transplanted from its top-geoherb region,Guangdong,to its current main production area,Yunnan,for>50 years in China.However,the genetic and transcriptomic differentiation among multiple AF source species(or varieties)and between the origin and transplanted populations of WVV is unknown.In our study,the observed overall higher expression of terpenoid biosynthesis genes in WVV than in WVX provided possible evidence for the better pharmacological effect of WVV.We also screened six candidate borneol dehydrogenases(BDHs)that potentially catalyzed borneol into camphor in WVV and functionally verified them.Highly expressed genes at the P2 stage of WVV,Wv05G1424 and Wv05G1438,were capable of catalyzing the formation of camphor from(+)-borneol,(-)-borneol and DL-isoborneol.Moreover,the BDH genes may experience independent evolution after acquiring the ancestral copies,and the following tandem duplications might account for the abundant camphor content in WVV.Furthermore,four populations of WVV,WVX,and WL are genetically differentiated,and the gene flow from WVX to WVV in Yunnan contributed to the greater genetic diversity in the introduced population(WVV-JH)than in its top-geoherb region(WVV-YC),which showed the lowest genetic diversity and might undergo genetic degradation.In addition,terpene synthesis(TPS)and BDH genes were selected among populations of multiple AF source species(or varieties)and between the top-and non-top-geoherb regions,which might explain the difference in metabolites between these populations.Our findings provide important guidance for the conservation,genetic improvement,and industrial development of the three source species(or varieties)and for identifying top-geoherbalism with molecular markers,and proper clinical application of AF.

Tetramethylpyrazine Nitrone Improved Motor Deficits and Alleviated Dystrophic Muscle Pathology in the <i>mdx</i>Mouse Model of Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a lethal X-linked recessive neuromuscular disorder caused by mutations in the dystrophin encoding gene, with the characteristics of a severe and progressive destruction of muscle structure and function. Skeletal muscle fibrosis is one of the pathological features of DMD. Tetramethylpyrazine (2,3,5,6-tetramethylpyrazine, TMP) has been demonstrated to reduce heart and liver fibrosis. Meanwhile, previous studies showed that Tetramethylpyrazine nitrone (TBN), a nitrone derivative of TMP, has promising therapeutic effects in several neurodegenerative models and is more potent than TMP. In this study, we investigated the potential effect of TBN on the mdx mouse model of DMD. Eight-week-old mdx mice were administered with TBN (30 mg/kg) intragastrically twice daily, with deflazacort (1 mg/kg) once a day as a positive control, for a total of 24 weeks. Behavioral tests including pole-climbing open-field test were monitored every 4 weeks. Histopathological assessment was conducted in the gastrocnemius and diaphragm muscles. The effects of TBN on protein levels of dysferlin were measured by immunohistochemistry. TBN significantly reduced the climbing time in pole test and increased the total distance moved in an open-field test of mdx mice. TBN attenuated fibrosis in the gastrocnemius and diaphragmatic muscles. In addition, TBN protected gastrocnemius muscle fibers via increasing expression of the dysferlin in mdx mice. In conclusion, this study demonstrated that TBN could improve the motor deficits and muscle pathology of mdx mouse, and it is worth further exploring the mechanism of action of TBN for DMD treatment.

Optimization of Casing Design Parameters to Mitigate Casing Failure Caused by Formation Slippage

