Risk factors for mid- and long-term mortality in lung transplant recipients aged 70 years and older.

OBJECTIVES: With increased lung transplantation in those aged 70 and older, limited literature addresses risk factors affecting their survival. Our study aims to identify independent factors impacting mid- and long-term mortality in this elderly population. METHODS: This study analyzed lung transplant patients over 70 from May 2005 to December 2022 using United Network for Organ Sharing data. The 3- or 5-year cohort excluded multi-organ, secondary transplantation and loss to follow-up. Univariable Cox analysis was conducted to assess recipient, donor and transplant factors. Factors with a significance level of P < 0.2 were subsequently included in a multivariable Cox model to identify correlations with 3- and 5-year mortality in patients aged over 70. RESULTS: Multivariable analysis has identified key factors affecting 3- and 5-year mortality in elderly lung transplant patients over 70. Common notable factors include recipient total bilirubin, intensive care unit status at the time of transplantation, donor diabetes, Cytomegalovirus (CMV) mismatch and single lung transplantation. Additionally, Hispanic/Latino patients and ischaemia time of the transplant significantly impact the 3-year mortality, while recipient age, diabetes, nitric oxide use before transplantation and creatinine were identified as unique independent risk factors affecting the 5-year morality. CONCLUSIONS: The study identified several independent risk factors that impact the mid- and long-term survival of lung transplantation for individuals over 70 years. These findings can contribute to the optimization of lung transplant treatment strategies and perioperative management in elderly patients, thereby enhancing the survival rate of this age group.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

AIMS: Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. MATERIALS AND METHODS: We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. RESULTS: The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. CONCLUSIONS: We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images.

Gastric cancer is a significant contributor to cancer-related fatalities globally. The automated segmentation of gastric tumors has the potential to analyze the medical condition of patients and enhance the likelihood of surgical treatment success. However, the development of an automatic solution is challenged by the heterogeneous intensity distribution of gastric tumors in computed tomography (CT) images, the low-intensity contrast between organs, and the high variability in the stomach shapes and gastric tumors in different patients. To address these challenges, we propose a self-attention backward network (SaB-Net) for gastric tumor segmentation (GTS) in CT images by introducing a self-attention backward layer (SaB-Layer) to feed the self-attention information learned at the deep layer back to the shallow layers. The SaB-Layer efficiently extracts tumor information from CT images and integrates the information into the network, thereby enhancing the network's tumor segmentation ability. We employed datasets from two centers, one for model training and testing and the other for external validation. The model achieved dice scores of 0.8456 on the test set and 0.8068 on the external verification set. Moreover, we validated the model's transfer learning ability on a publicly available liver cancer dataset, achieving results comparable to state-of-the-art liver cancer segmentation models recently developed. SaB-Net has strong potential for assisting in the clinical diagnosis of and therapy for gastric cancer. Our implementation is available at https://github.com/TyrionJ/SaB-Net.

A meta-analysis of treatment for early-stage cervical cancer: open versus minimally invasive radical trachelectomy.

BACKGROUND: In previous systematic reviews, meta-analysis was lacking, resulting in the statistical difference between the data of different surgeries being impossible to judge. This meta-analysis aims to contrast the fertility results and cancer outcomes between open and minimally invasive surgery. METHOD: We systematically searched databases including PubMed, Embase, Cochrane, and Scopus to collect studies that included open and minimally invasive radical trachelectomy. A random-effect model calculated the weighted average difference of each primary outcome via Review Manager V.5.4. RESULT: Eight studies (1369 patients) were incorporated into our study. For fertility results, the Open group excels MIS group in pregnancies-Third trimester delivery [OR = 2.68; 95% CI (1.29, 5.59); P = 0.008]. Nevertheless, there is no statistical difference in clinical pregnancy, miscarriage, and second-trimester rate. Concerning cancer outcomes, no difference was detected in the overall survival [OR = 1.56; 95% CI (0.70, 3.45); P = 0.27] and recurrence [OR = 0.63; 95% CI (0.35, 1.12); P = 0.12]. Concerning surgery-related outcomes, the comprehensive effects revealed that the estimated blood loss of the Open group was higher than that of the MIS group[MD = 139.40; 95% CI (79.05, 199.75); P < 0.0001]. However, there was no difference between the postoperative complication rate in the two groups [OR = 1.52; 95% CI (0.89, 2.60); P = 0.12]. CONCLUSION: This meta-analysis suggested that the fertility result of the Open group may be better than the MIS group, while the MIS group has better surgery-related outcomes. Owing to the poor cases of our study, a more robust conclusion requires more relevant articles in the future. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022352999.

TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma.

BACKGROUND AND OBJECTIVES: The pathological diagnosis of renal cell carcinoma is crucial for treatment. Currently, the multi-instance learning method is commonly used for whole-slide image classification of renal cell carcinoma, which is mainly based on the assumption of independent identical distribution. But this is inconsistent with the need to consider the correlation between different instances in the diagnosis process. Furthermore, the problem of high resource consumption of pathology images is still urgent to be solved. Therefore, we propose a new multi-instance learning method to solve this problem. METHODS: In this study, we proposed a hybrid multi-instance learning model based on the Transformer and the Graph Attention Network, called TGMIL, to achieve whole-slide image of renal cell carcinoma classification without pixel-level annotation or region of interest extraction. Our approach is divided into three steps. First, we designed a feature pyramid with the multiple low magnifications of whole-slide image named MMFP. It makes the model incorporates richer information, and reduces memory consumption as well as training time compared to the highest magnification. Second, TGMIL amalgamates the Transformer and the Graph Attention's capabilities, adeptly addressing the loss of instance contextual and spatial. Within the Graph Attention network stream, an easy and efficient approach employing max pooling and mean pooling yields the graph adjacency matrix, devoid of extra memory consumption. Finally, the outputs of two streams of TGMIL are aggregated to achieve the classification of renal cell carcinoma. RESULTS: On the TCGA-RCC validation set, a public dataset for renal cell carcinoma, the area under a receiver operating characteristic (ROC) curve (AUC) and accuracy of TGMIL were 0.98±0.0015,0.9191±0.0062, respectively. It showcased remarkable proficiency on the private validation set of renal cell carcinoma pathology images, attaining AUC of 0.9386±0.0162 and ACC of 0.9197±0.0124. Furthermore, on the public breast cancer whole-slide image test dataset, CAMELYON 16, our model showed good classification performance with an accuracy of 0.8792. CONCLUSIONS: TGMIL models the diagnostic process of pathologists and shows good classification performance on multiple datasets. Concurrently, the MMFP module efficiently diminishes resource requirements, offering a novel angle for exploring computational pathology images.

Siglec-9 acts as an immune-checkpoint molecule on macrophages in glioblastoma, restricting T-cell priming and immunotherapy response.

Neoadjuvant immune-checkpoint blockade therapy only benefits a limited fraction of patients with glioblastoma multiforme (GBM). Thus, targeting other immunomodulators on myeloid cells is an attractive therapeutic option. Here, we performed single-cell RNA sequencing and spatial transcriptomics of patients with GBM treated with neoadjuvant anti-PD-1 therapy. We identified unique monocyte-derived tumor-associated macrophage subpopulations with functional plasticity that highly expressed the immunosuppressive SIGLEC9 gene and preferentially accumulated in the nonresponders to anti-PD-1 treatment. Deletion of Siglece (murine homolog) resulted in dramatically restrained tumor development and prolonged survival in mouse models. Mechanistically, targeting Siglece directly activated both CD4+ T cells and CD8+ T cells through antigen presentation, secreted chemokines and co-stimulatory factor interactions. Furthermore, Siglece deletion synergized with anti-PD-1/PD-L1 treatment to improve antitumor efficacy. Our data demonstrated that Siglec-9 is an immune-checkpoint molecule on macrophages that can be targeted to enhance anti-PD-1/PD-L1 therapeutic efficacy for GBM treatment.

