Case Report of Maggot Infestation on Diabetic Foot Ulcer

Myiasis is originated from the Greek word, Miya, which means fly. Fly larva are called maggots. Infestation in humans by maggots is called myiasis. Fly maggots feed on and develop in the tissues of living beings and this condition is known as myasis. The maggot (larvae) invades the skin and subcutaneous tissue is known as Maggot infestation. It was found that farmers who are working in agricultural fields are more susceptible to this infestation. Myiasis symptoms may vary according to the fly type, the number of larvae, and the location of the infected area. Many organs can be infested by these larvae and the most common form is cutaneous myasis. The predisposing factors of cutaneous myasisare cutaneous immobilization, advanced age, poor social conditions, mental retardation, diabetes mellitus, alcoholism, vascular occlusive disease, and infected dermatitis as myiasis. Myiasis is more common in tropical and subtropical countries, especially in rural regions where people are in close contact with animals.Myiasisrepresents the fourth most common travel-associated skin disease. Here we report case on 55-year-old female patient was admitted with complaints of diabetic foot ulcer over left foot for 1 and half months and maggots were examined in the wound. The complete blood cell count [CBC] test shows that her HbA1c level was increased to 10.1%. The patient has undergone wound debridement on left forefoot and maggots were completely removed.

Pre-Symptomatic Detection of Viral Infection in Tobacco Leaves Using PAM Fluorometry

Chlorophyll fluorescence imaging was used to study potato virus X (PVX) infection of Nicotiana benthamiana. Infection-induced changes in chlorophyll fluorescence parameters (quantum yield of photosystem II photochemistry (ΦPSII) and non-photochemical fluorescence quenching (NPQ)) in the non-inoculated leaf were recorded and compared with the spatial distribution of the virus detected by the fluorescence of GFP associated with the virus. We determined infection-related changes at different points of the light-induced chlorophyll fluorescence kinetics and at different days after inoculation. A slight change in the light-adapted steady-state values of ΦPSII and NPQ was observed in the infected area of the non-inoculated leaf. In contrast to the steady-state parameters, the dynamics of ΦPSII and NPQ caused by the dark–light transition in healthy and infected areas differed significantly starting from the second day after the detection of the virus in a non-inoculated leaf. The coefficients of correlation between chlorophyll fluorescence parameters and virus localization were 0.67 for ΦPSII and 0.76 for NPQ. In general, the results demonstrate the possibility of reliable pre-symptomatic detection of the spread of a viral infection using chlorophyll fluorescence imaging.

Healing of periapical lesion after root canal treatment: A case report

Most of periapical lesions usually result from microbial infection with oral microorganisms originating from the degenerated pulp tissue. These lesions are commonly painless and incidentally found on routine radiographic examinations. Treating these cases using non-surgical root canal is the fruit of the innovative techniques, tools and root medicaments as well as the tendency toward minimally invasive treatment. The healing process of the infected area is conditioned by a proper diagnosis, a treatment that follows good clinical practice under aseptic environment including cleaning, shaping and root filing. The aim of the present clinical case report was to report non-surgical healing of a periapical lesion of endodontic origin associated with maxillary left central incisor, observed over a period of 2 years.

Local device infection successfully treated without pacemaker removal in a neonate: a case report

Aims: Local device infection is a serious complication, especially in neonates. Complete device removal is the gold standard treatment for cardiac device infection; however, in selected cases alternative strategies could be adopted. We describe a case of a 14-day-old neonate, weighing 2.5kg, who had undergone epicardial double chamber pacemaker implantation for a congenital complete atrioventricular block. The generator pocket was created in the epigastric area below the rectus abdominis. At six days after implantation, pocket infection was found; blood cultures and the transoesophageal echocardiogram were normal. Due to the low weight of the neonate, and the limited possibility of finding a new comfortable site for housing the generator far from the infected area, we opted for a conservative strategy. We successfully applied a combination of antibiotic therapy, a vacuum-assisted wound closure system (KCI, Germany) for 40 days, and then skin transfer flap from the right flank without device removal. At one-year follow-up there were no local or systemic signs of infection.

