Increasing 1,4-Diaminobutane Production in Escherichia coli by Optimization of Cofactor PLP and NADPH Synthesis.

1,4-diaminobutane is widely used in the industrial production of polymers, pharmaceuticals, agrochemicals and surfactants. Owing to economic and environmental concerns, there has been a growing interest in using microbes to produce 1,4-diaminobutane. However, there is lack of research on the influence of cofactors pyridoxal phosphate (PLP) and NADPH on the synthesis of 1,4-diaminobutane. PLP serves as a cofactor of ornithine decarboxylase in the synthesis of 1,4-diaminobutane. Additionally, the synthesis of 1 mol 1,4-diaminobutane requires 2 mol NADPH, thus necessitating consideration of NADPH balance in the efficient synthesis of 1,4-diaminobutane by Escherichia coli. The aim of this study was to enhance the synthesis efficiency of 1,4-diaminobutane through increasing production of PLP and NADPH. By optimizing the expression of the genes associated with synthesis of PLP and NADPH in E. coli, cellular PLP and NADPH levels increased, and the yield of 1,4-diaminobutane also increased accordingly. Ultimately, using glucose as the primary carbon source, the yield of 1,4-diaminobutane in the recombinant strain NAP19 reached 272 mg/L·DCW, by increased 79% compared with its chassis strain.

Development and validation of gestational diabetes mellitus health literacy scale.

OBJECTIVE: While there are various health literacy scales that exist, none of health literacy scale suitable for pregnant women with gestational diabetes mellitus (GDM). To address this gap, this study aimed to develop GDM health literacy scale and evaluate its psychometric properties. METHODS: Based on the Delphi expert consultation, we developed the initial GDM health literacy scale. Item analysis was taken using a sample (n = 299) recruited in China to form formal scale. Additional participants (n = 395) completed survey to assess the internal consistency reliability, test-retest reliability, content validity, construct validity and criterion correlation validity of scale. RESULTS: The scale performed well in terms of internal consistency reliability, content validity, construct validity and criterion correlation validity. Test-retest reliability indicated that the instrument was effective at measuring health literacy of GDM over time. CONCLUSION: The scale is a reliable and valid measure of six domains of health literacy for GDM. PRACTICE IMPLICATIONS: The scale can be used to effectively evaluate the level of health literacy of pregnant women with GDM. The information can provide targeted health support for pregnant women with GDM to improve their health literacy and self-management ability.

Effects of Natural Sound Therapy on Pain and Agitation Induced by Endotracheal Suctioning: A Real-World Study.

BACKGROUND: Music therapy has been used as a complementary intervention to provide synergistic analgesia for various procedures. OBJECTIVE: To evaluate the effects of natural sound therapy on pain intensity and agitation scores in intubated adult Chinese patients who received endotracheal suctioning in a critical care unit. METHODS: A prospective, real-world, randomized, double-blind, controlled study was conducted from July 2021 through February 2022 among intubated surgical intensive care unit patients in a Chinese hospital. Patients were randomly assigned to a control group receiving conventional treatment or an intervention group receiving natural sound therapy plus conventional treatment (50 patients in each group). Patients' pain intensity and agitation levels were analyzed before, during, immediately after, 5 minutes after, and 15 minutes after completion of endotracheal suctioning. Pain intensity was assessed with the Critical-Care Pain Observation Tool (CPOT); agitation was assessed with the Richmond Agitation-Sedation Scale (RASS). RESULTS: According to CPOT scores, patients in the intervention group had significant relief of pain intensity during, immediately after, and 5 minutes after endotracheal suctioning compared with patients in the control group (all P < .001). The RASS scores showed that agitation levels were significant lower in the intervention group than in the control group during (P = .002) and immediately after (P < .001) endotracheal suctioning. CONCLUSIONS: In this real-world study, natural sound therapy was part of a holistic bundle of interventions used to reduce pain and agitation in surgical intensive care unit patients during endotracheal suctioning.

Clinicopathologic Characteristics of MYC Copy Number Amplification in Breast Cancer.