Integrated Multi-Omics Techniques and Network Pharmacology Analysis to Explore the Material Basis and Mechanism of Simiao Pill in the Treatment of Rheumatoid Arthritis.

The Simiao pill (SMP) is a classic prescription that has shown anti-inflammatory, analgesic, and immunomodulatory effects and is clinically used to treat inflammatory diseases, such as rheumatoid arthritis (RA) and gouty arthritis, for which the effects and mechanism of action remain largely unknown. In this study, serum samples from RA rats were analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry based metabolomics technology and liquid chromatography with tandem mass spectrometry proteomics technology together with network pharmacology to explore the pharmacodynamic substances of SMP. To further verify the above results, we constructed a fibroblast-like synoviocyte (FLS) cell model and administered phellodendrine for the test. All these clues suggested that SMP can significantly reduce the level of interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in complete Freund's adjuvant rat serum and improve the degree of foot swelling; combined with metabolomics, proteomics, and network pharmacological technology, it is determined that SMP plays a therapeutic role through the inflammatory pathway, and phellodendrine is found to be one of the pharmacodynamic substances. By constructing an FLS model, it is further determined that phellodendrine could effectively inhibit the activity of synovial cells and reduce the expression level of inflammatory factors by downregulating the expression level of related proteins in the TLR4-MyD88-IRAK4-MAPK signal pathway to alleviate joint inflammation and cartilage injury. Overall, these findings suggested that phellodendrine is an effective component of SMP in the treatment of RA.

A molecular networking-based isolation of gardneria alkaloids from Gardneria distincta and their anti-inflammatory activity.

Gardneria distincta P. T. Li is traditionally applied as a herbal medicine for treatment various ailments, and is mainly distributed in Southwestern China. Under the guided separation of MS/MS-based molecular networking, eight undescribed oxindole alkaloids, gardistines A-H, as well as 17 known alkaloids were discovered from the whole parts of Gardneria distincta. Structural elucidation of these undescribed alkaloids was performed by various spectroscopic methods. Gardistine A is a rare oxindole gardneria alkaloid bearing an ester carbonyl group attached to C-18, which is the second reported alkaloid of oxindole gardneria-type. All of the identified monoterpene indole alkaloids were investigated for their anti-inflammatory activity in LPS-induced RAW 264.7 cells. Gardistines A-B and akuammidine demonstrated significant inhibitory effects on the expressions of nitric oxide, tumor necrosis factor alpha, and interleukin-6 at 20 µM.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives.

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images.

BACKGROUND AND OBJECTIVES: Gastric cancer has high morbidity and mortality compared to other cancers. Accurate histopathological diagnosis has great significance for the treatment of gastric cancer. With the development of artificial intelligence, many researchers have applied deep learning for the classification of gastric cancer pathological images. However, most studies have used binary classification on pathological images of gastric cancer, which is insufficient with respect to the clinical requirements. Therefore, we proposed a multi-classification method based on deep learning with more practical clinical value. METHODS: In this study, we developed a novel multi-scale model called StoHisNet based on Transformer and the convolutional neural network (CNN) for the multi-classification task. StoHisNet adopts Transformer to learn global features to alleviate the inherent limitations of the convolution operation. The proposed StoHisNet can classify the publicly available pathological images of a gastric dataset into four categories -normal tissue, tubular adenocarcinoma, mucinous adenocarcinoma, and papillary adenocarcinoma. RESULTS: The accuracy, F1-score, recall, and precision of the proposed model in the public gastric pathological image dataset were 94.69%, 94.96%, 94.95%, and 94.97%, respectively. We conducted additional experiments using two other public datasets to verify the generalization ability of the model. On the BreakHis dataset, our model performed better compared with other classification models, and the accuracy was 91.64%. Similarly, on the four-classification task on the Endometrium dataset, our model showed better classification ability than others with accuracy of 81.74%. These experiments showed that the proposed model has excellent ability of classification and generalization. CONCLUSION: The StoHisNet model had high performance in the multi-classification on gastric histopathological images and showed strong generalization ability on other pathological datasets. This model may be a potential tool to assist pathologists in the analysis of gastric histopathological images.

