The role of iron overload and ferroptosis in arrhythmia pathogenesis.

Ferroptosis is a newly discovered form of programmed cell death triggered by intracellular iron overload, which leads to the accumulation of lipid peroxides in various cells. It has been implicated in the pathogenesis and progression of various diseases, including tumors, neurological disorders, and cardiovascular diseases. The intricate mechanism underlying ferroptosis involves an imbalance between the oxidation and antioxidant systems, disturbances in iron metabolism, membrane lipid peroxidation, and dysregulation of amino acid metabolism. We highlight the key molecular mechanisms governing iron overload and ferroptosis, and discuss potential molecular pathways linking ferroptosis with arrhythmias.

VENet: Variational energy network for gland segmentation of pathological images and early gastric cancer diagnosis of whole slide images.

BACKGROUND AND OBJECTIVE: Gland segmentation of pathological images is an essential but challenging step for adenocarcinoma diagnosis. Although deep learning methods have recently made tremendous progress in gland segmentation, they have not given satisfactory boundary and region segmentation results of adjacent glands. These glands usually have a large difference in glandular appearance, and the statistical distribution between the training and test sets in deep learning is inconsistent. These problems make networks not generalize well in the test dataset, bringing difficulties to gland segmentation and early cancer diagnosis. METHODS: To address these problems, we propose a Variational Energy Network named VENet with a traditional variational energy Lv loss for gland segmentation of pathological images and early gastric cancer detection in whole slide images (WSIs). It effectively integrates the variational mathematical model and the data-adaptability of deep learning methods to balance boundary and region segmentation. Furthermore, it can effectively segment and classify glands in large-size WSIs with reliable nucleus width and nucleus-to-cytoplasm ratio features. RESULTS: The VENet was evaluated on the 2015 MICCAI Gland Segmentation challenge (GlaS) dataset, the Colorectal Adenocarcinoma Glands (CRAG) dataset, and the self-collected Nanfang Hospital dataset. Compared with state-of-the-art methods, our method achieved excellent performance for GlaS Test A (object dice 0.9562, object F1 0.9271, object Hausdorff distance 73.13), GlaS Test B (object dice 94.95, object F1 95.60, object Hausdorff distance 59.63), and CRAG (object dice 95.08, object F1 92.94, object Hausdorff distance 28.01). For the Nanfang Hospital dataset, our method achieved a kappa of 0.78, an accuracy of 0.9, a sensitivity of 0.98, and a specificity of 0.80 on the classification task of test 69 WSIs. CONCLUSIONS: The experimental results show that the proposed model accurately predicts boundaries and outperforms state-of-the-art methods. It can be applied to the early diagnosis of gastric cancer by detecting regions of high-grade gastric intraepithelial neoplasia in WSI, which can assist pathologists in analyzing large WSI and making accurate diagnostic decisions.

Novel 4-Aryl-4H-chromene derivative displayed excellent in vivo anti-glioblastoma efficacy as the microtubule-targeting agent.

In this study, a series of novel 4-Aryl-4H-chromene derivatives (D1-D31) were designed and synthesized by integrating quinoline heterocycle to crolibulin template molecule based on the strategy of molecular hybridization. One of these compounds D19 displayed positive antiproliferative activity against U87 cancer cell line (IC50 = 0.90 ± 0.03 µM). Compound D19 was verified as the microtubule-targeting agent through downregulating tubulin related genes of U87 cells, destroying the cytoskeleton of tubulins and interacting with the colchicine-binding site to inhibit the polymerization of tubulins by transcriptome analysis, immune-fluorescence staining, microtubule dynamics and EBI competition assays as well as molecular docking simulations. Moreover, compound D19 induced G2/M phase arrest, resulted in cell apoptosis and inhibited the migration of U87 cells by flow cytometry analysis and wound healing assays. Significantly, compound D19 dose-dependently inhibited the tumor growth of orthotopic glioma xenografts model (GL261-Luc) and effectively prolonged the survival time of mice, which were extremely better than those of positive drug temozolomide (TMZ). Compound D19 exhibited potent in vivo antivascular activity as well as no observable toxicity. Furthermore, the results of in silico simulation studies and P-gp transwell assays verified the positive correlation between compound D19's Blood-Brain Barrier (BBB) permeability and its in vivo anti-GBM activity. Overall, compound D19 can be used as a promising anti-GBM lead compound for the treatment of glioblastoma.

