Biggs Theorem for Directed Cycles and Topological Invariants of Digraphs

We generalize Biggs Theorem to the case of directed cycles of multi-digraphs allowing to compute the dimension of the directed cycle space independently of the graph representation with linear runtime complexity. By considering two-dimensional CW complex of elementary cycles and deriving formulas for the Betti numbers of the associated cellular homology groups, we extend the list of representation independent topological inavariants measuring the graph structure. We prove the computation of the 2nd Betti number to be sharp #P hard in general and present specific representation invariant sub-fillings yielding efficiently computable homology groups. Finally, we suggest how to use the provided structural measures to shed new light on graph theoretical problems as graph embeddings, discrete Morse theory and graph clustering.

Improved 5-Aminolevulinic Acid Production with Recombinant Escherichia coli by a Short-term Dissolved Oxygen Shock in Fed-batch Fermentation

5-Aminolevulinic acid （ALA） is a common precursor for tetrapyrrole compounds in all kinds of organ isms and has wide applications in agriculture and medicines. In this study, a new strategy, i.e. short-term dissolved oxygen （DO） shock during aerobic fermentation, was introduced to produce 5-aminolevulinic acid with a recombi-nant E. coli. Effects of duration time of DO shock operation on plasmid concentration, intracellular ALA synthase （ALAS） activity and ALA production were investigated in Erlenmeyer shake flasks. The results indicated that both ALAS activity and ALA yield were enhanced in an anaerobic operation of 45 rain in the early exponential phase during fermentation, while they decreased when the anaerobic operation time was further increased to 60 rain. The DO shock protocol was confirmed with the fed-batch fermentation in a 15 L fermenter and the ALA production achieved 9.4 g.L-1 （72 mmol.L-1）, which is the highest yield in the fermentation broth reported up to now.

Label-free imaging immune cells and collagen in atherosclerosis with two-photon and second harmonic generation microscopy

Atherosclerosis has been recognized as a chronic inflammation disease,in which many types of cells participate in this process,including lymphocytes,macrophages,dendritic cells(DCs),mast cells,vascular smooth muscle cells(SMCs).Developments in imaging technology provide the capability to observe cellular and tissue components and their interactions.The knowledge of the functions of immune cells and their interactions with other cell and tissue components will facilitate our discovery of biomarkers in atherosclerosis and prediction of the risk factor of rupture-prone plaques.Nonlinear optical microscopy based on two-photon excited autofluorescence and second harmonic generation(SHG)were developed to image mast cells,SMCs and collagen in plaque ex vivo using endogenous optical signals.Mast cells were imaged with two-photon tryptophan autofluorescence,SMCs were imaged with two-photon NADH auto fluorescence,and collagen were imaged with SHG.This development paves the way for further study of mast cell degranulation,and the effects of mast cell derived mediators such as induced synthesis and activation of matrix metalloproteinases(MMPs)which participate in the degradation of collagen.

The Dynamical Mechanisms of the Cell Cycle Size Checkpoint

Cell division must be tightly coupled to cell growth in order to maintain cell size,whereas the mechanisms of how initialization of mitosis is regulated by cell size remain to be elucidated.We develop a mathematical model of the cell cycle,which incorporates cell growth to investigate the dynamical properties of the size checkpoint in embryos of Xenopus laevis.We show that the size checkpoint is naturally raised from a saddle-node bifurcation,and in a mutant case,the cell loses its size control ability due to the loss of this saddle-node point.

Attractive target wave patterns in complex networks consisting of excitable nodes

This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving （DPAD） is introduced to reveal the dynamic structures in the networks supporting osciUations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center （say node A） and its driver （say node B） of a target wave can be used as a label, （A, B）, of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.

Regenerative capacity of Müller cells and their modulation as a tool to treat retinal degenerations

Vision is one of our most precious senses,and its impairment has a high socio-economic impact.In the industrialized world,degenerative diseases of the retina lead to vision loss,particularly among the elderly.These degenerations include,for instance,retinitis pigmentosa,age-related macular degeneration,and diabetic retinopathy.Although treatments are evolving to manage late-stage symptoms of retinal degenerations,no effective therapies to recover vision loss exist.Retinal degeneration often involves loss or damage to specialized neural cells,such as photoreceptors,and their death stimulates the activation and proliferation of Müller cells(Salman et al.,2021).