Outcomes of minimally invasive total mesoesophageal excision: a propensity score-matched analysis.

BACKGROUND: This study aimed to investigate the safety and efficacy of minimally invasive total mesoesophageal excision (TME) for esophageal cancer. METHODS: We retrospectively collected data from patients with esophageal cancer who underwent esophagectomy at our center between January 2011 and June 2017. Among 611 eligible patients, 302 underwent minimally invasive total mesoesophageal excision (the TME group) and 309 underwent non-total mesoesophageal excision (the NME group). Outcomes were compared after 1-to-1 propensity score matching, and subgroup analyses were performed for cases involving pT1-2 or pT3-4a disease. RESULTS: The propensity score matching produced 249 pairs of patients. The TME group had a shorter operative time (P < 0.001), lower intraoperative bleeding (P < 0.001), and a shorter postoperative hospital stay (P < 0.001). There were no significant differences between the two groups in the number of removed lymph nodes, 30-day mortality, or postoperative complications. In addition, both groups had similar 3-year rates of overall survival (OS) and disease-free survival (DFS). However, the 3-year recurrence rate in the esophageal bed was significantly lower in the TME group (P = 0.033). Furthermore, among patients with pT3-4a disease, the TME group had better 3-year rates of OS, DFS, and recurrence. CONCLUSION: Minimally invasive total mesoesophageal excision appears to be a safe technique that can reduce tumor recurrence in the esophageal bed. Furthermore, this technique provided survival benefits for patients with pT3-4a disease.

Nanostructure and reactivity of soot particles from open burning of household solid waste.

The main purpose of this work was to quantify and characterize chemically and morphologically the emission of soot particles from the open burning of several common solid waste including paperboard, wood, peel, chemical fiber, polyethylene (PE) and polyvinyl chloride (PVC). The experiment was conducted in a laboratory-scale open-burning combustor with a dilution sampling system to obtain soot particles. The thermogravimetric profiles (TGA) showed an increasing order of oxidation reactivity: PE > PVC > fiber > paper ≈ peel > wood. High resolution transmission electron microscopy (HRTEM) images revealed more detailed information about the morphology and the particle size of soot aggregates. Subsequent quantification of nanostructure by fringe analysis showed that plastics generated soot particles with the looser carbon layers with higher tortuosity compared to the three kind of biomass. Raman spectroscopy further confirms the observed differences. In addition, wood soot exhibited the highest content of C-OH group (17.5%) among the six samples (X-Ray photoelectron spectroscopy, XPS), whereas PE and PVC soot exhibited the highest absorption peaks of aliphatic C-H groups (Fourier transform infrared spectroscopy, FTIR). Comparative analysis revealed that the interlayer distance was more important on the evaluation of reactivity than soot morphologies. The present work concluded that the physiochemical characteristics of soot particles releasing during open burning are strongly depending on waste composition and provided new data for the understanding of soot emissions from open burning.

Isolation and Characterization of New Anti-Inflammatory and Antioxidant Components from Deep Marine-Derived Fungus Myrothecium SP. Bzo-l062.

In the present study, four new compounds including a pair of 2-benzoyl tetrahydrofuran enantiomers, namely, (-)-1S-myrothecol (1a) and (+)-1R-myrothecol (1b), a methoxy-myrothecol racemate (2), and an azaphilone derivative, myrothin (3), were isolated along with four known compounds (4-7) from cultures of the deep-sea fungus Myrothecium sp. BZO-L062. Enantiomeric compounds 1a and 1b were separated through normal-phase chiral high-performance liquid chromatography. The absolute configurations of 1a, 1b, and 3 were assigned by ECD spectra. Among them, the new compound 1a and its enantiomer 1b exhibited anti-inflammatory activity, inhibited nitric oxide formation in lipopolysaccharide-treated RAW264.7 cells, and exhibited antioxidant activity in the 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and oxygen radical absorbance capacity assays.

