Effectiveness of a hybrid approach in integrating GLP-1 agonists and lifestyle guidance for obesity and pre-diabetes management: RWE retrospective study.

Aim: Emerging anti-obesity pharmacotherapy provides an option to correct maladaptive physiological and hormonal changes associated with obesity. One of the widely used medications in this context is glucagon-like peptide 1 (GLP-1) agonists. However, the misuse of these medications without any guidance and monitoring of lifestyle modifications can lead to unfavorable outcomes. The study aims to evaluate the effectiveness of a hybrid care model, incorporating GLP-1 and GLP-1/GIP agonist therapies, in managing obese patients with/without pre-diabetes. This study showcases the midway results of a 6-month program, which includes a multidisciplinary care team and digital technology for continuous engagement and monitoring of patients, both in-clinic and remotely. Methods: In a retrospective observational study, 115 participants were treated with GLP-1s (semaglutide, tirzepatide, and liraglutide). Physicians, dietitians, and coaches worked together to support behavioral changes using a dedicated app provided to patients. At the care team end, an integrated portal enabled continuous data flow allowing for the care team to provide personalized care via chat at regular intervals. Data collected included food logs, continuous glucose monitoring (CGM), and digital biomarkers such as sleep and activity. Results: At the midpoint of the program, participants exhibited statistically significant improvements in various metabolic parameters. Mean weight reduction was 8 %, with significant reductions in BMI, fat mass, and cholesterol levels. 24 (20.9 %) of patients lost ≥5 % of body weight, 55 (47.8 %) patients lost ≥10 % weight, and 36 (31.3 %) patients lost ≥15 % weight. Sub-analysis of pre-diabetic patients (n=36) demonstrated substantial improvements, including control of pre-diabetes in 80.6 % of cases and reduced HbA1c levels back to normoglycemia (5.39 ± 0.27). Conclusion: The Zone.Health's program, which combines pharmacotherapy with continuous engagement and monitoring to enable sustainable lifestyle modifications, demonstrated significant improvements in weight, body composition, and metabolic markers. Pre-diabetes was also effectively addressed. It is necessary to conduct further research to assess the long-term sustainability and optimal adoption of such care models into clinical practice.

The time course of stimulus-specific perceptual learning.

Practice on perceptual tasks can lead to long-lasting, stimulus-specific improvements. Rapid stimulus-specific learning, assessed 24 hours after practice, has been found with just 105 practice trials in a face identification task. However, a much longer time course for stimulus-specific learning has been found in other tasks. Here, we examined 1) whether rapid stimulus-specific learning occurs for unfamiliar, non-face stimuli in a texture identification task; 2) the effects of varying practice across a range from just 21 trials up to 840 trials; and 3) if rapid, stimulus-specific learning persists over a 1-week, as well as a 1-day, interval. Observers performed a texture identification task in two sessions separated by one day (Experiment 1) or 1 week (Experiment 2). Observers received varying amounts of practice (21, 63, 105, or 840 training trials) in session 1 and completed 840 trials in session 2. In session 2, one-half of the observers in each group performed the task with the same textures as in session 1, and one-half switched to novel textures (same vs. novel conditions). In both experiments we found that stimulus-specific learning - defined as the difference in response accuracy in the same and novel conditions - increased as a linear function of the log number of session 1 training trials and was statistically significant after approximately 100 training trials. The effects of stimulus novelty did not differ across experiments. These results support the idea that stimulus-specific learning in our task arises gradually and continuously through practice, perhaps concurrently with general learning.

Engineering of a decellularized bovine skin coated with antibiotics-loaded electrospun fibers with synergistic antibacterial activity for the treatment of infectious wounds.

