bluuebunny/crossref_metadata_2025 huggingface dataset:
Feasibility and safety study of the use of a new robot (Maestro™) for laparoscopic surgery.
Authors: Cadière Guy-Bernard , Himpens Jacques , Poras Mathilde , Boyer Nicolas , Cadière Benjamin
Published: January 2024

1. Background
The emergence of laparoscopic surgery marked a significant progress in minimally invasive surgical techniques, despite definite shortcomings in terms of vision and exposure control. Telerobotic systems like Da Vinci™ were developed to enhance surgical control but created new limitations such as the separation of the operating surgeon from the operating table, learning curve, cost, and size. A new device, Maestro™, appears promising in addressing these limitations. This present work evaluates the feasibility, safety and satisfaction of the surgeon with the assistance provided by the Maestro System in standard elective minimally invasive digestive laparoscopic procedures.
2. Methods
The current study aims at presenting the initial experience with the Maestro System in common elective digestive laparoscopic procedures performed in humans (50 individuals).
3. Results
All 50 procedures were completed successfully. No significant complications related to the use of the Maestro System were recorded.
4. Conclusion
The use of the Maestro System in common digestive elective laparoscopic procedures is feasible and safe. The surgeon is satisfied in 92% with the assistance provided by the Maestro System.
The effects of nucleation and species functional traits on tree seedling performance in the early stage of ecological restoration
Authors: Manhães Adriana P. , Amazonas Nino T. , Pansonato Marcelo P. , Sansevero Jerônimo B. B. , Martini Adriana , Mantuano Dulce
Published: January 2024

The initiation of a new plant community in a restoration area hinge on the performance of seedlings post-planting. This study aimed to evaluate the impact of species functional traits—specific leaf area (SLA), wood density (WD), seed dry mass (SDM), and potential height (H)—on the seedling performance after 18 months of planting, comparing two planting designs (rows and clusters) and the influence of fertilization addition in clusters. The restoration area is a riparian tropical forest located at Caraguatatuba municipality, São Paulo, Brazil. We monitored 3,017 tree seedlings and estimated their survivorship and relative growth rate (RGR) using the diameter, height, and canopy area of the surviving seedlings and the stem biomass for the cluster RGR estimation. Using linear mixed models, we analyzed how the planting designs and the functional traits affect species survival and their RGR. We underscored the significance of slow-growth traits (low SLA, and high SDM and WD) in enhancing species survival, irrespective of the planting design. Whereas, maximizing species growth entails prioritizing seedlings with greater potential height. Cluster survival and growth improved with a greater abundance of species with low values of SDM (i.e., fast-growth species) and low functional divergence (high similarity). Fertilized clusters improved the RGR of slow-growth species. Including functional traits in restoration is advantageous for enhancing seedling performance at the species level, which is an important consideration for restoration practitioners. To optimize applied nucleation, clusters should target functional diversity at this community level to prevent the dominance of competitive species.
A Multidimensional Exploration of Narcissistic Personality Disorder through Psycholinguistic Analysis and Neuroscientific Correlates
Authors: Elleuch Dalia
Published: January 2024

Narcissistic Personality Disorder (NPD) manifests as a personality disorder marked by an inflated self-importance, heightened sensitivity to criticism, a lack of empathy, a preoccupation with appearance over substance, and features such as arrogance, grandiosity, a constant need for admiration, a tendency to exploit others, and an inclination towards demanding special treatment due to a sense of excessive entitlement. This interdisciplinary study delves into the intricate landscape of NPD through the systematic synthesis of psycholinguistic analysis and neuroscientific correlates. The cognitive and emotional dimensions of NPD reveal linguistic patterns, including grandiosity, entitlement, and manipulative communication. Neuroscientific investigations reveal structural brain differences and alterations in functional connectivity, further explaining the neural underpinnings of social cognition deficits observed in individuals with NPD. Genetic predispositions and neurotransmitter imbalances add a layer of complexity to the understanding of NPD. The necessity for linguistic intervention in diagnosing and treating Narcissistic Personality Disorder is underscored by an interdisciplinary study that intricately synthesizes psycholinguistic analysis and neuroscientific correlates, offering a comprehensive understanding of NPD's cognitive, emotional, and neural dimensions and paving the way for future practical, theoretical, and pedagogical approaches to address the complexities of this personality disorder.
Friction Velocity Determination Techniques in Turbulent Boundary Layers with Miniature Vortex Generators
Authors: Kong Jiahao , Nogroho Bagus , Bennetts Luke , Chin Rey , Chan Chi
Published: January 2024

