Newborn Screening for Inborn Errors of Metabolism by Next-Generation Sequencing Combined with Tandem Mass Spectrometry.

The aim of this study was to observe the outcomes of newborn screening (NBS) in a certain population by using next-generation sequencing (NGS) as a first-tier screening test combined with tandem mass spectrometry (MS/MS). We performed a multicenter study of 29,601 newborns from eight screening centers with NBS via NGS combined with MS/MS. A custom-designed panel targeting the coding region of the 142 genes of 128 inborn errors of metabolism (IEMs) was applied as a first-tier screening test, and expanded NBS using MS/MS was executed simultaneously. In total, 52 genes associated with the 38 IEMs screened by MS/MS were analyzed. The NBS performance of these two methods was analyzed and compared respectively. A total of 23 IEMs were diagnosed via NGS combined with MS/MS. The incidence of IEMs was approximately 1 in 1287. Within separate statistical analyses, the positive predictive value (PPV) for MS/MS was 5.29%, and the sensitivity was 91.3%. However, for genetic screening alone, the PPV for NGS was 70.83%, with 73.91% sensitivity. The three most common IEMs were methylmalonic academia (MMA), primary carnitine deficiency (PCD) and phenylketonuria (PKU). The five genes with the most common carrier frequencies were PAH (1:42), PRODH (1:51), MMACHC (1:52), SLC25A13 (1:55) and SLC22A5 (1:63). Our study showed that NBS combined with NGS and MS/MS improves the performance of screening methods, optimizes the process, and provides accurate diagnoses.

In Situ Synthesis of Self-Assembly Supramolecular Crystal Seeds within Continuous Carbon Nanofibers for Improved Fiber Graphitic Structure.

The utilization of carbon-based fibers as a fundamental constituent holds strong appeal for diverse materials and devices. However, the poor fiber graphitic structure resulting from the heat treatment of atactic polyacrylonitrile (PAN) precursors often leads to a modest performance of carbon-based fibers. This paper takes electrospun carbon nanofibers (CNFs) as the research object and provides a seed-assisted graphitization strategy to improve the fiber graphitic structures. The typical melamine/cyanuric acid self-assembly precursor of graphitic carbon nitride is applied as supramolecular seeds in CNFs and demonstrates significant promotion of fiber graphitization, while it decomposes at elevated temperatures. Further studies show that the higher carbon content contributes to the better heat resistance of seeds; thus, nanoscale 2,6-diaminopyridine/cyanuric acid and 2,4,6-triaminopyrimidine/barbituric acid supramolecular seeds are developed. Both systems can be uniformly distributed in PAN precursors through in situ self-assembly and withstand high-temperature carbonization without severe pyrolysis. The dispersed seeds contribute to the formation of fibrillar PAN crystals and promote their conversion to ordered graphitic domains through nucleation and templating roles. The obtained CNFs exhibit increased crystallinity and graphitization degree with improved orientation and refined size of fiber crystals. As a result, the strength, modulus, and elongation at break of CNFs are comprehensively enhanced.

Bioinspired Touch-Responsive Hydrogels for On-Demand Adhesion on Rough Surfaces.

Reversible adhesives are widely needed in our daily lives and industrial applications. However, robust and switchable adhesion on rough surfaces with on-demand attachment and detachment remains highly challenging. Here, we report a snail-mucus-inspired touch-responsive hydrogel (TRH), whose universal and robust adhesion is triggered by simple contact with the attaching surface. TRH is composed of a polymeric hydrogel and saturated sodium acetate (NaAc) and is prepared by one-pot synthesis. At room temperature, TRH remains in an amorphous and soft state, which allows it to conformally adapt to rough surfaces. The contact with the target surface triggers the crystallization of NaAc, which increases the modulus of TRH by an order of magnitude and interlocks with the target surfaces, achieving an adhesion of up to 204.84 ± 53.98 kPa. Upon heating, TRH returns to a soft state, facilitating easy detachment with adhesion of 5.12 ± 1.34 kPa. Meanwhile, the detached TRH is ready for the next adhesion without the need to be maintained at high temperature. TRH finds applications as a smart material for light-triggered adhesion switching, information encryption, and temperature sensors.

