Glycogen metabolic genes are involved in trehalose-6-phosphate synthase-mediated regulation of pathogenicity by the rice blast fungus Magnaporthe oryzae.

© 2013 Badaruddin et al.Editor - Peter N. Dodds, Commonwealth Scientific and Industrial Research Organisation (CSIRO), AustraliaThis work was funded by the Biotechnology and Biological Sciences Research Council and a European Research Council Advanced Investigator Award to NJT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The filamentous fungus Magnaporthe oryzae is the causal agent of rice blast disease. Here we show that glycogen metabolic genes play an important role in plant infection by M. oryzae. Targeted deletion of AGL1 and GPH1, which encode amyloglucosidase and glycogen phosphorylase, respectively, prevented mobilisation of glycogen stores during appressorium development and caused a significant reduction in the ability of M. oryzae to cause rice blast disease. By contrast, targeted mutation of GSN1, which encodes glycogen synthase, significantly reduced the synthesis of intracellular glycogen, but had no effect on fungal pathogenicity. We found that loss of AGL1 and GPH1 led to a reduction in expression of TPS1 and TPS3, which encode components of the trehalose-6-phosphate synthase complex, that acts as a genetic switch in M. oryzae. Tps1 responds to glucose-6-phosphate levels and the balance of NADP/NADPH to regulate virulence-associated gene expression, in association with Nmr transcriptional inhibitors. We show that deletion of the NMR3 transcriptional inhibitor gene partially restores virulence to a Δagl1Δgph1 mutant, suggesting that glycogen metabolic genes are necessary for operation of the NADPH-dependent genetic switch in M. oryzae.Biotechnology and Biological Sciences Research Council (BBSRC)European Research Council (ERC

ENHANCING NETWORK PERFORMANCE LOAD BALANCING IN CYBER CAFE NETWORKS WITH DIJKSTRA ALGORITHM ON MIKROTIK

The internet has become a fundamental necessity in various activities today. Stream Cyber Cafe, as an internet service provider, faces the challenge of maintaining network quality so that users can comfortably engage in activities such as gaming, streaming services, and social media. Load balancing, utilizing multiple internet sources from various ISPs, becomes a solution to enhance network efficiency and responsiveness. This research focuses on implementing the Dijkstra algorithm on MikroTik devices to determine the shortest path based on DNS server latency from various internet service providers (ISP). The main steps include configuring MikroTik devices, analyzing latency connections to DNS servers, and employing the Dijkstra algorithm. The Dijkstra algorithm, utilizing a Greedy approach, considers the minimum weight from the starting node to other nodes. Testing using the "PING" command provides information on the number of hops or steps required to reach each DNS server. Dijkstra adapts the shortest path based on latency, yielding optimal load balancing efficiency. Configuring MikroTik features, such as Firewall Mangle, Routing Table, and Routing Gateway, supports the functionality of the Dijkstra algorithm. Test results show that each ISP has a different shortest path to DNS servers, and the Dijkstra algorithm can determine the shortest path by considering time or latency factors. Although the author acknowledges some technical challenges during implementation, the proposed solution successfully overcomes these challenges. Thus, the use of the Dijkstra algorithm on MikroTik proves its effectiveness in enhancing the performance and reliability of the network in the Stream Cyber Cafe environment

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Wind Power Integration with Smart Grid and Storage System: Prospects and Limitations

Wind power generation is playing a pivotal role in adopting renewable energy sources in many countries. Over the past decades, we have seen steady growth in wind power generation throughout the world. This article aims to summarize the operation, conversion and integration of the wind power with conventional grid and local microgrids so that it can be a one-stop reference for early career researchers. The study is carried out primarily based on the horizontal axis wind turbine and the vertical axis wind turbine. Afterward, the types and methods of storing this electric power generated are discussed elaborately. On top of that, this paper summarizes the ways of connecting the wind farms with conventional grid and microgrid to portray a clear picture of existing technologies. Section-wise, the prospects and limitations are discussed and opportunities for future technologies are highlighted. It is envisaged that, this paper will help researchers and engineering professionals to grasp the fundamental concepts related to wind power generation concisely and effectively

Performance analysis of photovoltaic passive heat storage system with microencapsulated paraffin wax for thermoelectric generation