Introduction. MYC overexpression is a known phenomenon in breast cancer. This study investigates the correlation of MYC gene copy number amplification and MYC protein overexpression with coexisting genetic abnormalities and associated clinicopathologic features in breast cancer patients. Methods. The study analyzed data from 81 patients with localized or metastatic breast cancers using targeted next-generation sequencing and MYC immunohistochemical studies, along with pathological and clinical data. Results. Applying the criteria of MYC/chromosome 8 ratio ≥5, MYC copy number amplified tumors (n = 11, 14%) were associated with invasive ductal carcinoma (91% vs 68%, P = .048), poorly differentiated (grade 3, 64% vs 30%, P = .032), mitotically active (Nottingham mitotic score 3, 71% vs 20%, P = .004), estrogen receptor (ER)-negative (45% vs 12%, P = .008), and triple-negative (56% vs 12%, P = .013) compared to MYC non-amplified tumors. Among MYC-amplified breast cancer patients, those with triple-negative status showed significantly shorter disease-free survival time than non-triple negative MYC-amplified patients (median survival month: 25.5 vs 127.6, P = .049). MYC amplification is significantly associated with TP53 mutation (P = .007). The majority (10 of 11; 91%) of MYC-amplified tumors showed positive c-MYC immunostaining. Conclusion. Breast cancers with MYC copy number amplication display distinct clinicopathologic characteristics indicative of more aggressive behavior.

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders.

Clinical studies have proved that both structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) are implicitly associated with neuropsychiatric disorders (NDs), and integrating multi-modal to the binary classification of NDs has been thoroughly explored. However, accurately classifying multiple classes of NDs remains a challenge due to the complexity of disease subclass. In our study, we develop a heterogeneous neural network (H-Net) that integrates sMRI and fMRI modes for classifying multi-class NDs. To account for the differences between the two modes, H-Net adopts a heterogeneous neural network strategy to extract information from each mode. Specifically, H-Net includes an multi-layer perceptron based (MLP-based) encoder, a graph attention network based (GAT-based) encoder, and a cross-modality transformer block. The MLP-based and GAT-based encoders extract semantic features from sMRI and features from fMRI, respectively, while the cross-modality transformer block models the attention of two types of features. In H-Net, the proposed MLP-mixer block and cross-modality alignment are powerful tools for improving the multi-classification performance of NDs. H-Net is validate on the public dataset (CNP), where H-Net achieves 90% classification accuracy in diagnosing multi-class NDs. Furthermore, we demonstrate the complementarity of the two MRI modalities in improving the identification of multi-class NDs. Both visual and statistical analyses show the differences between ND subclasses.

Reevaluation of ovarian cyst fine-needle aspiration cytology: A 10-year institutional experience.

OBJECTIVES: Fine-needle aspiration (FNA) of ovarian cyst fluid remains useful for certain clinical circumstances despite low sensitivity and potential safety concerns. The current study aimed to reevaluate the performance of ovarian cystic fluid cytology following American College of Obstetricians and Gynecologists guidelines using a single-institution cohort. METHODS: A total of 507 ovarian cyst FNA cases from 2013 to 2023 were reviewed. Patients' demographics and clinical and radiologic information were collected through the electronic database. The performance was calculated using corresponding surgical pathology diagnosis as the gold standard. RESULTS: Overall, cytologic diagnoses were nondiagnostic (ND), negative for malignancy (NFM), atypical (ATY), suspicious for malignancy (SFM), and malignant (M) in 5 (1.0%), 478 (94.3%), 14 (2.7%), 2 (0.4%), and 8 (1.6%) cases, respectively. Among 349 specimens (68.8%) that had a corresponding surgical pathology, the rate of malignancy (including borderline tumors) was 1.2% (4 of 325) in NFM, 72.7% in ATY (8 of 11), and 100% in both SFM (2 of 2) and M (8 of 8) specimens. Considering NFM and ATY as negative results and SFM and M as positive results, overall, the sensitivity of ovarian cystic fluid cytology was 45.4% and the specificity was 100%. CONCLUSIONS: As an uncommon test, ovarian cystic fluid cytology has moderate sensitivity and high specificity. Despite limitations, ovarian cystic FNA cytology remains a valuable diagnostic tool in certain aspects.

Hierarchical Micro- and Mesoporous Zeolitic Imidazolate Framework-8-Based Enzyme Hybrid for Combination Antimicrobial by Lysozyme and Lactoferrin.

