bluuebunny/crossref_metadata_2025 huggingface dataset:
Organizational Diagnosis Approaches With Non-Profit Organizations
Authors: Baez Maria D.
Published: September 2023

An organizational diagnosis is a vital tool for process improvement in ineffective organizations. It involves thoroughly examining an organization's structure, culture, and systems to identify areas that require improvement. Organizational diagnosis is essential because it helps organizations identify the root causes of their problems and develop practical solutions. By conducting an organizational diagnosis, ineffective organizations can identify areas that require improvement, such as poor communication, inadequate leadership, lack of employee engagement, or outdated technology. Once these areas are identified, the organization can develop an action plan to address the issues and improve its processes. This chapter explores the complex nature of that approach to provide a roadmap for those in the practice world to engage in this process.
A Novel Approach to Identify Leaf Vein Morphology Using Laplacian Filter and Deep Learning for Plant Identification
Authors: Kanjalkar Pramod Madhavrao , Kanjalkar Jyoti , Zagade Atharva Janaba , Talnikar Vedhas
Published: September 2023

Identification of different plants, weeds, or any related type of vegetation is an important aspect of agricultural robotics and technologies. With the help of image processing and computer vision, multiple attempts have been made to achieve these results. These approaches made use of the shape and color of the leaf to identify a particular plant. But it can be observed that this approach has some limitations resulting in false positive and true negative errors. To overcome these limitations, the authors propose a novel approach of using Laplacian filter to extract veins morphology of leaves of a plant. This veins pattern is unique to every plant. With this Laplacian filter and data augmentation techniques, a unique dataset is developed on which a deep learning model can be trained. Based on this approach, the proposed system applies a deep learning algorithm called YOLO for plant identification. After preprocessing and YOLO training, the model is able to distinguish between plant and a weed successfully and create a bounding box for the detected type of plant.
A Privacy-Preserving Untraceable Group Data-Sharing Technique
Authors: Judy Flavia B. , Pavan Kumar D. , Teja R. Varun , Lakshman B.
Published: September 2023

Significant data privacy problems have been raised by adopting cloud computing, which has drawn much attention recently. Meanwhile, system security and cryptography offer a variety of security frameworks for protecting machine learning and maintaining privacy. Especially in the healthcare sector, cloud computing has drastically changed how we store and access data. Cloud computing has benefits but also increases the chance of data breaches and privacy abuses. Privacy protection is essential since using the cloud requires storing sensitive data on distant servers. Encrypting data and limiting access to only those with the necessary authorisation is one method to protect privacy. Data security is essential in the cloud to prevent unauthorised access, manipulation, and loss. Disaster recovery planning and routine backups are two methods we may use to maintain the previous data's security while using the BVK algorithm.
An Enhanced Approach for Multi-Modal Sentimental Analysis in Natural Language Processing
Authors: Vinitha V. , Jayanthi R. , Thirukumaran S. , Vedaiyan Ramchand , Raja G.
Published: September 2023

Sentiment analysis is a common technique in artificial intelligence and natural language processing. The automated assessment of consumer comments on services or products is becoming more prevalent. Multi-modal sentiment analysis has evolved as a fascinating study topic that evaluates and interprets sentiment expressions using several modalities, such as text, pictures, audio, and video. This technique enables a more thorough knowledge of human emotions by capturing the interaction of many modalities. The capacity to assess sentiment across various modalities has several advantages over unimodal techniques. Multi-modal sentiment analysis improves performance by combining text, images, audio, and video information. This allows it to catch complimentary and contextually relevant cues. Improving the performance of multi-modal sentiment analysis covers several processes, including sentiment polarity identification, multi-modal feature extraction, and fusion.
Comparative Study of Cancer Blood Disorder Detection Using Convolutional Neural Networks
Authors: Sujarani Pulla , Yogeshwari M.
Published: September 2023

Blood malignancies and various blood disorders can have an impact on a person. It is a major health issue in all age groups. A blood disorder, such as influence platelets, blood plasma, and white and red blood cells, can impact any of the four primary blood components. The primary goal of this chapter is to detect the cancer blood disorder. This paved the way to propose a comparative study with previous studies based on convolutional neural networks in this work. The authors propose a model for cancer blood disorder detection. It consists of five steps. The blood sample image data set is collected from the Kaggle. First, the data set is transferred for image preprocessing to remove the noise from the images. Next, it is applied to the image enhancement for clarity; the image and segmentation are performed on enhanced images. Next, feature selection is used to extract the features from the segmentation images. The convolutional neural network technique is used for classification finally.
Change Detection in Water Body Areas Through Optimization Algorithm Using High- and Low-Resolution Satellite Images
Authors: Sivasankari A. , Jayalakshmi S. , Booba B.
Published: September 2023

