Ultrasensitive Detection of Dimethylamine Gas for Early Diagnosis of Parkinson's Disease Using CeO2-Coated Ti3C2Tx MXene/Carbon Nanofibers.

Parkinson's disease is a prevalent neurological disorder, with dimethylamine (DMA) recognized as a crucial breath biomarker, particularly at the parts per billion (ppb) level. Detecting DMA gas at this level, especially at room temperature and high humidity, remains a formidable challenge. This study presents an ultrasensitive chemiresistor DMA gas sensor, leveraging the CeO2-coated Ti3C2Tx MXene/carbon nanofiber (CeO2/MXene/C NFs) heterostructure to enhance dimethylamine sensing. The high conductivity of MXene, combined with C-Ti-O bonds and a sp2 hybridized hexagonal carbon structure, increases surface active sites. The presence of Ce3+ promotes the formation of surface-active oxygen species, while the MXene-CeO2 heterojunction broadens the electron depletion layer. Theoretical calculations reveal that the highest adsorption energy for DMA gas is at the Ce top site, explaining the sensor's satisfactory sensitivity, rapid response and recovery process, low detection limit (5 ppb), and high selectivity at room temperature. The Ce3+/Ce4+ dynamic self-refresh mechanism, involving surface hydroxyl elimination, enhances the sensor's performance under high-humid conditions. Clinical breath tests demonstrate the sensor's ability to distinguish between healthy individuals and Parkinson's disease patients, paving the way for developing next-generation sensors for early diagnosis of neurological disorders.

Plant viruses exploit insect salivary GAPDH to modulate plant defenses.

Salivary proteins of insect herbivores can suppress plant defenses, but the roles of many remain elusive. One such protein is glyceraldehyde-3-phosphate dehydrogenase (GAPDH) from the saliva of the Recilia dorsalis (RdGAPDH) leafhopper, which is known to transmit rice gall dwarf virus (RGDV). Here we show that RdGAPDH was loaded into exosomes and released from salivary glands into the rice phloem through an exosomal pathway as R. dorsalis fed. In infected salivary glands of R. dorsalis, the virus upregulated the accumulation and subsequent release of exosomal RdGAPDH into the phloem. Once released, RdGAPDH consumed H2O2 in rice plants owing to its -SH groups reacting with H2O2. This reduction in H2O2 of rice plant facilitated R. dorsalis feeding and consequently promoted RGDV transmission. However, overoxidation of RdGAPDH could cause potential irreversible cytotoxicity to rice plants. In response, rice launched emergency defense by utilizing glutathione to S-glutathionylate the oxidization products of RdGAPDH. This process counteracts the potential cellular damage from RdGAPDH overoxidation, helping plant to maintain a normal phenotype. Additionally, salivary GAPDHs from other hemipterans vectors similarly suppressed H2O2 burst in plants. We propose a strategy by which plant viruses exploit insect salivary proteins to modulate plant defenses, thus enabling sustainable insect feeding and facilitating viral transmission.

Astragalus Polysaccharide improves immunogenicity of influenza vaccine as well as modulate gut microbiota in BALB/c mice.

BACKGROUND: Vaccination is the best way to prevent influenza virus infection, and insufficient antibodies make it difficult to resist influenza virus invasion. Astragalus Polysaccharide (APS) has a boosting effect on immunity, so we evaluate the effect of APS as an immune adjuvant for H1N1 influenza vaccines in this study. METHODS: The mice were immunized twice with influenza A (H1N1) vaccine and APS. Subsequently, the serum antibody levels were assessed using enzyme-linked immunosorbent assay (ELISA). The frequency of peripheral immune T cells was determined by flow cytometry. Following this, the immunized mice were exposed to a lethal dose of the virus, and changes in body weight and survival rates were recorded. Hematoxylin-eosin staining was employed to observe pathological alterations in lung and intestinal tissues. Western blot analysis was conducted to detect the expression of intestinal barrier function proteins (Occludin and Claudin-1). ELISA was utilized to measure the expression level of serum inflammatory cytokine TNF-α. Fresh mouse feces were collected after the initial immunization as well as after viral infection for 16S rRNA analysis aimed at detecting alterations in gut microbiota. RESULTS: Compared to the Hemagglutinin (HA) group, the APS group demonstrated higher levels of immunoglobulin G (IgG), IgG1, and IgG3, as well as neutralizing antibody levels. Additionally, it increased the frequency of CD8+ cells to enhance resistance against lethal infection. On day 14 post-infection, the high-dose APS group exhibited a higher survival rate (71.40 %) compared to the HA group (14.28 %), along with faster weight recovery. Furthermore, APS was found to ameliorate alveolar damage in lung tissue and rectify intestinal structural disorder. It also upregulated the expression levels of tight junction proteins Occludin and Claudin-1 in intestinal tissue while reducing serum TNF-α expression levels. In addition, populations of Colidextribacter, Peptococcaceae, and Ruminococcaceae were the dominant gut microbiota in the APS group after viral infection. CONCLUSION: APS has an immune-enhancing effect and is expected to be a novel adjuvant in the H1N1 influenza vaccine.