DNA methylation remodeling and the functional implication during male gametogenesis in rice.

BACKGROUND: Epigenetic marks are reprogrammed during sexual reproduction. In flowering plants, DNA methylation is only partially remodeled in the gametes and the zygote. However, the timing and functional significance of the remodeling during plant gametogenesis remain obscure. RESULTS: Here we show that DNA methylation remodeling starts after male meiosis in rice, with non-CG methylation, particularly at CHG sites, being first enhanced in the microspore and subsequently decreased in sperm. Functional analysis of rice CHG methyltransferase genes CMT3a and CMT3b indicates that CMT3a functions as the major CHG methyltransferase in rice meiocyte, while CMT3b is responsible for the increase of CHG methylation in microspore. The function of the two histone demethylases JMJ706 and JMJ707 that remove H3K9me2 may contribute to the decreased CHG methylation in sperm. During male gametogenesis CMT3a mainly silences TE and TE-related genes while CMT3b is required for repression of genes encoding factors involved in transcriptional and translational activities. In addition, CMT3b functions to repress zygotic gene expression in egg and participates in establishing the zygotic epigenome upon fertilization. CONCLUSION: Collectively, the results indicate that DNA methylation is dynamically remodeled during male gametogenesis, distinguish the function of CMT3a and CMT3b in sex cells, and underpin the functional significance of DNA methylation remodeling during rice reproduction.

Generative Adversarial Network Model to Classify Human Induced Pluripotent Stem Cell-Cardiomyocytes based on Maturation Level.

Objective: Our study develops a generative adversarial network (GAN)-based method that generates faithful synthetic image data of human cardiomyocytes at varying stages in their maturation process, as a tool to significantly enhance the classification accuracy of cells and ultimately assist the throughput of computational analysis of cellular structure and functions. Methods: Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) were cultured on micropatterned collagen coated hydrogels of physiological stiffnesses to facilitate maturation and optical measurements were performed for their structural and functional analyses. Control groups were cultured on collagen coated glass well plates. These image recordings were used as the real data to train the GAN model. Results: The results show the GAN approach is able to replicate true features from the real data, and inclusion of such synthetic data significantly improves the classification accuracy compared to usage of only real experimental data that is often limited in scale and diversity. Conclusion: The proposed model outperformed four conventional machine learning algorithms with respect to improved data generalization ability and data classification accuracy by incorporating synthetic data. Significance: This work demonstrates the importance of integrating synthetic data in situations where there are limited sample sizes and thus, effectively addresses the challenges imposed by data availability.

An oncolytic virus delivering tumor-irrelevant bystander T cell epitopes induces anti-tumor immunity and potentiates cancer immunotherapy.

Tumor-specific T cells are crucial in anti-tumor immunity and act as targets for cancer immunotherapies. However, these cells are numerically scarce and functionally exhausted in the tumor microenvironment (TME), leading to inefficacious immunotherapies in most patients with cancer. By contrast, emerging evidence suggested that tumor-irrelevant bystander T (TBYS) cells are abundant and preserve functional memory properties in the TME. To leverage TBYS cells in the TME to eliminate tumor cells, we engineered oncolytic virus (OV) encoding TBYS epitopes (OV-BYTE) to redirect the antigen specificity of tumor cells to pre-existing TBYS cells, leading to effective tumor inhibition in multiple preclinical models. Mechanistically, OV-BYTE induced epitope spreading of tumor antigens to elicit more diverse tumor-specific T cell responses. Remarkably, the OV-BYTE strategy targeting human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cell memory efficiently inhibited tumor progression in a human tumor cell-derived xenograft model, providing important insights into the improvement of cancer immunotherapies in a large population with a history of SARS-CoV-2 infection or coronavirus disease 2019 (COVID-19) vaccination.

