A Clinical Study of Intraoperative Perfusion Chemotherapy in Gastric Cancer: A Prospective Cohort Study.

INTRODUCTION: Gastric cancer (GC) is the third largest cause of cancer-related death worldwide, with major geographic disparities in incidence and outcomes. Sociodemographic indicators, food habits, and genetic predispositions all add to the load. Despite advances in systemic treatments, peritoneal metastasis remains a concern, with intraperitoneal chemotherapy (IPC) emerging as a promising treatment option. METHODS: A prospective cohort research was done, with 30 GC patients receiving cytoreductive surgery (CRS) followed by lobaplatin-based intraoperative chemotherapy. The study evaluated postoperative complications, survival rates, and disease recurrence using Statistical Package for the Social Sciences (SPSS) version 25.0 (IBM SPSS Statistics, Armonk, NY) for data analysis. The purpose of this study is to assess the effectiveness, safety, and dependability of lobaplatin as an intraoperative chemotherapeutic agent in patients having gastric cancer surgery, with a particular emphasis on those patients who do not have distant metastases. RESULTS: The study population had a balanced gender distribution, with an average age of 44.83 years. Most patients had advanced-stage cancer (T3 and T4), and lobaplatin treatment resulted in a low frequency of serious postoperative sequelae. Preliminary studies suggest that lobaplatin is a safe and potentially effective IPC drug for GC, with few side effects and adequate survival rates. CONCLUSION: Lobaplatin shows promise as an intraoperative chemotherapeutic treatment for gastric cancer, necessitating more research in bigger, randomized controlled studies to determine its efficacy and safety profile. The study emphasizes the need for novel treatment strategies to enhance the prognosis of GC patients, particularly those with peritoneal involvement.

A Clinical Study of Intraoperative Perfusion Chemotherapy With Raltitrexed in Colon Cancer: A Prospective Cohort Study.

INTRODUCTION: Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality among women and the third leading cause of cancer-associated mortality among men. Treatment of colon cancer is very crucial for a patient's survival. In this study, we assessed the reliability, efficacy, and safety of raltitrexed in intraoperative intraperitoneal chemotherapy for colon cancer. METHODOLOGY: A total of 57 patients with clinical stages II and III of colon cancer were included in the study. R0 resection surgery + hyperthermic intraperitoneal chemotherapy (HIPEC) procedure was done with raltitrexed. It was given in a dose of 3 mg/m2 in a 0.9% NS injection in a volume of 500 milliliters. Postoperative complications were observed. RESULT: The most common postoperative complication was nausea/vomiting, which was seen in 21 out of 57 patients (37%). The second most common complication was fever (18/57). None of the patients died or developed renal toxicity, hepatic toxicity, and intestinal obstruction. CONCLUSION: Raltitrexed is a reliable, efficient, and safe drug and can be used in intraoperative intraperitoneal chemotherapy of colon cancer.

Evaluation of the District Health Information System in District Kotli, Azad Jammu and Kashmir: A Retrospective Analysis.

BACKGROUND: It is essential to implement a high-quality electronic database for keeping important information. The District Health Information System (DHIS) is an active data-keeping system in Pakistan. This study aimed to evaluate the patients' data from the DHIS dashboard for the District Headquarters Hospital, Kotli, Azad Jammu and Kashmir (AJK). METHODOLOGY: The data was requested from the hospital administration at District Headquarters Hospital, Kotli, AJK, and the data was analyzed after permission was granted. The data was given in two forms; one was a hard copy of the data for August and September and the other was a comma-separated values file for October and November, 2023. RESULTS: The highest frequency of patients was received in the department of emergency and trauma and the patient's median age was between 15 and 49 years. The second department was medicine with the >50 years of age. Common conditions that needed more attention were chronic obstructive pulmonary disease, acute respiratory infection, diarrhea, pneumonia, diabetes mellitus, hypertension, and ischemic heart disease. CONCLUSION: For nations with constrained healthcare systems and funds, primary health care (PHC) is the only viable approach for managing non-communicable diseases (NCDs). However, PHC systems intended for infectious diseases have not sufficiently adapted to the growing requirement of chronic care for NCD. Research using health information databases offers numerous benefits, such as the evaluation of large data sets and unexpected prevalence of disease in certain populations, such as a higher prevalence of disease in one gender or age group. Health information system-based data analysis or studies are less expensive and faster but lack scientific control over data collection.

