Automatic Classification of Medicinal Plants Using State-Of-The-Art Pre-Trained Neural Networks

Now a days every mankind is suffering due to infections. Ayurveda, the science of life helped to take preventive measures which boost our immunity.  It is plant-based science. Many medicinal plants found useful in daily life of common people for boosting immunity. Identifying the plant species having medicinal plant is challenging, it requires botanical expert. In the process of manual identification, botanical experts use various plant features as the identification keys, which are examined adaptively and progressively to identify plant species. The shortage of experts and trained taxonomist created global taxonomic impediment problem which is one of the major challenges.  Various researchers have worked in the field of automatic classification of plants since the last decade. The leaf is considered as primary input as it is available throughout the whole year. The research paper mainly focuses on the study of transfer learning approach for medicinal plant classification, which reuse already developed model at the starting point for model on a second task. Transfer learning approach is a black box approach used for image classification and many more applications by extracting features from an image. Some of the transfer learning models are MobileNet-V1, VGG-19, ResNet-50, VGG-16. Here it uses Mendeley dataset of Indian medicinal plant species which is freely available. Output layer classifies the species of leaves. The result provides evaluation and variations of above listed features extracted models. MobileNetV1 achieves maximum accuracy of 98%

Polymyxin B in Combination with Rifampin and Meropenem against Polymyxin B-Resistant KPC-Producing Klebsiella pneumoniae

Safe and effective therapies are urgently needed to treat polymyxin-resistant KPC-producing K. pneumoniae and suppress the emergence of resistance. We investigated the pharmacodynamics of polymyxin B, rifampin, and meropenem alone and as polymyxin B-based double and triple combinations against KPC-producing K. pneumoniae . The rate and extent of killing with polymyxin B (1-128mg/L), rifampin (2-16mg/L), and meropenem (10-120mg/L) were evaluated against polymyxin B-susceptible (PB S ) and -resistant (PB R ) clinical isolates using 48h static time-kills. Additionally, humanized triple drug regimens of polymyxin B (C ss : 0.5, 1, 2mg/L), rifampin 600mg every 12 or 8h, and meropenem 1 or 2g every 8h dosed as an extended 3h infusion were simulated over 48h using a one-compartment in vitro dynamic infection model. Serial bacterial counts were measured to quantify pharmacodynamic effect. Population analysis profiles (PAPs) were used to assess the emergence of polymyxin B resistance. Monotherapy was ineffective against both isolates. Polymyxin B with rifampin demonstrated early bactericidal activity against the PB S isolate followed by regrowth by 48h. Bactericidal activity was sustained at all polymyxin B concentrations ≥2 mg/L in combination with meropenem. No two-drug combinations were effective against the PB R isolate, but all simulated triple-drug regimens showed early bactericidal activity by 8h that was sustained over 48h against both strains. PAPs did not reveal the emergence of resistant subpopulations. The triple drug combination of polymyxin B, rifampin, and meropenem may be a viable consideration for the treatment of PB R KPC-producing K. pneumoniae . Further investigation is warranted to optimize triple combination therapy

Paradoxical Effect of Polymyxin B: High Drug Exposure Amplifies Resistance in Acinetobacter baumannii

