Arsenic speciation in saliva of acute promyelocytic leukemia patients undergoing arsenic trioxide treatment

Arsenic trioxide has been successfully used as a therapeutic in the treatment of acute promyelocytic leukemia (APL). Detailed monitoring of the therapeutic arsenic and its metabolites in various accessible specimens of APL patients can contribute to improving treatment efficacy and minimizing arsenic-induced side effects. This article focuses on the determination of arsenic species in saliva samples from APL patients undergoing arsenic treatment. Saliva samples were collected from nine APL patients over three consecutive days. The patients received 10 mg arsenic trioxide each day via intravenous infusion. The saliva samples were analyzed using high-performance liquid chromatography coupled with inductively coupled plasma mass spectrometry. Monomethylarsonous acid and monomethylmonothioarsonic acid were identified along with arsenite, dimethylarsinic acid, monomethylarsonic acid, and arsenate. Arsenite was the predominant arsenic species, accounting for 71.8 % of total arsenic in the saliva. Following the arsenic infusion each day, the percentage of methylated arsenicals significantly decreased, possibly suggesting that the arsenic methylation process was saturated by the high doses immediately after the arsenic infusion. The temporal profiles of arsenic species in saliva following each arsenic infusion over 3 days have provided information on arsenic exposure, metabolism, and excretion. These results suggest that saliva can be used as an appropriate clinical biomarker for monitoring arsenic species in APL patients. [Figure: see text

Antimicrobial susceptibility, variation and relative expression of relative genes of Salmonella screened from different quinolone and fluoroquinolones

Objective To study the mutation and expression of genes of Salmonella when screened by different concentrations of quinolone and fluoroquinolones during propagation and their relation with antibiotic resistance. Methods Salmonella strain was cultured in broth medium and screened on nutrition plate with different concentration of quinolone and fluoroquinolones. Antimicrobial susceptibility of the screened subculture was tested by broth microdilution method, mutation of genes in quinolone resistance-determining region (QRDR) was detected using polymerase chain reaction (PCR) and DNA sequencing method, and expression level of the encoding genes of multi-drug associated efflux pump AcrAB-TolC was detected by real-time qPCR. Results Antibiotic resistance level of the subcultures screened from LB plate with quinolone and fluoroquinolones inducement increased in different extents. Mutation of Asp87Tyr in gyrA in QRDR was detected from the fifth to the seventh generation of nalidixic acid screened strains. Mutation of Asp87Asn in gyrA in QRDR was detected from the fourth to the seventh generation of ciprofloxacin screened strains. No amino acid mutation was detected from gyrA in the first to the seventh generation of gatifloxacin, levofloxacin and delafloxacin screened strains. Compared to the expression level of the multi-drug efflux pump AcrAB-TolC encoding genes of the original strain, those of the screened strains had significantly (P<0.05) increased resistance. No significant difference was detected among the expression level of AcrAB-TolC encoding genes in the seventh generation of screened strains. The ratio of the minimal inhibitory concentrations (MICs) of the screened strains and that of Salmonella Typhimurium (ATCC 14028s), gene variation and relative expression level of acrAB-tolC of Salmonella significantly positive correlated with subculture generation and antibiotic concentration. Conclusion Under the selective pressure of antibiotics, Salmonella strain could adapt the stress environment through QRDR mutation and increase the expression level of multi-drug efflux pump AcrAB-TolC. When the next generation fluoroquinolone was used, the mutation frequency of QRDR decreased. After subcultured several times, the expression level of acrAB-tolC of the screened strains increased, however, no significant difference was detected among the expression level, which avoided the antibiotic resistance of Salmonella to be further increased

Toxin-Encoding Genes and Drug Susceptibility of Staphylococcus aureus from Vegetables Consumed Raw

