Treatment with sacubitril/valsartan effectively manages hypertension and ameliorates left ventricular hypertrophy in hemodialysis patients.

Introduction The present study aimed at investigating the efficacy of sacubitril/valsartan on hypertension management and cardiac remodeling in hemodialysis patients. Methods Hemodialysis patients with stable blood pressure control were enrolled in the study. Sacubitril/valsartan was prescribed to replace previously used ACEI/ARB or other antihypertensive drugs. During a 6-month follow-up period, pre-dialysis blood pressure, routine biochemical markers and N-terminal pro-brain natriuretic peptide levels were measured. Volume status was assessed using bioelectrical impedance analysis. Endothelial damage was evaluated by measuring asymmetric dimethylarginine expression, while echocardiography and life quality assessed by short-form 12 were conducted at baseline and after treatment. Results The median daily dose of sacubitril/valsartan in 32 participants was 200 mg, and no obvious adverse reactions were reported. The defined daily dose of other antihypertensive drugs (baseline 2.00±1.18, end point 1.46±1.30, t=3.216, P=0.003) reduced significantly. After treatment with sacubitril/valsartan, left ventricular ejection fraction significantly increased from 64.81±8.16% to 67.55±5.85% (t=-4.022, P≤0.001) and the thickness of posterior wall of the left ventricle reduced from 1.05±0.14 cm to 1.00±0.11 cm (t=2.063, P=0.048). The inter-ventricular septal thickness (baseline 1.08±0.16 cm, endpoint 1.02±0.12 cm, t=2.260, P=0.031) remarkably reduced by the end of follow-up. The tricuspid regurgitation pressure gradient decreased from 28.47±8.26 mmHg at baseline to 23.79±6.61 mmHg (t=2.531, P=0.020) after treatment. Conclusion Sacubitril/valsartan effectively manages hypertension in hemodialysis patients and may also independently improve left ventricular hypertrophy and systolic function, regardless of changes in the blood pressure or the volume load.

Establishing equivalent circuits of mounted, high-power VCSEL arrays for iToF cameras.

Solid-state indirect time-of-flight (iToF) cameras are crucial to numerous short-to-medium-range applications, owing to their advantages in terms of system integrability and long-term reliability. However, due to the low light intensity, the sensing range of iToF cameras is generally limited to a few meters, which hinders their wide applications. Further increasing the sensing range requires not only higher-power laser diodes but also well-designed driver circuits, which are based on prior knowledge of the laser diodes' equivalent circuits (ECs). However, experimental studies on ECs of a mounted, high-power vertical-cavity surface-emitting laser (VCSEL) array that comprehensively incorporates all parasitic components, especially parasitic stemming from printed circuit boards (PCBs), remain absent. In this Letter, an 850 nm VCSEL array with a 15.3 W peak power and a 581 MHz bandwidth is fabricated, and more importantly, its EC is experimentally established. Leveraging the accurate EC, a compact iToF camera with a sensing range up to 11.50 m is designed. In addition, a modified precision model is proposed to better evaluate the iToF camera's performance.

Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

Isoflurane-induced neuroinflammation and NKCC1/KCC2 dysregulation result in long-term cognitive disorder in neonatal mice.