An ideal antibacterial wound dressing with strong antibacterial behavior versus highly drug-resistant bacteria and great wound-healing capacity is still being developed. There is a clinical requirement to progress the current clinical cares that fail to fully restore the skin structure due to post-wound infections. Here, we aim to introduce a novel two-layer wound dressing using decellularized bovine skin (DBS) tissue and antibacterial nanofibers to design a bioactive scaffold with bio-mimicking the native extracellular matrix of both dermis and epidermis. For this purpose, polyvinyl alcohol (PVA)/chitosan (CS) solution was loaded with antibiotics (colistin and meropenem) and electrospun on the surface of the DBS scaffold to fabricate a two-layer antibacterial wound dressing (DBS-PVA/CS/Abs). In detail, the characterization of the fabricated scaffold was conducted using biomechanical, biological, and antibacterial assays. Based on the results, the fabricated scaffold revealed a homogenous three-dimensional microstructure with a connected pore network, a high porosity and swelling ratio, and favorable mechanical properties. In addition, according to the cell culture result, our fabricated two-layer scaffold surface had a good interaction with fibroblast cells and provided an excellent substrate for cell proliferation and attachment. The antibacterial assay revealed a strong antibacterial activity of DBS-PVA/CS/Abs against both standard strain and multidrug-resistant clinical isolates of Acinetobacter baumannii, Pseudomonas aeruginosa, and Escherichia coli. Our bilayer antibacterial wound dressing is strongly suggested as an admirable wound dressing for the management of infectious skin injuries and now promises to advance with preclinical and clinical research.

Enzymatic and antibacterial activity of the recombinant endolysin PVP-SE1gp146 expressed in Hansenula polymorpha.

Antibiotic resistance, a major global concern, highlights the need for discovering alternative therapies. Recently, endolysins have garnered attention as antibacterial tools with a lower resistance development rate compared to conventional antibiotics, and their production in various expression hosts holds significance. Given its generally recognized as safe (GRAS) status and other advantages, Hansenula polymorpha offers a promising host for endolysin production. PVP-SE1gp146 originates from the Salmonella Enteritidis-specific phage PVP-SE1, which has been previously characterized. We inserted the PVP-SE1gp146 coding gene into the H. polymorpha expression vector pHIPX4. The resulting recombinant, pHIPX4-PVP-SE1gp146, was then introduced into H. polymorpha NCYC495 to facilitate the production of the endolysin PVP-SE1gp146. The expression level of the PVP-SE1gp146 protein was assessed, and it was determined to be approximately 43 mg/l of yeast culture medium. The enzymatic (muralytic) activity of this endolysin was also evaluated, corresponding to the version produced by the E. coli Bl21 strain. The endolysin exhibited admissible antibacterial activity against several gram-negative species, including P. aeruginosa, E. coli, and A. baumannii, while showing an almost negligible impact on K. pneumoniae. Endolysin production within GRAS-approved hosts holds potential for combating antibiotic-resistant bacteria. Challenges involve optimizing concentrations, targeting gram-negative species and improving attachment to bacterial cell walls. Addressing these issues requires dedicated research in endolysin engineering and a comprehensive evaluation of their production in diverse expression hosts.

Effectiveness of a hybrid technology enabled care model as measured by ICHOM standard set on established and managed type 2 diabetes already using medications: A RWE retrospective study.

Aims: Diabetes is a pressing global health issue, demanding innovative strategies for improved treatment. However, traditional care often falls short of patient goals. To address this, digital health solutions, including smartphone apps and remote monitoring, have emerged as crucial in diabetes management. This study aims to assess a comprehensive intervention, combining remote continuous data monitoring (RCDM) with in-clinic care, for enhancing diabetes-related outcomes. Additionally, it seeks to evaluate the effectiveness of the digital RCDM component by comparing adherent and non-adherent patients. Methods: Conducted in the United Arab Emirates, a retrospective study involved 89 patients primarily on anti-diabetic medications. They were split into two groups based on adherence to RCDM. Over time, significant improvements were observed across various parameters. Results: Notably, patients exhibited weight loss (-4.0 ± 5.3, p < 0.001), reduced waist circumference (-4.74 ± 7.8, p < 0.001), lowered HbA1c levels (-1.00 ± 1.3, p < 0.001), decreased systolic BP (-3.1 ± 13.1, p = 0.035), and diminished diastolic BP (-3.4 ± 9.9, p = 0.002) annually. Furthermore, patients adhering to the GluCare model demonstrated substantial HbA1c reductions (-1.53 ± 1.5, p < 0.001), improved lipid profiles, notably decreased total Cholesterol (-16.6 ± 50.3, p = 0.034), and lowered LDL levels (-18.65 ± 42.6, p = 0.006). Conclusions: The intervention model effectively managed T2D patients through a comprehensive approach, yielding notable improvements in HbA1c levels and other outcomes within a year. The study underscores the limitations of traditional care and reliance simply on pharmacotherapy, and emphasizes the need for a hyper-personalized, and continuous approach for T2D management.

