bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modality Matching for Efficient and Precise Text Interpretation: Experimentation with Large Language Models
Authors: Fa Xide , Zhu Weiwen , Liu Shaoqiang , Li Zheng , Huang Honghong 
Published: October 2024

Abstract

Language models have increasingly been tasked with interpreting complex and domain-specific texts, requiring both precision and efficiency in handling vast amounts of data. Modality matching introduces a novel technique that aligns different input modalities to enhance text interpretation by ensuring more consistent and coherent outputs, particularly when multimodal data is involved. The modifications to the Mistral model, including modality-aligned input layers and reconfigured attention mechanisms, led to significant improvements in both accuracy and computational efficiency. Experiments demonstrated that modality matching reduced memory usage and computational costs while increasing interpretative precision, particularly in tasks involving domain-specific terminology. By refining how multimodal data is processed, the study presents a robust and scalable approach to improving the overall performance of language models in complex NLP applications. Modality matching ultimately offers a highly adaptable framework, enabling more efficient text interpretation without sacrificing accuracy, even in real-time scenarios.
Discovering the Untouched Perspective of Endangered North American Herb Actaea racemosa
Authors: Kharumnuid Genevive , Pal Rashmi Saxena , Pal Yogendra , Chaitanya Motamarri Naga Lalitha , Srivastava Preeti 
Published: October 2024

Abstract:
Actaea racemosa (AR), sometimes also known as black cohosh, is a perennial herb
that grows in the Ranunculaceae family that effloresces in the middle of summer. This herb is
currently present throughout south and west North America despite being endangered in the
eastern section of the continent. Certain information about the photochemistry and biological potential
of this herb is available. In accordance with the scant available ethno-medical reports, this
herb possesses antioxidant, antidiabetic, anti-inflammatory, antiosteoporosis, and anticancer
properties. As per the available literature, caffeic acid, isoferulic acid, actein, 23-epi-26 deoxycatein,
cimicifugoside, and ferukinolic acid are the key components found in different parts of
AR. To date, no thorough research or systematic review has been done to highlight the traditional,
biological, and phytochemical benefits of this herb. Consequently, further research is needed
to gain a deeper understanding of this therapeutic herb, particularly about its separation and
pharmacological screening of its insulating portion for a range of biological functions. The goal
of this review was to compile the most recent data on the phytochemical presence of AR. in relation
to its ethnomedical applications, methods of extraction, pharmacological aActaea racemosa (AR), sometimes also known as black cohosh, is a perennial herb
that grows in the Ranunculaceae family that effloresces in the middle of summer. This herb is
currently present throughout south and west North America despite being endangered in the
eastern section of the continent. Certain information about the photochemistry and biological potential
of this herb is available. In accordance with the scant available ethno-medical reports, this
herb possesses antioxidant, antidiabetic, anti-inflammatory, antiosteoporosis, and anticancer
properties. As per the available literature, caffeic acid, isoferulic acid, actein, 23-epi-26 deoxycatein,
cimicifugoside, and ferukinolic acid are the key components found in different parts of
AR. To date, no thorough research or systematic review has been done to highlight the traditional,
biological, and phytochemical benefits of this herb. Consequently, further research is needed
to gain a deeper understanding of this therapeutic herb, particularly about its separation and
pharmacological screening of its insulating portion for a range of biological functions. The goal
of this review was to compile the most recent data on the phytochemical presence of AR. in relation
to its ethnomedical applications, methods of extraction, pharmacological applications, and
future potential.pplications, and
future potential.
The Anti-Leukemic Activities of Campesterol and Α-Tocopherol Against BCL-2 Target through Computational Drug Design Approaches
Authors: Agbeniyi Oluwayemisi Titobioluwa , Kumar Neeraj , Kuthi Najwa Ahmad , Okunola Yinka , Akingbade Tomilola Victor , Olowosoke Christopher Busayo , Kehinde Idayat Oyinkansola , Victor Omoboyede , Umar Haruna Isiyaku , Dev Bairagi Rahul , Bin Jardan Yousef A. , Bourhia Mohammed 
Published: October 2024

Introduction:
Heterogeneous Acute Myeloid Leukemia (AML) causes substantial
worldwide morbidity and death. AML is characterized by excessive proliferation of immature
myeloid cells in the bone marrow and impaired apoptotic regulator expression.

