Discrimination of foodborne pathogenic bacteria using synchrotron FTIR microspectroscopy

Traditional Fourier transform infrared(FTIR)spectroscopy has been recognized as a valuable method to characterize and classify kinds of microorganisms.In this study,combined with multivariate statistical analysis,synchrotron radiation-based FTIR(SR-FTIR) microspectroscopy was applied to identify and discriminate ten foodborne bacterial strains.Our results show that the whole spectra(3000-900 cm^(-1)) and three subdivided spectral regions(3000-2800,1800-1500 and 1200-900 cm^(-1),representing lipids,proteins and polysaccharides,respectively) can be used to type bacteria.Either the whole spectra or the three subdivided spectra are good for discriminating the bacteria at levels of species and subspecies,but the whole spectra should be given preference at the genus level.The findings demonstrate that SR-FTIR microspectroscopy is a powerful tool to identify and classify foodborne pathogenic bacteria at the genus,species and subspecies level.

Synchrotron infrared spectral regions as signatures for foodborne bacterial typing

Fourier-transform infrared(FTIR) spectroscopy has emerged as a viable alternative to biochemical and molecular biology techniques for bacterial typing with advantages such as short analysis time, low cost and laboratorial simplicity. In this study, synchrotron radiationbased FTIR(SR-FTIR) spectroscopy with higher spectral quality was successfully applied to type 16 foodborne pathogenic bacterial strains. Combined with principal component analysis(PCA) and hierarchical cluster analysis(HCA), we found that the specific spectral region1300-1000 cm^(-1), which reflects the information of phosphate compounds and polysaccharides, can be used as the signature region to cluster the strains into groups similar with genetic taxonomic method. These findings demonstrated that FTIR spectra combined with HCA have a great potential in quickly typing bacteria depending on their biochemical signatures.

Synchrotron FTIR spectroscopy reveals molecular changes in Escherichia coli upon Cu^2＋ exposure

Copper ions(e.g.,Cu^(2+)) have outstanding antibacterial properties,but the exact mechanism is rather complex and not fully understood.In this work,synchrotron Fourier transform infrared(FTIR) spectroscopy was used as an analytical tool to investigate the CuCl_2-induced biochemical changes in Escherichia coli.Our spectral measurements indicated that this technique is sensitive enough to detect changes in membrane lipids,nucleic acids,peptidoglycans and proteins of Cu^(2+)-treated bacteria.Interestingly,for short-time treated cells,the effects on phospholipid composition were clearly shown,while no significant alterations of proteins,nucleic acids and peptidoglycans were found.PeakForce quantitative nano-mechanics mode atomic force microscopy(AFM)confirmed the changes in the topography and mechanical properties of bacteria upon the Cu^(2+) exposure.This study demonstrated that FTIR spectroscopy combined with AFM can provide more comprehensive evaluation on the biochemical and mechanical responses of bacteria to copper.

Hybrid Intelligent Approach for the Selection of Third-Party Reverse Logistics Provider under Uncertainty

A hybrid intelligent approach is proposed to help the decision maker to select the appropriate third-party reverse logistics provider. The following process is included: firstly,the evaluation team is established to determine the selection criteria and evaluate them by triangular fuzzy numbers; secondly,calculate the weight of criteria by the proposed hybrid algorithm integrating particle swarm optimization( PSO) and simulated annealing( SA); then, the performance evaluation for each supplier is predicted by the proposed self-feedback neural network( SFBNN) based on the historical data. A numerical example is also presented to interpret the methodology above.

Low phase noise K-band signal generation using polarization diverse single-soliton integrated microcombs

Frequency microcombs with microwave and millimeter-wave repetition rates provide a compact solution for coherent communication and information processing.The implementation of these microcombs using a CMOS-compatible platform further paves the way for large-scale photonic integration and modularity.Here,we demonstrate free-running soliton microcombs with K-band repetition rates with very low phase noise over a 4 GHz pump detuning range reaching−117(−123)dBc/Hz at 10 kHz offset for a 19.7(10)GHz carrier without active pump stabilization,exceeding commercial electronic microwave oscillators at frequency offsets above 40 kHz.The minimum laser noise to soliton microwave signal transduction factor observed is−73dB.This noise performance is achieved using a hybridized dual-mode for soliton generation to achieve passive thermal stabilization and minimal soliton spectrum shift from prior Raman scattering and dispersive wave formation.We further examine the locking of the repetition rate to an external ultrastable photonic oscillator to illustrate the feasibility of phase noise suppression below the thermorefractive noise limits of microresonator frequency combs.