Pathogenic bacteria have consistently posed a formidable challenge to human health, creating the critical need for effective antibacterial solutions. In response, enzyme-metal-organic framework (MOF) composites have emerged as a promising class of antibacterial agents. This study focuses on the development of an enzyme-MOF composite based on HZIF-8, incorporating the advantages of simple synthesis, ZIF-8 antibacterial properties, lysozyme hydrolysis, and high biological safety. Through a one-pot method, core-shell nanoparticles (HZIF-8) were synthesized. This structure enables efficient immobilization of lysozyme and lactoferrin within the HZIF-8, resulting in the formation of the lysozyme-lactoferrin@HZIF-8 (LYZ-LF@HZIF-8) composite. Upon exposure to light irradiation, HZIF-8 itself possessed antibacterial properties. Lysozyme initiated the degradation of bacterial peptidoglycan and lactoferrin synergistically enhanced the antibacterial effect of lysozyme. All of the above ultimately contributed to comprehensive antibacterial activity. Antibacterial assessments demonstrated the efficacy of the LYZ-LF@HZIF-8 composite, effectively eradicating Staphylococcus aureus at a cell density of 1.5 × 106 CFU/mL with a low dosage of 200 µg/mL and completely inactivating Escherichia coli at 400 µg/mL with the same cell density. The enzyme-MOF composite exhibited significant and durable antibacterial efficacy, with no apparent cytotoxicity in vitro, thereby unveiling expansive prospects for applications in the medical and food industries.

Environmental fate of microplastics in high-altitude basins: the insights into the Yarlung Tsangpo River Basin.

Microplastics (MPs) have been found in remote high-altitude areas, but the main source and migration process remained unclear. This work explored the characteristics and potential sources of MPs in the Yarlung Tsangpo River Basin. The average abundances of MPs in water, sediment, and soil samples were 728.26 ± 100.53 items/m3, 43.16 ± 5.82 items/kg, and 61.92 ± 4.29 items/kg, respectively, with polypropylene and polyethylene as the main polymers. The conditional fragmentation model revealed that the major source of MPs lower than 4000 m was human activities, while that of higher than 4500 m was atmospheric deposition. Community analysis was further conducted to explore the migration process and key points of MPs among different compartments in the basin. It was found that Lhasa (3600 m) and Shigatse (4100 m) were vital sources of MPs inputs in the midstream and downstream, respectively. This work would provide new insights into the fate of MPs in high-altitude areas.

[Application and prospects of hyperspectral remote sensing in monitoring plant diversity in grassland]. / é«˜å ‰è°±é¥æ„Ÿåœ¨è‰åŽŸæ¤ç‰©å¤šæ ·æ€§ç›‘æµ‹ä¸­çš„åº”ç”¨ä¸Žå±•æœ›.

The biodiversity of grasslands is important for ecosystem function and health. The protection and mana-gement of grassland biodiversity requires the collection of the information on plant diversity. Hyperspectral remote sensing, with its unique advantages of extensive coverage and high spectral resolution, offers a new solution for long-term monitoring of plant diversity. We first reviewed the development history of hyperspectral remote sensing technology, emphasized its advantages in monitoring grassland plant diversity, and further analyzed its specific applications in this field. Finally, we discussed the challenges faced by hyperspectral remote sensing technology in its applications, such as the complexity of data processing, accuracy of algorithms, and integration with ground-based remote sensing data, and proposes prospects for future research directions. With the advancement of remote sensing technology and the integrated application of multi-source data, hyperspectral remote sensing would play an increasingly important role in grassland ecological monitoring and biodiversity conservation, which could provide scientific basis and technical support for global ecological protection and sustainable development.

Targetable ERBB2/HER2 Mutations in Gynecologic Malignancies: Clinicopathological, Immunohistochemical, and Molecular Correlations.