The Earth's surface has changed significantly as a result of human activity on the land expanding agriculture and population. To fulfil the growing demand for fundamental human necessities and wellbeing, it is crucial to have correct information on land use and land cover (LULC) and the best methods of using it. Large geographic regions can be found in sufficient detail in satellite photos, both qualitatively and quantitatively. The most effective methods for detecting together static and dynamic biophysical modules on the Earth's surface, which are regularly introduced for mapping LULC, are satellite depending remote sensing (RS) methods. In order to classify RS images into change/nochange classes, image pre-processing is done in this study, and the information content of the satellite images is assessed. In this work, a change detection method for identifying land cover and water bodies is proposed utilizing a stacked ensemble classifier with mean weight residual neural network (MWResNet) and entropy.
Certificate Authentication and Verification Using Secured Blockchain Approach for Blind People
Authors: Kanjalkar Jyoti P. , Shinde Rutuja , Sharma Tanmay , Tyade Abhishek , Thakur Uma , Kanjalkar Pramod
Published: September 2023

In 2021–2022, 5.57 crore students are expected to enroll in higher education in India, and every year, there will be close to 9 million graduates. According to estimates, there are 0.5 cases of this type of blindness per 1,000 people in India. Many children are blind or have severe visual impairment (SVI) or blindness (BL). Dealing with sight loss or low vision is just one of the difficulties that the visually impaired face in everyday life. There are many challenges in their daily life such as navigating around places, most of the information is inaccessible, finding reading material, etc. They are also facing many challenges in their educational careers as well. If any blind student has graduated and he/she wants to maintain all the original certificates, then it becomes tiresome to track these certificates and manually verify their legitimacy for them. Also, everything needs to be digitized with the principles of confidentiality, reliability, and availability in order to make the data more secure and safe.
Information Design and Unifying Approach for Secured Data Sharing Using Attribute-Based Access Control Mechanisms
Authors: Regin R. , Khanna A. Aakash , Krishnan Vamsi , Gupta Muskan , Rubin Bose S. , Rajest S. Suman
Published: September 2023

In response to the safety concerns surrounding the IoT, an attribute-based encryption and access control scheme (ABE-ACS) has been proposed. This scheme can be more effectively implemented through the use of cutting-edge technology and incorporating attribute-based encryption (ABE) and attribute-based access control (ABAC) models with features as the point of origin. Facing Edge-IoT is a heterogeneous network made up of certain nodes with more powerful computers and the majority of resource-constrained IoT devices. The authors provide a lightweight with an upgrade to the proof-of-work consensus to address the issues of excessive resource consumption and challenging deployment of existing platforms. To protect the confidentiality of the access control policies, the limits of the tree are utilised for transformation and allocation stored. Six smart contracts are created for devices and data to implement the ABAC and punishment mechanism, which outsources ABE to edge nodes for privacy and integrity. Thus, the plan implements device-controlled access and Edge-IoT privacy protection for data.
Shear-Wave Elastography for Metabolic Syndrome Patients' Non-Alcoholic Fatty Liver Disease (NAFLD) Assessment
Authors: Patil Shilpa C. , Mane Makarand B.
Published: September 2023

Hepatic steatosis is defined as the accumulation of fat in hepatocytes, making up more than 5% of the total weight of the liver. The global incidence of obesity and the incidence of steatosis of the liver is increasing simultaneously, which represents the commonest cause of liver disease. In addition to obesity, this liver disease is also closely related to a wide range of metabolic comorbidities such as dyslipidemia, type 2 diabetes, and high blood pressure. Patients with metabolic syndrome (MetS) have a high association with NAFLD (non-alcoholic fatty liver disease). Patients with NAFLD are at greater risk to develop fibrosis/cirrhosis and hepatocellular carcinoma (HCC) which causes great morbidity. The most common form of chronic liver disease worldwide by far is NAFLD. It is estimated that around one-third of the adult population in industrialized nations is affected by it. NAFLD is an asymptomatic condition, reaching advanced stages even before being suspected or diagnosed.
Development of Basic Blocks for Garments Using Anthropometric Data of Pre-teen Girls
Authors: Biney-Aidoo Vivian , Senayah William Kwesi , Kuma-kpobee Mercy , Mahama Sherrifa , Fianu Docea
Published: September 2023

Although sizing is usually established through the development of a size chart, the real elements of fit can only be ascertained after the creation of a garment pattern, based on the measurements of the size chart. Therefore, one of most fundamental stages in the garment manufacturing business is patternmaking. This study developed basic pattern blocks for garment manufacture using anthropometric data of Ghanaian girls (7 to 12 years), measured, and processed into a size chart in a previous study. First of all, the measurements of the size chart were extracted, after which one extra size (GH 6) was created based on the intervals observed between the sizes. Basic pattern blocks were developed and validated by producing trial samples and testing them on a sub-section of the target population. The major contribution of this study is the availability of a variation of ready-made standard garment blocks for use by garment manufacturers, and an enhanced fit of garments produced for the children's wear sector.
Design and Construction of a Drying Chamber for Millinery and Accessories
Authors: Akpoyo Beauty Awusi Nyavor , Asinyo Benjamin Kofi , Danso Daniel Kwabena
Published: September 2023

The study was conducted to design and construct a drying chamber for millinery and accessories production to reduce the risks involved in the old ways of drying hat. The design of the study is descriptive while the population includes fashion schools. The sample size for the study was 100 respondents while a researcher's self-developed questionnaire was used as the instrument for data collection. The blocked hat used the sun drying method, rather than the drying chamber, and considered the drying chamber more effective than sun drying method. The dryer constructed could dry the hats effectively and efficiently.
Fabrication of a Prosthetic Socket for a Transtibial Amputee
Authors: Donkor Evans Kwadwo , Boakye-Yiadom Fredrick , Akinruntan Rex Ifelaja
Published: September 2023

This chapter focused on sculptural fabricated prosthetic socket for a transtibial (below-knee) amputee. As part of this study, an in-depth examination of the special needs for lower limb prostheses with quality and attractiveness was conducted in Sekondi-Takoradi Metropolis. Qualitative inquiry employing studio-based and descriptive research designs was drawn from collecting data from ten (10) purposively selected samples consisting of two (2) Prosthetists, one (1) Orthotist, two (2) Laboratory technicians, one (1) Amputee, one (1) STMA official and three (3) Sculptors. Research instruments comprising personal interviews and direct observations were used for the on-site data collection for the study. Data were analysed using thematic content and input-output transformation model analysis tools. The results revealed that producing a prosthetic socket for the amputee increased the active workforce of the amputee. Prosthetic socket fabrication should be made a course-related programme in the sculpture technology department at Takoradi Technical University together with Supomu-Dunkwa health centre and STMA.
ChatGPT in Academic Writing and Publishing
Authors: Bakla Arif
Published: September 2023

Generative artificial intelligence systems are disruptive technologies that have been found useful in various domains, including academia and education. Being one of these technologies, ChatGPT can have smart conversations with its human users, answer questions and produce content virtually on any topic. Like other conversational agents, ChatGPT has advanced text processing capabilities, such as writing paragraphs, essays, research reports and paraphrasing texts. The use of this technology in academic writing classes and scholarly publications necessitates a discussion of possible problems and challenges that might undermine ethical and responsible use. This is because the ability of this new technology to produce content that sounds like human output has wider ethical implications not only for academic writing and publishing but also for learning and instruction. The issues of concern are related to transparency and credibility of the content, ownership of the text produced and integrity.
Transforming the Language Teaching Experience in the Age of AI
Authors: Satpute Reena Sudhakarrao
Published: September 2023

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, and speech recognition and machine vision. Learning is the core feature that is connected to education. Actually, with AI, we are trying to force machines to imitate human behavior. Education increases the power of visualization and to differentiate between right and wrong. Education these days has become costly for the poor guardians. Education helps realize the real values in relation to social and cultural behavior so that one can become a decent person in nature and in society. The role of technology in modern education helps to look at the current trends and to solve the problems using artificial intelligence in education.
Artificial Intelligence in Computer Science
Authors: Sihare Shyam
Published: September 2023

AI has the potential to revolutionize education by enhancing student performance and delivering tailored learning experiences. This chapter addresses the present state of artificial intelligence (AI) in computer science (CS) education, as well as how it is used to adaptive learning, intelligent learning systems, and automated grading. The authors examine recent studies on the use of AI in CS teaching, emphasizing the relative benefits of various approaches. One of the technology's most important benefits is its ability to customize courses to the interests and learning preferences of particular students in CS education. Using data analytics, adaptive learning systems evaluate student performance and offer personalized feedback and improvement recommendations. Intelligent tutoring systems offer adaptable and interactive learning environments by using machine learning (ML) and natural language processing (NLP).
Artificial Intelligence in Computer Science
Authors: Prasad G Arun , Kumar A. V. Senthil , Sharma Priyanka , Irawati Indrarini Dyah , D. V. Chandrashekar , Musirin Ismail Bin , Abdullah Hesham Mohammed Ali , Rao L Manjunatha
Published: September 2023

Artificial intelligence (AI) is a rapidly evolving field that has seen tremendous growth in recent years. In this chapter, the authors provide an overview of current trends in AI and their applications in computer science. They also discuss the future directions of AI research and their potential impact on the field of computer science. They start by introducing the basic concepts of AI and its various subfields. Then, they present an overview of current trends in AI research, including machine learning, natural language processing, computer vision, and robotics. The authors discuss how these trends are applied in computer science, such as autonomous vehicles, fraud detection, and personalized medicine. Finally, they discuss the future directions of AI research, including the development of more explainable AI systems, the integration of AI with other emerging technologies, and the ethical considerations of AI.
Comparative Analysis Implementation of Queuing Songs in Players Using Audio Clustering Algorithm
Authors: Aarthi B. , Selvakumar Prathap , Subiksha S. , Chhavi S. , Parathasarathy Swetha
Published: September 2023

This chapter compares the toughness of k-means, DBSCAN, and adaptive clustering algorithms for grouping data points into distinct clusters. The k-means algorithm is a widely used method that is easy to implement and efficient. The DBSCAN algorithm is a density-based method that is well-suited for datasets with clusters of varying densities, but it can be sensitive to the choice of parameters. In order to determine the ideal number of clusters within a dataset, adaptive clustering algorithms dynamically alter the number of clusters during the clustering process. The production of these algorithms is evaluated on a variety of datasets, and the results are compared in terms of accuracy and efficiency. According to the chapter's conclusion, each method has advantages and disadvantages of its own, and the ideal approach to apply will vary depending on the particular dataset and the objectives of the study.
Optimizing Leaf Diseases of Apple Scab and Apple Black Rot in the Context of “Useful” Information Measures and Distance Measurements
Authors: Dwivedi Pankaj Prasad , Sharma Dilip Kumar
Published: September 2023

Detecting disease on crops is an essential and time-consuming operation in agricultural techniques. It takes a significant amount of time and specialized effort. This research provides a clever and effective agricultural disease detection system based on information theory. In the present chapter, first information measures, ‘useful' information measures, and distance measures are defined and explained. The authors find out the distance measures between leaves of apple scab (AS) and apple black rot (ABR). Six leaves of AS and ABR are taken into consideration. After measuring the distance, the impact of disease in the leaves of AS and ABR has been noticed. It is shown that this measure can be embedded in most image classification techniques and is subject to reference transformation. Weak and strong information is also obtained. Finally, minimum and maximum distances are evaluated, and our findings indicate that the likelihood of illnesses in plant leaves is low when the information measure of leaves is low.
Vision-Based Data-Driven Modeling Vehicle Detection in Videos Using Convolutional Neural Network
Authors: Regin R. , Ramesh Sriraam , Kumar Athiyan Ramesh , Gandhi Praghalad Krishna , Bose S Rubin
Published: September 2023

Object detection is a vital component for autonomous driving, and autonomous cars rely on perception of their surroundings to ensure safe and robust driving performance. It shows how the perception system makes use of object identification algorithms to precisely identify nearby items like pedestrians, cars, traffic signs, and barriers. It goes on to say that detecting and localising these things in real-time depends greatly on deep learning-based object detectors. The most recent object detectors and unresolved issues with their integration into autonomous vehicles are also covered in the essay. It mentions that deep learning visual classification methods have achieved enormous accuracy in classifying visual scenes; it makes use of the convolutional neural network. However, it points out that the visual classifiers face difficulties examining the scenes in dark visible areas, especially during the nighttime, and in identifying the contexts of the scenes.
CD160 Signaling Is Essential for CD8+ T Cell Memory Formation via Upregulation of 4-1BB
Authors: Zhang Linxia , Zhang Anli , Zhu Xinyu , Tian Xinmei , Guo Jiaohan , He Qian , Zhu Lingyan , Yuan Songhua , Zhao Chen , Zhang Xiaoyan , Xu Jianqing
Published: September 2023

A better understanding of the regulatory mechanisms governing the development of memory CD8+ T cells could provide instructive insights into vaccination strategies and T cell–based immunotherapies. In this article, we showed that CD160 surface protein is required for CD8+ T cell memory formation. In the response to acute lymphocytic choriomeningitis virus infection in a mouse model, CD160 ablation resulted in the failure of the development of all three memory CD8+ T cell subsets (central, effective, and tissue-resident memory), concomitant with a skewed differentiation into short-lived effector T cells. Such memory-related defect was manifested by a diminished protection from viral rechallenge. Mechanistically, CD160 deficiency led to downregulation of 4-1BB in activated CD8+ T cells, which contributes to the impaired cell survival and decreased respiratory capacity. The nexus between CD160 and 4-1BB was substantiated by the observation that ectopic introduction of 4-1BB was able to largely complement the loss of CD160 in memory CD8+ T cell development. Collectively, our studies discovered that CD160, once thought to be a coinhibitor of T cell signaling, is an essential promoter of memory CD8+ T cell development via activation of the costimulatory molecule 4-1BB.
Genome-Wide CRISPR/Cas9 Screening Identifies That Mitochondrial Solute Carrier SLC25A23 Attenuates Type I IFN Antiviral Immunity via Interfering with MAVS Aggregation
Authors: Zhang Hongguang , Li Xin , Wang Yiwei , Liu Xianxian , Guo Jing , Wang Zheng , Zhang Lulu , Xiong Sidong , Dong Chunsheng
Published: September 2023

Activation of the mitochondrial antiviral signaling (MAVS) adaptor, also known as IPS-1, VISA, or Cardif, is crucial for antiviral immunity in retinoic acid–inducible gene I (RIG-I)–like receptor signaling. Upon interacting with RIG-I, MAVS undergoes K63-linked polyubiquitination by the E3 ligase Trim31, and subsequently aggregates to activate downstream signaling effectors. However, the molecular mechanisms that modulate MAVS activation are not yet fully understood. In this study, the mitochondrial solute carrier SLC25A23 was found to attenuate type I IFN antiviral immunity using genome-wide CRISPR/Cas9 screening. SLC25A23 interacts with Trim31, interfering with its binding of Trim31 to MAVS. Indeed, SLC25A23 downregulation was found to increase K63-linked polyubiquitination and subsequent aggregation of MAVS, which promoted type I IFN production upon RNA virus infection. Consistently, mice with SLC25A23 knockdown were more resistant to RNA virus infection in vivo. These findings establish SLC25A23 as a novel regulator of MAVS posttranslational modifications and of type I antiviral immunity.
Instantaneous stroke risk assessment of adults in Enugu, South East Nigeria: results from a random point survey
Authors: Ndionuka Ijeoma B. , Onwuekwe Ikenna O. , Ekenze Oluchi S. , Ezeala-Adikaibe Birinus , Orah Chidinma , Madu Victor , Okereke Chiamaka
Published: September 2023

