ABSTRACT
Multidrug and toxin extrusion (MATE) inhibitors improve the antimicrobial susceptibility of drug-resistant bacteria by preventing the efflux of administered antibiotics. In this study, we optimized the chemical structure of a previously identified bacterial-selective MATE inhibitor 1 (EC50 > 30 µM) to improve its activity further. Compound 1 was divided into three fragments (aromatic part, linker part, and guanidine part), and each part was individually optimized. Compound 31 (EC50 = 1.8 µM), a novel pentafluorosulfanyl-containing molecule synthesized following optimized parts, showed antimicrobial activity against MATE-expressing strains at concentrations lower than conventional inhibitor 1 when co-administrated with norfloxacin. Furthermore, 31 was not cytotoxic at effective concentrations. This suggests that compound 31 can be a promising candidate for combating bacterial infections, particularly those resistant to conventional antibiotics by MATE expression.
Subject(s)
Anti-Bacterial Agents , Membrane Transport Proteins , Membrane Transport Proteins/metabolism , Anti-Bacterial Agents/pharmacology , Norfloxacin/pharmacology , Biological Transport , Bacteria/metabolism , Bacterial Proteins/metabolismABSTRACT
OBJECTIVE: The purpose of this study was to evaluate the usefulness of the injection pressure-to-injection rate (IPIR) ratio for the early detection of contrast extravasation at the venipuncture site during contrast-enhanced computed tomography. METHODS: We retrospectively enrolled 57,528 patients who underwent contrast-enhanced computed tomography examinations in a single hospital. The power injector recorded the contrast injection pressure at 0.25-second intervals. We constructed logistic regression models using the IPIR ratio as the independent variable and extravasation occurrence as the dependent variable (IPIR ratio models) at 1, 2, 3, 4, 5, and 6 seconds after the start of contrast administration. Univariate logistic regression models in which injection pressure is used as an independent variable (injection pressure models) were also constructed as a reference baseline. The performance of the models was evaluated with the area under the receiver operating characteristic curves. RESULTS: Of the 57,528 cases, 46,022 were assigned to the training group and 11,506 were assigned to the test group, which included 112 extravasation cases (0.24%) in the training group and 28 (0.24%) in the test group. The area under the receiver operating characteristic curves for the IPIR ratio models and injection pressure models were 0.555 versus 0.563 at t = 1 (P = 0.270), 0.712 versus 0.678 at t = 2 (P = 0.305), 0.758 versus 0.693 at t = 3 (P = 0.032), 0.776 versus 0.688 at t = 4 (P = 0.005), 0.810 versus 0.699 at t = 5 (P = 0.002), and 0.811 versus 0.706 at t = 6 (P = 0.002). CONCLUSIONS: The IPIR ratio models perform better in detecting contrast extravasation at 3 to 6 seconds after the start of contrast administration than injection pressure models.
ABSTRACT
A patient undergoing cord blood transplantation for refractory angioimmunoblastic T-cell lymphoma was subsequently managed with long-term immunosuppressants for chronic graft-versus-host disease (GVHD). On day 591 post-transplant, she exhibited disorientation and cognitive dysfunction. Magnetic resonance imaging (MRI) of the brain revealed two hyperintense foci in the white matter, suggestive of progressive multifocal leukoencephalopathy (PML). However, we did not include PML in the differential diagnosis at that time. Unfortunately, she developed progressive cognitive impairment, and repeated brain MRIs showed a progression in lesion size. She was still taking immunosuppressants to control her GVHD, therefore we suspected PML. The diagnosis of PML was confirmed through the detection of a John Cunningham (JC) virus in the cerebrospinal fluid on day 640 post-transplant. This report highlights the critical need to consider PML in differential diagnoses for post-allogeneic transplant patients, especially those who exhibit progressive neurological symptoms while on prolonged immunosuppressant therapy.
Subject(s)
Cord Blood Stem Cell Transplantation , Graft vs Host Disease , Immunosuppressive Agents , Leukoencephalopathy, Progressive Multifocal , Magnetic Resonance Imaging , Humans , Leukoencephalopathy, Progressive Multifocal/etiology , Leukoencephalopathy, Progressive Multifocal/diagnosis , Leukoencephalopathy, Progressive Multifocal/cerebrospinal fluid , Female , Cord Blood Stem Cell Transplantation/adverse effects , Immunosuppressive Agents/therapeutic use , Immunosuppressive Agents/adverse effects , Graft vs Host Disease/etiology , Lymphoma, T-Cell/therapy , JC Virus/isolation & purification , Diagnosis, Differential , Middle Aged , Brain/diagnostic imaging , Brain/pathologyABSTRACT
Imeglimin is a recently developed anti-diabetic drug that could concurrently promote insulin secretion and insulin sensitivity, while its mechanisms of action are not fully understood. Here we show that imeglimin administration could protect mice from high fat diet-induced weight gain with enhanced energy expenditure and attenuated whitening of brown adipose tissue. Imeglimin administration led to significant alteration of gut microbiota, which included an increase of Akkermansia genus, with attenuation of obesity-associated gut pathologies. Ablation of microbiota by antibiotic treatment partially abrogated the insulin sensitizing effects of imeglimin, while not affecting its actions on body weight gain or brown adipose tissue. Collectively, our results characterize imeglimin as a potential agent promoting energy expenditure and gut integrity, providing new insights into its mechanisms of action.