Targeted anti-HER2 therapy has been recently added to the standard treatment recommendations in endometrial serous carcinoma. Current eligibility requires testing for HER2 overexpression and/or gene amplification by immunohistochemistry and by fluorescence in situ hybridization. However, clinical trials have also demonstrated the efficacy of anti-HER2 drugs against activating ERBB2/HER2 mutations in a variety of solid tumor types, and fam-trastuzumab deruxtecan is now approved by the US Food and Drug Administration for HER2-mutant non-small cell lung cancer. This study aimed at evaluating the detailed clinical, histomorphological, immunohistochemical, and molecular characteristics of gynecologic malignancies with ERBB2/HER2 mutations. We identified 16 tumors with 19 ERBB2/HER2 mutations in our departmental archives: 11 endometrial primaries, 2 endocervical adenocarcinomas, 1 ovarian mucinous adenocarcinoma, 1 tubo-ovarian undifferentiated carcinoma, and 1 high-grade endometrioid adenocarcinoma of Mullerian origin. ERBB2/HER2 mutations most often involved the tyrosine kinase domain (52.6%), and the most frequent specific mutation was R678Q (31.6%), involving the juxtamembrane domain. More than half (54.5%) of endometrial carcinomas and half of all tumors were MMR-deficient, resulting from MSH6 loss in all but 2 tumors. None of the tumors (0%) were POLE-mutated, while 18.8% were TP53-mutated. HER2 IHC was negative (score 0 or 1+) in 12 tumors (67%) and equivocal (score 2+) in 4 tumors (33%), whereas none of the tumors were scored as HER2 3+. Score 2+ was associated with R678Q, L755S, I767M mutations, and ERBB2/HER2 rearrangement with a breakpoint in exon 23. Concurrent ERBB2/HER2 amplification was identified in 2 endometrial carcinomas, with HER2/CEP17 ratios of 3.1 and 3.5. We also queried the cBioportal database, which revealed 70 ERBB2/HER2-mutant gynecologic tumors with a total of 77 ERBB2/HER2 mutations, most often involving the active site of the tyrosine kinase domain (n=36; 46.8%), and the most common specific mutation was S310F (n=20; 26%), located in the extracellular domain. Our results provide important details regarding the clinicopathological and molecular associations of potentially actionable ERBB2/HER2 mutations in endometrial carcinoma and other gynecological cancer types and contribute to addressing clinical treatment needs and improving pathology testing recommendations in the future.

Mechanism of antibiotic resistance spread during sub-lethal ozonation of antibiotic-resistant bacteria with different resistance targets.

The increase and spread of antibiotic-resistant bacteria (ARB) in aquatic environments and the dissemination of antibiotic resistance genes (ARGs) greatly impact environmental and human health. It is necessary to understand the mechanism of action of ARB and ARGs to formulate measures to solve this problem. This study aimed to determine the mechanism of antibiotic resistance spread during sub-lethal ozonation of ARB with different antibiotic resistance targets, including proteins, cell walls, and cell membranes. ARB conjugation and transformation frequencies increased after exposure to 0-1.0 mg/L ozone for 10 min. During sub-lethal ozonation, compared with control groups not stimulated by ozone, the conjugative transfer frequencies of E. coli DH5α (CTX), E. coli DH5α (MCR), and E. coli DH5α (GEN) increased by 1.35-2.02, 1.13-1.58, and 1.32-2.12 times, respectively; the transformation frequencies of E. coli DH5α (MCR) and E. coli DH5α (GEN) increased by 1.49-3.02 and 1.45-1.92 times, respectively. When target inhibitors were added, the conjugative transfer frequencies of antibiotics targeting cell wall and membrane synthesis decreased 0.59-0.75 and 0.43-0.76 times, respectively, while that for those targeting protein synthesis increased by 1-1.38 times. After inhibitor addition, the transformation frequencies of bacteria resistant to antibiotics targeting the cell membrane and proteins decreased by 0.76-0.89 and 0.69-0.78 times, respectively. Cell morphology, cell membrane permeability, reactive oxygen species, and antioxidant enzymes changed with different ozone concentrations. Expression of most genes related to regulating different antibiotic resistance targets was up-regulated when bacteria were exposed to sub-lethal ozonation, further confirming the target genes playing a crucial role in the inactivation of different target bacteria. These results will help guide the careful utilization of ozonation for bacterial inactivation, providing more detailed reference information for ozonation oxidation treatment of ARB and ARGs in aquatic environments.

Solid-liquid redistribution and degradation of antibiotics during hydrothermal treatment of sewage sludge: Interaction between biopolymers and antibiotics.

