Using Dynamic Gas Exchange Measurements During Oxygen Transients to Study Nonsteady-State Photorespiration.

Leaf-level gas exchange is widely used to investigate the largest carbon fluxes in illuminated leaves, offering a nondestructive way to investigate the impact of photorespiration on plant carbon balance. Modern commercial gas exchange systems allow high temporal resolution measurements under changing environments, aiding the development of nonsteady-state approaches for measuring dynamic photosynthetic responses. Here, we describe a nonsteady-state technique for acquiring the dynamic response of net CO2 assimilation to changes in photorespiratory fluxes manipulated by O2 mole fractions. This technique allows for the screening of plant genotypes with variations in their efficiencies of photorespiration under nonsteady-state conditions.

Combining Gas Exchange and Rapid Quenching of Leaf Tissue for Mass Spectrometry Analysis Directly in Gas Exchange Cuvette.

Isotopically nonstationary metabolic flux analysis (INST-MFA) is a powerful technique for studying plant central metabolism, which involves introducing a 13CO2 tracer to plant leaves and sampling the labeled metabolic intermediates during the transient period before reaching an isotopic steady state. The metabolic intermediates involved in the C3 cycle have exceptionally fast turnover rates, with some intermediates turning over many times a second. As a result, it is necessary to rapidly introduce the label and then rapidly quench the plant tissue to determine concentrations in the light or capture the labeling kinetics of these intermediates at early labeling time points. Here, we describe a rapid quenching (0.1-0.5 s) system for 13CO2 labeling experiments in plant leaves to minimize metabolic changes during labeling and quenching experiments. This system is integrated into a commercially available gas exchange analyzer to measure initial rates of gas exchange, precisely control ambient conditions, and monitor the conversion from 12CO2 to 13CO2.

Qualitative study on the perception of good death in patients with end-stage cancer in oncology nurses.

OBJECTIVE: To explore the perception of good death of patients with end-stage cancer by nurses in the oncology department. METHOD: In the study we used a phenomenological approach and semi-structured interviews. A total of 11 nurses from the oncology department of a Grade A hospital in Taizhou were interviewed on the cognition of good death from July 1 to September 30, 2022. Colaizzi's analysis method was used to analyse the interview data. This study followed the consolidated criteria for reporting qualitative research (COREQ). RESULT: Four themes were identified: a strong sense of responsibility and mission; To sustain hope and faith; The important role of family members; Improve patients' quality of life. CONCLUSION: The nurses in the department of oncology have a low level of knowledge about the "good death", and the correct understanding and view of the "good death" is the premise of the realization of " good death". The ability of nursing staff to improve the "good death", attention, and meet the needs and wishes of individuals and families, is the guarantee of the realization of "good death".

An eco-friendly and high-yield extraction of rare earth from the leaching solution of ion adsorbed minerals.

Ion-adsorbed rare earth minerals are rich in medium and heavy rare earth (RE), which are important strategic resources. In this article, a novel approach for the extraction of RE from ion adsorbed minerals was developed. Through a comprehensive assessment of their extraction and separation performance, the hydrophobic deep eutectic solvents (HDES) with a composition of trioctylphosphine oxide (TOPO): dodecanol (LA): 2-thiophenoyltrifluoroacetone (HTTA) = 1:1:1 was determined as the optimal configuration. Under optimized conditions, only RE were extracted by the HDES, while Al, Ca, Mg were not extracted at all. The HDES based extraction obviated the need for diluent such as kerosene, eliminating the generation of impurity removal residues. The RE in the stripping solution could be successfully enriched by saponified lauric acid, achieving an impressive precipitation rate of 99.7%. The RE precipitate underwent further enrichment, resulting in a RE concentration of 176 g/L (REO = 210 g/L). Unlike industrial precipitants such as oxalic acid and ammonium bicarbonate, lauric acid can be effectively recycled, thereby avoiding a large amount of wastewater and carbon dioxide emissions. The obtained RE solution product exhibits high yield and purity, this study provides an eco-friendly and high-yield approach for extracting RE.

Deep learning assists detection of esophageal cancer and precursor lesions in a prospective, randomized controlled study.

Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection rate remains challenging. We developed a system based on deep convolutional neural networks (CNNs) for detecting esophageal cancer and precancerous lesions [high-risk esophageal lesions (HrELs)] and validated its efficacy in improving HrEL detection rate in clinical practice (trial registration ChiCTR2100044126 at www.chictr.org.cn). Between April 2021 and March 2022, 3117 patients ≥50 years old were consecutively recruited from Taizhou Hospital, Zhejiang Province, and randomly assigned 1:1 to an experimental group (CNN-assisted endoscopy) or a control group (unassisted endoscopy) based on block randomization. The primary endpoint was the HrEL detection rate. In the intention-to-treat population, the HrEL detection rate [28 of 1556 (1.8%)] was significantly higher in the experimental group than in the control group [14 of 1561 (0.9%), P = 0.029], and the experimental group detection rate was twice that of the control group. Similar findings were observed between the experimental and control groups [28 of 1524 (1.9%) versus 13 of 1534 (0.9%), respectively; P = 0.021]. The system's sensitivity, specificity, and accuracy for detecting HrELs were 89.7, 98.5, and 98.2%, respectively. No adverse events occurred. The proposed system thus improved HrEL detection rate during endoscopy and was safe. Deep learning assistance may enhance early diagnosis and treatment of esophageal cancer and may become a useful tool for esophageal cancer screening.

Noninvasive twin genotyping for recessive monogenic disorders by relative haplotype dosage.

OBJECTIVE: To establish a haplotype-based noninvasive prenatal testing (NIPT) workflow for single-gene recessive disorders that adapt to dizygotic (DZ) twin pregnancies. METHOD: Twin pregnancies at risk of Duchenne muscular dystrophy, Becker muscular dystrophy, hemophilia B, spinal muscular atrophy, phenylketonuria, and nonsyndromic hearing loss were recruited. For subsequent analysis, capture sequencing targeting highly heterozygotic single nucleotide polymorphism sites was conducted. Paternal-specific alleles were used to calculate the total and individual fetal fractions and determine zygosity. A two-step Bayes Factor model was applied to clarify the complex genomic landscape in the maternal plasma: the first step involved determining whether the twins inherited the same haplotype, and the second step involved estimating their individual genotypes. NIPT results were subsequently confirmed by invasive diagnosis. RESULTS: Nine twin pregnancies were recruited, including five DZ and four monozygotic (MZ) twins. The earliest gestational age was 8+0 weeks, and the minimum fetal fraction was 4.6%. Three twin pregnancies were reported with one affected fetus, while the remaining six were reported without affected fetuses. Two dichorionic diamniotic twin pregnancies were confirmed to be MZ twins. The NIPT results were 100% consistent with those of invasive procedures or diagnostic genetic testing after birth. CONCLUSION: This study is the first to perform NIPT for single-gene disorders in twin pregnancies and preliminarily confirm its clinical feasibility. Acknowledging the twins' genotypes in the first trimester is valuable as it empowers obstetric care providers and parents to have adequate time for pregnancy management and decision-making.

Relationship between the microenvironment and survival in kidney transplantation: a bibliometric analysis from 2013 to 2023.

Background: Kidney transplantation is considered the most effective treatment for end-stage renal failure. Recent studies have shown that the significance of the immune microenvironment after kidney transplantation in determining prognosis of patients. Therefore, this study aimed to conduct a bibliometric analysis to provide an overview of the knowledge structure and research trends regarding the immune microenvironment and survival in kidney transplantation. Methods: Our search included relevant publications from 2013 to 2023 retrieved from the Web of Science core repository and finally included 865 articles. To perform the bibliometric analysis, we utilized tools such as VOSviewer, CiteSpace, and the R package "bibliometrix". The analysis focused on various aspects, including country, author, year, topic, reference, and keyword clustering. Results: Based on the inclusion criteria, a total of 865 articles were found, with a trend of steady increase. China and the United States were the countries with the most publications. Nanjing Medical University was the most productive institution. High-frequency keywords were clustered into 6 areas, including kidney transplantation, transforming growth factor ß, macrophage, antibody-mediated rejection, necrosis factor alpha, and dysfunction. Antibody mediated rejection (2019-2023) was the main area of research in recent years. Conclusion: This groundbreaking bibliometric study comprehensively summarizes the research trends and advances related to the immune microenvironment and survival after kidney transplantation. It identifies recent frontiers of research and highlights promising directions for future studies, potentially offering fresh perspectives to scholars in the field.

