bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of a high-protein and low-glycemic-index diet during pregnancy with offspring growth and obesity until the age of 18 years – a target trial emulation
Authors: Mogensen Christina , Mølgaard Christian , Magkos Faidon , Geiker Nina , Bjerregaard Anne , Granström Charlotta , Halldorsson Thorhallur , Olsen SF
Published: September 2024

Background
Maternal pre-pregnancy BMI and excessive gestational weight gain (GWG) are associated with offspring obesity. Moreover, maternal dietary patterns, particularly protein intake and glycemic index, influence GWG and fetal development. This study aimed to investigate the association of a high-protein, low-glycemic-index (HPLGI) diet during pregnancy with offspring growth and obesity.
Methods
Using observational data from the Danish National Birth Cohort, a target trial emulation was conducted to investigate the association of an HPLGI diet during pregnancy on offspring growth up to 18 years of age. A cohort of 17,551 women who met the inclusion criteria were categorized into exposure groups based on their protein intake and glycemic index to emulate the groups in the APPROACH trial.
Results
Offspring outcomes were assessed at various ages and a linear mixed model was used including potential confounders. Offspring born to women following an HPLGI diet during pregnancy had 2.59 kg higher body weight and 0.72 kg/m2 higher BMI at 18 years compared to those from the moderate-protein, moderate-glycemic-index (MPMGI) group. Maternal characteristics varied between the exposure groups, with the HPLGI women exhibiting 1.67 kg higher pre-pregnancy weight and 0.49 kg/m2 BMI, with no differences in GWG.
Conclusion
Offspring born to women consuming an HPLGI diet during pregnancy had higher body weight and BMI at 18 years compared to offspring born to women on an MPMGI diet. These findings raise questions about the long-term implications of maternal dietary patterns on offspring health. Further research is needed to elucidate the mechanisms underlying these associations.
Prevalence of Intestinal Parasitic Infections and Associated Risk Factors Among Patients Attending Dejen Primary Hospital, Amhara National Regional State, Ethiopia
Authors: Demissie Simachew , Ameha Eyouel , Tigu Fitsum
Published: September 2024

Intestinal parasitic infections (IPIs) are the greatest worldwide cause of illness and disease. About 1.5 billion individuals have been infected by IPIs in 2023, of these the lion shares of the burden is found in Sub-Saharan African regions. This study aimed to assess the prevalence of IPIs and associated risk factors among patients attending Dejen primary Hospital. The study was conducted in the Amhara National Regional State of Ethiopia, East Gojjam Zone, Dejen town, Dejen primary hospital. Patients in all age groups attending the hospital during the study period were included in the study. A total of 414 study participants were determined by standard formula. The socio-demographics characteristics were collected by face-to-face interview using well-structured questionnaires. Stool samples were examined microscopically using a direct wet mount method. In this study, five known parasites identified including Entamoeba histolytica, Giardia lamblia, Hookworm, Taenia spp. and Strongyloides stercoralis. Among them, E. histolytica and G. lamblia belonged to the leading protozoan parasites with 26.1 and 9.2% prevalence, respectively. The rest, Hookworm, Taenia spp. and Strongyloides stercoralis, categorized as soil helminthic parasites and accounts 3.1, 0.7 and 0.2% prevalence, respectively. The prevalence of IPIs in the study area is highly associated with the occupation of the patients, consumption of raw vegetables, swimming practice in rivers and source of drinking water.
Broken Tooth Gear Fault Detection Using Vibration Signals Based on Convolutional Neural Network
Authors: Goswami Priyom , Rai Rajiv Nandan
Published: September 2024

Gear faults are a major concern in industrial settings, leading to performance degradation and potential system failures. This paper explores the use of Convolutional Neural Networks (CNNs) for broken tooth fault detection in gear systems. Traditional methods for fault detection rely on manual feature extraction from vibration signals, which can be time-consuming and may not capture all relevant information. CNNs, on the other hand, can automatically learn complex patterns from data, making them well-suited for this task. In this paper we develop a computationally tractable deep learning (DL) based CNN model that can be used for broken tooth fault diagnosis in various industrial settings, irrespective of the type of gearbox or gears being used. The authors further compare the performance of developed CNN model with traditional signal processing techniques and Support Vector Machine (SVM)-based classification. The CNN model achieved superior accuracy (98.6%) in distinguishing between broken and healthy teeth across various operating conditions for one experimental setup. For a second setup with a less severe broken tooth fault, the accuracy was 93%. In contrast, SVM models achieved a maximum accuracy of 90.7% using manually selected features. These findings underscore the superiority of the proposed deep learning (DL) based CNN model for broken teeth gear fault detection. Moreover, it exhibits greater resilience to fluctuations in operating conditions and fault types compared to conventional techniques. Comparisons with established deep learning models such as VGG16, AlexNet etc. demonstrate that the proposed model surpasses all others in terms of classification accuracy.
Spatiotemporal Assessment and Machine Learning-Based Future Forecasting of Groundwater Hydro chemical Dynamics and Drawdown Variability
Authors: Maqbool Sheraz , Khan Muhammad Imran , Raza Aamir , Saddique Naeem , Saddique Qaisar , Dong Liu , Tariq Muhammad Abdur Rehman , Ghani Mubarra Tahreem , Mujahid Maha , Buttar Noman Ali
Published: September 2024