Effect of Repeated Use of Different Types of Scan Bodies on Transfer Accuracy of Implant Position.

Statement of the Problem: Some components of implant treatment are reusable. Therefore, possible changes during fixation, removal, and sterilization process should be tested. Many studies have examined the reuse of implant parts, but the impact of repeated use of scan bodies on the accuracy of implant position has not been well investigated. Purpose: The aim of this in vitro study was to compare the effect of repeated use of two different types of scan bodies on the accuracy of implant position. Materials and Method: In this in vitro experimental study, two acrylic resin maxillary models, each with two implant analogues inserted at the site of missing first and second molars were used. Two types of scan bodies including titanium and polyetheretherketone (PEEK) were used for digital impression. Then they were ten times removed and autoclaved for sterilization. The first scan was considered as a reference to be compared with the other next nine scans. Values of linear distance between two scan bodies, diameter changes of each scan body, and three-dimensional linear displacement (ΔR) were measured. These values were compared between the two types of scan bodies using t-test (α=.05). Results: There was significant difference between titanium and PEEK scan bodies regarding inter-implant distance variation (p=.006) and diameter change (p< .001) in repeated use. However, for the ΔR, there was no significant difference between them (p= 0.759). Conclusion: The results demonstrated that type of scan body could affect the accuracy of implant position transfer after repeated use. PEEK scan body performed better after 9 cycles of reuse in comparison with titanium scan body.

A cross-cultural, cross-disciplinary, and cross-gender study on Appraisal resources in PhD dissertation abstracts: Martin & White's (2005) Appraisal Theory in focus.

The abstract which complements proposals, articles, and dissertations, is a remarkable convention in scientific studies since it creates access for readers and authors to read or publish studies or articles. Research abstracts (RA) function as the gateway to view an article, journals' selection for contributions, and for conferences to accept or reject articles (Lores, 2004) In this study, we aimed to investigate the preferences of writers in 160 PhD dissertation abstracts, encompassing both male and female native and non-native authors, across various fields of study, both in the hard and soft sciences. Our primary objective was to discern the writers' inclinations towards utilizing specific linguistic resources, as proposed by Martin and White's Appraisal theory (2005), to convey their positions and engage with the perspectives articulated by their peers. The analysis of the data, conducted using statistical methods, unveiled a pervasive utilization of appraisal resources by the writers, enabling them to articulate their viewpoints, prospects, perceptions, and evaluations concerning diverse subjects. Among these resources, Attitude resources stood out prominently, constituting a substantial 84% of the total Appraisal resources employed in all the abstracts. Graduation resources held an intermediate position, while Engagement resources were the least utilized. Within the realm of Attitude subcategories, Appreciation resources emerged as the most prevalent. Remarkably, female authors specializing in the soft sciences displayed a higher degree of proficiency in the use of these resources, surpassing their counterparts in other categories. This finding suggests that female writers in the soft sciences possess exceptional interpersonal communication skills, making them particularly persuasive and inspirational. The implications of this study extend to the domains of language teaching and learning, material development, and syllabus design. It sheds light on how writers employ linguistic resources to convey their positions effectively, offering valuable insights for educational practices and curriculum enhancement.

HiREX: High-Throughput Reactivity Exploration for Extended Databases of Transition-Metal Catalysts.

A method is introduced for the automated analysis of reactivity exploration for extended in silico databases of transition-metal catalysts. The proposed workflow is designed to tackle two key challenges for bias-free mechanistic explorations on large databases of catalysts: (1) automated exploration of the chemical space around each catalyst with unique structural and chemical features and (2) automated analysis of the resulting large chemical data sets. To address these challenges, we have extended the application of our previously developed ReNeGate method for bias-free reactivity exploration and implemented an automated analysis procedure to identify the classes of reactivity patterns within specific catalyst groups. Our procedure applied to an extended series of representative Mn(I) pincer complexes revealed correlations between structural and reactive features, pointing to new channels for catalyst transformation under the reaction conditions. Such an automated high-throughput virtual screening of systematically generated hypothetical catalyst data sets opens new opportunities for the design of high-performance catalysts as well as an accelerated method for expert bias-free high-throughput in silico reactivity exploration.

The Relationship between the Biofilm Genes and Antibiotic Resistance in Stenotrophomonas maltophilia.

Objectives: Today, Stenotrophomonas maltophilia (S. maltophilia) is a major opportunistic pathogen among hospitalized or immunocompromised patients. Antibiotic-resistant clinical isolates are increasing in several parts of the world. Various antibiotic-resistance and biofilm-forming genes are identified in this bacterium. Its capacity to form biofilms is an important virulence factor that may impact antibiotic-resistance patterns. In the current study, we evaluated the biofilm-formation capacity, antibiotic-resistance profile, and prevalence of biofilm-forming genes as well as antibiotic resistance genes among S. maltophilia isolates. Materials and Methods: In this cross-sectional study, 94 clinical S. maltophilia isolates were recovered from four tertiary-care hospitals in Iran between 2021 and 2022. The presence of the selected antibiotic-resistance genes and biofilm-forming genes was examined by polymerase chain reaction (PCR). The ability of biofilm formation was examined by microtiter plate assay. The Kirby-Bauer disc diffusion method was used to evaluate the trimethoprim-sulfamethoxazole (TMP-SMX), levofloxacin, and minocycline resistance. Results: S. maltophilia is mainly isolated from bloodstream infections. Notably, 98.93% of isolates were biofilm producers, of which 19.35%, 60.22%, and 20.43% produced strong, moderate, and weak biofilm, respectively. The frequency of biofilm genes was 100%, 97.88%, 96.80%, and 75.53% for spgM, rmlA, smf-1, and rpfF, respectively. Isolates with the genotype of smf-1+/rmlA+/spgM+/rpfF+ were mostly strong biofilm producers. Among the antibiotic-resistance genes, the Smqnr, L1, and sul1 had the highest prevalence (76.59%, 72.34%, and 64.89), respectively. Antimicrobial susceptibility evaluation showed 1.06%, 3.19%, and 6.3% resistance to minocycline, TMP-SMX, and levofloxacin. Conclusion: The results of the current study demonstrated that S. maltophilia isolates differ in biofilm-forming ability. Moreover, smf-1, rmlA, and spgM genes were presented in all strong biofilm producers. Although the overall resistance rate to the evaluated antibiotics was high, there was no statistically significant relation between antibiotic resistance and the type of biofilm.

COVID-19: An Overview of SARS-CoV-2 Variants-The Current Vaccines and Drug Development.

The world is presently in crisis facing an outbreak of a health-threatening microorganism known as COVID-19, responsible for causing uncommon viral pneumonia in humans. The virus was first reported in Wuhan, China, in early December 2019, and it quickly became a global concern due to the pandemic. Challenges in this regard have been compounded by the emergence of several variants such as B.1.1.7, B.1.351, P1, and B.1.617, which show an increase in transmission power and resistance to therapies and vaccines. Ongoing researches are focused on developing and manufacturing standard treatment strategies and effective vaccines to control the pandemic. Despite developing several vaccines such as Pfizer/BioNTech and Moderna approved by the U.S. Food and Drug Administration (FDA) and other vaccines in phase 4 clinical trials, preventive measures are mandatory to control the COVID-19 pandemic. In this review, based on the latest findings, we will discuss different types of drugs as therapeutic options and confirmed or developing vaccine candidates against SARS-CoV-2. We also discuss in detail the challenges posed by the variants and their effect on therapeutic and preventive interventions.

Rapid identification of bacteria by the pattern of redox reactions rate using 2',7'-dichlorodihydrofluorescein diacetate.

Bacterial infection is a life-threatening situation, and its rapid diagnosis is essential for treatment. Apart from medical applications, rapid identification of bacteria is vital in the food industry or the public health system. There are various bacterial identification techniques, including molecular-based methods, immunological approaches, and biosensor-based procedures. The most commonly used methods are culture-based methods, which are time-consuming. The objective of this study is to find a fingerprint of bacteria to identify them. Three strains of bacteria were selected, and seven different concentrations of each bacterium were prepared. The bacteria were then treated with two different molar concentrations of the fluorescent fluorophore, dichlorodihydrofluorescein diacetate for 30 minutes. Then, using the fluorescence mode of a multimode reader, the fluorescence emission of each bacterium is scanned twice during 60 minutes. Plotting the difference between two scans versus the bacteria concentration results in a unique fluorescence pattern for each bacterium. Observation of the redox state of bacteria, during 90 minutes, results in a fluorescence pattern that is clearly a fingerprint of different bacteria. This pattern is independent of fluorophore concentration. Mean Squares Errors (MSE) between the fluorescence patterns of similar bacteria is less than that of different bacteria, which shows the method can properly identify the bacteria. In this study, a new label-free method is developed to detect and identify different species of bacteria by measuring the redox activity and using the fluorescence fluorophore, dichlorodihydrofluorescein diacetate. This robust and low-cost method can properly identify the bacteria, uses only one excitation and emission wavelength, and can be simply implemented with current multimode plate readers.