Subject(s)
Gastrointestinal Microbiome , Triazines , Animals , Mice , Adipose Tissue, Brown , Mice, Obese , Obesity/drug therapy , Weight GainABSTRACT
Fungal contamination in the indoor air of prefabricated temporary houses at the site of the Great East Japan Earthquake revealed extremely high levels compared to those found in conventional residences. We experimentally investigated fungal growth levels on different interior materials to support fungal overgrowth in prefabricated temporary houses. Three species each of allergenic fungi and invasive fungi observed in temporary housing were selected for inoculation tests with various interior materials. The experiments with fungal inoculation were conducted in conformance with standards for industrial products described in the Japanese" JIS Z 2911:2018 Methods of test for fungus resistance" with small modifications. After incubation, visual and stereomicroscopic assessments were performed to determine fungal growth levels. The viability of the fungi varied according to the interior material type. Our findings demonstrate the importance of antifungal measures in indoor environments and the need for additional research on the growth levels of fungal species on various interior materials.
Subject(s)
Earthquakes , Japan , HousingABSTRACT
A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m2, CKD stage G4-5); 172 with moderate renal dysfunction (30 ≤ eGFR < 60 mL/min/1.73 m2, CKD stage G3a/b); and 76 with mild renal dysfunction (eGFR ≥ 60 mL/min/1.73 m2, CKD stage G1-2) participated in this study. The model was applied to the right, left, and both kidneys, as well as to each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for the bilateral kidney models than for the unilateral kidney models. Our deep learning approach using kidney MRI can be applied to classify patients with CKD based on the severity of kidney disease.
Subject(s)
Glomerular Filtration Rate , Kidney , Magnetic Resonance Imaging , Neural Networks, Computer , Renal Insufficiency, Chronic , Severity of Illness Index , Humans , Renal Insufficiency, Chronic/diagnostic imaging , Renal Insufficiency, Chronic/pathology , Magnetic Resonance Imaging/methods , Female , Male , Middle Aged , Kidney/diagnostic imaging , Kidney/pathology , Aged , Adult , Deep Learning , Imaging, Three-Dimensional/methodsABSTRACT
BACKGROUND: Extracellular vesicles (EVs) hold the potential for elucidating the pathogenesis of amyotrophic lateral sclerosis (ALS) and serve as biomarkers. Notably, the comparative and longitudinal alterations in the protein profiles of EVs in serum (sEVs) and cerebrospinal fluid (CSF; cEVs) of sporadic ALS (SALS) patients remain uncharted. Ropinirole hydrochloride (ROPI; dopamine D2 receptor [D2R] agonist), a new anti-ALS drug candidate identified through induced pluripotent stem cell (iPSC)-based drug discovery, has been suggested to inhibit ALS disease progression in the Ropinirole Hydrochloride Remedy for Amyotrophic Lateral Sclerosis (ROPALS) trial, but its mechanism of action is not well understood. Therefore, we tried to reveal longitudinal changes with disease progression and the effects of ROPI on protein profiles of EVs. METHODS: We collected serum and CSF at fixed intervals from ten controls and from 20 SALS patients participating in the ROPALS trial. Comprehensive proteomic analysis of EVs, extracted from these samples, was conducted using liquid chromatography/mass spectrometer (LC/MS). Furthermore, we generated iPSC-derived astrocytes (iPasts) and performed RNA sequencing on astrocytes with or without ROPI treatment. RESULTS: The findings revealed notable disparities yet high congruity in sEVs and cEVs protein profiles concerning disease status, time and ROPI administration. In SALS, both sEVs and cEVs presented elevated levels of inflammation-related proteins but reduced levels associated with unfolded protein response (UPR). These results mirrored the longitudinal changes after disease onset and correlated with the revised ALS Functional Rating Scale (ALSFRS-R) at sampling time, suggesting a link to the onset and progression of SALS. ROPI appeared to counteract these changes, attenuating inflammation-related protein levels and boosting those tied to UPR in SALS, proposing an anti-ALS impact on EV protein profiles. Reverse translational research using iPasts indicated that these changes may partly reflect the DRD2-dependent neuroinflammatory inhibitory effects of ROPI. We have also identified biomarkers that predict diagnosis and disease progression by machine learning-driven biomarker search. CONCLUSIONS: Despite the limited sample size, this study pioneers in reporting time-series proteomic alterations in serum and CSF EVs from SALS patients, offering comprehensive insights into SALS pathogenesis, ROPI-induced changes, and potential prognostic and diagnostic biomarkers.