Frequency of Amblyopia in strabismus patients presenting to tertiary care hospital.

Objective: The rationale of study was to find the magnitude of amblyopia with reference to type of squint among the strabismus patients visiting Hayatabad Medical Complex Peshawar, Pakistan. Materials and Methods: After ethical approval, a cross sectional study was carried out in the Department of Ophthalmology, Hayatabad Medical Complex, Peshawar, Pakistan, from April 2022 to October 2022, the total number of patients included being 237. Results: Amblyopia was observed in 113 out of 160 (70.6%) cases of uniocular squint, while in alternating squint it was found to be 11 out of 77 (14.2%). Amblyopia in patients with esotropia was seen in 73.2% (107 out of 146), while 59.3% (54 out of 91) exotropia had associated amblyopia. Conclusion: Strabismus amblyopia leads to developmental arrest of vision in early critical years of life. Permanent visual loss can be avoided with comprehensive screening and detailed examination of strabismic patient.

Antibiotics induced changes in nitrogen metabolism and antioxidative enzymes in mung bean (Vigna radiata).

Excessive use and release of antibiotics into the soil environment in the developing world have resulted in altered soil processes affecting terrestrial organisms and posing a serious threat to crop growth and productivity. The present study investigated the influence of exogenously applied oxytetracycline (OXY) and levofloxacin (LEV) on plant physiological responses, key enzymes involved in nitrogen metabolism (e.g., nitrate reductase, glutamine synthetase), nitrogen contents and oxidative stress response of mung bean (Vigna radiata). Plants were irrigated weekly with antibiotics containing water for exposing the plants to different concentrations i.e., 1, 10, 20, 50, and 100 mg L-1. Results showed a significant decrease in nitrate reductase activity in both antibiotic treatments and their mixtures and increased antioxidant enzymatic activities in plants. At lower concentrations of antibiotics (≤20 mg L-1), 53.9 % to 78.4 % increase in nitrogen content was observed in levofloxacin and mixtures compared to the control, resulting in an increase in the overall plant biomass. Higher antibiotic (≥50 mg L-1) concentration showed 58 % decrease in plant biomass content and an overall decrease in plant nitrogen content upon exposure to the mixtures. This was further complemented by 22 % to 42 % increase in glutamine synthetase activity observed in the plants treated with levofloxacin and mixtures. The application of low doses of antibiotics throughout the experiments resulted in lower toxicity symptoms in the plants. However, significantly higher malondialdehyde (MDA) concentrations at higher doses (20 mg L-1 and above) than the control showed that plants' tolerance against oxidative stress was conceded with increasing antibiotic concentrations. The toxicity trend was: levofloxacin > mixture > oxytetracycline.

Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives.

In light of the constantly changing terrain of the COVID outbreak, medical specialists have implemented proactive schemes for vaccine production. Despite the remarkable COVID-19 vaccine development, the virus has mutated into new variants, including delta and omicron. Currently, the situation is critical in many parts of the world, and precautions are being taken to stop the virus from spreading and mutating. Early identification and diagnosis of COVID-19 are the main challenges faced by emerging technologies during the outbreak. In these circumstances, emerging technologies to tackle Coronavirus have proven magnificent. Artificial intelligence (AI), big data, the internet of medical things (IoMT), robotics, blockchain technology, telemedicine, smart applications, and additive manufacturing are suspicious for detecting, classifying, monitoring, and locating COVID-19. Henceforth, this research aims to glance at these COVID-19 defeating technologies by focusing on their strengths and limitations. A CiteSpace-based bibliometric analysis of the emerging technology was established. The most impactful keywords and the ongoing research frontiers were compiled. Emerging technologies were unstable due to data inconsistency, redundant and noisy datasets, and the inability to aggregate the data due to disparate data formats. Moreover, the privacy and confidentiality of patient medical records are not guaranteed. Hence, Significant data analysis is required to develop an intelligent computational model for effective and quick clinical diagnosis of COVID-19. Remarkably, this article outlines how emerging technology has been used to counteract the virus disaster and offers ongoing research frontiers, directing readers to concentrate on the real challenges and thus facilitating additional explorations to amplify emerging technologies.