Miniature vortex generators (MVGs) have the potential to control turbulent boundary layers (TBLs). Analyzing the scaled turbulent structure of MVG TBLs in experiments typically requires indirect methods for accurate friction velocity Uτ determination. The established methods for Uτ -determination need to be verified for non-generic TBLs, such as MVG TBLs, especially at near-wake stations. This study compares the performance of the five most common Uτ -determination methods for MVG TBLs. The methods are tuned in terms of their free parameters and fitting ranges using direct measurements of Uτ from large eddy simulation data and applied to a corresponding experiment to assess their accuracy. Based on the findings, a novel “inner” method, which is the Musker function with a drifting buffer layer plus a bump function, is recommended for MVG TBLs of the form investigated, as it provides a good estimation of Uτ with uncertainty < 5% for all streamwise stations. The method is applied to three further experimental tests with different flow conditions to study trends in Uτ. The error of the drag variation is <6%, which indicates the method is reliable for MVG TBLs at high Reynolds numbers.
Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique
Authors: El-Ela A. A. Abou , Ali M. K. , Nasef A. F. , Amer R. A.
Published: January 2024

Wind Energy Conversion Systems (WECS) is one of the burning research fields these days. Governments encourage researchers and planners to make plans towardincreasing the amount of power generation from renewable energy sources (RES) in the future because conventional energy sources will cause a crisis for the environment. The installationof WECS units can cause an adverse effect if they are notproperly allocated. Therefore, this paper presents the applications of modern optimization techniques such as the artificial rabbit optimization algorithm (ARO), the grey wolfoptimizer (GWO), and particle swarm optimization (PSO) for determining the optimal location and sizing of WECS. The effectiveness of these techniques is demonstrated with IEEE 14-bus and IEEE 30-bus considering various penetration conditions. Also, the effect of wind turbines on system transient performance is investigated using robust non-linear models ofboth synchronous machines and wind turbine generators whenthe system is exposed to a symmetrical three-phase short circuitfault. The results show the ability of the ARO algorithm compared to both GWO and PSO techniques in solving thewind turbine generator (WTG) placement and sizing problem.The result show that ARO-based WTG increases the stability ofthe power system, improves the voltage profile, reduces bothactive and reactive power losses in the systems, and enhances dynamics performance for the overall systems. All the simulations of the system models are carried out using MATLAB/SIMULINK and given in the form of comparative results with a three-phase short circuit, and changes in wind penetration level to show the stability of the system.
Enhanced artificial ecosystem-based optimization for global optimization and constrained engineering problems
Authors: Wang Yunpeng , Zhang Jixiang , Zhang Mengjian , Wang Deguang , Yang Ming
Published: January 2024

Artificial ecosystem-based optimization (AEO) is a nature-inspired intelligent optimization algorithm that has been widely applied to various real-world optimization problems. However, AEO has several limitations, including slow convergence and difficulty in escaping from local optima. To address these drawbacks, this study proposes an enhanced variant of AEO called enhanced artificial ecosystem-based optimization (EAEO). First, Latin hypercube sampling is introduced to achieve uniform population initialization. Then, a quadratic interpolation mechanism is embedded to accelerate convergence and improve accuracy. Finally, an adaptive neighborhood search inspired by animal migration behavior is designed to help to jump out of local optima. The performance of EAEO is evaluated using twenty-three benchmark functions and the CEC2017 test suite. Experimental results indicate that EAEO outperforms the original AEO and other comparison algorithms in terms of accuracy and stability. The proposed EAEO is applied to solve four engineering optimization problems. The results demonstrate the superiority of EAEO in addressing practical problems.
To profile or to marginalize - A SMEFT case study
Authors: Brivio Ilaria , Bruggisser Sebastian , Elmer Nina , Geoffray Emma , Luchmann Michel , Plehn Tilman
Published: January 2024

Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This agreement is encoded in measured Wilson coefficients and their uncertainties. A technical challenge of global analyses are correlations. We compare, for the first time, results from a profile likelihood and a Bayesian marginalization for a given data set with a comprehensive uncertainty treatment. Using the validated Bayesian framework we analyse a series of new kinematic measurements. For the updated dataset we find and explain differences between the marginalization and profile likelihood treatments.
Back to the formula - LHC edition
Authors: Butter Anja , Plehn Tilman , Soybelman Nathalie , Brehmer Johann
Published: January 2024

While neural networks offer an attractive way to numerically encode functions, actual formulas remain the language of theoretical particle physics. We use symbolic regression trained on matrix-element information to extract, for instance, optimal LHC observables. This way we invert the usual simulation paradigm and extract easily interpretable formulas from complex simulated data. We introduce the method using the effect of a dimension-6 coefficient on associated ZH production. We then validate it for the known case of CP-violation in weak-boson-fusion Higgs production, including detector effects.
Hemoglobin A1c Level Is Associated With Lymphovascular Space Invasion In Diabetic Endometrial Cancer Patients
Authors: Senkaya Ayse Rabia , Kantarci Sercan , Yildirim Karaca Suna , Sanci Muzaffer
Published: January 2024

Objective: Our aim in this study is to examine the relationship of hemoglobin A1c (HbA1c) and fasting glucose with the stage, grade and histological type of cancer and its value in predicting the prognosis of endometrial cancer in diabetic endometrial cancer patients.

Study Design: The data of 138 endometrial cancer patients with diabetes who met the study criteria were analyzed. Hemoglobin A1c levels and fasting glucose were compared with cancer stage, grade, histological type, lymphovascular invasion, chemotherapy and radiotherapy data.

Results: A statistically significant difference was found between the groups in terms of HbA1c values only according to the lymphovascular invasion (p=0.02). While there was no significant correlation between endometrial thickness and HbA1c, a low positive correlation was found between the fasting glucose value (r=0.191, p=0.025)

Conclusions: The higher rate of lymphovascular invasion in patients with high HbA1c value alone is insufficient in determining the prognosis when other parameters are considered.
Energy-based hydro-economic modeling of climate change effects on the Upper Euphrates Basin
Authors: Aytac Ayca , Dogan Mustafa Sahin , Tuna M. Cihat
Published: January 2024

Climate change and global warming are expected to affect water resources management and planning, requiring adaptations to changing conditions. Therefore, it is very important, especially for decision-makers, to identify demand deficits due to less water availability with climate change that may occur in the existing water supply system in advance. FEHEM, a hydroeconomic optimization model of the integrated reservoir system of the Upper Euphrates Basin, which is the largest and main basin providing water flow to the Euphrates River, is developed. Using a 45-year historical hydrological dataset, water management and hydroelectric operations are evaluated with a linear programming model at monthly time steps. The effects of climate change on the Upper Euphrates Basin are evaluated under low and high carbon emission scenarios. According to the average of the different climate scenarios studied in the model, the average decrease in flows is 37.5%. With climate change, peak flows will occur about 1–2 months earlier on average. As a result of these hydrological changes, the total amount of energy production in the basin will decrease by about 54% and energy revenue by the same percentage.
Effective degradation of quinoline by catalytic ozonation with MnCexOy catalysts: performance and mechanism
Authors: Zhang Jie , Wu Zhaochang , Dong Ben , Ge Sijie , He Shilong
Published: January 2024

Quinoline inevitably remains in the effluent of coking wastewater treatment plants due to its bio-refractory nature, which might cause unfavorable effects on human and ecological environments. In this study, MnCexOy was consciously synthesized by α-MnO2 doped with Ce3+ (Ce:Mn = 1:10) and employed as the ozonation catalyst for quinoline degradation. After that, the removal efficiency and mechanism of quinoline were systematically analyzed by characterizing the physicochemical properties of MnCexOy, investigating free radicals and monitoring the solution pH. Results indicated that the removal rate of quinoline was greatly improved by the prepared MnCexOy catalyst. Specifically, the removal efficiencies of quinoline could be 93.73, 62.57 and 43.76%, corresponding to MnCexOy, α-MnO2 and single ozonation systems, respectively. The radical scavenging tests demonstrated that •OH and •O2- were the dominant reactive oxygen species in the MnCexOy ozonation system. Meanwhile, the contribution levels of •OH and •O2- to quinoline degradation were about 42 and 35%, respectively. The abundant surface hydroxyl groups and oxygen vacancies of the MnCexOy catalyst were two important factors for decomposing molecular O3 into more •OH and •O2-. This study could provide scientific support for the application of the MnCexOy/O3 system in degrading quinoline in bio-treated coking wastewater.
Organogels: “GelVolution” in Topical Drug Delivery - Present and Beyond
Authors: Nikam Ajinkya Nitin , Roy Amrita , Raychaudhuri Ruchira , Navti Prerana D. , Soman Soji , Kulkarni Sanjay , Shirur Krishnaraj Somayaji , Pandey Abhijeet , Mutalik Srinivas
Published: January 2024

Topical drug delivery holds immense significance in dermatological treatments due to its non-invasive
nature and direct application to the target site. Organogels, a promising class of topical drug delivery systems,
have acquired substantial attention for enhancing drug delivery efficiency. This review article aims to explore
the advantages of organogels, including enhanced drug solubility, controlled release, improved skin penetration,
non-greasy formulations, and ease of application. The mechanism of organogel permeation into the
skin is discussed, along with formulation strategies, which encompass the selection of gelling agents, cogelling
agents, and additives while considering the influence of temperature and pH on gel formation. Various
types of organogelators and organogels and their properties, such as viscoelasticity, non-birefringence, thermal
stability, and optical clarity, are presented. Moreover, the biomedical applications of organogels in targeting
skin cancer, anti-inflammatory drug delivery, and antifungal drug delivery are discussed. Characterization parameters,
biocompatibility, safety considerations, and future directions in optimizing skin permeation, ensuring
long-term stability, addressing regulatory challenges, and exploring potential combination therapies are
thoroughly examined. Overall, this review highlights the immense potential of organogels in redefining topical
drug delivery and their significant impact on the field of dermatological treatments, thus paving the way for
exciting prospects in the domain.
Overcoming Low Adherence to Chronic Medications by Improving their
Effectiveness using a Personalized Second-generation Digital System
Authors: Bayatra Areej , Nasserat Rima , Ilan Yaron
Published: January 2024

Introduction:

Low adherence to chronic treatment regimens is a significant barrier to
improving clinical outcomes in patients with chronic diseases. Low adherence is a result of multiple
factors.

Methods:

We review the relevant studies on the prevalence of low adherence and present some
potential solutions.

Results:

This review presents studies on the current measures taken to overcome low adherence,
indicating a need for better methods to deal with this problem. The use of first-generation digital
systems to improve adherence is mainly based on reminding patients to take their medications,
which is one of the reasons they fail to provide a solution for many patients. The establishment
of a second-generation artificial intelligence system, which aims to improve the effectiveness of
chronic drugs, is described.

Conclusion:

Improving clinically meaningful outcome measures and disease parameters may
increase adherence and improve patients' response to therapy.
Recent Advances in Pharmaceutical Design: Unleashing the Potential of
Novel Therapeutics
Authors: Prajapati Ram Narayan , Bhushan Bharat , Singh Kuldeep , Chopra Himansu , Kumar Shivendra , Agrawal Mehak , Pathak Devender , Chanchal Dilip Kumar , Laxmikant
Published: January 2024

:

Pharmaceutical design has made significant advancements in recent years, leading to
the development of novel therapeutics with unprecedented efficacy and safety profiles. This
review highlights the potential of these innovations to revolutionize healthcare and improve patient
outcomes. The application of cutting-edge technologies like artificial intelligence, machine
learning, and data mining in drug discovery and design has made it easier to find potential drug
candidates. Combining big data and omics has led to the discovery of new therapeutic targets
and personalized medicine strategies. Nanoparticles, liposomes, and microneedles are examples
of advanced drug delivery systems that allow precise control over drug release, better bioavailability,
and targeted delivery to specific tissues or cells. This improves the effectiveness of the
treatment while reducing side effects. Stimuli-responsive materials and smart drug delivery systems
enable drugs to be released on demand when specific internal or external signals are
sent. Biologics and gene therapies are promising approaches in pharmaceutical design, offering
high specificity and potency for treating various diseases like cancer, autoimmune disorders, and
infectious diseases. Gene therapies hold tremendous potential for correcting genetic abnormalities,
with recent breakthroughs demonstrating successful outcomes in inherited disorders and
certain types of cancer. Advancements in nanotechnology and nanomedicine have paved the
way for innovative diagnostic tools and therapeutics, such as nanoparticle-based imaging agents,
targeted drug delivery systems, gene editing technologies, and regenerative medicine strategies.
Finally, the review emphasizes the importance of regulatory considerations, ethical challenges,
and future directions in pharmaceutical design. Regulatory agencies are adapting to the rapid
advancements in the field, ensuring the safety and efficacy of novel therapeutics while fostering
innovation. Ethical considerations regarding the use of emerging technologies, patient privacy,
and access to advanced therapies also require careful attention.
Emerging Therapeutic Approaches Targeting Ferroptosis in Cancer:
Focus on Immunotherapy and Nanotechnology
Authors: Yu Zongchao , Mo Zhongcheng , Qiu Yuan , Lu Hengzhe , Zheng Biao , Liu Longfei
Published: January 2024

:

Ferroptosis is a newly discovered form of programmed cell death characterized by
iron overload, ROS accumulation, and lipid peroxidation. It is distinguished by unique morphological, biochemical, and genetic features and stands apart from other known regulated cell
death mechanisms. Studies have demonstrated a close association between ferroptosis and various cancers, including liver cancer, lung cancer, renal cell carcinoma, colorectal cancer, pancreatic cancer, and ovarian cancer. Inducing ferroptosis has shown promising results in inhibiting
tumor growth and reversing tumor progression. However, the challenge lies in regulating ferroptosis in vivo due to the scarcity of potent compounds that can activate it. Integrating emerging
biomedical discoveries and technological innovations with conventional therapies is imperative.
Notably, considerable progress has been made in cancer treatment by leveraging immunotherapy
and nanotechnology to trigger ferroptosis. This review explores the relationship between ferroptosis and emerging immunotherapies and nanotechnologies, along with their potential underlying mechanisms, offering valuable insights for developing novel cancer treatment strategies.
Hydrogel Breakthroughs in Biomedicine: Recent Advances and
Implications
Authors: Mittal Ravi K , Mishra Raghav , Uddin Rehan , Sharma Vikram
Published: January 2024

Objective::

The objective of this review is to present a succinct summary of the latest
advancements in the utilization of hydrogels for diverse biomedical applications, with a particular
focus on their revolutionary impact in augmenting the delivery of drugs, tissue engineering,
along with diagnostic methodologies.

Methods::

Using a meticulous examination of current literary works, this review systematically
scrutinizes the nascent patterns in applying hydrogels for biomedical progress, condensing crucial
discoveries to offer a comprehensive outlook on their ever-changing importance.

Results::

The analysis presents compelling evidence regarding the growing importance of hydrogels
in biomedicine. It highlights their potential to significantly enhance drug delivery accuracy,
redefine tissue engineering strategies, and advance diagnostic techniques. This substantiates their
position as a fundamental element in the progress of modern medicine.