There has been lack of work efforts on how to optimize cementing and completing parameters in order to prevent casing failure induced by formation slippage in pertroleum industry scope.Once the weak plane fails,the formation will become easily undertaken slippage across a large area along its interface.The plenty of horizontal planes of weakness in reservoir formations,as reported for a number of oilfields,can easily undertaken slippage once it fails.To address the problem,three-dimensional finite element models were established by taking into considerations the elastoplastic mechanical characteristics of both the casing and the near-wellbore rock.Two types of casing impairment scenarios were considered:Casing collapse(that causes tubing stuck in the well)and complete casing shear-off.In this study,the critical slip displacement of casing shear damage under both cemented and un-cemented conditions was calculated,and the critical displacement of casing with various wall thicknesses and steel grades was compared.A new cementing practice for the Daqing oilfield was then proposed by optimizing casing parameters according to API standards,and a new research method was also put forward by proposing new casing materials to effectively mitigate casing failure caused by formation slippage for the future.Modeling results indicate that the stress and deformation associated with casing in the un-cemented condition is more diffused and the critical slippage displacement is larger than that in the cemented condition.Therefore,the un-cemented condition is more effective in preventing casing shear failure and easier for casing repair,for the case of casing damage caused by formation shear slippage.Casing elongation is the key parameter of casing shear failure in the un-cemented condition.Lower grade casing exhibits a larger critical slippage displacement because of its higher elongation capacity under stress.Casing with lower grade and smaller thickness provides more advantages in preventing casing damage in formations abundant with horizontal weak layers.If the elongation of casing can be largely improved,the critical displacement value can be increased by 21.40%.Higher grade and thicker casing is adapted for mitigate casing failure caused by formation slippage.

DC System Modeling and AC/DC System Harmonic Calculation under Asymmetric Faults

The accurate DC system model is the key to fault analysis and harmonic calculation of AC/DC system. In this paper, a frequency domain analysis model of DC system is established, and based on it a unified fundamental frequency and harmonic iterative calculation method is proposed. The DC system model is derived considering the dynamic switching characteristic of converter and the steady-state response features of dc control system synchronously. And the proposed harmonic calculation method fully considers the AC/DC harmonic interaction and fault interaction under AC asymmetric fault condition. The method is used to the harmonic analysis and calculation of CIGRE HVDC system. Compared with those obtained by simulation using PSCAD/EMTDC software, the results show that the proposed model and method are accurate and effective, and provides the analysis basis of harmonic suppression, filter configuration and protection analysis in AC/DC system.

Maintenance Scheduling of Distribution System with Optimal Economy and Reliability

With the continuous expansion of power distribution grid, the number of distribution equipments has become larger and larger. In order to make sure that all the equipments can operate reliably, a large amount of maintenance tasks should be conducted. Therefore, maintenance scheduling of distribution network is an important content, which has significant influence on reliability and economy of distribution network operation. This paper proposes a new model for maintenance scheduling which considers load loss, grid active power loss and system risk as objective functions. On this basis, Differential Evolution algorithm is adopted to optimize equipment maintenance time and load transfer path. Finally, the general distribution network of 33 nodes is taken for example which shows the maintenance scheduling model’s effectiveness and validity.

Quantum dot quantum cascade photodetector using a laser structure

We report on a quantum dot quantum cascade detector(QD-QCD), whose structure is derived from a QD cascade laser. In this structure, more ordered In As QD layers formed in the Stranski–Krastanow growth mode on a thin Ga As buffer layer are incorporated into the active region. This QD-QCD can operate up to room temperature with a peak detection wavelength of 5.8 μm. A responsivity of 3.1 mA/W at 160 K and a detectivity of 3.6 × 10~8 Jones at 77 K are obtained. The initial performance of the detector is promising, and, by further optimizing the growth of InA s QDs, integrated QD-quantum cascade laser/QCD applications are expected.