Identification and Biological Activities of the Phenolic Compounds in <i>Eisenia arborea</i>

Four polyphenols were isolated and purified from a brown alga Eisenia arborea. These phlorotannin compounds showed strong radical scavenging and some enzyme inhibitory activities. All of the compounds showed strong antioxidative, acetylcholinesterase and butyrylcholinesterase inhibitory, and tyrosinase inhbibitory activities at 100 μg/mL. Dieckol and PFF inhibited butyrylcholinesterase, a new target for the treatment of Alzheimer’s disease, very strongly even at 10 μg/mL, more strongly than AChE. These two compounds also effectively inhibited tyrosinase. These results support the potential of developing natural antioxidants and antidementia agents from the brown alga.

CancerSRT:a spatially resolved transcriptomics database for human cancers

Human cancer is one of the leading causes of death worldwide.Tumor heterogeneity and complex microenvironment are major challenges for anti-cancer treatment.A better understanding of the tumor heterogeneity might contribute to more precise diagnosis and treatment.Recent advances in single-cell RNA-sequencing(scRNA-seq)have provided valuable insights into cell fate determination and development in cancer,but the main limitation is that cellular spatial information is lost.Fortunately,spatially resolved transcriptomics technologies have enabled gene expression profiling with spatial coordinates in tissues,which opens up new avenues for deciphering the cancer spatial structure and accelerating oncological research.

Versatile effects of galectin-1 protein-containing lipid bilayer coating for cardiovascular applications

Modulating inflammatory cells in an implantation site leads to severe complications and still unsolved challenges for blood-contacting medical devices.Inspired by the role of galectin-1(Gal-1)in selective functions on multiple cells and immunomodulatory processes,we prepared a biologically target-specific surface coated with the lipid bilayer containing Gal-1(Gal-1-SLB)and investigate the proof of the biological effects.First,lipoamido-dPEG-acid was deposited on a gold-coated substrate to form a self-assembled monolayer and then conjugated dioleoylphosphatidylethanolamine(DOPE)onto that to produce a lower leaflet of the supported lipid bilayer(SLB)before fusing membrane-derived vesicles extracted from B16-F10 cells.The Gal-1-SLB showed the expected anti-fouling activity by revealing the resistance to protein adsorption and bacterial adhesion.In vitro studies showed that the Gal-1-SLB can promote endothelial function and inhibit smooth muscle cell proliferation.Moreover,Gal-1-SLB presents potential function for endothelial cell migration and angiogenic activities.In vitro macrophage culture studies showed that the Gal-1-SLB attenuated the LPS-induced inflammation and the production of macrophage-secreted inflammatory cytokines.Finally,the implanted Gal-1-SLB reduced the infiltration of immune cells at the tissue-implant interface and increased markers for M2 polarization and blood vessel formation in vivo.This straightforward surface coating with Gal-1 can be a useful strategy for modulating the vascular and immune cells around a blood-contacting device.

Reversible hydrogels with tunable mechanical properties for optically controlling cell migration

Synthetic hydrogels are widely used as biomimetic in vitro model systems to understand how cells respond to complex microenvironments. The mechanical properties of hydrogels are deterministic for many cellular behaviors, including cell migration, spreading, and differentiation. However, it remains a major challenge to engineer hydrogels that recapture the dynamic mechanical properties of native extracellular matrices. Here, we provide a new hydrogel platform with spatiotemporally tunable mechanical properties to assay and define cellular behaviors under light. The change in the mechanical properties of the hydrogel is effected by a photo-induced switch of the cross-linker fluorescent protein, Dronpa145N, between the tetrameric and monomeric states, which causes minimal changes to the chemical properties of the hydrogel. The mechanical properties can be rapidly and reversibly tuned for multiple cycles using visible light, as confirmed by rheological measurements and atomic force microscopy- based nano-indentation. We further demonstrated real-time and reversible modulation of cell migration behaviors on the hydrogels through photo-induced stiffness switching, with minimal invasion to the cultured cells. Hydrogels with a programmable mechanical history and a spatially defined mechanical hierarchy might serve as an ideal model system to better understand complex cellular functions.

Translational Informatics for Parkinson’s Disease:from Big Biomedical Data to Small Actionable Alterations

Parkinson’s disease(PD)is a common neurological disease in elderly people,and its morbidity and mortality are increasing with the advent of global ageing.The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations.To highlight the use of big data for precision PD medicine,we review PD big data and informatics for the translation of basic PD research to clinical applications.We emphasize some key findings in clinically actionable changes,such as susceptibility genetic variations for PD risk population screening,biomarkers for the diagnosis and stratification of PD patients,risk factors for PD,and lifestyles for the prevention of PD.The challenges associated with the collection,storage,and modelling of diverse big data for PD precision medicine and healthcare are also summarized.Future perspectives on systems modelling and intelligent medicine for PD monitoring,diagnosis,treatment,and healthcare are discussed in the end.

