Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines.

Lipid nanoparticles (LNPs) are a potent delivery technology that have made it possible for the recent clinical breakthroughs in mRNA therapeutics and vaccines. A key challenge to the broader implementation of mRNA therapeutics and vaccines is the development of technology to produce precisely defined LNP formulations, with throughput that can scale from discovery to commercial manufacturing and meet the stringent manufacturing standards of the pharmaceutical industry. To address these challenges, we have developed a microfluidic chip that incorporates 1×, 10×, or 256× LNP-generating units that achieve scalable production rates of up to 17 L/h of precisely defined LNPs. Using these chips, we demonstrate that LNP physical properties and potency in vivo are unchanged as throughput is scaled. Our chips are fabricated out of silicon and glass substrates, which have excellent solvent compatibility, compatibility with pharmaceutical manufacturing, and can be fully reset and reused. SARS-CoV-2 mRNA-LNP vaccines formulated by our chips triggered potent antibody responses in a preclinical study. These results demonstrate the feasibility of directly translating microfluidic-generated LNPs to the scale necessary for commercial production.

Inorganic-Organic Nanoarchitectonics: MXene/Covalent Organic Framework Heterostructure for Superior Microextraction.

One of the difficulties limiting covalent organic frameworks (COFs) from becoming excellent adsorbents is their stacking/aggregation architectures owing to poor morphology/structure control during the synthesis process. Herein, an inorganic-organic nanoarchitectonics strategy to synthesize the MXene/COF heterostructure (Ti3 C2 Tx /TAPT-TFP) is developed by the assembly of ß-ketoenamine-linked COF on the Ti3 C2 Tx MXene nanosheets. The as-prepared Ti3 C2 Tx /TAPT-TFP retains the 2D architecture and high adsorption capacity of MXenes as well as large specific surface area and hierarchical porous structure of COFs. As a proof of concept, the potential of Ti3 C2 Tx /TAPT-TFP for solid-phase microextraction (SPME) of trace organochlorine pesticides (OCPs) is investigated. The Ti3 C2 Tx /TAPT-TFP based SPME method achieves low limits of detection (0.036-0.126 ng g-1 ), wide linearity ranges (0.12-20.0 ng g-1 ), and acceptable repeatabilities for preconcentrating trace OCPs from fruit and vegetable samples. This study offers insights into the potential of constructing COF or MXene-based heterostructures for the microextraction of environmental pollutants.

StrucGP: de novo structural sequencing of site-specific N-glycan on glycoproteins using a modularization strategy.

Precision mapping of glycans at structural and site-specific level is still one of the most challenging tasks in the glycobiology field. Here, we describe a modularization strategy for de novo interpretation of N-glycan structures on intact glycopeptides using tandem mass spectrometry. An algorithm named StrucGP is also developed to automate the interpretation process for large-scale analysis. By dividing an N-glycan into three modules and identifying each module using distinct patterns of Y ions or a combination of distinguishable B/Y ions, the method enables determination of detailed glycan structures on thousands of glycosites in mouse brain, which comprise four types of core structure and 17 branch structures with three glycan subtypes. Owing to the database-independent glycan mapping strategy, StrucGP also facilitates the identification of rare/new glycan structures. The approach will be greatly beneficial for in-depth structural and functional study of glycoproteins in the biomedical research.

Precision Glycoproteomics Reveals Distinctive N-Glycosylation in Human Spermatozoa.

Spermatozoon represents a very special cell type in human body, and glycosylation plays essential roles in its whole life including spermatogenesis, maturation, capacitation, sperm-egg recognition, and fertilization. In this study, by mapping the most comprehensive N-glycoproteome of human spermatozoa using our recently developed site-specific glycoproteomic approaches, we show that spermatozoa contain a number of distinctive glycoproteins, which are mainly involved in spermatogenesis, acrosome reaction and sperm:oocyte membrane binding, and fertilization. Heavy fucosylation is observed on 14 glycoproteins mostly located at extracellular and cell surface regions in spermatozoa but not in other tissues. Sialylation and Lewis epitopes are enriched in the biological process of immune response in spermatozoa, while bisected core structures and LacdiNAc structures are highly expressed in acrosome. These data deepen our knowledge about glycosylation in spermatozoa and lay the foundation for functional study of glycosylation and glycan structures in male infertility.

