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.

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.

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.

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.

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.

Empirical Bayesian localization of event-related time-frequency neural activity dynamics.

Accurate reconstruction of the spatio-temporal dynamics of event-related cortical oscillations across human brain regions is an important problem in functional brain imaging and human cognitive neuroscience with magnetoencephalography (MEG) and electroencephalography (EEG). The problem is challenging not only in terms of localization of complex source configurations from sensor measurements with unknown noise and interference but also for reconstruction of transient event-related time-frequency dynamics of cortical oscillations. We recently proposed a robust empirical Bayesian algorithm for simultaneous reconstruction of complex brain source activity and noise covariance, in the context of evoked and resting-state data. In this paper, we expand upon this empirical Bayesian framework for optimal reconstruction of event-related time-frequency dynamics of regional cortical oscillations, referred to as time-frequency Champagne (TFC). This framework enables imaging of five-dimensional (space, time, and frequency) event-related brain activity from M/EEG data, and can be viewed as a time-frequency optimized adaptive Bayesian beamformer. We evaluate TFC in both simulations and several real datasets, with comparisons to benchmark standards - variants of time-frequency optimized adaptive beamformers (TFBF) as well as the sLORETA algorithm. In simulations, we demonstrate several advantages in estimating time-frequency cortical oscillatory dynamics compared to benchmarks. With real MEG data, we demonstrate across many datasets that the proposed approach is robust to highly correlated brain activity and low SNR data, and is able to accurately reconstruct cortical dynamics with data from just a few epochs.

The OmpA of commensal Escherichia coli of CRC patients affects apoptosis of the HCT116 colon cancer cell line.

BACKGROUND: Colorectal cancer ranks third globally among all types of cancers. Dysbiosis of the gut microbiota of people with CRC is one of the effective agents in the tumorigenesis and metastasis in this type of cancer. The population of Escherichia coli strains, a component of gut microbiota, is increased in the gut of people with CRC compared with healthy people. So, E.coli strains isolated from these patients may have a role in tumorigenesis. Because the most isolated strains belong to the B2 phylogenuetic group, there seems to be a linkage between the bacterium components and malignancy. MATERIAL AND METHODS: In this study, the proteomic comparison between isolated Ecoli from CRC patients and healthy people was assayed. The isolated spot was studied by Two-dimensional gel electrophoresis (2DE) and Liquid chromatography-mass spectrometry (LC-MS). The results showed that the expression of Outer membrane protein A (OmpA) protein increased in the commensal E.coli B2 phylogenetic group isolated from CRC patients. Additionally, we analyzed the effect of the OmpA protein on the expression of the four genes related to apoptosis in the HCT116 colon cancer cell line. RESULTS: This study identified that OmpA protein was overexpressed in the commensal E.coli B2 phylogenetic group isolated from CRC patients compared to the E.coli from the control group. This protein significantly decreased the expression of Bax and Bak, pro-apoptotic genes, as well as the expression of P53 in the HCT116 Cell Line, P < 0.0001. LC-MS and protein bioinformatics results confirmed that this protein is outer membrane protein A, which can bind to nucleic acid and some of the organelle proteins on the eukaryotic cell surface. CONCLUSIONS: According to our invitro and insilico investigations, OmpA of gut E.coli strains that belong to the B2 phylogenetic group can affect the eukaryotic cell cycle.

Evaluation the reactivity of a peptide-based monoclonal antibody derived from OmpA with drug resistant pulsotypes of Acinetobacter baumannii as a potential therapeutic approach.