Isolation and Identification of Pathogenic Bacteria from Baime Fish (Mystus armatus) and Evaluation of Antibiotic Susceptibility

Aquaculture products (fish) can harbor pathogenic bacteria which are part of the natural micro-flora of the environment. The current study was carried out for the extraction and identification of fish pathogenic microbes from Baime fish (Mystus armatus). Diseased fresh-water fishes were collected from different water bodies and fish landing centers of two study areas, namely the City area, Jhenaidah region. Bacteria are one of the important causative agents of fish diseases in both wild and cultured fish and are responsible for serious economic losses. Pathogenic bacteria strain was isolated from the infected area of Baime (M. armatus) fish skin. After isolation, isolates were finally identified by their desired morphological, characteristics, and biochemical test. They were gram-negative, rod-shaped bacteria that showed positive reaction for catalase, able to ferment glucose and one is citrate negative and another is citrate positive. After being persuaded above-mentioned test isolates were identified as genus Aeromonas and Pseudomonas. The ulcer type disease of M. armatus, the isolate was tested against several antibiotics’ treatment. Pseudomonas strains isolated from M. armatus is susceptible to penicillin G (10 μg), amoxicillin (10 μg), erythromycin (15 μg), Tetracycline (30 μg), Kanamycin (30 μg), moderately susceptible to Co-trimoxazole (25 μg), and Resistance to ceftazidime (10 μg). Aeromonas strains isolated from M. armatus is susceptible to amoxicillin (10 μg), erythromycin (15 μg), Tetracycline (30 μg), moderately susceptible to ceftazidime (10 μg), and Resistance to Co-trimoxazole (25 μg), penicillin G (10 μg), Kanamycin (30 μg). The results of the present study constitute an advance in the available diagnostic and bacterial pathogens in fish farms.

Segmentation of infected region in CT images of COVID-19 patients based on QC-HC U-net

Since the outbreak of COVID-19 in 2019, the rapid spread of the epidemic has brought huge challenges to medical institutions. If the pathological region in the COVID-19 CT image can be automatically segmented, it will help doctors quickly determine the patient’s infection, thereby speeding up the diagnosis process. To be able to automatically segment the infected area, we proposed a new network structure and named QC-HC U-Net. First, we combine residual connection and dense connection to form a new connection method and apply it to the encoder and the decoder. Second, we choose to add Hypercolumns in the decoder section. Compared with the benchmark 3D U-Net, the improved network can effectively avoid vanishing gradient while extracting more features. To improve the situation of insufficient data, resampling and data enhancement methods are selected in this paper to expand the datasets. We used 63 cases of MSD lung tumor data for training and testing, continuously verified to ensure the training effect of this model, and then selected 20 cases of public COVID-19 data for training and testing. Experimental results showed that in the segmentation of COVID-19, the specificity and sensitivity were 85.3% and 83.6%, respectively, and in the segmentation of MSD lung tumors, the specificity and sensitivity were 81.45% and 80.93%, respectively, without any fitting.

Generation of Synthetic Peptide-Specific Antibody for the Development of A Southern Rice Black-Streaked Dwarf Virus Diagnostic Test

Southern rice black-streaked dwarf virus (SRBSDV) causes severe epidemical disease on rice with the infected area up to millions of hectares in South China and North and Central of Vietnam. So far, there are no effective, cheap, quick, and practicable methods for diagnosing SRBSDV. The conventional RT-PCR technique is the most popular method for detecting SRBSDV with high accuracy. However, it is hard to apply this method for large-scale SDBSDV diagnosis because of the requirements of expensive reagents and instruments, as well as complex procedures. Meanwhile, SRBSDV diagnostic techniques based on antigen detection have outstanding advantages due to their low cost, easy manipulation, and wide application possibility. Today, there are still no commercially available specific antibodies to SRBSDV. In a previous study, to develop the SRBSDV diagnostic technique by the ELISA technique, a SRBSDV specific antibody was generated by a recombinant P10 envelope protein (66kDa), which has a titer of 1:5,000. In this study, we continued to study the production of SRBSDV specific polyclonal antibodies from small antigen–rich peptides from the SRBSDV P10 envelope protein. The resulting purified antibody can specifically bind to the P10 protein and at the diluted concentration of 1:100,000 it can detect SRBSDV in infected rice samples via the dot-blot technique. Our research results open up new opportunities for proactive antibodies to develop a SRBSDV membrane rapid diagnostic kit.