abkBA toxin-antitoxin system may act as antipersister modules in Acinetobacter baumannii clinical isolates.

Aim: Persistence cells comprise a subpopulation of bacteria that is resistant to treatment. In this study, the role of the toxin-antitoxin (TA) system in the formation of persistence cells of Acinetobacter baumannii isolates was investigated. Methods: After confirming all isolates, TA systems abkBA, mqsRA and higBA were identified. Persister cells were confirmed using the standard method. Real-time PCR was used to compare the expression of TA systems in isolates in persistence and normal states. Results: The abkAB system was present in all isolates; 4% of isolates formed persister cells. The expression level of the abkB gene in persistent isolates showed a sevenfold increase compared with nonpersistent isolates. Conclusion: The abkBA system is proposed as an antipersistence target in A. baumannii isolates.

Serum Level of Antibodies Against Novel Acinetobacter Baumannii OmpA-selected Peptides in ICU Staff: Promise for the Future of Vaccine Development.

Extensively drug-resistant Acinetobacter baumannii is considered one of the most dangerous threats to global health, requiring novel therapeutic interventions. The outer membrane protein A (OmpA) is an immunogenic agent that triggers immune responses. The current study evaluated serum antibody levels against previously determined immunogenic OmpA peptides from A baumannii in ICU staff. Serum samples were collected from 62 ICU staff members (representing the exposed group), healthy controls (representing the nonexposed group), and patients with systemic lupus erythematosus (SLE) (as controls for nonspecific antibody reactions). After excluding the cross-reactive antibodies via Escherichia coli lysate pretreatment, all the samples were assessed in the vicinity of A baumannii lysate by enzyme-linked immunosorbent assay (ELISA). All the positive samples were assessed for interaction with previously designed and selected peptides using ELISA. The protective potential of positive serum antibodies was surveyed in vitro using an opsonophagocytic study. The most antibody positive samples against one of the dominant peptides were determined in the ICU personnel (75%).  SLE serum samples did not react with candidate peptides. The strongest positive reaction was observed in serum treatment with one of the OmpA peptides (No. 5) with significant differences compared to other designed peptides. Our findings showed that ICU samples have substantially higher antibody levels than the nonexposed group; Positive samples show strong results in the opsonophagocytosiis assay. This study demonstrates A baumannii colonization at human mucosal surfaces, especially in exposed healthy workers. Novel OmpA-derived peptides could be used to identify immunogenic vaccine candidates. Therefore, more studies are needed  before this peptide and antibody levels are used in diagnosis, prevention, or treatment.

Bayesian Adaptive Beamformer for Robust Electromagnetic Brain Imaging of Correlated Sources in High Spatial Resolution.

Reconstructing complex brain source activity at a high spatiotemporal resolution from magnetoencephalography (MEG) or electroencephalography (EEG) remains a challenging problem. Adaptive beamformers are routinely deployed for this imaging domain using the sample data covariance. However adaptive beamformers have long been hindered by 1) high degree of correlation between multiple brain sources, and 2) interference and noise embedded in sensor measurements. This study develops a novel framework for minimum variance adaptive beamformers that uses a model data covariance learned from data using a sparse Bayesian learning algorithm (SBL-BF). The learned model data covariance effectively removes influence from correlated brain sources and is robust to noise and interference without the need for baseline measurements. A multiresolution framework for model data covariance computation and parallelization of the beamformer implementation enables efficient high-resolution reconstruction images. Results with both simulations and real datasets indicate that multiple highly correlated sources can be accurately reconstructed, and that interference and noise can be sufficiently suppressed. Reconstructions at 2-2.5mm resolution (  âˆ¼  150K voxels) are possible with efficient run times of 1-3 minutes. This novel adaptive beamforming algorithm significantly outperforms the state-of-the-art benchmarks. Therefore, SBL-BF provides an effective framework for efficiently reconstructing multiple correlated brain sources with high resolution and robustness to interference and noise.