ATM Activation is Key in Vasculogenic Mimicry Formation by Glioma Stem-like Cells.

Objective: Vasculogenic mimicry (VM) is a novel vasculogenic process integral to glioma stem cells (GSCs) in glioblastoma (GBM). However, the relationship between VM and ataxia-telangiectasia mutated (ATM) serine/threonine kinase activation, which confers chemoradiotherapy resistance, remains unclear. Methods: We investigated VM formation and phosphorylated ATM (pATM) levels by CD31/GFAP-periodic acid-Schiff dual staining and immunohistochemical staining in 145 GBM specimens. Glioma stem-like cells (GSLCs) derived from the formatted spheres of U87 and U251 cell lines and their pATM level and VM formation ability were examined using western blot and three-dimensional culture. For the examination of the function of pATM in VM formation by GSLCs, ATM knockdown by shRNAs and deactivated via ATM phosphorylation inhibitor KU55933 were studied. Results: VM and high pATM expression occurred in 38.5% and 41.8% of tumors, respectively, and were significantly associated with reduced progression-free and overall survival. Patients with VM-positive GBMs exhibited higher pATM levels ( r s = 0.425, P = 0.01). The multivariate analysis established VM as an independent negative prognostic factor ( P = 0.002). Furthermore, GSLCs expressed high levels of pATM and formed vascular-like networks in vitro. ATM inactivation or knockdown hindered VM-like network formation concomitant with the downregulation of pVEGFR-2, VE-cadherin, and laminin B2. Conclusion: VM may predict a poor GBM prognosis and is associated with pATM expression. We propose that pATM promotes VM through extracellular matrix modulation and VE-Cadherin / pVEGFR-2 activation, thereby highlighting ATM activation as a potential target for enhancing anti-angiogenesis therapies for GBM.

Structural Models of Human Norepinephrine Transporter Ensemble Reveal the Allosteric Sites and Ligand-Binding Mechanism.

The norepinephrine transporter (NET) plays a pivotal role in recycling norepinephrine (NE) from the synaptic cleft. However, the structures referring to the conformational heterogeneity of NET during the transport cycle remain poorly understood. Here, three structural models of NE bound to the orthosteric site of NET in outward-open (OOholo), outward-occluded (OCholo), and inward-open (IOholo) conformations were first obtained using the multistate structures of serotonin transporter as templates and further characterized through Gaussian-accelerated molecular dynamics and free energy reweighting. Analysis of the structures revealed eight potential allosteric sites on the functional-specific states of NET. One of the pharmacologically relevant pockets located at the extracellular vestibule was further verified by simulating the binding behaviors of a clinical trial drug χ-MrIA that is allosterically regulating NET. These structural and energetic insights into NET advanced our understanding of NE reuptake and paved the way for discovering novel molecules targeting the allosteric sites.

Exploring gut microbial metabolites as key players in inhibition of cancer progression: Mechanisms and therapeutic implications.