BACKGROUND: The inhalational anesthetic isoflurane is commonly utilized in clinical practice, particularly in the field of pediatric anesthesia. Research has demonstrated its capacity to induce neuroinflammation and long-term behavioral disorders; however, the underlying mechanism remains unclear [1]. The cation-chloride cotransporters Na+-K+-2Cl--1 (NKCC1) and K+-2Cl--2 (KCC2) play a pivotal role in regulating neuronal responses to gamma-aminobutyric acid (GABA) [2]. Imbalances in NKCC1/KCC2 can disrupt GABA neurotransmission, potentially leading to neural circuit hyperexcitability and reduced inhibition following neonatal exposure to anesthesia [3]. Therefore, this study postulates that anesthetics have the potential to dysregulate NKCC1 and/or KCC2 during brain development. METHODS: We administered 1.5% isoflurane anesthesia to neonatal rats for a duration of 4 h at postnatal day 7 (PND7). Anxiety levels were assessed using the open field test at PND28, while cognitive function was evaluated using the Morris water maze test between PND31 and PND34. Protein levels of NKCC1, KCC2, BDNF, and phosphorylated ERK (P-ERK) in the hippocampus were measured through Western blotting analysis. Pro-inflammatory cytokines IL-1ß, IL-6, and TNF-α were quantified using ELISA. RESULTS: We observed a decrease in locomotion trajectories within the central region and a significantly shorter total distance in the ISO group compared to CON pups, indicating that isoflurane induces anxiety-like behavior. In the Morris water maze (MWM) test, rats exposed to isoflurane exhibited prolonged escape latency onto the platform. Additionally, isoflurane administration resulted in reduced time spent crossing in the MWM experiment at PND34, suggesting long-term impairment of memory function. Furthermore, we found that isoflurane triggered activation of pro-inflammatory cytokines IL-1ß, IL-6, and TNF-α; downregulated KCC2/BDNF/P-ERK expression; and increased the NKCC1/KCC2 ratio in the hippocampus of PND7 rats. Bumetadine (NKCC1 specific inhibitors) reversed cognitive damage and effective disorder induced by isoflurane in neonatal rats by inhibiting TNF-α activation, normalizing IL-6 and IL-1ß levels, restoring KCC2 expression levels as well as BDNF and ERK signaling pathways. Based on these findings, it can be speculated that BDNF, P-ERK, IL-1ß, IL-6 and TNF - α may act downstream of the NKCC1/KCC2 pathway. CONCLUSIONS: Our findings provide evidence that isoflurane administration in neonatal rats leads to persistent cognitive deficits through dysregulation of the Cation-Chloride Cotransporters NKCC1 and KCC2, BDNF, p-ERK proteins, as well as neuroinflammatory processes.

Causal association between urine albumin-to-creatinine ratio and risk of colorectal cancer: A two-sample Mendelian randomization study.

Previous observational studies have investigated the association between urinary albumin excretion and the risk of colorectal cancer (CRC), but the results have been inconsistent. This study aimed to explore the causal association between urine albumin-to-creatinine ratio (ACR) and CRC risk through a two-sample Mendelian randomization (MR) analysis. The genome-wide association study (GWAS) data of ACR (n = 382,500) and CRC (CRC: 6,509 cases and 287,137 controls) were obtained from the IEU OpenGWAS project website and the FinnGen database, respectively. The TwoSampleMR and MR-PRESSO R packages were used to search for and analyze genetic variations that served as instrumental variables for ACR. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using the inverse-variance weighted method, MR-Egger, and weighted median. Genetically predicted ACR was not associated with CRC risk (all P > 0.05). Further analysis based on the site of onset (colon or rectum) also did not show a significant association (all P > 0.05). MR-PRESSO, MR-Egger regression and leave-one-out sensitivity analysis all indicated that the current results were robust and reliable. These findings suggest that ACR does not affect CRC risk and may not be used as a marker of CRC risk in clinical practice. However, relevant studies especially in ethnically diverse populations are still needed to confirm the current findings.

Can carbon reduction policies promote sustainable construction development? Evidence from China's green building market.

Carbon emissions have become a global challenge, and China, as the world's largest developing country, has a serious emissions problem. Developing green buildings is an important way of reducing carbon emissions. China's low-carbon city pilot policy may be an effective way of promoting green building development and reducing these emissions. This study uses the low carbon city pilot policy as a quasi-natural experiment and employs the staggered difference-in-differences method to investigate its impact on green building development. The results show that the low-carbon city pilot policy promotes green building development, and this policy promotes it by enhancing regional green innovation capacity, improving green total factor productivity at the firm and regional levels, and reducing the financing constraints of firms in the construction and real estate sectors. In addition, the promotion effect of the policy on green building development is stronger in western and non-resource-based regions and large-scale cities in China. This study contributes to the literature related to environmental policy, green building, and carbon emissions and supports the promotion of green building development and the reduction of carbon emissions.