Method:
B-Cell Lymphoma 2 (BCL-2), an anti-apoptotic protein overexpressed in AML, promotes
leukemic cell survival and chemoresistance. Thus, reducing BCL-2 may treat AML. Anticancer
activities are found in Aloe barbadensis Miller (Aloe vera). Thus, this work used molecular
modeling to assess Aloe vera bioactive chemicals as BCL-2 inhibitors. Molecular docking simulation
showed that all identified Aloe vera phytocompounds have strong BCL-2 binding affinities
(-6.7 to -8.7 kcal/mol).

Result:
Campesterol and α-tocopherol were identified as promising compounds for BCL-2 inhibitor
research based on their drug-likeness, pharmacokinetics, and toxicity profiles. The stability
and conformational of the BCL-2-compound complexes showed that the compounds were stable
in BCL-2's binding pocket.

Conclusion:
Campesterol and α-tocopherol are promising BCL-2 inhibitors that might become effective
anti-leukemic therapies with additional in vitro and in vivo research.

conclusion:
The stability and conformational of the BCL-2-compound complexes showed that the compounds were stable in BCL-2&amp;#039;s binding pocket.
Campesterol and α-tocopherol are promising BCL-2 inhibitors that might become effective anti-leukemic therapies with additional in vitro and in vivo research.
Long Non-coding RNAs: Potential Diagnostic and Treatment Targets for Non-small Cell Lung Cancer
Authors: Li Rizhu , Li Yepeng , Chen Hongming , Gao Jie , Liew Fong Fong 
Published: October 2024

Abstract:
Lung cancer is the leading cause of cancer-related deaths globally, necessitating ongoing
scientific research to understand its detection, treatment, and prevention. Long non-coding
RNAs (lncRNAs) are a diverse group of non-coding RNAs that play crucial roles in regulating tumorigenic
processes, such as cell proliferation, invasion, and metastasis in non-small cell lung cancer
(NSCLC). Despite not encoding proteins, lncRNAs have significant impacts on the development
and progression of NSCLC. Recent evidence suggests that lncRNAs may serve as valuable
biomarkers for diagnosing and prognosticating NSCLC through tissue or blood analysis, and as potential
therapeutic targets. This review provides a comprehensive overview of recent advancements
in lncRNA research for NSCLC, offering new insights into their mechanisms of action and
potential therapeutic applications. It also explores promising avenues for therapeutic development.
By elucidating the complex roles of lncRNAs in NSCLC, this article aims to contribute to the development
of innovative diagnostic and therapeutic strategies that can significantly enhance patient
outcomes. Understanding the multifaceted functions of lncRNAs in lung cancer has the potential
to lead to substantial progress in early disease detection, targeted treatments, and personalized
medicine, ultimately improving the prognosis and quality of life for individuals affected by this devastating
disease.
Electrochemical Determination of Tartrazine and Carmoisine Dyes from Aqueous Solutions on Modified Electrodes
Authors: Jabeen Shaista , Bano Shah , Ahmed Safeer 
Published: October 2024

Introduction:
The recognition of the health hazards of azo dyes has highlighted the need
to develop efficient, rapid, and reliable analytical methods for dye determination.

Method:
In this work, electrochemical probing of the azo group of Tartrazine (TZ) and Carmoisine
(CR) in food dyes was carried out. Synthesized bismuth and zinc oxide nanoparticles were used to
modify Graphite Electrode (GE).

Results:
Electrochemical analysis showed a much better electrochemical response using ZnO+Bi/GE
as a modifier than individually nanoparticle-modified graphite electrodes. From the CV analysis, it
was found that both the dyes exhibited irreversible electrochemical behavior, and the redox parameters
were calculated. The Limit of Detection (LOD) values recorded for TZ and CR for ZnO+Bi/GEbased
sensors were 0.84 uM and 2.80 uM, respectively. The obtained sensitivity values were 11.86
uA/uM/cm2 for TZ and 17.3 uA/uM/cm2 for CR.