BACKGROUND: Acinetobacter baumannii is an opportunistic and antibiotic-resistant pathogen that predominantly causes nosocomial infections. There is urgent need for development nonantibiotic-based treatment strategies. We developed a novel monoclonal antibody (mAb) against a peptide of conserved outer membrane protein A (OmpA) and evaluated its reactivity with different pulsotypes of A. baumannii. METHODS: Peptide derived from A. baumannii OmpA was conjugated to keyhole limpet hemocyanin and injected into BALB/c mice. Splenocytes of immunized mice were fused with SP2/0 myeloma cells followed by selection of antibody-producing hybridoma cells. After screening of different hybridoma colonies by ELISA, one monoclone was selected as 3F10-C9 and the antibody was tested for reaction with five different Acinetobacter pulsotypes that were resistant to carbapenem antibiotics. The affinity constant was measured by ELISA. The ELISA, western blotting, indirect immunofluorescence (IFA), and in vitro opsonophagocytosis assays were used to evaluate the reactivity of generated mAb. RESULTS: The anti-OmpA antibody reacted with the immunizing peptide and had a high affinity (1.94 × 10-9 M) for its antigen in the ELISA. Specific binding of mAb to OmpA was confirmed in Western blot. IFA assays revealed that mAb recognized specific OmpA on the pulsotypes. Opsonophagocytosis assays showed that the mAb increased the bactericidal activity of macrophage cells. The antibody function was higher in the presence of serum complement. CONCLUSIONS: The peptide-based mAb demonstrated optimal performance in laboratory experiments which may be appropriate in investigation on OmpA in Acinetobacter pathogenesis and development of passive immunization as a novel therapeutic approach.

Characterization of Sequence Types and Mechanisms of Resistance to Tigecycline Among Acinetobacter baumannii Isolated from Children.

The present study aimed to investigate the mechanisms of resistance to tigecycline and to determine sequence types of Acinetobacter baumannii isolates recovered from children, using the Multilocus Sequence Typing (MLST). A total of 74 A. baumannii isolates were recovered from patients at one of the children's hospital in Tehran, Iran. Antimicrobial susceptibility testing of the isolates was performed for different classes of antibiotics and minimum inhibitory concentrations of colistin and tigecycline were determined using broth microdilution method and E-test strips, respectively. The presence of ISAba1, AbaR, tet(39), and tetX and the expressions of adeB, adeG, and adeJ efflux pump genes were measured using Polymerase Chain Reaction (PCR) and quantitative real-time PCR (RT-PCR), respectively. The diversity of mutations across the regulatory genes of RND efflux pumps (adeRS, adeL, and adeN) and trm gene were determined using their PCR amplification and DNA sequencing in tigecycline-resistant isolates. In addition, STs of tigecycline-resistant isolates were determined using MLST method. Three A. baumannii isolates were resistant to tigecycline. Several amino acid substitutions were identified in AdeRS, AdeN, and Trm but no alteration was found in AdeL. Nevertheless, adeB, adeG, and adeJ overexpression were observed in 1, 2, and 1 isolates, respectively. The tigecycline-resistant isolates belonged to ST1720 and ST2285. This is the first study reporting on ST2285 in A. baumannii populations. Among 74 isolates, two tigecycline susceptible isolates carried tet(39) gene but no tetX gene was detected. We concluded that mutations in regulatory genes of RND efflux pumps and the trm gene may play some important role in A. baumannii resistance to tigecycline.

Antimicrobial resistance patterns and virulence gene profiles of Salmonella enteritidis and Salmonella typhimurium recovered from patients with gastroenteritis in three cities of Iran.

This study evaluated distribution of virulence factors and antibiotic resistance in clinical isolates of Salmonella enteritidis and Salmonella typhimurium in three cities of Iran. Altogether 48 S. enteritidis and S. typhimurium isolates were collected from patients at certain Iranian hospitals between May 2018 and September 2021. Antimicrobial susceptibility testing was performed by disk diffusion and broth microdilution methods. The presence of antibiotic-resistance genes (blaTEM,blaSHV,blaCTX-M,blaNDM,strA, strB, aadA1, tetA, tetB, floR, sul1, sul2, dfrA), integrons (classe 1 and 2), and virulence-associated genes (invA, stn, sopB, spvC, rck, phoPQ) was investigated by PCR and sequencing. Antimicrobial agents like trimethoprim-sulfamethoxazole and imipenem represent highly efficient agents with 97% susceptibility. S. enteritidis and S. typhimurium exhibited high resistance to ciprofloxacin (n = 20, 71.43%) and ceftazidime (n = 9, 45%), respectively. Overall, 3 (6.25%), 13 (27.08%), and 6 (12.5%) isolates were divided into strong, moderate, and weak biofilm producers, respectively. Moreover, blaCTX-M,blaTEM, blaSHV, sul1, sul2, tetA, tetB, floR, strA, and strB resistant genes were detected in 10 (20.8%), 5 (10.4%), 1 (2.08%), 7 (14.58%), 1 (2.08%), 3 (6.25%), 2 (4.1%), 1 (2.08%), 2 (4.1%), 2 (4.1%), respectively. Furthermore, 7 (14.58%) strains had classe 1 integron. All tested S. enteritidis strains had invA and sopB, and all S. typhimurium strains had invA and phoPQ. However, spvC remained undetected in all isolates. Extensive surveillance and efficient control measures against infection help to stop the upsurge of various antibiotic-resistant isolates.