Latent Class Analysis of Sleep in Mild Cognitive Impairment Patients and its Influencing Factors.

Background: Individuals with mild cognitive impairment (MCI) frequently experience sleep disorders, which may elevate the risk of developing Alzheimer's disease. Yet, sleep types in MCI patients and the factors influencing them have not been sufficiently investigated. Objective: The objective of this study was to explore potential sleep typing and its influencing factors in patients with MCI using latent class analysis. Methods: A cross-sectional survey was conducted in Jiangsu Province, China. Cognitive function in older adults was assessed using neuropsychological tests, including the Montreal Cognitive Assessment Scale-Beijing version (MoCA), the Mini-Mental State Examination (MMSE), the Activities of Daily Living Scale (ADL), and the Clinical Dementia Rating Scale (CDR). Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Latent class analysis based on PSQI scores and multinomial logistic regression analyses were employed to explore the influencing factors of sleep typing. Results: The study included a total of 611 patients with MCI. Latent class analysis identified three latent classes to categorize the sleep patterns of MCI patients: the good sleep type (56.6%), the insufficient sleep type (29.6%), and the difficulty falling asleep type (13.7%). Potential sleep typing is influenced by gender, chronic disease, physical exercise, social activity, brain exercise, smoking, frailty, subjective cognitive status, and global cognitive function. Conclusions: The findings of this study underscore the notable heterogeneity in the sleep patterns of patients with MCI. Future research may provide targeted prevention and interventions to address the characteristics and influencing factors of patients with different subtypes of sleep MCI.

Continuous estimation of respiratory system compliance and airway resistance during pressure-controlled ventilation without end-inspiration occlusion.

BACKGROUND: Assessing mechanical properties of the respiratory system (Cst) during mechanical ventilation necessitates an end-inspiration flow of zero, which requires an end-inspiratory occlusion maneuver. This lung model study aimed to observe the effect of airflow obstruction on the accuracy of respiratory mechanical properties during pressure-controlled ventilation (PCV) by analyzing dynamic signals. METHODS: A Hamilton C3 ventilator was attached to a lung simulator that mimics lung mechanics in healthy, acute respiratory distress syndrome (ARDS) and chronic obstructive pulmonary disease (COPD) models. PCV and volume-controlled ventilation (VCV) were applied with tidal volume (VT) values of 5.0, 7.0, and 10.0 ml/kg. Performance characteristics and respiratory mechanics were assessed and were calibrated by virtual extrapolation using expiratory time constant (RCexp). RESULTS: During PCV ventilation, drive pressure (DP) was significantly increased in the ARDS model. Peak inspiratory flow (PIF) and peak expiratory flow (PEF) gradually declined with increasing severity of airflow obstruction, while DP, end-inspiration flow (EIF), and inspiratory cycling ratio (EIF/PIF%) increased. Similar estimated values of Crs and airway resistance (Raw) during PCV and VCV ventilation were obtained in healthy adult and mild obstructive models, and the calculated errors did not exceed 5%. An underestimation of Crs and an overestimation of Raw were observed in the severe obstruction model. CONCLUSION: Using the modified dynamic signal analysis approach, respiratory system properties (Crs and Raw) could be accurately estimated in patients with non-severe airflow obstruction in the PCV mode.

Immune checkpoints: new insights into the pathogenesis of thyroid eye disease.

Thyroid eye disease (TED) is a disfiguring autoimmune disease characterized by changes in the orbital tissues and is caused by abnormal thyroid function or thyroid-related antibodies. It is the ocular manifestation of Graves' disease. The expression of thyroid-stimulating hormone receptor (TSHR) and the insulin-like growth factor-1 receptor (IGF-1 R) on the cell membrane of orbital fibroblasts (OFs) is responsible for TED pathology. Excessive inflammation is caused when these receptors in the orbit are stimulated by autoantibodies. CD34+ fibrocytes, found in the peripheral blood and orbital tissues of patients with TED, express immune checkpoints (ICs) like MHC II, B7, and PD-L1, indicating their potential role in presenting antigens and regulating the immune response in TED pathogenesis. Immune checkpoint inhibitors (ICIs) have significantly transformed cancer treatment. However, it can also lead to the occurrence of TED in some instances, suggesting the abnormality of ICs in TED. This review will examine the overall pathogenic mechanism linked to the immune cells of TED and then discuss the latest research findings on the immunomodulatory role of ICs in the development and pathogenesis of TED. This will offer fresh perspectives on the study of pathogenesis and the identification of potential therapeutic targets.