Conclusion:
The sensor evidently demonstrated reliable simultaneous detection of both dyes, making
it suitable for practical applications in food safety analysis.
Exploring Innovations in Transdermal Drug Delivery: Microneedle Technologies and the Latest in Patent Developments
Authors: K. Rathod Prachi , Rathod Niravsinh , Vora Pratik Ashwinbhai , Prajapati Bijal , Dharamsi Abhay , Patel Rakesh 
Published: October 2024

Introduction/Objective:
Microneedle technology has emerged as a promising approach for
drug delivery, offering advantages such as improved patient compliance and enhanced therapeutic
efficacy. This review aims to provide a comprehensive overview of recent advancements in microneedle-
based drug delivery systems, emphasizing their potential to overcome limitations associated with
traditional transdermal drug delivery methods. The objective is to synthesize existing knowledge,
identify key trends, and highlight potential applications of microneedle technology in various medical
fields.

Methods:
A systematic approach was employed to select and analyse relevant studies on microneedle
technology. Databases were searched for peer-reviewed articles published and patents or patent applications
worldwide within the last decade, focusing on innovations in microneedle materials, design,
fabrication techniques, and applications. Studies were evaluated based on their methodology,
outcomes, and relevance to current trends in drug delivery. Key data were extracted and synthesized
to provide an integrated perspective on the state of microneedle technology.

Results:
The review highlights significant progress in microneedle technology; innovations in materials,
fabrication techniques, and applications. Advancements include biodegradable microneedles,
vaccine drug delivery systems, and integration with biosensors. Innovations led to improved drug
bioavailability and reduced side effects. Challenges such as scalability, standardization, and regulatory
considerations were also identified.

Conclusion:
In conclusion, microneedle technology has evolved significantly, offering a versatile
platform for controlled drug delivery and various medical applications. The diversity in design and
fabrication methods allows customization for specific therapeutic or diagnostic needs, with numerous
patents filed for microneedle innovations, reflecting the intense research and development in this
field.
The Association between Gallstone Disease and Incidence of Cardiovascular Disease: A Systematic Review and Meta-Analysis
Authors: Rahimi Rasoul , Heidari-Soureshjani Saeid , Sherwin Catherine MT , Kasiri Karamali , Rahimian Ghorbanali 
Published: October 2024

Background:
Gallstone Disease (GSD) is a multifactorial risk factor for various complications.

Objective:
This study aimed to examine the relationship between GSD and Cardiovascular Disease
(CVD) incidence through a systematic review and meta-analysis approach.

Methods:
A thorough search was conducted across Web of Science, Scopus, MEDLINE/PubMed,
Cochrane Library, and Embase databases. Only studies published between 1980 and December
2023 were included. Chi-square, I2, and forest plots were used to assess heterogeneity. Begg's and
Egger's tests were used to evaluate publication bias. Statistical significance was considered at p
<0.05, and all analyses were performed using Stata 17.

Results:
This meta-analysis involved 21 studies and comprised 2,138,282 participants; there has
been a significant association found between GSD and an increased risk of CVD (with a relative
risk of 1.46, 95% confidence interval: 1.32-1.63, p <0.001). The analysis found no evidence of
publication bias based on Begg's test (p =0.085) and Egger's test (p =0.231). Subgroup analysis of
the studies showed a higher risk of CVD in studies with a sample size of less than 10,000 participants,
conducted in 2016 or later, utilizing a cross-sectional design, in Asian countries; the analysis
had a moderate quality score, with a follow-up period of equal to or less than ten years.

Conclusion:
There has been a significant association found between GSD and an increased risk of
incidence of CVD. Taking proactive steps to implement targeted interventions for individuals with
gallstone disease could potentially reduce the risk of cardiovascular disease within this population.
Artificial Intelligence in Diabetes Mellitus Prediction: Advancements and Challenges - A Review
Authors: Awasthi Rohit , Mahavar Anjali , Shah Shraddha , Patel Darshana , Patel Mukti , Shah Drashti , Patel Ashish 
Published: October 2024

Abstract:
Poor dietary habits and a lack of understanding are contributing to the rapid global increase
in the number of diabetic people. Therefore, a framework that can accurately forecast a large
number of patients based on clinical details is needed. Artificial intelligence (AI) is a rapidly evolving
field, and its implementations to diabetes, a worldwide pandemic, have the potential to revolutionize
the strategy of diagnosing and forecasting this chronic condition. Algorithms based on artificial
intelligence fundamentals have been developed to support predictive models for the risk of developing
diabetes or its complications. In this review, we will discuss AI-based diabetes prediction.
Thus, AI-based new-onset diabetes prediction has not beaten the statistically based risk stratification
models, in traditional risk stratification models. Despite this, it is anticipated that in the near future, a
vast quantity of well-organized data and an abundance of processing power will optimize AI's predictive
capabilities, greatly enhancing the accuracy of diabetic illness prediction models.
Navigating into the Paradigm of Nose-to-brain Delivery of Nanotherapeutics and their Repurposing as Nanotheranostics for Neurodegenerative Diseases
Authors: Ali Asad , A. Emad Nasr , Sultana Niha , Waheed Ayesha , Aqil Mohd. , Sultana Yasmin , Mujeeb Mohd 
Published: October 2024

Abstract:
Repurposing drugs for neurodegenerative diseases using the nose-to-brain route of administration
is an intriguing concept with potential benefits. The nose-to-brain route involves delivering
drugs directly to the brain via the olfactory or trigeminal pathways, bypassing the blood-brain
barrier, which can improve drug efficacy and reduce systemic side effects. Treatment of numerous
neurodegenerative diseases such as Multiple sclerosis, Amyotrophic lateral sclerosis, Huntington's,
Alzheimer's, and Parkinson's diseases has been attempted using this route of administration. These
drugs may include neuroprotective agents, anti-inflammatory drugs, antioxidants, or diseasemodifying
therapies. Nanotheranostics, which integrates therapeutic and diagnostic functions in a
nanosystem, improves treatment precision and efficacy. Repurposing nanotherapeutics as nanotheranostics
for neurodegenerative diseases through the nose-to-brain route of administration holds
great potential for both diagnosis and treatment. This review highlights the various mechanisms engaged
in transporting nanocarriers from nose-to-brain and the proposed fate of these nanocarriers
using different live imaging techniques. Additionally, the discussion covers the recent combinatorial
therapeutic approaches and theranostic applications of various nanocarriers used for neurodegenerative
diseases through the nose-to-brain. Toxicity to the CNS and nasal mucosa and regulatory considerations
about these delivery systems are also deliberated. Overall, repurposed nanoparticles designed
as nanotheranostic agents offer a versatile platform for precise diagnosis, targeted therapy,
and personalized management of neurodegenerative diseases, holding great promise for improving
patient care and advancing our understanding of these complex disorders.
In vitro Characterization and Drug Release Studies of Ethambutol-Loaded Nanoparticles for Pulmonary Delivery
Authors: Jayronia Sonali , Singh Amrita , Mishra Sudhanshu 
Published: October 2024

Background:
The development of more effective drug delivery techniques is necessary
to increase treatment efficacy and patient compliance since tuberculosis (TB) is still a serious
worldwide health concern. Ethambutol is a vital aspect of TB treatment, and using nanoparticles to
carry it to the lungs may provide targeted delivery and prolonged release, which might enhance the
effectiveness of the treatment.

Objective:
This work aimed to optimize the formulation for prolonged drug release by synthesizing
and assessing ethambutol-loaded nanoparticles using the desolation technique with albumin as the
polymer. Additionally, the effects of different drug-polymer ratios and stirring rates were investigated.

Methods:
Nine formulations of ethambutol-loaded nanoparticles were prepared by varying the
drug-polymer ratios (1:1 to 1:2) and stirring speeds (500 to 1500 rpm). Key parameters, such as
particle size, drug entrapment efficiency, and zeta potential, were measured. The optimized formulation
was selected based on the smallest particle size and highest drug entrapment efficiency.
Scanning electron microscopy was used to analyze the surface morphology of the nanoparticles.
The in vitro drug release profile of the optimized formulation was studied over 24 hours.

Results:
Increasing the drug-polymer ratio from 1:1 to 1:2 increased nanoparticle size from 192.1
nm to 605.06 nm and decreased drug entrapment efficiency from 75.7%±0.08 to 34%±0.06. Higher
stirring speeds (500 to 1500 rpm) also led to larger particle sizes and reduced drug entrapment due
to polymer self-aggregation. Zeta potential values ranged from -5.56 to -25.6 mV. Scanning electron
microscopy confirmed smooth, spherical nanoparticles. The optimized formulation, EN-5, exhibited
the smallest particle size and highest drug entrapment efficiency. In vitro drug release studies
showed a sustained ethambutol release, with 42.66±1.53% released in 12 hours and
79.082±2.98% in 24 hours.

