Protein and drug engineering comprises a major part of the medical and research industries, and yet approaches to discovering and understanding therapeutic molecular interactions in biological systems rely on trial and error. The general approach to molecular discovery involves screening large libraries of compounds, proteins, or antibodies, or in vivo antibody generation, which could be considered “bottom-up” approaches to therapeutic discovery. In these bottom-up approaches, a minimal amount is known about the therapeutics at the start of the process, but through meticulous and exhaustive laboratory work, the molecule is characterised in detail. In contrast, the advent of “big data” and access to extensive online databases and machine learning technologies offers promising new avenues to understanding molecular interactions. Artificial intelligence (AI) now has the potential to predict protein structure at an unprecedented accuracy using only the genetic sequence. This predictive approach to characterising molecular structure—when accompanied by high-quality experimental data for model training—has the capacity to invert the process of molecular discovery and characterisation. The process has potential to be transformed into a top-down approach, where new molecules can be designed directly based on the structure of a target and the desired function, rather than performing screening of large libraries of molecular variants. This paper will provide a brief evaluation of bottom-up approaches to discovering and characterising biological molecules and will discuss recent advances towards developing top-down approaches and the prospects of this. Understanding and predicting molecular interactions in living systems and designing new molecules to bind to, destroy, disrupt, or promote biological molecular pathways have long been driving forces behind much of molecular biology research and funding. In recent years, the therapeutics industry has boomed. In 2020, the FDA approved 53 drugs, the second highest approval rate ever , and theThe novel coronavirus pandemic has highlighted the urgency for efficient discovery and production of molecular therapeutics. For example, the first drug to be approved across major global regulatory authorities for the antiviral treatment of COVID-19 was remdesivir see , where iAdvances in molecular discovery have traditionally focussed on improving the efficiency and reliability of in vitro and in vivo discovery and synthesis techniques, approaches which can be considered as “bottom-up” techniques. In this review we specifically define “bottom-up” as methods for therapeutic molecular discovery that use animal antibody generation (in vivo), or the screening vast libraries of potential therapeutic molecules against therapeutic targets (in vitro), where molecules with the best biological response are selected see . These aMolecular discovery may be broadly grouped into in vivo, in vitro and in silico approaches. Most current approaches to molecular discovery may be considered bottom-up, particularly for in vivo or in vitro approaches, as generally little is known about the conformation of the final therapeutic before screening or antibody generation takes place. Whilst these techniques have not yet succeeded in flipping discovery towards top-down approaches, the field has produced a wealth of innovation and advancements that have enabled significant leaps in the field of therapeutic discovery. The therapeutics discovery pipeline has been outlined in 11 different molecular combinations [In vivo techniques have typically relied on the animal and human natural adaptive immune response, where antibodies are produced upon immunisation with a desired antigen ,11,12 s. Many tyinations . Humanisinations , where pinations . HybridoThere are some limitations to in vivo techniques, but new innovations have sought to overcome these. First, mAbs produced in non-human models traditionally require humanisation in order to minimise undesirable responses from the human immune system . HoweverWhile traditional in vivo methods benefit from the tremendous natural diversity of the animal immune response, they are not as high throughput as library screening techniques. It can take a significant amount of time (around 6 weeks ) for immBothrops jararacussu snake venom [In vitro approaches were initially aimed towards widening the range of possible therapeutic molecule types and making discovery more easily scalable than in vivo techniques. Techniques are generally geared towards mimicking the natural immune response in vitro and technological advances broadly involve widening the sampling of chemical space through high-throughput wet lab technologies. In addition to now having higher throughput than in vivo approaches, in vitro techniques can allow for screening against toxic compounds that may alternatively have been difficult or cumbersome to produce neutralising antibodies for in vivo approaches. For example, antivenoms can be produced in vitro, rather than using the traditional approach of horse immunisation. One approach used phage-displayed camelid nanobodies to produce neutralising activity against ke venom . High coke venom  make in Most in vitro techniques rely on the production of hugely diverse libraries of chemicals, peptides, antibodies, or antibody fragments, with the aim of isolating unique variants from the combinatory pool that will bind to a desired antigen. This means that larger library diversities are more advantageous as the likelihood of identifying a suitable binder scale proportionally. Libraries can be either labelled (linked to a descriptive tag such as DNA) or unlabelled. Labelled library types include well-established phage display ,26, bactInitial molecular discovery techniques did not involve the use of labelled libraries, and instead relied on the synthesis and individual storage of unique compounds. A limitation in the size of available molecular libraries was, for a significant period, one of the major bottlenecks to new molecule discovery . The advDeveloped by George Smith in 1985, phage display has been one of the driving technologies for the discovery of new antibodies and peptides through labelled molecular library screening . It is o8 molecules, where compounds are chemically conjugated to DNA sequences that indicate their chemistry. Cell-free display techniques such as mRNA display allow for the production of libraries, with some of the largest degrees of genetic variation—reportedly above 1012 variants—because they can employ PCR-based approaches for generation of library variation [There is a range of different labelled approaches see  that areariation . Some teariation . In thisOne notable drawback of cell-free in vitro display methods is that the size and complexity of the molecules that can be expressed are usually limited. For example, phage display is limited by attenuation of phage infectivity and inefficient incorporation of large proteins into the major pIII phage coat protein . Normall9 variants [In contrast, cellular techniques such as bacteria, yeast, and mammalian surface display have the advantage of allowing for the display of larger molecules and do not require the post-panning bacterial infection step that may cause infection efficiency bias in enriched phage libraries. However, due to the necessity for cell transformation, cell display library sizes are smaller, reaching about a maximum of about 10variants . Both ceIt is possible that future peptide library panning campaigns will not require a genotype–phenotype linkage. Recently, a nanopore sequencing technique has allowed for the direct sequencing of a 26-amino-acid peptide sequence . This noGO [Approaches to improve the efficiency of labelled molecular library screening are becoming increasingly inventive. Microfluidics platforms are one of the most prevalent tactics to improve speed and efficiency of biopanning. Generally, these platforms are designed to reduce sample volume, create controllable fluid dynamics (uniform shear stress and velocity gradient), improve panning efficiency, and allow for automation of the biopanning process. It is important to be able to control fluid dynamics in panning systems, as mechanical force variation from shear stress induced in fluid flow affects peptide and antibody affinity for targets significantly ,66,67,68GO  use dropGO . This phGO ,76,77,78GO —which caGO .Bottom-up in silico  approaches have grown from complementing and augmenting in vivo and in vitro experimental techniques for molecular discovery. Techniques either search the theoretical chemical space to produce a list of candidate molecules that can be verified for function with wet-lab experiments or search already wet-lab-characterised molecules to find suitable structural templates for novel molecular design. More recently, computational methods have been used to begin to design molecules de novo, using data available online compiled from years of wet-lab experimental work. This is a movement towards more top-down molecular discovery approaches and will be described in more detail in the latter part of this review. In this section, some of the prominent bottom-up molecular discovery techniques will be briefly discussed.60 [It has become common for chemical libraries to undergo screening for activity against therapeutic targets using in silico approaches, as it is infeasible for in vitro synthesised libraries to represent the full extent of the possible drug-like molecules . The acc60  observab60 . In sili60 . General60 . Virtual60  currentl60 ,87. MoleMost current in silico techniques for discovery of biologically generated molecules (peptides and antibodies) are designed to enhance and compliment wet-lab experimental data by building on and enhancing known structures. For example, computational modelling using data from BLAST searches of custom online databases and PDB has been used to assist prediction of the in vitro developability of antibodies  or to moHomo sapiens, where at present, there are about 79,000 known proteins in the proteome as described in the online database UniProt [Whilst using the available molecular docking programs enables a far higher-throughput approach to screening the vast chemical space, these approaches are not yet able to comprehensively flip therapeutic discovery to a top-down approach. Although chemical compound structures are more easily computationally predicted than proteins, molecular docking still requires the input of a high-resolution image of the target structure (preferably ligand-bound) . Protein UniProt . Further UniProt . TherefoThe current pipeline for taking new therapeutic molecules from discovery to clinic involves an incredibly lengthy, complex, and expensive process. This is in part because drug development necessitates collaborations between many fields of expertise, from chemists and biologists to process scientists, clinicians, intellectual property and industry specialists and partners. It has been estimated that the median capitalized development and research cost to bring a new medicine to FDA approval in the United States between 2009 and 2018 was about USD 985 million, with projected costs expected to be in the billions . The medThere is an extraordinary amount of resources used in the current drug development pipeline. It takes years of work in the laboratory to first study and understand the biology of new therapeutic targets. Vast arrays of possible effector molecules are then screened against these new targets and narrowed down to a small cohort of binders, which are then characterised and further tested. Understanding the mechanisms and key targets for certain diseases can take entire careers to research and discover; thus, the next hurdle of developing a new therapeutic and taking it to clinic remains. For example, high-throughput molecular screening approaches for new drug discovery, such as phage-displayed library panning and enrichment ,26 take Once a drug has been isolated, it must then make it to the clinic. If enough funding and support is received, and a candidate molecule has been successfully isolated, trials can then begin in a small group of patients. If the molecule passes safety and efficacy tests, then the trials can expand to larger groups of patients. Because it takes a significant amount of funding to develop new therapeutics, it becomes a substantial gamble and barrier for investors on whether a potential new molecule will have clinical value compared to existing treatments. Unfortunately, this means that many drugs may not make it to the clinic simply because they have not received the required financial support. Once the