Organs Of Human Body Research Articles

AYURVEDIC MANAGEMENT OF SWITRA ROGA: A CASE STUDY

Skin is the largest organ of human body. Skin complaints affect people of all ages from the neonate to the elderly and cause harm in a number of ways such as discomfort, disfigurement, disability and even death rarely. Vitiligo is the condition presenting with whitish discoloration of the skin. It is an acquired condition in which circumscribed de-pigmented patches can be seen. The destruction of melanocytes, pigment forming cells, causes lack of melanin, coloring pigment which leads to this condition. It affects 1-2% of the population worldwide. Onset is usually in the childhood and females are mostly affected. In Ayurveda, the science of life, the disease called “switra” can be correlated to vitiligo. Aim of the present study is to evaluate the action of Ayurvedic medications on switra roga. Here, am presenting a case of 5 years old girl who came to OPD with c/o white patches over left side of the face. A notable improvement in the condition has been observed in this case. Keywords: Switra roga, Vitiligo, twak vikara.

An Efficient Emergency Patient Monitoring Based on Mobile Ad Hoc Networks

Medical sensors are implanted within the vital organs of human body to record and monitor the vital signs of pulse rate, heartbeat, electrocardiogram, body mass index, temperature, blood pressure, etc. to ensure their effective functioning. These are monitored to detect patient’s health from anywhere and at any time. The Wireless Sensor Networks are embedded in the form of Body Area Nets and are capable of sensing and storing the information on a digital device. Later this information could be inspected or even sent to a remotely located storage device specifically (server or any public or private cloud for analysis) so that a medical doctor can diagnose the present medical condition of a person or a patient. Such a facility would be of immense help in the event of an emergency such as a sudden disaster or natural calamity where communication is damaged, and the potential sources become inaccessible. The aim of this paper is to create a mobile platform using Mobile Ad hoc Network to support healthcare connectivity and treatment in emergency situations.

Guest Editorial: Special Section on New Trends in Parallel and Distributed Computing for Human Sensible Applications

The papers in this special section focus on collecting high-quality scientific contributions from the research community working in the fields of parallel and distributed computing, data analytics algorithms and big data frameworks, application specific processing. Specifically, the main focus is on emerging new computing trends that affect the concrete human life, the so-called “Human Sensible Applications”. Problems in parallel computing related to implement precision medicine and novel therapeutical targets, real-time architectures for biomedical IoT, computational biology and chemical compounds simulations, realistic modelling of human body organs, bioimaging processing, but even emerging computing systems for Human Sustainability, including weather and climate changes monitoring/prediction, resources management, safety, disaster prediction and prevention, belong to this scenario.

A Modified Exact Reconstruction Algorithm to Determine the Complex Permittivity Perturbations of a Cancer Affected Biological Target using Microwave Tomography Technique

Microwave Tomography Technique (MTT) is an emerging technology that is showing its effectiveness in detecting Cancer at early stage. Due to absolute random and non-deterministic characteristics of Cancer cells, more advancements are required in MTT to accurately detect the presence as well as the location of the affected region. Considering this fundamental issue, in this paper, we have proposed a modified Exact Reconstruction Algorithm (mERA) which is capable enough to provide a detailed analysis of all kinds of complex dielectric perturbations of a cancer affected biological target. In MTT, the detection of presence of a cancerous tumor inside any organ of human body has been done using different image reconstruction algorithms. On the other hand, this algorithm uses a selective data segregation mechanism to generate the perturbed complex cell permittivities of the affected organ tissues. Through this study, it has also been verified that how efficiently our proposed approach can able to detect all types of dielectric variations that may be large (20%), small (5%), positive or may be negative and even in a mixed kind of scenario where affected cells possess the mixture of all types of perturbations simultaneously. As cancerous cell shows peculiar behaviour inside human body and its nature varies from person to person and even in-between different stages (stage 1, stage 2, stage 3, stage 4) of cancer, the algorithm is designed in such a fashion that it can able to detect the presence of tumor considering all such possibilities into account. The results validate its high accuracy and effectiveness in the field of cancer diagnosis.