Pakistan's groundwater resources are vital to the country's water supply, yet increasingly threatened by issues such as over-extraction, inadequate management practices, and insufficient conservation regulations. This study was conducted to examine spatiotemporal aquifer behavior, fluctuations in drawdown levels, and water quality parameters like pH, Electrical Conductivity (EC), Total Dissolved Salts (TDS), Calcium, Magnesium, Total Hardness (TH), Bicarbonates and Chlorides by using geospatial techniques to address sustainable groundwater resource management needs. For future forecasting four machine learning (ML) models were used; Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF). Observed data were obtained from Water and Sanitation Agency (WASA) Faisalabad from year 2013 to 2023 which included 29 inline field area well stations and 25 Japan International Cooperation Agency (JICA) well stations, and weather data from the Terra Climate dataset. Groundwater drawdown patterns and quality changes over time were analyzed by GIS-based spatial analysis by utilizing historical data to train and test predictive models for 2024-2028. The XGBoost model demonstrated exceptional performance in predicting drawdown pre-monsoon (8.35m) and post-monsoon (7.65m) until 2028 and hydro chemical quality, with an average R-squared value of 0.86, RMSE below 0.08, and MAE under 0.05 for both. The study's spatial analysis revealed significant seasonal variations, with post-monsoon increases in mineral concentrations due to intensified leaching processes and identified a concerning rise in chloride levels after 2022, linked to anthropogenic activities. These findings underscored the importance of advanced machine learning techniques, particularly XGBoost, in accurately forecasting groundwater dynamics and hydro chemical quality.
Quantification of ochratoxin A in a coffee sample utilizing an electrochemical aptasensor fabricated through encapsulation of toluidine blue within a Zn- based metal-organic framework
Authors: Amini–Nogorani Elaheh , Zare Hamid R. , Jahangiri–Dehaghani Fahime , Benvidi Ali
Published: September 2024

Due to the widespread presence of mycotoxins and their significant impact on both health and the economy, there is a clear need for a fast and cost-effective analytical tool to measure these harmful substances. In response to this, an electrochemical aptasensor has been developed specifically for the sensitive and selective determination of ochratoxin A (OTA), one of the most important mycotoxins. The aptasensor utilizes a glassy carbon electrode that has been modified with toluidine blue (TB) encapsulated in a Zn-based metal organic framework (TB@Zn-MOF). The results demonstrate that in the presence of OTA, the peak current of the differential pulse voltammogram (DPV) related to TB oxidation is notably decreased. The changes in the oxidation peak current of TB encapsulated in Zn-MOF, both in the absence and presence of OTA, serve as an analytical signal for accurately measuring its concentration. With the proposed aptasensor, OTA can be measured within a linear concentration range of 1.0 × 10− 4 − 200.0 ng mL-1, with a detection limit of 2.1×10− 5 ng mL-1. Furthermore, this aptasensor design is suitable for measuring OTA concentration in coffee powder samples. This represents the first report to utilize TB@Zn-MOF in designing an applicable aptasensor to OTA measurement. The high porosity of the Zn-MOF allows for a large number of TB molecules to be encapsulated in its cavities, while its large surface area enables more OTA aptamers to be immobilized on the electrode surface. These two key features significantly enhance the sensitivity of the aptasensor in measuring OTA concentration.
Impact of the East Asian subtropical westerly jet on the interannual variability of the South China Sea summer monsoon onset and associated precursory thermal forcing role of the Tibetan Plateau
Authors: Song Chengyu , Wang Jing , Liu Yanju , Ding Yihui
Published: September 2024

Based on the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and the Global Precipitation Climatology Project (GPCP) data, this study investigates the meteorological anomalies tied to the interannual variability of the South China Sea summer monsoon onset (SCSSMO), and its relationship with the change of the subtropical westerly jet position (SWJP), and the potential influence of the precursory thermal forcing over the eastern Tibetan Plateau (TP). The results show that during the earlier (later) SCSSMO years, there exist significant cyclonic (anticyclonic) circulation anomalies over the South China Sea (SCS) and its adjoining areas, featuring enhanced (suppressed) precipitation. The earlier SCSSMO years correspond to the southward-shifted upper-level subtropical westerly jet position to the north of the SCS. This favors the occurrence of non-geostrophic southward winds in the upper troposphere, the occurrence of upper-level divergence (convergence) and low-level convergence ascending (divergence) over the SCS and its nearby areas (Yangtze River basin) on the south (north) side of the jet axis, and the strengthening of the meridional circulation anomaly with anomalous ascending over the low-latitude and descending over the middle-latitude East Asia. Further analysis suggests that the anomalous heating over the eastern TP is significantly related to the SCSSMO and the change of SWJP. When the previous first-two-pentad heating anomalies over the eastern TP are positive, an anomalous anticyclonic circulation is formed in the upper troposphere, stimulating an eastward-propagating wave train. This, in turn, generates an anomalous cyclonic circulation downstream of the TP in the upper troposphere. As a result, the subtropical upper-level westerly jet downstream of TP shifts southward, which further affected the variation of atmospheric circulation over East Asia, ultimately leading to the earlier SCSSMO.
Licensing Exam Pass Rate Disparities in Marriage and Family Therapy: Using an Analysis of Predictive Factors to Inform a More Equitable Licensing Exam Process
Authors: Lyness Kevin , Gehart Diane , Hannigan Brian , Birge Barrie , Ross Sheiketha
Published: September 2024