Extremely Robust Gas-Quenching Deposition of Halide Perovskites on Top of Hydrophobic Hole Transport Materials for Inverted (p-i-n) Solar Cells by Targeting the Precursor Wetting Issue.

Lead halide perovskite solar cells afford high power conversion efficiencies, even though the photoactive layer is formed in a solution process. At the same time, solution processing may impose some severe dewetting issues, especially if organic, hydrophobic charge transport layers are considered. Ultimately, very narrow processing windows with a relatively large spread in device performance and a considerable lab-to-lab variation result. Here, we unambiguously identify dimethylsulfoxide (DMSO), which is commonly used as a co-solvent and complexing agent, to be the main reason for dewetting of the precursor solution on hydrophobic hole transport layers, such as polytriarylamine, in a gas-quenching-assisted deposition process. In striking contrast, we will show that N-methyl-2-pyrrolidon (NMP), which has a lower hydrophilic-lipophilic-balance, can be favorably used instead of DMSO to strongly mitigate these dewetting issues. The resulting high-quality perovskite layers are extremely tolerant with respect to the mixing ratio (NMP/dimethylformamide) and other process parameters. Thus, our findings afford an outstandingly robust, easy to use, and fail-safe deposition technique, yielding single (MAPbI3) and double (FA0.94Cs0.06PbI3) cation perovskite solar cells with high efficiencies (∼18.5%). Most notably, the statistical variation of the devices is significantly reduced, even if the deposition process is performed by different persons. We foresee that our results will further the reliable preparation of perovskite thin films and mitigate process-to-process variations that still hinder the prospects of upscaling perovskite solar technology.

Methane Control of Adventitious Rooting Requires γ-Glutamyl Cysteine Synthetase-Mediated Glutathione Homeostasis.

Although the key role of methane (CH4) in the induction of cucumber adventitious rooting has been observed previously, the target molecules downstream of the CH4 action are yet to be fully elucidated. Here, we reported that exogenous glutathione (GSH) induced cucumber adventitious root formation; while l-buthionine-sulfoximine (BSO) treatment inhibited it. BSO is a known inhibitor of γ-glutamyl cysteine synthetase (γ-ECS), an enzyme involved in GSH biosynthesis. Further investigations showed that endogenous GSH content was rapidly increased by CH4 application, which was correlated with the increased CsGSH1 transcript and γ-ECS activity. Mimicking the responses of GSH, CH4 could upregulate cell cycle regulatory genes (CsCDC6, CsCDPK1, CsCDPK5 and CsDNAJ-1) and auxin-response genes (CsAux22D-like and CsAux22B-like). Meanwhile, adventitious rooting-related CsmiR160 and CsmiR167 were increased or decreased, respectively, and contrasting tendencies were observed in the changes of their target genes, that included CsARF17 and CsARF8. The responses above were impaired by the removal of endogenous GSH with BSO, indicating that CH4-triggered adventitious rooting was GSH-dependent. Genetic evidence revealed that in the presence of CH4, Arabidopsis mutants cad2 (a γ-ECS-defective mutant) exhibited, not only the decreased GSH content in vivo, but also the defects in adventitious root formation, both of which were rescued by GSH administration other than CH4. Together, it can be concluded that γ-ECS-dependent GSH homeostasis might be required for CH4-induced adventitious root formation.

A "Triple Trouble" Case of Facioscapulohumeral Muscular Dystrophy Accompanied by Peripheral Neuropathy and Myoclonic Epilepsy.