The traditional uses, pharmacology, and phytochemistry of Peucedanum praeruptorum Dunn.

Bai Hua Qian Hu (Qianhu; Peucedanum praeruptorum Dunn) is a classical medicinal plant traditionally prescribed for respiratory ailments, including cough, pulmonary hypertension, and asthma. In this review, we summarize the research progress of the toxicology, pharmacokinetics, pharmacology, phytochemistry, botany, quality control, and traditional uses of P. praeruptorum in order to support future investigations into the scientific and therapeutic promise of this important medicinal plant. Information pertaining to P. praeruptorum was collected from scientific databases (ScienceDirect, Springer, SciFinder, PubMed, Baidu Scholar, Google Scholar, Web of Science), as well as toxicology papers from local conferences, M. Sc. and Ph.D. theses and dissertations, local magazines, classic texts on Chinese botanical drugs, and peer-reviewed journals. The Plant List (www.theplantlist.org) was utilized to verify the taxonomy of P. praeruptorum. P. praeruptorum was found to contain more than 119 distinct phytochemicals, including simple coumarins, pyranocoumarins, furanocoumarins, flavonoids, ketones, organic acids, and sterols, among others (e.g., praeruptorins A and B). Both crude plant extracts and purified metabolites of P. praeruptorum have been reported as treatments for hypertension, osteoporosis, Huntington's disease, and cancer. In addition, extracts of P. praeruptorum are reported to exhibit diverse pharmacological activities, including osteogenic, anti-osteoclastogenic, antidepressant, neuroprotective, antitumor, and anti-inflammatory effects. Research into the pharmacology and phytochemistry of P. praeruptorum partially support both traditional uses and extraction methods. However, further research is required to elucidate the relationships between these metabolites, their molecular mechanisms, their structure-function roles, and their antagonistic and synergistic effects.

Circulating T cells: a promising biomarker of anti-PD-(L)1 therapy.

Anti-PD-(L)1 therapy has shown great efficacy in some patients with cancer. However, a significant proportion of patients with cancer do not respond to it. Another unmet clinical need for anti-PD-(L)1 therapy is the dynamic monitoring of treatment effects. Therefore, identifying biomarkers that can stratify potential responders before PD-(L)1 treatment and timely monitoring of the efficacy of PD-(L)1 treatment are crucial in the clinical setting. The identification of biomarkers by liquid biopsy has attracted considerable attention. Among the identified biomarkers, circulating T cells are one of the most promising because of their indispensable contribution to anti-PD-(L)1 therapy. The present review aimed to thoroughly explore the potential of circulating T cells as biomarkers of anti-PD-(L)1 therapy and its advantages and limitations.

Spread of antibiotic resistance genes in drinking water reservoirs: Insights from a deep metagenomic study using a curated database.

The exploration of antibiotic resistance genes (ARGs) in drinking water reservoirs is an emerging field. Using a curated database, we enhanced the ARG detection and conducted a comprehensive analysis using 2.2 Tb of deep metagenomic sequencing data to determine the distribution of ARGs across 16 drinking water reservoirs and associated environments. Our findings reveal a greater diversity of ARGs in sediments than in water, underscoring the importance of extensive background surveys. Crucial ARG carriers-specifically Acinetobacter, Pseudomonas, and Mycobacterium were identified in drinking water reservoirs. Extensive analysis of the data uncovered a considerable concern for drinking water safety, particularly in regions reliant on river sources. Mobile genetic elements have been found to contribute markedly to the propagation of ARGs. The results of this research suggest that the establishment of drinking water reservoirs for supplying raw water may be an effective strategy for alleviating the spread of water-mediated ARGs.

[Simultaneous determination of six benzodiazepine sedatives residue in aquatic products by high performance liquid chromatography-triple quadrupole mass spectrometry].