Stroke remains a major cause of morbidity, death, and disability around the world, most especially in black Africans. Understanding the magnitude and appreciation of stroke risk in susceptible populations remains a key strategy in reducing stroke burden. This study examined and compared 5-year stroke risk in an adult population in Enugu, Southeast Nigeria. A point cross-sectional survey assessing stroke risk in adults was done in October 2019 in the city of Enugu as part of the World Stroke Day commemoration using the Stroke Riskometer app, and the data was analyzed. Ethical approval was obtained. The total number of participants in this survey was 117 traders in a market in the Enugu metropolis, Enugu State, Nigeria. More males, 63%, than females, 37%, participated in this study. The total mean age was 47.50 years, with a total mean 5-year stroke risk of 3.93. Stroke risk was noted to be higher in females 4.56 than in males 3.56. Elevated blood pressure was present in 35% of the participants, and elevated blood glucose was seen in 5% of the total population. The World Stroke Organization’s Stroke Riskometer app is a valuable tool in assessing stroke risks especially in resource poor settings. This app also serves as a cost-effective method of conducting epidemiological research in stroke and other non-communicable diseases internationally. Hypertension remains the most common risk factor for stroke globally. Higher stroke risk in females likely associated with higher mean age.
Fracture of the mandible treatment in a child: a simplified technique
Authors: Houben Christoph H. , Campbell Lundy , Chiok Stephen Kuol Chuol
Published: September 2023

After being hit by a motorcycle a seven-year old boy presented with a displaced fracture of the body of the right mandible [type III]. In the absence of orthodontic internal fixation or ligature wire equipment suture material was used to provide approximation and stabilisation of the fracture. The non-absorbable suture was fed through a cannula which was pierced through the bone on either side of the fracture.

We present this simplified technique as a suitable alternative for the fixation of mandible fractures in settings with very limited resources.
Seasonal variation in the relative strength of bottom-up vs top-down effects in pelagic cladoceran populations identified through contribution analysis of birth rate
Authors: Kasparson Anna A. , Polishchuk Leonard V.
Published: September 2023

Pelagic freshwater communities are characterized by the presence of strong trophic interactions, with the dominance of either food limitation (bottom-up effect) or predation pressure (top-down effect) alternating in time. Though this temporal variation should have a major impact on zooplankton dynamics, few studies have examined it. We consider here an approach that involves identifying signatures of food availability and size-selective fish predation based on the demographic characteristics of cladoceran populations. The relative strength of top-down vs bottom-up effects was assessed on short sampling intervals as contributions of the proportion of adults and fecundity, respectively, to the resulting change in birth rate. The dominant effect on each sampling interval was determined based on the absolute value of the ratio of those contributions (R). From previous experiments, we expected that under the dominant effect of food, R should be less than unity, while under fish predation it should be 1 < R < 3.4. We analyzed two datasets – one collected for a pelagic cladoceran community of three species, and another retrieved from the published data for Daphnia catawba in 1986. In the former case, the temporal variation in the dominant effect was assumed from the pattern of cladoceran populationdynamics as well as limited data on zooplankton consumption by planktivorous fish; in the latter case, the seasonal change in predation pressure by fish on the daphnids was known from the original data. Our results show that the probability density functions for R values from the two datasets indicate an increased probability of the ratio values associated with the abovementioned ranges, suggesting that both bottom-up and top-down effects should have been driving cladoceran population dynamics during the study periods. Based on the results of the Generalized Additive Models (GAMs), the fitted R values for the most abundant species from the first dataset - Bosmina longirostris - changed from the values indicative of strong food effect at the beginning of the study period to those indicative of strong top-down effect when fish with substantial numbers of bosminids in the gut were caught. In the second dataset, for the two time intervals associated with increased predation pressure by fish, the fitted R values were predominantly located between 1 and 3.4, as expected. For both datasets, our results indicate that contribution analysis of birth rate can be used as an informative, albeit preliminary, tool to identify trophic interactions driving zooplankton seasonal population fluctuations in freshwater communities.
Jujuboside a Improved Energy Metabolism in Senescent H9c2 Cells Injured by Ischemia, Hypoxia, and Reperfusion through the CD38/Silent Mating Type Information Regulation 2 Homolog 3 Signaling Pathway
Authors: Hu Yi-Ran , Qu Hui-Yan , Guo Jia-Ying , Yang Tao , Zhou Hua
Published: September 2023

Objective:

This study explored the myocardial protection role of Jujuboside A through an ischemia–hypoxia–reperfusion (IHR) model.

Materials and Methods:

H9c2 cells were induced by D-galactose (D-gal) and IHR to establish an aging and IHR model. There are four groups of experiments: Control, IHR, D-gal + IHR, and D-gal + IHR + Jujuboside A. Cells viability, Adenosine triphosphate (ATP), reactive oxygen species (ROS), nicotinamide adenine dinucleotide (NAD+), nicotinamide adenine dinucleotide hydride (NADH) content, and NAD+/NADH ratio were detected using biochemical methods. Inflammatory cytokines level was detected by enzyme-linked immunosorbent assay. The expression of CD38, Recombinant NLR Family, pyrin domain-containing protein 3 (NLRP3), and silent mating type information regulation 2 homolog 3 (SIRT3) protein was detected by Western blotting.