Electrospinning and Electrospraying with Cells for Applications in Biomanufacturing

Biomanufacturing of cell-laden scaffolds with biomimetic cell-scaffold organizations resembling the structures and anatomy of human body tissues and organs holds great promise in tissue engineering and regenerative medicine. In human body tissues and organs, specific types of cells are supported by nanofibrous extracellular matrix (ECM) in well-defined three-dimensional (3D) manners. Electrospinning is a facile and effective technique for producing nanofibrous scaffolds, which exhibit high similarities in the structure compared to ECM that offers structural and mechanical supports to cells in the human body. The incorporation within the electrospun nanofibrous scaffolds has therefore been considered as a promising approach for biomanufacturing of cell-laden scaffolds with tissue-mimicking structures. However, limited by low controllability of conventional cell seeding strategies and small sizes of interconnected pores of normal electrospun scaffolds, it is highly difficult to incorporate living cells within electrospun scaffolds on demand and results in cell-laden scaffolds with desirable 3D cell-scaffold organization. With recent advances in electrospinning and electrospraying with cells, it is visible to directly incorporate living cells within scaffolds via cell microencapsulation approaches and therefore offer promising alternatives for biomanufacturing of cell-laden scaffolds with tissue-mimicking structures. In this review, we will summarize the applications and challenges of cell seeding strategies and cell microencapsulation technologies for incorporating cells within electrospun scaffolds. Some techniques with high potentials to be integrated with electrospinning for forming the cell-laden scaffolds in continuous and noncontact manners, including aerodynamic-assisted cell microencapsulation, hydrodynamic-assisted cell microencapsulation and electrohydrodynamic-assisted cell microencapsulation (i.e., cell electrospinning and cell electrospraying), are highlighted. In particular, the cell microencapsulation and the subsequent formation of cell-laden scaffolds directly by electrospinning and electrospraying with living cells are overviewed in a detailed manner. Finally, the perspective and challenges of electrospinning and electrospraying with cells for biomanufacturing of cell-laden scaffolds with tissue-mimicking structures are discussed.

Deep learning based chronic kidney disease detection through iris

Kidney is an important organ in human body as it maintains the nutrients and fluid balance in our body. It is extremely beneficial if its dysfunctionality is diagnosed at an early stage. Iridology provides a pathway to examine the kidney disease through iris images. Therefore, in this work we proposed the Iris-based Kidney Disease Identification System (IKDIS). The IKDIS would aid in identifying abnormalities through iris images an input which would be followed by application of deep neural network model for assessment. This type of diagnostic system without involving any instruments for assessment of human body organs is much popular these days. The data of 49 patients gives promising results of IKDIS, achieving overall accuracy of 86.9% during the experiment.

Notice of Retraction: Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning

The liver is a vital human body organ and its functionality can be degraded by several diseases such as hepatitis, fatty liver disease, and liver cancer and so forth. Hence, the early diagnosis of liver diseases is extremely crucial for saving human lives. With the rapid development of multimedia technology, it is now possible to design and implement a non-invasive system that can chronic liver diseases. For this purpose, machine learning and Artificial Intelligence (AI) have been used within the past few years. In this regard, digital image processing supported by AI methods has been implemented in the diagnosis of diseases that also showed high reliability. Therefore, in this paper, an iris feature-based non-invasive technique is proposed by incorporating a novel machine-learning algorithm. The experimental setup involved data set for the models' training included 879 subjects from Pakistan, of which 453 subjects have chronic liver disease and 426 are healthy. The iris images were collected using an infrared camera that consists of a lens, a thermal sensor and digital electronics processing. The lens focuses on the infrared energy on the sensor, using distinctive forms of features twenty-two physiological and thirty-three iris features. The designed classification model for a non-invasive system combined eleven different classifiers and used cross-validation techniques for comparing the results. The overall performance of the model was analyzed using five parameters: accuracy, precision, F-score, specificity, and sensitivity. The results confirmed that the proposed non-invasive model is capable of predicting chronic liver diseases with 98% of accuracy.