Bioengineered vascular grafts with a pathogenic TGFBR1 variant model aneurysm formation in vivo and reveal underlying collagen defects.

Thoracic aortic aneurysm (TAA) is a life-threatening vascular disease frequently associated with underlying genetic causes. An inadequate understanding of human TAA pathogenesis highlights the need for better disease models. Here, we established a functional human TAA model in an animal host by combining human induced pluripotent stem cells (hiPSCs), bioengineered vascular grafts (BVGs), and gene editing. We generated BVGs from isogenic control hiPSC-derived vascular smooth muscle cells (SMCs) and mutant SMCs gene-edited to carry a Loeys-Dietz syndrome (LDS)-associated pathogenic variant (TGFBR1A230T). We also generated hiPSC-derived BVGs using cells from a patient with LDS (PatientA230T/+) and using genetically corrected cells (Patient+/+). Control and experimental BVGs were then implanted into the common carotid arteries of nude rats. The TGFBR1A230T variant led to impaired mechanical properties of BVGs, resulting in lower burst pressure and suture retention strength. BVGs carrying the variant dilated over time in vivo, resembling human TAA formation. Spatial transcriptomics profiling revealed defective expression of extracellular matrix (ECM) formation genes in PatientA230T/+ BVGs compared with Patient+/+ BVGs. Histological analysis and protein assays validated quantitative and qualitative ECM defects in PatientA230T/+ BVGs and patient tissue, including decreased collagen hydroxylation. SMC organization was also impaired in PatientA230T/+ BVGs as confirmed by vascular contraction testing. Silencing of collagen-modifying enzymes with small interfering RNAs reduced collagen proline hydroxylation in SMC-derived tissue constructs. These studies demonstrated the utility of BVGs to model human TAA formation in an animal host and highlighted the role of reduced collagen modifying enzyme activity in human TAA formation.

Exosomes derived from vMIP-II-Lamp2b gene-modified M2 cells provide neuroprotection by targeting the injured spinal cord, inhibiting chemokine signals and modulating microglia/macrophage polarization in mice.

Inflammation is one of the key injury factors for spinal cord injury (SCI). Exosomes (Exos) derived from M2 macrophages have been shown to inhibit inflammation and be beneficial in SCI animal models. However, lacking targetability restricts their application prospects. Considering that chemokine receptors increase dramatically after SCI, viral macrophage inflammatory protein II (vMIP-II) is a broad-spectrum chemokine receptor binding peptide, and lysosomal associated membrane protein 2b (Lamp2b) is the key membrane component of Exos, we speculated that vMIP-II-Lamp2b gene-modified M2 macrophage-derived Exos (vMIP-II-Lamp2b-M2-Exo) not only have anti-inflammatory properties, but also can target the injured area by vMIP-II. In this study, using a murine contusive SCI model, we revealed that vMIP-II-Lamp2b-M2-Exo could target the chemokine receptors which highly expressed in the injured spinal cords, inhibit some key chemokine receptor signaling pathways (such as MAPK and Akt), further inhibit proinflammatory factors (such as IL-1ß, IL-6, IL-17, IL-18, TNF-α, and iNOS), and promote anti-inflammatory factors (such as IL-4 and Arg1) productions, and the transformation of microglia/macrophages from M1 into M2. Moreover, the improved histological and functional recoveries were also found. Collectively, our results suggest that vMIP-II-Lamp2b-M2-Exo may provide neuroprotection by targeting the injured spinal cord, inhibiting some chemokine signals, reducing proinflammatory factor production and modulating microglia/macrophage polarization.

