Absolute Structures of a Mirror Pair of Infinite Na(H2O)4 + -Connected ε-Keggin-Al13 Species.

The absolute structures of a pair of infinite Na(H2O)4+-connected ε-Keggin-Al13 species (Na-ε-K-Al13) that were inversion structures and mirror images of each other were determined. Single crystals obtained by adding A2SO4 (A = Li, Na, K, Rb, or Cs) solution to NaOH-hydrolyzed AlCl3 solution were subjected to X-ray structure analyses. The statistical results for 36 single crystals showed that all the crystals had almost the same unit cell parameter, belonged to the same F4̅3m space group, and possessed the same structural formula [Na(H2O)4AlO4Al12(OH)24(H2O)12](SO4)4·10H2O. However, the crystals had two inverse absolute structures (denoted A and B), which had a crystallization ratio of 1:1. From Li+ to Cs+, with increasing volume of the cation coexisting in the mother solution, the degree of disorder of the four H2O molecules in the Na(H2O)4+ hydrated ion continuously decreased; they became ordered when the cation was Cs+. Absolute structures A and B are the first two infinite aluminum polycations connected by statistically occupied [(Na1/4)4(H2O)4]+ hydrated ions. The three-dimensional structure of the infinite Na-ε-K-Al13 species can be regarded as the assembly of finite ε-K-Al13 species linked by [(Na1/4)4(H2O)4]+ in a 1:1 ratio. In this assembly, each [(Na1/4)4(H2O)4]+ is connected to four ε-K-Al13 and each ε-K-Al13 is also connected to four [(Na1/4)4(H2O)4]+ in tetrahedral orientations to form a continuous rigid framework structure, which has an inverse spatial orientation between absolute structure A and B. This discovery clarifies that the ε-K-Al13 (or ε-K-GaAl12) species in Na[MO4Al12(OH)24(H2O)12](XO4)4·nH2O (M = Al, Ga; X = S, Se; n = 10-20) exists as discrete groups and deepens understanding of the formation and evolution process of polyaluminum species in forcibly hydrolyzed aluminum salt solution. The reason why Na+ statistically occupies the four sites was examined, and a formation and evolution mechanism of the infinite Na-ε-K-Al13 species was proposed.

The natural polyphenol fisetin in atherosclerosis prevention: a mechanistic review.

The incidence and mortality rate of atherosclerotic cardiovascular disease (ASCVD) is increasing yearly worldwide. Recently, a growing body of evidence has unveiled the anti-atherosclerotic properties of fisetin, a natural polyphenol compound. In this article, we reviewed the pharmacologic actions of fisetin on experimental atherosclerosis and its protective effects on disease-relevant cell types such as endothelial cells, macrophages, vascular smooth muscle cells, and platelets. Based on its profound cardiovascular actions, fisetin holds potential for clinical translation and could be developed as a potential therapeutic option for atherosclerosis and its related complications. Large-scale randomized clinical trials are warranted to ascertain the safety and efficacy of fisetin in patients with or high risk for ASCVD.

Comparative analysis of machine learning algorithms for Alzheimer's disease classification using EEG signals and genetic information.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairments, and behavioral changes. The presence of abnormal beta-amyloid plaques and tau protein tangles in the brain is known to be associated with AD. However, current limitations of imaging technology hinder the direct detection of these substances. Consequently, researchers are exploring alternative approaches, such as indirect assessments involving monitoring brain signals, cognitive decline levels, and blood biomarkers. Recent studies have highlighted the potential of integrating genetic information into these approaches to enhance early detection and diagnosis, offering a more comprehensive understanding of AD pathology beyond the constraints of existing imaging methods. Our study utilized electroencephalography (EEG) signals, genotypes, and polygenic risk scores (PRSs) as features for machine learning models. We compared the performance of gradient boosting (XGB), random forest (RF), and support vector machine (SVM) to determine the optimal model. Statistical analysis revealed significant correlations between EEG signals and clinical manifestations, demonstrating the ability to distinguish the complexity of AD from other diseases by using genetic information. By integrating EEG with genetic data in an SVM model, we achieved exceptional classification performance, with an accuracy of 0.920 and an area under the curve of 0.916. This study presents a novel approach of utilizing real-time EEG data and genetic background information for multimodal machine learning. The experimental results validate the effectiveness of this concept, providing deeper insights into the actual condition of patients with AD and overcoming the limitations associated with single-oriented data.