Waste activated sludge serves an important reservoir for antibiotics within wastewater treatment plants, and understanding the occurrence and evolution of antibiotics during sludge treatment is crucial to mitigate the potential risks of subsequent resource utilization of sludge. This study explores the degradation and transformation mechanisms of three typical antibiotics, oxytetracycline (OTC), ofloxacin (OFL), and azithromycin (AZI) during sludge hydrothermal treatment (HT), and investigates the influence of biopolymers transformation on the fate of these antibiotics. The findings indicate that HT induces a shift of antibiotics from solid-phase adsorption to liquid-phase dissolution in the initial temperature range of 25-90 °C, underscoring this phase's critical role in preparing antibiotics for subsequent degradation phases. Proteins (PN) and humic acids emerge as crucial for antibiotic binding, facilitating their redistribution within sludge. Specifically, the binding capacity sequence of biopolymers to antibiotics is as follows: OFL>OTC>AZI, highlighting that OFL-biopolymers display stronger electrostatic attraction, more available adsorption sites, and more stable binding strength. Furthermore, antibiotic degradation mainly occurs above 90 °C, with AZI being the most temperature-sensitive, degrading 92.97% at 180 °C, followed by OTC (91.26%) and OFL (52.51%). Concurrently, the degradation products of biopolymers compete for active sites to form novel amino acid-antibiotic conjugates, which inhibits the further degradation of antibiotics. These findings illuminate the effects of biopolymers evolution on intricate dynamics of antibiotics fate in sludge HT and are helpful to optimize the sludge HT process for effective antibiotics abatement.

Polypeptide N-Acetylgalactosaminyl transferase 14 is a novel mediator in pancreatic ß-cell function and growth.

Polypeptide N-Acetylgalactosaminyl transferase 14 (GALNT14) plays important roles in cancer progression and chemotherapy response. Here, we show that GALNT14 is highly expressed in pancreatic ß cells and regulates ß cell function and growth. We found that the expression level of Ganlt14 was significantly decreased in the primary islets from three rodent type-2 diabetic models. Single-Cell sequencing defined that Galnt14 was mainly expressed in ß cells of mouse islets. Galnt14 knockout (G14KO) INS-1 cell line, constructed by using CRISPR/Cas9 technology were growth normal, but showed blunt shape, and increased basal insulin secretion. Combined proteomics and glycoproteomics demonstrated that G14KO altered cell-to-cell junctions, communication, and adhesion. Insulin receptor (IR) and IGF1-1R were indirectly confirmed for GALNT14 substrates, contributed to diminished IGF1-induced p-AKT levels and cell growth in G14KO cells. Overall, this study uncovers that GALNT14 is a novel modulator in regulating ß cells biology, providing a missing link of ß cells O-glycosylation to diabetes development.

Research on domain ontology construction based on the content features of online rumors.

Online rumors are widespread and difficult to identify, which bring serious harm to society and individuals. To effectively detect and govern online rumors, it is necessary to conduct in-depth semantic analysis and understand the content features of rumors. This paper proposes a TFI domain ontology construction method, which aims to achieve semantic parsing and reasoning of the rumor text content. This paper starts from the term layer, the frame layer, and the instance layer, and based on the reuse of the top-level ontology, the extraction of core literature content features, and the discovery of new concepts in the real corpus, obtains the core classes (five parent classes and 88 subclasses) of the rumor domain ontology and defines their concept hierarchy. Object properties and data properties are designed to describe relationships between entities or their features, and the instance layer is created according to the real rumor datasets. OWL language is used to encode the ontology, Protégé is used to visualize it, and SWRL rules and pellet reasoner are used to mine and verify implicit knowledge of the ontology, and judge the category of rumor text. This paper constructs a rumor domain ontology with high consistency and reliability.

A comparative study on urban waterlogging susceptibility assessment based on multiple data-driven models.