CRITICAL ANALYSIS OF CHAKSHUSHYA DRAVYAS AND ITS CLINICAL APPLICATIONS WITH SPECIAL REFERENCE TO SUSHRUTA SAMHITA

Netra is considered as one of the very important organs in human body. Chakshushya dravyas are the materials which are believed to be beneficial for eyes, henceforth usages of those Dravyas are recommended in various contexts of Sushruta Samhita. In the light of this knowledge and based on Rasadi gunas of Chakshushya dravyas explained in Ayurveda, a critical analysis of those dravyas is done to find out the logic behind the labelling of ‘Chakshushya dravyas’. Triphala, Ksheera, Madhu, Ghrita, Prapaundarika, Saindhava, Yava, Shatavari, Mudga, Jeevanti, Patola are critically analyzed. Even though most of the Chakshushya dravyas are predominantly Madhura rasa dravyas, there are dravyas that are Katu and Kashaya rasa predominant which are seldom told as Chakshushya. Tikta rasa is not considered as Chakshushya but some of the Chakshushya dravyas are Tikta rasa Pradhana. Majority of Chakshushya dravyas possess Rasayana, Brimhana, or Vrishya properties and all of them are not directly contributing to vision. There are ‘Chakshushya Rasayana’ dravyas i.e., dravyas which directly enhances the vision and other dravyas which pacifies the underlying diseases of eye and prevent the secondary manifestations.

ResNet-50 vs VGG-19 vs training from scratch: A comparative analysis of the segmentation and classification of Pneumonia from chest X-ray images

In medical imaging, segmentation plays a vital role towards the interpretation of X-ray images where salient features are extracted with the help of image segmentation. Without undergoing surgery, clinicians employ various modalities ranging from X-rays and CT-Scans to ultrasonography, and other imaging techniques to visualise and examine interior human body organ and structures. To ensure appropriate convergence, training a deep convolutional neural network (CNN) from scratch is tough since it requires more computational time, a big amount of labelled training data and a considerable degree of experience. Fine-tuning a CNN that has been pre-trained using, for instance, a huge set of labelled medical datasets, is a viable alternative. In this paper, a comparative study was done using pre-trained models such as VGG-19 and ResNet-50 as against training from scratch. To reduce overfitting, data augmentation and dropout regularization was used. With a recall of 92.03%, our analysis showed that the pre-trained models with proper finetuning was comparable with Iyke-Net, a CNN trained from scratch.

ANATOMY DESCRIBED IN AYURVEDA AND MODERN SCIENCE: A REVIEW ARTICLE

Anatomy is broadly appreciated as being one of the cornerstones of medical education. If we go through the his- tory of human anatomy, it seems that the anatomy of modern times is well recognized from the days of the re- naissance that is from the 15th century. Medical Science was one area where surprising advances had been made in ancient times in India. Specifically, these advances were in the areas of human dissection, embryology, plastic surgery, extraction of cataracts, description of Asthi, Sandhi, Peshi, Snayu, Marma And Pramana Sharira etc. These do not just claim. There is documentary evidence to prove the existence of these practices. Acharya Sushruta has paid great should start his surgical carrier unless he is well aware of human anatomy. Acharya Charaka also studied the anatomy of the human body and various organs. He also described the number of mus- cles joints etc., in the human body. The object of the present study is to trace out the most significant and valua- ble hidden treasures of anatomy practised in the past by Acharya and its review in Modern science. Keywords: Asthi, Sandhi, Plastic surgery, Snayu Marma

Analysis of performance metrics of heart failured patients using Python and machine learning algorithms

Heart is one of the most important organs in Human's body. In life, some changes may happen that may bring various diseases like, blood pressure, sugar, etc. Similarly, heart failure is also a dreadful disease. Heart failure is a serious condition and there is no cure for this disease. It is a situation in which the patient's heart is not pumping the blood well as the normal heart pumps. Heart Failure prediction is a complex task in the medical field. The rates of heart failure have been increasing day by day as the rate of population is also increasing day by day. This paper aims at analyzing the machine learning algorithms based on the percentage of various performance metrics (such as, Accuracy, Precision and Recall). The machine learning methodology is proposed. The most suitable algorithm for each metrics is predicted. It is analyzed using the specific variables in the dataset by using the python programming as well as different supervised machine learning algorithms which include, Decision Tree, Logistic Regression, KNN and Random Forest. Anaconda jupyter notebook is used for implementing python scripting.

