Prevalence And Antimicrobial Susceptibility Pattern Of Methicillin Resistant Staphylococcus aureus From Healthcare And Community Associated Sources

Methicillin resistant Staphylococcus aureus (MRSA) is an important nosocomial pathogen. We report the prevalence and antibiotic susceptibility pattern of MRSA in Amravati, Maharashtra state (India). A total of 150 healthcare-associated (HA) sources (doctors mobiles phone and wound/pus swabs), and 160 community-associated (CA) sources (hand swab) were screened for MRSA and their antibiotic resistance pattern was performed. Out of 41 isolated strains of S. aureus, 77% from HA and 50% CA samples were found to be methicillin resistant. There were high prevalence of MRSA in doctor's mobile phone (83%) and wound/pus (71%) (HA sources) than the hand swab. Almost all HA and CA MRSA strains were resistant to penicillin and penicillin V (100%) followed by cloxacillin and cephalexin, co-trimoxazole. About 56 - 67% HA and CA-MRSA strains were resistance to erythromycin, ceftazidime, lincomycin, ceftazidime, cephalexin, erythromycin and tetracycline indicating high degree of multi-resistance MRSA prevalence in the region. However, 67% strains of CA and 56% strains of HA were sensitive to vancomycin. The study showed high prevalence of MRSA in hospital setting indicating need of good control measures such as proper hand hygiene, avoiding mobile phone while wound dressing and treating patient, surveillance cultures and monitoring of susceptibility patterns of MRSA may also help in arresting the spread of infections in this part of India. Keywords: MRSA, Wound, Mobile Phone, Hands swab African Journal of Infectious Diseases Vol. 1 (1) 2007: pp. 52-5

Antibacterial susceptibility of some urinary tract pathogens to commonly used antibiotics

Urinary tract infection represents one of the most common diseases encountered in medical practice today and occurring from the neonate to the geriatric age group. Despite the widespread availability of antibiotics, it remains the most common bacterial infection in the human being. A total of 174 urine samples were analyzed for isolation and identification, 68 found to be significant bacteriuria with Escherichia coli (59%), followed by  Pseudomonas aeruginosa (15%), Klebsiella pneumoniae (10%), Proteus mirabilis (9%), Staphylococcus aureus (6%) and Citrobacter freundii (1%). The urinary tract infections were found to most frequently in female (63%) than male (37%). The isolated uropathogens showed resistant to ampicillin (87%), co-trimoxazole (91%), nalidixic acid (88%) and sensitive to nitrofurantoin (52%), cephotaxime (54%) and norfloxacin (71%)

Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement

Burst image processing is becoming increasingly popular in recent years. However, it is a challenging task since individual burst images undergo multiple degradations and often have mutual misalignments resulting in ghosting and zipper artifacts. Existing burst restoration methods usually do not consider the mutual correlation and non-local contextual information among burst frames, which tends to limit these approaches in challenging cases. Another key challenge lies in the robust up-sampling of burst frames. The existing up-sampling methods cannot effectively utilize the advantages of single-stage and progressive up-sampling strategies with conventional and/or recent up-samplers at the same time. To address these challenges, we propose a novel Gated Multi-Resolution Transfer Network (GMTNet) to reconstruct a spatially precise high-quality image from a burst of low-quality raw images. GMTNet consists of three modules optimized for burst processing tasks: Multi-scale Burst Feature Alignment (MBFA) for feature denoising and alignment, Transposed-Attention Feature Merging (TAFM) for multi-frame feature aggregation, and Resolution Transfer Feature Up-sampler (RTFU) to up-scale merged features and construct a high-quality output image. Detailed experimental analysis on five datasets validates our approach and sets a state-of-the-art for burst super-resolution, burst denoising, and low-light burst enhancement.Comment: Accepted at CVPR 202