OBJECTIVE: To establish a method for the simultaneous determination of 6 benzodiazepine sedatives residue in aquatic products by high performance liquid chromatography-triple quadrupole mass spectrometry. METHODS: The samples were extracted with acetonitrile and purified by C_(18 )solid phase extraction column. The sample solution was separated by Waters ACQUITY UPLC BEH C_(18 )column(2.1 mm×50 mm, 1.7 µm) using 0.1% formic acid and methanol as mobile phase for gradient elution, determined in multiple reaction monitoring mode and quantified by internal standard method. RESULTS: Six benzodiazepine sedatives had a good linear relationship in the range of 1.0-50.0 µg/L with r>0.9990, the limits of detection and limits of quantification were 0.3 and 1.0 µg/kg. Average recoveries for the analytes at 3 spiked levels ranged from 74.2%-108.0% with relative standard deviations of 1.1%-6.7%(n=6). CONCLUSION: The method is simple, rapid, sensitive and accurate, which is suitable for simultaneous determination of 6 benzodiazepine sedatives residue in aquatic products.

Methylomonas defluvii sp. nov., a type I methane-oxidizing bacterium from a secondary sedimentation tank of a wastewater treatment plant.

An aerobic methanotroph was isolated from a secondary sedimentation tank of a wastewater treatment plant and designated strain OY6T. Cells of OY6T were Gram-stain-negative, pink-pigmented, motile rods and contained an intracytoplasmic membrane structure typical of type I methanotrophs. OY6T could grow at a pH range of 4.5-7.5 (optimum pH 6.5) and at temperatures ranging from 20 °C to 37 °C (optimum 30 °C). The major cellular fatty acids were C14 : 0, C16 : 1ω7c/C16 : 1ω6c and C16 : 1ω5c; the predominant respiratory quinone was MQ-8. The genome size was 5.41 Mbp with a DNA G+C content of 51.7 mol%. OY6T represents a member of the family Methylococcaceae of the class Gammaproteobacteria and displayed 95.74-99.64 % 16S rRNA gene sequence similarity to the type strains of species of the genus Methylomonas. Whole-genome comparisons based on average nucleotide identity (ANI) and digital DNA-DNA hybridisation (dDDH) confirmed that OY6T should be classified as representing a novel species. The most closely related type strain was Methylomonas fluvii EbBT, with 16S rRNA gene sequence similarity, ANI by blast (ANIb), ANI by MUMmer (ANIm) and dDDH values of 99.64, 90.46, 91.92 and 44.5 %, respectively. OY6T possessed genes encoding both the particulate methane monooxygenase enzyme and the soluble methane monooxygenase enzyme. It grew only on methane or methanol as carbon sources. On the basis of phenotypic, genetic and phylogenetic data, strain OY6T represents a novel species within the genus Methylomonas for which the name Methylomonas defluvii sp. nov. is proposed, with strain OY6T (=GDMCC 1.4114T=KCTC 8159T=LMG 33371T) as the type strain.

Machine learning approach for predicting post-intubation hemodynamic instability (PIHI) index values: towards enhanced perioperative anesthesia quality and safety.

BACKGROUND: Adequate preoperative evaluation of the post-intubation hemodynamic instability (PIHI) is crucial for accurate risk assessment and efficient anesthesia management. However, the incorporation of this evaluation within a predictive framework have been insufficiently addressed and executed. This study aims to developed a machine learning approach for preoperatively and precisely predicting the PIHI index values. METHODS: In this retrospective study, the valid features were collected from 23,305 adult surgical patients at Peking Union Medical College Hospital between 2012 and 2020. Three hemodynamic response sequences including systolic pressure, diastolic pressure and heart rate, were utilized to design the post-intubation hemodynamic instability (PIHI) index by computing the integrated coefficient of variation (ICV) values. Different types of machine learning models were constructed to predict the ICV values, leveraging preoperative patient information and initiatory drug infusion. The models were trained and cross-validated based on balanced data using the SMOTETomek technique, and their performance was evaluated according to the mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and R-squared index (R2). RESULTS: The ICV values were proved to be consistent with the anesthetists' ratings with Spearman correlation coefficient of 0.877 (P < 0.001), affirming its capability to effectively capture the PIHI variations. The extra tree regression model outperformed the other models in predicting the ICV values with the smallest MAE (0.0512, 95% CI: 0.0511-0.0513), RMSE (0.0792, 95% CI: 0.0790-0.0794), and MAPE (0.2086, 95% CI: 0.2077-0.2095) and the largest R2 (0.9047, 95% CI: 0.9043-0.9052). It was found that the features of age and preoperative hemodynamic status were the most important features for accurately predicting the ICV values. CONCLUSIONS: Our results demonstrate the potential of the machine learning approach in predicting PIHI index values, thereby preoperatively informing anesthetists the possible anesthetic risk and enabling the implementation of individualized and precise anesthesia interventions.