This article describes the findings of a study that explored potential factors that influence the pass rate for those taking marriage and family therapy (MFT) licensing exams, both the national and California exams. An online, national survey was conducted to determine factors associated with passing the MFT licensing exams. The survey included measures of test anxiety, coping strategies, perceived stress, and experience of discrimination. The demographic results included patterns of racial and age disparities similar to those reported by the Association of Social Work Boards (2022), especially for Black respondents. Specific and readily implemented recommendations for making the current exams more equitable include (a) changing the phrasing of questions, (b) clarifying and reducing the scope of the content, (c) reducing the number of questions during the 4-hour period, and (d) ensuring adequate accommodations for disabilities.
Smart Driver Assistance: Real-Time Drowsiness Detection Using CNN and Computer Vision
Authors: Thampi Lidiya Lilly , Kashyap Kanchan Lata , T Neethu C , Reddy Ariveeti Karthikeya , Khan Ibrahim Ahmed , Aswathy M A , Kumar Abhishek , Kumar Sunny
Published: September 2024

The primary aim of this research is to identify driver drowsiness to prevent car accidents and improve road safety. This study explores and proposes potential solutions to mitigate drowsiness-related accidents and enhance overall road security by monitoring the indicators such as driver’s eye, mouth, and head movements. An algorithm has been developed to track these movements. This work includes analyzing CNN and computer vision models for eye detection, yawn detection, and head movement. The CNN models are trained by using MRL and YawDD datasets for eye and mouth tracking. In the computer vision approach, Dlib and MediaPipe library functions are used for tracking facial landmarks. In this approach also, three features namely, head & eye movements, and yawns are considered for drowsiness detection. Highest accuracy of 84.53% and 96.42% is obtained using CNN approach for MRL Eye and YawDD Dataset, respectively. Performance of the computer vision based approach is better as compared to CNN method.
Crystal structure of an AT-hook motif bound to DNA and inhibition by antikinetoplastid minor groove binders
Authors: Nué-Martínez J. Jonathan , Maturana Marta , Lagartera Laura , Gutiérrez Juan-Antonio Rodríguez , Boer Roeland , Campos J. Lourdes , Saperas Núria , Dardonville Christophe
Published: September 2024

High mobility group (HMG) proteins are intrinsically disordered nuclear non-histone chromosomal proteins that play an essential role in many biological processes by regulating the expression of numerous genes in eukaryote cells. HMGA proteins contain three DNA binding motifs, the “AT-hooks”, that bind preferentially to AT-rich sequences in the minor groove of B-form DNA. Understanding the interactions of AT-hook domains with DNA is very relevant from a medical point of view because HMGA proteins are involved in different conditions including cancer and parasitic diseases. We present here the first crystal structure (1.40 Å resolution) of the HMGA AT-hook 1 domain, bound to the minor groove of AT-rich DNA. The binding affinity and thermodynamics of binding were studied in solution with surface plasmon resonance (SPR)-biosensor and isothermal titration calorimetry (ITC) experiments. AT-hook 1 forms an entropy-driven 2:1 complex with (TTAA)2-containing DNA with relatively slow kinetics of association/dissociation. We show that N-phenylbenzamide-derived antikinetoplastid compounds (1–3) bind strongly and specifically to the minor groove of AT-DNA and compete with AT-hook 1 for binding. These findings provide clues regarding a mode of action of DNA minor groove binding compounds that are relevant to major neglected tropical diseases such as leishmaniasis and trypanosomiases.
Channel Estimator Endorsed Rate AdaptationAlgorithm for IEEE 802.11 Standards
Authors: C SMERA , J SANDEEP
Published: September 2024

Rate adaptation is an essential mechanism in the WLAN network to enhance network performance. The latest amendments of IEEE 802.11 standards introduced a large number of rate levels. Traditional rate adaptation algorithms are inadequate to manage large rate search space and the interference created by an increasing number of devices. In this paper, a new rate adjustment approach, ChannelEstimator Endorsed Rate Adaptation (CEERA) is designed, implemented, andanalysed using a network simulation tool. This algorithm used the Block acknowledgment and RSSI effectively to identify the channel conditions. A weighted value obtained by processing these two parameters was used for rate selection. The research was simulated using NS3 for different network scenarios. Results were evident for the improved performance of the CEERA algorithm when compared with the RaCa. The result also shows that it consumes lower energy than the RaCA with improved packet delivery ratio and throughput.
MJO representation in the Community Earth System Model 2 Large Ensemble: detection, seasonality and amplitude
Authors: Henderson Gina R , Hottovy Scott , Barrett Bradford S.
Published: September 2024