Objective: To investigate the toxin-encoding genes and antibiotic susceptibility of Staphylococcus aureus isolates from retail vegetables consumed raw. Methods: The 27 S. aureus isolates from tomato, lettuce, spinach and cabbage collected from supermarkets, farmers’ markets and vendors in Xi’an, Baoji, Hanzhong and Yan’an of Shaanxi province were identified by PCR amplification of the nuc gene, the prevalence of 19 toxin-encoding genes and 12 antibiotic resistance encoding genes in these isolates was evaluated, and the antibiotic susceptibility to 14 antibiotics was determined by the agar dilution method. Results: Seventeen of these isolates were identified as methicillin-susceptible S. aureus (MSSA) and the remaining 10 isolates were identified as oxacillin-susceptible methicillin-resistant S. aureus (OS-MRSA). A total of eight toxin-encoding genes were detected in the 27 isolates, and the detection rate (29.6%, 8/27) of sec was highest. In addition, 51.9% (14/27) of these isolates carried at least one toxin-encoding gene, and nine toxin-encoding gene profiles were totally identified. Seven antibiotic resistance genes including blaZ, mecA, ermC, tetK, dfrG, dfrK, and aac(6’)/aph(2”) were detected. The isolates were all susceptible to oxacillin, rifampicin and vancomycin. Resistance to amoxicillin/clavulanate was most commonly detected, followed by trimethoprim/sulfamethoxazole, ampicillin, erythromycin, cefoxitin, ciprofloxacin, ceftriaxone, gentamicin, amikacin, tetracycline and chloramphenicol. Twenty-four (88.9%) isolates were resistant to three or more antibiotics. Conclusion: OS-MRSA is prevalent in vegetables consumed raw in Shaanxi province, and it has multiple antibiotic resistances and carries multiple toxin-encoding gens, posing a potential food safety hazard

A Rigid-Flexible Coupling Dynamic Model for Robotic Manta with Flexible Pectoral Fins

The manta ray, exemplifying an agile swimming mode identified as the median and paired fin (MPF) mode, inspired the development of underwater robots. Robotic manta typically comprises a central rigid body and flexible pectoral fins. Flexible fins provide excellent maneuverability. However, due to the complexity of material mechanics and hydrodynamics, its dynamics are rarely studied, which is crucial for the advanced control of robotic manta (such as trajectory tracking, obstacle avoidance, etc.). In this paper, we develop a multibody dynamic model for our novel manta robot by introducing a pseudo-rigid body (PRB) model to consider passive deformation in the spanwise direction of the pectoral fins while avoiding intricate modeling. In addressing the rigid-flexible coupling dynamics between flexible fins and the actuation mechanism, we employ a sequential coupling technique commonly used in fluid-structure interaction (FSI) problems. Numerical examples are provided to validate the MPF mode and demonstrate the effectiveness of the dynamic model. We show that our model performs well in the rigid-flexible coupling analysis of the manta robot. In addition to the straight-swimming scenario, we elucidate the viability of tailoring turning gaits through systematic variations in input parameters. Moreover, compared with finite element and CFD methods, the PRB method has high computational efficiency in rigid-flexible coupling problems. Its potential for real-time computation opens up possibilities for future model-based control

Epidemiology and Characterization of CTX-M-55-Type Extended-Spectrum β-Lactamase-Producing Salmonella enterica Serovar Enteritidis Isolated from Patients in Shanghai, China

The emergence of extended-spectrum &beta;-lactamase-producing Salmonella enterica serovar Enteritidis (ESBL-SE) in humans and foods has gained global attention. In particular, CTX-M-type ESBL-SE are increasingly being detected from various sample types. The aim of this study was to comprehensively analyze the epidemiology and characteristics of blaCTX-M-55-carrying ESBL-SE isolates of clinical origin in Shanghai, China. A total of 292 S. Enteritidis isolates were recovered from the feces and blood of outpatients and inpatients between 2006 and 2014. Overall, there was a high frequency of cefotaxime-resistant isolates (97.3%), which was significantly higher (p &lt; 0.01) than that of isolates resistant to the other tested antibiotics. All S. Enteritidis isolates exhibited resistance to &ge;1 antibiotic, and 98.0% were multidrug resistant. A total of 233 isolates were identified as ESBL-SE, 166 of which were CTX-M type. Six subtypes of CTX-M-encoding genes were detected, among which blaCTX-M-55 (91.6%, 152/166) was the most prevalent genotype. There was high genetic similarity among blaCTX-M-55-positive ESBL-SE. The blaCTX-M-55 gene in the ESBL-SE donor strains could be easily transferred into Enterobacteriaceae recipient strains. This study highlights that CTX-M-55 should be considered an important surveillance target in Shanghai, China. Cephalosporins, especially cefotaxime, must be used with caution in empirical treatment for Salmonella infections

Maximizing the Formation of Reactive Oxygen Species for Deep Oxidation of NO via Manipulating the Oxygen-Vacancy Defect Position on (BiO)(2)CO3