[Research progress on active ingredients of Coicis Semen].

As a common medicinal and edible resource in China, Coicis Semen has a long history of cultivation and medicinal use. Traditional Chinese medicine(TCM) clinically believes that Coicis Semen has the effect of strengthening the spleen and tonifying the lungs, clearing heat and dampness, removing pus and paralysis, and stopping diarrhea. Therefore, it is used to treat edema, foot odor, spleen deficiency, diarrhea, and other symptoms. The above effects are closely related to the active ingredients of Coicis Semen, such as esters, fatty acids, polysaccharides, proteins, as well as phenolic acids, sterols, flavonoids, lactams, triterpenes, alkaloids, and adenosine. Modern research has found that Coicis Semen also has anti-cancer, anti-inflammatory, antioxidant, hypoglycemic, and hypotensive effects and other pharmacological activities, and it can improve immunity and regulate lipid metabolism. Coicis Semen is widely distributed in China, mainly produced in Guizhou, Yunnan, Fujian, Sichuan, and other places, and the quality of Coicis Semen from different origins varies. From ancient times to the present, Coicis Semen processing methods have experienced the process from simple to complex, and the types of auxiliary materials are more extensive, such as soil, bran, and river sand. These processing methods have been inherited from generation to generation. Nowadays, the commonly used methods are bran-fried, stir-fried, sand-fried, etc. In this paper, by reviewing the relevant literature in China and abroad in recent years, the main active ingredients and related pharmacological effects of Coicis Semen are sorted out, and the effects of different origins and processing methods on the chemical composition of Coicis Semen are summarized, with a view to providing references for the comprehensive development and utilization of Coicis Semen and the further study of its mechanism of action.

GsPKS24, a calcineurin B-like protein-interacting protein kinase gene from Glycine soja, positively regulates tolerance to pH stress and ABA signal transduction.

SOS2-like protein kinases (PKS/CIPK) family genes are known to be involved in various abiotic stresses in plants. Even though, its functions have been well characterized under salt and drought stresses. The roles of PKS genes associated with alkaline stress response are not fully established yet. In this study, we identified 56 PKS family genes which could be mainly classified into three groups in wild soybean (Glycine soja). PKS family genes transcript profiles revealed different expression patterns under alkali stress. Furthermore, we confirmed the regulatory roles of GsPKS24 in response to NaHCO3, pH and ABA treatments. Overexpression of GsPKS24 enhanced plant tolerance to pH stress in Arabidopsis and soybean hairy roots but conferred suppressed pH tolerance in Arabidopsis atpks mutant. Additionally, Overexpression of GsPKS24 decreased the ABA sensitivity compared to Arabidopsis atpks mutant which displayed more sensitivity towards ABA. Moreover, upregulated expression of stress responsive and ABA signal-related genes were detected in GsPKS24 overexpression lines. In conclusion, we identified the wild soybean PKS family genes, and explored the roles of GsPKS24 in positive response to pH stress tolerance, and in alleviation of ABA sensitivity.

Unveiling immunogenic cell death-related genes in colorectal cancer: an integrated study incorporating transcriptome and Mendelian randomization analyses.

Immunogenic cell death (ICD), a type of cell death that activates the tumor-specific immune response and thus exerts anti-tumor effects, is an emerging target in tumor therapy, but research on ICD-related genes (ICDGs) in colorectal cancer (CRC) remains limited. This study aimed to identify the CRC-specific ICDGs and explore their potential roles. Through RNA sequencing for tissue samples from CRC patients and integration with The Cancer Genome Atlas (TCGA) data, we identified 33 differentially expressed ICDGs in CRC. We defined the ICD score based on these genes in single-cell data, where a high score indicated an immune-active microenvironment. Additionally, molecular subtypes identified in bulk RNA data showed distinct immune landscapes. The ICD-related signature constructed with machine learning effectively distinguished patients' prognosis. The summary data-based Mendelian randomization (SMR) and colocalization analysis prioritized CFLAR for its positive association with CRC risk. Molecular docking revealed its stable binding with chemotherapeutic drugs like irinotecan. Furthermore, experimental validation confirmed CFLAR overexpression in CRC samples, and its knockdown inhibited tumor cell proliferation. Overall, this study expands the understanding of the potential roles and mechanisms of ICDGs in CRC and highlights CFLAR as a promising target for CRC.