The Madden-Julian Oscillation (MJO) is the leading mode of tropical intraseasonal variability in the atmosphere and impacts weather and climate, both locally in the tropics as well as globally through tropical–extratropical interactions. Various metrics have been used to classify the intensity and character of the MJO. One popular metric is the Real-time Multivariate MJO (RMM) index, which is based on an empirical orthogonal function (EOF) of zonal winds at 850 hPa and 200 hPa and outgoing longwave radiation (OLR). To date, many climate models have struggled to reproduce a realistic MJO RMM signal, due to issues associated with model tropical convective schemes and failure to capture the eastward propagation of the MJO circulation. In this study, we assess the seasonality and amplitude of the MJO in the CESM2 Large Ensemble version 2 (CESM2-LE) experiment. We reproduce the RMM index from model output to explore the utility of OLR versus precipitation in MJO representation. Overall, we find that the model climatologies of MJO look similar to those present in the NCEP–NCAR reanalysis (for winds) and NOAA polar-orbiting satellites (for OLR). Both OLR and precipitation are found to be good indicators of MJO activity. When considering MJO amplitude over four categories (inactive, RMM < 1.0; active, RMM > 1.0; very active, RMM > 1.5; and extremely active, RMM > 2.5) the CESM2-LE model tends produce more inactive and fewer very active MJO events. Dynamically, MJO events in the CESM2-LE model are slower to propagate and weaker than observed. This is further demonstrated by model tendencies for strong MJO events to transition to weaker events faster than observed, particularly over the Indian Ocean and Maritime Continent.
Post-harvest Quality of Red Bell Pepper: Effect of Ozonized Mist and Protective Film
Authors: Sitoe Eugénio da Piedade Edmundo , Usberti Franciane Colares Souza , Aguiar Rosa Helena , Pedro Cesar
Published: September 2024

This study investigates the effectiveness of ozonized mist and protective film in preserving red peppers during storage. Ozonized mist was applied at 20.10 mg L⁻¹ and 2.0 L min⁻¹ for 5, 10, and 15 minutes, with and without a protective film, and compared to untreated controls and chlorine treatment. Stored at 25°C and 60% relative humidity for 21 days, peppers treated with ozonized mist exhibited significant reductions in mold and yeast counts, with the 15-minute treatment achieving reductions of 4.00 logs for molds and 4.34 logs for yeasts, surpassing chlorine treatment. The protective film effectively minimized mass loss and preserved the peppers’ commercial appearance. Importantly, the combination of ozonized mist and protective film did not significantly affect the peppers’ physico-chemical quality. These findings suggest that ozonized mist and protective film are effective for reducing post-harvest losses in bell peppers, offering practical benefits for the storage sector.
CMFF_VS：A Video Summarization Extraction Model based on Cross-modal Feature Fusion
Authors: Xin Chaoqun , Wang Mingyang , Zhao Xianhao
Published: September 2024

Video summarization aims to present the most relevant and important information in the video stream in the form of a summary. Most existing researches focus on the selection process of keyframes, determining the importance of video frames by obtaining dependency information between them. However, these works overlook the feature extraction process of video frames. In fact, rich and reliable video frame features are an important basis for determining whether video frames can be selected correctly. This article proposes a cross-modal video summarization extraction model CMFF_VS by extracting deep semantic information from video frames. CMFF_VS model utilizes the mutual enhancement of video modality and text modality to extract richer semantic information of video frames, thereby providing necessary features for the subsequent video frame selection process. To solve the alignment problem between semantic information of two modalities, CMFF_VS introduces a cross-modal attention mechanism, which utilizes the semantic correlation of modalities to achieve cross-modal semantic fusion. At the same time, CMFF_VS introduces the ASPP module to extract and fuse multi-scale semantic features of individual modalities, enriching the capture of advanced semantic information for each modality. The experimental results show that compared with the state-of-art unimodal and multimodal video summarization models, CMFF-VS achieves the best performance, indicating that the cross-modal deep feature extraction and fusion strategy proposed in CMFF-VS is reasonable and effective.
Ransomware Classification Using BTLS Algorithm and Machine Learning Approaches
Authors: Wasoye Samuel , Stevens Michael , Morgan Christopher , Hughes David , Walker James
Published: September 2024

Ransomware attacks have become one of the most severe threats in cybersecurity, causing significant financial and operational damage to organisations worldwide. The ability to accurately classify ransomware, especially in real-time, is critical to limiting the impact of these attacks, yet existing detection methods often struggle with the rapid evolution of ransomware variants. A novel approach is proposed through the integration of the Binary Transformation and Lightweight Signature (BTLS) algorithm with machine learning models, aiming to enhance the accuracy and efficiency of ransomware detection. The BTLS algorithm allows for the extraction of both static and dynamic features from ransomware samples, enabling more comprehensive analysis and classification. The experimental results demonstrate that the combined feature sets significantly improved classification accuracy, while the reduction in false positives highlights the algorithm’s practicality for real-world deployment. The proposed system offers a scalable solution capable of adapting to novel ransomware variants, addressing the limitations of traditional detection techniques and advancing the state of machine learning-driven cybersecurity solutions.
Computation of Separate Product and Ratio Exponential Estimators Under Neutrosophic Stratified Sampling: Application to Climate Data
Authors: Singh Abhishek , Patkar Vedangee Gunesh , Kulkarni Hemant , Vishwakarma Gajendra K.
Published: September 2024

Within the confines of this article, we unveil a ground-breaking methodology, introducing for the first time product, product and ratio exponential estimators within the framework of neutrosophic stratified sampling an endeavour that integrates auxiliary variables. A comprehensive analysis has been executed theoretically, and through artificial and real data to assess the bias and mean square error (MSE) of these novel estimators, reaching up to the first-order approximation. Our findings unequivocally showcase the superior performance of these estimators in comparison to conventional unbiased counterparts. Additionally, our research underscores the heightened reliability inherent in neutrosophic stratified estimators when juxtaposed with classical stratified estimators.
Mathematics Subject Classification: 62D05, 62A86.
Investigating the influence of social media influencer credibility on beauty product purchase behaviors: a case study from Vietnam
Authors: Khuong An Gia , Thuy An Ngo Thi , Tu Tran Thanh , Thy Nguyen Phuong
Published: September 2024