Smart Active Vibration Control System of a Rotary Structure Using Piezoelectric Materials.

A smart active vibration control (AVC) system containing piezoelectric (PZT) actuators, jointly with a linear quadratic regulator (LQR) controller, is proposed in this article to control transverse deflections of a wind turbine (WT) blade. In order to apply controlling rules to the WT blade, a state-of-the-art semi-analytical solution is developed to obtain WT blade lateral displacement under external loadings. The proposed method maps the WT blade to a Euler-Bernoulli beam under the same conditions to find the blade's vibration and dynamic responses by solving analytical vibration solutions of the Euler-Bernoulli beam. The governing equations of the beam with PZT patches are derived by integrating the PZT transducer vibration equations into the vibration equations of the Euler-Bernoulli beam structure. A finite element model of the WT blade with PZT patches is developed. Next, a unique transfer function matrix is derived by exciting the structures and achieving responses. The beam structure is projected to the blade using the transfer function matrix. The results obtained from the mapping method are compared with the counter of the blade's finite element model. A satisfying agreement is observed between the results. The results showed that the method's accuracy decreased as the sensors' distance from the base of the wind turbine increased. In the designing process of the LQR controller, various weighting factors are used to tune control actions of the AVC system. LQR optimal control gain is obtained by using the state-feedback control law. The PZT actuators are located at the same distance from each other an this effort to prevent neutralizing their actuating effects. The LQR shows significant performance by diminishing the weights on the control input in the cost function. The obtained results indicate that the proposed smart control system efficiently suppresses the vibration peaks along the WT blade and the maximum flap-wise displacement belonging to the tip of the structure is successfully controlled.

Relationships between Efflux Pumps and Emergence of Heteroresistance: A Comprehensive Study on the Current Findings.

Heteroresiatnce (HR) is the type of resistance toward one or more antibiotics appearing as a population of the bacterial load consisting of one or more subpopulations with lower antibiotic susceptibility levels than others. Due to the lack of appropriate diagnosis of HR isolates and their importance in resistance emergence to antibiotics, investigating the origins, emergence factors, and HR inhibitors is critical in combating antibiotic resistance. Efflux pumps (EPs) are bacterial systems that own an influential role in acquiring resistance toward anti-bacterial compounds. Studies on EPs revealed that they can affect HR emergence mechanisms and are competent to be introduced as a suitable bacterial target for diagnostic and therapeutic development in combating HR isolates. This review will consider the relations between EPs and the emergence of HR isolates and discuss their importance in confronting this type of antibiotic resistance.

Decreased Susceptibility of Shigella Isolates to Azithromycin in Children in Tehran, Iran.