Analysis of differentially expressed genes in torn rotator cuff tendon tissues in diabetic patients through RNA-sequencing.

BACKGROUND: Rotator cuff tears (RCT) is a common musculoskeletal disorder in the shoulder which cause pain and functional disability. Diabetes mellitus (DM) is characterized by impaired ability of producing or responding to insulin and has been reported to act as a risk factor of the progression of rotator cuff tendinopathy and tear. Long non-coding RNAs (lncRNAs) are involved in the development of various diseases, but little is known about their potential roles involved in RCT of diabetic patients. METHODS: RNA-Sequencing (RNA-Seq) was used in this study to profile differentially expressed lncRNAs and mRNAs in RCT samples between 3 diabetic and 3 nondiabetic patients. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed to annotate the function of the differentially expressed genes (DEGs). LncRNA-mRNA co-expression network and competing endogenous RNA (ceRNA) network were constructed to elucidate the potential molecular mechanisms of DM affecting RCT. RESULTS: In total, 505 lncRNAs and 388 mRNAs were detected to be differentially expressed in RCT samples between diabetic and nondiabetic patients. GO functional analysis indicated that related lncRNAs and mRNAs were involved in metabolic process, immune system process and others. KEGG pathway analysis indicated that related mRNAs were involved in ferroptosis, PI3K-Akt signaling pathway, Wnt signaling pathway, JAK-STAT signaling pathway and IL-17 signaling pathway and others. LncRNA-mRNA co-expression network was constructed, and ceRNA network showed the interaction of differentially expressed RNAs, comprising 5 lncRNAs, 2 mRNAs, and 142 miRNAs. TF regulation analysis revealed that STAT affected the progression of RCT by regulating the apoptosis pathway in diabetic patients. CONCLUSIONS: We preliminarily dissected the differential expression profile of lncRNAs and mRNAs in torn rotator cuff tendon between diabetic and nondiabetic patients. And the bioinformatic analysis suggested some important RNAs and signaling pathways regarding inflammation and apoptosis were involved in diabetic RCT. Our findings offer a new perspective on the association between DM and progression of RCT.

Synthesis, Herbicidal Activity against Barnyard Grass, and Photolytic Behavior of Aryl 2,6-Dipyrimidinoxybenzoates.

In this study, we investigated the characteristics and herbicidal potential of bispyribac phenolic esters, which belong to the 2-(pyrimidin-2-yloxy)benzoic acid (PYB) class of acetohydroxyacid synthase (AHAS-)-inhibiting herbicides. These herbicides are primarily used for controlling Poaceae and broadleaf weeds. Among them, bispyribac-sodium stands out as a representative in this class. Surprisingly, other bispyribac esters, including alkanol and phenol esters exhibit considerably reduced herbicidal activity compared to bispyribac-sodium. In contrast, oxime esters (e.g., pyribenzoxim) demonstrate high activity. To further understand and develop novel PYB herbicides, we synthesized and screened a series of bispyribac phenolic esters while investigating their photochemical behaviors. Several compounds displayed excellent herbicidal activity, with compounds Ia-19 and Ic showing impressive 90% effective dosages for fresh weight inhibition of barnyard grass, measuring 0.55 and 0.60 g a.i./hm2, respectively. These values were approximately half of bispyribac-sodium or pyribenzoxim. The results indicate that the herbicidal activity of phenolic esters is influenced by both their binding ability to the AHAS enzyme and their decomposition into bispyribac acid. For instance, bispyribac phenol ester exhibited considerably reduced receptor affinity compared to bispyribac-sodium, and faced challenges in transforming into bispyribac acid, explaining its diminished herbicidal activity. However, introducing a photosensitive nitro group led to a complete transformation. This modification improved its affinity with AHAS and accelerated its decomposition into bispyribac acid, further accelerated by photocatalysis. Consequently, nitro-containing compounds displayed heightened herbicidal activity. The findings from this study open possibilities for structural optimization of phenolic esters through quantitative structure-activity relationship analysis, potentially regulating their activity-releasing period. Furthermore, the high activity of aromatic heterocyclic esters offers new insights into developing novel PYB herbicides.

High contribution of new particle formation to ultrafine particles in four seasons in an urban atmosphere in south China.

Ultra fine particles (UFP) cover the size range of both nucleation mode particles (NUC, Dp < 25 nm) and Aitken mode particles (AIT, 25 nm < Dp < 100 nm), and play important roles in radiative forcing and human health. In this study, we identified new particle formation (NPF) events and undefined events, explored their potential formation mechanism, and quantified their contributions to UFP number concentration (NUFP) in urban Dongguan of the Pearl River Delta (PRD) region. Field campaigns were carried out in four seasons in 2019 to measure particle number concentration in the size range of 4.7-673.2 nm, volatile organic compounds (VOCs), gaseous pollutants, chemical compositions in PM2.5, and meteorological parameters. The frequency of the occurrence of NPF, as indicated by a significant increase in NUC number concentration (NNUC), was 26 %, and that of the undefined event, as indicated by substantial increases in NNUC or AIT number concentration (NAIT), was 32 % during the whole campaign period. The NPF events mainly occurred in autumn (with a frequency of 59 %) and winter (33 %) and only occasionally in spring (4 %) and summer (4 %). On the contrary, the frequencies of the undefined events were higher in spring (52 %) and summer (38 %) than in autumn (19 %) and winter (22 %). The burst periods of the NPF events mainly occurred before 11:00 Local Time (LT), while those of the undefined events mainly occurred after 11:00 LT. Accompanied to NPF events were low concentrations of VOCs and high concentrations of O3. The undefined events by NUC or AIT were associated with the upwind transport of newly formed particles. Source apportionment analysis suggested that NPF and undefined events were the largest contributor to NNUC (51 ± 28 %), NAIT (41 ± 26 %), and NUFP (45 ± 27 %), while coal combustion and biomass burning, and traffic emission were the second largest contributor to NNUC (22 ± 20 %) and NAIT (39 ± 28 %), respectively.

Mitochondria-Targeting Pyroptosis Amplifier of Lonidamine-Modified Black Phosphorus Nanosheets for Glioblastoma Treatments.

Pyroptosis is accompanied by immunogenic mediators' release and serves as an innovative strategy to reprogram tumor microenvironments. However, damaged mitochondria, the origin of pyroptosis, are frequently eliminated by mitophagy, which will severely impair pyroptosis-elicited immune activation. Herein, black phosphorus nanosheets (BP) are employed as a pyroptosis inducer delivery and mitophagy flux blocking system since the degradation of BP could impair lysosomal function by altering the pH within lysosomes. The pyroptosis inducer of lonidamine (LND) was precoupled with the mitochondrial target moiety of triphenylphosphonium to facilitate the occurrence of pyroptosis. The mitochondria-targeting LND-modified BP (BPTLD) were further encapsulated into the macrophage membrane to endow the BPTLD with blood-brain barrier penetration and tumor-targeting capability. The antitumor activities of membrane-encapsulated BPTLD (M@BPTLD) were investigated using a murine orthotopic glioblastoma model. The results demonstrated that the engineered nanosystem of M@BPTLD could target the mitochondria, and induce as well as reinforce pyroptosis via mitophagy flux blocking, thereby boosting the release of immune-activated factors to promote the maturation of dendritic cells. Furthermore, upon near-infrared (NIR) irradiation, M@BPTLD induced stronger mitochondrial oxidative stress, which further advanced robust immunogenic pyroptosis in glioblastoma cells. Thus, this study utilized the autophagy flux inhibition and phototherapy performance of BP to amplify LND-mediated pyroptosis, which might greatly contribute to the development of pyroptosis nanomodulators.

