Light microscopic and ultrastructural studies on the enteric nerve plexuses of the domestic fowl

1. The aim of the thesis was to contribute new knowledge on the intestinal nerve plexuses of birds using the domestic fowl (Gallus gallus) as the subject.2. The literature on the histology of the intestinal nerve plexuses was analysed and the gaps in our present knowledge of the structure of the plexuses were outlined.3. The detailed objectives were: (a) to establish the appearance and distribution of the enteric plexuses using both histochemical and empirical staining methods; (b) to provide quantitative data on the myenteric plexus by estimating the number and size of the perikarya; (c) to provide information on the fine structure of the myenteric and submucosal plexuses; (d) to interpret the findings in the light of the available information on intestinal motility in birds.4. The appearance and distribution of the nerve plexuses was investigated in male and female, immature and adult birds, by means of the cholinesterase and glyoxylic acid fluorescence histochemical methods and the osmic acid and silver empirical methods. The nervous tissue was examined in strip preparations, whole mount stretch preparations and frozen sections.(a) Cholinesterase-positive and fluorescent fibres were distributed at all levels of the intestines as myenteric, submucosal, muscle, mucosal and perivascular plexuses. The nerve cell bodies were restricted to the myenteric and submucosal plexuses and were mainly cholinesterase-positive. None of the perikarya was fluorescent. Treatment with reserpine, nialamide and L-DOPA suggested that the fluorescent fibres were probably adrenergic. The density of innervation varied at different levels of the intestinal tract and was best developed in the rectum.(b) The myenteric plexus remained attached to the longitudinal muscle layer and consisted of a primary meshwork of relatively thick nerve bundles within which was a secondary meshwork of finer nerve bundles. The appearance of the myenteric plexus varied along the intestines, the primary meshwork being best developed in the rectum. The perikarya occurred mainly in well-defined ganglia at the nodes of the plexus, a small number of cells occurring in the internodal nerve bundles and the nodes of the secondary meshwork. The majority of the fluorescent fibres in the nodes were strongly fluorescent and varicose, whereas in the internodal bundles most of the fibres were weakly fluorescent and non-varicose. Pretreatment with NADH-Nitro BT to stain the nerve cell bodies showed that the strongly fluorescent varicose fibres formed dense pericellular networks around the majority of the ganglion cells.(c) The position of the submucosal plexus varied in the different regions of the intestines. In the small intestine the plexus lay close to the inner surface of the circular muscle layer, whereas in the rectum and caeca the plexus was situated deeply within the submucosa. The appearance of the submucosal plexus also varied in the different parts of the intestines. Thus, in the small intestine and rectum the plexus was arranged in one plane, whilst in the caecum it consisted of outer and inner parts. The nerve cell bodies occurred in both the ganglia and internodal bundles, but in the small intestine the perikarya were almost equally distributed between the nodal and internodal regions. Many fluorescent varicose fibres surrounded the non-fluorescent ganglion cells. The number of the internodal varicosities in the submucosal plexus appeared to be far less than in the myenteric plexus.(d) The circular muscle layer, especially in the rectum, contained a substantial number of cholinesterase-positive and fluorescent fibres. The longitudinal layer of muscle was sparsely innervated except in the rectum. The fluorescent fibres in the longitudinal muscle layer of the small intestine and caeca were associated with blood vessels.(e) The mucous membrane was innervated by fine cholinesterasepositive and fluorescent nerve bundles from the submucosal plexus. These nerve fibres formed dense meshworks beneath the intestinal glands and within the villi. None of the fibres entered the epithelium. The muscularis mucosae was sparsely innervated.(f) The intestinal arteries were accompanied by thick anastomosing bundles of cholinesterase-positive fibres. A few nerve cell bodies occurred along the course of the periarterial nerves. Thick bundles of non-varicose fluorescent fibres also ran close to the arteries and gave off fine strongly fluorescent varicose fibres which entered the arterial wall. The intestinal veins were sparsely innervated.(g) With the empirical staining methods the appearance and distribution of the enteric plexuses was essentially similar to that demonstrated by the histochemical methods. A wide variation in the staining reactions of the enteric perikarya with the silver technique was observed, argyrophobic and argyrophilic multipolar neurons and argyrophobic unipolar neurons being demonstrated. The argyrophilic nerve cell bodies corresponded to Dogiel's type I, II and III neurons.(h) These observations were discussed in the light of the available histological evidence of the innervation of the gut in birds and other classes of vertebrates.5. The number and size of the perikarya in the myenteric plexus of three immature and three mature birds was estimated in strip and whole mount stretch preparations using the histochemical technique for detecting NADH-diaphorase activity. (a) In the chicks and adults the mean neuron density per cm and the total number of the cells in each region increased distally. The difference between the counts in adjacent regions were generally 2 significant. With age the neuron density per cm decreased and the absolute number of neurons increased. The mean neuron density in each region in the chick was two to three times higher than in the 2 adult. The neuron density per cm was significantly greater in the mesenteric zone of the plexus. The calculated total number of cells in the adult was significantly higher than in the chick. (b) The size of the neurons varied in the different regions of the intestines and increased with age. In both the chick and adult the largest neurons were present in the distal part of the caecum. 0 Small-sized neurons were present in the chick and adult although they were especially numerous in the chick. (c) The differences in neuron density and estimated cell sizes between the chicks and adults were discussed and compared with similar data in other vertebrates.6. The ultrastructure of the myenteric and submucosal plexuses was investigated in male and female, immature and adult birds. (a) The ganglia consisted of a dense neuropil consisting of nerve cell bodies, myelinated and unmyelinated axons, Schwann cells and satellite cells. At the outside of the ganglia was a basal lamina and dense connective tissue containing fibroblasts, interstitial cells and blood vessels. Whilst most of the nerve cell bodies were covered by satellite cells, a part of some of them lay directly under the basal lamina; (b) The perikarya displayed the basic structural features of nerve cell bodies. The majority of them had a small number of randomlydistributed granular vesicles. (c) Small and large axon profiles were identified. Small axon profiles contained mainly microtubules and neurofilaments, whilst larger profiles contained mainly granular and agranular vesicles. Three types of varicosity were described. One type of varicosity contained numerous small agranular vesicles which were sometimes intermingled with medium-sized granular vesicles. This axon profile was probably cholinergic. A second type of varicosity contained small granular vesicles and small agranular vesicles and was probably adrenergic. The third type of axon profile contained numerous small agranular vesicles, many large granular vesicles and a few small granular vesicles. The possibility was considered that this type of varicosity was adrenergic. All three types of varicosity formed typical motor synapses with the neurons. At the synaptic junction only agranular vesicles were associated with the presynaptic membrane of the axon. (d) The structure of the Schwann cells and satellite cells was essentially similar. The perikarya of the Schwann cells gave rise to long, attenuated processes which ensheathed many axons. Structurally, the interstitial cells resembled fibroblasts. (e) The findings were discussed in relation to the available ultrastructural information in other classes of vertebrates.7. The difficulties in interpreting the present observations in the light of the available information on intestinal motility were outlined. The findings emphasized the urgent need for electro physiological studies on the avian enteric plexuses