Cutaneous Wound Healing: An Update from Physiopathology to Current Therapies.

The skin is the biggest organ of human body which acts as a protective barrier against deleterious agents. When this barrier is damaged, the organism promotes the healing process with several molecular and cellular mechanisms, in order to restore the physiological structure of the skin. The physiological control of wound healing depends on the correct balance among its different mechanisms. Any disruption in the balance of these mechanisms can lead to problems and delay in wound healing. The impairment of wound healing is linked to underlying factors as well as aging, nutrition, hypoxia, stress, infections, drugs, genetics, and chronic diseases. Over the years, numerous studies have been conducted to discover the correct approach and best therapies for wound healing, including surgical procedures and non-surgical treatments such as topical formulations, dressings, or skin substitutes. Thus, this general approach is necessary to facilitate the direction of further studies. This work provides updated concepts of physiological mechanisms, the factors that can interfere, and updated treatments used in skin wound healing.

Mir-140 and Mir-34a as Molecular Markers for Apoptotic Brain in Sunset Yellow and Carmoisine Intoxicated Mice

Brain is the central organ in human body, that is working 24hr/7days even before we leave our mother`s womb. None surprising that care should be paid for the food consumed that consequently affecting brain environment, neurotransmitters as well as oxidative state. Carmoisine (Car) and sunset yellow (SY) are synthetic food additives extensively utilized during food processing and subsequently affecting brain health. The apoptotic effect underling the behavioral changes after oral consumption of either Car or SY remains not fully understudied. Respective biochemical and molecular biological parameters by means of one fifty adult male mice were conducted. The study extended for 3 months on 5 different groups with ten mice each; Group 1 was utilized as the control group, group 2 was treated with the acceptable daily intake (ADI) of SY (30 mg/kg BW), group 3 was treated with 10x ADI of SY, group 4 was treated with ADI of Car (4 mg/kg BW) and group 5 was administered 10x ADI of Car; all doses were given orally via gastric lavage. Exposure to higher doses of either SY or Car significantly altered the biochemical parameters; decreased both serotonin and dopamine levels and total antioxidant capacity as well. However, increased the lipid peroxidation marker malonaldehyde (MDA), upregulated the mRNA expression of the pro-apoptotic genes (Fas, Fas-L, Bax and casp3) and down regulated the transcriptional level of the anti-apoptotic gene Bcl2.Moreover upregulated both miR-140 and miR-34a expression levels and consequently down-regulated their target genes NRF-2 and SIRT-1, respectively. So, we can conclude that excessive oral administration of either Car or SY has apoptotic effect and care should be paid with their usage.

Integrated 8 Wisdom Compounds Interaction in Multitasking Healing System: Confinement Energy in 4D Frequency Interconnection

The total energy in multitasking healing system of herbal medicine is extremely important due to an effective recovery of treated cells or organs in human body. This short communication research reports an exact calculation of the total effective mass involve in multitasking healing system of herbal medicine based on a simple smart model from general physics implemented in organic complex compounds found normally in Maluku/ Halmahera Galoba fruits (Zingiberaceae spp.) such as Amomum spp., Hornstedtia spp., Elim alliacea, Etlinger alba (Blume) A.D. Poulsen, et cetera. The invented results shows that the total mass involved in such multitasking healing system is ~24.24% with the total number of on-target atoms of ~93 atoms from 382 total atoms. This finding suggests that the healing time of herbal medicines with multitasking healing system shall be slower that that from FDA pharmaceutical approved products which is one target with ~100% healing system. The value of strong confinement energy in multitasking healing system of such 8 wisdom compounds in herbal medicine based Galoba fruits is about 4 time larger than its weak confinement energy