Comparison of prilocaine/lidocaine cream with piroxicam gel for reducing pain during cannulation of arteriovenous fistula for adults undergoing haemodialysis: A randomized crossover clinical trial.

BACKGROUND: Pain is a traumatic experience for most patients on hemodialysis. In this trial, we compared prilocaine/lidocaine cream with piroxicam gel for pain reduction during arteriovenous fistula needling. METHODS: This randomized double-blind crossover clinical trial was done at dialysis unit of a tertiary care hospital from June to August 2022. Adult patients, aged 18-75 years, on maintenance hemodialysis through an arteriovenous fistula were selected randomly. Pain severity during needling of fistula was assessed during initial two hemodialysis sessions without application of any drug. Patients were then randomized into two groups receiving 5% prilocaine/lidocaine cream or 0.5% piroxicam gel 1 h before the next two hemodialysis sessions. After a 7-day washout period, patients crossed over to other groups for another two hemodialysis sessions. Pain was assessed on all these occasions. Primary outcome was reduction in pain with each intervention. RESULTS: There were 32 patients aged 46.44 ± 11.58 years. Pain intensity was 6.69 ± 0.58, 3.13 ± 1.28, and 4.55 ± 1.95 without any medication, prilocaine/lidocaine cream and piroxicam gel respectively. There was greater pain reduction with prilocaine/lidocaine cream than piroxicam gel (3.56 ± 1.35 vs 2.14 ± 1.78; p = 0.001). Local redness with prilocaine/lidocaine cream was reported by one (3.13%) patient, whereas no side effects were seen with piroxicam gel (p = 1.000). CONCLUSION: Prilocaine/lidocaine cream provides better pain relief than piroxicam gel during arteriovenous fistula needling.

A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique.

In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge scale and deployment of IoMT networks. Machine learning (ML) and blockchain (BC) technologies have significantly enhanced the capabilities and facilities of healthcare 5.0, spawning a new area known as "Smart Healthcare." By identifying concerns early, a smart healthcare system can help avoid long-term damage. This will enhance the quality of life for patients while reducing their stress and healthcare costs. The IoMT enables a range of functionalities in the field of information technology, one of which is smart and interactive health care. However, combining medical data into a single storage location to train a powerful machine learning model raises concerns about privacy, ownership, and compliance with greater concentration. Federated learning (FL) overcomes the preceding difficulties by utilizing a centralized aggregate server to disseminate a global learning model. Simultaneously, the local participant keeps control of patient information, assuring data confidentiality and security. This article conducts a comprehensive analysis of the findings on blockchain technology entangled with federated learning in healthcare. 5.0. The purpose of this study is to construct a secure health monitoring system in healthcare 5.0 by utilizing a blockchain technology and Intrusion Detection System (IDS) to detect any malicious activity in a healthcare network and enables physicians to monitor patients through medical sensors and take necessary measures periodically by predicting diseases. The proposed system demonstrates that the approach is optimized effectively for healthcare monitoring. In contrast, the proposed healthcare 5.0 system entangled with FL Approach achieves 93.22% accuracy for disease prediction, and the proposed RTS-DELM-based secure healthcare 5.0 system achieves 96.18% accuracy for the estimation of intrusion detection.

Supervised Machine Learning Empowered Multifactorial Genetic Inheritance Disorder Prediction.

Fatal diseases like cancer, dementia, and diabetes are very dangerous. This leads to fear of death if these are not diagnosed at early stages. Computer science uses biomedical studies to diagnose cancer, dementia, and diabetes. With the advancement of machine learning, there are various techniques which are accessible to predict and prognosis these diseases based on different datasets. These datasets varied (image datasets and CSV datasets) around the world. So, there is a need for some machine learning classifiers to predict cancer, dementia, and diabetes in a human. In this paper, we used a multifactorial genetic inheritance disorder dataset to predict cancer, dementia, and diabetes. Several studies used different machine learning classifiers to predict cancer, dementia, and diabetes separately with the help of different types of datasets. So, in this paper, multiclass classification proposed methodology used support vector machine (SVM) and K-nearest neighbor (KNN) machine learning techniques to predict three diseases and compared these techniques based on accuracy. Simulation results have shown that the proposed model of SVM and KNN for prediction of dementia, cancer, and diabetes from multifactorial genetic inheritance disorder achieved 92.8% and 92.5%, 92.8% and 91.2% accuracy during training and testing, respectively. So, it is observed that proposed SVM-based dementia, cancer, and diabetes from multifactorial genetic inheritance disorder prediction (MGIDP) give attractive results as compared with the proposed model of KNN. The application of the proposed model helps to prognosis and prediction of cancer, dementia, and diabetes before time and plays a vital role to minimize the death ratio around the world.