BACKGROUND: Facioscapulohumeral muscular dystrophy (FSHD) is characterized by asymmetric muscular deficit of facial, shoulder-girdle muscles, and descending to lower limb muscles, but it exists in several extramuscular manifestations or overlapping syndromes. Herein, we report a "complex disease plus" patient with FSHD1, accompanied by peripheral neuropathy and myoclonic epilepsy. METHODS: Standard clinical assessments, particular auxiliary examination, histological analysis, and molecular analysis were performed through the new Comprehensive Clinical Evaluation Form, pulsed-field gel electrophoresis-based Southern blot, Multiplex Ligation-dependent Probe Amplification (MLPA), whole exome sequencing (WES), and targeted methylation sequencing. RESULTS: The patient presented with mild facial weakness, humeral poly-hill sign, scapular winging, peroneal weakness, drop foot, pes cavus, and myoclonic epilepsy. Furthermore, electrophysiology revealed severely demyelinated and axonal injury. The muscle and nerve biopsy revealed broadly fiber Type II grouping atrophy and myelinated nerve fibers that significantly decreased with thin myelinated fibers and onion bulbs changes. Generalized sharp and sharp-slow wave complexes on electroencephalography support the diagnosis toward myoclonic epilepsy. In addition, molecular testing demonstrated a co-segregated 20-kb 4q35-EcoRI fragment and permissive allele A, which corresponded with D4Z4 hypomethylation status in the family. Both the patient's mother and brother only presented the typical FSHD but lacked overlapping syndromes. However, no mutations for hereditary peripheral neuropathy and myoclonic epilepsy were discovered by MLPA and WES. CONCLUSIONS: The present study described a "tripe trouble" with FSHD, peripheral neuropathy, and myoclonic epilepsy, adding the spectrum of overlapping syndromes and contributing to the credible diagnosis of atypical phenotype. It would provide a direct clue on medical care and genetic counseling.

A case report of CRB2 mutation identified in a Chinese boy with focal segmental glomerulosclerosis.

RATIONALE: Focal segmental glomerulosclerosis (FSGS) is a common disease resulting in end-stage renal disease. The incidence of FSGS is increasing in Western countries. The clinical manifestations include proteinuria, hypoproteinemia, oedema, and hypertension. Single-gene heritable mutations are considered to be the source of FSGS pathogenicity according to recent in-depth studies on the pathogenesis. Here, we first reported the case of a Chinese boy whose histology presented with FSGS caused by a compound heterozygous mutation. PATIENT CONCERNS: A 7-year-old Chinese boy was repeatedly admitted to our hospital for fever, cough, and proteinuria since he was 1.6 years old. DIAGNOSES: FSGS was identified by renal biopsy. Whole exome sequencing (WES) showed that a novel mutation of crumbs homolog 2 (CRB2) was identified in a Chinese boy with FSGS. INTERVENTIONS: Patient was treated with low-dose corticosteroid and mycophenolate mofetil for maintenance therapy. OUTCOMES: At last follow-up, protein (+∼++) was observed in his urinalysis. LESSONS: We identified a novel mutation of CRB2 in a Chinese boy with FSGS that had never been described in a previous report. These findings suggested that mutations in recessive disease genes are more frequent among early-onset disease.

Near-room-temperature Chern insulator and Dirac spin-gapless semiconductor: nickel chloride monolayer.

A great obstacle for practical applications of the quantum anomalous Hall (QAH) effect is the lack of suitable QAH materials (Chern insulators) with a large non-trivial band gap, room-temperature magnetic order and high carrier mobility. Based on first-principles calculations it is shown here that a nickel chloride (NiCl3) monolayer has all these characteristics. Thus, the NiCl3 monolayer represents a new class of Dirac materials with Dirac spin-gapless semiconducting properties and high-temperature ferromagnetism (∼400 K). Taking into account the spin-orbit coupling, the NiCl3 monolayer becomes an intrinsic Chern insulator with a large non-trivial band gap of ∼24 meV, corresponding to an operating temperature as high as ∼280 K at which the quantum anomalous Hall effect could be observed. The calculated large non-trivial gap, high Curie temperature and single-spin Dirac states reported herein for the NiCl3 monolayer led us to propose that this material gives a great promise for potential realization of a near-room temperature QAH effect and potential applications in spintronics. Last but not least the calculated Fermi velocities of Dirac fermions of about 4 × 105 m s-1 indicate very high mobility in NiCl3 monolayers.