Accurate identification of urban waterlogging areas and assessing waterlogging susceptibility are crucial for preventing and controlling hazards. Data-driven models are utilized to forecast waterlogging areas by establishing intricate relationships between explanatory variables and waterlogging states. This approach tackles the constraints of mechanistic models, which are frequently complex and unable to incorporate socio-economic factors. Previous research predominantly employed single-type data-driven models to predict waterlogging locations and evaluation of their effectiveness. There is a scarcity of comprehensive performance comparisons and uncertainty analyses of different types of models, as well as a lack of interpretability analysis. The chosen study area was the central area of Beijing, which is prone to waterlogging. Given the high manpower, time, and economic costs associated with collecting waterlogging information, the waterlogging point distribution map released by the Beijing Water Affairs Bureau was selected as labeled samples. Twelve factors affecting waterlogging susceptibility were chosen as explanatory variables to construct Random Forest (RF), Support Vector Machine with Radial Basis Function (SVM-RBF), Particle Swarm Optimization-Weakly Labeled Support Vector Machine (PSO-WELLSVM), and Maximum Entropy (MaxEnt). The utilization of diverse single evaluation indicators (such as F-score, Kappa, AUC, etc.) to assess the model performance may yield conflicting results. The Distance between Indices of Simulation and Observation (DISO) was chosen as a comprehensive measure to assess the model's performance in predicting waterlogging points. PSO-WELLSVM exhibited the highest performance with a DISOtest value of 0.63, outperforming MaxEnt (0.78), which excelled in identifying areas highly susceptible to waterlogging, including extremely high susceptibility zones. The SVM-RBF and RF models demonstrated suboptimal performance and exhibited overfitting. The examination of waterlogging susceptibility distribution maps predicted by the four models revealed significant spatial differences due to variations in computational principles and input parameter complexities. The integration of four WSAMs based on logistic regression has been shown to significantly decrease the uncertainty of a single data-driven model and identify the most flood-prone areas. To improve the interpretability of the data model, a geographical detector was incorporated to demonstrate the explanatory capacity of 12 variables and the process of waterlogging. Building Density (BD) exhibits the highest explanatory power in relation to explain waterlogging susceptibility (Q value = 0.202), followed by Distance to Road, Frequency of Heavy Rainstorms (FHR), DEM, etc. The interaction between BD and FHR results in a nonlinear increase in the explanatory power of waterlogging susceptibility. The presence of waterlogging susceptibility risk in the research area can be attributed to the interactions of multiple factors.

A multi-scale feature fusion neural network for multi-class disease classification on the maize leaf images.

Maize is a globally important cereal crop, however, maize leaf disease is one of the most common and devastating diseases that afflict it. Artificial intelligence methods face challenges in identifying and classifying maize leaf diseases due to variations in image quality, similarity among diseases, disease severity, limited dataset availability, and limited interpretability. To address these challenges, we propose a residual-based multi-scale network (MResNet) for classifying multi-type maize leaf diseases from maize images. MResNet consists of two residual subnets with different scales, enabling the model to detect diseases in maize leaf images at different scales. We further utilize a hybrid feature weight optimization method to optimize and fuse the feature mapping weights of two subnets. We validate MResNet on a maize leaf diseases dataset. MResNet achieves 97.45% accuracy. The performance of MResNet surpasses other state-of-the-art methods. Various experiments and two additional datasets confirm the generalization performance of our model. Furthermore, thermodynamic diagram analysis increases the interpretability of the model. This study provides technical support for the disease classification of agricultural plants.

The Effects of Tremella fuciformis Polysaccharide on the Physicochemical, Multiscale Structure and Digestive Properties of Cyperus esculentus Starch.

In this study, we have investigated the effects of Tremella fuciformis polysaccharide (TP) on the pasting, rheological, structural and in vitro digestive properties of Cyperus esculentus starch (CS). The results showed that the addition of TP significantly changed the pasting characteristics of CS, increased the pasting temperature and pasting viscosity, inhibited pasting, reduced the exudation of straight-chain starch and was positively correlated with the amount of TP added. The addition of the appropriate amount of TP could increase its apparent viscosity and enhance its viscoelasticity. The composite system of CS/TP exhibited higher short-range ordered structure and solid dense structure, which protected the crystal structure of CS, but was related to the amount of TP added. In addition, the introduction of TP not only decreased the in vitro digestion rate of CS and increased the content of slow-digestible starch (SDS) and resistant starch (RS), but also reduced the degree of digestion. Correlation studies established that TP could improve the viscoelasticity, relative crystallinity and short-range order of the CS/TP composite gel, maintain the integrity of the starch granule and crystalline structure, reduce the degree of starch pasting and strengthen the gel network structure of CS, which could help to lower the digestibility of CS.