Rapid droplet-based mixing for single-molecule spectroscopy.

Probing non-equilibrium dynamics with single-molecule spectroscopy is important for dissecting biomolecular mechanisms. However, existing microfluidic rapid-mixing systems for this purpose are incompatible with surface-adhesive biomolecules, exhibit undesirable flow dispersion and are often demanding to fabricate. Here we introduce droplet-based microfluidic mixing for single-molecule spectroscopy to overcome these limitations in a wide range of applications. We demonstrate its robust functionality with binding kinetics of even very surface-adhesive proteins on the millisecond timescale.

Driving forces of the complex formation between highly charged disordered proteins.

Highly disordered complexes between oppositely charged intrinsically disordered proteins present a new paradigm of biomolecular interactions. Here, we investigate the driving forces of such interactions for the example of the highly positively charged linker histone H1 and its highly negatively charged chaperone, prothymosin α (ProTα). Temperature-dependent single-molecule Förster resonance energy transfer (FRET) experiments and isothermal titration calorimetry reveal ProTα-H1 binding to be enthalpically unfavorable, and salt-dependent affinity measurements suggest counterion release entropy to be an important thermodynamic driving force. Using single-molecule FRET, we also identify ternary complexes between ProTα and H1 in addition to the heterodimer at equilibrium and show how they contribute to the thermodynamics observed in ensemble experiments. Finally, we explain the observed thermodynamics quantitatively with a mean-field polyelectrolyte theory that treats counterion release explicitly. ProTα-H1 complex formation resembles the interactions between synthetic polyelectrolytes, and the underlying principles are likely to be of broad relevance for interactions between charged biomolecules in general.

Characterization of the gut microbiota in polycystic ovary syndrome with dyslipidemia.

BACKGROUND: Polycystic ovary syndrome (PCOS) is an endocrinopathy in childbearing-age females which can cause many complications, such as diabetes, obesity, and dyslipidemia. The metabolic disorders in patients with PCOS were linked to gut microbial dysbiosis. However, the correlation between the gut microbial community and dyslipidemia in PCOS remains unillustrated. Our study elucidated the different gut microbiota in patients with PCOS and dyslipidemia (PCOS.D) compared to those with only PCOS and healthy women. RESULTS: In total, 18 patients with PCOS, 16 healthy females, and 18 patients with PCOS.D were enrolled. The 16 S rRNA sequencing in V3-V4 region was utilized for identifying the gut microbiota, which analyzes species annotation, community diversity, and community functions. Our results showed that the ß diversity of gut microbiota did not differ significantly among the three groups. Regarding gut microbiota dysbiosis, patients with PCOS showed a decreased abundance of Proteobacteria, and patients with PCOS.D showed an increased abundance of Bacteroidota compared to other groups. With respect to the gut microbial imbalance at genus level, the PCOS.D group showed a higher abundance of Clostridium_sensu_stricto_1 compared to other two groups. Furthermore, the abundances of Faecalibacterium and Holdemanella were lower in the PCOS.D than those in the PCOS group. Several genera, including Faecalibacterium and Holdemanella, were negatively correlated with the lipid profiles. Pseudomonas was negatively correlated with luteinizing hormone levels. Using PICRUSt analysis, the gut microbiota community functions suggested that certain metabolic pathways (e.g., amino acids, glycolysis, and lipid) were altered in PCOS.D patients as compared to those in PCOS patients. CONCLUSIONS: The gut microbiota characterizations in patients with PCOS.D differ from those in patients with PCOS and controls, and those might also be related to clinical parameters. This may have the potential to become an alternative therapy to regulate the clinical lipid levels of patients with PCOS in the future.

Effects of SARS-CoV-2 infection during ovarian stimulation on ART outcomes.