An Intelligent Proposed Model for Task Offloading in Fog-Cloud Collaboration Using Logistics Regression.

Smart applications and intelligent systems are being developed that are self-reliant, adaptive, and knowledge-based in nature. Emergency and disaster management, aerospace, healthcare, IoT, and mobile applications, among them, revolutionize the world of computing. Applications with a large number of growing devices have transformed the current design of centralized cloud impractical. Despite the use of 5G technology, delay-sensitive applications and cloud cannot go parallel due to exceeding threshold values of certain parameters like latency, bandwidth, response time, etc. Middleware proves to be a better solution to cope up with these issues while satisfying the high requirements task offloading standards. Fog computing is recommended middleware in this research article in view of the fact that it provides the services to the edge of the network; delay-sensitive applications can be entertained effectively. On the contrary, fog nodes contain a limited set of resources that may not process all tasks, especially of computation-intensive applications. Additionally, fog is not the replacement of the cloud, rather supplement to the cloud, both behave like counterparts and offer their services correspondingly to compliance the task needs but fog computing has relatively closer proximity to the devices comparatively cloud. The problem arises when a decision needs to take what is to be offloaded: data, computation, or application, and more specifically where to offload: either fog or cloud and how much to offload. Fog-cloud collaboration is stochastic in terms of task-related attributes like task size, duration, arrival rate, and required resources. Dynamic task offloading becomes crucial in order to utilize the resources at fog and cloud to improve QoS. Since this formation of task offloading policy is a bit complex in nature, this problem is addressed in the research article and proposes an intelligent task offloading model. Simulation results demonstrate the authenticity of the proposed logistic regression model acquiring 86% accuracy compared to other algorithms and confidence in the predictive task offloading policy by making sure process consistency and reliability.

Phytotoxicity of different antibiotics to rice and stress alleviation upon application of organic amendments.

Extensive use of antibiotic results in significant antibiotics pollution in the environment. Main objective of this study was to gain insight into potential impacts of antibiotics on plant physiological growth and nutritional composition, and stress alleviation through application of different organic amendments. Effects of five antibiotics (ciprofloxacin, levofloxacin, ofloxacin, amoxicillin and ampicillin) were observed in the presence of three organic amendments (rice husk, farmyard manure and poultry litter) with rice (Oryza sativa L.) as a model plant. Organic amendments were mixed with soil (@ 5 g kg-1) and after three weeks, antibiotics were applied (@10 mg kg-1) and plants were allowed to grow for four months. After which plants were harvested and physical growth parameters (root/shoot length, biomass) and nutritional composition (grain protein content, carbohydrates, phosphorous and iron) were monitored. It was observed that germination rate, seedling root/shoot length, seedling biomass and vigor index were negatively impacted. The application of organic amendments alleviated antibiotic stress on seedling dry biomass, length and vigor index by 1.8-, 3.1- and 2.5-folds, respectively as compared to the antibiotic controls. Concentrations of phosphorous, iron, carbohydrates and proteins were decreased by 5.3-, 1.3-, 1.4- and 1.6-folds upon application of antibiotics. Rice husk was the most effective treatment in case of physical growth parameters and alleviating antibiotics' induced genotoxicity. Whereas, poultry litter had the highest positive effect on nutritional composition of plants. In general, the application of organic amendments alleviated the phytotoxicity as well as genotoxicity in plants under antibiotics stress.

In-silico pharmacophoric and molecular docking-based drug discovery against the Main Protease (Mpro) of SARS-CoV-2, a causative agent COVID-19.

COVID-19 (Coronavirus Disease 2019) caused by a novel 'SARS-CoV-2' virus resulted in public health emergencies across the world. An effective vaccine to cure this virus is not yet available, thus requires concerted efforts at various scales. In this study, we employed Computer-Aided Drug Design (CADD) based approach to identify the drug-like compounds - inhibiting the replication of the main protease (Mpro) of SARS-CoV-2. Our database search using an online tool "ZINC pharmer" retrieved ~1500 compounds based on pharmacophore features. Lipinski's rule was applied to further evaluate the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with Mpro based on S-score (higher than reference inhibitor) and root-mean-square deviation (RMSD) value (less than reference inhibitor) using AutoDock 4.2. Resultantly, ~200 compounds were identified having strong interaction with Mpro of SARS-CoV-2. After evaluating their binding energy using the AutoDock 4.2 software, three compounds (ZINC20291569, ZINC90403206, ZINC95480156) were identified that showed highest binding energy with Mpro of SARS-CoV-2 and strong inhibition effect than the N3 (reference inhibitor). A good binding energy, drug likeness and effective pharmacokinetic parameters suggest that these candidates have greater potential to stop the replication of SARS-CoV-2, hence might lead to the cure of COVID-19.

In silico Characterization of a Candidate Protein from Aphid Gelling Saliva with Potential for Aphid Control in Plants.

BACKGROUND: Sheath or gelling saliva, secreted during feeding by aphids, is a hard material that supports the piercing mouthparts and remains in the plant after feeding. Solidification or gelling of the saliva might be due to the composition of amino acids in the constituent proteins, many of which probably interact with plant defenses. OBJECTIVE: The complete complement of proteins in the gelling saliva are still unknown, although one sheath protein (SHP) has previously been identified as a potential candidate protein to control aphid feeding, but its structure and its physiochemical role remains obscure. The current study provides structural information and biochemical properties of the aphid sheath protein. METHODS: The Sheath protein encoding gene was amplified from cDNA of the pea aphid (Acyrthosiphon pisum) through PCR using specific gene primers. Sequence was in silico characterized by using EXPASY, Berkeley Drosophila Genome Project (BDGP) Neural Network Promoter Prediction, BioEdit, Mega7, ProtParam, Phyre server, 3D LigandSite SMART, MEME and GSDS programs, available online. RESULTS: BLASTp analysis revealed that the sequenced gene was identical (100%) to the sequence from Acyrthosiphon pisum, with 87% identity to Metpolophium dirhodum and 84% identity to Sitobion avenae. Phylogenetically monocot feeders such as M. dirhodum and S. avenae are in a sister taxa to dicot feeders. In silico analysis of the sequence revealed that sheath protein has a molecular weight of 144 kDa and 50% of the protein is composed of only six amino acids, i.e., threonine, serine, aspartic acid, glutamic acid, isoleucine and tyrosine. The computed IP value revealed that sheath protein is acidic in nature. Ligand binding sites for sheath protein were predicted on residues 1123 and 1125 (isoleucine and glutamine, respectively). Metallic heterogens are also present in sheath protein that are iron, zinc and magnesium, respectively. CONCLUSION: It is conceivable that variation in the salivary gene sequences may reveal important biological information of relevance to the insect-plant interaction. Further exploration of insect salivary proteins, their composition and structure will provide powerful information, especially when these proteins are interacting with plant proteins, and specific information about the sheath protein, which is interacting with plants at a molecular/cellular level, will be important to progress strategies aimed specifically against sucking pests such as aphids.

Field evaluation ratified by transcript and computational analyses unveils myco-protective role of SUGARWIN proteins in sugarcane.