therapeutic has been shown to have efficacy, it must still be able to be manufactured and distributed in a form that it is conducive to its use . Therefore, it is of significant interest to develop new techniques for therapeutics development that give investors and prescribers greater confidence in the efficacy of the product. Greater confidence that the molecule is going to behave in a more predictable way through patient trials and in the market will help to streamline the development process, reducing barriers to investment and delivery to patients.The time and costs are not the only negatives associated with the slow and expensive drug development pipeline. Current limitations in the discovery pipeline means that current disease treatment tends towards more generic, rather than personalised approaches, which can affect patient experience and outcomes. With existing technologies, it is not yet feasible to develop molecular therapeutics on a patient-to-patient basis, although individual patient screening and characterisation and the use of global therapeutics that are tailored to a patients’ clinical presentation is generally regarded by clinicians as crucial ,105,106.Targeted therapeutics such as mAbs have high specificity for target antigens and have been employed as therapeutic agents for the past two decades . AntibodTop-down approaches, where we can design a therapeutic from scratch and be able to predict molecular interactions, would have a massive benefit to streamlining the development pipeline and ultimately to patients. If we could design a therapeutic from scratch to specifically interact with a desired target, then it is possible that we could design novel therapeutics or modify existing ones with their specific interactome in mind. This would enable better prediction, and possibly elimination, of off-target toxicities in patients and better tools for clinicians to predict which patients to prescribe and which patients not to prescribe. For the same reasons, a top-down approach may help to streamline many areas of the therapeutics development pipeline, not only by improving molecular design but by making products more likely to be competitive in the market. Increased confidence in and better prediction of drug performance shifts the risk of drug development to earlier in the pipeline, where there is minimal collateral damage incurred upon the failure of a new product. This could help reduce barriers to financial investment and regulatory approval at later stages of the pipeline by increasing the likelihood and predictability of drug success.Recent advances in computational science are beginning to make the paradigm shift to a top-down approach for molecular discovery possible. Major developments in high-throughput technologies, including next generation sequencing, protein expression and protein characterisation, protein structure deconvolution and computational advances, are the foundation for shifting to top-down technologies. The wealth of information available pertaining to molecular sequence and structural information in online databases has accelerated computational technologies to the forefront of top-down molecular discovery approaches. Whilst many computational approaches have largely focussed on improving known target-ligand interactions or are designed to complement wet-lab techniques, recently, there has been a shift towards developing entirely de novo molecular designs.A range of de novo approaches to molecular design has been developed to date. Deep and reinforcement learning has been used to generate novel chemical libraries that have desired properties. A novel computational strategy call ReLeaSE  integrates a generative and a predictive deep neural network to generate libraries of de novo structures. These libraries can be geared towards having certain levels of structural complexity, or a specific range of physical properties , or to have inhibitory activity against certain targets. Specifically designing libraries in this manner allows molecular libraries to be targeted towards certain functions and increases the likelihood of finding a molecule with desired properties in wet-lab experiments. The process of obtaining a new binder using this method is not strictly top-down, as the new libraries still need to be specifically screened against the target of interest. However, they still use de novo molecular generation techniques to create desired properties; thus, this could be viewed as a top-down approach in this aspect.Nres × Nres array) that are refined as they progress through the model. The final paired and MSA representations are then fed into a model that gives 3D structure in terms of rotation and translation for each residue of the protein, and further iterative refinement processes in the model produces an output of predicted protein structure.ML algorithms trained using sets of known structures of proteins available online on PDB and other databases have recently made significant advances in predicting protein folding ,126,127.Saccharomyces cerevisiae, 699 of which had been structurally characterised and 700 of which were supported in the literature. However, these are predictions of stable protein complex formations, which would likely have highly conserved and stable pMSAs through different species, due to the nature of the interaction being under significant selective pressure. More transient, weaker interactions that are under lower selective pressure were noted by the authors as likely to be difficult to predict, as well as binary protein complexes from high-order obligate protein associations. It was also noted that predictions would be inaccurate for species-unique protein complexes and that there would be an overrepresentation of hydrophobic or amphipathic domains. As well as this, recent approaches involving deep network hallucination have investigated the generation of new proteins with entirely novel backbone structures and amino acid sequences [There is a range of groups that have produced variations or alternatives to the technology, particularly since the second iteration of AlphaFold from the CASP14 competition. The team behind the second-best protein structure prediction method after AlphaFold, RoseTTAFold , which cequences .Other groups have made significant steps towards de novo design of target-binding proteins given nothing but the target structure. The design of proteins given no other information (such as homologous target-binding proteins) other than the target structure has been a major challenge for in silico therapeutics development. As previously described, it is challenging to predict interactions that are more transient, non-covalent and under lower selective pressure. The David Baker lab at EMBL-EBI is one of the first groups claiming to be able to perform de novo design for more transient interactions of protein binders and targets. In this work, the group has moved beyond using a native or homologous protein scaffold and previously identified hot-spot residues to identify and predict proteins with favourable and more transient interactions . This apSpirited claims have been made that the recent advances in machine learning models are one of the greatest developments in structural biology in the past 20 years, which is also one of the biggest achievements in artificial intelligence in recent history . Some hahttps://github.com/deepmind/alphafold, accessed on 28 February 2022), the value in ML lies not in the code but in the training dataset. ML algorithms will have markedly different outputs depending on the data they are trained on. Whilst it is possible to recreate the AlphaFold training dataset, it remains highly computationally challenging and time consuming to build and mimic. This means that whilst the code may have been released for these ML algorithms, it is not in a form that allows this technology to be readily accessed by researchers to predict new structures or interactions. As well as this, whilst data for protein structure are readily available, the complexity of molecular interactions and a limit to online datasets specific to molecular interactions and therapeutics make AI for molecular discovery and interaction predictions challenging. Regardless of the challenge of compiling a robust and accessible drug-related database, proteins are constantly in motion in cells [Whilst the prospects of this computational achievement are exciting, it remains a question of how realistically useful and reliable these models are in their current state, particularly for molecular discovery applications. Foremost, this technology is not yet user friendly or easy to access by anyone who is not an expert in the field. For example, whilst the open-source code for AlphaFold has been released and is publicly available (in cells . Not onlin cells . Google’in cells . Howeverin cells . AlphaFoin cells . It is aAlthough there are many caveats to in silico predictive technologies that need development, there is still much promise in the field. Similar issues to accurate structure and protein interaction prediction exist with any protein structure imaging technique. Whether an image is obtained in the holo or apo state, it is still only a snapshot of the possible conformations that this protein could undertake. As previously mentioned, there are also a significant number of protein structures in PDB that are relatively low resolution due to limitations to wet-lab experimental approaches; thus, ML techniques such as AlphaFold could help to improve the ability to perform molecular docking with these structures. Post-translational modifications, such as glycosylation, and flexible, less constrained domains are also still difficult to structurally determine using X-ray crystallography . It may It is not yet clear how this new AI technology can be adopted by drug developers, and in which role it will play in therapeutics development. It can be hypothesised that the technology will streamline and accelerate the journey to progress a therapeutic from discovery to clinic. If successful, the technology could reduce the time taken to obtain new therapeutics, by reducing or perhaps eliminating the need for bottom-up or library screening approaches. Blue-sky thinking would encourage the idea that we may begin to create drugs on an individual patient basis. Potentially, the technology could allow for identification and screening of off-target binders that produce toxicity for patients by allowing whole proteome screening. Being able to reduce the risk of patient toxicity would certainly improve investor confidence that the drug candidate will be successful in clinic, as well as decreasing the likelihood of failure through clinical trials. These things would allow for the acceleration of therapeutics through the development journey. Whilst the recent predictive technologies are a shift in the top-down approach to molecular discovery, in the current state, they are not yet positioned to replace the existing gold standard in in vivo and in vitro techniques. As well as this, biological diversity is thus large that the amount of information that would need to be processed for AI to predict off-targets for a single existing drug for each patient with high accuracy would be vast, let alone creating new drugs on a patient-by-patient basis. Predictive models such as AlphaFold still require significant development and further prospective validation experiments, but existing data are promising.Before computational approaches can enable a top-down approach to drug discovery, a united effort between all areas of bottom-up therapeutics discovery will likely be required. Expansive, high-quality wet-lab data are generally considered as critical for the development of successful ML algorithms for molecular discovery . Large vThere is a clear need for a more efficient pipeline for the journey of therapeutics, from discovery to the clinic, as highlighted by the recent novel coronavirus pandemic. Emerging AI technologies may enable a smoother transition through the various stages of the pipeline, including reducing barriers such as regulatory hurdles and market performance.Bottom-up techniques are slower and more resource exhaustive than top-down techniques and, due to the nature of the approach, requires much downstream characterisation and validation. It is recommended that we should continue to improve the quality of data generated from bottom-up technologies. This will be a critical step to move to top-down technologies, as these data will feed these new approaches.The earlier that the risk of failure of the development of a new drug is addressed and predicted, the more likely it is that the drug will successfully and quickly reach the clinic with minimal losses. It is recommended that we move towards top-down approaches to drug discovery that enable stronger understanding of molecular behaviour, as investors are more likely to support a drug that they are confident will be successful and competitive in the market.It is hypothesised that access to more personalised medicine will enable clinicians to effectively compete with the biological intricacies of complex disease.Emerging top-down AI technologies are improving the prediction of molecular structures, molecular behaviour and optimal de novo drug design. It is recommended that we continue to incorporate and improve these techniques into therapeutics discovery, as they will help to streamline the development pipeline, although further work is needed to contend with the massive complexity of biological systems.Encouraging the sharing and improved accessibility to ML approaches for people who are not specialists in the field may help to drive innovation and discovery with new ideas and perspectives.The recent advances in therapeutics discovery have the potential to be highly beneficial to all areas of the drug discovery journey. In summary, the critical points from this review article are:


Self-expanding nitinol stent (SENS) implantation is commonly oversized in the superficial femoral artery (SFA), and leads to chronic outward force (COF) and in-stent restenosis (ISR). This study aimed to investigate the impact of COF of oversizing SENS on ISR of SFA.In patients with implanted SENS in SFA, intimal hyperplasia especially between proximal segment and distal segment was evaluated by quantitative angiography, and the impact of COF on mid-term angiographic outcomes was investigated. In addition, porcine model with implanted SENS was used to evaluate the impact of COF on angiographic and histopathologic outcomes at 1 month. Excised stented arteries were evaluated by histopathologic analysis.P < 0.001). In the long SFA stent, stent-to-vessel ratio was significantly higher in the distal stent than in the proximal stent . ISR incidence was higher at the distal stent . All 11 pigs survived for 4 weeks after SENS implantation. The vessel diameter was 4.04 ± 0.40 mm (control group) vs 4.45 ± 0.63 mm (oversized group), and the implanted stent diameter was 5.27 ± 0.46 mm vs. 7.18 ± 0.4 mm (P = 0.001). The stent-to-vessel diameter ratio was 1.31 ± 0.12 versus 1.63 ± 0.20 (P < 0.001). After 4 weeks, restenosis % was 29.5 ± 12.9% versus 46.8 ± 21.5% (P = 0.016). The neointimal area was 5.37 ± 1.15 mm2 vs. 8.53 ± 5.18 mm2 (P = 0.05). The restenosis % was 39.34 ± 8.53% versus 63.97 ± 17.1% (P = 0.001).We analyzed 65 SENS in 61 patients with follow-up angiography at 6 months to 1 year. The baseline diameter was 6.8 ± 0.71 mm and length were 97.0 ± 33.8 mm for the SENS. The ratio of the diameter of the stent to the reference vessel was 1.3 ± 0.24 at the proximal portion and 1.53 ± 0.27 at the distal portion (COF is an important cause of restenosis in the distal portion of the SFA stent. Optimal sizing of the SFA stent is important to reduce the incidence of restenosis. Therefore, COF was an important factor of restenosis following distal SFA stenting. Balloon angioplasty and stent implantation are popular in patients with peripheral artery disease (PAD) –3. The sThis study aimed to evaluate the impact of SENS oversizing on ISR of SFA. We examined clinical and animal experiments data to determine the impact of COF on the arterial wall, and investigated the impact of SENS oversizing with respect to continued expansion following stenting and the mid-term histological impact of oversized stent on SFA.The clinical evaluation focused on intimal hyperplasia especially between the proximal and distal segments by implanted SENS in SFA. Quantitative angiography (QA) was used to determine the ISR rate following mid-term catheter angiography. The impact of COF on mid-term angiographic and clinical outcomes was investigated Fig. .Fig. 1FlPreclinical data were obtained from a porcine model following SENS  implantation. The model was used to evaluate the impact of COF on angiographic outcomes and histopathologic outcomes at 1 month. Control pigs received an adequately sized SENS, whereas the COF group received an over-sized stent 1.5 to 1.8 times larger than the control size. At 4 weeks, catheter angiography and histopathologic evaluation was performed  registry of Korea University Guro Hospital (KUGH) . PTA registry is a single-center, prospective, all-comer registry designed to reflect “real world” practice since 2004. Patients had signs of a moderate intermittent claudication (Rutherford stage 2), severe intermittent claudication (Rutherford stage 3) or ischemic pain (Rutherford stage 4), or significant atherosclerotic effect in one or both femoral arteries (stenosis diameter > 70%).Data were collected by a trained study-coordinator, following a standardized case report form. The participants or their legal guardians provided written consent to participate in the study. The study protocol was approved by Medical Review Board of KUGH.Aspirin and clopidogrel were used in all patients and 70 U/kg heparin were given after the start of the procedure. After local anesthesia with Lidocain 2% 5F or 6F sheath was delivered through the femoral artery by the Seldinger approach. If balloon angioplasty or stenting proved technically feasible by ipsilateral antegrade approach, an antegrade puncture was preferred. Otherwise, a contralateral femoral approach or retrograde puncture from the distal SAF or proximal tibial access for bi-directional approach was used.A 5-Fr Omni internal mammary catheter, or Judkin's right catheter was inserted into the aortic-iliac artery branch when contralateral approach was needed. The introducing soft Terumo wire was inserted into the lesion, and then the guiding sheath was placed for SFA treatment. Most frequently used guiding sheaths were 6F Ansel Checkflo , 6-8F Balkin sheath  or 8F Contralateral-1 guiding sheath .After the successful wire crossing by 018 or 035 long wires, conventional balloon angioplasty was performed. The balloon dilatation duration was extended for at least 120 s with adequately sized balloon . Once the balloon response was not favorable, including flow limiting intimal dissection, significant residual stenosis or thrombus formation, SENS was implanted. Angiographic success was considered to be the case when residual stenosis was < 30% after the procedure and blood flow was well maintained through and distal to the target lesion.Patients with successful intervention were clinically followed at 30 days and 3 months respectively to monitor the diabetic foot recovery or the severity of symptoms. Patients were strongly recommended for mid-term imaging follow-up by invasive or CT angiography at 6 to 12 months. QA was used to assess the impact of COF on ISR in proximal and distal SFA stents.Animal experiments were conducted at the K-BIO Osong Animal Research Center and the protocols were approved by Animal Care and Use Review Board (No. KBIO-IACUC-2016–005) according to the guidelines by the National Institute of Health. Eleven non-atherosclerotic female pigs (weight 25–35 kg) were assigned. Twenty self-expanding nitinol stents  5.0–8.0 mm in diameter and 30–50 mm in length were used.Aspirin (100 mg/day) and clopidogrel (75 mg/day) were given 3 days before the procedure. On the day of the procedure, after general anesthesia with isoflurane followed by respiratory anesthesia using an animal ventilator, the right carotid artery was incised, the carotid artery was exposed, a 6-F sheath was inserted, and 200 IU/kg of heparin was injected. The 6-F guiding catheter was inserted into the SFA and baseline SFA angiography was performed. SFA in the control group was treated using SENS of the appropriate size. SFA in the COF group was treated by an oversized stent. After the procedure, the carotid artery was ligated, the pigs were transferred to the breeding farm and observed for 4 weeks. During this period, aspirin and clopidogrel were administered continuously.The effect of COF was analyzed by angiography and histopathologic results. After 4 weeks, catheter angiography was performed through the opposite carotid artery, and QA using CAAS software was used for the evaluation of stent patency, fracture, and ISR degree. To be euthanized, pigs are given an intravenous carbon dioxide/oxygen gas mixture after general anesthesia with isoflurane and excised stented arteries were fixed in 10% formalin for 24 h for histopathologic analysis of inflammation, necrosis and intimal hyperplasia.The tissues were embedded in paraffin and cut into fine section (50–100 μm) using a low-speed diamond wafer mounted on an isoment saw . After hematoxylin and eosin (H&E) staining, the sections were analyzed by calibrated microscope digital video imaging system and a VISUS 2000 computerized visual image analysis system. The external elastic lamina (EEL) area, internal elastic lamina (IEL) area and the lumen area of the central, proximal and distal part of the stent from pig SFA were examined. The area stenosis of the stent vessels was conventionally calculated as: 100 × (1-lm area/IEL area).The injury score of the vessel wall by the stent and inflammation score were evaluated by Schwartz method . The injP < 0.05 was considered statistically significant.All statistical analyses were performed using SPSS for Windows version 20.0 . The normality was verified via one-sample Kolmogorov–Smirnov test. Continuous variables are expressed as mean ± standard deviation (SD), categorical data were reported as frequencies and percentages. Unpaired Student's t-test were used to compare continuous variables while Chi-square test was used to compare categorical variables. Correlation between the stent/vessel ratio and the stenosis results was determined using linear regression analysis. The receiver operating characteristic (ROC) analysis was performed to get area under the curve (AUC). P = 0.619). The mean stent diameter and length was 6.8 ± 0.71 mm and 97.0 ± 33.8 mm, respectively. The ratio of the diameter of the stent to the reference vessel was 1.3 ± 0.24 at the proximal portion and 1.53 ± 0.27 at the distal portion (P < 0.01)  was 0.85 ± 1.32 at the proximal lesion site mm and 0.91 ± 1.15 mm at distal lesion site (P = 0.12). The mean stent diameter implanted in the control group was 5.27 ± 0.46 mm and 7.18 ± 0.4 mm in the oversized group (P = 0.001). The stent-to-vessel diameter ratio was 1.31 ± 0.12 versus 1.63 ± 0.20 in control and oversized groups, respectively (P < 0.001) (Table P = 0.002). In the histopathologic examination, the incidence of ISR was higher, lumen area was smaller, neointimal and stenosis area were larger in oversized group. There was a trend toward higher inflammation score in oversized group (Table P = 0.010)  aimed to overcome issues related to areas of high flexion and minimal COF . RecentlThe length of the SENS is also an important factor of ISR. Long stenosis (> 100 mm) had poor outcome, with restenosis rate exceeding 70% at 1 year . The resStents are designed to be larger in diameter than the healthy artery, which is referred as “stent oversizing” . The sigIn summary, we investigated the impact of oversized SENS implanted in tapered SFA arteries on restenosis caused by COF. Oversizing of the stent is an important determinant of final arterial wall diameter and stress. Therefore, SENS with optimal oversizing should be designed in cases with significant arterial tapering.In clinical study, our single-center retrospective study design only allowed for analysis based on our routine clinical practice. The sample size did not provide sufficient power to detect ISR incidence or compare clinical events. Operators were not blinded to baseline measures. Finally, our data reflected in-hospital outcomes, and we did not analyze long-term outcomes. Therefore, future randomized studies are needed to confirm our conclusions.In animal study, the sample size of 22 stents was small, and we did not find significant differences in incidence of restenosis or related parameters between the two groups. In addition, we used healthy animals with non-atherosclerotic arteries. Although blood vessels of pig are very similar to those of human, the results of animal experiments may not be same as those of clinical studies.COF is an important cause of restenosis in the distal portion of the SFA stent. Optimal sizing of the SFA stent implantation with SENS is important to reduce the incidence of restenosis. Therefore, COF was an important factor of restenosis following distal SFA stenting.