A dense matching method for remote sensing images fused with CPS denoising.

Dense matching of remote sensing images is crucial for 3D reconstruction. This study proposes an enhanced dense matching method employing the CPS image denoising algorithm, aiming to boost the SGM algorithm's accuracy and efficiency in remote sensing image matching. The stereo image pair's quality is evaluated using the PSNR index, and a decision-making criterion based on the CPS algorithm is incorporated to determine the need for denoising. Preprocessing steps, including image cropping and pixel coordinate transformation, significantly reduce computational requirements. An epipolar line model, minimizing the disparity between two pixels, is used for calculations. This model is employed to construct an epipolar image, enhancing the accuracy and efficiency of the process. The study conducted experimental validation and analysis of the mismatch rate, running time, and denoising effect of the algorithm using the Middlebury 2021 stereo datasets. Additionally, the matching results of the World-View3 satellite stereo image pairs were visualized and analyzed. The experimental results indicate that the proposed algorithm reduces the average mismatch rate by 13.1% and increases the running speed by about 3 to 4 times compared to the SGBM algorithm. Specifically, the denoising effect reduces the mismatch rate of the reconstructed image by an average of 8.97%. The results indicate that the CPS method effectively addresses dense matching challenges in the presence of image blur and noise, thereby improving the operational efficiency and accuracy of the dense matching algorithm.

Synthetic biology approaches for improving the specificity and efficacy of cancer immunotherapy.

Immunotherapy has shown robust efficacy in treating a broad spectrum of hematological and solid cancers. Despite the transformative impact of immunotherapy on cancer treatment, several outstanding challenges remain. These challenges include on-target off-tumor toxicity, systemic toxicity, and the complexity of achieving potent and sustainable therapeutic efficacy. Synthetic biology has emerged as a promising approach to overcome these obstacles, offering innovative tools for engineering living cells with customized functions. This review provides an overview of the current landscape and future prospects of cancer immunotherapy, particularly emphasizing the role of synthetic biology in augmenting its specificity, controllability, and efficacy. We delineate and discuss two principal synthetic biology strategies: those targeting tumor surface antigens with engineered immune cells and those detecting intratumoral disease signatures with engineered gene circuits. This review concludes with a forward-looking perspective on the enduring challenges in cancer immunotherapy and the potential breakthroughs that synthetic biology may contribute to the field.

A Better Fruit Quality of Grafted Blueberry Than Own-Rooted Blueberry Is Linked to Its Anatomy.

To further clarify the impact of different rootstocks in grafted blueberry, fruit quality, mineral contents, and leaf gas exchange were investigated in 'O'Neal' blueberry (Vaccinium corymbosum) grafted onto 'Anna' (V. corymbosum) (AO), 'Sharpblue' (V. corymbosum) (SO), 'Baldwin' (V. virgatum) (BO), 'Plolific' (V. virgatum) (PO), and 'Tifblue' (V. virgatum) (TO) rootstocks and own-rooted 'O'Neal' (NO), and differences in anatomic structures and drought resistance were determined in AO, TO, and NO. The findings revealed that fruit quality in TO and PO was excellent, that of BO and SO was good, and that of AO and NO was medium. 'Tifblue' and 'Plolific' rootstocks significantly increased the levels of leaf phosphorus and net photosynthetic rate of 'O'Neal', accompanied by a synchronous increase in their transpiration rates, stomatal conductance, and intercellular CO2. Additionally, the comprehensive evaluation scores from a principal component analysis based on anatomic structure traits from high to low were in the order TO > AO > NO. The P50 (xylem water potential at 50% loss of hydraulic conductivity) values of these grafted plants descended in the order NO > AO > TO, and the branch hydraulic conductivity of TO and sapwood hydraulic conductivity of TO and AO were significantly lower than those of NO. Thus, TO plants exhibited the strongest drought resistance, followed by AO, and NO, and this trait was related to the effects of different rootstocks on the fruit quality of 'O'Neal' blueberry. These results provided a basis for a deeper understanding of the interaction between rootstocks and scions, as well mechanisms to improve blueberry fruit quality.