Novel CRTC1::MRTFB(MKL2) Gene Fusion detected in Myxoid Mesenchymal Neoplasms with Myogenic Differentiation involving Bone and Soft Tissue.

Appropriate classification of fusion-driven bone and soft tissue neoplasms continues to evolve, often relying on the careful integration of morphologic findings with immunohistochemical, molecular, and clinical data. Herein, we present three cases of a morphologically distinct myxoid mesenchymal neoplasm with myogenic differentiation and novel CRTC1::MRTFB (formerly MKL2) gene fusion. Three tumors occurred in 2 female and 1 male patient with a median age of 72 (range: 28-78). Tumors involved the left iliac bone, the right thigh, and the left perianal region with a median size of 4.0 cm (4.0-7.6 cm). While one tumor presented as an incidental finding, the other two tumors were noted given their persistent growth. At the time of last follow-up, one patient was alive with unresected disease at 6 months, one patient was alive without evidence of disease at 12 months after surgery and one patient died of disease 24 months after diagnosis. On histologic sections, the tumors showed multinodular growth and were composed of variably cellular spindle to round-shaped cells with distinct brightly eosinophilic cytoplasm embedded within a myxoid stroma. One tumor showed overt smooth muscle differentiation. Cytologic atypia and mitotic activity ranged from minimal (2 cases) to high (1 case). By immunohistochemistry, the neoplastic cells expressed focal smooth muscle actin, h-caldesmon, and desmin in all tested cases. Skeletal muscle markers were negative. Next-generation sequencing detected nearly identical CRTC1::MRTFB gene fusions in all cases. We suggest that myxoid mesenchymal tumors with myogenic differentiation harboring a CRTC1::MRTFB fusion may represent a previously unrecognized, distinctive entity that involves soft tissue and bone. Continued identification of these novel myxoid neoplasms with myogenic differentiation will be important in determining appropriate classification, understanding biologic potential, and creating treatment paradigms.

Differentiating mixed epithelial and stromal tumor family from predominantly cystic renal cell carcinoma using magnetic resonance imaging-based Bosniak classification system version 2019.

PURPOSE: To differentiate mixed epithelial and stromal tumor family (MESTF) of the kidney from predominantly cystic renal cell carcinoma (RCC) using the magnetic resonance imaging (MRI)-based Bosniak classification system version 2019 (v2019). MATERIALS AND METHODS: The study included 36 consecutive patients with MESTF and 77 with predominantly cystic RCC who underwent preoperative renal MRI. One radiologist evaluated and documented the clinical and MRI characteristics (age, sex, laterality, R.E.N.A.L. Nephrometry Score [RNS], surgical approach, the signal intensity on T2-weighted imaging, restricted diffusion and enhancement features in corticomedullary phase). Blinded to clinical and pathological information, another two radiologists independently evaluated Bosniak category of all masses. Interobserver agreement based on Bosniak classification system v2019 was measured by the weighted Cohen/Conger's Kappa coefficient. Furthermore, predominantly cystic RCCs and MESTFs were divided into low (categories I, II, and IIF) and high-class (categories III, and IV) tumors. The independent sample t test (Mann-Whitney U test) or Pearson Chi-square test (Fisher's exact probability test) was utilized to compare clinical and imaging characteristics between MESTFs and predominantly cystic RCCs. The performance of the Bosniak classification system v2019 in distinguishing MESTF from predominantly cystic RCC was investigated via receiver operating characteristic curve analysis. RESULTS: MESTF and predominantly cystic RCC groups significantly differed in terms of age, lesion size, RNS, restricted diffusion, and obvious enhancement in corticomedullary phase, but not sex, laterality, surgical approach, and the signal intensity on T2WI. Interobserver agreement was substantially based on the Bosniak classification system v2019. There were 24 low-class tumors and 12 high-class tumors in the MESTF group. Meanwhile, 13 low-class tumors and 64 high-class tumors were observed in the predominantly cystic RCC group. The distribution of low- or high-class tumors significantly differed between the MESTF and predominantly cystic RCC groups. Bosniak classification system v2019 had excellent discrimination (cutoff value = category III), and an area under curve value was 0.81; accuracy, 80.5%; sensitivity, 87.0%; and specificity, 66.7%. CONCLUSION: The MRI-based Bosniak classification system v2019 can effectively distinguish MESTF from predominantly cystic RCC if category III was used as a cutoff reference.

Diagnostic Value of Clear Cell Likelihood Score v1.0 and v2.0 for Common Subtypes of Small Renal Masses: A Multicenter Comparative Study.