Antimicrobial resistance (AMR) is a global health threat. Antibiotics, heavy metals, and microplastics are environmental pollutants that together potentially have a positive synergetic effect on the development, persistence, transport, and ecology of antibiotic resistant bacteria in the environment. To evaluate this, a wide array of experimental methods would be needed to quantify the occurrence of antibiotics, heavy metals, and microplastics as well as associated microbial communities in the natural environment. In this mini-review, we outline the current technologies used to characterize microplastics based ecosystems termed “plastisphere” and their AMR promoting elements  and highlight emerging technologies that could be useful for systems-level investigations of AMR in the plastisphere. The increasing resistance of pathogenic bacteria to common antibiotics (AB) found in human and veterinary settings worldwide  highligh14 times higher than currently measured MP concentrations.The emerging contaminant—plastic—has potential to further enhance AMR by providing porous micro ecosystems termed “plastisphere” . In the via waste flows from industrial activities , but may also be mobilized due to natural processes  (The plastisphere creates a habitat that promotes attachment of and subsequent biofilm production by microbes . In thisthering) . HM pollthering) .It is hypothesized that weathering can intensify both HM  and AB aIn this mini-review, we discuss the role of plastisphere in the development of AMR, and the current technologies used to address various aspects of AB-HM-MP pollution and highlight the data gaps, novel techniques, and approaches.z-axis), enabling constructing landscape maps of surfaces. Spectroscopy methods based on molecular vibration such as Raman spectroscopy  depending on a variety of factors  of whichvia fluorescent self-transmissible plasmids  . Fluoresplasmids . To studplasmids . This isplasmids . Overallplasmids . Sequencplasmids .Metagenomics with possible combination of metatranscriptomics permits analysis of the species present in the microbial community, including non-culturable bacteria, while simultaneously studying regulation of ARGs, MRGs, and other genes at the mRNA/functional level within the whole community . FunctioIn vivo experiments with mice being exposed to HMs via oral administration followed by sequencing of the gut microbiota have shed light on the effect of HMs in mammals in vivo , might be to merge completely new analytical methods with the existing technologies . For nowin situ and ex situ experiments. Ex situ batch sorption experiments provide the opportunity to focus on specific parameters  presence of non-culturable bacteria and (2) expression level of resistant genes in the bacterial communities. Integrating metagenomics and metatranscriptomics with machine-learning tools such as DeepARG, trained to find the existing and novel ARGs and MRGs, is a suitable option for this challenge . Studyinvia their mass-to-charge ratio, and currently, there are three MSI methods commercially available for analyzing bacteria (Proteomic and metabolomic pathways in bacteria play an important role in AMR . 1D and bacteria . Though bacteria . Neverthbacteria . This enbacteria .Microbial colonization and ability to form biofilm are also heterogenous characteristics of microbes, and they play a key role in AMR. Microfluidic platforms show great potential for enabling complex biofilm studies , includiIn this mini-review, we highlighted technologies that have been used for analyzing different aspects of plastisphere-associated AMR. Although we found that many different aspects of AMR have been explored through multiple studies using advanced methods, knowledge gaps remain. To address these gaps, we summarize currently available technologies potentially suitable for future research. This should provide analytical tools for scientists of diverse backgrounds seeking answers for complex urgent problems: HM- and AB-contaminated plastisphere-associated promotion of AMR.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements  and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R The current epidemic involving the coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has completely disturbed the global health system and the world economy. The first patient of COVID-19 was reported in Wuhan, China, in December, 2019 [SARS-CoV-2 belongs to the family of Coronaviridae and the genus Betacoronavirus . These aAs this global pandemic has recently appeared and developing a new medicine for a disease usually takes a lot of time, to date, there is no side-effect-free vaccine or drug available for the prevention or the treatment of COVID-19. However, certain active pharmaceuticals, developed for other diseases, such as anti-malarial (Chloroquine and Hydroxychloroquine), anti-Ebola , and vaccines from Moderna, Pfizer, etc., have gained emergency use authorization from drug regulatory agencies in many countries for management of critical COVID-19 infections ,11,12. TFor the fast and cheaper development of medicines treating SARS-CoV-2, drug repositioning strategy is proposed. This approach is based on exploring the anti-SARS-CoV-2 potential of leverage molecules earlier reported to have inhibitory activity against genetically related viruses such as SARS-CoV.A high semblance of SARS-CoV-2 with SARS-CoV is a primary hope to develop a safer and cheaper drug candidate. That is, the existing knowledge about SARS-CoV, a high similarity of SARS-CoV-2 with SARS-CoV, and a compound previously tested for SARS-CoV is a viable candidate to develop a therapeutic drug. It is rational to believe that a SARS-CoV inhibitor could also be equipotent against SARS-CoV-2. In other words, a cheaper, time-saving, feasible strategy is to leverage molecules earlier reported to have inhibitory activity against similar viruses such as SARS-CoV.The e-Chemistry approach   and predictive (Quantitative) approaches ,20,21,22Generally, researchers use molecular docking based HTS (high-throughput screening) for identifying hits, but its hit rate ranges between 0.1 and 0.01% . TherefoMolecular docking is a contemporary structure-based drug design approach, which involves simulations of interactions between a lead/drug molecule with a target enzyme. It provides an in-depth knowledge and understanding of binding patterns to identify the important structural features of a small molecule that are responsible for its binding with the enzyme .Thus, a concomitant use of QSARs and molecular docking not only provides consensus and complementary information about prominent structural features but it is useful also to predict the bio-activity of a compound before its wet lab synthesis and testing. Therefore, in the present work, we employed QSARs, QSAR-based virtual screening, and molecular docking analyses to achieve the desired goals.In the present work, the QSAR analysis and molecular docking were performed to identify important structural features. The QSAR model was build using easily interpretable molecular descriptors to correlate them with structural features. The five-parametric GA–MLR model has good external predictive ability with the presence of easily understandable molecular descriptors along with interpretation in terms of structural features. Even though, in the present analysis, a straight evaluation of Ki values of the molecules of the dataset was performed to explain the effect of a specific descriptor, it is important to note that the combined or converse effect of unknown factors or other molecular descriptors could have a substantial effect on the Ki value of a molecule.pKi = 4.618 (± 0.415) + 2.774 (± 0.475) * fnotringCamdN3B + 0.762 (± 0.135) * aroN_sp3O_4B + 0.035 (± 0.021) * fringClipo5B + 0.962 (± 0.262) * flipoplaN2B −0.279 (± 0.089) * com_sp2O_5AR2tr = 0.898, R2adj. = 0.886, LOF = 0.291, trRMSE = 0.432, trMAE = 0.349, trCCC = 0.947, s = 0.460, F = 77.120, R2cv (Q2loo) = 0.859, cvRMSE = 0.507, cvMAE = 0.402, cvCCC = 0.926, Q2LMO = 0.848, R2Yscr = 0.102, Q2Yscr = −0.164, exRMSE = 0.648, exMAE = 0.537, R2ex = 0.799, Q21−F = 0.795, Q2−F2 = 0.795, Q2−F3 = 0.769, exCCC = 0.893R2tr (coefficient of determination), R2adj. (adjusted coefficient of determination), LOF (lack of fit), and R2cv (Q2loo)  indicate that the model comprises optimum number of variables and free from over-fitting. The high value of Q2LMO  confirms the acceptable internal validation of a model. The low value of R2Yscr and Q2Yscr (Y-scrambling related parameters) suggests that the developed model is free from chance correlations. The high value of R2ex , Q2n−F and exCCC (Concordance Correlation Coefficient) vindicate the acceptable external predictive ability. The F (Fischer F-ratio) value vindicates the high statistical significance of the model. In addition, an analysis of the correlation matrix  of the present dataset contain such a combination of amide Nitrogen and non-ring Carbon atoms as pyrrolidin-2-one ring. Konno et al., and Regnier et al. [r et al. ,34 have aroN_sp3O_4B: The molecular descriptor aroN_sp3O_4B points out the presence of aromatic Nitrogen atoms within foru bonds from sp3-hybridized Oxygen atoms. It is another molecular descriptor with positive coefficient in the developed model, therefore increasing the number of such combinations could augment the Ki value. Only eight molecules, which are also the top eight active candidates, possess a higher value of this molecular descriptor. These eight molecules are benzotriazole derivatives. This could be a reason for better Ki value for benzotriazole derivatives. The docking pose for molecule 1 supports the importance of aromatic Nitrogen atoms , 49 (4.34 M), 53 (3.95 M), 54 (3.95 M), 55 (3.87 M), and 60 (3.32 M) could be attributed to high frequency of occurrence of such Oxygen atoms within 5Å from center of mass of molecules (com_sp2O_5A = 5). Interestingly, all these molecules are peptidomimetic derivatives. There are five peptidomimetic molecules present in the top 15 molecules from the present dataset, which contain two to four such Oxygen atoms within 5Å from center of mass of molecules. Therefore, it is reasonable to say that the value of com_sp2O_5A should be less than five to a have good Ki value.In the present QSAR analysis, the constituent molecular descriptors of the GA–MLR QSAR model have provided salient and hidden information about the structural features related to diverse set of molecules tested for their activity for the main protease (Mpro). It is essential to understand that no single molecular descriptor can completely explain the observed distribution of Ki for such a diverse set of molecules. That is, the performance of the developed QSAR model relies on the concomitant use of constituent molecular descriptors.1 and food compounds used for virtual screening are available in 1 and the ten most active molecules from the food database, as predicted by the developed QSAR model. From The SMILES notations, calculated values of molecular descriptors, pKi and Ki for different variants of compound 13b is available, which was used to validate the docking protocol. 