Harmful Effects of COVID-19 on Major Human Body Organs: A Review

The world experienced the outbreak of a new pandemic disease in 2019, known as coronavirus (CoV) disease 2019 (COVID-19), which is caused by the novel severe acute respiratory syndrome-CoV-2 (SARS-CoV-2). The respiratory system is the organ system most commonly affected by COVID-19; however, several other organ systems have been reported to be affected. The SARS-CoV-2 RNA found in infected stub samples can cause lung contagion by binding to the angiotensin-converting enzyme-2 (ACE-2) receptor of the alveolar epithelial cells. The gut microbiota (GM) promote immunity, indicating that the alignment of the microbiota and corresponding metabolic processes in COVID-19 can help to identify novel biomarkers and new therapeutic targets for this disease. The cause of kidney damage in COVID-19 patients is possibly multifactorial, involving a complex mechanism that involves complement dysregulation and thrombotic microangiopathy, as well as the occurrence of a “cytokine storm” syndrome, which are immune responses that are abandoned and dysfunctional with unfavorable prognosis in severe COVID-19 cases. Furthermore, COVID-19 involves a continuous proliferation and activation of macrophages and lymphocytes. SARS-CoV-2 can also bind to the ACE-2 receptor expressed in the cerebral capillary endothelial cells that can invade the blood-brain wall, to penetrate the brain parenchyma. However, in the ongoing pandemic, there has been a surge in studies on a wide range of topics, including causes of respiratory failure, asymptomatic patients, intensive care patients, and survivors. This review briefly describes the damaging effects of COVID-19 on vital human organs and the inhibitory function of the ACE-2 receptor on the GM, which causes gut dysbiosis, and thus, this review discusses topics that have an opportunity for further investigation.

Primitive Diabetes Prediction using Machine Learning Models: An Empirical Investigation

Diabetes is a prevalent metabolic disease that causes numerous amounts of death each year. It affects patients of all age groups and huge populations around the world. Early detection would help in early treatment that facilitates the prognosis. Untreated diabetes disturbs the proper functionality of other organs in human body. The contemporary lifestyle has led to unhealthy eating habits causing type 2 diabetes .Various computational intelligence techniques have been proposed in predicting diabetes based on the historical records of related symptoms. Hence early detection is a significant process to have a healthy life style. Diabetes needs greatest support of machine learning to detect diabetes disease in early stage, since it cannot be cured and also brings great complication to our health system. In this research article, a novel model is generated for prediction of diabetes using Gaussian Naive Bayes (GNB), Random Forest (RF), Support Vector Classifier (SVC) and Multinomial Naive Bayes (MNB) based on the significant attributes, and the relationship of the differing attributes. The computation of the model is simple; hence enabling an efficient process for prediction. Computer simulation experiments is performed by using the diabetes dataset is used to compare the performance of the different models.

Mitochondrial remodelling-a vicious cycle in diabetic complications.

Diabetes mellitus (DM) is a chronic, metabolic condition characterized by excessive blood glucose that causes perturbations in physiological functioning of almost all the organs of human body. This devastating metabolic disease has its implications in cognitive decline, heart damage, renal, retinal and neuronal complications that severely affects quality of life and associated with decreased life expectancy. Mitochondria possess adaptive mechanisms to meet the cellular energy demand and combat cellular stress. In recent years mitochondrial homeostasis has been point of focus where several mechanisms regulating mitochondrial health and function are evaluated. Mitochondrial dynamics plays crucial role in maintaining healthy mitochondria in cell under physiological as well as stress condition. Mitochondrial dynamics and corresponding regulating mechanisms have been implicated in progression of metabolic disorders including diabetes and its complications. In current review we have discussed about role of mitochondrial dynamics under physiological and pathological conditions. Also, modulation of mitochondrial fission and fusion in diabetic complications are described. The available literature supports mitochondrial remodelling as reliable target for diabetic complications.

Effect of Ayurvedic Formulation Orally and Karanj tail locally in the management of Vicharchika WSR to Eczema –A case study.

Skin is the largest and important organ of the body .A number of skin conditions last a long time. some may start in childhood and continue into adulthood.
 In ayurveda the word Kushta is broad term which cover almost all skin disorder.
 Skin is the Largest Organ of Human Body. all the skin diseases in Ayurveda have been
 Classified under the broad heading of” Kushta’ which are furthur Classified in to Mahakushta and Kshudra kushta.
 Vicharchika is defined under kshudra kushta. Vicharchika is kaphapradhan vyadhi it can be correlate with eczema in modern medicine.
 Eczema is a condition where in patches of skin become inflamed,itchy,cracked,and rough.some types can also cause blisters.
 