BACKGROUND: Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension. PURPOSE: To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs. STUDY TYPE: Retrospective. POPULATION: 797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses. FIELD STRENGTH/SEQUENCES: 3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging. ASSESSMENT: Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions. STATISTICAL TESTS: Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05. RESULTS: The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993). CONCLUSION: The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Enhanced Electron Transport and Mitigated Voltage Loss in Perovskite Photovoltaics Using Sb2O5@SnO2 Composite Electron Transport Layer.

The efficacy of electron transport layers (ETLs) is pivotal for optimizing the device performance of perovskite photovoltaic applications. However, colloidal dispersions of SnO2 are prone to aggregation and possess structural defects, such as terminal-hydroxyls (OHT) and oxygen vacancies (VOs), which can degrade the quality of ETLs, impede charge extraction and transport, and affect the nucleation and growth processes of the perovskite layer. In this study, the Sb(OH)4 - ions hydrolyzed from SbCl3 in colloidal dispersion can bind to defect sites and effectively stabilize the SnO2 nanocrystals are demonstrated. Upon oxidative annealing, a Sb2O5@SnO2 composite film is formed, in which the Sb2O5 not only mitigates the aforementioned defects but also broadens the energy range of unoccupied states through its dispersed conduction band. The increased electron affinity (EA) facilitates more efficient capture of photoexcited electrons from the perovskite layer, thus augmenting electron extraction and minimizing electron-hole recombination. As a result, a significant improvement in power conversion efficiency (PCE) from 22.60% to 24.54% is achieved, with an open circuit voltage (VOC) of up to 1.195 V, along with excellent stability of unsealed devices under various conditions. This study provides valuable insights for the understanding and design of ETLs in perovskite photovoltaic applications.

Reg3A Overexpression Facilitates Hepatic Metastasis by Altering Cell Adhesion in LoVo Colon Cancer Cells.

Reg3A is upregulated in various cancers and considered a potential target for antitumor treatments. However, the effect of Reg3A in metastasis has been elusive. This study aims to disclose the role of Reg3A overexpression in hepatic metastasis of LoVo colon cancer cells. A stable cell line of LoVo cells overexpressing Reg3A (LoVo-luc-Reg3A), labeled with luc reporter gene, was constructed. Cell proliferation, apoptosis, migration, and invasion were determined using MTT, EdU, Hoechst's staining, flow cytometry, and transwell assays, respectively. Hepatic metastasis of LoVo-luc-Reg3A cells was investigated in BALB/c nude mice. Living bioluminescence imaging, histological examination, and mRNA sequencing (mRNA-seq) were performed to assess the metastatic efficiency and gene expression alteration. Reg3A content was determined by Western blotting and Enzyme-Linked Immunosorbent Assay. Cell attachment capacity was determined in the Matrigel culture. Reg3A overexpression did not promote LoVo cell proliferation or apoptosis, but facilitated cell migration and invasion. In the hepatic metastasis model, Reg3A overexpression increased the number of metastatic colonies. The result of mRNA-seq suggested 349 differentially expressed genes (DEGs) by Reg3A upregulation, many of which were related to colon adenocarcinoma tumorigenesis compared to normal colon tissue. Gene ontology enrichment assay indicated that the DEGs are mainly associated with cell adhesion, leukocyte regulation, extracellular matrix (ECM) remodeling, integrin binding, and STAT protein binding. Reg3A overexpression led to an enrichment of Reg3A protein in local tumor tissue of liver metastasis and ECM/intracellular space in ex vivo cultured cells. However, Reg3A concentration in serum and culture medium was relatively low. Reg3A overexpression also resulted in an increased number of cells that attach to Matrigel, which was attenuated by treatments of siRNA-Reg3A and single-chain variable fragment against Reg3A. Endogenous Reg3A overexpression facilitates hepatic metastasis of LoVo colon cancer cells. The prometastatic effect could be contributed by Reg3A enrichment in ECM, which alters the cell adhesion behavior.

Overexpression of wild-type HRAS drives non-alcoholic steatohepatitis to hepatocellular carcinoma in mice.