The gut microbiota plays a critical role in numerous biochemical processes essential for human health, such as metabolic regulation and immune system modulation. An increasing number of research suggests a strong association between the gut microbiota and carcinogenesis. The diverse metabolites produced by gut microbiota can modulate cellular gene expression, cell cycle dynamics, apoptosis, and immune system functions, thereby exerting a profound influence on cancer development and progression. A healthy gut microbiota promotes substance metabolism, stimulates immune responses, and thereby maintains the long-term homeostasis of the intestinal microenvironment. When the gut microbiota becomes imbalanced and disrupts the homeostasis of the intestinal microenvironment, the risk of various diseases increases. This review aims to elucidate the impact of gut microbial metabolites on cancer initiation and progression, focusing on short-chain fatty acids (SCFAs), polyamines (PAs), hydrogen sulfide (H2S), secondary bile acids (SBAs), and microbial tryptophan catabolites (MTCs). By detailing the roles and molecular mechanisms of these metabolites in cancer pathogenesis and therapy, this article sheds light on dual effects on the host at different concentrations of metabolites and offers new insights into cancer research.

Self-Supervised Representation Distribution Learning for Reliable Data Augmentation in Histopathology WSI Classification.

Multiple instance learning (MIL) based whole slide image (WSI) classification is often carried out on the representations of patches extracted from WSI with a pre-trained patch encoder. The performance of classification relies on both patch-level representation learning and MIL classifier training. Most MIL methods utilize a frozen model pre-trained on ImageNet or a model trained with self-supervised learning on histopathology image dataset to extract patch image representations and then fix these representations in the training of the MIL classifiers for efficiency consideration. However, the invariance of representations cannot meet the diversity requirement for training a robust MIL classifier, which has significantly limited the performance of the WSI classification. In this paper, we propose a Self-Supervised Representation Distribution Learning framework (SSRDL) for patch-level representation learning with an online representation sampling strategy (ORS) for both patch feature extraction and WSI-level data augmentation. The proposed method was evaluated on three datasets under three MIL frameworks. The experimental results have demonstrated that the proposed method achieves the best performance in histopathology image representation learning and data augmentation and outperforms state-of-the-art methods under different WSI classification frameworks. The code is available at https://github.com/lazytkm/SSRDL.

Thoracic SMARCA4-Deficient Undifferentiated Tumor Mimicking Malignant Pleural Mesothelioma on FDG PET/CT.

ABSTRACT: We describe contrast-enhanced CT and FDG PET/CT findings in a case of thoracic SMARCA4-deficient undifferentiated tumor with extensive pleural involvement and mediastinal lymph node metastases. Contrast-enhanced CT showed multiple enhancing right-sided pleural masses and soft tissue plaques and enlarged mediastinal lymph nodes. The pleural lesions and mediastinal lymph nodes showed intense FDG uptake mimicking malignant pleural mesothelioma with mediastinal lymph node metastases.

Partial-Label Contrastive Representation Learning for Fine-grained Biomarkers Prediction from Histopathology Whole Slide Images.

In the domain of histopathology analysis, existing representation learning methods for biomarkers prediction from whole slide images (WSI) face challenges due to the complexity of tissue subtypes and label noise problems. This paper proposed a novel partial-label contrastive representation learning approach to enhance the discrimination of histopathology image representations for fine-grained biomarkers prediction. We designed a partial-label contrastive clustering (PLCC) module for partial-label disambiguation and a dynamic clustering algorithm to sample the most representative features of each category to the clustering queue during the contrastive learning process. We conducted comprehensive experiments on three gene mutation prediction datasets, including USTC-EGFR, BRCA-HER2, and TCGA-EGFR. The results show that our method outperforms 9 existing methods in terms of Accuracy, AUC, and F1 Score. Specifically, our method achieved an AUC of 0.950 in EGFR mutation subtyping of TCGA-EGFR and an AUC of 0.853 in HER2 0/1+/2+/3+ grading of BRCA-HER2, which demonstrates its superiority in fine-grained biomarkers prediction from histopathology whole slide images. The source code is available at https://github.com/WkEEn/PLCC.

Understanding the factors of wearable devices among the patients with thyroid cancer: A modified UTAUT2 model.