Highly stable Ag-doped Cu2O immobilized cellulose-derived carbon beads with enhanced visible-light photocatalytic degradation of levofloxacin.

Ag-doped Cu2O immobilized carbon beads (Ag/Cu2O@CB) based composite photocatalysts have been prepared for the removal of levofloxacin, an antibiotic, from water. The photocatalysts were prepared by the processes of chemical reduction and in-situ solid-phase precipitation. The composite photocatalyst was characterized by a porous and interconnected network structure. Ag nanoparticles were deposited on Cu2O particles to develop a metal-based semiconductor to increase the catalytic efficiency of the system and the separation efficiency of the photogenerated carriers. Cellulose-derived carbon beads (CBs) can also be used as electron storage libraries which can capture electrons released from the conduction band of Cu2O. The results revealed that the maximum catalytic degradation efficiency of the composite photocatalyst for the antibiotic levofloxacin was 99.02 %. The Langmuir-Hinshelwood model was used to study the reaction kinetics, and the process of photodegradation followed first-order kinetics. The maximum apparent rate was recorded to be 0.0906 min-1. The mass spectrometry technique showed that levofloxacin degraded into carbon dioxide and water in the presence of the photocatalyst. The results revealed that the easy-to-produce photocatalyst was stable and efficient in levofloxacin removing.

CD7-positive leukemic blasts with DNMT3A mutations predict poor prognosis in patients with acute myeloid leukemia.

Background: DNMT3A mutations can be detected in premalignant hematopoietic stem cells and are primarily associated with clonal hematopoiesis of indeterminate potential; however, current evidence does not support assigning them to a distinct European Leukemia Net (ELN) prognostic risk stratification. CD7 is a lymphoid antigen expressed on blasts in approximately 30% of acute myeloid leukemia (AML), and its role in AML remains unclear and depends on subgroup evaluation. This study investigated the prognostic value of DNMT3A mutation combined with CD7 expression in AML. Methods: We retrospectively analyzed the clinical data of 297 newly diagnosed non-M3 AML patients. According to the DNMT3A mutation and CD7 expression in AML cells, patients were divided into the DNMT3A-mutated/CD7-positive (CD7+), DNMT3A-mutated/CD7-negative (CD7-), DNMT3A-wild-type/CD7+, and DNMT3A-wild-type/CD7- groups. Results: The DNMT3A-mutated/CD7+ group had lower complete remission rates and higher relapse rates. Importantly, these patients had significantly shorter overall survival (OS) and relapse-free survival (RFS). Furthermore, multivariate analysis showed that CD7+ with DNMT3A mutation was an independent risk factor for OS and RFS. Conclusion: CD7+ with DNMT3A mutation predicts a poor prognosis in AML patients, and the immunophenotype combined with molecular genetic markers can help to further refine the current risk stratification of AML.

Dual-TranSpeckle: Dual-pathway transformer based encoder-decoder network for medical ultrasound image despeckling.

The majority of existing deep learning-based image denoising algorithms mainly focus on processing the overall image features, ignoring the fine differences between the semantic and pixel features. Hence, we propose Dual-TranSpeckle (DTS), a medical ultrasound image despeckling network built on a dual-path Transformer. The DTS introduces two different paths, named "semantic path" and "pixel path," to facilitate the parallel transfer of feature information within the image. The semantic path passes a global view of the input semantic features, and the image features are passed through a Semantic Block to extract global semantic information from pixel-level features. The pixel path is employed to transmit finer-grained pixel features. Within the dual-path network framework, two essential modules, namely Dual Block and Merge Block, are designed. These leverage the Transformer architecture during the encoding and decoding stages. The Dual Block module facilitates information interaction between the semantic and pixel features by considering the interdependencies across both paths. Meanwhile, the Merge Block module enables parallel transfer of feature information by merging the dual path features, thereby facilitating the self-attention calculations for the overall feature representation. Our DTS is extensively evaluated on two public datasets and one private dataset. The DTS network demonstrates significant enhancements in quantitative evaluation results in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), feature similarity (FSIM), and naturalness image quality evaluator (NIQE). Furthermore, our qualitative analysis confirms that the DTS has significant improvements in despeckling performance, effectively suppressing speckle noise while preserving essential image structures.