Ultrasensitive Single Extracellular Vesicle Detection Using High Throughput Droplet Digital Enzyme-Linked Immunosorbent Assay.

Extracellular vesicles (EVs) have attracted enormous attention for their diagnostic and therapeutic potential. However, it has proven challenging to achieve the sensitivity to detect individual nanoscale EVs, the specificity to distinguish EV subpopulations, and a sufficient throughput to study EVs among an enormous background. To address this fundamental challenge, we developed a droplet-based optofluidic platform to quantify specific individual EV subpopulations at high throughput. The key innovation of our platform is parallelization of droplet generation, processing, and analysis to achieve a throughput (∼20 million droplets/min) more than 100× greater than typical microfluidics. We demonstrate that the improvement in throughput enables EV quantification at a limit of detection = 9EVs/µL, a >100× improvement over gold standard methods. Additionally, we demonstrate the clinical potential of this system by detecting human EVs in complex media. Building on this work, we expect this technology will allow accurate quantification of rare EV subpopulations for broad biomedical applications.

Identification of NPF Family Genes in Brassica rapa Reveal Their Potential Functions in Pollen Development and Response to Low Nitrate Stress.

Nitrate Transporter 1/Peptide Transporter Family (NPF) genes encode membrane transporters involved in the transport of diverse substrates. However, little is known about the diversity and functions of NPFs in Brassica rapa. In this study, 85 NPFs were identified in B. rapa (BrNPFs) which comprised eight subfamilies. Gene structure and conserved motif analysis suggested that BrNFPs were conserved throughout the genus. Stress and hormone-responsive cis-acting elements and transcription factor binding sites were identified in BrNPF promoters. Syntenic analysis suggested that tandem duplication contributed to the expansion of BrNPFs in B. rapa. Transcriptomic profiling analysis indicated that BrNPF2.6, BrNPF2.15, BrNPF7.6, and BrNPF8.9 were expressed in fertile floral buds, suggesting important roles in pollen development. Thirty-nine BrNPFs were responsive to low nitrate availability in shoots or roots. BrNPF2.10, BrNPF2.19, BrNPF2.3, BrNPF5.12, BrNPF5.16, BrNPF5.8, and BrNPF6.3 were only up-regulated in roots under low nitrate conditions, indicating that they play positive roles in nitrate absorption. Furthermore, many genes were identified in contrasting genotypes that responded to vernalization and clubroot disease. Our results increase understanding of BrNPFs as candidate genes for genetic improvement studies of B. rapa to promote low nitrate availability tolerance and for generating sterile male lines based on gene editing methods.

Predicting carbon futures prices based on a new hybrid machine learning: Comparative study of carbon prices in different periods.

Accurate prediction of carbon price is of great significance to national energy security and climate environment policies. This paper comes up with a new forecasting model variational mode decomposition, convolutional neural network, bidirectional long short-term memory, and multi-layer perceptron (VMD-CNN-BILSTM-MLP) to predict EUA carbon futures prices in two periods of five years before and after the introduction of emission reduction policies. The parameters of the VMD model are determined by genetic algorithm (GA) firstly, carbon futures prices are broken down into subsequences of different frequencies using the model. The MLP model is then applied to predict the highest frequency sequence. The CNN-BILSTM model is applied to predict other subsequences later. Finally, the predicted values of each subsequence are linearly added to obtain the final result of the entire model. The prediction effect of the model is mainly tested by root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R2) and the modification of Diebold-Mariano test (MDM). In both periods, the proposed model predicts better than the other models, and the prediction effect of carbon futures price in the first five years is a little better than that in the second five years. In general, the experiment of predicting carbon futures prices in two different periods, the experiment of changing the proportion of data set and the experiment of predicting the whole sample all prove that the mixed model proposed in this paper has good prediction effect.

Identification of the joint line in revision total knee arthroplasty using a multiple linear regression model: a cadaveric study.