3D printed high-precision porous scaffolds prepared by fused deposition modeling induce macrophage polarization to promote bone regeneration.

Macrophage-mediated bone immune responses significantly influence the repair of bone defects when utilizing tissue-engineered scaffolds. Notably, the scaffolds' physical structure critically impacts macrophage polarization. The optimal pore size for facilitating bone repair remains a topic of debate due to the imprecision of traditional methods in controlling scaffold pore dimensions and spatial architecture. In this investigation, we utilized fused deposition modeling (FDM) technology to fabricate high-precision porous polycaprolactone (PCL) scaffolds, aiming to elucidate the impact of pore size on macrophage polarization. We assessed the scaffolds' mechanical attributes and biocompatibility. Real-time quantitative reverse transcription polymerase chain reaction was used to detect the expression levels of macrophage-related genes, and enzyme linked immunosorbent assay for cytokine secretion levels.In vitroosteogenic capacity was determined through alkaline phosphatase and alizarin red staining. Our findings indicated that macroporous scaffolds enhanced macrophage adhesion and drove their differentiation towards the M2 phenotype. This led to the increased production of anti-inflammatory factors and a reduction in pro-inflammatory agents, highlighting the scaffolds' immunomodulatory capabilities. Moreover, conditioned media from macrophages cultured on these macroporous scaffolds bolstered the osteogenic differentiation of bone marrow mesenchymal stem cells, exhibiting superior osteogenic differentiation potential. Consequently, FDM-fabricated PCL scaffolds, with precision-controlled pore sizes, present promising prospects as superior materials for bone tissue engineering, leveraging the regulation of macrophage polarization.

The role of surface functionalization in quantum dot-based photocatalytic CO2 reduction: balancing efficiency and stability.

Photocatalytic CO2 reduction offers a promising strategy to produce hydrocarbons without reliance on fossil fuels. Visible light-absorbing colloidal nanomaterials composed of earth-abundant metals suspended in aqueous media are particularly attractive owing to their low-cost, ease of separation, and highly modifiable surfaces. The current study explores such a system by employing water-soluble ZnSe quantum dots and a Co-based molecular catalyst. Water solubilization of the quantum dots is achieved with either carboxylate (3-mercaptopropionic acid) or ammonium (2-aminoethanethiol) functionalized ligands to produce nanoparticles with either negatively or positively-charged surfaces. Photocatalysis experiments are performed to compare the effectiveness of these two surface functionalization strategies on CO2 reduction and ultrafast spectroscopy is used to reveal the underlying photoexcited charge dynamics. We find that the positively-charged quantum dots can support sub-picosecond electron transfer to the carboxylate-based molecular catalyst and also produce >30% selectivity for CO and >170 mmolCO gZnSe-1. However, aggregation reduces activity in approximately one day. In contrast, the negatively-charged quantum dots exhibit >10 ps electron transfer and substantially lower CO selectivity, but they are colloidally stable for days. These results highlight the importance of the quantum dot-catalyst interaction for CO2 reduction. Furthermore, multi-dentate catalyst molecules create a trade-off between photocatalytic efficiency from strong interactions and deleterious aggregation of quantum dot-catalyst assemblies.

Crosstalk of HDAC4, PP1, and GSDMD in controlling pyroptosis.

Gasdermin D (GSDMD) functions as a pivotal executor of pyroptosis, eliciting cytokine secretion following cleavage by inflammatory caspases. However, the role of posttranslational modifications (PTMs) in GSDMD-mediated pyroptosis remains largely unexplored. In this study, we demonstrate that GSDMD can undergo acetylation at the Lysine 248 residue, and this acetylation enhances pyroptosis. We identify histone deacetylase 4 (HDAC4) as the specific deacetylase responsible for mediating GSDMD deacetylation, leading to the inhibition of pyroptosis both in vitro and in vivo. Deacetylation of GSDMD impairs its ubiquitination, resulting in the inhibition of pyroptosis. Intriguingly, phosphorylation of HDAC4 emerges as a critical regulatory mechanism promoting its ability to deacetylate GSDMD and suppress GSDMD-mediated pyroptosis. Additionally, we implicate Protein phosphatase 1 (PP1) catalytic subunits (PP1α and PP1γ) in the dephosphorylation of HDAC4, thereby nullifying its deacetylase activity on GSDMD. This study reveals a complex regulatory network involving HDAC4, PP1, and GSDMD. These findings provide valuable insights into the interplay among acetylation, ubiquitination, and phosphorylation in the regulation of pyroptosis, offering potential targets for further investigation in the field of inflammatory cell death.