Conclusion::

In summary, the constantly evolving advancement of hydrogel applications in biomedicine
calls for ongoing investigation and resources, given their diverse contributions that can
revolutionize therapeutic approaches and diagnostic methods, thereby paving the way for improved
patient well-being.
The Gut Microbiota and Major Depressive Disorder: Current
Understanding and Novel Therapeutic Strategies
Authors: Bahmani Mohaddeseh , Mehrtabar Saba , Jafarizadeh Ali , Zoghi Sevda , Heravi Fatemah Sadeghpour , Abbasi Amin , Sanaie Sarvin , Rahnemayan Sama , Leylabadlo Hamed Ebrahimzadeh
Published: January 2024

:

Major depressive disorder (MDD) is a common neuropsychiatric challenge that primarily targets young females. MDD as a global disorder has a multifactorial etiology related to
the environment and genetic background. A balanced gut microbiota is one of the most important environmental factors involved in human physiological health. The interaction of gut
microbiota components and metabolic products with the hypothalamic-pituitary-adrenal system
and immune mediators can reverse depression phenotypes in vulnerable individuals. Therefore,
abnormalities in the quantitative and qualitative structure of the gut microbiota may lead to the
progression of MDD. In this review, we have presented an overview of the bidirectional relationship between gut microbiota and MDD, and the effect of pre-treatments and microbiomebased approaches, such as probiotics, prebiotics, synbiotics, fecal microbiota transplantation,
and a new generation of microbial alternatives, on the improvement of unstable clinical conditions caused by MDD.
In silico Approaches for Exploring the Pharmacological Activities of
Benzimidazole Derivatives: A Comprehensive Review
Authors: Srivastava Manisha , Singh Kuldeep , Kumar Sanjay , Hasan Syed Misbahul , Mujeeb Samar , Kushwaha Shom Prakash , Husen Ali
Published: January 2024

Background:

This article reviews computational research on benzimidazole derivatives.
Cytotoxicity for all compounds against cancer cell lines was measured and the results revealed that
many compounds exhibited high inhibitions. This research examines the varied pharmacological
properties like anticancer, antibacterial, antioxidant, anti-inflammatory and anticonvulsant activities
of benzimidazole derivatives. The suggested method summarises in silico research for each activity.
This review examines benzimidazole derivative structure-activity relationships and pharmacological
effects. In silico investigations can anticipate structural alterations and their effects on these derivative’s
pharmacological characteristics and efficacy through many computational methods. Molecular
docking, molecular dynamics simulations and virtual screening help anticipate pharmacological
effects and optimize chemical design. These trials will improve lead optimization, target selection,
and ADMET property prediction in drug development. In silico benzimidazole derivative studies
will be assessed for gaps and future research. Prospective studies might include empirical verification,
pharmacodynamic analysis, and computational methodology improvement.

Objectives:

This review discusses benzimidazole derivative in silico research to understand their specific
pharmacological effects. This will help scientists design new drugs and guide future research.

Methods:

Latest, authentic and published reports on various benzimidazole derivatives and their
activities are being thoroughly studied and analyzed.

Result:

The overview of benzimidazole derivatives is more comprehensive, highlighting their
structural diversity, synthetic strategies, mechanisms of action, and the computational tools used to
study them.

Conclusion:

In silico studies help to understand the structure-activity relationship (SAR) of
benzimidazole derivatives. Through meticulous alterations of substituents, ring modifications, and
linker groups, this study identified the structural factors influencing the pharmacological activity of
benzimidazole derivatives. These findings enable the rational design and optimization of more
potent and selective compounds.
Antidepressant Effect of Sodium Butyrate is Accompanied by Brain Epigenetic Modulation in Rats Subjected to Early or Late Life Stress
Authors: Valvassori Samira Silva , Varela Roger Bitencourt , Resende Wilson Rodrigues , Possamai-Della Taise , Borba Laura de Araujo , Behenck João Paulo , Réus Gislaine Zilli , Quevedo João
Published: January 2024

Background:

Major depression has a complex and multifactorial etiology constituted
by the interaction between genetic and environmental factors in its development.

Objective:

The aim of this study was to evaluate the effects of sodium butyrate (SD) on epigenetic
enzyme alterations in rats subjected to animal models of depression induced by maternal
deprivation (MD) or chronic mild stress (CMS).

Methods:

To induce MD, male Wistar rats were deprived of maternal care during the first
10 days of life. To induce CMS, rats were subjected to the CMS for 40 days. Adult rats were
then treated with daily injections of SD for 7 days. Animals were subjected to the forced swimming
test (FST), and then, histone deacetylase (HDAC), histone acetyltransferase (HAT), and
DNA methyltransferase (DNMT) activities were evaluated in the brain.

Results:

MD and CMS increased immobility time in FST and increased HDAC and DNMT activity
in the animal brains. SD reversed increased immobility induced by both animal models
and the alterations in HDAC and DNMT activities. There was a positive correlation between
enzyme activities and immobility time for both models. HDAC and DNMT activities also presented
a positive correlation between themselves.