Skeletal Muscle Magnetic Resonance Imaging of the Lower Limbs in Late-onset Lipid Storage Myopathy with Electron Transfer Flavoprotein Dehydrogenase Gene Mutations.

BACKGROUND: Lipid storage myopathy (LSM) is a genetically heterogeneous group with variable clinical phenotypes. Late-onset multiple acyl-coenzyme A dehydrogenation deficiency (MADD) is a rather common form of LSM in China. Diagnosis and clinical management of it remain challenging, especially without robust muscle biopsy result and genetic detection. As the noninvasion and convenience, muscle magnetic resonance imaging (MRI) is a helpful assistant, diagnostic tool for neuromuscular disorders. However, the disease-specific MRI patterns of muscle involved and its diagnostic value in late-onset MADD have not been systematic analyzed. METHODS: We assessed the MRI pattern and fat infiltration degree of the lower limb muscles in 28 late-onset MADD patients, combined with detailed clinical features and gene spectrum. Fat infiltration degree of the thigh muscle was scored while that of gluteus was described as obvious or not. Associated muscular atrophy was defined as obvious muscle bulk reduction. RESULTS: The mean scores were significantly different among the anterior, medial, and posterior thigh muscle groups. The mean of fat infiltration scores on posterior thigh muscle group was significantly higher than either anterior or medial thigh muscle group (P < 0.001). Moreover, the mean score on medial thigh muscle group was significantly higher than that of anterior thigh muscle group (P < 0.01). About half of the patients displayed fat infiltration and atrophy in gluteus muscles. Of 28 patients, 12 exhibited atrophy in medial and/or posterior thigh muscle groups, especially in posterior thigh muscle group. Muscle edema pattern was not found in all the patients. CONCLUSIONS: Late-onset MADD patients show a typical muscular imaging pattern of fat infiltration and atrophy on anterior, posterior, and medial thigh muscle groups, with major involvement of posterior thigh muscle group and gluteus muscles and a sparing involvement of anterior thigh compartment. Our findings also suggest that muscle MRI of lower limbs is a helpful tool in guiding clinical evaluation on late-onset MADD.

Triterpene-loaded microemulsion using Coix lacryma-jobi seed extract as oil phase for enhanced antitumor efficacy: preparation and in vivo evaluation.

Ganoderma lucidum triterpene-loaded microemulsions (TMEs) using Coix lacryma-jobi (adlay) seed oil as oil phase were prepared, characterized, and evaluated for enhanced antitumor activity. Ternary phase diagrams for the TMEs were constructed and the optimal preparation was developed. Transmission electron microscopy and dynamic light scattering showed that this formulation had a well defined spherical shape, a homogeneous distribution, a small size, and a narrow polydispersity index. The drug-loading rate was determined to be 9.87% by ultraviolet spectrophotometry, and acceptable stability under various stimulations in vitro was confirmed. Importantly, the TME formulation showed a significantly greater antiproliferative effect towards human lung carcinoma (A549) cells and murine lung tumor (Lewis) cells in comparison with suspension formulations containing triterpene and adlay seed oil as a positive control. The half-maximal inhibitory concentration of the TMEs was about 0.62 mg crude drug per mL, being 2.5-fold improved relative to that of the corresponding suspension formulation, but no significant cytotoxicity was observed for the bare microemulsion in A549 cells and Lewis cells. In vivo, the TME formulation showed markedly enhanced antitumor efficacy in a xenograft model of Lewis lung cancer after intragastric administration. Compared with cyclophosphamide, the TME formulation showed similar antitumor activity but less general toxicity. These results indicate the feasibility of using a microemulsion to increase the solubility of triterpene and adlay. TMEs hold promise as an efficient drug delivery system for the treatment of lung cancer.