Azithromycin (AZT) has widely been used for the treatment of shigellosis in children. Recent studies showed a high rate of decreased susceptibility to azithromycin due to different mechanisms of resistance in Shigella isolates. Accordingly, the purpose of this study was to investigate the role of azithromycin resistance mechanisms of Shigella isolates in Iran during a two-year period. In this study, we investigated the mechanisms of resistance among Shigella spp. that were isolated from children with shigellosis. The minimum inhibitory concentration (MIC) of Shigella isolates to azithromycin was determined by the agar dilution method in the presence and absence of Phe-Arg-ß-naphthylamide inhibitor. The presence of 12 macrolide resistance genes was investigated for all isolates by PCR for the first time in Tehran province in Iran. Among the 120 Shigella spp., only the mph(A) gene (49.2%) was detected and other macrolide resistance genes were absent. The phenotypic activity of efflux pump was observed in 1.9% of isolates which were associated with over expression of both omp(A) and omp(W) genes. The high prevalence of the mph(A) gene among DSA isolates may indicate that azithromycin resistance has evolved as a result of antimicrobial selection pressures and inappropriate use of azithromycin.

MicroRNAs in the interaction between host-bacterial pathogens: A new perspective.

Gene expression regulation plays a critical role in host-pathogen interactions, and RNAs function is essential in this process. miRNAs are small noncoding, endogenous RNA fragments that affect stability and/or translation of mRNAs, act as major posttranscriptional regulators of gene expression. miRNA is involved in regulating many biological or pathological processes through targeting specific mRNAs, including development, differentiation, apoptosis, cell cycle, cytoskeleton organization, and autophagy. Deregulated microRNA expression is associated with many types of diseases, including cancers, immune disturbances, and infection. miRNAs are a vital section of the host immune response to bacterial-made infection. Bacterial pathogens suppress host miRNA expression for their benefit, promoting survival, replication, and persistence. The role played through miRNAs in interaction with host-bacterial pathogen has been extensively studied in the past 10 years, and knowledge about these staggering molecules' function can clarify the complicated and ambiguous interactions of the host-bacterial pathogen. Here, we review how pathogens prevent the host miRNA expression. We briefly discuss emerging themes in this field, including their role as biomarkers in identifying bacterial infections, as part of the gut microbiota, on host miRNA expression.

Robust estimation of noise for electromagnetic brain imaging with the champagne algorithm.

Robust estimation of the number, location, and activity of multiple correlated brain sources has long been a challenging task in electromagnetic brain imaging from M/EEG data, one that is significantly impacted by interference from spontaneous brain activity, sensor noise, and other sources of artifacts. Recently, we introduced the Champagne algorithm, a novel Bayesian inference algorithm that has shown tremendous success in M/EEG source reconstruction. Inherent to Champagne and most other related Bayesian reconstruction algorithms is the assumption that the noise covariance in sensor data can be estimated from "baseline" or "control" measurements. However, in many scenarios, such baseline data is not available, or is unreliable, and it is unclear how best to estimate the noise covariance. In this technical note, we propose several robust methods to estimate the contributions to sensors from noise arising from outside the brain without the need for additional baseline measurements. The incorporation of these methods for diagonal noise covariance estimation improves the robust reconstruction of complex brain source activity under high levels of noise and interference, while maintaining the performance features of Champagne. Specifically, we show that the resulting algorithm, Champagne with noise learning, is quite robust to initialization and is computationally efficient. In simulations, performance of the proposed noise learning algorithm is consistently superior to Champagne without noise learning. We also demonstrate that, even without the use of any baseline data, Champagne with noise learning is able to reconstruct complex brain activity with just a few trials or even a single trial, demonstrating significant improvements in source reconstruction for electromagnetic brain imaging.

Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework.

Methods for electro- or magnetoencephalography (EEG/MEG) based brain source imaging (BSI) using sparse Bayesian learning (SBL) have been demonstrated to achieve excellent performance in situations with low numbers of distinct active sources, such as event-related designs. This paper extends the theory and practice of SBL in three important ways. First, we reformulate three existing SBL algorithms under the majorization-minimization (MM) framework. This unification perspective not only provides a useful theoretical framework for comparing different algorithms in terms of their convergence behavior, but also provides a principled recipe for constructing novel algorithms with specific properties by designing appropriate bounds of the Bayesian marginal likelihood function. Second, building on the MM principle, we propose a novel method called LowSNR-BSI that achieves favorable source reconstruction performance in low signal-to-noise-ratio (SNR) settings. Third, precise knowledge of the noise level is a crucial requirement for accurate source reconstruction. Here we present a novel principled technique to accurately learn the noise variance from the data either jointly within the source reconstruction procedure or using one of two proposed cross-validation strategies. Empirically, we could show that the monotonous convergence behavior predicted from MM theory is confirmed in numerical experiments. Using simulations, we further demonstrate the advantage of LowSNR-BSI over conventional SBL in low-SNR regimes, and the advantage of learned noise levels over estimates derived from baseline data. To demonstrate the usefulness of our novel approach, we show neurophysiologically plausible source reconstructions on averaged auditory evoked potential data.