Nine elite sugarcane genotypes (SPF-234, CPF-246, CPF-247, CPF-248, HSF-240, CP-77-400, S-2006-US-658, S-2003-US-127 and S-2006-US-633) were assessed for field level tolerance against Colletotrichum falcatum followed by quantitative expression and computational analyses of mycoprotective proteins. Plug inoculation method was used to assess level of tolerance of aforementioned genotypes while growing in the field. Genotype S-2006-US-658 was categorized as resistant whereas genotypes CPF-246, CPF-248, HSF-240, S-2003-US-127, S-2006-US-633 and CP-77-400 were categorized as moderately resistant and genotypes SPF-234, CPF-247 as moderately susceptible. Quantitative transcript analyses also revealed that the expression of mycoprotective genes (SUGARWIN1 and SUGARWIN2) was maximum in genotype CPF-246 whereas lowest in genotype SPF-234. Hence these mycoprotective proteins play some critical role in fungal pathogen protection as genotypes with higher expression are more tolerant compared to the genotypes with lower expression of mycoprotective proteins. In-silico interaction of these mycoprotective proteins with chitin, glucan, chitosan and mannan (the core constituents of fungal cell wall) also validated their role in disease susceptibility or resistance. These studies will prove a step forward in understanding mycoprotective proteins and can be employed to develop molecular markers for the selection and screening of red rot resistant sugarcane varieties resulting in enhanced productivity of this valuable cash crop.

Mitochondrial Transcriptome Control and Intercompartment Cross-Talk During Plant Development.

We address here organellar genetic regulation and intercompartment genome coordination. We developed earlier a strategy relying on a tRNA-like shuttle to mediate import of nuclear transgene-encoded custom RNAs into mitochondria in plants. In the present work, we used this strategy to drive trans-cleaving hammerhead ribozymes into the organelles, to knock down specific mitochondrial RNAs and analyze the regulatory impact. In a similar approach, the tRNA mimic was used to import into mitochondria in Arabidopsis thaliana the orf77, an RNA associated with cytoplasmic male sterility in maize and possessing sequence identities with the atp9 mitochondrial RNA. In both cases, inducible expression of the transgenes allowed to characterise early regulation and signaling responses triggered by these respective manipulations of the organellar transcriptome. The results imply that the mitochondrial transcriptome is tightly controlled by a "buffering" mechanism at the early and intermediate stages of plant development, a control that is released at later stages. On the other hand, high throughput analyses showed that knocking down a specific mitochondrial mRNA triggered a retrograde signaling and an anterograde nuclear transcriptome response involving a series of transcription factor genes and small RNAs. Our results strongly support transcriptome coordination mechanisms within the organelles and between the organelles and the nucleus.

Acquiring control: The evolution of ROS-Induced oxidative stress and redox signaling pathways in plant stress responses.

Reactive oxygen species (ROS) - the byproducts of aerobic metabolism - influence numerous aspects of the plant life cycle and environmental response mechanisms. In plants, ROS act like a double-edged sword; they play multiple beneficial roles at low concentrations, whereas at high concentrations ROS and related redox-active compounds cause cellular damage through oxidative stress. To examine the dual role of ROS as harmful oxidants and/or crucial cellular signals, this review elaborates that (i) how plants sense and respond to ROS in various subcellular organelles and (ii) the dynamics of subsequent ROS-induced signaling processes. The recent understanding of crosstalk between various cellular compartments in mediating their redox state spatially and temporally is discussed. Emphasis on the beneficial effects of ROS in maintaining cellular energy homeostasis, regulating diverse cellular functions, and activating acclimation responses in plants exposed to abiotic and biotic stresses are described. The comprehensive view of cellular ROS dynamics covering the breadth and versatility of ROS will contribute to understanding the complexity of apparently contradictory ROS roles in plant physiological responses in less than optimum environments.

Cytosolic Isocitrate Dehydrogenase from Arabidopsis thaliana Is Regulated by Glutathionylation.

NADP-dependent (Nicotinamide Adénine Dinucléotide Phosphate-dependent) isocitrate dehydrogenases (NADP-ICDH) are metabolic enzymes involved in 2-oxoglutarate biosynthesis, but they also supply cells with NADPH. Different NADP-ICDH genes are found in Arabidopsis among which a single gene encodes for a cytosolic ICDH (cICDH) isoform. Here, we show that cICDH is susceptible to oxidation and that several cysteine (Cys) residues are prone to S-nitrosylation upon nitrosoglutathione (GSNO) treatment. Moreover, we identified a single S-glutathionylated cysteine Cys363 by mass-spectrometry analyses. Modeling analyses suggest that Cys363 is not located in the close proximity of the cICDH active site. In addition, mutation of Cys363 consistently does not modify the activity of cICDH. However, it does affect the sensitivity of the enzyme to GSNO, indicating that S-glutathionylation of Cys363 is involved in the inhibition of cICDH activity upon GSNO treatments. We also show that glutaredoxin are able to rescue the GSNO-dependent inhibition of cICDH activity, suggesting that they act as a deglutathionylation system in vitro. The glutaredoxin system, conversely to the thioredoxin system, is able to remove S-nitrosothiol adducts from cICDH. Finally, NADP-ICDH activities were decreased both in a catalase2 mutant and in mutants affected in thiol reduction systems, suggesting a role of the thiol reduction systems to protect NADP-ICDH activities in planta. In line with our observations in Arabidopsis, we found that the human recombinant NADP-ICDH activity is also sensitive to oxidation in vitro, suggesting that this redox mechanism might be shared by other ICDH isoforms.