The depletion of non-renewable energy sources and negative effects towards the environment push research towards the widespread adoption of renewable energy sources such as solar energy. The main drawback of solar panels is that temperatures above 27°C will result in an efficiency drop of 0.1-0.5%/°C. In previous studies, usage of photovoltaic thermal (PVT) systems was mainly for the purpose of heating water, warming buildings, and drying crops. This research will focus on the usage of a standalone PVT and thermoelectric generator (TEG) system whereby it uses heat extracted from the PVT system for thermoelectric generation. A passive standalone PVT-TEG system design with microencapsulated paraffin wax as a phase change material (PCM) as a heat storage medium was created. The heat stored in the PCM is used as a heat source for thermoelectric generation. To extract the heat from the PV panel, an aluminum heatsink underneath the PV panel is used as a heat absorber to passively extract heat without external power sources. This setup reduces the surface temperature by 22.7°C. Transient thermal analysis and thermoelectric simulation of the system was conducted through Computational Fluid Dynamics (CFD) using ANSYS 2019 software. The error recorded between the experimental and simulation results was 4.2%. This proposed system panel successfully increased the electrical efficiency of the PV panel by approximately 12.8%, where the overall electrical power produced shows a significant increase from 7.7W to 17.7W

COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network

The reliable and rapid identification of the COVID-19 has become crucial to prevent the rapid spread of the disease, ease lockdown restrictions and reduce pressure on public health infrastructures. Recently, several methods and techniques have been proposed to detect the SARS-CoV-2 virus using different images and data. However, this is the first study that will explore the possibility of using deep convolutional neural network (CNN) models to detect COVID-19 from electrocardiogram (ECG) trace images. In this work, COVID-19 and other cardiovascular diseases (CVDs) were detected using deep-learning techniques. A public dataset of ECG images consisting of 1937 images from five distinct categories, such as normal, COVID-19, myocardial infarction (MI), abnormal heartbeat (AHB), and recovered myocardial infarction (RMI) were used in this study. Six different deep CNN models (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, and MobileNetv2) were used to investigate three different classification schemes: (i) two-class classification (normal vs COVID-19); (ii) three-class classification (normal, COVID-19, and other CVDs), and finally, (iii) five-class classification (normal, COVID-19, MI, AHB, and RMI). For two-class and three-class classification, Densenet201 outperforms other networks with an accuracy of 99.1%, and 97.36%, respectively; while for the five-class classification, InceptionV3 outperforms others with an accuracy of 97.83%. ScoreCAM visualization confirms that the networks are learning from the relevant area of the trace images. Since the proposed method uses ECG trace images which can be captured by smartphones and are readily available facilities in low-resources countries, this study will help in faster computer-aided diagnosis of COVID-19 and other cardiac abnormalities

Composition and Diversity of Tree Species with DBH of 5 cm and above at Pulau Banding, Gerik, Perak, Malaysia

A total of 92 individual trees with DBH of 5 cm and above comprising 21 families, 28 genera and 35 species were measured, identified and recorded. This study aimed to enumerate the tree species composition and estimate the diversity index of trees with DBH of 5 cm and above at Pulau Banding, Perak. An ecological plot size of 70 m x 70 m or 0.49 ha was established and divided into three subplots. The data collection was collected to determine the number of species, number of individuals and DBH within the plots. The Shannon Diversity Index was estimated at H’ = 2.98 (H’max = 3.53) while the Simpson’s Index (D) was 0.10 and Species Evenness (E) was 0.85. Murraya paniculata (Rutaceae) was the most important species with an IV i (Important Value Index) of 24.7%, while Dipterocarpaceae was the dominant family for the study area with an IV i of 45.36%. The total aboveground biomass of all trees with a DBH of 5 cm and above in a 0.49 ha plot in Pulau Banding was estimated at 66.2 t/ha. Hence this study is providing preliminary data on tree species composition at Pulau Banding, Perak for conserving the remaining valued timber trees that are still in the regeneration phase

The prevalence of pulmonary hypertension after successful tuberculosis treatment in a community sample of adult patients