13b from the active site and relocking it again. The alignment of Mpro with the crystal ligand 13b and the redocked ligand is depicted in Main protease (Mpro), also known as Nsp5 and 3CLpro, is a cysteine protease enzyme active in homodimer form only ,35,36. I1 is most active, molecule 10 has a better docking score. In fact, molecule 10 has the sixth best docking score  with Glu166. The benzene part of indole moiety is near to Gln189 due to lipophilic interactions. The same observation is vindicated by the presence of two molecular descriptors flipoplaN2B and fringClipo5B, which highlight the importance of lipophilic atoms in the newly developed QSAR model. The -NH- part of Indole ring is accountable for the H-bond formation with Asp187 (2.31 Å). Thus, QSAR and molecular docking analyses provide similar, as well as complementary, results.From the docking pose, it appears that most active molecule 1  is acceptable conferred its stable conformation  showed alteration at the α-Helical turn (1 geometry (red). Moreover, there was a tilt of the ligand  during the course of simulation ). The dataset contains diverse compounds, thus covering enough chemical space. Then, dataset curation involving the removal of salts, duplicates, and entries with ambiguous Ki values led to a reduced dataset of sixty-two compounds. However, the remaining sixty-two compounds have a wide range of activities against SARS-CoV , thus justifying the composition of the dataset. Afterward, prior to subsequent QSAR analysis, the reported Ki values were converted to pKi (pKi = −log10Ki). The Simplified Molecular-Input Line-Entry System (SMILES) notation for all selected molecules, along with their reported activity values Ki and pKi are present in the In the present work, a dataset of 351 molecules was downloaded from Binding database  according to Organisation for Economic Co-operation and Development (OECD) principles. Model with a high internal and external predictive ability has been reported. Further details about the QSAR model development are available in the literature [After that, GA–MLR (Genetic Algorithm–Multilinear Regression)  was usedterature ,29,30,311 served as a template to generate a good number of heterocyclic variants using RDKit ). This resulted in a pool of 360 different heterocyclic variants. Moreover, a database of 26,467 food compounds was downloaded from FooDB (http://foodb.ca/ (accessed on 28 September 2020)), followed by the application of rule of five; the removal of duplicates, salts, and metal derivatives led to a reduced dataset of 8453 molecules. Thus, 8813 (360 + 8453) molecules were used for QSAR-based VS. Prior to molecular descriptor calculations, the 3D structures of molecules were prepared in the same way as modeling set. Then, the molecular descriptors were calculated, and the properly validated five-parametric QSAR model was used to predict the biological property of novel compounds.For QSAR-based virtual screening, the most active compound https://swissmodel.expasy.org/repository/species/ (accessed on 28 September 2020)). The pdb 6lu7 [The pdb file for main protease was fetched from SWISS-MODEL ). It has the ability to detect the surface cavities in a protein and use them as target binding-sites for docking simulations with the help of FlexAID [For the molecular docking analysis, the software NRGSuite  was used FlexAID . It uses FlexAID .13b, a known peptidomimetic inhibitor of Mpro [For validation of molecular docking, the molecule  of Mpro , was use1. To set up the simulations, initially, the systems were built for complex 1-Mpro and apo-Mrpo, respectively, in the system builder. For this purpose, Desmond 2018-4 was used to set up the initial parameters within explicit SPC water model orthorhombic box 4.0 × 4.0 × 4.0Å. The protease ligand complex and apo-Mpro were neutralized with NaCl salt by adding 0.15 M Na+ ions. The ASL module was used to select the specific residues of ligand and protein molecules for the better prepared systems, which were relaxed by using the Desmond default protocol of relaxation [1 were analyzed for the final outcome of root mean square deviation (RMSD), root mean square fluctuation (RMSF), and number of hydrogen bonds formation derived from simulation. Binding energies of the complexes were calculated by using MMGBSA [Molecular Dynamics Simulation (MDS) studies were carried out in order to determine stability and convergence  of main laxation . MDS runlaxation , at a telaxation . All othlaxation . After tg MMGBSA  for everg MMGBSA .1 within the active pocket of Mpro shed the light about the important pharmacophoric moieties involved in the binding interactions which are responsible for the inhibitory potential. It appeared that molecule 1 occupied the S1 and S2 pockets of the active site. Molecular docking and MD analysis identified the crucial role of triazole and benzene rings in establishing lipophilic and H-bonding with the important residues like Leu141, Met165, Glu166, Asp187, Gln189, etc., of the active site Mpro. QSAR and molecular docking provided consensus, as well as complementary pharmacophoric features, which therefore have to be retained in developing potent and selective SARS-CoV-2 inhibitors. Lastly, the significantly high binding energy of compound 1 with Mpro vindicates the higher affinity and opens the new arena for a novel inhibitor drug against SARS-CoV-2. The results could be highly useful to develop a therapeutic agent for SARS-CoV-2.In the present study, the repositioning approach of SARS-CoV inhibitors, alongside QSARs, QSAR-based virtual screening, and molecular docking–molecular dynamics analyses were performed to identify new potent inhibitor candidates against main protease of SARS-CoV-2. A five parametric GA–MLR QSAR model was developed to identify the main pharmacophoric features that govern the Mpro inhibitory activity. Internal and external validation and other stringent tests according to OECD principles were performed for the developed model. From the present analysis, pharmacophoric features like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, lipophilic atoms, etc., appeared as prominent features that govern the Mpro inhibitory activity. The developed QSAR model possesses high external predictive ability and robustness for fitting and internal validation. In addition, virtual screening successfully offered new derivatives of molecule 1 and from food database with improved Ki values in the range from 0.59 to 11.59 nM. Additionally, molecular docking of active candidate


Background: Antimicrobial resistance (AMR) represents a significant global public health crisis. Despite ample availability of Gram-positive antibiotics, there is a distinct lack of agents against Gram-negative pathogens, including carbapenem-resistant Enterobacterales, which remains a real threat in Japan. The AMR Action Plans aim to mitigate the growing public health concern posed by AMR.Objective: This study aims to estimate the clinical and economic outcomes of drug-resistant Gram-negative pathogens forecasts for Japan to guide resource allocation defined within the upcoming National AMR Action Plan.Methods: A previously published and validated dynamic health economic model was adapted to the Japanese setting. The model used a 10-year time horizon with a willingness-to-pay threshold of ¥5 000 000 (US $46 827) and discounting was applied at a rate of 2% to costs and benefits. Clinical and economic outcomes were assessed as a function of varying AMR levels of three Gram-negative pathogens in Japan by up to 100% of the current level.Results: Reducing drug-resistant Gram-negative pathogens in Japan has the potential to save 4 249 096 life years, corresponding to 3 602 311 quality-adjusted life years. The associated maximum clinical and economic gains were estimated at up to 4 422 284 bed days saved, up to 3 645 480 defined daily doses of antibiotics avoided, up to ¥117.6 billion (US $1.1 billion) saved in hospitalization costs, and a net monetary benefit of up to ¥18.1 trillion (US $169.8 billion).Discussion: Learnings from this study can be used by the Japanese government to help inform decision-making on the strategies that may be included in the upcoming National AMR Action Plan and facilitate allocation of the required budget.Conclusions: This analysis demonstrated the considerable economic and clinical value of reducing AMR levels of three Gram-negative pathogens in Japan and could be utilized to support the valuation of antimicrobial treatment and resistance in Japan and more broadly. Staphylococcus aureus and fluoroquinolone-resistant Escherichia coli exceed 8000 per year.Antimicrobial resistance (AMR) represents a significant global public health crisis and, with its increasing prevalence, treatment options available to patients infected with resistant pathogens become increasingly limited. Each year 700 000 people die from AMR-related causes globally, a figure that is projected to rise to 10 million by 2050 at a cost of US $100 trillion dollars to the global gross domestic product if we do not take action.Staphylococcus aureus and anti-Vancomycin-resistant Enterococci agents, there is a lack of agents against Gram-negative bacteria and carbapenem-resistant Enterobacterales remains a threat.Even though AMR occurs naturally, both human interventions and, paradoxically, inaction are further increasing resistance rates and therefore exacerbating the situation. On one hand, any use of antibiotics contributes to the development of AMR, and their overuse and misuse can considerably accelerate it.As a result of this global crisis, an international effort is now underway to tackle