Stem Cell Applications and Tenogenic Differentiation Strategies for Tendon Repair.

Tendons are associated with a high injury risk because of their overuse and age-related tissue degeneration. Thus, tendon injuries pose great clinical and economic challenges to the society. Unfortunately, the natural healing capacity of tendons is far from perfect, and they respond poorly to conventional treatments when injured. Consequently, tendons require a long period of healing and recovery, and the initial strength and function of a repaired tendon cannot be completely restored as it is prone to a high rate of rerupture. Nowadays, the application of various stem cell sources, including mesenchymal stem cells (MSCs) and embryonic stem cells (ESCs), for tendon repair has shown great potential, because these cells can differentiate into a tendon lineage and promote functional tendon repair. However, the mechanism underlying tenogenic differentiation remains unclear. Moreover, no widely adopted protocol has been established for effective and reproducible tenogenic differentiation because of the lack of definitive biomarkers for identifying the tendon differentiation cascades. This work is aimed at reviewing the literature over the past decade and providing an overview of background information on the clinical relevance of tendons and the urgent need to improve tendon repair; the advantages and disadvantages of different stem cell types used for boosting tendon repair; and the unique advantages of reported strategies for tenogenic differentiation, including growth factors, gene modification, biomaterials, and mechanical stimulation.

Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal.

Low-cost air quality (LCAQ) sensors are increasingly being used for community air quality monitoring. However, data collected by low-cost sensors contain significant noise, and proper calibration of these sensors remains a widely discussed, but not yet fully addressed, area of concern. In this study, several LCAQ sensors measuring nitrogen dioxide (NO2) and ozone (O3) were deployed in six cities in the United States (Atlanta, GA; New York City, NY; Sacramento, CA; Riverside, CA; Portland, OR; Phoenix, AZ) to evaluate the impacts of different climatic and geographical conditions on their performance and calibration. Three calibration methods were applied, including regression via linear and polynomial models and random forest methods. When signals from carbon monoxide (CO) sensors were included in the calibration models for NO2 and O3 sensors, model performance generally increased, with pronounced improvements in selected cities such as Riverside and New York City. Such improvements may be due to (1) temporal co-variation between concentrations of CO and NO2 and/or between CO and O3; (2) different performance levels of low-cost CO, NO2, and O3 sensors; and (3) different impacts of environmental conditions on sensor performance. The results showed an innovative approach for improving the calibration of NO2 and O3 sensors by including CO sensor signals into the calibration models. Community users of LCAQ sensors may be able to apply these findings further to enhance the data quality of their deployed NO2 and O3 monitors.

Fine particulate pollution driven by nitrate in the moisture urban atmospheric environment in the Pearl River Delta region of south China.

To identify potential sources of fine particles (PM2.5, with aerodynamic diameter (Da) ≤ 2.5 µm) in urban Dongguan of south China, a comprehensive campaign was carried out in the whole 2019. Hourly PM2.5 and its dominant chemical components including organic carbon (OC), elemental carbon (EC), water-soluble inorganic ions (WSIIs) and thirteen elements were measured using online instruments. Gaseous pollutants including NH3, HNO3, NO2, NO and O3 and meteorological parameters were also synchronously measured. PM2.5 was dominated by carbonaceous aerosols in summer and by WSIIs in the other seasons. PM2.5 and its dominant chemical components mostly peaked around noon (10:00-14:00 LST). Furthermore, high PM2.5 levels during the daytime were closely related with the increased NO3- levels. The high mass concentrations of NO3- in urban Dongguan during the daytime were likely related with regional transport of NO3- from suburban Dongguan, which was originated from the reaction between NO2 and O3 under the moisture condition during the nighttime. Seven major source factors for PM2.5 including secondary sulfate, ship emission, traffic emission, secondary nitrate, industrial processes, soil dust and coal combustion were identified by positive matrix factorization (PMF) analysis, which contributed 26 ± 14%, 16 ± 16%, 16 ± 10%, 14 ± 11%, 12 ± 11%, 8 ± 6% and 8 ± 6%, respectively, to annual PM2.5 mass concentration. Although secondary sulfate contributed much more than secondary nitrate to PM2.5 on annual basis, the latter exceeded the former source factor when daily PM2.5 mass concentration was higher than 60 µg m-3, indicating the critical role nitrate played in PM2.5 episode events.