Adaptive responses of erythritol-producing Yarrowia lipolytica to thermal stress after evolution.

Elucidation of the thermotolerance mechanism of erythritol-producing Yarrowia lipolytica is of great significance to breed robust industrial strains and reduce cost. This study aimed to breed thermotolerant Y. lipolytica and investigate the mechanism underlying the thermotolerant phenotype. Yarrowia lipolytica HT34, Yarrowia lipolytica HT36, and Yarrowia lipolytica HT385 that were capable of growing at 34 °C, 36 °C, and 38.5 °C, respectively, were obtained within 150 days (352 generations) by adaptive laboratory evolution (ALE) integrated with 60Co-γ radiation and ultraviolet ray radiation. Comparative genomics analysis showed that genes involved in signal transduction, transcription, and translation regulation were mutated during adaptive evolution. Further, we demonstrated that thermal stress increased the expression of genes related to DNA replication and repair, ceramide and steroid synthesis, and the degradation of branched amino acid (BCAA) and free fatty acid (FFA), while inhibiting the expression of genes involved in glycolysis and the citrate cycle. Erythritol production in thermotolerant strains was remarkably inhibited, which might result from the differential expression of genes involved in erythritol metabolism. Exogenous addition of BCAA and soybean oil promoted the growth of HT385, highlighting the importance of BCAA and FFA in thermal stress response. Additionally, overexpression of 11 out of the 18 upregulated genes individually enabled Yarrowia lipolytica CA20 to grow at 34 °C, of which genes A000121, A003183, and A005690 had a better effect. Collectively, this study provides novel insights into the adaptation mechanism of Y. lipolytica to thermal stress, which will be conducive to the construction of thermotolerant erythritol-producing strains. KEY POINTS: • ALE combined with mutagenesis is efficient for breeding thermotolerant Y. lipolytica • Genes encoding global regulators are mutated during thermal adaptive evolution • Ceramide and BCAA are critical molecules for cells to tolerate thermal stress.

Generation of a humanized mAce2 and a conditional hACE2 mouse models permissive to SARS-COV-2 infection.

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) remains a public health concern and a subject of active research effort. Development of pre-clinical animal models is critical to study viral-host interaction, tissue tropism, disease mechanisms, therapeutic approaches, and long-term sequelae of infection. Here, we report two mouse models for studying SARS-CoV-2: A knock-in mAce2F83Y,H353K mouse that expresses a mouse-human hybrid form of the angiotensin-converting enzyme 2 (ACE2) receptor under the endogenous mouse Ace2 promoter, and a Rosa26 conditional knock-in mouse carrying the human ACE2 allele (Rosa26hACE2). Although the mAce2F83Y,H353K mice were susceptible to intranasal inoculation with SARS-CoV-2, they did not show gross phenotypic abnormalities. Next, we generated a Rosa26hACE2;CMV-Cre mouse line that ubiquitously expresses the human ACE2 receptor. By day 3 post infection with SARS-CoV-2, Rosa26hACE2;CMV-Cre mice showed significant weight loss, a variable degree of alveolar wall thickening and reduced survival rates. Viral load measurements confirmed inoculation in lung and brain tissues of infected Rosa26hACE2;CMV-Cre mice. The phenotypic spectrum displayed by our different mouse models translates to the broad range of clinical symptoms seen in the human patients and can serve as a resource for the community to model and explore both treatment strategies and long-term consequences of SARS-CoV-2 infection.

Inhibition of hyphal formation together with biochar addition promotes erythritol production by Yarrowia lipolytica.