Hepatocellular carcinoma (HCC), a prevalent solid carcinoma of significant concern, is an aggressive and often fatal disease with increasing global incidence rates and poor therapeutic outcomes. The etiology and pathological progression of non-alcoholic steatohepatitis (NASH)-related HCC is multifactorial and multistage. However, no single animal model can accurately mimic the full NASH-related HCC pathological progression, posing considerable challenges to transition and mechanistic studies. Herein, a novel conditional inducible wild-type human HRAS overexpressed mouse model (HRAS-HCC) was established, demonstrating 100% morbidity and mortality within approximately one month under normal dietary and lifestyle conditions. Advanced symptoms of HCC such as ascites, thrombus, internal hemorrhage, jaundice, and lung metastasis were successfully replicated in mice. In-depth pathological features of NASH- related HCC were demonstrated by pathological staining, biochemical analyses, and typical marker gene detections. Combined murine anti-PD-1 and sorafenib treatment effectively prolonged mouse survival, further confirming the accuracy and reliability of the model. Based on protein-protein interaction (PPI) network and RNA sequencing analyses, we speculated that overexpression of HRAS may initiate the THBS1-COL4A3 axis to induce NASH with severe fibrosis, with subsequent progression to HCC. Collectively, our study successfully duplicated natural sequential progression in a single murine model over a very short period, providing an accurate and reliable preclinical tool for therapeutic evaluations targeting the NASH to HCC continuum.

Application of MR images in radiotherapy planning for brain tumor based on deep learning.

PURPOSE: Explore the function and dose calculation accuracy of MRI images in radiotherapy planning through deep learning methods. METHODS: 131 brain tumor patients undergoing radiotherapy with previous MR and CT images were recruited for this study. A new series of MRI from the aligned MR was firstly registered to CT images strictly using MIM software and then resampled. A deep learning method (U-NET) was used to establish a MRI-to-CT conversion model, for which 105 patient images were used as the training set and 26 patient images were used as the tuning set. Data from additional 8 patients were collected as the test set, and the accuracy of the model was evaluated from a dosimetric standpoint. RESULTS: Comparing the synthetic CT images with the original CT images, the difference in dosimetric parameters D98, D95, D2 and Dmean of PTV in 8 patients was less than 0.5%. The gamma passed rates of PTV and whole body volume were: 1%/1 mm: 93.96%±6.75%, 2%/2 mm: 99.87%±0.30%, 3%/3 mm: 100.00%±0.00%; and 1%/1 mm: 99.14%±0.80%, 2%/2 mm: 99.92%±0.08%, 3%/3 mm: 99.99%±0.01%. CONCLUSION: MR images can be used both in delineation and treatment efficacy evaluation and in dose calculation. Using the deep learning way to convert MR image to CT image is a viable method and can be further used in dose calculation.

Detoxification and underlying mechanisms towards toxic alkaloids by Traditional Chinese Medicine processing: A comprehensive review.

BACKGROUND: Alkaloids have attracted enduring interest worldwide due to their remarkable therapeutic effects, including analgesic, anti-inflammatory, and anti-tumor properties, thus offering a rich source for lead compound design and new drug discovery. However, some of these alkaloids possess intrinsic toxicity. Processing (Paozhi) is a pre-treatment step before the application of herbal medicines in traditional Chinese medicine (TCM) clinics, which has been employed for centuries to mitigate the toxicity of alkaloid-rich TCMs. PURPOSE: To explore the toxicity phenotypes, chemical basis, mode of action, detoxification processing methods, and underlying mechanisms, we can gain crucial insights into the safe and rational use of these toxic alkaloid-rich herbs. Such insights have the great potential to offer new strategies for drug discovery and development, ultimately improving the quality of life for millions of people. METHODS: Literatures published or early accessed until December 31, 2023, were retrieved from databases including PubMed, Web of Science, and CNKI. The following keywords, such as "toxicity", "alkaloid", "detoxification", "processing", "traditional Chinese medicine", "medicinal plant", and "plant", were used in combination or separately for screening. RESULTS: Toxicity of alkaloids in TCM includes hepatotoxicity, nephrotoxicity, neurotoxicity, cardiotoxicity, and other forms of toxicity, primarily induced by pyrrolizidines, quinolizidines, isoquinolines, indoles, pyridines, terpenoids, and amines. Factors such as whether the toxic-alkaloid enriched part is limited or heat-sensitive, and whether toxic alkaloids are also therapeutic components, are critical for choosing appropriate detoxification processing methods. Mechanisms of alkaloid detoxification includes physical removal, chemical decomposition or transformation, as well as biological modifications. CONCLUSION: Through this exploration, we review toxic alkaloids and the mechanisms underlying their toxicity, discuss methods to reduce toxicity, and unravel the intricate mechanisms behind detoxification. These offers insights into the quality control of herbs containing toxic alkaloids, safe and rational use of alkaloid-rich TCMs in clinics, new strategies for drug discovery and development, and ultimately helping improve the quality of life for millions of people.