Artificial intelligence recognition of pathological T stage and tumor invasion in rectal cancer based on large panoramic pathological sections

Background The incidence of colorectal cancer is increasing worldwide,and it currently ranks third among all cancers.Moreover,pathological diagnosis is becoming increasingly arduous.Artificial intelligence has demon-strated the ability to fully excavate image features and assist doctors in making decisions.Large panoramic patho-logical sections contain considerable amounts of pathological information.In this study,we used large panoramic pathological sections to establish a deep learning model to assist pathologists in identifying cancerous areas on whole-slide images of rectal cancer,as well as for T staging and prognostic analysis.Methods We collected 126 cases of primary rectal cancer from the Affiliated Hospital of Qingdao University West Coast Hospital District(internal dataset)and 42 cases from Shinan and Laoshan Hospital District(external dataset)that had tissue surgically removed from January to September 2019.After sectioning,staining,and scanning,a total of 2350 hematoxylin-eosin-stained whole-slide images were obtained.The patients in the internal dataset were randomly divided into a training cohort(n=88)and a test cohort(n=38)at a ratio of 7:3.We chose DeepLabV3+and ResNet50 as target models for our experiment.We used the Dice similarity coefficient,accuracy,sensitivity,specificity,receiver operating characteristic(ROC)curve,and area under the curve(AUC)to evaluate the performance of the artificial intelligence platform in the test set and validation set.Finally,we followed up patients and examined their prognosis and short-term survival to corroborate the value of T-staging investigations.Results In the test set,the accuracy of image segmentation was 95.8%,the Dice coefficient was 0.92,the accuracy of automatic T-staging recognition was 86%,and the ROC AUC value was 0.93.In the validation set,the accuracy of image segmentation was 95.3%,the Dice coefficient was 0.90,the accuracy of automatic classification was 85%,the ROC AUC value was 0.92,and the image analysis time was 0.2 s.There was a difference in survival in patients with local recurrence or distant metastasis as the outcome at follow-up.Univariate analysis showed that T stage,N stage,preoperative carcinoembryonic antigen(CEA)level,and tumor location were risk factors for postoperative recurrence or metastasis in patients with rectal cancer.When these factors were included in a multivariate analysis,only preoperative CEA level and N stage showed significant differences.Conclusion The deep convolutional neural networks we have establish can assist clinicians in making decisions of T-stage judgment and improve diagnostic efficiency.Using large panoramic pathological sections enables better judgment of the condition of tumors and accurate pathological diagnoses,which has certain clinical application value.

REDH:A database of RNA editome in hematopoietic differentiation and malignancy

Background:The conversion of adenosine(A)to inosine(I)through deamination is the prevailing form of RNA editing,impacting numerous nuclear and cytoplasmic transcripts across various eukaryotic species.Millions of high-confidence RNA editing sites have been identified and integrated into various RNA databases,providing a convenient platform for the rapid identification of key drivers of cancer and potential therapeutic targets.However,the available database for integration of RNA editing in hematopoietic cells and hematopoietic malignancies is still lacking.Methods:We downloaded RNA sequencing(RNA-seq)data of 29 leukemia patients and 19 healthy donors from National Center for Biotechnology Information(NCBI)Gene Expression Omnibus(GEO)database,and RNA-seq data of 12 mouse hematopoietic cell populations obtained from our previous research were also used.We performed sequence alignment,identified RNA editing sites,and obtained characteristic editing sites related to normal hematopoietic development and abnormal editing sites associated with hematologic diseases.Results:We established a new database,"REDH",represents RNA editome in hematopoietic differentiation and malignancy.REDH is a curated database of associations between RNA editome and hematopoiesis.REDH integrates 30,796 editing sites from 12 murine adult hematopoietic cell populations and systematically characterizes more than 400,000 edited events in malignant hematopoietic samples from 48 cohorts(human).Through the Differentiation,Disease,Enrichment,and knowledge modules,each A-to-I editing site is systematically integrated,including its distribution throughout the genome,its clinical information(human sample),and functional editing sites under physiological and pathological conditions.Furthermore,REDH compares the similarities and differences of editing sites between different hematologic malignancies and healthy control.Conclusions:REDH is accessible at http://www.redhdatabase.com/.This user-friendly database would aid in understanding the mechanisms of RNA editing in hematopoietic differentiation and malignancies.It provides a set of data related to the maintenance of hematopoietic homeostasis and identifying potential therapeutic targets in malignancies.