This study aimed to investigate the effect of hyphal formation in Yarrowia lipolytica and biochar addition on erythritol production by submerged fermentation. Hyphal formation significantly inhibited erythritol production by Y. lipolytica. Transcriptome analysis suggested that the impaired erythritol synthesis of hyphal cells was associated with the differential expression of genes involved in amino acid metabolism, lipid metabolism, and cell wall stability. Deletion of RAS2 responsible for yeast-to-hypha transition and EYD1 included in erythritol degradation blocked hyphal formation and improved erythritol production. Biochar prepared from corncob, sugarcane bagasse (SB), corn straw, peanut shell, coconut shell, and walnut shell (WS) had a positive effect on erythritol production, of which WS pyrolyzed at 500°C (WSc) performed the best in flask fermentation. In a 3.7 L bioreactor, 220.20 ± 10 g/L erythritol with a productivity of 2.30 ± 0.10 g/L/h was obtained in the presence of 1.4% (w/v) WSc and 0.7% SBc (SB pyrolyzed at 500°C) within 96 h. These results suggest that inhibition of hyphal formation together with biochar addition is an efficient way to promote erythritol production.

DIAGNOSTIC PERFORMANCE OF CENTRAL NERVOUS SYSTEM INFECTIONS IN PATIENTS WITH NEUROSURGICAL INTENSIVE CARE USING METAGENOMIC NEXT-GENERATION SEQUENCING: A PROSPECTIVE OBSERVATIONAL STUDY.

ABSTRACT: Background. Identifying the causative pathogens of central nervous system infections (CNSIs) is crucial, but the low detection rate of traditional culture methods in cerebrospinal fluid (CSF) has made the pathogenic diagnosis of CNSIs a longstanding challenge. Patients with CNSIs after neurosurgery often overlap with inflammatory and bleeding. Metagenomic next-generation sequencing (mNGS) has shown some benefits in pathogen detection. This study aimed to investigate the diagnostic performance of mNGS in the etiological diagnosis of CNSIs in patients after neurosurgery. Methods. In this prospective observational study, we enrolled patients with suspected CNSIs after neurosurgical operations who were admitted to the intensive care unit of Beijing Tiantan Hospital. All enrolled patients' CSF was tested using mNGS and pathogen culture. According to comprehensive clinical diagnosis, the enrolled patients were divided into CNSIs group and non-CNSIs group to compare the diagnostic efficiency of mNGS and pathogen culture. Results. From December 2021 to March 2023, 139 patients were enrolled while 66 in CNSIs group and 73 in non-CNSIs. The mNGS exceeded culture in the variety and quantity of pathogens detected. The mNGS outperformed traditional pathogen culture in terms of positive percent agreement (63.63%), accuracy (82.01%), and negative predictive value (75.00%), with statistically significant differences ( P < 0.05) for traditional pathogen culture. The mNGS also detected bacterial spectrum and antimicrobial resistance genes. Conclusions. Metagenomics has the potential to assist in the diagnosis of patients with CNSIs who have a negative culture.

Heterogeneous Domain Adaptation With Generalized Similarity and Dissimilarity Regularization.

Heterogeneous domain adaptation (HDA) aims to address the transfer learning problems where the source domain and target domain are represented by heterogeneous features. The existing HDA methods based on matrix factorization have been proven to learn transferable features effectively. However, these methods only preserve the original neighbor structure of samples in each domain and do not use the label information to explore the similarity and separability between samples. This would not eliminate the cross-domain bias of samples and may mix cross-domain samples of different classes in the common subspace, misleading the discriminative feature learning of target samples. To tackle the aforementioned problems, we propose a novel matrix factorization-based HDA method called HDA with generalized similarity and dissimilarity regularization (HGSDR). Specifically, we propose a similarity regularizer by establishing the cross-domain Laplacian graph with label information to explore the similarity between cross-domain samples from the identical class. And we propose a dissimilarity regularizer based on the inner product strategy to expand the separability of cross-domain labeled samples from different classes. For unlabeled target samples, we keep their neighbor relationship to preserve the similarity and separability between them in the original space. Hence, the generalized similarity and dissimilarity regularization is built by integrating the above regularizers to facilitate cross-domain samples to form discriminative class distributions. HGSDR can more efficiently match the distributions of the two domains both from the global and sample viewpoints, thereby learning discriminative features for target samples. Extensive experiments on the benchmark datasets demonstrate the superiority of the proposed method against several state-of-the-art methods.