Interplay between mobility, multi-seeding and lockdowns shapes COVID-19 local impact

Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. While many factors affect disease incidence at a local level, making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can lead to independent outbreaks that spark from distinct areas of the local contact (social) network. Such mechanism has the potential to boost incidence, making control efforts and contact tracing less effective. Here, through a modeling approach we show that the effect produced by the number of initial infections is non-linear on the incidence peak and peak time. When case importations are carried by mobility from an already infected area, this effect is further enhanced by the local demography and underlying mixing patterns: the impact of every seed is larger in smaller populations. Finally, both in the model simulations and the analysis, we show that a multi-seeding effect combined with mobility restrictions can explain the observed spatial heterogeneities in the first wave of COVID-19 incidence and mortality in five European countries. Our results allow us for identifying what we have called epidemic epicenter: an area that shapes incidence and mortality peaks in the entire country. The present work further clarifies the nonlinear effects that mobility can have on the evolution of an epidemic and highlight their relevance for epidemic control.

Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning

Breast cancer is one of the main causes of death among women worldwide. Early detection of this disease helps reduce the number of premature deaths. This research aims to design a method for identifying and diagnosing breast tumors based on ultrasound images. For this purpose, six techniques have been performed to detect and segment ultrasound images. Features of images are extracted using the fractal method. Moreover, k-nearest neighbor, support vector machine, decision tree, and Naïve Bayes classification techniques are used to classify images. Then, the convolutional neural network (CNN) architecture is designed to classify breast cancer based on ultrasound images directly. The presented model obtains the accuracy of the training set to 99.8%. Regarding the test results, this diagnosis validation is associated with 88.5% sensitivity. Based on the findings of this study, it can be concluded that the proposed high-potential CNN algorithm can be used to diagnose breast cancer from ultrasound images. The second presented CNN model can identify the original location of the tumor. The results show 92% of the images in the high-performance region with an AUC above 0.6. The proposed model can identify the tumor’s location and volume by morphological operations as a post-processing algorithm. These findings can also be used to monitor patients and prevent the growth of the infected area.

First report that Mucor irregularis causes white mold disease on substrates used for wine-cap mushroom (Stropharia rugosoannulata) cultivation in China

Stropharia rugosoannulata, a world-wide popular mushroom, is one of the edible fungi recommended by the Food and Agriculture Organization of the United Nations (FAO) to developing countries (Hawksworth et al., 1996). In China, the cultivation scale of S. rugosoannulata exceeded 40 km2 in 2020 according to the incomplete statistics from emushroom network (http://www.emushroom.net/news/202104/06/33499.html). In October 2020, white mold disease was found on substrates of S. rugosoannulata in a heliogreenhouse in Huai’an city, Jiangsu province, China (Figure 1). The cultivation materials of S. rugosoannulata included rice straw (30%), wheat straw (30%), saw dust (30%), and a small amount of wheat bran (5%) and rice bran (5%). After mixing them together, the mycelial strain of S. rugosoannulata was seeded into the mixture, and then covered by casing soil for further cultivation. In the heliogreenhouse, the average air temperature and relative air humidity were 18 ± 4℃ and 73 ± 3%, respectively. In the diseased substrates, a large amount of thick white fungal mycelia were observed with yellow ooze on the surface, which prevented the growth of the mycelia and fruiting bodies of S. rugosoannulata (Figure 2). However in the fruiting period, no disease symptoms were found on mature fruiting bodies of S. rugosoannulata. The white mold disease incidence was calculated as ~ 30% by dividing the total infected area of substrates with the total area of the substrates examined. This white mold disease resulted in serious economic losses due to reduced production.