ABSTRACT Administering polymyxin antibiotics in a traditional fashion may be ineffective against Gram-negative ESKAPE ( Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumoniae , Acinetobacter baumannii , Pseudomonas aeruginosa , and Enterobacter species) pathogens. Here, we explored increasing the dose intensity of polymyxin B against two strains of Acinetobacter baumannii in the hollow-fiber infection model. The following dosage regimens were simulated for polymyxin B ( t 1/2 = 8 h): non-loading dose (1.43 mg/kg of body weight every 12 h [q12h]), loading dose (2.22 mg/kg q12h for 1 dose and then 1.43 mg/kg q12h), front-loading dose (3.33 mg/kg q12h for 1 dose followed by 1.43 mg/kg q12h), burst (5.53 mg/kg for 1 dose), and supraburst (18.4 mg/kg for 1 dose). Against both A. baumannii isolates, a rapid initial decline in the total population was observed within the first 6 h of polymyxin exposure, whereby greater polymyxin B exposure resulted in greater maximal killing of −1.25, −1.43, −2.84, −2.84, and −3.40 log 10 CFU/ml within the first 6 h. Unexpectedly, we observed a paradoxical effect whereby higher polymyxin B exposures dramatically increased resistant subpopulations that grew on agar containing up to 10 mg/liter of polymyxin B over 336 h. High drug exposure also proliferated polymyxin-dependent growth. A cost-benefit pharmacokinetic/pharmacodynamic relationship between 24-h killing and 336-h resistance was explored. The intersecting point, where the benefit of bacterial killing was equal to the cost of resistance, was an f AUC 0–24 (area under the concentration-time curve from 0 to 24 h for the free, unbound fraction of drug) of 38.5 mg · h/liter for polymyxin B. Increasing the dose intensity of polymyxin B resulted in amplification of resistance, highlighting the need to utilize polymyxins as part of a combination against high-bacterial-density A. baumannii infections

High-intensity meropenem combinations with polymyxin B: new strategies to overcome carbapenem resistance in Acinetobacter baumannii

The pharmacodynamics of polymyxin/carbapenem combinations against carbapenem-resistant Acinetobacter baumannii (CRAB) are largely unknown. Our objective was to determine whether intensified meropenem regimens in combination with polymyxin B enhance killing and resistance suppression of CRAB

Reporting trends, practices, and resource utilization in neuroendocrine tumors of the prostate gland: a survey among thirty-nine genitourinary pathologists

Background: Neuroendocrine differentiation in the prostate gland ranges from clinically insignificant neuroendocrine differentiation detected with markers in an otherwise conventional prostatic adenocarcinoma to a lethal high-grade small/large cell neuroendocrine carcinoma. The concept of neuroendocrine differentiation in prostatic adenocarcinoma has gained considerable importance due to its prognostic and therapeutic ramifications and pathologists play a pivotal role in its recognition. However, its awareness, reporting, and resource utilization practice patterns among pathologists are largely unknown. Methods: Representative examples of different spectrums of neuroendocrine differentiation along with a detailed questionnaire were shared among 39 urologic pathologists using the survey monkey software. Participants were specifically questioned about the use and awareness of the 2016 WHO classification of neuroendocrine tumors of the prostate, understanding of the clinical significance of each entity, and use of different immunohistochemical (IHC) markers. De-identified respondent data were analyzed. Results: A vast majority (90%) of the participants utilize IHC markers to confirm the diagnosis of small cell neuroendocrine carcinoma. A majority (87%) of the respondents were in agreement regarding the utilization of type of IHC markers for small cell neuroendocrine carcinoma for which 85% of the pathologists agreed that determination of the site of origin of a high-grade neuroendocrine carcinoma is not critical, as these are treated similarly. In the setting of mixed carcinomas, 62% of respondents indicated that they provide quantification and grading of the acinar component. There were varied responses regarding the prognostic implication of focal neuroendocrine cells in an otherwise conventional acinar adenocarcinoma and for Paneth cell-like differentiation. The classification of large cell neuroendocrine carcinoma was highly varied, with only 38% agreement in the illustrated case. Finally, despite the recommendation not to perform neuroendocrine markers in the absence of morphologic evidence of neuroendocrine differentiation, 62% would routinely utilize IHC in the work-up of a Gleason score 5 + 5 = 10 acinar adenocarcinoma and its differentiation from high-grade neuroendocrine carcinoma. Conclusion: There is a disparity in the practice utilization patterns among the urologic pathologists with regard to diagnosing high-grade neuroendocrine carcinoma and in understanding the clinical significance of focal neuroendocrine cells in an otherwise conventional acinar adenocarcinoma and Paneth cell-like neuroendocrine differentiation. There seems to have a trend towards overutilization of IHC to determine neuroendocrine differentiation in the absence of neuroendocrine features on morphology. The survey results suggest a need for further refinement and development of standardized guidelines for the classification and reporting of neuroendocrine differentiation in the prostate gland

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe