The AAP gene family for amino acid permeases contributes to development of the cyst nematode Heterodera schachtii in roots of Arabidopsis

The beet cyst nematode Heterodera schachtii is able to infect Arabidopsis plants and induce feeding sites in the root. These syncytia are the only source of nutrients for the nematodes throughout their life and are a nutrient sink for the host plant. We have studied here the role of amino acid transporters for nematode development. Arabidopsis contains a large number of different amino acid transporters in several gene families but those of the AAP family were found to be especially expressed in syncytia. Arabidopsis contains 8 AAP genes and they were all strongly expressed in syncytia with the exception of AAP5 and AAP7, which were slightly downregulated. We used promoter::GUS lines and in situ RT-PCR to confirm the expression of several AAP genes and LHT1, a lysine- and histidine-specific amino acid transporter, in syncytia. The strong expression of AAP genes in syncytia indicated that these transporters are important for the transport of amino acids into syncytia and we used T-DNA mutants for several AAP genes to test for their influence on nematode development. We found that mutants of AAP1, AAP2, and AAP8 significantly reduced the number of female nematodes developing on these plants. Our study showed that amino acid transport into syncytia is important for the development of the nematodes

Impact of Macroeconomic Conditions, Industry Attributes and Firms Related Variables on Capital Structure: A Cross Industry Analysis

Purpose: This study is conducted to examine the main strength of firms’ specific variables, industry effects and macroeconomic conditions in predicting the capital structure choices of non financial listed companies of Pakistan Stock Exchange (PSX-100). Design/Methodology/Approach: To perform the study, a sample of twelve sectors covering a period from 2012 to 2017 is taken from PSX-100.  Seemingly Unrelated Regression (SUR) model is applied to explore the capital structure choices. Results of study indicate that the short term debt plays a major part in designing the capital structure of listed companies of PSX-100. Findings: Macroeconomic conditions have been identified to cause an increase in financial distress and costs of debt unanimously. The financial distress and costs are significant in financial market developments for a time horizons. Implications/Originality/Value: The development in financial markets can have an opportunity to increase the choice of capital structure of firms optimistically. It is explored that source of capital choice seems to decrease in agency behavior and risk due to refinancing. The less agency problem and less risk provide better choice of debt and future growth to the financial market. The growth environment is life blood of financial market and economy

PROTECTING OUR CROPS - APPROACHES FOR PLANT PARASITIC NEMATODE CONTROL

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Improved Model Predictive Direct Power Control for Parallel Distributed Generation in Grid-Tied Microgrids

This research proposes an improved finite control set direct power model predictive control method (FCS-DPMPC) for grid-tie distributed generation (DG). FCS-DPMPC predicts the system outcomes using the system model. During the next sampling time, a voltage vector is defined using the cost function to minimize the power ripple, consequently allowing flexibility for power regulation. Furthermore, the impact of implementing a one-step delay is studied and compensated through a model forecast pattern. In addition, a new two-step horizon technique has been developed to minimize switching frequency and computation burden. Simulation results for single DG and parallel operated DGs in a grid-tie manner confirm the effectiveness of the suggested control strategy, which signifies that this is an appropriate approach for distributed generation in microgrids.© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Three siblings with familial non-medullary thyroid carcinoma: a case series

Abstract BACKGROUND: In 2015, thyroid carcinoma affected approximately 63,000 people in the USA, yet it remains one of the most treatable cancers. It is mainly classified into medullary and non-medullary types. Conventionally, medullary carcinoma was associated with heritability but increasing reports have now begun to associate non-medullary thyroid carcinoma with a genetic predisposition as well. It is important to identify a possible familial association in patients diagnosed with non-medullary thyroid carcinoma because these cancers behave more destructively than would otherwise be expected. Therefore, it is important to aggressively manage such patients and screening of close relatives might be justified. Our case series presents a diagnosis of familial, non-syndromic, non-medullarycarcinoma of the thyroid gland in three brothers diagnosed over a span of 6 years. CASE PRESENTATIONS: We report the history, signs and symptoms, laboratory results, imaging, and histopathology of the thyroid gland of three Pakistani brothers of 58 years, 55 years, and 52 years from Sindh with non-medullary thyroid carcinoma. Only Patients 1 and 3 had active complaints of swelling and pruritus, respectively, whereas Patient 2 was asymptomatic. Patients 2 and 3 had advanced disease at presentation with lymph node metastasis. All patients underwent a total thyroidectomy with Patients 2 and 3 requiring a neck dissection as well. No previous exposure to radiation was present in any of the patients. Their mother had died from adrenal carcinoma but also had a swelling in the front of her neck which was never investigated. All patients remained stable at follow-up. CONCLUSIONS: Non-medullary thyroid carcinoma is classically considered a sporadic condition. Our case report emphasizes a high index of suspicion, a detailed family history, and screening of first degree relatives when evaluating patients with non-medullarythyroid carcinoma to rule out familial cases which might behave more aggressively