Results:

Compared to the IHR group, cell viability, ATP content, NAD + content, NAD+/NADH ratio, and SIRT3 protein expression decreased, ROS level and inflammatory cytokines increased, and CD38 and NLRP3 proteins raised in the D-gal + IHR group. Compared to the D-gal + IHR group, cell viability, ATP content, NAD + content, NAD+/NADH ratio, and expression of SIRT3 protein increased, ROS level and inflammatory cytokines level decreased, and expression of the CD38 and NLRP3 proteins decreased in the D-gal + IHR + Jujuboside A group.

Conclusions:

Jujuboside A inhibited the expression of CD38, improved energy metabolism disorder, and mitochondrial function, and decreased inflammation in D-gal-induced H9c2 cells.
The Mechanism of Total Ginseng Extracts in the Treatment of Lung Cancer Progression Based on Network Pharmacology and Experimental Validation
Authors: Hana Hong-Kuan , Qian Cheng , Song Meng-Yao , Zhang Teng , Yang Chun-Mei , Gu Ren-Jun , Zhou Xian , Wei Zhong-Hong , Zhao Yang , Lu Yin
Published: September 2023

Objective:

The objective of this study was to investigate the mechanism by which total ginseng extract (TGE) inhibits the progression of lung cancer through network pharmacology and experimentation.

Materials and Methods:

A Lewis lung carcinomas (LLC) model was established by injecting cancer cells through the tail vein and through administering different doses of TGE. The infiltrated immune cells into the microenvironment of lung cancer metastasis through flow cytometry were evaluated, and the messenger RNA (mRNA) expression levels of various immune cell-related chemokines were determined using quantitative reverse transcription–polymerase chain reaction. Therapeutic targets and signaling pathways of TGE in nonsmall cell lung cancer were investigated using systematic pharmacology and virtual docking. Immunoblotting was performed to determine the impacts of TGE on migration-related proteins.

Results:

Flow cytometry showed that 1.82 g/kg TGE increased the infiltrated T cells and inhibited the recruitment of myeloid cells, which was caused by decreased mRNA expression of chemokines after TGE treatment. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the delayed progression of lung cancer by TGE might be related to the promotion of lung cancer cell apoptosis-associated signaling pathways. The virtual docking results indicated that the active components of ginseng are directly bound to apoptosis-related proteins. Immunoblotting showed that TGE inhibited tumor metastasis by regulating the expression of migration-related proteins.

Conclusions:

The study reveals the potential mechanism of ginseng extract in the treatment of lung cancer progression and provides a reliable basis for its clinical application.
A Case Series of Scrub Meningoencephalitis from a Tertiary Care Center in North India
Authors: Suri Vikas , Singh Harpreet , Ary Kunwer A. , Biswal Manisha , Ahuja Chirag K. , Kharbanda Parampreet , Sharma Navneet
Published: September 2023

Scrub typhus infection is reemerging leading cause of acute febrile illnesses in post-rainy or monsoon season in Southeast Asia. It is caused by Orientia tsutsugamushi and spread by the bite of chiggers, larval forms of trombiculid mites. The clinical picture can range from simple acute febrile illness to multiorgan dysfunction. Neurological manifestations also vary from aseptic meningitis, meningoencephalitis, cerebral infarction, acute disseminated encephalomyelitis, transverse myelitis, and psychiatric manifestations. Here, we present a case series of eight cases of scrub meningoencephalitis diagnosed based on clinical, laboratory, and radiological criteria.
Impaired Kidney Function Portended a Bleak Prognosis for Surgically Treated Hypertensive Intracerebral Hemorrhage Patients
Authors: Wang Jian , Wang Rui , Qin Hu , Zuo Lei
Published: September 2023

Purpose:

Spontaneous intracerebral hemorrhage (ICH) cases caused by hypertension often have poor prognoses. The use of dehydrant agents, such as mannitol, is common to reduce intracranial pressure and alleviate cerebral edema, but they may also pose a risk of worsening kidney function. This study aimed to investigate the impact of impaired kidney function on the outcomes of surgically treated hypertensive ICH patients.

Methods:

We conducted a retrospective analysis of a consecutive cohort of patients who underwent surgical intervention due to hypertension-related ICH at our institute between December 1, 2017, and January 31, 2022. Demographic, clinical, radiological, and prognostic data were collected. Patients were categorized into two groups based on 90-day mortality: group A [overall survival (OS) ≤3 months] and group B (OS >3 months). Survival analysis was performed to identify factors associated with poor outcomes.

Results:

Among the 232 eligible patients, group A exhibited significantly impaired kidney function, as indicated by mean estimated glomerular filtration rate (eGFR) at admission, postoperative, 3-day postoperative, and 7-day postoperative time points (91.9, 82.5, 73.5, 75.2 ml/min/1.73 m²). In contrast, group B did not show significant changes in kidney function (mean eGFR for the corresponding time points: 108.1, 106.5, 111.5, 109.6 ml/min/1.73 m²). The 3-day postoperative eGFR showed the strongest predictive ability for assessing prognosis [areas under the curve (AUC): 0.617, 0.675, 0.737, 0.730]. Univariate and multivariate analyses identified low Glasgow Coma Scale (GCS) score (3–8), ventricle intrusion of hematomas, cardiac failure, larger hematoma volume, infection, and lower 3-day postoperative eGFR as adverse factors for survival.