Fabrication of magnesium-doped porous polylactic acid microsphere for bone regeneration.

Biodegradable polymer microspheres that can be used as drug carriers are of great importance in biomedical applications, however, there are still challenges in controllable preparation of microsphere surface morphology and improvement of bioactivity. In this paper, firstly, poly(L-lactic acid) (PLLA) was synthesised by ring-opening polymerisation under anhydrous anaerobic conditions and further combined with the emulsion method, biodegradable PLLA microspheres (PM) with sizes ranging from 60-100 µm and with good sphericity were prepared. In addition, to further improve the surface morphology of PLLA microspheres and enhance their bioactivity, functionalised porous PLLA microspheres loaded with magnesium oxide (MgO)/magnesium carbonate (MgCO3) (PMg) were also prepared by the emulsion method. The results showed that the loading of MgO/MgCO3 resulted in the formation of a porous structure on the surface of the microspheres (PMg) and the dissolved Mg2+ could be released slowly during the degradation of microspheres. In vitro cellular experiments demonstrated the good biocompatibility of PM and PMg, while the released Mg2+ further enhanced the anti-inflammatory effect and osteogenic activity of PMg. Functionalised PMg not only show promise for controlled preparation of drug carriers, but also have translational potential for bone regeneration.

Global Research Trends in Tendon Stem Cells from 1991 to 2020: A Bibliometric and Visualized Study.

Background: Tendinopathy is a disabling musculoskeletal disorder affecting the athletics and general populations. There have been increased studies using stem cells in treating tendon diseases. The aim of this bibliometric and visualized study is to comprehensively investigate the current status and global trends of research in tendon stem cells. Methods: Publications related to tendon stem cells from 1991 to 2020 were retrieved from Web of Science and then indexed using a bibliometric methodology. VOSviewer software was used to conduct the visualized study, including coauthorship, cocitation, and cooccurrence analysis and to analyze the publication trends of research in tendon stem cells. Results: In total, 2492 articles were included and the number of publications increased annually worldwide. The United States made the largest contribution to this field, with the most publications (938 papers, 37.64%), citation frequency (68,195 times), and the highest H-index (103). The most contributive institutions were University of Pittsburgh (96 papers), Zhejiang University (70 papers), Shanghai Jiao Tong University, and Chinese University of Hong Kong (both 64 papers). The Journal of Orthopaedic Research published the most relative articles. Studies could be classified into five clusters: "Animal study," "Tissue engineering," "Clinical study," "Mechanism research," and "Stem cells research", which show a balanced development trend. Conclusion: Publications on tendon stem cells may reached a platform based on current global trends. According to the inherent changes of hotspots in each cluster and the possibilities of cross-research, the research in tendon stem cells may exist a balanced development trend.

A New Tool for Rapid Assessment of Acute Exercise-Induced Fatigue.

Background: There are limited sensitive evaluation methods to distinguish people's symptoms of peripheral fatigue and central fatigue simultaneously. The purpose of this study is to identify and evaluate them after acute exercise with a simple and practical scale. Methods: The initial scale was built through a literature review, experts and athlete population survey, and a small sample pre-survey. Randomly selected 1,506 students were evaluated with the initial scale after exercise. Subjective fatigue self-assessments (SFSA) were completed at the same time. Results: The Acute Exercise-Induced Fatigue Scale (AEIFS) was determined after performing a factor analysis. In the exploratory factor analysis, the cumulative variance contribution rate was 65.464%. The factor loadings of the total 8 questions were 0.661-0.816. In the confirmatory factor analysis, χ2/df = 2.529, GFI = 0.985, AGFI = 0.967, NFI = 0.982, IFI = 0.989, CFI = 0.989, and RMSEA = 0.048. The Cronbach's alpha coefficient for the scale was 0.872, and it was 0.833 for peripheral fatigue and 0.818 for central fatigue. The intra-class correlation coefficient for the scale was 0.536, and the intra-class correlation coefficients for peripheral fatigue and central fatigue were 0.421 and 0.548, respectively. The correlation coefficient between the total score of the AEIFS and the SFSA score was 0.592 (p < 0.01). Conclusion: Our results demonstrate that the AEIFS can distinguish peripheral fatigue and central fatigue and can also reflect their correlation. This scale can be a useful evaluation tool not only for measuring fatigue after acute exercise but also for guiding reasonable exercise, choosing objective testing indicators, and preventing sports injuries resulting from acute exercise-induced fatigue.