Conclusion:

These results suggest that epigenetics can play an important role in major depression
pathophysiology triggered by early or late life stress and its treatment.
Association of Autoimmune Disorders and Disease-modifying
Antirheumatic Drugs: (DMARDs) with the Risk of Alzheimer’s and/or
Dementia: A Population Study Using Medicare Beneficiary Data
Authors: Ding Qian , Lamberts Jennifer , Konieczny Alison M. , Bringedahl Tyler B. , Torres Garcia Kiara Y.
Published: January 2024

Objectives:

Alzheimer’s disease (AD) and/or dementia is a prevalent neurocognitive disorder
primarily affecting individuals over the age of 65. Identifying specific causes of AD and/or
dementia can be challenging, with emerging evidence suggesting a potential association with autoimmune
inflammatory conditions such as rheumatoid arthritis (RA). This study aimed to assess
the prevalence rate of AD and/or dementia among Medicare beneficiaries reporting an autoimmune
disorder. Additionally, this study sought to identify the comparative prevalence of AD
and/or dementia in patients with an autoimmune disorder who were using disease-modifying antirheumatic
drugs (DMARDs) compared to those not using DMARDs.

Methods:

Cross-sectional secondary data analyses were conducted on Medicare Current Beneficiary
Survey (MCBS) data from 2017 and 2018. The MCBS data consists of a nationally representative
sample of the Medicare population, a population that is largely 65 and older, and provides
de-identified patient information. Patients from this dataset with a self-reported autoimmune disorder
were included in the analyses. Descriptive analyses were conducted on demographic variables,
chronic conditions, and medication use. The prevalence of AD and/or dementia was compared between
patients with and without an autoimmune disorder. A backward stepwise selection regression
was used to identify the risk factors associated with the prevalence of AD and/or dementia.

Results:

The study included 18,929 Medicare beneficiaries, with 4,405 identified as having one autoimmune
disorder. The prevalence of AD and/or dementia was significantly higher in patients
with an autoimmune disorder. The multivariate regression showed that RA was significantly associated
with a higher risk of AD and/or dementia. Other demographic factors, including advanced
age, African-American or Hispanic ethnicity, low body mass index, and chronic conditions of ischemic
heart disease, history of myocardial infarction, history of stroke, depression, mental health
disorder(s), and traumatic brain injury also showed statistically significant associations with AD
and/or dementia. Patients using DMARDs demonstrated a reduced likelihood of having AD
and/or dementia, compared to patients not using DMARDs.

Conclusion:

This study provides evidence of an association between RA and increased risk of AD
and/or dementia. The findings suggest that DMARD use may have a protective effect against the
development of AD and/or dementia in patients with an autoimmune disorder.
Sedation with Ketamine-Propofol in Patients Undergoing Transcatheter
Aortic Valve Implantation: A Comparative Retrospective Study on
General Anesthesia
Authors: Yilmaz Nurdan , Gul Yasar Gokhan , Ugurlucan Murat
Published: January 2024

Background:

Transcatheter aortic valve implantation (TAVI) is used for patients with
severe aortic stenosis who are at high risk for surgery. Since these patients are elderly and have
comorbidities, their management is of great importance.

Objectives:

This retrospective study compares two anesthesia techniques during TAVI: sedation (ketamine
and propofol) and general anesthesia.

Methods:

Patients with severe aortic stenosis undergoing TAVI during 2021 in our hospital were
retrospectively screened. Demographic data, comorbidities, anesthesia management, complications,
and mortality of the patients were obtained from the records.

Results:

There were 137 patients treated with TAVI; 74 (54%) patients had sedation and 63 (46%)
had general anesthesia. When the anesthesia management was evaluated, no significant difference in
mortality was observed between the patients who received general anesthesia and sedation. After
univariate and multivariate logistic regression analyses were performed to investigate factors having
an impact on mortality, anemia (only in univariate analysis) in the whole study population was a statistically
significant risk factor for mortality in patients undergoing TAVI (p<0.014).

Conclusion:

There was no significant difference in mortality in terms of anesthesia management.
Anemia was a risk factor for mortality (only in univariate analysis) in the whole study population.
We concluded that conscious sedation with ketamine and propofol is effective and safe for TAVI
procedures compared to general anesthesia.
Facile Synthesis and Antitumor Activity of o-Iodoaromatic Ether
Authors: Mao Xiaoxia , Zhang Yuying , Wang Keyang , Zhao Guiqin , Zhou Dejun , Cui Zhengguo
Published: January 2024

In this study, an efficient method for the synthesis of one type of aromatic ether was introduced,
and its antitumor activity was investigated. Specifically, (diacetoxyiodo)arene was prepared
from 2-methyliodobenzene and used to oxidize the 4-nitrophenol to give the aromatic ether. Our
study further found that aromatic ether has a strong apoptotic effect on U937 monocytes, suggesting
that it might be developed as a new drug for the treatment of acute myeloid leukemia.
Exploring the Promising Role of Guggulipid in Rheumatoid Arthritis
Management: An In-depth Analysis
Authors: Sahu Amit , Rathee Sunny , Jain Sanjay Kumar , Patil Umesh Kumar
Published: January 2024

Background:

Guggulipid, an oleo-gum resin extracted from the bark of Commiphora
wightii of the Burseraceae family, holds a significant place in Ayurvedic medicine due to its historical
use in treating various disorders, including inflammation, gout, rheumatism, obesity, and lipid
metabolism imbalances.