The role of distinct co-mutation patterns with TP53 mutation in immunotherapy for NSCLC

TP53 mutations was reported to be correlated to the efficacy of program death-1(PD-1)and program death ligand-1(PD-L1).The role of co-mutations of TP53 with other recurrently mutated genes in outcome of anti-PD-(L)1 treatment for non-small cell lung cancer(NSCLC)is unknown.Here we mined a previously generated dataset to address the effect of co-mutations on the progression free survival(PFS)of NSCLC patients.Non-synonymous mutations and clinical data of 240 NSCLC patients with anti-PD-(L)1 based therapy was downloaded from cBioPortal.Totally 206 patients received monotherapy and 34 patients received combination therapy.In 240 NSCLC patients,TP53 mutation rate was 59.2%.For the monotherapy cohort,TP53 mutated NSCLC patients have a significantly longer PFS(4.3 vs.2.5 months,P=0.0019)compared with TP53 wild type NSCLC patients.The same tendency was also observed in the combination therapy cohort,but the difference in PFS(6.3 vs.5.4 months,P=0.12)was not significant.Ever-smoker had a longer PFS compared to never-smokers(4.0 vs.2.7 months).For further co-mutation analysis with TP53 including KEAP1 mutation(53/240,22.1%),KMT3C mutation(26/240,10.8%),STK11 mutation(56/240,23.3%),EGFR mutation(28/240,11.7%)and KRAS mutation(86/240,35.8%).Patients with both TP53 plus KEAP1 mutations in all 240 patients had a longer PFS compared with co-wild population(PFS 9.2 vs.4.2 months,P=0.012)when treated with PD-1/PD-L1 inhibitors.TP53 might be the dominating mutation correlating with longer PFS in PD-1/PD-L1 monotherapy.Different genes displayed distinct effect when co-mutated with TP53 in NSCLC patients.

Algorithmic challenges in structure-based drug design and NMR structural biology

The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms search the pose space exhaustively with the pose space itself being limited to a set of hierarchical manifolds that represent, respectively, surfaces, curves and points with unique geometric and energetic properties. These algorithms promise to be es- pecially valuable for the docking of fragments and small compounds as well as for virtual screening.

Active Nematodynamics on Curved Surfaces–The Influence of Geometric Forces on Motion Patterns of Topological Defects

We derive and numerically solve a surface active nematodynamics model.We validate the numerical approach on a sphere and analyse the influence of hydro-dynamics on the oscillatory motion of topological defects.For ellipsoidal surfaces the influence of geometric forces on these motion patterns is addressed by taking into ac-count the effects of intrinsic as well as extrinsic curvature contributions.The numerical experiments demonstrate the stronger coupling with geometric properties if extrinsic curvature contributions are present and provide a possibility to tuneflow and defect motion by surface properties.

iNID： An Analytical Framework for Identifying Network Models for Interplays among Developmental Signaling in Arabidopsis

Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors （IEFs）. However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling （iNID） in Arabidopsis. iNID provides a comprehensive resource of （1） transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and （2） protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of （1） phytohormones and light and （2） phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid （BR）-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.

Multivariate competing endogenous RNA network characterization for cancer microRNA biomarker discovery:a novel bioinformatics model with application to prostate cancer metastasis

Background:MicroRNAs(miRNAs)are post-transcriptional regulators with potential as biomarkers for cancer management.Datadriven competing endogenous RNA(ceRNA)network modeling is an effective way to decipher the complex interplay between miRNAs and spongers.However,there are currently no general rules for ceRNA network-based biomarker prioritization.Methods and results:In this study,a novel bioinformatics model was developed by integrating gene expression with multivariate miRNA-target data for ceRNA network-based biomarker discovery.Compared with traditional methods,the structural vulnerability in the human long non-coding RNA(lncRNA)–miRNA–messenger RNAs(mRNA)network was comprehensively analyzed,and the single-line regulatory or competing mode among miRNAs,lncRNAs,and mRNAs was characterized and quantified as statistical evidence for miRNA biomarker identification.The application of this model to prostate cancer(PCa)metastasis identified a total of 12 miRNAs as putative biomarkers from the metastatic PCa-specific lncRNA–miRNA–mRNA network and nine of them have been previously reported as biomarkers for PCa metastasis.The receiver operating characteristic curve and cell line qRT-PCR experiments demonstrated the power of miR-26b-5p,miR-130a-3p,and miR-363-3p as novel candidates for predicting PCa metastasis.Moreover,PCa-associated pathways such as prostate cancer signaling,ERK/MAPK signaling,and TGF-βsignaling were significantly enriched by targets of identified miRNAs,indicating the underlying mechanisms of miRNAs in PCa carcinogenesis.Conclusions:A novel ceRNA-based bioinformatics model was proposed and applied to screen candidate miRNA biomarkers for PCa metastasis.Functional validations using human samples and clinical data will be performed for future translational studies on the identified miRNAs.