the threat of AMR. In 2015, the World Health Organization published the Global Action Plan on AMR, calling for a “one health” response.In this study, we adapted to the Japanese setting a simplified version of a previously published and validated dynamic health economic model of AMR to estimate the clinical and economic consequences of different AMR forecasts, with the aim to guide resource allocation defined within the upcoming National AMR Action Plan.We adapted a previously developed AMR dynamic cost-effectiveness modelEscherichia coli (E. coli), Klebsiella pneumoniae (K. pneumoniae), and Pseudomonas aeruginosa (P. aeruginosa) include complicated urinary tract infections (cUTIs), complicated intra-abdominal infections (cIAIs), or hospital-associated pneumonia including ventilator-associated pneumonia (HAP/ VAP) were included in the model. These were selected because infections with gram-negative bacteria are highly problematic in terms of resistance development with UTIs, IAIs, and HAP being common among carbapenem-resistant Enterobacterales and multi-drug resistant P. aeruginosa (MDRP) infections in the Japan Medical Data Vision (MDV).Gram-negative infections caused by The annual infected population and corresponding numbers exhibiting resistance in Japan were not directly available and were estimated by using available data from a hospital-based administrative claims database, MDV , and the national surveillance program ,Scenario 1: Population (A) was obtained by extracting data from the MDV inpatients with a diagnosis of interest  and multiplying the probability of the three pathogens being implicated in each disease. Probabilities were sourced from published literatureOnline Supplementary Material.Scenario 2: Population (B) was obtained by extracting data from the MDV inpatients with a diagnosis of interest . Eligible patients were prescribed with injectable antimicrobial agents that are covered by National Health Insurance and can be used in current clinical practice with possible antibacterial sensitivity against the three modelled pathogens: E. coli, K. pneumoniae, and P. aeruginosa, including generic products. Of note the antibiotic agent that was prescribed to the most patients was piperacillin/tazobactam (first), followed by meropenem (second).Scenario 3: Population (C) was obtained by extracting from the MDV inpatients with a diagnosis of interest and prescribed piperacillin/tazobactam or meropenem, including generic products.To note, outpatient costs were not evaluated as Gram-negative bacteria are mostly associated with nosocomial infections.To estimate the number of patients across Japan who correspond to the three targeted populations, the ratio between the number of new hospitalized patients from the MDV data relative to the number of new hospitalized patients across Japan was calculated for the same period (January to December 2019). Thus, a scaling factor of 6.039 was applied, derived from the number of new admissions in general wards in Japan from the Ministry of Health, Labor and WelfareAntibiotic resistance rates were calculated for each population since resistance rates of the three pathogens differed between populations. Hence, antibiotic resistance rates were based on the proportion of patients with infectious disease for each population.Pathogen-specific resistance levels for each treatment were informed by the national surveillance program JANIS.Where possible, local model inputs were sourced to better reflect the clinical environment and AMR levels in Japan. Key inputs are summarized in The cost-effectiveness analysis assessed both clinical and economic outcomes as a function of varying AMR levels of three Gram-negative pathogens in Japan (increasing or decreasing relative to the current level by up to 100%). The outcomes were evaluated for each population  and included hospital LOS  and the corresponding cost of hospitalization based on indication-specific general ward costs, DDD, the number of LYs lost as a result of infection (LYs lost), and the number of QALYs lost as a result of infection (QALYs lost). For each population, current AMR levels of three Gram-negative pathogens were increased/reduced in order to evaluate the impact on incremental benefits. The model was run over a 10-year time horizon with a willingness-to-pay threshold of ¥5 000 000 (US $46 827), in line with the most conservative threshold used in the Japan Health Technology Assessment to estimate NMB.One-way sensitivity analyses (OWSA) were conducted on key model input parameters, listed in The absolute and incremental outcomes derived based on populations A-C are presented in Estimates based on populations A  and C T were subThe maximum economic gains realized over a 10-year period from AMR levels of three Gram-negative pathogens were estimated at up to 4 422 284 bed days saved, up to 3 645 480 DDDs avoided, up to ¥117.6 billion (US $1.1 billion) saved in hospitalization costs, and an NMB of up to ¥18.1 trillion (US $169.8 billion).Varying the input for treatment efficacy (given no resistance) had the greatest impact on QALYs gained. Estimates for LOS for unsuccessful treatment had the largest impact on hospitalization costs saved. Hospitalization costs saved were also sensitive to estimates for infected population (per year) and treatment efficacy (given no resistance). E. coli, K. pneumoniae, and P. aeruginosa) causing cUTI, cIAI, and HAP/VAP, and population C on cUTI, cIAI, and HAP/VAP treated with piperacillin/tazobactam or meropenem. Population B was a broad population of patients with cUTI, cIAI, and HAP/VAP treated with agents potentially effective against E. coli, K. pneumoniae, and P. aeruginosa. The broadest population (B), having the highest annual number of infections, gained the greatest clinical and economic benefits from AMR reduction. The outcomes estimated for populations A and C were broadly similar, with a larger potential resource and cost savings attained in population A, owing to the higher annual number of infections than in population C. Conversely, LYs and QALYs gained were greater in population C, in which baseline resistance was higher than in population A. Patients whose infections are resistant to both piperacillin/tazobactam and meropenem have potentially very limited treatment options, so that a reduction in AMR in this setting was associated with high LY and QALY gains.The analysis undertaken in this study demonstrates the potential clinical and economic savings from reducing future Gram-negative AMR levels in Japan, as well as the threats associated with potential increases in Gram-negative AMR levels. JANIS-derived populations A, B, and C represent different scenarios in which a reduction in Gram-negative AMR may be realized, with population A focused on specific pathogens  represents the maximum value of investment according to the Japanese willingness-to-pay threshold and can be used by the Japanese government to help inform decision-making on the strategies that may be included in the upcoming National AMR Action Plan and facilitate allocation of the required budget. This figure, however, is likely to be an underestimation since our study focuses only on a limited number of indications and pathogens. Therefore, when considering other infections with high prevalence, such as methicillin-resistant E. coli. resistance on a national scale in Japan.P. aeruginosa isolates.Reducing the use of inappropriate antimicrobial agents is one way of lowering AMR rates, as evidenced in a study by Terahara et al, which showed an association between fluoroquinolone consumption and Morel et al presented a framework guiding AMR-related cost assessments across different localizations, with the aim that this can feed into both more detailed analyses comparing AMR-related interventions at the local level and broader analyses aiming to capture the economic burden of AMR at a global level.While efforts to optimize the use of existing antimicrobials are ongoing, there is stagnation in the development of novel antimicrobial agents, owing to the lack of investment in this area. This is a particular problem in Japan, where only 6 antibiotic agents have been approved since 2002. Conversely, within the same time-frame, the amount of antibiotic agents approved in the United States and the European Union has almost quadrupled this amount,Whilst the development of antimicrobial agents has halted in recent years, efforts are being made in some countries to overcome this issue, such as in the United Kingdom, the United States and Sweden. In the United Kingdom, an antimicrobial reimbursement pilot program has been launched,E. coli, K. pneumoniae, and P. aeruginosa) were 13.88%, 6.23%, and 6.56%, respectively, of the total number of patients with available specimens. While the pathogens considered are frequently implicated in nosocomial infection, the generalizability of our results to other bacterial species is uncertain. Fifth, in Japan, hospitalization costs are calculated on a DPC basis in DPC hospitals  and on a fee-for-service reimbursement basis in non-DPC hospitals . Nevertheless, the DPC costs were used in the results. Sixth, the model does not account for the additional benefits of reduced AMR, including reduced secondary transmission, the impact of infection on pregnant women, or prophylactic use of antimicrobial agents in surgery. Seventh, hospitalization costs have not been adjusted for inflation over the 10 years assessed and are therefore likely underestimated. Finally, estimates of hospital LOS are uncertain due to the reliance on expert opinion in the absence of empirical research.There are some limitations to this study that need to be addressed. First, although this analysis may help inform the value of reducing AMR levels of three Gram-negative pathogens, or the burden associated with their increase, it does not consider the methods required to achieve these outcomes, including any additional costs they might incur. Second, changes in future populations, including demographic changes such as the growth in the number of older people, were not considered. Third, the number of pathogens evaluated was limited to 3 due to the constraints of the model structure. Fourth, the diseases and pathogens analyzed were limited. According to the data published by JANIS, the isolation rates of the three organisms  and cannot be made available by the authors.