Celastrol induced the autophagy of spermatogonia cells contributed to tripterygium glycosides-related testicular injury.

Tripterygium glycosides (TG) is extracted from the roots of Chinese herbal medicine named Tripterygium wilfordii Hook F (TwHF). TG tablets are the representative TwHF-based agents with anti-inflammatory and immunomodulatory activities for treating rheumatoid arthritis. Although the curative effect of TG is remarkable, the clinical application is limited by a variety of organ toxicity. One of the most serious side-effects induced by TG is damage of the male reproductive system and the toxic mechanism is still not fully elucidated. TG-induced testicular injury was observed in male mice by treated with different concentrations of TG. The results showed that TG induced a significant decrease in testicular index. Pathological observation showed that spermatogenic cells were obviously shed, arranged loosely, and the spermatogenic epithelium was thin compared with control mice. In addition, the toxic effect of TG on mouse spermatogonia GC-1 cells was investigated. The results displayed that TG induced significant cytotoxicity in mouse GC-1 cells. To explore the potential toxic components that triggered testicular injury, the effects of 8 main components of TG on the viability of GC-1 cells were detected. The results showed that celastrol was the most toxic component of TG to GC-1 cells. Western blot analysis showed that LC3-II and the ratio of LC3-II/LC3-I were significantly increased and the expression level of p62 were decreased in both TG and celastrol treated cells, which indicated the significant activation of autophagy in spermatogonia cells. Therefore, autophagy plays an important role in the testicular injury induced by TG, and inhibition of autophagy is expected to reduce the testicular toxicity of TG.

Translational PET Imaging of Nectin-4 Expression in Multiple Different Cancers with 68Ga-N188.

Nectin cell adhesion molecule 4 (nectin-4) is a transmembrane protein overexpressed on a variety of cancers and plays an important role in oncogenic and metastatic processes. The nectin-4-targeted antibody-drug conjugate enfortumab vedotin has been approved for treating locally advanced or metastatic urothelial cancer, but the efficacy in other types of cancer remains to be explored. The aim of this study was to evaluate the feasibility of nectin-4-targeted PET imaging with 68Ga-N188 as a noninvasive method to quantify membranous nectin-4 expression in multiple tumor types-an approach that may provide insight for patient stratification and treatment selection. Methods: Sixty-two patients with 16 types of cancer underwent head-to-head 68Ga-N188 and 18F-FDG PET/CT imaging for initial staging or detection of recurrence and metastases. Correlation between lesion SUVmax and nectin-4 expression determined by immunohistochemistry staining was analyzed in 36 of 62 patients. Results: The SUVmax of 68Ga-N188 had a positive correlation with membranous nectin-4 expression in the various tumor types tested (r = 0.458; P = 0.005), whereas no association was observed between the SUVmax and cytoplasmic nectin-4 expression. The detection rates for patient-based analysis of 68Ga-N188 and 18F-FDG PET/CT examinations were comparable (95.00% [57/60] vs. 93.33% [56/60]). In patients with pancreatic cancer, 68Ga-N188 exhibited a potential advantage for detecting residual or locally recurrent tumors; this advantage may assist in clinical decision-making. Conclusion: The correlation between nectin-4-targeted 68Ga-N188 PET imaging and membranous nectin-4 expression indicates the potential of 68Ga-N188 as an effective tool for selecting patients who may benefit from enfortumab vedotin treatment. The PET imaging results provided evidence to explore nectin-4-targeted therapy in a variety of tumors. 68Ga-N188 may improve the restaging of pancreatic cancer but requires further evaluation in a powered, prospective setting.

Flexible SERS sensor based on the photodecoration of Au-NPs on Co3O4 NWs/carbon fiber cloth for the ultrasensitive detection of methylene blue in the curved fish surfaces.