Constructing oxygen vacancies (OVs) in metaloxide semiconductors is an effective and simple way to enhance the photocatalytic performance via promoting the utilization of solar light and boosting the formation of surface reactive oxygen species (ROS). The presence of different oxygen atoms in the same crystal structure can possibly lead to the formation of different types of OVs with distinct physicochemical and optoelectronic properties. Particularly, the two different crystallographic positions of oxygen atoms in the [BiO](2)(2+) layer of (BiO)(2)CO3 (BOC) allow the construction of two types of OVs (OVs1 and OVs2). In this work, OVs1-BOC and OVs2-BOC are synthesized via introducing the OVs1 and OVs2 on the surface of the BOC. The influence of OVs1 and OVs2 on the generation of ROS in the BOC is demonstrated based on theoretical and experimental studies by analyzing the separation and redox potentials of photogenerated charge carriers, absorption surface adsorbates (H2O and O-2), and reaction active energy. The photocatalytic performance is evaluated by photo-oxidative nitric oxide (NO) removal efficiency under visible light irradiation. The OVsl-BOC and OVs2-BOC exhibit 50.0 and 41.6% photo-oxidative NO removal efficiencies, while generating 15.6 and 16.54 ppb NO2, respectively. The in situ Fourier transform infrared spectroscopy and estimated NO conversion pathway reveal the photo-oxidative NO removal mechanism and suppression of NO2 formation on the surfaces of OVs1-BOC and OVs2-BOC. This work demonstrates a straightforward approach for enhancing the photo-oxidative NO removal via manipulating the OV defect position in semiconductors

Prediction models for postoperative delirium in elderly patients with machine-learning algorithms and SHapley Additive exPlanations

Abstract Postoperative delirium (POD) is a common and severe complication in elderly patients with hip fractures. Identifying high-risk patients with POD can help improve the outcome of patients with hip fractures. We conducted a retrospective study on elderly patients (≥65 years of age) who underwent orthopedic surgery with hip fracture between January 2014 and August 2019. Conventional logistic regression and five machine-learning algorithms were used to construct prediction models of POD. A nomogram for POD prediction was built with the logistic regression method. The area under the receiver operating characteristic curve (AUC-ROC), accuracy, sensitivity, and precision were calculated to evaluate different models. Feature importance of individuals was interpreted using Shapley Additive Explanations (SHAP). About 797 patients were enrolled in the study, with the incidence of POD at 9.28% (74/797). The age, renal insufficiency, chronic obstructive pulmonary disease (COPD), use of antipsychotics, lactate dehydrogenase (LDH), and C-reactive protein are used to build a nomogram for POD with an AUC of 0.71. The AUCs of five machine-learning models are 0.81 (Random Forest), 0.80 (GBM), 0.68 (AdaBoost), 0.77 (XGBoost), and 0.70 (SVM). The sensitivities of the six models range from 68.8% (logistic regression and SVM) to 91.9% (Random Forest). The precisions of the six machine-learning models range from 18.3% (logistic regression) to 67.8% (SVM). Six prediction models of POD in patients with hip fractures were constructed using logistic regression and five machine-learning algorithms. The application of machine-learning algorithms could provide convenient POD risk stratification to benefit elderly hip fracture patients

Pneumonia detection based on RSNA dataset and anchor-free deep learning detector

Abstract Pneumonia is a highly lethal disease, and research on its treatment and early screening tools has received extensive attention from researchers. Due to the maturity and cost reduction of chest X-ray technology, and with the development of artificial intelligence technology, pneumonia identification based on deep learning and chest X-ray has attracted attention from all over the world. Although the feature extraction capability of deep learning is strong, existing deep learning object detection frameworks are based on pre-defined anchors, which require a lot of tuning and experience to guarantee their excellent results in the face of new applications or data. To avoid the influence of anchor settings in pneumonia detection, this paper proposes an anchor-free object detection framework and RSNA dataset based on pneumonia detection. First, a data enhancement scheme is used to preprocess the chest X-ray images; second, an anchor-free object detection framework is used for pneumonia detection, which contains a feature pyramid, two-branch detection head, and focal loss. The average precision of 51.5 obtained by Intersection over Union (IoU) calculation shows that the pneumonia detection results obtained in this paper can surpass the existing classical object detection framework, providing an idea for future research and exploration