One of the possible consequences of incarcerated inguinal hernia in boys is testicular ischemia because of the prolonged compression of spermatic cord structures by the sac contents, resulting in ipsilateral testicular atrophy. This complication is well described in the literature and occurs in 5-34% of patients. The incidence of testicular atrophy secondary to incarcerated hernia is estimated to be 2-3%. Testicular necrosis as the result of hernia incarceration is, however, an extremely rare clinical setting. We present 4 male infants aged 3-10 weeks with inguinal hernia incarceration which led to ipsilateral testicular loss. All the boys had to be operated on because of irreducible incarcerated hernia and in all the cases testicular necrosis was found intraoperatively. The time of incarceration before surgical intervention ranged from 4 to 12 hours (mean 6.75). Our data show that every case of hernia incarceration in a very young male infant requires rapid diagnosis and proper intervention, i.e. surgical treatment, instead of repeated attempts of manual reduction. Ultrasound examination should estimate not only blood flow through the incarcerated intestinal loop, but also through the ipsilateral testis. Moreover, during the operation of the incarcerated hernia in a boy it is necessary to estimate the ipsilateral testis. Inguinal hernia in children is one of the most common congenital disorders managed by pediatricians and pediatric surgeons. Inguinal hernia repair is also one of the most common operations performed by pediatric surgeons. The main etiological factor for hernia development in children is prolonged patency of processus vaginalis, therefore indirect inguinal hernia occurs almost exclusively . In the general pediatric population the overall incidence of inguinal hernia is estimated at approximately 3% to 5%.Because processus vaginalis plays an important role in testicular descent, male children with hernias outnumber females by an 8:1 to 10:1 ratio , 3, 4.The most serious complication of inguinal hernia is its incarceration. The risk for hernia incarceration is the highest in children less than 1 year old (70% of cases) and decreases with age. Younger age and as well as prematurity are attributed as a risk factor for incarceration , 3, 4.One of the possible consequences of incarcerated inguinal hernia in boys is testicular ischemia as a result of prolonged spermatic cord structure compression , 6, 7, 8The aim of this study is to present a case series of male infants with testicular necrosis and its loss as a complication of incarcerated inguinal hernia.Over the last year 4 boys aged 3, 4, 5 and 10 weeks were diagnosed with irreducible incarcerated inguinal hernia and referred for urgent surgery. After the diagnosis of hernia incarceration at least one attempt to reduce the hernia manually was made. The clinical data of the patients are presented in In all the boys ultrasound (US) was performed after the recognition of hernia incarceration, although in every case blood flow was checked only within the incarcerated bowel loop. The US revealed the presence of an incarcerated bowel loop within the inguinal canal. In 2 boys enlargement of the ipsilateral testis was diagnosed: in one there was slightly abnormal testicular echogenicity, in the other normal testicular structure. In the third case slight enlargement of the testis was found, with an abnormal structure, but there was visible blood flow, while in the last one the testis was described as completely normal. Only in one out of the 4 cases was there estimated blood flow through the testis .th patient bowel resection with primary anastomosis was necessary, because of concomitant bowel necrosis. As the attempts of revascularization of the testes by their warming and local lidocaine injection were ineffective  and all were referred for urgent surgery because of irreducible incarcerated inguinal hernias.To date we have not found a similar case series presented in the literature. We were able to find only two similar single cases, including one with necrosis of an undescended testis by an incarcerated hernia , 22.Our observations confirm that the reduction of the incarcerated inguinal hernia should be performed as early as possible, not only to preserve the bowel, but also to avoid excess pressure on the spermatic cord structures with possible testicular injury. On the other hand it seems that incarceration in a very young male infant requires proper intervention, i.e. operative treatment instead of repeated attempts of manual reduction, so as to avoid additional injury to the testis. It is also worth emphasizing that the initial ultrasound examination should estimate not only blood flow through the incarcerated inguinal loop, but also through the ipsilateral testis. During the operation of an incarcerated hernia in a boy it is necessary to estimate the ipsilateral testis.


Hemodynamically significant patent ductus arteriosus (hsPDA) in premature newborns is associated with a risk of PDA-related morbidities. Classification into risk groups may have a clinical utility in cases of suspected hsPDA to decrease the need for echocardiograms and unnecessary treatment. This prospective observational study included 99 premature newborns with extremely low body weight, who had an echocardiogram performed within the first three days of life. Discriminant analysis was utilized to find the best combination of prognostic factors for evaluation of hsPDA. We used binary logistic regression analysis to predict the relationship between parameters and hsPDA. The cohort’s mean and standard deviation gestational age was 27.6 ± 2.55 weeks, the mean birth weight was 1015 ± 274 g. Forty-six (46.4%) infants had a PDA with a mean diameter of 2.78 mm. Median NT-pro-BNP levels were 17,600 pg/mL for infants with a PDA and 2773 pg/mL in the non-hsPDA group. The combination of prognostic factors of hsPDA in newborns of extremely low body weight on the third day of life was determined: NT-pro-BNP, Apgar score, Silverman–Anderson score . A cut-off value of NT-pro-BNP of more than 8500 pg/mL can predict hsPDA . Patent ductus arteriosus (PDA) is an extra blood vessel found in babies before birth and just after birth. In full-term newborns, it usually closes shortly after birth, and in premature infants it functions in most cases for up to one month . Long-teThe current therapeutic approach in the form of prescribing preterm infants non-steroidal anti-inflammatory drugs (COX inhibitors) in order to close the PDA earlier is largely subjective and is associated with side effects, when the harm from treatment may outweigh the benefits , since PSurgical PDA ligation is also significantly associated with a high likelihood of adverse outcomes and has no long-term benefits ,13.Contemporary tactics for managing patients with PDA are observational in nature. The decision on therapy is made in the case of hemodynamic significance of PDA. According to the American Academy of Pediatrics, a combination of standard echocardiographic assessments of PDA and biomarkers should be preferred ,12.It should be noted that there are several approaches to define hsPDA . The hemBrain natriuretic peptide and its inactive fragment N-terminal pro-BNP (NT-pro-BNP) are reliable markers of ventricular dysfunction in adults and children . It was Therefore, timely prediction of the hemodynamic significance of PDA in premature infants is especially important in the early neonatal period (during the first 48–72 h), and contributes to the timely appointment of adequate therapy ,20.Recently, BNP estimation was shown to be a useful prognostic marker of all-cause mortality in extremely low body weight infants with bronchopulmonary dysplasia-associated pulmonary hypertension . All curThus, the hypothesis of the present study was to establish a combination of clinical predictors with an acceptable degree of specificity and sensitivity predicting hsPDA in preterm infants on day 3 of life. To solve the problem, discriminant analysis was applied.A retrospective study was carried out in Perm Krai Perinatal Center. Data on 99 infants born from October of 2018 to April of 2020 were collected. Patients with gestational age ranging from 25 to 32 weeks and birth weights ranging from 500 up to 1500 g were included in the study . NewbornNT-pro-BNP level in plasma was evaluated on the third day of life by reagent set . Moreover, echocardiogram initial screening to visualize PDA was performed on the third day of life.The definition of an hsPDA was based on previously established criteria ,29,30 anA Vivid Q cardiovascular ultrasound system  was utilized during the study.Clinical, demographic, and biochemical data were obtained retrospectively from medical records.Written informed consent was obtained from patients’ parents. The study was approved by the Ethics Committee of S.G. Sukhanov Cardiovascular Center, Perm, Russia.t-test. Aggregates of quantitative indicators, the distribution of which differed from normal, were described using the values of the median (Me) and the lower and upper quartiles (Q1–Q3) and compared by the Mann–Whitney test. The nominal data were described with the indication of absolute values and percentages. Comparison of nominal data was carried out using a Pearson χ2 test.In the case of describing quantitative indicators with a normal distribution, the data obtained were combined into variation series, where the arithmetic mean values (M), standard deviations (SD), and confidence limits (a 95% confidence level) were calculated. Comparisons were performed using a Student’s p-level of <0.05 was considered significant.BNP and NT-pro-BNP were log-transformed to obtain a normal distribution for analysis. The correlation coefficients were obtained to describe the relationship between BNP and NT-pro-BNP and the presence and size of a PDA. A To create a predictive model, the discriminant analysis method was used. The PDA hemodynamical significance indicator was defined as a dependent variable, taking two values, which were coded as 1 (yes) and 0 (no), respectively. Quantitative indicators were used as independent variables.In total, 40 variables were used for discriminant analysis: anthropometric indicators (weight and height at birth), gestational age, clinical assessment of the cardiovascular and respiratory systems at birth , baby therapy after birth , type of respiratory support , results of neurosonography and radiography, laboratory data , echocardiographic criteria, maternal history , obstetric history, and somatic diseases of the mother. The groups of variables for analysis are provided in 0 is a constant, а1…n are regression coefficients, x1…n are independent variables . The stepwise method selected the discriminant variables on basis of Wilks’ lambda statistic, and in general, the F value was set at F Entry = 3.84 and F Removal = 2.71. Assuming that the mean discriminant score of the controls was The model was created on the principle of the possibility of predicting the dependent variable based on the values of the measured factor signs and was presented in the form of the following equation:P is the probability of hsPDA, x1...xn are risk factor values, a1...an are regression coefficients. The selection of independent variables was carried out by the step-by-step direct selection method using Wald statistics as an exclusion criterion. The statistical significance of the resulting model was determined using the χ2 criterion. To assess the diagnostic significance of quantitative signs in predicting the outcome, calculated using a regression model, the method of analysis of ROC curves was used. The relationships were graphically represented by probability curves. Receiver operator characteristic (ROC) analysis was used to determine the area under the curve (AUC). The highest value of the Youden index was used to determine the optimal cut-off point. Sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and positive and negative likelihood ratios (LR+ and LR−) were calculated. Statistical analysis was performed using IBM SPSS Statistics v.26 software. We used binary logistic regression analysis to predict the relationships between NT-pro-BNP and hsPDA. The predictive model can be written as follows:р = 0.001), OR = 3.46 (95% CI 1.3–9.15). A total of 45 (45.4%) mothers received antenatal corticosteroid therapy: 41.3% (19/46) in the hsPDA group, 49.0% (26/53) in the non-hsPDA group, OR = 0.73 (95% CI 0.3–1.6). Respiratory support was required in 91.3% (42/46) and 84.9% (45/53), OR = 1.8 (95% CI 0.5–6.6) in the hsPDA group and in the non-hsPDA group, respectively. An Apgar score 5 min after birth ≤6 points was found in 26.1% (12/46) in the hsPDA group, 9.4% (5/53) in the non-hsPDA group, OR = 3.4 (95% CI 1.1–10.5). A Silverman–Anderson score (respiratory severity score) [The clinical characteristics of patients are shown in y score)  of respip = 0.001). Pulmonary hyperperfusion was assessed by an LA/Ao ratio ≥1.5, which indicates a heavy load on the left side of the heart: in the hsPDA group, 73.9% (34/46), with non-hsPDA—3.8% (2/53), OR = 72.3 (95% CI 15.2–343). Systemic hypoperfusion was assessed by the presence of retrograde blood flow equal to or greater than 50% of direct blood flow in the descending aorta: in the hsPDA group, 76.1% (35/46), in children with non-hsPDA—7.5% (4/53), OR = 39 (95% CI 11.5–133)  diameter of the PDA in children with hsPDA is 2.78 ± 0.72 mm, in children with non-hsPDA—1.26 ± 0.66 mm (1.5–133) .p = 0.001). BNP levels in the hsPDA group were significantly higher: the median value (IQR) of BNP was 17,600  pg/mL, and 2773 (Q1–Q3: 1532–3739) pg/mL in the non-hsPDA group (p = 0.01 (95% CI 0.31–0.68), determination coefficient r2 = 0.36 (p = 0.05 (95% CI 0.26–0.66), r2 = 0.26, for the left atrium/aorta LA/Ao ratio r = 0.51, p = 0.05 (95% CI 0.34–0.70), r2 = 0.26. Correlation analysis showed no dependence of NT-pro-BNP level on gestational age  and body weight .There was a direct correlation between the NT-pro-BNP values and hsPDA echo criteria: for PDA r = 0.60, 2 = 0.36 , for retp < 0.001), and three variables were selected, as follows: Apgar score  based on the three screened variables that were statistically significant. The stepwise discriminant analysis showed that Wilks’ lambda, as a test of the discriminant function, was significant /2 = 0.073. Then, we calculated the discriminant function value of Z for each subject; if Z > 0.073, the subject was considered highly likely to be a case of hsPDA, and if Z ≤ 0.073, the subject was regarded as normal. The classification results obtained using the discriminant function are presented in In the discriminant analysis, Analysis using a receiver operating characteristic curve shown in Early diagnosis of hsPDA in preterm infants is undoubtedly a clinical problem as it is associated with serious clinical outcomes and in-hospital mortality. However, over the past decade, there has been a tendency towards a decrease in the use of both medical and surgical treatment of hsPDA in this group of patients .We analyzed the statistical data of the Perm Krai Perinatal Center in the period from 2015 to 2019, according to which the proportion of children who received surgical PDA ligation decreased 3.7 times (from 17.0% to 4.5%). The median age of the operated children was 20 months. Of the patients participating in our study, two children (aged 32 and 43 days) underwent surgery.In our practice, we adhere to the conservative approach aimed at improving the effects of left-to-right shunting by fluid restriction, diuretics prescription, etc. Good results of conservative treatment without surgery have been reported in a number of studies, according to which the frequency of spontaneous closure of PDA at 36 weeks postmenstrual age reaches 83–85% ,33.However, at present, there is a problem of lack of evidence in favor of using a conservative approach to the treatment of premature infants with PDA, since the currently existing echocardiography-guided approach to PDA management is characterized by significant variability . UltrasoEcho criteria traditionally used for hsPDA diagnosis, such as PDA diameter, for example, do not allow prediction of serious clinical outcomes ,35. For 2) values, as a result of which there is a decrease in muscle wall tone, leading to the duct staying open. The advantages of applying the Silverman–Anderson scale include simplicity and the possibility of use in conditions with limited resources. In our study, we initially used 40 diagnostic criteria, but the greatest ability in predicting probabilities of persistent PDA was established for a combination of criteria: Apgar score ≤ 6 points, Silverman–Anderson score ≥ 5 points, and NT-pro-BNP over lg3.9 pg/mL.For example, Kindler et al.  developeThe novel contribution of our work is that our suggested combination of predictors is new, having not been previously described, and is substantiated by the results of discriminant and variance analyses. We have identified the combination of predictors that has high specificity values , leading to a low probability of a false positive diagnosis, which is of practical importance for making a clinical decision on surgical correction of the duct.As for the clinical utility of measuring the biomarker NT-pro-BNP for prediction of hsPDA, the increase in its plasma concentration is significantly correlated with the increase in the left atrium arising from PDA . The bioIn two of the eight studies, sensitivity was lower than 0.7, with 42,285   and 10,2In other studies, the sensitivity ranged from 0.85 to 0.95 (95% CI from 0.59 to 1.0) for NT-pro-BNP cut-off values of 5000 to 24,102 ,47,48.In comparison with the presented studies, the result of our study, which determined the threshold for NT-pro-BNP as lg3.9 pg/mL, shows one of the best combinations of high sensitivity  and specificity  and a narrow confidence interval. We used the obtained threshold value of NT-pro-BNP to create a model capable of dividing patients with extremely low body weight according to the degree of hemodynamic significance of PDA into two functional classes. The predictive model derived from discriminant analysis successfully classified 85.9% of participants with an AUC of 0.89.The use of Apgar and Silverman–Anderson scores in our predictive model as predictors has its advantages and disadvantages. The advantages include the unification of decision making, and the possibility of quantitative assessment. The disadvantages are the uncertainty of the forecast time lag, the static nature of the forecast, dependence on the population, and the absence of standards. Additionally, a limitation of the study is that surgeons participating in the study were aware of NT-pro-BNP values in patients. Another limitation of our study was the small cohort of patients; however, the predictor correlation values seem reasonable. There was some selection bias in the study cohort: we included only premature infants for blood sampling and the decision to request an echocardiogram was based on the opinion of the attending physician. Strictly speaking, scales can be used if it is proven that their application reliably improves prognosis, compared to decisions made by a doctor without using scales. We believe that in conditions of limited resources, this provision is important, since it allows replacement of the standard echocardiographic assessment of hsPDA in newborns of VLBW on the third day of life by a combination of the following factors: NT-pro-BNP level more than lg3.9 pg/mL, Apgar score ≤ 6 points, Silverman–Anderson score (RSS) ≥ 5 points.In the future, we plan to conduct a study in which we will compare our model with a group in which only NT-pro-BNP will be determined, the group in which only echocardiographic assessment will be used as an internal control.Undoubtedly, therapeutic approaches to the problem of PDA closure continue to evolve, and much is being rethought and re-evaluated. We believe that future research should be as individualized as possible and we hope to make a small contribution to the benefit of patients.The results of this study show that the accuracy of the clinical prognosis of hsPDA in premature infants weighing less than 1500 g can be significantly improved using affordable and inexpensive predictors that allow newborns to be classified according to hsPDA risk groups: NT-pro-BNP level more than lg3.9 pg/mL, Apgar score ≤ 6 points, and Silverman–Anderson score ≥ 5 points. Further research in this area will help to improve understanding of the problem of functioning PDA in children born very prematurely, and awareness of the fine line between norm and pathology determines the use of the most sparing therapeutic approaches in this group of patients.