First-trimester noninvasive prenatal diagnosis of seven facioscapulohumeral muscular dystrophy type 1 families using SNP-based amplicon sequencing: An earlier, rapid and safer way.

The study is to explore the feasibility and value of SNP-based noninvasive prenatal diagnosis (NIPD) for facioscapulohumeral muscular dystrophy type 1 (FSHD1) in early pregnancy weeks. We prospectively collected seven FSHD1 families, with an average gestational age of 8+6. Among these seven couples, there were three affected FSHD1 mothers and four affected fathers. A multiplex-PCR panel comprising 402 amplicons was designed to selective enrich for highly heterozygous SNPs upstream of the DUX4 gene. Risk haplotype was constructed based on familial linkage analysis. Fetal genotypes were accurately inferred through relative haplotype dosage analysis using Bayes Factor. All tests were successfully completed in a single attempt, and no recombination events were detected. NIPD results were provided within a week, which is 4 weeks earlier than karyomapping and 7 weeks earlier than Bionano single-molecule optical mapping (BOM). Ultimately, five FSHD1 fetuses and two normal fetuses were successfully identified, with a 100% concordance rate with karyomapping and BOM. Therefore, SNP-based NIPD for FSHD1 was demonstrated to be feasible and accurate in early weeks of gestation, although the risk of recombination events cannot be completely eliminated. In the future, testing of more cases is still necessary to fully determine the clinical utility.

Developing a Prognostic Model for Primary Biliary Cholangitis Based on a Random Survival Forest Model.

Background: Primary biliary cholangitis (PBC) is a rare autoimmune liver disease with few effective treatments and a poor prognosis, and its incidence is on the rise. There is an urgent need for more targeted treatment strategies to accurately identify high-risk patients. The use of stochastic survival forest models in machine learning is an innovative approach to constructing a prognostic model for PBC that can improve the prognosis by identifying high-risk patients for targeted treatment. Method: Based on the inclusion and exclusion criteria, the clinical data and follow-up data of patients diagnosed with PBC-associated cirrhosis between January 2011 and December 2021 at Taizhou Hospital of Zhejiang Province were retrospectively collected and analyzed. Data analyses and random survival forest model construction were based on the R language. Result: Through a Cox univariate regression analysis of 90 included samples and 46 variables, 17 variables with p-values <0.1 were selected for initial model construction. The out-of-bag (OOB) performance error was 0.2094, and K-fold cross-validation yielded an internal validation C-index of 0.8182. Through model selection, cholinesterase, bile acid, the white blood cell count, total bilirubin, and albumin were chosen for the final predictive model, with a final OOB performance error of 0.2002 and C-index of 0.7805. Using the final model, patients were stratified into high- and low-risk groups, which showed significant differences with a P value <0.0001. The area under the curve was used to evaluate the predictive ability for patients in the first, third, and fifth years, with respective results of 0.9595, 0.8898, and 0.9088. Conclusion: The present study constructed a prognostic model for PBC-associated cirrhosis patients using a random survival forest model, which accurately stratified patients into low- and high-risk groups. Treatment strategies can thus be more targeted, leading to improved outcomes for high-risk patients.

Anoikis-related signature identifies tumor microenvironment landscape and predicts prognosis and drug sensitivity in colorectal cancer.