The growing dominance of social media as a marketing platform underscores the importance of understanding how influencer credibility affects consumer behavior. Social media influencers, through effective personal branding and content creation, form strong connections with their followers, significantly impacting their audience’s perceptions, attitudes, and purchasing decisions. This study explores the effects of social media influencers’ source credibility, comprising trustworthiness, expertise, and attractiveness, on consumers’ purchase intentions and behaviors regarding beauty products in Vietnam. A quantitative approach was utilized, with data collected from 269 Vietnamese consumers through a structured questionnaire and analyzed using partial least squares structural equation modeling. The results showed that all three components of source credibility, including trustworthiness, expertise, and attractiveness, significantly and positively influenced consumers’ purchase intentions for beauty products. Among these factors, expertise had the strongest effect on purchase intention (β = 0.289, p < 0.001), followed by trustworthiness (β = 0.216, p = 0.001), and attractiveness had the weakest influence on purchase intention (β = 0.195, p < 0.001). Moreover, purchase intention was found to have a significant positive impact on purchase behavior (β = 0.545, p = 0.004). These findings provide valuable insights for marketing managers and companies seeking to optimize their influencer partnerships by selecting influencers whose credibility aligns with their brand values and leveraging their expertise to build consumer trust, drive engagement, and influence purchase decisions.
AcknowledgementThe researchers express sincere gratitude to all the participants who participate in this research study.
Joint Effect of Working Conditions and Wages on Labor Shortage in Healthcare
Authors: Merkulov Nikolay , Anisimov Aleksandr
Published: September 2024

Healthcare quality depends on medical personnel, i.e., motivation, professional burnout, work-life balance, etc. The authors used standard research methods to investigate the relationship between performance, staff turnover, salary, and motivation in healthcare in various federal districts. The hypothesis was that the high workload and a disproportionate payment system reduce the motivation, which increases staff turnover and leads to shortage of qualified personnel. In this research, stronger labor intensity indeed contributed to lower motivation of medical personnel and triggered staff turnover. The labor intensity correlated with the level of staff turnover, but no correlation was revealed between the labor intensity and the wages. The article explains the need for a more effective labor rationing system and a more rational workload distribution.
Role of Vitamins in Therapeutic and Targeting Approaches for Prostate Cancer: An Overview
Authors: Panda Pritish Kumar , Saraf Shivani , Verma Amit , Jain Ankit , Bidla Pooja Das , Raikwar Sarjana , Kumari Priyanka , Jain Sanjay K.
Published: September 2024

:

Vitamins play a crucial role in cellular functions like cell cycling and proliferation, differentiation,
and apoptosis. These also help in the induction of cell cycle arrest and/or apoptosis.
They can inhibit normal prostatic epithelial cell growth and might be helpful for the prevention of
prostate cancer (PCa). Many essential vitamins including the fat-soluble vitamins (vitamin A, vitamin
D, vitamin E, and vitamin K) and the water-soluble vitamins (vitamin B complexes and vitamin
C) have a huge impact on the inhibition of growth and progression of PCa. Vitamins show anticancer
properties and are involved in regulatory processes like the DNA repairing process,
which inhibit the growth of PCa. Consumption of multivitamins prevents methylation of cancer
cells and possesses an enormous potential that can be applied for the prevention as well as in the
management of PCa. They have a great role in the inhibition of different signalling pathways involved
in PCa. Moreover, they have also displayed a significant role in targeting of PCa with various
nanocarrier systems. This review encompasses the recent studies about the individual actions
of different vitamins and vitamin analogs, the combination of vitamins, and their efficient functions
in various therapeutic and targeting approaches for PCa.
Revolutionizing Skin Cancer Treatment: The Rise of PD-1/PDL-1 and CTLA-4 as Key Therapeutic Targets
Authors: Sharma Neha , Mazumder Rupa , Rai Pallavi
Published: September 2024

:

Skin cancer is a significant health concern, affecting millions of individuals globally on
an annual basis. According to data from the World Health Organization, it stands as the most prevalent
form of cancer within the white population. Current treatments for skin cancer typically involve
a combination of chemotherapy, radiation therapy, and surgery. However, these methods often
come with drawbacks, such as side effects and potential scarring. Therefore, there is a growing
need for alternative treatments that can offer effective results with fewer adverse effects, driving
ongoing research in skin cancer therapy. The advancement of immune checkpoint inhibitors has
been facilitated by a more profound comprehension of the interplay between tumors and the immune
system, along with the regulatory mechanisms governing T-cells. As cancer treatment continues
to evolve, immunotherapy is emerging as a powerful strategy, leading to a growing interest
in the role of immunological checkpoints in skin cancer. Various types of immune checkpoints
and their expression, including PD-1, PDL-1, CTLA-4, lymphocyte activation gene 3, and B7-H3,
along with their blockers and monoclonal antibodies, have been established for various cancers.
PD-1, PDL-1, and CTLA-4 are crucial immune system regulators, acting as brakes to prevent T--
cell overactivation and potential autoimmunity. However, tumors can exploit these checkpoints to
evade immune detection. Inhibiting these immune checkpoints can enhance the body's ability to
recognize and attack cancer cells. This review focuses on the characteristics of PD-1, PDL-1, and
CTLA-4 immune checkpoints, their mechanism of action, and their role in skin cancer. Additionally,
it summarizes the ongoing clinical trials sponsored or conducted by various pharmaceutical
companies and provides insights into the latest patent data.
Nanofiber-Based Drug Delivery Systems: A Review on Its Applications, Challenges, and Envisioning Future Perspectives
Authors: Alfadhel Munerah
Published: September 2024