INTRODUCTION: The results of revision total knee arthroplasty (rTKA) may be compromised by excessive joint line (JL) elevation. It is critical but challenging in reestablishing the JL in rTKA. Previous studies have confirmed that, biomechanically and clinically, JL elevation should not exceed 4 mm. Image-based studies described several approaches to locate the JL intraoperatively, however magnification errors could occur. In this cadaveric study, we aim to define an accurate and reliable method to determine the JL. MATERIALS AND METHODS: Thirteen male and eleven female cadavers were used, with an average age of death being 48.3 years. The transepicondylar width (TEW), the distance from the medial (MEJL) and lateral (LEJL) epicondyle, adductor tubercle (ATJL), fibular head (FHJL) and tibial tubercle (TTJL) to the JL were measured in 48 knees. Intra- and interobserver reliability and validity were tested prior to any additional analysis. Pearson correlation and linear regression analysis were used to examine the correlations between landmark-JL distances (LEJL, MEJL, ATJL, FHJL and TTJL) and the TEW, and to further derive models for intraoperative JL determination. The accuracy of different models, quantified by errors between estimated and measured landmark-JL distances, was compared using the Friedman and post hoc Dunn tests. RESULTS: The intra- and inter-observer measurements for TEW, MEJL, LEJL, ATJL, TTJL and FHJL did not differ significantly (p > 0.05). Between genders, significant differences were found on TEW, MEJL, LEJL, ATJL, FHJL and TTJL (p < 0.05). There was no association between TEW and either FHJL or TTJL (p > 0.05), while ATJL, MEJL, and LEJL were found to be correlated with TEW (p < 0.05). Six models were derived: (1) MEJL = 0.37*TEW (r = 0.384), (2) LEJL = 0.28*TEW (r = 0.380), (3) ATJL = 0.47*TEW (r = 0.608), (4) MEJL = 0.413*TEW - 4.197 (R2 = 0.473), (5) LEJL = 0.236*TEW + 3.373 (R2 = 0.326), (6) ATJL = 0.455*TEW + 1.440 (R2 = 0.556). Errors were defined as deviations between estimated and actual landmark-JL distances. The mean absolute value of the errors, created by Model 1-6 was 3.18 ± 2.25, 2.53 ± 2.15, 2.64 ± 2.2, 1.85 ± 1.61, 1.60 ± 1.59 and 1.71 ± 1.5, respectively. The error could be limited to 4 mm in 72.9%, 83.3%, 72.9%, 87.5%, 87.5%, and 93.8% of the cases by referencing Model 1-6, respectively. CONCLUSION: Compared to previous image-based measurements, the current cadaveric study most closely resembles a realistic view of intraoperative settings and could circumvents magnification errors. We recommend using Model 6, the JL can be best estimated by referencing the AT and the ATJL can be calculated as ATJL (mm) = 0.455*TEW (mm) + 1.440 (mm).

An evaluation of remote sensing algorithms for the estimation of diffuse attenuation coefficients in the ultraviolet bands.

In this study, six algorithms (both empirical and semi-analytical) developed for the estimation of Kd in the ultraviolet (UV) domain (specifically 360, 380, and 400 nm) were evaluated from a dataset of 316 stations covering oligotrophic ocean and coastal waters. In particular, the semi-analytical algorithm (Lee et al. 2013) used remote sensing reflectance in these near-blue UV bands estimated from a recently developed deep learning system as the input. For Kd(380) in a range of 0.018 - 2.34 m-1, it is found that the semi-analytical algorithm has the best performance, where the mean absolute relative difference (MARD) is 0.19, and the coefficient of determination (R2) is 0.94. For the empirical algorithms, the MARD values are 0.23-0.90, with R2 as 0.70-0.92, for this evaluation dataset. For a VIIRS and in situ matchup dataset (N = 62), the MARD of Kd(380) is 0.21 (R2 as 0.94) by the semi-analytical algorithm. These results indicate that a combination of deep learning system and semi-analytical algorithms can provide reliable Kd(UV) for past and present satellite ocean color missions that have no spectral bands in the UV, where global Kd(UV) products are required for comprehensive studies of UV radiation on marine primary productivity and biogeochemical processes in the ocean.

Surface nanostructuring of alkali-aluminosilicate Gorilla display glass substrates using a maskless process.