Background: Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports on the impact of anoikis on colorectal cancer. Method: A clustering analysis was done on 133 anoikis-related genes in GSE39582, and we compared clinical features between clusters, the tumor microenvironment was analyzed with algorithms such as "Cibersort" and "ssGSEA". We investigated risk scores of clinical feature groups and anoikis-associated gene mutations after creating a predictive model. We incorporated clinical traits to build a nomogram. Additionally, the quantitative real-time PCR was employed to investigate the mRNA expression of selected anoikis-associated genes. Result: We identified two anoikis-related clusters with distinct prognoses, clinical characteristics, and biological functions. One of the clusters was associated with anoikis resistance, which activated multiple pathways encouraging tumor metastasis. In our prognostic model, oxaliplatin may be a sensitive drug for low-risk patients. The nomogram showed good ability to predict survival time. And SIRT3, PIK3CA, ITGA3, DAPK1, and CASP3 increased in CRC group through the PCR assay. Conclusion: Our study identified two distinct modes of anoikis in colorectal cancer, with active metastasis-promoting pathways inducing an anti-anoikis subtype, which has a stronger propensity for metastasis and a worse prognosis than an anoikis-activated subtype. Massive immune cell infiltration may be an indicator of anoikis resistance. Anoikis' role in the colorectal cancer remains to be investigated.

MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural Networks.

Heterogeneous graph neural networks (HGNNs) were proposed for representation learning on structural data with multiple types of nodes and edges. To deal with the performance degradation issue when HGNNs become deep, researchers combine metapaths into HGNNs to associate nodes closely related in semantics but far apart in the graph. However, existing metapath-based models suffer from either information loss or high computation costs. To address these problems, we present a novel Metapath Context Convolution-based Heterogeneous Graph Neural Network (MECCH). MECCH leverages metapath contexts, a new kind of graph structure that facilitates lossless node information aggregation while avoiding any redundancy. Specifically, MECCH applies three novel components after feature preprocessing to extract comprehensive information from the input graph efficiently: (1) metapath context construction, (2) metapath context encoder, and (3) convolutional metapath fusion. Experiments on five real-world heterogeneous graph datasets for node classification and link prediction show that MECCH achieves superior prediction accuracy compared with state-of-the-art baselines with improved computational efficiency. The code is available at https://github.com/cynricfu/MECCH.

Exploring factors impacting haplotype-based noninvasive prenatal diagnosis for single-gene recessive disorders.

Haplotype-based noninvasive prenatal diagnosis (NIPD) is applicable for various recessive single-gene disorders in proband families. However, a comprehensive exploration of critical factors influencing the assay performance, such as fetal fraction, informative single nucleotide polymorphism (SNP) count, and recombination events, has yet to be performed. It is critical to identify key factors affecting NIPD performance, including its accuracy and success rate, and their impact on clinical diagnostics to guide clinical practice. We conducted a prospective study, recruiting 219 proband families with singleton pregnancies at risk for eight recessive single-gene disorders (Duchenne muscular dystrophy, spinal muscular atrophy, phenylketonuria, methylmalonic acidemia, hemophilia A, hemophilia B, non-syndromic hearing loss, and congenital adrenal hyperplasia) at 7-14 weeks of gestation. Haplotype-based NIPD was performed by evaluating the relative haplotype dosage (RHDO) in maternal circulation, and the results were validated via invasive prenatal diagnosis or newborn follow-ups. Among the 219 families, the median gestational age at first blood draw was 8+5 weeks. Initial testing succeeded for 190 families and failed for 29 due to low fetal fraction (16), insufficient informative SNPs (9), and homologous recombination near pathogenic variation (4). Among low fetal fraction families, successful testing was achieved for 11 cases after a redraw, while 5 remained inconclusive. Test failures linked to insufficient informative SNPs correlated with linkage disequilibrium near the genes, with F8 and MMUT exhibiting the highest associated failure rates (14.3% and 25%, respectively). Homologous recombination was relatively frequent around the DMD and SMN1 genes (8.8% and 4.8%, respectively) but led to detection failure in only 44.4% (4/9) of such cases. All NIPD results from the 201 successful families were consistent with invasive diagnostic findings or newborn follow-up. Fetal fraction, informative SNPs count, and homologous recombination are pivotal to NIPD performance. Redrawing blood effectively improves the success rate for low fetal fraction samples. However, informative SNPs count and homologous recombination rates vary significantly across genes, necessitating careful consideration in clinical practice. We have designed an in silico method based on linkage disequilibrium data to predict the number of informative SNPs. This can identify genomic regions where there might be an insufficient number of SNPs, thereby guiding panel design. With these factors properly accounted for, NIPD is highly accurate and reliable.