Wearable devices hold promising prospects on a global scale, including in China. Thyroid cancer prevalence is notably high in China.This purpose of this researchwas to provide an updated theoretical model for assessing Chinese thyroid cancer patients' intentions towards wearable devices, based on the UTAUT2 framework, and to ascertain the factors that have an impact on these intents. A cross-sectional study with an institutional focus wasconducted from January 20, 2023, to June 30, 2023, at several general hospitals in China. Five hundred participants were recruited to identify predictors of wearable device use.The questionnaire survey about patients' intentionswas collected using a face-to-face method, employing a random sampling technique for patient selection. Four hundred sixty-nine individuals (93.8%) had the intention to use wearable devices. The intentions were highly impacted by performance expectancy (PE), effort expectancy (EE), social influence (SI), hedonic motivation (HM), price value (PV) and habit (HA). Usage intention (UI)was a statistically predictor of Usage behavior (UB). The facilitating condition(FC) was not significant. Gender positively moderated the relationship between EE and UI. Income positively moderated the relationship between all variables and UI.Overall, the utilization of wearable devices among patients diagnosed with thyroid cancer has demonstrated considerable potential. This study offers a series of suggestions for digital health developers,healthcare decision-makers,doctors and patients.

Understanding the mechanisms and treatments of long COVID to address future public health risks.

The 2019 coronavirus disease (COVID-19), triggered by the severe acute respiratory syndrome coronavirus (SARS-CoV-2), has seen numerous individuals undergo and recover from it, drawing extensive attention to their health conditions. Extensive studies indicate that even after surpassing the acute phase of infection, patients continue to experience persistent symptoms such as fatigue, pain, depression, weakening, and anosmia. COVID-19 appears not to have concluded but rather to persist long-term in certain individuals, termed as "long COVID." This represents a heterogeneous ailment involving multiple organ systems, with a perceived complex and still elusive pathogenesis. Among patients with long COVID, observations reveal immune dysregulation, coagulation impairments, and microbial dysbiosis, considered potential mechanisms explaining sustained adverse outcomes post COVID-19. Based on the multifactorial nature, varied symptoms, and heterogeneity of long COVID, we have summarized several categories of current therapeutic approaches. Furthermore, the symptoms of long COVID resemble those of other viral illnesses, suggesting that existing knowledge may offer novel insights into long-term COVID implications. Here, we provide an overview of existing literature associated with long COVID and summarize potential mechanisms, treatment modalities, and other analogous conditions. Lastly, we underscore the inadequacies in long COVID treatment approaches and emphasize the significance of conducting further research and clinical trials.

NMT2 alleviates depression-like behavior in a rat model of chronic unpredictable stress: An integrated proteomic and phosphoproteomic analysis.

Proteomics has been widely used to investigate multiple diseases. Combining the analyses of proteomics with phosphoproteomics can be used to further explain the pathological mechanisms of depression. In this study, depression-like behavior was induced in a rat model of chronic unpredictable mild stress (CUMS). We subsequently conducted the sucrose preference test, open field experiment, and forced swimming test to assess depressive-like behavior. Proteomic and phosphoproteomic sequencing of the hippocampal tissues from depressive-like behavior and normal rats were analyzed to identify differentially expressed proteins (DEPs) and differentially phosphorylated proteins (DPPs). Differentially expressed phosphorylated proteins (DEPPs) were obtained by intersecting the DEPs and DPPs, and functional enrichment analysis, as well as ingenuity pathway analysis (IPA), were subsequently performed. The study also investigated correlations among the DEPPs and used qRT-PCR to quantify the expression levels of key genes. Five DEPPs were identified, Gys1, Nmt2, Lrp1, Bin1, and Atp1a1, which were found to activate the synaptogenesis signaling pathway, induce mitochondrial dysfunction, and activate the phosphoinositide biosynthesis and degradation pathways. The qRT-PCR results confirmed the proteomic findings for Gys1, Nmt2, Lrp1, and Atp1a1. Importantly, inhibiting Nmt2 was found to alleviate depression-like behavior and alleviate neuronal apoptosis in the hippocampus of CUMS rats. In conclusion, we identified five DEPPs associated with the synaptogenesis signaling pathway, mitochondrial dysfunction, and phosphoinositide biosynthesis and degradation in depression. Furthermore, NMT2 may be a potential target for the treatment or diagnosis of depression. Our findings provide novel insights into the molecular mechanisms of depression.

Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In this study, an artificial intelligence-powered deep learning framework was developed for the weakly supervised prediction of EGFR mutations in non-small cell lung cancer from hematoxylin and eosin-stained histopathology whole-slide images. The study cohort was partitioned into training and validation subsets. Foreground regions containing tumor tissue were extracted from whole-slide images. A convolutional neural network employing a contrastive learning paradigm was implemented to extract patch-level morphologic features. These features were aggregated using a vision transformer-based model to predict EGFR mutation status and classify patient cases. The established prediction model was validated on unseen data sets. In internal validation with a cohort from the University of Science and Technology of China (n = 172), the model achieved patient-level areas under the receiver-operating characteristic curve (AUCs) of 0.927 and 0.907, sensitivities of 81.6% and 83.3%, and specificities of 93.0% and 92.3%, for surgical resection and biopsy specimens, respectively, in EGFR mutation subtype prediction. External validation with cohorts from the Second Affiliated Hospital of Anhui Medical University and the First Affiliated Hospital of Wannan Medical College (n = 193) yielded patient-level AUCs of 0.849 and 0.867, sensitivities of 79.2% and 80.7%, and specificities of 91.7% and 90.7% for surgical and biopsy specimens, respectively. Further validation with The Cancer Genome Atlas data set (n = 81) showed an AUC of 0.861, a sensitivity of 84.6%, and a specificity of 90.5%. Deep learning solutions demonstrate potential advantages for automated, noninvasive, fast, cost-effective, and accurate inference of EGFR alterations from histomorphology. Integration of such artificial intelligence frameworks into routine digital pathology workflows could augment existing molecular testing pipelines.

Masked hypergraph learning for weakly supervised histopathology whole slide image classification.

BACKGROUND AND OBJECTIVES: Graph neural network (GNN) has been extensively used in histopathology whole slide image (WSI) analysis due to the efficiency and flexibility in modelling relationships among entities. However, most existing GNN-based WSI analysis methods only consider the pairwise correlation of patches from one single perspective (e.g. spatial affinity or embedding similarity) yet ignore the intrinsic non-pairwise relationships present in gigapixel WSI, which are likely to contribute to feature learning and downstream tasks. The objective of this study is therefore to explore the non-pairwise relationships in histopathology WSI and exploit them to guide the learning of slide-level representations for better classification performance. METHODS: In this paper, we propose a novel Masked HyperGraph Learning (MaskHGL) framework for weakly supervised histopathology WSI classification. Compared with most GNN-based WSI classification methods, MaskHGL exploits the non-pairwise correlations between patches with hypergraph and global message passing conducted by hypergraph convolution. Concretely, multi-perspective hypergraphs are first built for each WSI, then hypergraph attention is introduced into the jointed hypergraph to propagate the non-pairwise relationships and thus yield more discriminative node representation. More importantly, a masked hypergraph reconstruction module is devised to guide the hypergraph learning which can generate more powerful robustness and generalization than the method only using hypergraph modelling. Additionally, a self-attention-based node aggregator is also applied to explore the global correlation of patches in WSI and produce the slide-level representation for classification. RESULTS: The proposed method is evaluated on two public TCGA benchmark datasets and one in-house dataset. On the public TCGA-LUNG (1494 WSIs) and TCGA-EGFR (696 WSIs) test set, the area under receiver operating characteristic (ROC) curve (AUC) were 0.9752±0.0024 and 0.7421±0.0380, respectively. On the USTC-EGFR (754 WSIs) dataset, MaskHGL achieved significantly better performance with an AUC of 0.8745±0.0100, which surpassed the second-best state-of-the-art method SlideGraph+ 2.64%. CONCLUSIONS: MaskHGL shows a great improvement, brought by considering the intrinsic non-pairwise relationships within WSI, in multiple downstream WSI classification tasks. In particular, the designed masked hypergraph reconstruction module promisingly alleviates the data scarcity and greatly enhances the robustness and classification ability of our MaskHGL. Notably, it has shown great potential in cancer subtyping and fine-grained lung cancer gene mutation prediction from hematoxylin and eosin (H&E) stained WSIs.

Genetic associations between Rapid Eye Movement (REM) sleep behavior disorder and cardiovascular diseases.

