Self-partitioning SlipChip for slip-induced droplet formation and human papillomavirus viral load quantification with digital LAMP

Human papillomavirus (HPV) is one of the most common sexually transmitted infections worldwide, and persistent HPV infection can cause warts and even cancer. Nucleic acid analysis of HPV viral DNA can be very informative for the diagnosis and monitoring of HPV. Digital nucleic acid analysis, such as digital PCR and digital isothermal amplification, can provide sensitive detection and precise quantification of target nucleic acids, and its utility has been demonstrated in many biological research and medical diagnostic applications. A variety of methods have been developed for the generation of a large number of individual reaction partitions, a key requirement for digital nucleic acid analysis. However, an easily assembled and operated device for robust droplet formation without preprocessing devices, auxiliary instrumentation or control systems is still highly desired. In this paper, we present a self-partitioning SlipChip (sp-SlipChip) microfluidic device for the slip-induced generation of droplets to perform digital loop-mediated isothermal amplification (LAMP) for the detection and quantification of HPV DNA. In contrast to traditional SlipChip methods, which require the precise alignment of microfeatures, this sp-SlipChip utilized a design of “chain-of-pearls” continuous microfluidic channel that is independent of the overlapping of microfeatures on different plates to establish the fluidic path for reagent loading. Initiated by a simple slipping step, the aqueous solution can robustly self-partition into individual droplets by capillary pressure-driven flow. This advantage makes the sp-SlipChip very appealing for the point-of-care quantitative analysis of viral load. As a proof of concept, we performed digital LAMP on an sp-SlipChip to quantify human papillomaviruses (HPVs) 16 and 18 and tested this method with fifteen anonymous clinical samples

GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting

Transformer-based models have emerged as promising tools for time series forecasting. However, these model cannot make accurate prediction for long input time series. On the one hand, they failed to capture global dependencies within time series data. On the other hand, the long input sequence usually leads to large model size and high time complexity. To address these limitations, we present GCformer, which combines a structured global convolutional branch for processing long input sequences with a local Transformer-based branch for capturing short, recent signals. A cohesive framework for a global convolution kernel has been introduced, utilizing three distinct parameterization methods. The selected structured convolutional kernel in the global branch has been specifically crafted with sublinear complexity, thereby allowing for the efficient and effective processing of lengthy and noisy input signals. Empirical studies on six benchmark datasets demonstrate that GCformer outperforms state-of-the-art methods, reducing MSE error in multivariate time series benchmarks by 4.38% and model parameters by 61.92%. In particular, the global convolutional branch can serve as a plug-in block to enhance the performance of other models, with an average improvement of 31.93\%, including various recently published Transformer-based models. Our code is publicly available at https://github.com/zyj-111/GCformer

Self-partitioning SlipChip for slip-induced droplet formation and human papillomavirus viral load quantification with digital LAMP

Human papillomavirus (HPV) is one of the most common sexually transmitted infections worldwide, and persistent HPV infection can cause warts and even cancer. Nucleic acid analysis of HPV viral DNA can be very informative for the diagnosis and monitoring of HPV. Digital nucleic acid analysis, such as digital PCR and digital isothermal amplification, can provide sensitive detection and precise quantification of target nucleic acids, and its utility has been demonstrated in many biological research and medical diagnostic applications. A variety of methods have been developed for the generation of a large number of individual reaction partitions, a key requirement for digital nucleic acid analysis. However, an easily assembled and operated device for robust droplet formation without preprocessing devices, auxiliary instrumentation or control systems is still highly desired. In this paper, we present a self-partitioning SlipChip (sp-SlipChip) microfluidic device for the slip-induced generation of droplets to perform digital loop-mediated isothermal amplification (LAMP) for the detection and quantification of HPV DNA. In contrast to traditional SlipChip methods, which require the precise alignment of microfeatures, this sp-SlipChip utilized a design of “chain-of-pearls” continuous microfluidic channel that is independent of the overlapping of microfeatures on different plates to establish the fluidic path for reagent loading. Initiated by a simple slipping step, the aqueous solution can robustly self-partition into individual droplets by capillary pressure-driven flow. This advantage makes the sp-SlipChip very appealing for the point-of-care quantitative analysis of viral load. As a proof of concept, we performed digital LAMP on an sp-SlipChip to quantify human papillomaviruses (HPVs) 16 and 18 and tested this method with fifteen anonymous clinical samples

Improved Generation of Induced Cardiomyocytes Using a Polycistronic Construct Expressing Optimal Ratio of Gata4, Mef2c and Tbx5