Conclusions:

Preserving kidney function is crucial for achieving favorable outcomes in hypertensive ICH cases. Impaired 3-day postoperative eGFR emerged as an independent risk factor for overall survival. Patients with cardiac failure, infection, and larger hematoma volume should receive careful management to improve outcomes.
Translation and Validation of ID-Migraine Questionnaire to North-Indian Vernacular Languages
Authors: Sahu Prachi , Chaturvedi Pragya , Khan Rahul , Singla Monika , Munshi Anjana , Singh Gagandeep
Published: September 2023

Background:

ID-Migraine is an established screening tool for migraine. Translation and validation in more languages can increase its reach and scope.

Aim:

To translate and validate ID-Migraine for screening migraine patients in two North-Indian vernacular languages, that is, Hindi and Punjabi.

Methods:

ID Migraine was translated into Hindi and Punjabi. Subjects with headaches in outpatient clinics were administered the questionnaire according to their preferred language of choice and referenced clinical evaluations, performed by an experienced neurologist, based on current the ICHD-3 diagnostic criteria.

Results:

One hundred subjects with complaints of headaches and 60 healthy controls were recruited after informed consent. Of the 100 subjects with headaches, 73 (73%) screened positive with a translated version of ID-Migraine, and 60 (60%) were eventually diagnosed with migraine without aura. The sensitivity of the Hindi version of ID-Migraine was 94% (95% confidence intervals, 79% to 99%); specificity, 56% (95% CI, 31% to 78%); positive predictive value, 79% (95% CI, 69% to 86%) and negative predictive value, 83% (95% CI, 55% to 95%). The Punjabi version demonstrated a sensitivity of 86% (95% CI, 68% to 96%); specificity, 43% (95% CI, 23% to 66%); PPV, 68% (95% CI, 58% to 76%); and NPV, 69% (95% CI, 44% to 86%).

Conclusion:

The translated versions of ID-Migraine demonstrated high sensitivity and fair specificity for screening migraine in Indian subjects who speak and understand Hindi and Punjabi.
The Interface between Depression and Alzheimer’s Disease. A Comprehensive Approach
Authors: Modrego Pedro J. , Cerio Leyre D. de , Lobo Antonio
Published: September 2023

Depression and Alzheimer’s disease (AD) are frequent interacting diseases in the elderly with a negative impact on the quality of life of patients and caregivers. Late-life depression may be regarded either as an early symptom of AD or a risk factor for AD, depending on the context. This review was focused on the latest developments in the fields of the neurobiological basis and treatment of depression in AD. We found that some plausible hypotheses are emerging to correlate with depression in AD, such as neuroinflammation and dysimmune regulation. It seems that depression is not related to amyloid deposition, but this issue is not completely resolved. The response to antidepressants is controversial according to the evidence from 10 small double-blind randomized placebo-controlled clinical trials with antidepressants in AD patients with depression: four with sertraline, one with three arms (sertraline, mirtazapine, placebo), one with fluoxetine, one with imipramine, one with clomipramine, one with escitalopram, and one with vortioxetine. The total number of treated patients completing the trials was 638. The main criterion of a positive response was a reduction in the scores of clinical scales for depression of at least 50%. The weighted OR (odds ratio) was calculated with the method of Mantel-Haenszel: 1.29; 95% CI: 0.77–2.16. No significant differences were found compared with placebo. Antidepressants did not have a meaningful negative influence on cognition, which was measured with the mini-mental state examination (MMSE) in 18 clinical trials. Alternatives other than drugs are also discussed. Although there have been important advances in this field, pathophysiology and treatment deserve further research.
Demystifying Partial Tears of the Anterior Cruciate Ligament: A Review of Current Diagnostic and Management Strategies
Authors: Chandra Abhishek , Agarwal Aakanksha , Azam Md. Quamar
Published: September 2023

Partial tears of anterior cruciate ligament (ACL) are a diagnostic and management challenge. There is ongoing discussion and debate about the ideal management of a partial tear with “ala carte” options available in the current literature. Findings can remain occult on imaging studies, necessitating more efficient clinical examination and acumen to identify patients requiring surgical intervention. The authors through this literature review provide an overview on partial tears of ACL including the background anatomy, pathology, clinical diagnosis, imaging finding, and surgical techniques. The literature is critically probed and tabulated for effortless assessment. The objective is to help the orthopedic surgeon decide the optimal course for a suspected partial ACL tear. The authors do not aim to provide a guideline but rather present an inventory of available options and approaches for managing partial ACL tear. This review is a comprehensive amalgamation of the heterogeneity in the present literature.
Hip and Knee Arthroplasty: A Review of Complications and Advances in Imaging
Authors: Chua Elise , Shah Dhiren
Published: September 2023