Application of ionic liquid extractant in enhanced separation of 2-propanol-n-hexane azeotrope system.

2-Propanol and n-hexane are widely used (as) chemical reagents in electronic, pharmaceutical, and chemical industries. An efficient separation of the azeotropic system of 2-propanol-n-hexane is of profound practical significance. By using the conductor-like screening model for real solve (COSMO-RS) predictive model, ionic liquids as extractants for separating the azeotropic system of 2-propanol-n-hexane were evaluated with selectivity coefficients (S) and capacity (C) as the evaluation indexes. Based on the evaluation results, one high-performance extractants named hydroxylamine Cl (C8A19) was selected from 435 kinds of ionic liquids designed by combining 29 kinds of anions and 15 kinds of cations. Moreover, the reliability of the model in predicting the vapor-liquid phase equilibrium behavior of 2-propanol-n-hexane system was verified. Then, the effect of C8A19 on the vapor-liquid phase equilibrium of the 2-propanol-n-hexane system was investigated theoretically and experimentally. The results show that the azeotrope of the system can be broken when the molar fraction of C8A19 is 0.02, denoting that C8A19 can be used for enhanced separation of 2-propanol-n-hexane system. On the basis of the aforementioned study, the selectivity mechanism of the extractant was analyzed from the perspective of microscopic molecular interactions by using the descriptor (σ-profiles) of COSMO-RS. This study provides both theoretical and data support for further designing high-performance ionic liquid extractants and extraction process.

Extreme risk spillovers between US and Chinese agricultural futures markets in crises: A dependence-switching copula-CoVaR model.

The linkages between the US and China, the world's two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.

A Whole W-Band Multi-Polarization Horn Antenna Based on Boifot-Type OMT.

A wideband multi-polarized square-horn antenna based on an orthogonal mode transducer (OMT) is developed for working in the whole W-band in this paper. The designed antenna is capable of radiating multiple polarization modes as horizontal polarization (HP) and vertical polarization (VP) when as single-port excitation and left-handed circular polarization (LHCP) and right-handed circular polarization (RHCP) when as dual-port excitation, owing to the characteristic of the OMT with the transmitting of orthogonally polarized waves. A CNC-layered fabrication approach is proposed, which means that the antenna prototype integrating with a Boifot-type OMT, turning waveguide, twisting waveguide and phase shifter is divided into three layers along the vertical direction to be fabricated based on computerized numerical control (CNC) technology. In the design, the turning waveguide and twisting waveguide are employed to achieve plane consistency of the antenna branch ports. Furthermore, a phase shifter is designed to compensate the orthogonally polarized waves, which can keep the phase of the orthogonally polarized waves consistent in a wideband frequency range from 75 GHz to 110 GHz. A prototype is fabricated and measured to verify the performance of the proposed multi-polarization antenna, and the measured results agree well with the simulation ones. In the whole W-band, the value of return loss is better than 10 dB of all polarization modes, and the value of AR of the LHCP and RHCP is below 3.5 dB. The maximum gain of the antenna reaches up to 18.8 dBi at 110 GHz. In addition, regarding the layered structure, the possible layered assembly error analysis is discussed, which verifies the feasibility of the layered machining for this antenna.