This paper reports on the formation of moth-eye nanopillar structures on surfaces of alkali-aluminosilicate Gorilla glass substrates using a self-masking plasma etching method. Surface and cross-section chemical compositions studies were carried out to study the formation of the nanostructures. CFxinduced polymers were shown to be the self-masking material during plasma etching. The nanostructures enhance transmission at wavelengths over 525 nm may be utilized for fluid-induced switchable haze. Additional functionalities associated with nanostructures may be realized such as self-cleaning, anti-fogging, and stain-resistance.

Evaluation of absorbent cotton for glycopeptide enrichment.

Selecting proper and efficient glycopeptide enrichment approaches are essential for mass spectrometry-based glycoproteomics since glycopeptides are usually with microheterogeneity and low abundance in most biological samples. Herein, we introduced a cotton hydrophilic interaction liquid chromatography (HILIC) approach for large-scale glycopeptide enrichment with 80% acetonitrile/1% trifluoroacetic acid as the optimal sample loading buffer. The comparison of cotton HILIC with Venusil HILIC and mixed anion-exchange (MAX) approaches indicated that cotton HILIC was superior in overall glycopeptide enrichment, whereas Venusil HILIC preferred in complex glycan structures and MAX performed better with high mannose glycans. Exploration of capacity and recovery rate of cotton HILIC illustrated that 5mg cotton packed in a 200µL tip achieved a reasonable glycopeptide enrichment performance (~6% recovery) from ~0.5mg peptides. In conclusion, cotton HILIC can be used as an optional glycopeptide enrichment approach in glycosylation analysis with its specific merit.

Dielectric-loading approach for extra electric field enhancement and spatially transferring plasmonic hot-spots.

Plasmonic nanoantennas have been widely explored for boosting up light-matter interactions due to their ability of providing strongly confined and highly enhanced electric near fields, so called 'hot-spots'. Here, we propose a dielectric-loading approach for hot-spots engineering by coating the conventional plasmonic nanoantennas with a conformal high refractive index dielectric film and forming dielectric-loaded plasmonic nanoantennas. Compared to the conventional plasmonic nanoantennas, the corresponding dielectric-loaded ones that resonate at the same frequency are able to provide an extra enhancement in the local electric fields and meanwhile spatially transfer the hot spots to the dielectric surfaces. These findings have important implications for the design of optical nanoantennas with general applications in surface enhanced linear and nonlinear spectroscopies. As a demonstration application, we show that the maximum achievable fluorescence intensity in the dielectric-loaded plasmonic nanoantennas could be significantly larger than that in the conventional plasmonic nanoantennas.

Biological Functions and Large-Scale Profiling of Protein Glycosylation in Human Semen.

Glycosylation is one of the most important post-translational modifications of proteins and plays an essential role in spermatogenesis, maturation, extracellular quality control, capacitation, sperm-egg recognition, and final fertilization. Spermatozoa are synthesized in the testes inactively with a thick glycocalyx and passed through the epididymis for further modification by glycosylation, deglycosylation, and integration to reach maturation. Subsequently, sperm capacitation and further fertilization require redistribution of glycoconjugates and dramatic glycocalyx modification of the spermatozoa surface. Furthermore, glycoproteins and glycans in seminal plasma are functional in maintaining spermatozoa structure and stability. Therefore, aberrant glycosylation may cause alteration of semen function and even infertility. Currently, mass spectrometry-based technologies have allowed large-scale profiling of glycans and glycoproteins in human semen. Quantitative analysis of semen glycosylation has also indicated many involved glycoproteome issues in male infertility and the potential biomarkers for diagnosis of male infertility in clinical. This review summarizes the role of glycosylation during spermatozoa development, the large-scale profiling of glycome and glycoproteome in human semen, as well as the association of aberrant glycosylation with infertility.

Site-Specific N-Glycoproteomic Analysis Reveals Upregulated Sialylation and Core Fucosylation during Transient Regeneration Loss in Neonatal Mouse Hearts.