RESEARCH QUESTION: Does severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection during ovarian stimulation affect assisted reproductive technology outcomes? DESIGN: This retrospective cohort study conducted at the Reproductive Medicine Centre of The First Affiliated Hospital of Anhui Medical University aimed to assess the effects of acute SARS-CoV-2 infection during IVF on treatment outcomes and the reproductive system. The study included 151 treatment cycles involving couples with coronavirus disease 2019 (COVID-19) during ovarian stimulation, along with 224 cycles of non-infected couples as a control group. Clinical characteristics and laboratory parameters were analysed, including total gonadotrophin dosage, duration of ovarian stimulation, number of oocytes retrieved, fertilization method, fertilization rate, and number of blastocyst embryos available. Forty-six follicular fluid samples, 38 semen samples and 78 embryo culture medium samples from patients with COVID-19 were tested for SARS-CoV-2 RNA using reverse transcription polymerase chain reaction assay. RESULTS: The treatment and control groups showed similar cycle characteristics, including fertilization method, total gonadotrophin dosage and duration of ovarian stimulation. The mean number of oocytes retrieved per cycle and rate of mature oocytes in intracytoplasmic sperm injection cycles were comparable. No significant difference was observed in the total number of blastocyst embryos available between the groups. Furthermore, no SARS-CoV-2 RNA was detected in any of the samples of patients with COVID-19. CONCLUSIONS: In conclusion, acute SARS-CoV-2 infection during ovarian stimulation does not have a significant impact on IVF treatment outcomes. Additionally, no risk to the reproductive system was observed in patients infected with SARS-CoV-2. Therefore, individuals with asymptomatic or mild COVID-19 can safely continue IVF treatment. Future research is needed to investigate the long-term effects of COVID-19 on fertility and reproductive outcomes.

Novel mutations in DNAH17 cause sperm flagellum defects and their influence on ICSI outcome.

PURPOSE: To identify new mutations in DNAH17 that cause male infertility and analyze intracytoplasmic sperm injection (ICSI) outcomes in patients with DNAH17 mutations. METHODS: A total of five cases of new DNAH17 mutations exhibiting the multiple morphological abnormalities of the sperm flagella (MMAF) phenotype were identified through semen analysis and genetic testing. They were recruited at our reproductive medicine center from September 2018 to July 2022. Information on DNAH17 genetic mutations and ICSI outcomes was systematically explored following a literature review. RESULTS: Three novel compound mutations in DNAH17 were identified in patients with male infertility caused by MMAF. This study and previous publications included 21 patients with DNAH17 mutations. DNAH17 has been associated with asthenozoospermia and male infertility, but different types of DNAH17 variants appear to be involved in different sperm phenotypes. In 11 couples of infertile patients with DNAH17 mutations, there were 17 ICSI cycles and 13 embryo transplantation cycles. Only three men with DNAH17 variants ultimately achieved clinical pregnancy with their partners through ICSI combined with assisted oocyte activation (AOA). CONCLUSIONS: Loss-of-function mutations in DNAH17 can lead to severe sperm flagellum defects and male infertility. Patients with MMAF-harboring DNAH17 mutations generally have worse pregnancy outcomes following ICSI. ICSI combined with AOA may improve the outcome of assisted reproductive techniques (ARTs) for men with DNAH17 variants.

Droplet-Based Microfluidic Temperature-Jump Platform for the Rapid Assessment of Biomolecular Kinetics.

Protein folding, unfolding, and aggregation are important in a variety of biological processes and intimately linked to "protein misfolding diseases". The ability to perform experiments at different temperatures allows the extraction of important information regarding the kinetics and thermodynamics of such processes. Unfortunately, conventional stopped-flow methods are difficult to implement, generate limited information, and involve complex sample handling. To address this issue, we present a temperature-controlled droplet-based microfluidic platform that allows measurement of reaction kinetics on millisecond to second timescales and at temperatures between ambient and 90 °C. The utility of the microfluidic platform for measuring fast biomolecular kinetics at high temperatures is showcased through the investigation of the unfolding kinetics of haloalkane dehalogenases and the elongation of fibrils composed of the amyloid ß peptide associated with Alzheimer's disease. In addition, a deep-ultraviolet (UV) fluorescence microscope was developed for the on-chip recording of protein intrinsic fluorescence spectrum originating from aromatic amino acid residues. We envision that the developed optofluidic platform will find wide applicability in the analysis of biological processes, such as protein refolding and phase separation.

Droplet-based optofluidic systems for measuring enzyme kinetics.