Multiple Energy Transfer Channels in Rare Earth Doped Multi-Exciton Emissive Perovskites.

Revealing the energy transfer (ET) process from excitons to rare earth ions in halide perovskites has great guiding value for designing optoelectronic materials. Here, the multiple ET channels in multi-exciton emissive Sb3+ /Nd3+ co-doped Cs2 ZrCl6 are explored to comprehend the ET processes. Förster-Dexter ET theory reveals that the sensitizer concentration rather than the overlap integral of the spectra plays the leading function in the comparison of the ET efficiency among multiple ET channels from the host self-trapped excitons (STEs) and dopant triplet STEs to Nd3+ ions. Besides, Sb3+ /Nd3+ co-doped Cs2 ZrCl6 enables varied color delivery and has great potential as anti-counterfeiting material. Under X-ray irradiation, Sb3+ /Nd3+ co-doped Cs2 ZrCl6 presents a high light yield of ≈13300 photons MeV-1 and promising X-ray imaging ability. This work provides new insight for investigating the ET efficiency among multiple ET processes and presents great potentiality of multi-exciton emissive perovskites in the fields of anti-counterfeiting and X-ray imaging.

Mechanistic insights into aniline-induced liver injury: Role of the mmu_circ_26984/Myh9/NLRP3 axis and modulation by N-acetylcysteine.

Aniline is a widely used chemical. Chronic or high-dose exposure to aniline can lead to hepatocellular damage. Although the hepatic pathogenicity of aniline has been established in previous studies, studies involving pathogenic genes during aniline-induced liver injury are limited. Our study first discovered and identified the role and mechanism underlying a new circRNA mmu_circ_26984 in aniline-induced chemical liver injury. Further, we discuss the protective effect of N-acetylcysteine (NAC) in this pathway. After constructing in vitro and in vivo models of aniline treatment, we screened the circRNA with significant differences in expression in AML12 cells from control and aniline-treated groups by circRNA microarray analysis. Next, using RNA pulldown, liquid chromatography-mass spectrometry (LC-MS), and RNA immunoprecipitation, we analyzed the relationship between mmu_circ_26984 and myosin heavy chain 9 (Myh9). Subsequently, we determined the specific mechanism of action of mmu_circ_26984 and Myh9 in aniline-induced liver injury and the protective effect of NAC against aniline-induced liver injury process using Cell Counting Kit-8, Western blot, RNA extraction, a reverse transcription quantitative polymerase chain reaction (RT-qPCR), fluorescence in situ hybridization, immunohistochemistry, and immunofluorescence. The expression of mmu_circ_26984 was significantly increased in liver tissues and AML12 cells of aniline-treated mice compared with the control group. This high expression of mmu_circ_26984 increased the expression of injury-related inflammatory factors, such as NLRP3, Caspase-1, IL-18, and IL-1ß in vivo and ex vivo, which exacerbated the level of liver injury. The interaction of mmu_circ_26984 with Myh9 also affected the course of liver injury. Mmu_circ_26984 overexpression and reduced treatment affected the levels of Myh9 expression in AML12 cells, as well as downstream inflammatory factors associated with injury, such as NLRP3. In addition, NAC reduced the process of liver injury mediated by the mmu_circ_26984/Myh9/NLRP3 axis. In conclusion, mmu_circ_26984 is a potential molecular marker and therapeutic target in the process of aniline-induced liver injury that can mediate aniline-exposure-induced liver injury via modulation of the mmu_circ_26984/Myh9/NLRP3 axis, and NAC can effectively attenuate the effect of this liver injury.

Haplotype-based noninvasive prenatal diagnosis of methylmalonic acidemia and the discovery of a recurrent pathogenic haplotype associated with c.609G>A.