Myocardial infarction (MI) is one of the leading causes of deaths worldwide. Because of the incapability of regeneration, the cardiomyocyte loss with MI is replaced by fibrotic scar tissue, which eventually leads to heart failure. Reconstructing regeneration of an adult human heart has been recognized as a promising strategy for cardiac therapeutics. A neonatal mouse heart, which possesses transient regenerative capacity at the first week after birth, represents an ideal model to investigate processes associated with cardiac regeneration. In this work, an integrated glycoproteomic and proteomic analysis was performed to investigate the differences in glycoprotein abundances and site-specific glycosylation between postneonatal day 1 (P1) and day 7 (P7) of mouse hearts. By large-scale profiling and quantifying more than 2900 intact N-glycopeptides in neonatal mouse hearts, we identified 227 altered N-glycopeptides between P1 and P7 hearts. By extracting protein changes from the global proteome data, the normalized glycosylation changes for site-specific glycans were obtained, which showed heterogeneity on glycosites and glycoproteins. Systematic analysis of the glycosylation changes demonstrated an overall upregulation of sialylation and core fucosylation in P7 mice. Notably, the upregulated sialylation was a comprehensive result of increased sialylated glycans with Neu5Gc, with both Neu5Gc and core fucose, and decreased sialylated glycans with Neu5Ac. The upregulated core fucosylation resulted from the increase of glycans containing both core fucose and Neu5Gc but not glycans containing sole core fucose. These data provide a valuable resource for future functional and mechanism studies on heart regeneration and discovery of novel therapeutic targets. All mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD017139.

Novel cucurmosin-based immunotoxin targeting programmed cell death 1-ligand 1 with high potency against human tumor in vitro and in vivo.

Immunotoxins are Ab-cytotoxin chimeric molecules with mighty cytotoxicity. Programmed cell death 1-ligand 1 (PD-L1), is a transmembrane protein expressed mainly in inflammatory tumor tissues and plays a pivotal role in immune escape and tumor progression. Although PD-L1 immune checkpoint therapy has been successful in some cases, many patients have not benefited enough due to primary/secondary resistance. In order to optimize the therapeutic efficacy of anti-PD-L1 mAb, we used durvalumab as the payload and CUS245C , a type I ribosome-inactivating protein isolated from Cucurbita moschata, as the toxin moiety, to construct PD-L1-specific immunotoxin (named D-CUS245C ) through the engineered cysteine residue. In vitro, D-CUS245C selectively killed PD-L1+ tumor cells. In vivo studies also showed that D-CUS245C had obvious antitumor effect on PD-L1+ human xenograft tumors in nude mice. In conclusion, in the combination of the toxin with mAb, this study developed a new immunotoxin targeting PD-L1, emphasizing a novel and promising treatment strategy and providing a valuable way to optimize cancer immunotherapy.

Multiplexable high-temperature stable and low-loss intrinsic Fabry-Perot in-fiber sensors through nanograting engineering.

This paper presents a method of using femtosecond laser inscribed nanograting as low-loss- and high-temperature-stable in-fiber reflectors. By introducing a pair of nanograting inside the core of a single-mode optical fiber, an intrinsic Fabry-Perot interferometer can be created for high-temperature sensing applications. The morphology of the nanograting inscribed in fiber cores was engineered by tuning the fabrication conditions to achieve a high fringe visibility of 0.49 and low insertion loss of 0.002 dB per sensor. Using a white light interferometry demodulation algorithm, we demonstrate the temperature sensitivity, cross-talk, and spatial multiplexability of sensor arrays. Both the sensor performance and stability were studied from room temperature to 1000°C with cyclic heating and cooling. Our results demonstrate a femtosecond direct laser writing technique capable of producing highly multiplexable in-fiber intrinsic Fabry-Perot interferometer sensor devices with high fringe contrast, high sensitivity, and low-loss for application in harsh environmental conditions.

Multiplexable intrinsic Fabry-Perot interferometric fiber sensors for multipoint hydrogen gas monitoring.

This Letter presents an approach to produce multiplexable optical fiber chemical sensor using an intrinsic Fabry-Perot interferometer (IFPI) array via the femtosecond laser direct writing technique. Using the hydrogen-sensitive palladium (Pd) alloy as a functional sensory material, Pd alloy coated IFPI devices can reproducibly and reversibly measure hydrogen concentrations with a detection limit of 0.25% at room temperature. Seven IFPI sensors were fabricated in one fiber and performed simultaneous temperature and hydrogen measurements at seven different locations. This Letter demonstrates a simple yet effective approach to fabricate multiplexable fiber optical chemical sensors for use in harsh environments.