Direct conversion of cardiac fibroblasts (CFs) into induced cardiomyocytes (iCMs) holds great potential for regenerative medicine by offering alternative strategies for treatment of heart disease. This conversion has been achieved by forced expression of defined factors such as Gata4 (G), Mef2c (M) and Tbx5 (T). Traditionally, iCMs are generated by a cocktail of viruses expressing these individual factors. However, reprogramming efficiency is relatively low and most of the in vitro G,M,T-transduced fibroblasts do not become fully reprogrammed, making it difficult to study the reprogramming mechanisms. We recently have shown that the stoichiometry of G,M,T is crucial for efficient iCM reprogramming. An optimal stoichiometry of G,M,T with relative high level of M and low levels of G and T achieved by using our polycistronic MGT vector (hereafter referred to as MGT) significantly increased reprogramming efficiency and improved iCM quality in vitro. Here we provide a detailed description of the methodology used to generate iCMs with MGT construct from cardiac fibroblasts. Isolation of cardiac fibroblasts, generation of virus for reprogramming and evaluation of the reprogramming process are also included to provide a platform for efficient and reproducible generation of iCMs

Systematic comparison of 2A peptides for cloning multi-genes in a polycistronic vector

Cloning of multiple genes in a single vector has greatly facilitated both basic and translational studies that require co-expression of multiple factors or multi-units of complex protein. Many strategies have been adopted, among which 2A "self-cleaving" peptides have garnered increased interest for their polycistronic nature, small size and high "cleavage" efficiency. However, broad application of 2 A peptides is limited by the lack of systematic comparison of different 2As alone or in combination. Here we characterized the effect of varying gene position and 2As on the expression of proteins encoded in bi-, tri-, or quad-cistronic constructs. Using direct cardiac reprogramming as an example, we further determined the effect of varied 2As on the efficiency of fluorescent cell labeling and cell fate conversion. We found that the expression of fluorophores decreased as it was moved towards the end of the construct while reprogramming was most efficient with the fluorophore at the second position. Moreover, quad-cistronic TPE2A constructs resulted in more efficient reprogramming than 3P2A or PTE2A constructs. We expect that the bi-, tri-, and quad-cistronic vectors constructed here and our results on protein expression ratios from different 2A constructs could serve to guide future utilization of 2A peptides in basic research and clinical applications

Bmi1 Is a Key Epigenetic Barrier to Direct Cardiac Reprogramming

Direct reprogramming of induced cardiomyocytes (iCMs) suffers from low efficiency and requires extensive epigenetic repatterning, although the underlying mechanisms are largely unknown. To address these issues, we screened for epigenetic regulators of iCM reprogramming and found that reducing levels of the polycomb complex gene Bmi1 significantly enhanced induction of beating iCMs from neonatal and adult mouse fibroblasts. The inhibitory role of Bmi1 in iCM reprogramming is mediated through direct interactions with regulatory regions of cardiogenic genes, rather than regulation of cell proliferation. Reduced Bmi1 expression corresponded with increased levels of the active histone mark H3K4me3 and reduced levels of repressive H2AK119ub at cardiogenic loci, and de-repression of cardiogenic gene expression during iCM conversion. Furthermore, Bmi1 deletion could substitute for Gata4 during iCM reprogramming. Thus, Bmi1 acts as a critical epigenetic barrier to iCM production. Bypassing this barrier simplifies iCM generation and increases yield, potentially streamlining iCM production for therapeutic purposes

Bilayer game strategy of regional integrated energy system under multi-agent incomplete information

In view of the high coupling degree of regional integrated energy system, a bilayer interaction strategy, consisting of energy suppliers, distribution networks, and users, is proposed. Game interaction strategy includes two aspects: scheduling and bidding. The independent system operator (ISO) coordinates all adjustable resources. Depending on the quotation price and multi-energy load prediction, ISO minimises the total energy cost, which realises the complementary of the multi-energy in the cooperative game. Under the assumption of incomplete information and bounded rationality, this study designs bidding functions and pay-as-bid settlement protocols. On this basis, according to history scheduling data and units’ characteristics, agents for energy suppliers pursue maximum interests. Also, the non-cooperative bidding process in multi-energy market is simulated by using Q-learning algorithm. Finally, the evolutionary process of the bilayer competitive game model is studied by practical example, and the existence local Nash equilibrium of the strategy is also proven

Improved Generation of Induced Cardiomyocytes Using a Polycistronic Construct Expressing Optimal Ratio of Gata4, Mef2c and Tbx5

Direct conversion of cardiac fibroblasts (CFs) into induced cardiomyocytes (iCMs) holds great potential for regenerative medicine by offering alternative strategies for treatment of heart disease. This conversion has been achieved by forced expression of defined factors such as Gata4 (G), Mef2c (M) and Tbx5 (T). Traditionally, iCMs are generated by a cocktail of viruses expressing these individual factors. However, reprogramming efficiency is relatively low and most of the in vitro G,M,T-transduced fibroblasts do not become fully reprogrammed, making it difficult to study the reprogramming mechanisms. We recently have shown that the stoichiometry of G,M,T is crucial for efficient iCM reprogramming. An optimal stoichiometry of G,M,T with relative high level of M and low levels of G and T achieved by using our polycistronic MGT vector (hereafter referred to as MGT) significantly increased reprogramming efficiency and improved iCM quality in vitro. Here we provide a detailed description of the methodology used to generate iCMs with MGT construct from cardiac fibroblasts. Isolation of cardiac fibroblasts, generation of virus for reprogramming and evaluation of the reprogramming process are also included to provide a platform for efficient and reproducible generation of iCMs