BACKGROUND: Early diagnosis and intervention are crucial for the prognosis of methylmalonic acidemia (MMA). However, research focused on early prenatal diagnosis of MMA is limited. METHODS: A 161.89kb capture panel was designed for selectively enriching highly heterozygous SNPs. Fetal genotypes were inferred using relative haplotype dosage (RHDO) and Bayes factor, followed by invasive prenatal diagnosis (IPD) for validation. A core pathogenic haplotype associated with c.609G>A was identified based on the frequency differences between pathogenic and normal haplotypes. RESULTS: We recruited 41 pregnancies at risk of MMA with a median gestational age of 8+2  weeks. The assay success rate of NIPD-MMA for maternal variants was 92.7% (38/41), and after incorporating the paternal result, the overall assay success rate reached 100% (41/41). All NIPD results were concordant with IPD. Notably, a core haplotype (hap_2), comprising 28 SNPs, demonstrates significant enrichment within pathogenic haplotypes bearing the c.609G>A variation. On average, c.609G>A carriers had 22.38 heterozygous loci within these 28 SNPs. CONCLUSION: NIPD-MMA presents a viable choice for early, accurate, and safe prenatal diagnosis. Furthermore, the discovery of the recurrent core pathogenic haplotype provides a novel approach for haplotype phasing and has the potential for realizing proband-independent NIPD in the future.

Methodological and reporting quality of systematic reviews on health effects of air pollutants were higher than extreme temperatures: a comparative study.

BACKGROUND: An increasing number of systematic reviews (SRs) in the environmental field have been published in recent years as a result of the global concern about the health impacts of air pollution and temperature. However, no study has assessed and compared the methodological and reporting quality of SRs on the health effects of air pollutants and extreme temperatures. This study aims to assess and compare the methodological and reporting quality of SRs on the health effects of ambient air pollutants and extreme temperatures. METHODS: PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, and Epistemonikos databases were searched. Two researchers screened the literature and extracted information independently. The methodological quality of the SRs was assessed through A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2). The reporting quality was assessed through Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA). RESULTS: We identified 405 SRs (286 for air pollution, 108 for temperature, and 11 for the synergistic effects). The methodological and reporting quality of the included SRs were suboptimal, with major deficiencies in protocol registration. The methodological quality of SRs of air pollutants was better than that of temperature, especially in terms of satisfactory explanations for any heterogeneity (69.6% v. 45.4%). The reporting quality of SRs of air pollution was better than temperature, however, adherence to the reporting of the assessment results of risk of bias in all SRs (53.5% v. 34.3%) was inadequate. CONCLUSIONS: Methodological and reporting quality of SRs on the health effect of air pollutants were higher than those of temperatures. However, deficiencies in protocol registration and the assessment of risk of bias remain an issue for both pollutants and temperatures. In addition, developing a risk-of-bias assessment tool applicable to the temperature field may improve the quality of SRs.

Study on the metabolic process of phthalic acid driven proliferation of Rhizoctonia solani.

Introduction: Continuous cropping obstacle seriously affects the quality and yield of Salvia miltiorrhiza, and the synergistic effect of root exudates and rhizosphere pathogenic microorganisms may be an important cause of continuous cropping obstacle. This study aimed to explore the effects of representative organic acids on the growth and metabolism of specific microorganisms in the S. miltiorrhiza rhizosphere soil under continuous cropping, and clarify its mechanism. Methods: The effect of phthalic acid (PA) on the growth and metabolism of Rhizoctonia solani was evaluated by mycelial growth inhibition method. Ultra-high performance liquid chromatography and tandem mass spectrometry were used to identify the differential metabolites of R. solani induced by exogenous PA. Results: PA exerted a concentration-dependent effect on mycelial growth, biomass, intracellular polysaccharides con-tent, and total protein content in R. solani. A total of 1773 metabolites and 1040 differential metabolites were identified in the blank medium (CK), Fungi (CK + fungi), and PA-Fungi (CK + fungi + acid) groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the differential metabolites were mainly involved in the sugar, lipid, and protein metabolic pathways related to stable membrane structure and cell growth. Discussion: The proliferation and metabolism network of R. solani induced by PA was proposed, and the enhancement of sugar, lipid, and amino acid metabolism was presumed to be related to the active resistance of cells to organic acid stress. These results offer new in-sights into the effects of PA metabolism on promoting R. solani proliferation, and provide theoretical support for further optimizing the rhizosphere microecological environment of Salvia miltiorrhiza continuous cropping soil and reducing continuous cropping obstacle.