NON-INTRUSIVE DROWSINESS DETECTION TECHNIQUES AND THEIR APPLICATION IN DETECTING EARLY DEMENTIA IN OLDER DRIVERS.

Drowsy drivers cause the most car accidents thus, adopting an efficient drowsiness detection system can alert the driver promptly and precisely which will reduce the numbers of accidents and also save a lot of money. This paper discusses many tactics and methods for drowsy driving warning. The non-intrusive nature of most of the strategies mentioned and contrasted means both vehicular and behavioural techniques are examined here. Thus, the latest strategies are studied and discussed for both groups, together with their benefits and drawbacks. The goal of this review was to identify a practical and low-cost approach for analysing elder drivers' behaviour.

Global prevalence and distribution of antibiotic resistance among clinical isolates of Stenotrophomonas maltophilia: A systematic review and meta-analysis.

OBJECTIVES: Stenotrophomonas maltophilia (S. maltophilia), an opportunistic pathogen, causes infection in patients undergoing immunosuppressive therapy, mechanical ventilation, or catheters and in long-term hospitalized patients. Due to its extensive resistance to various antibiotics and chemotherapeutic agents, S. maltophilia is challenging to treat. Using case reports, case series, and prevalence studies, the current study provides a systematic review and meta-analysis of antibiotic resistance profiles across clinical isolates of S. maltophilia. METHODS: A systematic literature search was performed for original research articles published in Medline, Web of Science, and Embase databases from 2000 to 2022. Statistical analysis was performed using STATA 14 software to report antibiotic resistance of S. maltophilia clinical isolates worldwide. RESULTS: 223 studies (39 case reports/case series and 184 prevalence studies) were collected for analysis. A meta-analysis of prevalence studies demonstrated that the most antibiotic resistance worldwide was to levofloxacin, trimethoprim-sulfamethoxazole (TMP/SMX), and minocycline (14.4%, 9.2%, and 1.4%, respectively). Resistance to TMP/SMX (36.84%), levofloxacin (19.29%), and minocycline (1.75%) were the most prevalent antibiotic resistance types found in evaluated case reports/case series studies. The highest resistance rate to TMP/SMX was reported in Asia (19.29%), Europe (10.52%), and America (7.01%), respectively. CONCLUSION: Considering the high resistance to TMP/SMX, more attention should be paid to patients' drug regimens to prevent the emergence of multidrug-resistant S. maltophilia isolates.

Detection of Virulence Factors and Antibiotic Resistance among Klebsiella pneumoniae Isolates from Iran.

The current study assessed the detection of virulence genes and drug resistance among Klebsiella pneumoniae isolates from Iran. During 2018 to 2020, 52 K. pneumoniae isolates were obtained from patients at Iran hospitals. By disk diffusion method, the antimicrobial susceptibility of K. pneumoniae isolates was assessed, and ESBL-producing K. pneumoniae isolates were detected by CDDT method. PCR analysis was done to detect virulence genes (iucB, iutA, iroN, kfu, allS, fimH, ybtS, mrkD, and entB); ESBL-encoding genes (bla TEM, bla PER, bla CTX-M, bla VEB, and bla SHV); and class D (bla OXA-48), class B (bla VIM, bla NDM, and bla IMP), and class A (bla KPC and bla GES) carbapenemase genes. Among all isolates, 84.6%, 13.5%, and 1.9% isolates were multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR), respectively. Also, 84.6% were ESBL-producing and 71.2%, 53.8%, 40.4%, and 9.6% of all isolates were carrying bla TEM, bla SHV, bla CTX-M, and bla OXA-48 genes, respectively. Six isolates (11.5%) were positive for bla NDM gene. In contrast, no isolates were positive for the presence of bla KPC, bla IMP, and bla VIM. Virulence factor genes including iucB, iutA, iroN, kfu, allS, fimH, ybtS, mrkD, and entB were carried by 24%, 46.2%, 25%, 11.5%, 17.3%, 86.5%, 75%, 88.5%, and 100% isolates, respectively. This study evaluated the distribution and prevalence of virulence factor genes among K. pneumoniae isolates. The treatment of these infections is challenging due to the existence of particular virulence factors and the rise of antibiotic resistance. Therefore, the current study accentuates the necessity of finding new and efficient solutions for stopping the increase of antibiotic resistance.