Nanomaterials, especially nanofibers, hold considerable promise as drug delivery systems
(DDS) by providing targeted administration of drugs due to their unique properties, such as
large surface area, high porosity, and mechanical robustness. Nanofibers can be fabricated using
various techniques like electrospinning, self-assembly, phase separation, and template synthesis,
offering properties such as adjustable size, shape, high precision, and biodegradability. Additionally,
features such as multiple target functionalization, controlled release of the drug, and prolonged
circulation of the drug make nanofibers particularly suitable for biomedical applications, including
drug delivery, tissue regeneration, and biosensing. This comprehensive review explores the
characteristics, types, fabrication methods, and applications of nanofibers. Diverse types of polymer
nanofibers are used in drug delivery, such as blended nanofibers, core-shell nanofibers, and
layer-by-layer assembly, each demonstrating their own advantages in controlled drug release and
targeted therapy. Electrospun nanofibers are extensively utilized in biomedical applications due to
their superior mechanical performance and high porosity and advancements in coaxial electrospinning
enabling the fabrication of core-shell nanofibers, offering controlled drug release kinetics and
protection of loaded molecules. These nanofibers demonstrate enhanced bioactivity and biocompatibility
and can find application in tissue engineering. Furthermore, this review addresses the
challenges associated with nanofiber production, including reproducibility and scalability. Nanofibers
exhibit the potential to revolutionize medical treatment across diverse therapeutic areas. Future
research directions and challenges in nanofiber-based drug delivery discussed in this review
offer guidance for further advancements in this rapidly evolving field.
Practical Way to Use Supraglottic Airway Device
Authors: Dell’Orto Valentina Giovanna , Beretta Virginia , Petrolini Chiara , Perrone Serafina
Published: September 2024

We read a review of case reports published on Current Pediatric Reviews 2024 about
the use of I-gel® in neonatal complicated intubation, and we decided to write a commentary on the
benefits and limitations of using supraglottic airways in neonatal age, with a specific focus on Igel
[1]. The use of supraglottic airway devices in neonatal ages is limited to particular conditions,
but further research is showing the utility of these devices as the first choice in neonatal resuscitation
or airway stabilization. Our commentary highlights the broader practical applications of I-gel
and reinforces its role as a valuable tool in neonatal resuscitation.
Sexual Dysfunction in Women with Asthma and Associated Factors
Authors: Ozkarafakili Mufide A. , Turkmen Nihat
Published: September 2024

Background:

Asthma is a common chronic inflammatory airway disease. Female sexual
dysfunction (FSD) is frequently seen in asthmatics but often unnoticed in clinical practice. This
study evaluated the associations between asthma disease characteristics and (FSD).

Methods:

A total of 73 female asthma patients who visited the chest department outpatient clinic
and age-matched 73 healthy controls were enrolled. All the participants completed the questionnaires:
female sexual function index (FSFI), BECK depression, and BECK anxiety inventory, and
underwent pulmonary function tests. Patients with asthma completed an asthma quality of life
questionnaire (AQLQ) and asthma control test (ACT). FSD risk factors were analyzed using logistic
regression analysis.

Results:

About 68.8% of asthmatics had female sexual dysfunction. BECK anxiety and FSFI
scores with all six subsets were statistically significantly lower than healthy individuals in asthmatics
(p < 0.001). CRP levels, BECK anxiety, and depression scores had inverse (r = -0.386 r =
-0.343 r = -0.286), and FEV1% had a positive correlation with FSFI total scores. About 37.5% of
asthma patients with FSD were current smokers, the most compromised domain of the FSFI scale
was sexual arousal with a mean of 2.94 ± 0.56 and their FEV1% was lower, and CRP was higher
than the asthma patients without FSD (p < 0.001, p < 0.021). Smoking, high levels of CRP and
BECK anxiety scores, and low FEV1% were found to be risk factors for FSD in regression analysis.

Conclusions:

Female sexual dysfunction is frequently present in asthma patients. Smokers, patients
who have anxiety, lower FEV1% predicted values, and higher CRP levels tend to be susceptible
to sexual dysfunction, which implicates inflammation as an underlying mechanism.
Exploring Quinoline Derivatives: Their Antimalarial Efficacy and Structural Features
Authors: Mishra Raghav , da Cunha Xavier Jayze , Kumar Nitin , Krishna Gaurav , Dhakad Prashant Kumar , dos Santos Helcio Silva , Bandeira Paulo Nogueira , Rodrigues Tigressa Helena Soares , Gondim Diego Romao , Ribeiro Walber Henrique Ferreira , da Silva Draulio Sales , Teixeira Alexandre Magno Rodrigues , Pereira Wandresa Francelino , Marinho Emmanuel Silva , Sucheta
Published: September 2024

Objectives:

Malaria continues to be the primary cause of mortality worldwide, and timely
recognition and prompt intervention are crucial in mitigating adverse consequences. This review
article aims to examine the effectiveness and structural characteristics of quinoline-based compounds
as antimalarial agents. It specifically focuses on their therapeutic effects as well as potential
prospects for exploring structure-activity relationship (SAR). In addition, this study aims to identify
lead compounds that can efficiently battle multidrug-resistant forms of Plasmodium falciparum and
Plasmodium vivax.

Methods:

A comprehensive review was conducted to evaluate the effectiveness of quinoline-based
antimalarial medications in eradicating P. falciparum and P. vivax. The mechanism of action and
SAR of these compounds were analyzed

Results:

Quinoline-based antimalarials demonstrated significant effectiveness in eliminating P.
falciparum parasites, particularly in regions severely impacted by malaria, including Africa and
Asia. These compounds were found to exhibit tolerance and immune-modulating properties, indicating
their potential for more widespread utilization. The investigation identified various new
quinoline compounds with improved antimalarial activity, including metal-chloroquine complexes,
diaminealkyne chloroquines, and cinnamoylated chloroquine hybrids. This study explored different
mechanisms by which these compounds interact with parasites, including their ability to accumulate
in the parasite’s acidic food vacuoles and disrupt heme detoxification. The derivatives demonstrated
strong efficacy against chloroquine-resistant strains and yielded positive results.

Conclusion:

Quinoline-based compounds represent a promising avenue for combating malaria due
to their demonstrated efficacy against P. falciparum and P. vivax parasites. Further research on
their mechanisms of action and SAR could lead to the development of more effective antimalarial
medications.
Unraveling the Mysteries of PCOS: A Comprehensive Investigation into Causes, Mechanisms, and Molecular Docking Analysis with Dolichos biflorus Linn.
Authors: Sharma Priyanshu , Mittal Payal , Arya Girish Chandra
Published: September 2024

Polycystic ovary syndrome (PCOS) presents as a complex endocrine and metabolic disorder
characterized by anovulation, infertility, obesity, insulin resistance, and polycystic ovaries. Various
factors contribute to PCOS risk, including lifestyle choices, diet, environmental pollutants, genetics,
gut dysbiosis, neuroendocrine changes, and obesity. These factors can impact hyperinsulinemia,
oxidative stress, hyperandrogenism, decreased folliculogenesis, and irregular menstrual cycles,
ultimately contributing to metabolic syndrome. Conventional treatments for PCOS often carry significant
side effects, prompting exploration into Ayurvedic alternatives. This review concentrates on
molecular docking studies of phytochemicals sourced from Dolichos Biflorus Linn. against key proteins
implicated in PCOS pathogenesis. Identification, modeling, and evaluation of target proteins
were conducted, followed by the assessment of their interactions with selected phytochemicals and
additional ADMET analysis. Molecular docking studies utilizing Auto Dock Vina software were
then performed to forecast the binding affinities of these phytochemicals to the active sites of the
specified targets.
Aptamer-based Strategies for COVID-19 Detection and Treatment: A Systematic Review Study
Authors: Nakhaie Mohsen , Ghoreshi Zohreh-al-sadat , Charostad Javad , Salajegheh Faranak , Rezaei Zadeh Rukerd Mohammad , Arefinia Nasir
Published: September 2024

Background:

Aptamer-based strategies have emerged as promising tools for the detection
and treatment of COVID-19, offering advantages such as high specificity, sensitivity, and versatility.
This systematic review aims to evaluate the effectiveness and innovation of aptamer-based approaches
for COVID-19 detection and treatment.

Methods:

Following the guidelines of the Cochrane Handbook for Systematic Reviews and the
PRISMA 2020 guidelines, a systematic search was conducted across multiple databases up to 2024.
The search included studies that utilized aptamers for the diagnosis or therapy of COVID-19. Screening
and selection of studies were performed independently by two reviewers, with any disagreements
resolved by a third reviewer. Data were extracted regarding study characteristics, aptamer details,
and outcomes.

Results:

In our systematic review, 98 studies from an initial pool of 1541 records met the inclusion
criteria for analysis. Aptamers, single-stranded DNA or RNA molecules with unique threedimensional
(3D) structures, were extensively explored for COVID-19 detection and treatment. Various
aptamer-based assays, including electrochemical sensors, surface plasmon resonance (SPR)
biosensors, and lateral flow assays, demonstrated high sensitivity and specificity in detecting SARSCoV-
2 in clinical samples such as saliva, nasal swabs, and wastewater. Several aptamer structures
targeting viral proteins like the spike and nucleocapsid proteins were employed. Nucleic Acid Amplification
Techniques (NAATs) utilizing aptamers, such as Clustered Regularly Interspaced Short
Palindromic Repeats (CRISPR)-based and Loop-mediated Isothermal Amplification (LAMP) assays,
showed exceptional sensitivity in detecting viral genetic material. Aptamer-based therapeutic approaches
showed potential by blocking viral protein activity or serving as delivery vehicles for therapeutic
agents like small interfering RNAs (siRNAs). Despite their advantages, aptamer technologies
face limitations such as susceptibility to nuclease degradation and rapid renal clearance, highlighting
the need for further optimization.

Conclusion:

Aptamer-based strategies present promising avenues for COVID-19 detection and treatment.
These approaches offer advantages such as high sensitivity, specificity, and rapid detection, making
them valuable tools in combating the COVID-19 pandemic. Further research and development are
warranted to optimize aptamer-based strategies for widespread application in clinical settings.
Preparation, Characterization and Sustained-release Study of Encapsulated Cinnamon Essential Oil Microcapsules
Authors: Haputhanthri Rukshani , Dehigahawatta Sajini , Sandaruwan Chanaka , Perera Kasuni Kanchanamali , Pieris Colin
Published: September 2024

Aims:

The aim of this study is to study preparation, characterization and sustained release
of Encapsulated Cinnamon Essential Oil Microcapsules.