BACKGROUND: Development of flexible platform via the surface-enhanced Raman spectroscopy (SERS) technique has gained enormous attention as a low-cost and portable substrate for a wide range application. In particular, the fabrication of semiconductors and tuning their surface morphologies with plasmonic nanoparticles are considered to be a fascinating strategy to create numerous hotspots to yield superior SERS enhancement. RESULTS: This work involved fabricating a flexible SERS active substrate using the carbon fiber cloth (CFC), which is hydrothermally grown with cobalt oxide nanowires (Co3O4 NWs) and photodecorated with plasmonic gold nanoparticles (Au-NPs) for the ultrasensitive detection of organic dye, methylene blue (MB). The proposed substrate exhibits high enhancement factor (4.5 × 1010), low limit of detection (1.42 × 10-10 M), good uniformity (6.27 %), superior reproducibility (6.30 %) and demonstrate an excellent mechanical strength up to 40 cycles towards the MB detection. The residues of the MB are directly detected on the fish surfaces by adopting a facile swab-sampling technique. Additionally, the proposed flexible SERS sensor exhibit a successful photodegradation of MB at 90 min under UVC light irradiation. SIGNIFICANCE AND NOVELTY: The proposed flexible SERS methodology for detecting MB in the curved surfaces exhibited a superior SERS enhancement owing to the synergistic effect raised from the Co3O4 NWs (chemical enhancement) and Au NPs (electromagnetic enhancement). These findings indicate that the CFC-based flexible SERS sensor is a promising candidate for detecting various organic pollutants in real-time and on non-planar surfaces.

Effect of ceftazidime-avibactam combined with different antimicrobials against carbapenem-resistant Klebsiella pneumoniae.

This study aimed to assess the in vitro efficacy of ceftazidime-avibactam (CZA) in combination with various antimicrobial agents against carbapenem-resistant Klebsiella pneumoniae (CRKP). We selected 59 clinical CRKP isolates containing distinct drug resistance mechanisms. The minimum inhibitory concentrations (MICs) of meropenem (MEM), colistin (COL), eravacycline (ERA), amikacin (AK), fosfomycin (FOS), and aztreonam (ATM), both individually and in combination with CZA, were tested using the checkerboard method. The interactions of antimicrobial agent combinations were assessed by fractional inhibitory concentration index (FICI) and susceptible breakpoint index (SBPI). The time-kill curve assay was employed to dynamically evaluate the effects of these drugs alone and in combination format. In the checkerboard assay, the combination of CZA+MEM showed the highest level of synergistic effect against both KPC-producing and carbapenemase-non-producing isolates, with synergy rates of 91.3% and 100%, respectively. Following closely was the combination of FOS+CZA . For metallo-beta-lactamases (MBLs) producing strains, ATM+CZA displayed complete synergy, while the combination of MEM+CZA showed a synergy rate of only 57.14% for NDM-producing strains and 91.67% for IMP-producing strains. In the time-kill assay, MEM+CZA also demonstrated significant synergistic effects against the two KPC-2-producing isolates (Y070 and L70), the two carbapenemase-non-producing isolates (Y083 and L093), and the NDM-1-producing strain L13, with reductions in log10 CFU/mL exceeding 10 compared to the control. Against the IMP-producing strain Y047, ATM+CZA exhibited the highest synergistic effect, resulting in a log10 CFU/mL reduction of 10.43 compared to the control. The combination of CZA and MEM exhibited good synergistic effects against KPC-producing and non-enzyme-producing strains, followed by the FOS+CZA combination. Among MBL-producing strains, ATM+CZA demonstrated the most pronounced synergistic effect. However, the combinations of CZA with ERA, AK, and COL show irrelevant effects against the tested clinical isolates. IMPORTANCE: Our study confirmed the efficacy of the combination CZA+MEM against KPC-producing and non-carbapenemase-producing strains. For metalloenzyme-producing strains, CZA+ATM demonstrated the most significant synergy. Additionally, CZA exhibited a notable synergy effect when combined with FOS. These combination therapies present promising new options for the treatment of CRKP infection.

Coordination cages integrated into swelling poly(ionic liquid)s for guest encapsulation and separation.

Coordination cages have been widely reported to bind a variety of guests, which are useful for chemical separation. Although the use of cages in the solid state benefits the recycling, the flexibility, dynamicity, and metal-ligand bond reversibility of solid-state cages are poor, preventing efficient guest encapsulation. Here we report a type of coordination cage-integrated solid materials that can be swelled into gel in water. The material is prepared through incorporation of an anionic FeII4L6 cage as the counterion of a cationic poly(ionic liquid) (MOC@PIL). The immobilized cages within MOC@PILs have been found to greatly affect the swelling ability of MOC@PILs and thus the mechanical properties. Importantly, upon swelling, the uptake of water provides an ideal microenvironment within the gels for the immobilized cages to dynamically move and flex that leads to excellent solution-level guest binding performances. This concept has enabled the use of MOC@PILs as efficient adsorbents for the removal of pollutants from water and for the purification of toluene and cyclohexane. Importantly, MOC@PILs can be regenerated through a deswelling strategy along with the recycling of the extracted guests.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.