Obstetric outcome in pregnancy complicated by ovarian cysts

Background: Ovarian masses are diagnosed in 0.5-1% pregnancies. During pregnancy ovarian cysts can undergo: resolution of the cyst, change of ultrasound pattern, occurrence of ovarian torsion and intra-cystic haemorrhage or rupture. Ovarian masses (esp torsion) is a cause of pain abdomen during pregnancy. The choice of treatment is mainly conservative, provided the patient is asymptomatic. Dilemma in management arises when the patient is symptomatic. Optimal timing for a planned surgery is the second trimester as it is shown to have least neonatal outcome. The objective of this study was to evaluate management options for ovarian cyst in pregnancy and its effect on outcome of pregnancy.Methods: This study was conducted for 2 years from June 2014 to June 2016, at RL Jalappa Hospital, Kolar. A total of 46 pregnant women were included. The pregnancy outcome and the management used were studied. Also studied were the complications most likely to occur in pregnancies complicated by ovarian masses ovarian masses.Results: Out of 46 patients, 2 (4.3%) patients with ovarian cyst torsion underwent emergency laparotomy. 8 patients underwent surgery (6 in 2nd trimester and 2 at term) for various complications. Only one patient had miscarriage and remaining patients continued till term. Histopathological report of all the masses excised were obtained and 6 were reported to be benign serous cystadenomas,1 benign mucinous cystadenoma and 3 simple cysts.Conclusions: Optimal management for ovarian cyst is conservative in pregnancy provided patient remain asymptomatic and characteristic of cyst are consistent with benign pathology. Surgical management is to be reserved for symptomatic patient

An Optimized Deep Learning Based Optimization Algorithm for the Detection of Colon Cancer Using Deep Recurrent Neural Networks

Colon cancer is the second leading dreadful disease-causing death. The challenge in the colon cancer detection is the accurate identification of the lesion at the early stage such that mortality and morbidity can be reduced. In this work, a colon cancer classification method is identified out using Dragonfly-based water wave optimization (DWWO) based deep recurrent neural network. Initially, the input cancer images subjected to carry a pre-processing, in which outer artifacts are removed. The pre-processed image is forwarded for segmentation then the images are converted into segments using Generative adversarial networks (GAN). The obtained segments are forwarded for attribute selection module, where the statistical features like mean, variance, kurtosis, entropy, and textual features, like LOOP features are effectively extracted. Finally, the colon cancer classification is solved by using the deep RNN, which is trained by the proposed Dragonfly-based water wave optimization algorithm. The proposed DWWO algorithm is developed by integrating the Dragonfly algorithm and water wave optimization

GBS-based SNP map pinpoints the QTL associated with sorghum downy mildew resistance in maize (Zea mays L.)

Sorghum downy mildew (SDM), caused by the biotrophic fungi Peronosclerospora sorghi, threatens maize production worldwide, including India. To identify quantitative trait loci (QTL) associated with resistance to SDM, we used a recombinant inbred line (RIL) population derived from a cross between resistant inbred line UMI936 (w) and susceptible inbred line UMI79. The RIL population was phenotyped for SDM resistance in three environments [E1-field (Coimbatore), E2-greenhouse (Coimbatore), and E3-field (Mandya)] and also utilized to construct the genetic linkage map by genotyping by sequencing (GBS) approach. The map comprises 1516 SNP markers in 10 linkage groups (LGs) with a total length of 6924.7 cM and an average marker distance of 4.57 cM. The QTL analysis with the phenotype and marker data detected nine QTL on chromosome 1, 2, 3, 5, 6, and 7 across three environments. Of these, QTL namely qDMR1.2, qDMR3.1, qDMR5.1, and qDMR6.1 were notable due to their high phenotypic variance. qDMR3.1 from chromosome 3 was detected in more than one environment (E1 and E2), explaining the 10.3% and 13.1% phenotypic variance. Three QTL, qDMR1.2, qDMR5.1, and qDMR6.1 from chromosomes 1, 5, and 6 were identified in either E1 or E3, explaining 15.2%–18% phenotypic variance. Moreover, genome mining on three QTL (qDMR3.1, qDMR5.1, and qDMR6.1) reveals the putative candidate genes related to SDM resistance. The information generated in this study will be helpful for map-based cloning and marker-assisted selection in maize breeding programs

An inexpensive and rapid diagnostic method for detection of SARS-CoV-2 RNA by loop-mediated isothermal amplification (LAMP)

SARS-CoV-2 is a public pandemic health concern globally. Nasopharyngeal and oropharyngeal swab samples are used for Covid-19 viral detection. Sample collection procedure was tedious and uncomfortable and unsuitable for biochemical and CBC analysis in swab samples. Biochemistry and CBC tests are key determinant in management of Covid-19 patients. We developed a LAMP test to detect viral RNA in blood samples. LAMP is required four specific primers targeting the internal transcribed S-region and loop primers for viral RNA amplification. RNA was extracted from blood samples by TRIzol method. LAMP reaction was performed at 60 °C for 1 hour and amplicons were visualized in HNB dye. No cross-reactivity was seen with HBV, HCV, and HIV infected sample. Out of 40 blood samples, 33 samples were positive for LAMP and Q-PCR analysis, one sample was positive for LAMP and negative for Q-PCR, two samples were negative for LAMP but positive for Q-PCR, and four blood samples were negative for LAMP and Q-PCR. LAMP method has an accuracy of 92.50%, with sensitivity and specificity of 94.28% and 80%, respectively. Thus, LAMP diagnostic test has proved reliable, fast, inexpensive and can be useful for detection where the limited resources available. • LAMP method is a potential tool for detection of SARS-CoV-2. • Blood samples are the key determinant for routine diagnostics as well as molecular diagnostics. • LAMP assay is an appropriate diagnostics method which offers greater simplicity, low cost, sensitivity, and specificity than other methods in molecular diagnostics

Hypofibrinogenemia in isolated traumatic brain injury in Indian patients

Coagulation abnormalities are common in patients with head injuries. However, the effect of brain injury on fibrinogen levels has not been well studied prospectively to assess coagulation abnormalities in patients with moderate and severe head injuries and correlate these abnormalities with the neurologic outcome. Consecutive patients with moderate (Glasgow Comma Scale (GCS),9-12) and severe (GCS≤8) head injuries were the subjects of this pilot study, All patients had coagulation parameters, including plasma fibrinogen levels measured. Clinical and computed tomography (CT) scan findings and immediate clinical outcome were analyzed. Of the 100 patients enrolled, only seven (7%) patients had hypofibrinogenemia (fibrinogen ≤200 mg/dL). The head injury was moderate in two patients and severe in five patients. Fibrinogen levels showed a progressively increasing trend in four patients (three with severe head injuries and one with moderate head injury). CT scan revealed subdural hematoma in five patients; extradural hematoma in one; and subarachnoid hemorrhage in another patient. Of the seven patients, two patients died during hospital. Large-scale prospective studies are needed to assess the fibrinogen level in patients with head injury and its impact on outcome