The study of enzyme kinetics is of high significance in understanding metabolic networks in living cells and using enzymes in industrial applications. To gain insight into the catalytic mechanisms of enzymes, it is necessary to screen an enormous number of reaction conditions, a process that is typically laborious, time-consuming, and costly when using conventional measurement techniques. In recent times, droplet-based microfluidic systems have proved themselves to be of great utility in large-scale biological experimentation, since they consume a minimal sample, operate at high analytical throughput, are characterized by efficient mass and heat transfer, and offer high levels of integration and automation. The primary goal of this review is the introduction of novel microfluidic tools and detection methods for use in high-throughput and sensitive analysis of enzyme kinetics. The first part of this review focuses on introducing basic concepts of enzyme kinetics and describing most common microfluidic approaches, with a particular focus on segmented flow. Herein, the key advantages include accurate control over the flow behavior, efficient mass and heat transfer, multiplexing, and high-level integration with detection modalities. The second part describes the current state-of-the-art platforms for high-throughput and sensitive analysis of enzyme kinetics. In addition to our categorization of recent advances in measuring enzyme kinetics, we have endeavored to critically assess the limitations of each of these detection approaches and propose strategies to improve measurements in droplet-based microfluidics. Graphical abstract.

Integrally Cooperative Spatio-Temporal Feature Representation of Motion Joints for Action Recognition.

In contemporary research on human action recognition, most methods separately consider the movement features of each joint. However, they ignore that human action is a result of integrally cooperative movement of each joint. Regarding the problem, this paper proposes an action feature representation, called Motion Collaborative Spatio-Temporal Vector (MCSTV) and Motion Spatio-Temporal Map (MSTM). MCSTV comprehensively considers the integral and cooperative between the motion joints. MCSTV weighted accumulates limbs' motion vector to form a new vector to account for the movement features of human action. To describe the action more comprehensively and accurately, we extract key motion energy by key information extraction based on inter-frame energy fluctuation, project the energy to three orthogonal axes and stitch them in temporal series to construct the MSTM. To combine the advantages of MSTM and MCSTV, we propose Multi-Target Subspace Learning (MTSL). MTSL projects MSTM and MCSTV into a common subspace and makes them complement each other. The results on MSR-Action3D and UTD-MHAD show that our method has higher recognition accuracy than most existing human action recognition algorithms.

[Study on HPLC fingerprint of Sabia parviflora].

This research was performed to establish the HPLC fingerprint of Sabia parviflora. HPLC method was carried out on a Thermo Accucore-C18(4. 6 mm×150 mm,2. 6 µm) column by 30% tetrahydrofuran in methyl alcohol-acetonitrile-0. 1% phosphate solution as mobile phase at a flow rate of 1. 0 m L·min-1,the column temperature was 30 ℃ and the detection wavelength was 360 nm. The fingerprints were further evaluated by chemometrics methods including similarity analysis,hierarchical clustering analysis,and principal component analysis. In HPLC fingerprint,15 common peaks were selected as the common peaks,and 6 contents of them were identified. The similarity degrees of 38 batches of the samples was more than 0. 710,and the samples were divided into 6 clusters by their quality difference. The method was precision,repeatable,stable,simple and reliable,which could be used for quality control and evaluation of S. parviflora.

Fluoropolymer-Coated PDMS Microfluidic Devices for Application in Organic Synthesis.

In recent years there has been huge interest in the development of microfluidic reactors for the synthesis of small molecules and nanomaterials. Such reaction platforms represent a powerful and versatile alternative to traditional formats since they allow for the precise, controlled, and flexible management of reactive processes. To date, the majority of microfluidic reactors used in small-molecule synthesis have been manufactured using conventional lithographic techniques from materials such as glasses, ceramics, stainless steel, and silicon. Surprisingly, the fabrication of microfluidic devices from such rigid materials remains ill-defined, complex, and expensive. Accordingly, the microfluidic toolkit for chemical synthesis would significantly benefit from the development of solvent-resistant microfluidic devices that can be manufactured using soft-lithographic prototyping methods. Whilst significant advances in the development of solvent-resistant polymers have been made, only modest steps have been taken towards simplifying their use as microfluidic reactors. Herein, we emphasize the benefits of using a commercially available, amorphous perfluorinated polymer, CYTOP, as a coating with which to transform PDMS into a chemically inert material for use in organic synthesis applications. Its efficacy is demonstrated through the subsequent performance of photooxidation reactions and reactions under extremely acidic or basic conditions.