Background:

In this work, encapsulated cinnamon essential oil (CEO) microcapsules were prepared,
characterized, and analyzed for their sustained-release properties. CEO microcapsules were encapsulated
from an alginate polymer using homogenization and extrusion, and the encapsulation mechanism
used was ionic gelation. The potent antibacterial properties of natural cinnamon oil extracts and
their shelf-life activity can be reduced or eliminated as a result of deterioration caused by light, heat,
and oxygen exposure during production. High-speed homogenization was utilized for the encapsulation,
which encloses and protects the volatile compounds from degradation.

Objective:

The objective of this study is to synthesize sustained-release encapsulated cinnamon essential
oil (CEO) microcapsules.

Method:

The preparation of encapsulated cinnamon oil was achieved through homogenization. The
extrusion method was employed to obtain microcapsules encapsulating liquid active ingredients (AI)
with alginate polymer to induce ionic gelation.

Results:

SEM and Optical images reveal that all microcapsules maintain their spherical shape with
clearly defined membranes. XPS analysis indicates the presence of oxygen (O), carbon (C), and sodium
(Na) on the surface, suggesting the presence of an alginate-based ionic gelation. Chromatographic
studies demonstrate a high encapsulation efficiency of 99%. The average microcapsule size
is 261.5 nm for the fresh sample and 278 nm after 3.5 months. The zeta potential is -29.8 mV for the
fresh sample and -28.2 mV after 3.5 months. Notably, there is no evidence of microcapsule agglomeration
during the 3.5-month storage period as observed in the study. TGA data reveals that only
7.5% of the adsorbed water and essential oil mixture is lost at 40°C over 4 hours, in contrast to
11.7% for the adsorbed water material, indicating a sustained release of the encapsulated CEO from
the microcapsules.

Conclusion:

The microcapsules exhibited an impressive encapsulation efficiency of 99%, demonstrating
stability over the 3.5-month investigation period and showcasing sustained-release properties.
Recent Advances in the Preparation, Properties, and Applications of Solid
Lipid Nanoparticles in Drug Delivery
Authors: Biswas Ujjwal Kumar , Bose Anindya , Parmanik Ankita
Published: September 2024

Solid lipid nanoparticles (SLNs) are one of the extensively utilized nanocarriers in the
pharmaceutical field due to their biocompatibility and biodegradability. These features of the carrier
system have fuelled its use as the drug delivery system since the last three decades. This review presents
different SLN preparation techniques, such as high shear homogenization, hot homogenization,
cold homogenization, microemulsion-based technique, etc. The physicochemical nature of SLNs,
comprising drug loading, drug release, particle size, zeta potential, stability, cytotoxicity, and cellular
uptake, has been concisely discussed. The article also explains why SLNs are preferred to develop
drug delivery systems in several pharmaceutical preparations. The key ingredients like lipid, surfactant/
stabilizer accompanied by co-surfactant, cryoprotectant, or charge modifiers used to fabricate
SLNs are also briefly conferred. Here is an elaborate discussion of drugs that are used through various
routes by the SLN carrier system and their outcome for utilization of this system. Regulatory aspects,
patent aspects, and future prospects of SLN are also discussed here.
Pengaruh Perencanaan Keuangan, Literasi Keuangan, Dan Pendapatan Terhadap Pengelolaan Keuangan
Authors: Gusti Marchella An , Juwita Himmiyatul Amanah Jiwa
Published: September 2024

The objective of this research is to identify the effects of financial planning, financial literacy, and income on financial management. The research objects are civil servant teachers of Sijunjung Regency. This explanatory research elucidates the casual relationship between its dependent and independent variables using quantitative approach. The data of this research was harvested via closed 5-point Likert-scaled questionnaires distributed to 93 respondents, which were selected using proportionate stratified random sampling. The analysis as performed in IBM SPSS Statistics version 25 using multiple linear regression. This study finds that financial planning, financial literacy, and income significantly influence financial management. Therefore, it is crucial to increase the awareness of the civil servant teachers about the importance of financial management.
 
Abstrak
Penelitian ini bertujuan untuk mengetahui pengaruh perencanaan keuangan, literasi keuangan, dan pendapatan terhadap pengelolaan keuangan. Objek penelitian yang digunakan yaitu Guru PNS di Kabupaten Sijunjung. Penelitian ini merupakan explanatory research yang menjelaskan hubungan kausal antar variabel dependen dan independen melalui pendekatan kuantitatif. Metode pengumpulan data dilakukan dengan penyebaran kuesioner tertutup menggunakan skala pengukuran likert lima poin. Pengambilan sampel dilakukan dengan metode proportionate stratified random sampling. Sampel yang digunakan pada penelitian ini berjumlah 93 responden. Data diolah dengan menggunakan metode analisis regresi linear berganda dengan software SPSS IBM Statistic versi 25. Hasil penelitian menunjukkan bahwa perencanaan keuangan, literasi keuangan, dan pendapatan berpengaruh secara signifikan terhadap pengelolaan keuangan. Implikasi dari penelitian ini adalah meningkatkan kesadaran Guru PNS akan pentingnya pengelolaan keuangan.