There are an estimated 155 million survivors of tuberculosis (TB). Clinical experience suggests that post-pulmonary tuberculosis lung disease (PTLD) is an important cause of group 3 pulmonary hypertension (PH). However, TB is not listed as a cause of PH in most guidelines. A cross-sectional, community-based study was conducted in non-health care seeking adults who had successfully completed TB treatment. Subjects underwent questionnaires, spirometry, a six-minute walk distance test (6MWD) and transthoracic echocardiography (TTE). Screen probable PH was defined on TTE as an estimated pulmonary artery peak systolic pressure (PASP) of ≥40mmHg. One hundred adults (71 males) were enrolled, with a mean age of 42 years (SD 13.8 years) and a median of one TB episode (IQR: 1 -2). Co-morbidities included hypertension (21%), diabetes (16%), HIV (10%) and asthma/COPD (5%). Only 25% had no residual symptoms after TB. Probable PH was found in 9%, while 7% had borderline raised PASP values (PASP 35-40mmHg). An association was found between PH and the number of previous TB episodes, with each additional episode of TB increasing the odds of PH-post-TB 2.13-fold (CI 1.17-3.88; P=0.013). All of those found to have PH were smokers or ex-smokers yielding an unadjusted odds ratio for PH-post-TB of 3.67 (95%CI 0.77-17.46). There was no statistical difference in spirometry or 6MWD, between those with and without PH. Neither symptoms nor co-morbidities demonstrated significant association with PH. PH after TB was a common finding in this community-based population. Further research is needed to confirm and determine the significance of these findings

Association of depression with newly diagnosed type 2 diabetes among adults aged between 25 to 60 years in Karachi, Pakistan

<p>Abstract</p> <p>Background</p> <p>The combination of depression with type 2 diabetes is a public health problem. If diabetes is managed in its initial phase, the morbidity and mortality due to this combination may be prevented at an early stage. Therefore, we aimed to determine the association of depression with newly diagnosed type 2 diabetes among adults aged between 25 to 60 years in Karachi, Pakistan.</p> <p>Methods</p> <p>From July 2006 to September 2007, a matched case control study (n = 592) was conducted in Civil Hospital, Karachi. Incident cases of type 2 diabetes (n = 296) diagnosed within one month were recruited from diabetic Out Patient Department (OPD) of Civil Hospital, Karachi. They were matched on age and sex with controls (n = 296), who were attendants sitting in the medical out patient department of the same hospital, recruited on the basis of absence of classical symptoms of polyuria and polydispia along with random blood glucose level of <200 mg/dl measured by a glucometer. Depression was identified by the Siddiqui Shah Depression Scale. Conditional logistic regression was applied to examine the association of depression and other independent variables with newly diagnosed type 2 diabetes at 95% C.I. and P < 0.05.</p> <p>Results</p> <p>The study comprised of 592 subjects with 432(73%) males and 160(27%) females. Depression was significantly associated with newly diagnosed type 2 diabetes having mild level (mOR: 3.86; 95%CI: 2.22,6.71) and moderate to severe level (mOR: 3.41; 95%CI: 2.07,5.61). History of (h/o) gestational diabetes (mOR: 2.83; 95%CI: 1.05,7.64), family h/o diabetes (mOR: 1.59; 95%CI: 1.04,2.43), nuclear family (mOR: 1.75; 95%CI: 1.14,2.69), BMI (mOR: 1.62; 95%CI: 1.01,2.60 for obese and mOR: 2.12; 95%CI: 1.19,3.79 for overweight vs healthy to underweight) were also significantly associated with outcome, adjusting for age, sex, marital status, h/o smoking and h/o high BP.</p> <p>Conclusions</p> <p>Diabetics should be screened simultaneously for depression and concomitant preventive strategies for gestational diabetes, nuclear family and high BMI should also be used to prevent mortality/morbidity among patients between 25 to 60 years of age.</p

Distribution and Diversity of Family Rubiaceae in Pulau Banding, Gerik, Perak

The distribution and diversity of the Rubiaceae species were investigated along one trail at Pulau Banding, Gerik, Perak. This study aims to identify and estimate the diversity of the Rubiaceae species. The diversity and distribution of the Rubiaceae species were calculated using Shannon-Wiener’s Diversity Index, Simpson's Diversity Index and relative abundance index. A total of 139 individuals from nine species were recorded from Pulau Banding, Perak which are Mitracarpus hirtus, Gardenia carinata, Aidia densiflora, Hypobathrum hirtum, Coffea arabica, Psychotria marginata, Lasianthus constrictus, Porterandia anisophyllea and Ixora finlaysoniana. The values of the Shannon-Wiener’s Diversity Index (H′) and Simpson's Diversity Index (D) are 1.55 and 3.27, respectively. This indicates that M. hirtus is the most dominant species, encompassing 49% of all recorded Rubiaceae. Since it has many benefits such as food, timber, medicine, and the diversity of conservation value, this is vital as baseline data for researchers to propose solutions to the stakeholders and conservation sustainability of the Rubiaceae family as plant resources in Pulau Banding, Perak