Thermal Performance of a High-Rise Residential Building with Internal Courtyard in Tropical Climate

Natural ventilation is an effectual passive design approach to create a better indoor thermal condition as well as energy efficiency. The primary goal of building design is providing a healthy and comfortable indoor environment titled as sustainable architecture.  Literature suggests that the significant feature that alteration has to take place on for better energy performance is the envelope design. This paper aims to augment the Window to Wall Ratio (WWR), orientation and courtyard corridor size for improving the design of naturally ventilated courtyard high-rise residential buildings. Briefly, the findings indicate that contending with WWR, orientation and courtyard corridor size could increase the potential of improving its natural ventilation and thus, thermal performance

Linear and Quadratic GUP, Liouville Theorem, Cosmological Constant, and Brick Wall Entropy

Motivated by the works on Equivalence Principle in the context of linear Generalized Uncertainty Principle and, independently, in the context of quadratic Generalized Uncertainty Principle, we expand these endeavors in the context of Generalized Uncertainty Principle when both linear and quadratic terms in momentum are include. We demonstrate how the definitions of equations of motion change upon that expansion. We also show how to obtain an analogue of Liouville theorem in the presence of linear and quadratic Generalized Uncertainty Principle. We employ the corresponding modified invariant unit volume of phase space to discuss the resulting density of states, the problem of cosmological constant, the black body radiation in curved spacetime, the concurrent energy and consequent no Brick Wall entropy.Comment: v1: 10 pages, RevTex, 7 figures; v2: references updated, one footnote added; v3: two footnotes and references added, no change in physics, to appear in EPJ

Leveraging FAERS and Big Data Analytics with Machine Learning for Advanced Healthcare Solutions

This research study explores the potential of leveraging the FDA Adverse Event Reporting System (FAERS), combined with big data analytics and machine learning techniques, to enhance healthcare solutions. FAERS serves as a comprehensive database maintained by the U.S. Food and Drug Administration (FDA), encompassing reports of adverse events, medication errors, and product quality issues associated with diverse drugs and therapeutic interventions.By harnessing the power of big data analytics applied to the vast information within FAERS, healthcare professionals and researchers gain valuable insights into drug safety, discover potential adverse reactions, and uncover patterns that may not have been discernible through traditional methods. Particularly, machine learning plays a pivotal role in processing and analyzing this extensive dataset, enabling the extraction of meaningful patterns and prediction of adverse events.The findings of this study demonstrate various ways in which FAERS, big data analytics, and machine learning can be leveraged to provide advanced healthcare solutions. Machine learning algorithms trained on FAERS data can effectively identify early signals of adverse events associated with specific drugs or treatments, allowing for prompt detection and appropriate actions.Big data analytics applied to FAERS data facilitate pharmacovigilance and drug safety monitoring. Machine learning models automatically classify and analyze adverse event reports, efficiently flagging potential safety concerns and identifying emerging trends.The integration of FAERS data with big data analytics and machine learning enables signal detection and causality assessment. This approach aids in the identification of signals that suggest a causal relationship between drugs and adverse events, thereby enhancing the assessment of drug safety.By analyzing FAERS data in conjunction with patient-specific information, machine learning models can assist in identifying patient subgroups that are more susceptible to adverse events. This information is instrumental in personalizing treatment plans and optimizing medication choices, ultimately leading to improved patient outcomes.The combination of FAERS data with other biomedical information offers insights into potential new uses or indications for existing drugs. Machine learning algorithms analyze the integrated data, identifying patterns and making predictions about the efficacy and safety of repurposing existing drugs for new applications.The implementation of FAERS, big data analytics, and machine learning in advanced healthcare solutions necessitates meticulous consideration of data privacy, security, and ethical implications. Safeguarding patient privacy and ensuring responsible data use through anonymization techniques and appropriate data governance are paramount.The integration of FAERS, big data analytics, and machine learning holds immense potential in advancing healthcare solutions, enhancing patient safety, and optimizing medical interventions. The findings of this study demonstrate the multifaceted benefits that can be derived from leveraging these technologies, paving the way for a more efficient and effective healthcare ecosystem

Empirical Equations for Analysis of Two-Way Reinforced Concrete Slabs

There are many different methods for analysis of two-way reinforced concrete slabs. The most efficient methods depend on using certain factors given in different codes of reinforced concrete design. The other ways of analysis of two-way slabs are the direct design method and the equivalent frame method. But these methods usually need a long time for analysis of the slabs.In this paper, a new simple method has been developed to analyze the two-way slabs by using simple empirical formulae, and the results of final analysis of some examples have been compared with other different methods given in different codes of practice.The comparison proof that this simple proposed method gives good results and it can be used in analysis of two-way slabs instead of other methods