Opto-fluidically multiplexed assembly and micro-robotics

Techniques for high-definition micromanipulations,such as optical tweezers,hold substantial interest across a wide range of disciplines.However,their applicability remains constrained by material properties and laser exposure.And while microfluidic manipulations have been suggested as an alternative,their inherent capabilities are limited and further hindered by practical challenges of implementation and control.Here we show that the iterative application of laser-induced,localized flow fields can be used for the relative positioning of multiple micro-particles,irrespectively of their material properties.Compared to the standing theoretical proposal,our method keeps particles mobile,and we show that their precision manipulation is non-linearly accelerated via the multiplexing of temperature stimuli below the heat diffusion limit.The resulting flow fields are topologically rich and mathematically predictable.They represent unprecedented microfluidic control capabilities that are illustrated by the actuation of humanoid micro-robots with up to 30 degrees of freedom,whose motions are sufficiently well-defined to reliably communicate personal characteristics such as gender,happiness and nervousness.Our results constitute high-definition micro-fluidic manipulations with transformative potential for assembly,micro-manufacturing,the life sciences,robotics and optohydraulically actuated micro-factories.

Phase-driven progress in nanophotonic biosensing

In the continuous pursuit of enhancing the sensitivity of nanophotonic biosensors by leveraging phase phenomena,a recent development involved the engineering of an atomically thin Ge2Sb2Te5 layer on a silver nanofilm to generate large Goos–Hänchen-shifts associated with phase singularities.The resulting detection limit reached~7×10^(-7)RIU.

Regulation of epithelial function, differentiation, and remodeling in the epididymis

The epididymis is a single convoluted tubule lined by a pseudostratified epithelium. Specialized epididymal epithelial cells, the so-called principal, basal, narrow, and clear cells, establish a unique luminal environment for the maturation and storage of spermatozoa. The epididymis is functionally and structurally divided into several segments and sub-segments that create regionally distinct luminal environments. This organ is immature at birth, and epithelial cells acquire their fully differentiated phenotype during an extended postnatal period, but the factors involved in this complex process remain incompletely characterized. In the adult epididymis, the establishment of an acidic luminal pH and low bicarbonate concentration in the epididymis contributes to preventing premature activation of spermatozoa during their maturation and storage. Clear cells are proton-secreting cells throughout the epididymis, but principal cells have distinct acid/base transport properties, depending on their localization within the epididymis. Basal cells are located in all epididymal segments, but they have a distinct morphology depending on the segment and species examined. How this structural plasticity of basal cells is regulated is discussed here. Also, the role of luminal factors and androgens in the regulation of epithelial cells is reviewed in relation to their respective localization in the proximal versus distal regions of the epididymis. Finally, we describe a novel role for CFTR in tubulogenesis and epithelial cell differentiation.

Deciphering Brain Complexity Using Single-cell Sequencing

The human brain contains billions of highly differentiated and interconnected cells that form intricate neural networks and collectively control the physical activities and high-level cognitive functions,such as memory,decision-making,and social behavior.Big data is required to decipher the complexity of cell types,as well as connectivity and functions of the brain.The newly developed single-cell sequencing technology,which provides a comprehensive landscape of brain cell type diversity by profiling the transcriptome,genome,and/or epigenome of individual cells,has contributed substantially to revealing the complexity and dynamics of the brain and providing new insights into brain development and brain-related disorders.In this review,we first introduce the progresses in both experimental and computational methods of single-cell sequencing technology.Applications of single-cell sequencing-based technologies in brain research,including cell type classification,brain development,and brain disease mechanisms,are then elucidated by representative studies.Lastly,we provided our perspectives into the challenges and future developments in the field of single-cell sequencing.In summary,this mini review aims to provide an overview of how big data generated from single-cell sequencing have empowered the advancements in neuroscience and shed light on the complex problems in understanding brain functions and diseases.