3D-printing magnesium-polycaprolactone loaded with melatonin inhibits the development of osteosarcoma by regulating cell-in-cell structures.

Melatonin has been proposed as a potent anticarcinogen presents a short half-life for osteosarcoma (OS). Cell-in-cell (CIC) structures play a role in the development of malignant tumors by changing the tumor cell energy metabolism. This study developed a melatonin-loaded 3D printed magnesium-polycaprolactone (Mg-PCL) scaffold and investigated its effect and molecular mechanism on CIC in OS. Mg-PCL scaffold was prepared by 3D-printing and its characteristic was determined. The effect and molecular mechanism of Mg-PCL scaffold as well as melatonin-loaded Mg-PCL on OS growth and progression were investigated in vivo and in vitro. We found that melatonin receptor 1 (MT1) and CIC expressions were increased in OS tissues and cells. Melatonin treatment inhibit the key CIC pathway, Rho/ROCK, through the cAMP/PKA signaling pathway, interfering with the mitochondrial physiology of OS cells, and thus playing an anti-invasion and anti-metastasis role in OS. The Mg-PCL-MT could significantly inhibit distant organ metastasis of OS in the in vivo model. Our results showed that melatonin-loaded Mg-PCL scaffolds inhibited the proliferation, invasion and metastasis of OS cells through the CIC pathway. The Mg-PCL-MT could be a potential therapeutics for OS.

REUR: A unified deep framework for signet ring cell detection in low-resolution pathological images.

Detecting signet ring cells (SRCs) in pathological images is essential for carcinoma diagnosis. However, it is time consuming for pathologists to detect SRCs manually from pathological images, and the accuracy of detecting them is also relatively low because of their small sizes. Recently, the exploration of deep learning methods in pathology analysis has been widely investigated by researchers. Nevertheless, the automatic detection of SRCs from real pathological images faces two problems. One is that labeled pathological images are insufficient and usually incomplete. The other is that the training data and the real clinical data have a large difference in resolution. Hence, adopting the transfer learning method affects the performance of deep learning methods. To address these two problems, we present a unified framework named REUR [RetinaNet combining USRNet (unfolding super-resolution network) with the RGHMC (revised gradient harmonizing mechanism classification) loss] that can accurately detect SRCs in low-resolution (LR) pathological images. First, the framework with the super-resolution (SR) module can address the difference in resolution between the training data and the real clinical data. Second, the framework with the label correction module can obtain the revised ground-truth labels from noisy examples, which are embedded into the gradient harmonizing mechanism to acquire the RGHMC loss. The results of the numerical experiments showed that the framework can perform better than other one-stage detectors based on the RetinaNet architecture in the high-resolution (HR) noisy dataset. It achieved a kappa value of 0.74 and an accuracy of 0.89 in the test with 27 randomly selected whole slide images (WSIs), and, thus, it can assist pathologists in better analyzing WSIs. The framework provides an essential method in computer-aided diagnosis for medical applications.

Selecting Classification Methods for Small Samples of Next-Generation Sequencing Data.