Colistin resistance mechanisms in Gram-negative bacteria: a Focus on Escherichia coli.

Multidrug-resistant (MDR) Escherichia coli strains have rapidly increased worldwide, and effective antibiotic therapeutic options are becoming more restricted. As a polymyxin antibiotic, colistin has a long history of usage, and it is used as a final line of treatment for severe infections by Gram-negative bacteria (GNB) with high-level resistance. However, its application has been challenged by the emergence of E. coli colistin resistance. Hence, determining the mechanism that confers colistin resistance is crucial for monitoring and controlling the dissemination of colistin-resistant E. coli strains. This comprehensive review summarizes colistin resistance mechanisms in E. coli strains and concentrates on the history, mode of action, and therapeutic implications of colistin. We have mainly focused on the fundamental mechanisms of colistin resistance that are mediated by chromosomal or plasmid elements and discussed major mutations in the two-component systems (TCSs) genes and plasmids that transmit the mobilized colistin resistance resistant genes in E. coli strains.

Bayesian Algorithms for Joint Estimation of Brain Activity and Noise in Electromagnetic Imaging.

Simultaneously estimating brain source activity and noise has long been a challenging task in electromagnetic brain imaging using magneto- and electroencephalography. The problem is challenging not only in terms of solving the NP-hard inverse problem of reconstructing unknown brain activity across thousands of voxels from a limited number of sensors, but also for the need to simultaneously estimate the noise and interference. We present a generative model with an augmented leadfield matrix to simultaneously estimate brain source activity and sensor noise statistics in electromagnetic brain imaging (EBI). We then derive three Bayesian inference algorithms for this generative model (expectation-maximization (EBI-EM), convex bounding (EBI-Convex) and fixed-point (EBI-Mackay)) to simultaneously estimate the hyperparameters of the prior distribution for brain source activity and sensor noise. A comprehensive performance evaluation for these three algorithms is performed. Simulations consistently show that the performance of EBI-Convex and EBI-Mackay updates is superior to that of EBI-EM. In contrast to the EBI-EM algorithm, both EBI-Convex and EBI-Mackay updates are quite robust to initialization, and are computationally efficient with fast convergence in the presence of both Gaussian and real brain noise. We also demonstrate that EBI-Convex and EBI-Mackay update algorithms can reconstruct complex brain activity with only a few trials of sensor data, and for resting-state data, achieving significant improvement in source reconstruction and noise learning for electromagnetic brain imaging.

Synergetic dual antibiotics-loaded chitosan/poly (vinyl alcohol) nanofibers with sustained antibacterial delivery for treatment of XDR bacteria-infected wounds.

Resistance of bacterial pathogens to conventional antibiotics has remained a significant challenge in managing post-wound infections, especially in developing countries. Here, a nanofibrous chitosan/poly (vinyl alcohol) (CS/PVA) mat was designed for controlled delivery of three different concentrations of two antibiotics (colistin/meropenem ratio of 32/64 µg/ml (AB1), 64/128 µg/ml (AB2), and 128/256 (AB3) µg/ml) with synergistic antibacterial activity against ATCC and extensively drug-resistant (XDR) Acinetobacter baumannii clinical isolates. The scaffolds showed a uniform fibrous structure with no bead formation with a sustained release of the antibiotics for one week. The elongation at break, wettability, porosity, and average fiber diameter decreased with increased antibiotics concentrations. Young's modulus and tensile strength showed a significant increase after adding antibiotics. All the constructs showed excellent in vitro cytocompatibility for fibroblasts and biocompatibility in an animal model. The antibacterial assays confirmed the dose-dependent antibacterial activity of the CS/PVA. The scaffolds loaded with AB2 and AB3 showed biocidal properties against ATCC, while only CS/PVA/AB3 had antibacterial activity against XDR clinical isolates. This study suggests the CS/PVA/AB3 nanofibrous scaffold contained 128/256 µg/ml colistin/meropenem as an excellent antibacterial wound dressing for protection of skin wounds from XDR clinical isolates and now promises to proceed with pre-clinical investigations.