Objective:

This comprehensive review aims to elucidate the molecular targets of guggulipids and
explore their cellular responses. Furthermore, it summarizes the findings from in-vitro, in-vivo,
and clinical investigations related to arthritis and various inflammatory conditions.

Methods:

A comprehensive survey encompassing in-vitro, in-vivo, and clinical studies has been
conducted to explore the therapeutic capacity of guggulipid in the management of rheumatoid
arthritis. Various molecular pathways, such as cyclooxygenase-2 (COX-2), vascular endothelial
growth factor (VEGF), PI3-kinase/AKT, JAK/STAT, nitric oxide synthase (iNOS), and NFκB signaling
pathways, have been targeted to assess the antiarthritic and anti-inflammatory effects of
this compound.

Results:

The research findings reveal that guggulipid demonstrates notable antiarthritic and anti-inflammatory
effects by targeting key molecular pathways involved in inflammatory responses. These
pathways include COX-2, VEGF, PI3-kinase/AKT, JAK/STAT, iNOS, and NFκB signaling
pathways. in-vitro, in-vivo, and clinical studies collectively support the therapeutic potential of
guggulipid in managing rheumatoid arthritis and related inflammatory conditions.

Conclusion:

This review provides a deeper understanding of the therapeutic mechanisms and potential
of guggulipid in the management of rheumatoid arthritis. The collective evidence strongly
supports the promising role of guggulipid as a therapeutic agent, encouraging further research and
development in guggulipid-based treatments for these conditions.
Curcumin and Curcumin Derivatives for Therapeutic Applications:
In vitro and In vivo Studies
Authors: Gupta Babita , Sharma Pramod Kumar , Malviya Rishabha , Mishra Prem Shankar
Published: January 2024

:

Curcumin is a naturally derived phytochemical compound obtained from the turmeric
plant Curcuma longaL. (Zingiberaceae family), which is a popular spice and food color and has
been actively researched for decades. It has been shown to have a variety of pharmacological properties
both in vitro and in vivo. Several investigations have shown that curcumin's metabolites contribute
to its pharmacological effectiveness. Curcumin has potent anti-inflammatory and anti-tumor
activity when used alone or in conjunction with conventional treatments. There are various
unique and diverse pharmacological effects of curcumin against various disease conditions like diabetes,
inflammation, cancer, malaria, and Alzheimer's. The in vitro and in vivo mechanisms by
which curcumin exerts its pharmacological effects are reviewed. Based on data from the clinical
and experimental evaluation of curcumin in animal models and human subjects, the review summarizes
the pharmacological effect of curcumin and its derivatives concerning anti-tumor property,
their mechanism of action, and their cellular target. The current research focuses on identifying
curcumin's function in the immune system's cascade and determining the ideal effective dose
(ED50). Through in-vitro and in-vivo experiments, the current study aims to comprehend and
establish the role of curcumin in the healing of disease conditions.
Quality of Life Questionnaire for Infertile Women with Female Factor: Development and Psychometric
Authors: Kiani Zahra , Simbar Masoumeh , Hajian Sepideh , Zayeri Farid
Published: January 2024

Background:

The quality of life of infertile women is distinguished from that of men as
these women face different problems at individual, social, psychological, and family levels. However,
there is no tool for evaluating infertile women's quality of life.

Objective:

This study aimed to develop and validate a questionnaire to evaluate infertile women's
quality of life.

Methods:

This was exploratory sequential research. It was performed in two phases (qualitativequantitative)
on 320 infertile women who lived in Northern Iran. To confirm the validity of the
questionnaire, content, face, structural, and concurrent validities were used. The reliability of the
questionnaire was evaluated by assessing internal consistency and calculating Cronbach's alpha coefficient,
as well as using stability assessment by test-retest and Intra-cluster correlation coefficient
(ICC) calculation.

Results:

Following psychometric assessment, a questionnaire was developed with 25 items in seven
factors, including psychological effects, sexual life with infertility, family and social effects, infertility-
related concerns, physical effects, adaptive approaches, and inhibitory factors/factors preventing
adaptation), which explained 51.86% of the variance. The Cronbach's alpha coefficient and ICC
of the questionnaire were 0.87 and 0.97, respectively.

Conclusion:

This questionnaire with 25 items is a valid and reliable questionnaire to assess the
quality of life of infertile women with the female factor that can be used to find needs for improving
the client's quality of life.
Investigation of Medical Image Technology Based on Big Data Neuroscience in
Exercise Rehabilitation
Authors: Zhang Shuhua , Sun Jijin
Published: January 2024

Purpose::

The purpose of this article is to combine the functional information of CT images with the anatomical and soft tissue information of MRI through
image fusion technology, providing more detailed information for rehabilitation treatment and thus providing a scientific basis for clinical
applications and better training plans.

Methods::

In this paper, functional brain imaging technology combining CT (computed tomography) and MRI (magnetic resonance imaging) was used for
image fusion, and SURF (accelerated robust feature) feature points of images were extracted. In this study, 40 patients with mild and moderate
closed traumatic brain injury admitted to the rehabilitation department of a rehabilitation center from 2018 to 2022 were selected as the research
objects.