The controversial association of gut and urinary microbiota with kidney stone formation.

Nephrolithiasis (kidney stones) is one of the most common chronic kidney diseases that are typically more common among adult men comparing to adult women. The prevalence of this disease is increasing which is influenced by genetic and environmental factors. Kidney stones are mainly composed of calcium oxalate and urinary oxalate which is considered a dangerous factor in their formation. Besides diverse leading reasons in the progression of nephrolithiasis, the gut and urinary microbiome has been recognized as a major player in the development or prevention of it. These microbes produce metabolites that have diverse effects on host biological functions. Therefore, Changes in the composition and structure of the microbiome (dysbiosis) have been implicated in various diseases. The present review focuses on the roles of gut and urinary in kidney stone formation.

Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

Computational chemistry provides a versatile toolbox for studying mechanistic details of catalytic reactions and holds promise to deliver practical strategies to enable the rational in silico catalyst design. The versatile reactivity and nontrivial electronic structure effects, common for systems based on 3d transition metals, introduce additional complexity that may represent a particular challenge to the standard computational strategies. In this review, we discuss the challenges and capabilities of modern electronic structure methods for studying the reaction mechanisms promoted by 3d transition metal molecular catalysts. Particular focus will be placed on the ways of addressing the multiconfigurational problem in electronic structure calculations and the role of expert bias in the practical utilization of the available methods. The development of density functionals designed to address transition metals is also discussed. Special emphasis is placed on the methods that account for solvation effects and the multicomponent nature of practical catalytic systems. This is followed by an overview of recent computational studies addressing the mechanistic complexity of catalytic processes by molecular catalysts based on 3d metals. Cases that involve noninnocent ligands, multicomponent reaction systems, metal-ligand and metal-metal cooperativity, as well as modeling complex catalytic systems such as metal-organic frameworks are presented. Conventionally, computational studies on catalytic mechanisms are heavily dependent on the chemical intuition and expert input of the researcher. Recent developments in advanced automated methods for reaction path analysis hold promise for eliminating such human-bias from computational catalysis studies. A brief overview of these approaches is presented in the final section of the review. The paper is closed with general concluding remarks.

Bacteriophage therapy for inhibition of multi drug-resistant uropathogenic bacteria: a narrative review.

Multi-Drug Resistant (MDR) uropathogenic bacteria have increased in number in recent years and the development of new treatment options for the corresponding infections has become a major challenge in the field of medicine. In this respect, recent studies have proposed bacteriophage (phage) therapy as a potential alternative against MDR Urinary Tract Infections (UTI) because the resistance mechanism of phages differs from that of antibiotics and few side effects have been reported for them. Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis are the most common uropathogenic bacteria against which phage therapy has been used. Phages, in addition to lysing bacterial pathogens, can prevent the formation of biofilms. Besides, by inducing or producing polysaccharide depolymerase, phages can easily penetrate into deeper layers of the biofilm and degrade it. Notably, phage therapy has shown good results in inhibiting multiple-species biofilm and this may be an efficient weapon against catheter-associated UTI. However, the narrow range of hosts limits the use of phage therapy. Therefore, the use of phage cocktail and combination therapy can form a highly attractive strategy. However, despite the positive use of these treatments, various studies have reported phage-resistant strains, indicating that phage-host interactions are more complicated and need further research. Furthermore, these investigations are limited and further clinical trials are required to make this treatment widely available for human use. This review highlights phage therapy in the context of treating UTIs and the specific considerations for this application.