Next-generation sequencing has emerged as an essential technology for the quantitative analysis of gene expression. In medical research, RNA sequencing (RNA-seq) data are commonly used to identify which type of disease a patient has. Because of the discrete nature of RNA-seq data, the existing statistical methods that have been developed for microarray data cannot be directly applied to RNA-seq data. Existing statistical methods usually model RNA-seq data by a discrete distribution, such as the Poisson, the negative binomial, or the mixture distribution with a point mass at zero and a Poisson distribution to further allow for data with an excess of zeros. Consequently, analytic tools corresponding to the above three discrete distributions have been developed: Poisson linear discriminant analysis (PLDA), negative binomial linear discriminant analysis (NBLDA), and zero-inflated Poisson logistic discriminant analysis (ZIPLDA). However, it is unclear what the real distributions would be for these classifications when applied to a new and real dataset. Considering that count datasets are frequently characterized by excess zeros and overdispersion, this paper extends the existing distribution to a mixture distribution with a point mass at zero and a negative binomial distribution and proposes a zero-inflated negative binomial logistic discriminant analysis (ZINBLDA) for classification. More importantly, we compare the above four classification methods from the perspective of model parameters, as an understanding of parameters is necessary for selecting the optimal method for RNA-seq data. Furthermore, we determine that the above four methods could transform into each other in some cases. Using simulation studies, we compare and evaluate the performance of these classification methods in a wide range of settings, and we also present a decision tree model created to help us select the optimal classifier for a new RNA-seq dataset. The results of the two real datasets coincide with the theory and simulation analysis results. The methods used in this work are implemented in the open-scource R scripts, with a source code freely available at https://github.com/FocusPaka/ZINBLDA.

Clinical and Microbiological Characteristics of Invasive and Hypervirulent Klebsiella pneumoniae Infections in a Teaching Hospital in China.

PURPOSE: To investigate the clinical and microbiological characteristics of invasive and hypervirulent Klebsiella pneumoniae (HvKP) in a teaching hospital in Southern China. PATIENTS AND METHODS: A total of 495 non-repetitive K. pneumoniae strains were isolated from Dongguan People's Hospital affiliated to Southern Medical University in 2018. Multivariate analysis was performed using the patients' clinical data to identify the risk factors for HvKP. RESULTS: Eighty-one isolates were HvKP (16.4%, 81/495), of which 43 (53.1%) were invasive HvKP, whereas 38 (46.9%) were non-invasive HvKP. The incidence of extended spectrum beta-lactamases (ESBLs) in HvKP and classic K. pneumoniae (cKP) were 7.4% (6/81) and 28.0% (116/414), respectively (p<0.05). Multivariate analysis indicated that diabetes mellitus (odds ratio [OR]=12.849, 95% confidence interval [CI]: 1.494-110.511, P=0.020) was an independent risk factor for invasive HvKP infection. Altogether, 51.2% (22/43) of invasive HvKP infections were treated with antimicrobial therapy combined with surgical drainage, and achieved good prognosis. K1-ST23 HvKP accounted for a higher proportion of invasive infections than non-invasive infections (P<0.05), but there was no statistical difference in the prognosis between the two groups (P>0.05). The most prevalent virulence genes in HvKP were rmpA 98.7% (80/81), followed by rmpA2 (82.7%, 67/81), iroN (98.7%, 80/81), and iutA 90.1% (70/81). There was no significant difference in the distribution of virulence genes between invasive HvKP and non-invasive HvKP isolates (P>0.05). CONCLUSION: Invasive HvKP infection in this study was positively associated with diabetes as independent risk factors. Antibiotic therapy combined with surgical drainage is one of the most effective treatment measures of HvKP infection. Adequate attention should be paid to HvKP infection in clinical and microbiological laboratories.

Phase retrieval via reweighted Wirtinger flow.

Phase retrieval (PR) is a kind of ill-condition inverse problem which can be found in various applications. Based on the Wirtinger flow (WF) method, a reweighted Wirtinger flow (RWF) method is proposed to deal with the PR problem. In a nutshell, RWF searches the global optimum by solving a series of sub-PR problems with changing weights. Theoretical analyses illustrate that the RWF has a geometric convergence from a deliberate initialization when the weights are bounded by 1 and 109. Numerical tests also show the RWF has a lower sampling complexity compared with the WF. As an essentially adaptive truncated Wirtinger flow (TWF) method, the RWF performs better than the TWF especially when the ratio between sampling number m and length of signal n is small.