Burstormer: Burst Image Restoration and Enhancement Transformer

On a shutter press, modern handheld cameras capture multiple images in rapid succession and merge them to generate a single image. However, individual frames in a burst are misaligned due to inevitable motions and contain multiple degradations. The challenge is to properly align the successive image shots and merge their complimentary information to achieve high-quality outputs. Towards this direction, we propose Burstormer: a novel transformer-based architecture for burst image restoration and enhancement. In comparison to existing works, our approach exploits multi-scale local and non-local features to achieve improved alignment and feature fusion. Our key idea is to enable inter-frame communication in the burst neighborhoods for information aggregation and progressive fusion while modeling the burst-wide context. However, the input burst frames need to be properly aligned before fusing their information. Therefore, we propose an enhanced deformable alignment module for aligning burst features with regards to the reference frame. Unlike existing methods, the proposed alignment module not only aligns burst features but also exchanges feature information and maintains focused communication with the reference frame through the proposed reference-based feature enrichment mechanism, which facilitates handling complex motions. After multi-level alignment and enrichment, we re-emphasize on inter-frame communication within burst using a cyclic burst sampling module. Finally, the inter-frame information is aggregated using the proposed burst feature fusion module followed by progressive upsampling. Our Burstormer outperforms state-of-the-art methods on burst super-resolution, burst denoising and burst low-light enhancement. Our codes and pretrained models are available at https:// github.com/akshaydudhane16/BurstormerComment: Accepted at CVPR 202

PREVALENCE AND ANTIMICROBIAL SUSCEPTIBILITY PATTERN OF METHICILLIN RESISTANT STAPHYLOCOCCUS AUREUS FROM HEALTHCARE AND COMMUNITY ASSOCIATED SOURCES

Methicillin resistant Staphylococcus aureus (MRSA) is an important nosocomial pathogen. We report the prevalence and antibiotic susceptibility pattern of MRSA in Amravati, Maharashtra state (India). A total of 150 healthcare-associated (HA) sources (doctors mobiles phone and wound/pus swabs), and 160 community-associated (CA) sources (hand swab) were screened for MRSA and their antibiotic resistance pattern was performed. Out of 41 isolated strains of S. aureus, 77% from HA and 50% CA samples were found to be methicillin resistant. There were high prevalence of MRSA in doctor’s mobile phone (83%) and wound/pus (71%) (HA sources) than the hand swab. Almost all HA and CA MRSA strains were resistant to penicillin and penicillin V (100%) followed by cloxacillin and cephalexin, co-trimoxazole. About 56 - 67% HA and CA-MRSA strains were resistance to erythromycin, ceftazidime, lincomycin, ceftazidime, cephalexin, erythromycin and tetracycline indicating high degree of multi-resistance MRSA prevalence in the region. However, 67% strains of CA and 56% strains of HA were sensitive to vancomycin. The study showed high prevalence of MRSA in hospital setting indicating need of good control measures such as proper hand hygiene, avoiding mobile phone while wound dressing and treating patient, surveillance cultures and monitoring of susceptibility patterns of MRSA may also help in arresting the spread of infections in this part of India

Biocontrol of Sclerotium rolfsii in Groundnut by Using Microbial Inoculants

Sclerotium rolfsii (Sacc.) is the causal agent of stem-rot in groundnut (Arachis hypogaea L.)crop. With the increase in demand for the groundnut, control of stem-rot efficiently by microbial strains is fast becoming inevitable as the conventional system of chemicals is degrading our ecosystem. This investigation here emphasizes on inoculation of arbuscular mycorrhizal fungi (AMF) and Trichoderma species for growth achievement and disease control. The present investigation showed that these microbial strains were found to be worth applying as they stimulated growth and decreased harmful effects of S. rolfsii (cv. ‘Western-51’). The increased biochemical parameters and antioxidant activities also indicated their defence related activities in groundnut plants. In spite of positive attributes meted out by these microbial strains towards groundnut crop, the interaction among AM fungi and Trichoderma species seemed to be less co-operative between each other which were noted when mycorrhizal dependency and percent root colonization were observed. However, in summary more practical application of low-input AM fungi along with Trichoderma species may be needed for the advancement of modern agricultural systems

AM Fungi Influences the Photosynthetic Activity, Growth and Antioxidant Enzymes in Allium sativum L. under Salinity Condition

Potential of Arbuscular mycorrhizal (AM) fungi in alleviating adverse salt effects on growth was tested in garlic (Allium sativum L.). Towards this objective we analyzed the AM root colonization and the activities of various antioxidant enzymes like peroxidase, catalase, and superoxide dismutase at 0, 100, 200 and 300 mM salinity levels. The activities of all the antioxidant enzymes studied were found to be increased in AM garlic plants. Antioxidant activity was maximum in 100 and 200 mM NaCl (sodium chloride) in AM and non-AM plants. Proline accumulation was induced by salt levels and it was more in leaves as well as roots of AM plants as compared to non-AM plants, this indicating that mycorrhiza reduced salt injury. Growth parameters of garlic plants like leaf area, plant fresh and dry weight and antioxidant enzyme activities were higher at moderate salinity level. This work suggests that the mycorrhiza helps garlic plants to perform better under moderate salinity level by enhancing the antioxidant activity and proline content as compared to non-AM plants