A High-Sensitivity, Integrated Absorbance and Fluorescence Detection Scheme for Probing Picoliter-Volume Droplets in Segmented Flows.

Droplet-based microfluidic systems that incorporate flowing streams of pL-volume droplets surrounded by a continuous and immiscible carrier phase have attracted significant recent attention due to their utility in complex chemical and biological experimentation. Analysis of pL droplets, generated at kHz frequencies and moving at high linear velocities, is almost exclusively achieved using fluorescence-based detection schemes. To extend the applicability of such optical detection schemes, we herein report the development of a simple and cost-effective optofluidic platform, integrating liquid-core PDMS waveguides, that allows the accurate measurement of absorbance within individual pL-volume droplets moving within segmented flows. Using such an approach, differential measurements of "sample "and "reference" droplets can be acquired at 1 kHz and yield detection limits of 400 nM for fluorescein in water. Significantly, the presented technique enables simultaneous fluorescence and absorbance interrogation of rapidly moving droplets in a fully automated manner. Proof of principle is demonstrated through the titration and monitoring of pH gradients in real time.

PATrans: Pixel-Adaptive Transformer for edge segmentation of cervical nuclei on small-scale datasets.

Transformer has shown excellent performance in various visual tasks, making its application in medicine an inevitable trend. Nevertheless, simply using transformer for small-scale cervical nuclei datasets will result in disastrous performance. Scarce nuclei pixels are not enough to compensate for the lack of CNNs-inherent intrinsic inductive biases, making transformer difficult to model local visual structures and deal with scale variations. Thus, we propose a Pixel Adaptive Transformer(PATrans) to improve the segmentation performance of nuclei edges on small datasets through adaptive pixel tuning. Specifically, to mitigate information loss resulting from mapping different patches into similar latent representations, Consecutive Pixel Patch (CPP) embeds rich multi-scale context into isolated image patches. In this way, it can provide intrinsic scale invariance for 1D input sequences to maintain semantic consistency, allowing the PATrans to establish long-range dependencies quickly. Futhermore, due to the existing handcrafted-attention is agnostic to the widely varying pixel distributions, the Pixel Adaptive Transformer Block (PATB) effectively models the relationships between different pixels across the entire feature map in a data-dependent manner, guided by the important regions. By collaboratively learning local features and global dependencies, PATrans can adaptively reduce the interference of irrelevant pixels. Extensive experiments demonstrate the superiority of our model on three datasets(Ours, ISBI, Herlev).

An efficient Fusion-Purification Network for Cervical pap-smear image classification.

BACKGROUND AND OBJECTIVES: In cervical cell diagnostics, autonomous screening technology constitutes the foundation of automated diagnostic systems. Currently, numerous deep learning-based classification techniques have been successfully implemented in the analysis of cervical cell images, yielding favorable outcomes. Nevertheless, efficient discrimination of cervical cells continues to be challenging due to large intra-class and small inter-class variations. The key to dealing with this problem is to capture localized informative differences from cervical cell images and to represent discriminative features efficiently. Existing methods neglect the importance of global morphological information, resulting in inadequate feature representation capability. METHODS: To address this limitation, we propose a novel cervical cell classification model that focuses on purified fusion information. Specifically, we first integrate the detailed texture information and morphological structure features, named cervical pathology information fusion. Second, in order to enhance the discrimination of cervical cell features and address the data redundancy and bias inherent after fusion, we design a cervical purification bottleneck module. This model strikes a balance between leveraging purified features and facilitating high-efficiency discrimination. Furthermore, we intend to unveil a more intricate cervical cell dataset: Cervical Cytopathology Image Dataset (CCID). RESULTS: Extensive experiments on two real-world datasets show that our proposed model outperforms state-of-the-art cervical cell classification models. CONCLUSIONS: The results show that our method can well help pathologists to accurately evaluate cervical smears.

Application of modern synthetic biology technology in aromatic amino acids and derived compounds biosynthesis.

Aromatic amino acids (AAA) and derived compounds have enormous commercial value with extensive applications in the food, chemical and pharmaceutical fields. Microbial production of AAA and derived compounds is a promising prospect for its environmental friendliness and sustainability. However, low yield and production efficiency remain major challenges for realizing industrial production. With the advancement of synthetic biology, microbial production of AAA and derived compounds has been significantly facilitated. In this review, a comprehensive overview on the current progresses, challenges and corresponding solutions for AAA and derived compounds biosynthesis is provided. The most cutting-edge developments of synthetic biology technology in AAA and derived compounds biosynthesis, including CRISPR-based system, genetically encoded biosensors and synthetic genetic circuits, were highlighted. Finally, future prospects of modern strategies conducive to the biosynthesis of AAA and derived compounds are discussed. This review offers guidance on constructing microbial cell factory for aromatic compound using synthetic biology technology.

Towards an active droplet-based microfluidic platform for programmable fluid handling.

Droplet-based microfluidic systems have emerged as powerful alternatives to conventional high throughput screening platforms, due to their operational flexibility, high-throughput nature and ability to efficiently process small fluid volumes. However, the challenges associated with performing bespoke operations on user-defined droplets often limit their utility in screening applications that involve complex workflows. To this end, the marriage of droplet- and valve-based microfluidic technologies offers the prospect of balancing the controllability of droplet manipulations and analytical throughput. In this spirit, we present a microfluidic platform that combines the capabilities of integrated microvalve technology with droplet-based sample compartmentalization to realize a highly adaptable programmable fluid handling functionality. The microfluidic device consists of a programmable formulator linked to an automated droplet generation device and storage array. The formulator leverages multiple inputs coupled to a mixing ring to produce combinatorial solution mixtures, with a peristaltic pump enabling titration of reagents into the ring with picoliter resolution. The platform allows for the execution of user-defined reaction protocols within an array of storage chambers by consecutively merging programmable sequences of pL-volume droplets containing specified reagents. The precision in formulating solutions with small differences in concentration is perfectly suited for the accurate estimation of kinetic parameters. The utility of our platform is showcased through the performance of enzymatic kinetic measurements of beta-galactosidase and horseradish peroxidase with fluorogenic substrates. The presented platform provides for a range of automated manipulations and paves the way for a more diverse range of droplet-based biological experiments.

Multidimensional engineering of Escherichia coli for efficient synthesis of L-tryptophan.

Development of microbial cell factory for L-tryptophan (L-trp) production has received widespread attention but still requires extensive efforts due to weak metabolic flux distribution and low yield. Here, the riboswitch-based high-throughput screening (HTS) platform was established to construct a powerful L-trp-producing chassis cell. To facilitate L-trp biosynthesis, gene expression was regulated by promoter and N-terminal coding sequences (NCS) engineering. Modules of degradation, transport and by-product synthesis related to L-trp production were also fine-tuned. Next, a novel transcription factor YihL was excavated to negatively regulate L-trp biosynthesis. Self-regulated promoter-mediated dynamic regulation of branch pathways was performed and cofactor supply was improved for further L-trp biosynthesis. Finally, without extra addition, the yield of strain Trp30 reached 42.5 g/L and 0.178 g/g glucose after 48 h of cultivation in 5-L bioreactor. Overall, strategies described here worked up a promising method combining HTS and multidimensional regulation for developing cell factories for products in interest.

In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning.

Nowadays, the vastly increasing demand for novel biotechnological products is supported by the continuous development of biocatalytic applications that provide sustainable green alternatives to chemical processes. The success of a biocatalytic application is critically dependent on how quickly we can identify and characterize enzyme variants fitting the conditions of industrial processes. While miniaturization and parallelization have dramatically increased the throughput of next-generation sequencing systems, the subsequent characterization of the obtained candidates is still a limiting process in identifying the desired biocatalysts. Only a few commercial microfluidic systems for enzyme analysis are currently available, and the transformation of numerous published prototypes into commercial platforms is still to be streamlined. This review presents the state-of-the-art, recent trends, and perspectives in applying microfluidic tools in the functional and structural analysis of biocatalysts. We discuss the advantages and disadvantages of available technologies, their reproducibility and robustness, and readiness for routine laboratory use. We also highlight the unexplored potential of microfluidics to leverage the power of machine learning for biocatalyst development.

MicroRNA-451a plays a role in polycystic ovary syndrome by regulating ovarian granulosa cell proliferation and apoptosis.

The present study aimed to investigate whether microRNA (miR)-451a plays a role in polycystic ovary syndrome by regulating the biological function of ovarian granulosa cells and investigate the underlying molecular mechanism. In the present study, reverse transcription-quantitative PCR (RT-qPCR) analysis detected markedly low expression of miR-451a in KGN cells. TargetScan predicted that cyclic AMP-dependent transcription factor ATF-2 (ATF2) was a potential target gene of miR-451a, which was confirmed by a Dual-Luciferase reporter gene assay. Moreover, western blotting and RT-qPCR experiments indicated that ATF2 was significantly overexpressed in KGN cells. In addition, western blotting and RT-qPCR experiments were utilized to assess cell transfection efficiency, and it was found that miR-451a mimic significantly increased miR-451a expression in KGN cells. Subsequently, MTT assay was performed to detect cell proliferation and flow cytometry was utilized to detect cell apoptosis. Western blot and RT-qPCR assays were utilized to assess the protein and mRNA expression of ATF2 and cyclin D1. The results confirmed that miR-451a mimic significantly decreased ATF2 protein and mRNA expression in KGN cells, and this decrease was reversed by ATF2-plasmid co-transfection. Moreover, miR-451a mimic inhibited cell proliferation, enhanced cell apoptosis, reduced cyclin D1 expression, increased caspase-3 activity and cleaved caspase-3 protein levels, while it reduced pro-caspase 3 protein levels in KGN cells, and these effects were significantly reversed by ATF2-plasmid. The present preliminary results demonstrated that miR-451a regulated the proliferation and apoptosis of ovarian granulosa cells by targeting ATF2. Thus, the miR-451a/ATF2 axis may be a new potential target for the treatment of polycystic ovary syndrome.

Spectrum-effect relationship study between HPLC fingerprints and antioxidant activity of Sabia parviflora.

Nowadays, the increased prevalence of sub-health significantly affects human health worldwide. Suppressed sub-healthy by dietotherapy/herbal remedy which showed excellent safety profile, low cost and effectiveness, is an effective way. In this research, the fingerprint and antioxidant activity of Sabia parviflora were obtained by HPLC instrument and DPPH, ABTS, FRAP heatmap assays. And the antioxidant active substances were selected by spectrum-effect relationship. The results showed that significant differences in chemical compositions of samples from different sources, and EW, EE extracts had strong antioxidant activity. The antioxidant activity of Sabia parviflora was mainly determined by the complex interaction of various flavonoids (promoting, competing or antagonizing). These findings revealed that the abundant flavonoids in Sabia parviflora had significant antioxidant activity and could be potential antioxidants. With therapeutic potential for sub-health, this special tea might provide dietotherapy/herbal to remedy sub-healthy population.

[Preparation and in vitro drug release behavior of a novel matrine-loading chitosan/glycerol film].

OBJECTIVE: To prepare a drug-loading film using chitosan and carboxymethyl chitosan as the carrier materials for delivering matrine to oral ulcers. METHODS: Matrine-loading films using chitosan or carboxymethyl chitosan as the carrier materials were prepared by solution casting method and orthogonal experiment at room temperature. The mechanical properties, surface morphology and drug-loading capacity of the drug-loading film were characterized using tensile test, scanning electron microscopy (SEM), swelling test and in vitro drug release test. RESULTS: When the molecular weight of chitosan was 650 000 and the mass ratio of chitosan/glycerol was 1:1.4, the prepared film had the maximum mechanical strength and tensile modulus reaching 0.7875 MPa. SEM observation showed that matrine aggregated at the bottom of the drug-loading film with an asymmetrical distribution. The in vitro drug release test showed that the film had a high drug-loading capacity and a sustained drug release property. The duration of drug release from the drug-loading film was prolonged as the molecular weight of chitosan increased, reaching 23 h when the molecular weight of chitosan was 650 000. The duration of drug release was further increased to 108 h when the bottom of the drug-loading film was coated with a layer of 1% carboxymethyl chitosan. CONCLUSION: The matrix materials of the drug-loading film are natural, green, nontoxic and biodegradable, and the preparation of the film is simple without using large quantities of organic solvents. The novel drug-loading film can obviously prolong the duration of drugs release for better local drug delivery to oral ulcers in a sustained manner.