ABSTRACT
OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-phase sequence. MATERIALS AND METHODS: In this retrospective study, 29 patients who underwent lumbar spine MRI, including an MR bone imaging sequence between January and April 2023, were analyzed. Images were reconstructed with and without SR-DLR (Matrix sizes: 960 × 960 and 320 × 320, respectively). The signal-to-noise ratio (SNR) of the vertebral body and spinal canal and the contrast and contrast-to-noise ratio (CNR) between the vertebral body and spinal canal were quantitatively evaluated. Furthermore, the slope at half-peak points of the profile curve drawn across the posterior border of the vertebral body was calculated. Two radiologists independently assessed image noise, contrast, artifacts, sharpness, and overall image quality of both image types using a 4-point scale. Interobserver agreement was evaluated using weighted kappa coefficients, and quantitative and qualitative scores were compared via the Wilcoxon signed-rank test. RESULTS: SNRs of the vertebral body and spinal canal were notably improved in images with SR-DLR (p < 0.001). Contrast and CNR were significantly enhanced with SR-DLR compared to those without SR-DLR (p = 0.023 and p = 0.022, respectively). The slope of the profile curve at half-peak points across the posterior border of the vertebral body and spinal canal was markedly higher with SR-DLR (p < 0.001). Qualitative scores (noise: p < 0.001, contrast: p < 0.001, artifact p = 0.042, sharpness: p < 0.001, overall image quality: p < 0.001) were superior in images with SR-DLR compared to those without. Kappa analysis indicated moderate to good agreement (noise: κ = 0.56, contrast: κ = 0.51, artifact: κ = 0.46, sharpness: κ = 0.76, overall image quality: κ = 0.44). CONCLUSION: SR-DLR, which is based on k-space data, has the potential to enhance the image quality of lumbar spine MR bone imaging utilizing a 3D gradient echo in-phase sequence. CLINICAL RELEVANCE STATEMENT: The application of SR-DLR can lead to improvements in lumbar spine MR bone imaging quality.
Subject(s)
Deep Learning , Lumbar Vertebrae , Magnetic Resonance Imaging , Humans , Female , Lumbar Vertebrae/diagnostic imaging , Male , Retrospective Studies , Middle Aged , Magnetic Resonance Imaging/methods , Aged , Adult , Signal-To-Noise Ratio , Imaging, Three-Dimensional/methods , Aged, 80 and over , Spinal Diseases/diagnostic imagingABSTRACT
BACKGROUND: The current pipeline for new antibiotics fails to fully address the significant threat posed by drug-resistant Gram-negative bacteria that have been identified by the World Health Organization (WHO) as a global health priority. New antibacterials acting through novel mechanisms of action are urgently needed. We aimed to identify new chemical entities (NCEs) with activity against Klebsiella pneumoniae and Acinetobacter baumannii that could be developed into a new treatment for drug-resistant infections. METHODS: We developed a high-throughput phenotypic screen and selection cascade for generation of hit compounds active against multidrug-resistant (MDR) strains of K. pneumoniae and A. baumannii. We screened compound libraries selected from the proprietary collections of three pharmaceutical companies that had exited antibacterial drug discovery but continued to accumulate new compounds to their collection. Compounds from two out of three libraries were selected using "eNTRy rules" criteria associated with increased likelihood of intracellular accumulation in Escherichia coli. FINDINGS: We identified 72 compounds with confirmed activity against K. pneumoniae and/or drug-resistant A. baumannii. Two new chemical series with activity against XDR A. baumannii were identified meeting our criteria of potency (EC50 ≤50 µM) and absence of cytotoxicity (HepG2 CC50 ≥100 µM and red blood cell lysis HC50 ≥100 µM). The activity of close analogues of the two chemical series was also determined against A. baumannii clinical isolates. INTERPRETATION: This work provides proof of principle for the screening strategy developed to identify NCEs with antibacterial activity against multidrug-resistant critical priority pathogens such as K. pneumoniae and A. baumannii. The screening and hit selection cascade established here provide an excellent foundation for further screening of new compound libraries to identify high quality starting points for new antibacterial lead generation projects. FUNDING: BMBF and GARDP.