Improving Patient Care with Machine Learning: A Game-Changer for Healthcare

Machine learning has revolutionized the field of healthcare by offering tremendous potential to improve patient care across various domains. This research study aimed to explore the impact of machine learning in healthcare and identify key findings in several areas.Machine learning algorithms demonstrated the ability to detect diseases at an early stage and facilitate accurate diagnoses by analyzing extensive medical data, including patient records, lab results, imaging scans, and genetic information. This capability holds the potential to improve patient outcomes and increase survival rates.The study highlighted that machine learning can generate personalized treatment plans by analyzing individual patient data, considering factors such as medical history, genetic information, and treatment outcomes. This personalized approach enhances treatment effectiveness, reduces adverse events, and contributes to improved patient outcomes.Predictive analytics utilizing machine learning techniques showed promise in patient monitoring by leveraging real-time data such as vital signs, physiological information, and electronic health records. By providing early warnings, healthcare providers can proactively intervene, preventing adverse events and enhancing patient safety.Machine learning played a significant role in precision medicine and drug discovery. By analyzing vast biomedical datasets, including genomics, proteomics, and clinical trial information, machine learning algorithms identified novel drug targets, predicted drug efficacy and toxicity, and optimized treatment regimens. This accelerated drug discovery process holds the potential to provide more effective and personalized treatment options.The study also emphasized the value of machine learning in pharmacovigilance and adverse event detection. By analyzing the FDA Adverse Event Reporting System (FAERS) big data, machine learning algorithms uncovered hidden associations between drugs, medical products, and adverse events, aiding in early detection and monitoring of drug-related safety issues. This finding contributes to improved patient safety and reduced occurrences of adverse events.The research demonstrated the remarkable potential of machine learning in medical imaging analysis. Deep learning algorithms trained on large datasets were able to detect abnormalities in various medical images, facilitating faster and more accurate diagnoses. This technology reduces human error and ultimately leads to improved patient outcomes.While machine learning offers immense benefits, ethical considerations such as patient privacy, algorithm bias, and transparency must be addressed for responsible implementation. Healthcare professionals should remain central to decision-making processes, utilizing machine learning as a tool to enhance their expertise rather than replace it. This study showcases the transformative potential of machine learning in revolutionizing healthcare and improving patient care

Data management, communication systems and the edge: Challenges for the future of transportation

Edge cloud systems have emerged as a new promising alternative to address the needs of many emerging latency-critical applicationssuch as autonomous vehicles. These applications are ill-suited for traditional clouds due to the end-to-end latency and the limited bandwidth between the cloud\u27s (few) data centers and these applications.In the edge cloud model, a myriad of small-scale computing clusters are brought next to the applications at the edge of the network. Many Applicationsin transportation engineering such as autonomous vehicle collision avoidance, and fleet management, requiring more global decision making for safety and correctness of operation, can thus make use of edge cloud systems, offloading their computations to these edge clusters.The edge can then analyze data from these vehicles to optimize the traffic flow, reduce accidents, and provide transportation systems with moreautonomy. The idea of edge computing today forms a cornerstone in the design of many future systems, including, 5G networks and autonomousvehicles, among many others

Preparation, Characterization, and Analytical Application of Ramipril Membrane-Based Ion-Selective Electrode

The fabrication and electrochemical evaluation of two PVC membrane-based Ion-Selective electrodes responsive for ramipril drug have been proposed. The sensitive membranes were prepared using ramipril-phosphomolibdate and ramipril-tetraphenylborate ion-pair complexes as electroactive sensing materials in plasticized PVC support. The electrodes based on these materials provide near-Nernestian response (sensitivity of 53 ± 0.5–54 ± 0.5 mV/concentration decade) covering the concentration range of 1.0 × 10−2–1.0 × 10−5 mol L−1 with a detection limit of 3.0 × 10−6–4.0 × 10−6 mol L−1. The suggested electrodes have been successfully used in the determination of ramipril drug in some pharmaceutical formulations using direct potentiometry with average recovery of >96% and mean standard deviation of <3% (n = 5)