Conclusion:
Ethambutol-loaded nanoparticles having the ability to transport drugs to the lungs
over an extended period of time were developed and optimized in the study. With improved drug
delivery systems, the optimized formulation showed notable drug entrapment efficiency and controlled
release, suggesting its potential to improve tuberculosis therapy.
Data Collection and Recharging of Sensor Node by Mobile Sink in Wireless Sensor Network
Authors: Zafor Hanif , Ali Sheikh Tasher , Mazumdar Nabajyoti , Nag Amitava 
Published: October 2024

Abstract:
The wireless sensor network (WSN) has limited battery and storage capacity. The main
challenge in static sink nodes is the lack of energy and data transfer to the base station (BS). A mobile
sink (MS) is an excellent way to handle these difficulties in WSN. The use of an MS solution
not only ensures long-term network functionality, but also improves network performance. In this
paper, the MS-based data collection and recharging, mobile device is used for data collection from
sensor nodes and recharging the sensor nodes throughout the network whenever required. There are
two types of MS-based solutions described as (i) Mobile devices for data collection from sensor
nodes in the network. (ii) Mobile device for collecting data and recharging sensor nodes from the
network. Finally, in this paper, we presented the advantages, disadvantages, and other criteria of
both types. Also, a potential framework is presented for data collection and recharging of sensor
nodes by MS in WSN. The core contribution of this paper is present the state of art and future
roadmap for data collection and recharging of sensor nodes by MS in WSN. The identification of
the main open challenges and future direction in this research area are also highlighted and discussed.
Deep Learning-Based Network Security Situation Prediction for Sensor-Enabled Networks
Authors: Indrasenareddy M , Sudhakar Kattupalli , Raguru Jaya Krishna , Chitra D , Kavitha J , Thakur Gopal Kumar , Reddy Pundru Chandra Shaker 
Published: October 2024

Aims and background:
Network security detection has become increasingly complex
due to the proliferation of Internet nodes and the ever-changing nature of network architecture. To
address this, a multi-layer feedforward neural-network has been employed to construct a model for
security threat detection, which has enhanced network security protection.

Objectives and Methods:
Improving prediction accuracy and real-time performance, this research
suggests an optimal strategy based on Clockwork Recurrent-Neural-Networks(CW-RNNs) to handle
nonlinearity and temporal dynamics in network security circumstances. We get the model to
pick up on both the short-term and long-term temporal aspects of network-security situations by using
the clock-cycle RNN. To further improve the network security scenario prediction model, we
tune the network hyperparameters using the Grey-Wolf-Optimization(GWO) technique. By incorporating
a clock-cycle for hidden units, the model can improve its pattern recognition capabilities
by learning short-term knowledge from high-frequency update modules and preserving long-term
memory from low-frequency update modules.

Results:
The optimized clock-cycle RNN achieves better prediction accuracy than competing network
models when it comes to extracting nonlinear and temporal characteristics of network security
scenarios, according to the experimental data.

Conclusions:
In addition, our method is perfect for tracking massive amounts of data transmitted by
sensor networks because of its minimal time complexity and outstanding real-time performance.
Invasomes: An Artificial Vesicle Nanocarrier to Enhance Transdermal Drug Delivery
Authors: Preeti  , Puri Dinesh , Singh Sanjay 
Published: October 2024

Abstract:
The greatest and most noticeable organ in the body is the skin. The stratum corneum, or top layer of skin, acts as a vital barrier to prevent skin penetration for many drugs. To over-come this barrier, numerous nanocarrier frameworks have been developed, which are important for the functioning of active agents. Vascular systems known as invasomes contain low levels of ethanol as well as terpenes or terpene combinations, which have a higher skin penetration rate and function as potential carriers. Improved drug delivery via the skin using a carrier that can pene-trate these barriers presents a wide range of difficulties and possibilities for further study and the creation of new and better treatment options. The main objective of an invasome-based delivery system is to significantly improve patient compliance and therapeutic value, in addition to bol-stering the safety and efficacy of the drug. This article gives a summary of the synthesis process, invasome characterizations, penetration mechanisms, and applications. This review paper also in-cludes phospholipids and their classification. Phospholipids are present in the cell membrane and provide ceramide, a bioactive molecule that moisturizes skin and protects against environmental damage in transdermal drug delivery systems. Pharmaceutical studies demonstrate that many drug molecules have less solubility, stability, bioavailability, and penetrating power. Invasomes repre-sent a novel dosage form with promising properties for enhancing transdermal drug delivery.