Arthroplasty-related complications are challenging to diagnose as they often present with nonspecific signs and symptoms, and can lead to long-term morbidity if inadequately managed. The difficulty in imaging implants is compounded by its intrinsic propensity to artifacts. Strategies to reduce this include: Judicious use of the appropriate imaging modality for the relevant clinical indication; knowledge of optimizing imaging acquisition parameters; and use of metal artifact reduction (MAR) software. We review the literature on expected normal appearances of hip and knee arthroplasties, findings of arthroplasty-related complications on various imaging modalities, advances in imaging techniques, and subsequently, suggest an algorithm for painful arthroplasty assessment. Serial radiographs remain key in identifying subtle changes in component position, hardware failure, periprosthetic osteolysis, and potential for loosening, given their ready availability, high resolution, and minimal metal-related artifact. Computed tomography with MAR provides 3D assessment and information on bone stock for surgical planning and custom implants. Magnetic resonance imaging with MAR can identify complications at earlier stages, such as loosening, capsular dehiscence in instability, and periprosthetic edema in nondisplaced fractures. It has high diagnostic performance in infection (lamellated synovitis), particle disease, adverse reactions to metal debris, in addition to demonstrating impingement on neurovascular structures. Nuclear medicine imaging is used as a problem-solving tool and is valuable in its high negative predictive value. Novel imaging techniques can further reduce artifacts and improve visualization of the implant-bone interface, and machine learning can facilitate image interpretation although attaining sufficient data and clinical validation will be challenging.
Day Case Knee Osteotomy
Authors: Kocialkowski Cezary , Hart Sam ,   Bristol Knee Group*, Murray James R. D.
Published: September 2023

Introduction:

Knee osteotomy, both high tibial osteotomy (HTO) and distal femoral osteotomy (DFO), is a well-recognized treatment for young, active patients with unicompartmental knee osteoarthritis. Osteotomy around the knee is usually performed as an inpatient procedure. The aim of this study was to assess the effectiveness and patient satisfaction of our day-case protocol for knee osteotomy.

Methods:

All patients who underwent day-case knee osteotomy at the study unit, over a 3-year period, were reviewed to assess the success of ambulatory care for knee osteotomy. Patients were sent questionnaires to assess functional outcome and patient satisfaction with our day-case process.

Results:

Thirty-three knee osteotomies were performed as a day-case protocol, of which same-day discharge was achieved in 24 patients (73%) and discharge within 24 h achieved in 32 patients (97%). The mean postoperative Knee Osteoarthritis Outcome Score was 67.1% and 79% of patients rated their care as good or excellent. Return to sporting activities was achieved in 75% of patients, and 88% of the patients reported they would be happy to undergo day-case knee osteotomy again.

Conclusions:

Knee osteotomy, both HTO and DFO, can be performed as a day-case procedure with similar improvements in functional outcomes and no increased complication rate, compared to in-patient osteotomy.
Outcomes of Patients Undergoing Total Knee Arthroplasty with Spinal Anesthesia: A Comparison of Mepivacaine versus Bupivacaine
Authors: Holbert Samuel Elliott , Brennan Jane , Bahethi Shreeya , Mandich Madilyn , Cheema Minahil , Turcotte Justin J. , Macdonald James , King Paul
Published: September 2023

Introduction:

Previous literature indicates that mepivacaine used for spinal anesthesia may lead to reduced recovery time and urinary retention compared to bupivacaine in patients undergoing total knee arthroplasty (TKA). We sought to compare outcomes between spinal anesthetics in our high-volume joint institution.

Materials and Methods:

A retrospective review of 553 unilateral primary TKA patients who received spinal anesthesia was conducted. Patients were divided by their receipt of mepivacaine or bupivacaine. Univariate comparisons before and after propensity score matching were used to compare outcomes for TKA patients receiving mepivacaine with those who did not.

Results:

Of the 553 patients, 102 received mepivacaine, and 451 received bupivacaine. After propensity score matching, patients who received bupivacaine experienced longer lengths of stay, received more oral morphine milligram equivalents (OMMEs), and were less likely to be discharged home. No differences in rates of nausea, urinary retention, or 30-day readmissions were observed between the groups.

Discussion:

In patients undergoing TKA with a spinal anesthesia, after adjusting for potentially confounding factors using propensity score matching, the use of mepivacaine was associated with shorter length of stay, less overall OMME requirements, and increased likelihood of home discharge, with no increase in complication rates. Based on these results, mepivacaine appears to be a viable alternative to bupivacaine for use in TKA rapid recovery protocols.
Biventricular Endomyocardial Fibrosis with Severe Aortic Stenosis: A Rare Combination
Authors: Soman Suman Omana , Vijayaraghavan G. , Pillai Ramakrishna , Muneer A. R. , Teena M. V.
Published: September 2023

Endomyocardial fibrosis is the most common form of restrictive cardiomyopathy worldwide. Primarily it is a disease of the young with apical fibrosis, endocardial thickening with involvement of the papillary muscles and atrio-ventriclar valves. Its association with valvular heart disease of other etiology is rather uncommon. We are reporting a case of 65year old lady with classical features of biventricular Endomyocardial fibrosis and valvular aortic stenosis.