Psychological and psychotherapeutic challenges of COVID-19

Coronavirus is a deadly disease, classified on 30th January 2020, by the World Health Organization (WHO) that acknowledged the outburst of coronavirus disease 2019  (COVID-19), after several cases were reported from China’s 34 regions. In 2020 the virus originated from the wholesale seafood market in Wuhan (China)spreading life all around the world. Quarantine, restraints, and economic closure can change a whole psychological environment in all the countries having coronavirus. affect Although this situation should give several opportunities for personal growth and family unity, disadvantages may compensate for these benefits affecting the psychological health of children and adolescents. But in this difficult time anxiety, and stress are common due to lake of relationships and also due to a reduction in other opportunities other risk includes parents’ mental illness, domestic violence, and lack of treatment for the child during an illness. This was especially common in adolescents and children because they need special care thus causing disabilities, traumatic experiences, and mental health problems. With all these above-mentioned problems this was definitely a challenging time. In Italy where Covid-19 had severe effects on physical health but on mental health also and psychological issues are long-term and main challenges for our healthcare systems where mental health gain not as much important as other physical illnesses

A study on microbial self-healing concrete using expanded perlite

The increasing concern for the safety and sustainability of structures is calling for the development of smart self-healing materials and preventive repair methods. This research is carried out to investigate the extent of self-healing in normal-strength concrete by using Sporosarcina aquimarina – NCCP-2716 immobilized in expanded perlite (EP) as the carrier. The efficacy of crack-healing was also tested using two alternative self-healing techniques, i.e. expanded perlite (EP) concrete and direct introduction of bacteria in concrete. A bacterial solution was embedded in EP and calcium lactate pentahydrate was added as the nutrient. Experiments revealed that specimens containing EP-immobilized bacteria had the most effective crack-healing. After 28 days of healing, the values of completely healed crack widths were up to 0.78 mm, which is higher than the 0.5 mm value for specimens with the direct addition of bacteria. The specimen showed a significant self-healing phenomenon caused by substantial calcite precipitation by bacteria. The induced cracks were observed to be repaired autonomously by the calcite produced by the bacteria without any adverse effect on strength. The results of this research could provide a scientific foundation for the use of expanded perlite as a novel microbe carrier and Sporosarcina aquimarina as a potential microbe in bacteria-based self-healing concrete

Selective Deeply Supervised Multi-Scale Attention Network for Brain Tumor Segmentation

Brain tumors are among the deadliest forms of cancer, characterized by abnormal proliferation of brain cells. While early identification of brain tumors can greatly aid in their therapy, the process of manual segmentation performed by expert doctors, which is often time-consuming, tedious, and prone to human error, can act as a bottleneck in the diagnostic process. This motivates the development of automated algorithms for brain tumor segmentation. However, accurately segmenting the enhanced and core tumor regions is complicated due to high levels of inter- and intra-tumor heterogeneity in terms of texture, morphology, and shape. This study proposes a fully automatic method called the selective deeply supervised multi-scale attention network (SDS-MSA-Net) for segmenting brain tumor regions using a multi-scale attention network with novel selective deep supervision (SDS) mechanisms for training. The method utilizes a 3D input composed of five consecutive slices, in addition to a 2D slice, to maintain sequential information. The proposed multi-scale architecture includes two encoding units to extract meaningful global and local features from the 3D and 2D inputs, respectively. These coarse features are then passed through attention units to filter out redundant information by assigning lower weights. The refined features are fed into a decoder block, which upscales the features at various levels while learning patterns relevant to all tumor regions. The SDS block is introduced to immediately upscale features from intermediate layers of the decoder, with the aim of producing segmentations of the whole, enhanced, and core tumor regions. The proposed framework was evaluated on the BraTS2020 dataset and showed improved performance in brain tumor region segmentation, particularly in the segmentation of the core and enhancing tumor regions, demonstrating the effectiveness of the proposed approach. Our code is publicly available. 2023 by the authors.Scopu

Robust hybrid synchronization control of chaotic 3-cell CNN with uncertain parameters using smooth super twisting algorithm

This paper presents the control design framework for the hybrid synchronization (HS) and parameter identification of the 3-Cell Cellular Neural Network. The cellular neural network (CNN) of this kind has increasing practical importance but due to its strong chaotic behavior and the presence of uncertain parameters make it difficult to design a smooth control framework. Sliding mode control (SMC) is very helpful for this kind of environment where the systems are nonlinear and have uncertain parameters and bounded disturbances. However, conventional SMC offers a dangerous chattering phenomenon, which is not acceptable in this scenario. To get chattering-free control, smooth higher-order SMC formulated on the smooth super twisting algorithm (SSTA) is proposed in this article. The stability of the sliding surface is ensured by the Lyapunov stability theory. The convergence of the error system to zero yields hybrid synchronization and the unknown parameters are computed adaptively. Finally, the results of the proposed control technique are compared with the adaptive integral sliding mode control (AISMC). Numerical simulation results validate the performance of the proposed algorithm