A comparison of next-generation sequencing analysis methods for cancer xenograft samples

The application of next-generation sequencing （NGS） technology in cancer is influenced by the quality and purity of tissue samples. This issue is especially critical for patient-derived xenograft （PDX） models, which have proven to be by far the best preclinical tool for investigating human tumor biology, because the sensitivity and specificity of NGS analysis in xenograft samples would be compromised by the contamination of mouse DNA and RNA. This definitely affects downstream analyses by causing inaccurate mutation calling and gene expression estimates. The reliability of NGS data analysis for cancer xenograft samples is therefore highly dependent on whether the sequencing reads derived from the xenograft could be distinguished from those originated from the host. That is, each sequence read needs to be accurately assigned to its original species. Here, we review currently available methodologies in this field, including Xenome, Disambiguate, bamcmp and pdxBlacklist, and provide guidelines for users.

A 3D bio-printed spheroids based perfusion in vitro liver on chip for drug toxicity assays

Liver is the foremost organ of human being for drug metabolism,and it played a significant role in toxicity evaluation of drugs.Establishing a liver model in vitro can accelerate the process of the drug screening and new drug research and development.We provide a 3D printing based hepatic sinusoid-on-a-chip microdevice that reconstitutes organ-level liver functions to create a drug screening model of toxicity evaluation on chip.The microfluidic device,which recapitulates the hepatic sinusoid microenvironment,consists of PET polyporous membranes which mimic the perisinusoidal space,and experience fluid flow to mimic the hepatic arterial capillaries.The PET membrane was used to separate the hepatocyte and endotheliocyte.The endotheliocyte was cultured on the downside of the membrane and the hepatocyte were 3D seeded on the membrane via the 3D printer.This device was used to reproduce the in vitro liver model for drug toxicity assays.The expression of several biomarkers of liver was compared with the monoculture and 2D cultured conditions,and the results reveal that this organ-on-a-chip microdevice mimics the drug hepatoxicity that has not been possible by 2D cell-based and animal models,providing a useful platform for screening the drugs and developing an effective therapy in hepatopathy.

A Novel Small Deletion in the A TP2A2 Gene in a Patient with Sporadic Darier's Disease and Concomitant Depression: A Case Report

Introduction:Darier's disease is a rare autosomal dominant skin disorder caused by mutations in ATP2A2.Recently,the high prevalence of neuropsychiatric symptoms is frequently reported in Darier's disease patients.We present a case of patient with concurrence of Darier's disease and depression and detected the mutations in Case presentation:A 29-year-old man presented with a 15-year history of brown,harsh keratotic papules on his scalp,face,neck,trunk,axilla,ingunia and upper limbs.Meanwhile,he had persistent depression.He was diagnosed as Darier's disease according to clinical manifestations and result of histological examination.We sequenced all coding regions of ATP2A2.The mutation c.2993_2994del(p.Val998Alafs*33)in exon 20 of ATP2A2 was detected.Discussion:Darier's disease has been associated with several extracutaneous manifestations,in particular neuropsychiatric morbidity.Likely gene disrupting mutations in ATP2A2 was reported to have a close relationship to Darier's disease cases with reported co-occurring neuropsychiatric features.Consistent with the previous reports,an likely gene disrupting mutations was detected in our patient with concurrence of DD end depression.Conclusion:The psychiatric disorders in patients with Darier's disease should be well appreciated.The underlying mechanism in correlation between the mutation in ATP2A2 and neuropsychiatric phenotypes in Darier's disease remain unclarified and warrants further investigation.

Highly efficient base editing in human tripronuclear zygotes

There are hundreds of disease-causing single-gene mutations, mainly caused by single-nucleotide substitutions or point mutations rather than small insertions/deletions （in- dels）, and often there are no cures for these diseases.

Gene dysregulation analysis builds a mechanistic signature for prognosis and therapeutic benefit in colorectal cancer

The implementation of cancer precision medicine requires biomarkers or signatures for predicting prognosis and therapeutic benefits.Most of current efforts in this field are paying much more attention to predictive accuracy than to molecular mechanistic interpretability.Mechanism-driven strategy has recently emerged,aiming to build signatures with both predictive power and explanatory power.Driven by this strategy,we developed a robust gene dysregulation analysis framework with machine learning algorithms,which is capable of exploring gene dysregulations underlying carcinogenesis from high-dimensional data with cooperativity and synergy between regulators and several other transcriptional regulation rules taken into consideration.We then applied the framework to a colorectal cancer(CRC)cohort from The Cancer Genome Atlas.The identified CRC-related dysregulations significantly covered known carcinogenic processes and exhibited good prognostic effect.By choosing dysregulations with greedy strategy,we built a four-dysregulation(4-DysReg)signature,which has the capability of predicting prognosis and adjuvant chemotherapy benefit.4-DysReg has the potential to explain carcinogenesis in terms of dysfunctional transcriptional regulation.These results demonstrate that our gene dysregulation analysis framework could be used to develop predictive signature with mechanistic interpretability for cancer precision medicine,and furthermore,elucidate the mechanisms of carcinogenesis.

TGPred:a tumor gene prediction webserver for analyzing structural and functional impacts of variants

With the increasing use of high-throughput sequencing technology in tumor research,a large number of somatic variations are being identified and some of them have proved to be responsible for tumorigenesis(Cancer Genome Atlas Research Network et al.,2013).Investigating structural and functional impacts of tumor somatic variants would greatly help to identify causal variations,understand the mechanisms of carcinogenesis,and develop novel anti-tumor therapies.Therefore,many efforts have recently been made to map genomic variations to 3D protein structure,such as G23D(Solomon et al.,2016)and G2S(Wang et al.,2018).

Strategic planning for national biomedical big data infrastructure in China

The promise that big data will revolutionize scientific discovery and technology innovation is now being widely recognized. With the explosive growth of biomedical data, life science is being transformed into a digital science in which novel insights are gained from in-depth data analysis and modeling. Extensive and innovative utilization of biomedical big data is a key to the success of precision medicine. Therefore, constructing a centralized national-level biomedical big data infrastructure becomes crucial and urgent for China. Such infrastructure should achieve superb capacity of safe data storage, standardized data processing and quality control, systematic data integration across multiple types, and in-depth data mining and effective data sharing. Full data chain service including information retrieval, knowledge discovery and technology support can be provided to data centers, research institutes and healthcare industries. Relying on Shanghai Institutes for Biological Sciences, agreements have been signed that a main node of the infrastructure will be located in Shanghai, and a backup node will be set up in Guizhou Province. After a construction period of five years, the infrastructure should greatly enhance China＇s core competence in collection, interpretation and application of biomedical big data.

De novo assembly of transcriptome from next-generation sequencing data

Reconstruction of transcriptome by de novo assembly from next generation sequencing （NGS） short-sequence reads provides an essential mean to catalog expressed genes, identify splicing isoforms, and capture the expression detail of transcripts for organisms with no reference genome available. De novo transcriptome assembly faces many unique challenges, including alternative splicing, variable expression level covering a dynamic range of several orders of magnitude, artifacts introduced by reverse transcription, etc. In the current review, we illustrate the grand strategy in applying De Bruijn Graph （DBG） approach in de novo transcriptome assembly. We further analyze many parameters proven critical in transcriptome assembly using DBG. Among them, k-met length, coverage depth of reads, genome complexity, performance of different programs are addressed in greater details. A multi-k-mer strategy balancing efficiency and sensitivity is discussed and highly recommended for de novo transcriptome assembly. Future direction points to the combination of NGS and third generation sequencing technology that would greatly enhance the power of de novo transcriptomics study.