BACKGROUND: Previous studies revealed that sleep disorders are potential risk factors for cardiovascular diseases, such as obstructive sleep apnea and rapid eye movement (REM) sleep behavior disorder (RBD). However, the causal associations between RBD and cardiovascular diseases remained unknown. MATERIALS AND METHODS: We used the latest and largest summary-level genome-wide association studies of RBD, stroke and its subtypes, coronary artery disease (CAD), myocardial infarction (MI), and heart failure (HF) to select genetic variants as the instrumental variables. Mendelian randomization (MR) analysis was performed to test the causal associations between RBD and the cardiovascular diseases above. Inverse variance weighted method was used as the main analysis. RESULTS: After multiple comparisons, genetically predicted RBD was significantly associated with the risk of HF [odds ratio (OR) = 1.033, 95% CI 1.013-1.052, p = 0.001]. Leave-one-out analysis further supported the robustness of the causal association. Furthermore, we identified a suggestive association between genetically predicted MI and RBD (OR = 0.716, 95% CI 0.546-0.940, p = 0.016). However, in our study no associations were identified of RBD with CAD or stroke and its subtypes. CONCLUSION: Our study highlighted the potential associations between RBD and cardiovascular diseases at genetic level, including HF and MI. More studies were required to clarify the biological mechanisms involved the associations.

Clinical, pathological, and molecular features of central nervous system tumors with BCOR internal tandem duplication.

Central nervous system tumor with BCOR internal tandem duplication (CNS tumor with BCOR-ITD) constitutes a molecularly distinct entity, characterized by internal tandem duplication within exon 15 of the BCOR transcriptional co-repressor gene (BCOR-ITD). The current study aimed to elucidate the clinical, pathological, and molecular attributes of CNS tumors with BCOR-ITD and explore their putative cellular origin. This study cohort comprised four pediatric cases, aged 23 months to 13 years at initial presentation. Magnetic resonance imaging revealed large, well-circumscribed intra-CNS masses localized heterogeneously throughout the CNS. Microscopically, tumors were composed of spindle to ovoid cells, exhibiting perivascular pseudorosettes and palisading necrosis, but lacking microvascular proliferation. Immunohistochemical staining showed diffuse tumor cell expression of BCOR, CD56, CD99, vimentin, and the stem cell markers PAX6, SOX2, CD133 and Nestin, alongside focal positivity for Olig-2, S100, SOX10, Syn and NeuN. Molecularly, all cases harbored BCOR-ITDs ranging from 87 to 119 base pairs in length, including one case with two distinct ITDs. Notably, the ITDs were interrupted by unique 1-3 bp insertions in all cases. In summary, CNS tumors with BCOR-ITD exhibit characteristic clinical, pathological, and molecular features detectable through BCOR immunohistochemistry and confirmatory molecular analyses. Their expression of stem cell markers raises the possibility of an origin from neuroepithelial stem cells rather than representing true embryonal neoplasms.

Preparation and characterization of mouse-derived monoclonal antibodies against the hemagglutinin of the H1N1 influenza virus.

H1N1 influenza virus is a significant global public health concern. Monoclonal antibodies (mAbs) targeting specific viral proteins such as hemagglutinin (HA) have become an important therapeutic strategy, offering highly specific targeting to block viral transmission and infection. This study focused on the development of mAbs targeting HA of the A/Victoria/2570/2019 (H1N1pdm09, VIC-19) strain by utilizing hybridoma technology to produce two mAbs with high binding capacity. Notably, mAb 2B2 has demonstrated a strong affinity for HA proteins in recent H1N1 influenza vaccine strains. In vitro assessments showed that both mAbs exhibited broad-spectrum hemagglutination inhibition and potent neutralizing effects against various vaccine strains of H1N1pdm09 viruses. 2B2 was also effective in animal models, offering both preventive and therapeutic protection against infections caused by recent H1N1 strains, highlighting its potential for clinical application. By individually co-cultivating each of the aforementioned mAbs with the virus in chicken embryos, four amino acid substitution sites in HA (H138Q, G140R, A141E/V, and D187E) were identified in escape mutants, three in the antigenic site Ca2, and one in Sb. The identification of such mutations is pivotal, as it compels further investigation into how these alterations could undermine the binding efficacy and neutralization capacity of antibodies, thereby impacting the design and optimization of mAb therapies and influenza vaccines. This research highlights the necessity for continuous exploration into the dynamic interaction between viral evolution and antibody response, which is vital for the formulation of robust therapeutic and preventive strategies against influenza.

Total Synthesis of Strigolactones via Palladium-Catalyzed Cascade Carbonylative Carbocyclization of Enallenes.