Results::

Compared with using only CT images and MRI images for brain injury diagnosis, the fusion image had a higher detection rate of abnormal brain
injury diagnosis, with a detection rate of 97.5%. When using fused images for the diagnosis of abnormal brain injury, the patient’s exercise
rehabilitation effect was better.

Conclusion::

CT and MRI image fusion technology had a high diagnostic accuracy for brain injury, which could timely guide doctors in determining exercise
rehabilitation plans and help improve the effectiveness of patient exercise rehabilitation
Medical Imaging and Analysis of Thermal Necrosis During Bone Grinding:
Implementation of Non-dominated Sorting Genetic Algorithm (NSGA-III) in
Healthcare
Authors: Babbar Atul , Jain Vivek , Gupta Dheeraj , Kumar Vidyapati , Pathri Bhargav Prajwal , Sharma Ankit
Published: January 2024

Background::

Medical imaging plays a key role in neurosurgery; thereby, imaging and analysis of the soft and hard tissues during bone grinding is of paramount
importance for neurosurgeons. Bone grinding, a minimally invasive operation in the field of neurosurgery amid osteotomy, has been used during
brain cancer surgery.

Aims and Objectives::

With increasing attention to neural tissue damage in machining operations, imaging of these neural tissues becomes vital and reducing temperature
is imperative.

Methods::

In the present study, a novel attempt has been made to perform the imaging of bone tissues during the bone grinding procedure and further
investigate the relationship between rotational speed, feed rate, depth of cut with cutting forces, and temperature. The role of cutting forces and
temperature has been addressed as per the requirements of neurosurgeons. Firstly, a three-factor, three-level design was constructed with a full
factorial design. Regression models were employed to construct the models between input parameters and response characteristics. Medical
imaging techniques were used to perform a thorough analysis of thermal necrosis and damage to the bone. Subsequently, the non-dominated
sorting genetic algorithm (NSGA-III) was used to optimize the parameters for reduction in the cutting forces and temperature during bone grinding
while reducing neural tissue damage.

Results::

The results revealed that the maximum value of tangential force was 21.32 N, thrust force was 9.25 N, grinding force ratio was 0.453, torque was
4.55 N-mm, and temperature was 59.3°C. It has been observed that maximum temperature was generated at a rotational speed of 55000 rpm, feed
rate of 60 mm/min, and depth of cut of 1.0 mm. Histopathological imaging analysis revealed the presence of viable lacunas, empty lacunas,
haversian canals, and osteocytes in the bone samples. Furthermore, the elemental composition of the bone highlights the presence of carbon (c)
59.49%, oxygen (O) 35.82%, sodium (Na) 0.11%, phosphorous 1.50%, sulphur 0.33%, chlorine 0.98%, and calcium 1.77%.

Conclusion::

The study revealed that compared to the initial scenario, NSGA-III can produce better results without compromising the trial results. According to
a statistical study, the rise in temperature during bone grinding was significantly influenced by rotating speed. The density of osteocytes in the
lacunas was higher at lower temperatures. Furthermore, the results of surface electron microscopy and energy dispersive spectroscopy revealed the
presence of bone over the surface of the grinding burr, which resulted in the loading of the grinding burr. The results of the present investigation
will be beneficial for researchers and clinical practitioners worldwide.
Environment-friendly Simple, and Straight forward Approach Towards the C-4 functionalization of (2S)-5-oxoproline Methyl Ester
Authors: Panday Sharad Kumar , Kumar Munish
Published: January 2024

Background:

4-Substituted- 5-oxo-prolinates (pyroglutamates) are important components
in various natural products, e.g. (-)-bulgecinine, (-)-anatoxin, salinosporamide, as well as
ACE inhibitors.

Aim:

These also act as important intermediates in the synthesis of many of the bioactive molecules.
Due to these reasons, the synthesis of 4-substituted-(2S)-5-oxo-prolinates has received
much attention over the globe in the last three decades. However, most of the synthetic strategies
available in the literature describe either the use of expensive lithium enolate-derived lowtemperature
chemistry or the rigorous reaction conditions, and therefore, a simple, environmentfriendly,
and cost-effective approach was truly demanding.

Methods:

In our ongoing research program, we required different 4-substituted pyroglutamates as
intermediates, and with that very basic objective, we were looking for an alternate strategy which
should be simple, requiring cheap reagents and consequently, in the process, it was thought to
attempt proline catalyzed aldol/alkylation reactions on pyroglutamates, and the idea provided excellent
outcome.

Results:

Herein we wish to report the L-proline catalyzed asymmetric functionalization at C-4 of
(2S)-5-oxoproline methyl ester, which furnished desired products at room temperature at the
same time, not requiring expensive reagents and, therefore, in turn, cost-effective.

Conclusion:

This new strategy explored for synthesizing 4-substituted pyroglutamates could be
useful for researchers across the globe working in the area and requiring substitution at C-4 of
pyroglutamates for synthesizing bioactive molecules/natural products.