 . In adults, Eczema appear anywhere, mostly Hand and foot . the affected skin may be blakish ,eruptive .In Ayurvedic terminology symptom of विचर्चिका-
 
 १)सकण्डु पिडका श्यावा बहुस्त्रावा विचर्चिका||
 “च.चि.७/२६,यो.र/भा.प्र.५४/२७
 vicharchika are
 1) Kandu(itching),
 2) Shyavata (blackish discolouration), 3)Pidaka (erruption), 
 4)Bahustrava (disharge),
 5)Ruja(pain),
 6)Rajyo(marked lining due to thickness of lesion),
 7) Rukshata (dryness).
 Chronic skin conditions typically aren’t curable but they can managed using drugs.
 In spite of presence of antibiotic, antihistamines, steroids etc, the skin disorder remains refractory to treatment But Ayurveda is the repository of skin remedies which are therapeutically safe and effectiveness.
 In ayurveda there are various drugs formulation mentioned in samhita which show significant effect on vicharchika.

Metabolic complications of hepatitis C virus infection.

Hepatitis C virus (HCV) infection is a systemic disease that is implicated in multiple extrahepatic organ dysfunction contributing to its protean manifestations. HCV is associated with diverse extrahepatic disorders including atherosclerosis, glucose and lipid metabolic disturbances, alterations in the iron metabolic pathways, and lymphoproliferative diseases over and above the traditional liver manifestations of cirrhosis and hepatocellular carcinoma. The orchestration between HCV major proteins and the liver-muscle-adipose axis, poses a major burden on the global health of human body organs, if not adequately addressed. The close and inseparable associations between chronic HCV infection, metabolic disease, and cardiovascular disorders are specifically important considering the increasing prevalence of obesity and metabolic syndrome, and their economic burden to patients, the healthcare systems, and society. Cellular and molecular mechanisms governing the interplay of these organs and tissues in health and disease are therefore of significant interest. The coexistence of metabolic disorders and chronic hepatitis C infection also enhances the progression to liver fibrosis and hepatocellular carcinoma. The presence of metabolic disorders is believed to influence the chronicity and virulence of HCV leading to liver disease progression. This comprehensive review highlights current knowledge on the metabolic manifestations of hepatitis C and the potential pathways in which these metabolic changes can influence the natural history of the disease.

MULTIDISCIPLINARY APPROACH IN THE PREVENTION AND MANAGEMENT OF OCULAR HEALTH

In today’s era of globalization, prevention plays an important role in the field of health science. Excess us-age of gadgets like use of computers, ipads and smart phones is leading to over functioning of eyes. Eyes are the windows to the mind. among the five sense organs Ayurveda gives prime importance to eyes. Now-a-days changed work expectations requiring prolonged working hours in front of computers, nutritional deficiency, pollution, stress, indiscriminate use of topical ocular drugs and increased incidence of allergic disorders, etc. lead to eye diseases. Suffering from ocular disorders with uncorrected refractive error in children result into adverse effect on quality of life and significantly affect their vision, education and psy-chosocial development. Working in artificial light either dim light or bright light is another culprit for dete-rioration of ocular health so emphasis should be laid on the prevention of these, as eyes are the most im-portant and sensitive of five sense organs in human body. Ayurveda is one of the greatest gifts to mankind. In Ayurveda, selected classical daily regimes like Netraprakshalana (eye wash), Anjana (collyrium), Snana(bath), Padabhyanga (foot massage with oil), Nasya (nasal application of drugs), wholesome and unwholesome dietetics are promoted as high-end measures for the maintenance of eye-health. Various Netravyayamas (eye exercises), Yogasanas, Pranayamas, Neti and Trataka are said to be beneficial for the same cause. The main aim of this review is to promote and spread the awareness about maintenance of oc-ular health and prevention from the earlier causation of ocular diseases.