Here we report an efficient route for synthesizing strigolactones (SLs) and their derivatives. Our method relies on a palladium-catalyzed oxidative carbonylation/carbocyclization/carbonylation/alkoxylation cascade reaction, which involves the formation of three new C-C bonds and a new C-O bond while cleaving one C(sp3)-H bond in a single step. With our versatile synthetic strategy, both naturally occurring and artificial SLs were prepared.

Clinical analysis of colistin sulfate in the treatment of pneumonia caused by carbapenem-resistant Gram-negative bacteria.

BACKGROUND: Multidrug-resistant Gram-negative bacteria, exacerbated by excessive use of antimicrobials and immunosuppressants, are a major health threat. AIM: To study the clinical efficacy and safety of colistin sulfate in the treatment of carbapenem-resistant Gram-negative bacilli-induced pneumonia, and to provide theoretical reference for clinical diagnosis and treatment. METHODS: This retrospective analysis involved 54 patients with Gram-negative bacilli pneumonia admitted to intensive care unit of The General Hospital of the Northern Theater Command of the People's Liberation Army of China from August 2020 to June 2022. After bacteriological culture, the patients' airway secretions were collected to confirm the presence of Gram-negative bacilli. The patients were divided into the experimental and control groups according to the medication used. The research group consisted of 28 patients who received polymyxin sulfate combined with other drugs through intravenous, nebulization, or intravenous combined with nebulization, with a daily dosage of 1.5-3.0 million units. The control group consisted of 26 patients who received standard dosages of other antibiotics (including sulbactam sodium for injection, cefoperazone sodium sulbactam for injection, tigecycline, meropenem, or vaborbactam). RESULTS: Of the 28 patients included in the research group, 26 patients showed improvement, treatment was ineffective for two patients, and one patient died, with the treatment efficacy rate of 92.82%. Of the 26 patients in the control group, 18 patients improved, treatment was ineffective for eight patients, and two patients died, with the treatment efficacy rate of 54.9%; significant difference was observed between the two groups (P < 0.05). The levels of white blood cell (WBC), procalcitonin (PCT), and C-reactive protein (CRP) in both groups were significantly lower after treatment than before treatment (P < 0.05), and the levels of WBC, PCT, and CRP in the research group were significantly lower than those in the control group (P < 0.05). Compared with before treatment, there were no significant changes in aspartate aminotransferase, creatinine, and glomerular filtration rate in both groups, while total bilirubin and alanine aminotransferase decreased after treatment (P < 0.05) with no difference between the groups. In patients with good clinical outcomes, the sequential organ failure assessment (SOFA) score was low when treated with inhaled polymyxin sulfate, and specific antibiotic treatment did not improve the outcome. Sepsis and septic shock as well as a low SOFA score were independent factors associated with good clinical outcomes. CONCLUSION: Polymyxin sulfate has a significant effect on the treatment of patients with multiple drug-resistant Gram-negative bacilli pneumonia and other infections in the lungs and is safe and reliable. Moreover, the administration route of low-dose intravenous injection combined with nebulization shows better therapeutic effects and lower adverse reactions, providing new ideas for clinical administration.

Microstructure and Properties of Pressureless-Sintered Zirconium Carbide Ceramics with MoSi2 Addition.

Zirconium carbide (ZrC) ceramics have a high melting point, low neutron absorption cross section, and excellent resistance to the impact of fission products and are considered to be one of the best candidate materials for fourth-generation nuclear energy systems. ZrC ceramics with a high relative density of 99.1% were successfully prepared via pressureless sintering using a small amount of MoSi2 as an additive. The influence of the MoSi2 content on the densification behavior, microstructure, mechanical properties, and thermal properties of ZrC ceramics was systematically investigated. The results show that the densification of ZrC was significantly enhanced by the introduction of MoSi2 due to the formation of a liquid phase during sintering. In addition, the ZrC grains were refined due to the pinning effect of the generated silicon carbide. The flexural strength and Vickers hardness of ZrC ceramics with 2.5 vol% MoSi2 sintered at 1850 °C were 408 ± 12 MPa and 17.1 GPa, respectively, which were approximately 30% and 10% higher compared to the samples without the addition of MoSi2. The improved mechanical properties were mainly attributed to the high relative density (99.1%) and refined microstructure.