Self-protection of cytosolic malate dehydrogenase against oxidative stress in Arabidopsis.

Plant malate dehydrogenase (MDH) isoforms are found in different cell compartments and function in key metabolic pathways. It is well known that the chloroplastic NADP-dependent MDH activities are strictly redox regulated and controlled by light. However, redox dependence of other NAD-dependent MDH isoforms have been less studied. Here, we show by in vitro biochemical characterization that the major cytosolic MDH isoform (cytMDH1) is sensitive to H2O2 through sulfur oxidation of cysteines and methionines. CytMDH1 oxidation affects the kinetics, secondary structure, and thermodynamic stability of cytMDH1. Moreover, MS analyses and comparison of crystal structures between the reduced and H2O2-treated cytMDH1 further show that thioredoxin-reversible homodimerization of cytMDH1 through Cys330 disulfide formation protects the protein from overoxidation. Consistently, we found that cytosolic thioredoxins interact specifically with cytMDH in a yeast two-hybrid system. Importantly, we also show that cytosolic and chloroplastic, but not mitochondrial NAD-MDH activities are sensitive to H2O2 stress in Arabidopsis. NAD-MDH activities decreased both in a catalase2 mutant and in an NADP-thioredoxin reductase mutant, emphasizing the importance of the thioredoxin-reducing system to protect MDH from oxidation in vivo. We propose that the redox switch of the MDH activity contributes to adapt the cell metabolism to environmental constraints.

The Reverse Transcriptase/RNA Maturase Protein MatR Is Required for the Splicing of Various Group II Introns in Brassicaceae Mitochondria.

Group II introns are large catalytic RNAs that are ancestrally related to nuclear spliceosomal introns. Sequences corresponding to group II RNAs are found in many prokaryotes and are particularly prevalent within plants organellar genomes. Proteins encoded within the introns themselves (maturases) facilitate the splicing of their own host pre-RNAs. Mitochondrial introns in plants have diverged considerably in sequence and have lost their maturases. In angiosperms, only a single maturase has been retained in the mitochondrial DNA: the matR gene found within NADH dehydrogenase 1 (nad1) intron 4. Its conservation across land plants and RNA editing events, which restore conserved amino acids, indicates that matR encodes a functional protein. However, the biological role of MatR remains unclear. Here, we performed an in vivo investigation of the roles of MatR in Brassicaceae. Directed knockdown of matR expression via synthetically designed ribozymes altered the processing of various introns, including nad1 i4. Pull-down experiments further indicated that MatR is associated with nad1 i4 and several other intron-containing pre-mRNAs. MatR may thus represent an intermediate link in the gradual evolutionary transition from the intron-specific maturases in bacteria into their versatile spliceosomal descendants in the nucleus. The similarity between maturases and the core spliceosomal Prp8 protein further supports this intriguing theory.

Mitochondrial targeting of catalytic RNAs.

Genetic transformation of mitochondria in multicellular eukaryotes has remained inaccessible, hindering fundamental investigations and applications to gene therapy or biotechnology. In this context, we have developed a strategy to target nuclear transgene-encoded RNAs into mitochondria in plants. We describe here mitochondrial targeting of trans-cleaving ribozymes destined to knockdown organelle RNAs for regulation studies and inverse genetics and biotechnological purposes. The design and functional assessment of chimeric RNAs combining the ribozyme and the mitochondrial shuttle are detailed, followed by all procedures to prepare constructs for in vivo expression, generate stable plant transformants, and establish target RNA knockdown in mitochondria.