bluuebunny/crossref_metadata_2025 huggingface dataset:
Posterior Segment Evaluation of Patients with Systemic Sclerosis Using Optical Coherence Tomography Angiography
Authors: El-Hameed Hassnaa Abd , Hammouda Laila Mohammed , Esmail Mohamed , Omar Ismail
Published: February 2024

Background
systemic sclerosis is an autoimmune disease with ocular affection. This study is for the evaluation of the retinal microvascular changes in systemic sclerosis patients by using the OCTA.
Methods
This prospective observational case-control study comprised twenty eyes of twenty systemic sclerosis patients as group I and another twenty eyes of twenty normal subjects as group II. All study members were examined with optical coherence tomography angiography in addition to a full ophthalmic examination.
Results
Both groups had more females gender than males without significant differences between them. Also, the mean age difference was statistically insignificant, with nearly the same range, which was 30 to 59 years in group I and 32 to 58 years in group II. Analysis of OCTA parameters revealed significantly lower differences in group I in the superficial vessel density at parafoveal, temporal, superior, and nasal regions. Lower values were recorded in group I at all zones of the deep layer except at the foveal zone. Vessel density measurements of the choriocapillaris revealed no statistically significant differences between groups in all zones.
Conclusions
The OCTA has demonstrated impairment of retinal microperfusion, confirming the presence of vascular damage. The duration of the disease had correlated with the DCP-VD and choriocapillaris VD. So, once systemic sclerosis has been diagnosed, microvascular retinal and choroidal evaluations should be considered to identify any sub-clinical alterations using OCTA.
Epi-off riboflavin with vitamin E TPGS (Ribocross) cross-linking: One-year outcome
Authors: Saba Pietro Paolo , Feo Alessandro , Pagano Luca , Vinciguerra Paolo , Vinciguerra Riccardo
Published: February 2024

Purpose: To assess the short and mid-term outcomes of epi-off corneal collagen cross-linking using Riboflavin with Vitamin E TPGS (Epi-off Ribocross® CXL) for progressive keratoconus
Design: Retrospective, single-center noncomparative interventional study.
Methods: Patients with progressive keratoconus who underwent CXL using Riboflavin with Vitamin E TPGS (Ribocross®) from May 2021 to May 2022 who completed at least 12 months of follow-up in Humanitas Clinical and Research Center, Rozzano, Milan, Italy. Corrected distance visual acuity (CDVA), tomographic parameters (Belin ABCD) and topographic parameters were evaluated at baseline and at last follow up.
Results: Twenty eyes of 20 patients fulfilled inclusion criteria. CDVA remained stable at last follow up (0,88 ± 0,19 from 0,83 ± 0,21, p=0.45) with a significant reduction in cylinder (1,97 ± 1,69 from 2,78 ± 2,19, p=0.03). Kmax significantly improved from 53.18D ± 6.32 to 50.96 ± 5.3D (p= 0.005). At the last follow up, no case of progression was noted.
Conclusions: Epi-off Ribocross® CXL proved to be a safe treatment for progressive KC, with a stabilisation of all cases at the one year follow up. Further studies are needed to confirm long-term stability.
BRILLO: Personalised HRI with a Bartender Robot
Authors: Rossi Alessandra , Rossi Silvia , Maro Maria , Origlia Antonio
Published: February 2024

The BRILLO (Bartending Robot for Interactive Long-Lasting Operations) project aims to create an autonomous robotic bartender that can interact with customers while accomplishing its bartending tasks. In such a scenario, people's novelty effect connected to the use of an attractive technology is destined to wear off and, consequently, negatively affects the success of the service robotics application. For this reason, providing personalised natural interaction while people access its services is fundamental for increasing users' engagement and, consequently, their loyalty. In this paper, we present the developed three-layer ROS architecture integrating a perception layer managing the processing of different social signals, a decision-making layer for handling multi-party interactions, and an execution layer controlling the behaviour of a complex robot composed of arms and a face. Finally, user modelling through a beliefs layer allows for personalized interaction. We also present the results of both people's interaction, experience and performances in a real user case. The user study involved 116 participants and showed that BRILLO is considered an easy-to-use and attractive system by the users.
Synthesis, characterization and investigation of liquid crystalline properties for some cross-link polymers containing melamine
Authors: Sultan Maha T. , Ahmed Basma J. , Tomma Jumbad H. , AlDujaili Ammar
Published: February 2024

In this study condensation polymerization was used to synthesize a number of novel liquid crystal polymers with 1,3,4-oxadiazole rings based on melamine. The new synthesized polymers were characterized by Fourier Transform Infrared (FTIR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. Differential scanning calorimetry (DSC) and optical polarization microscopy (OPM) were used to investigate their liquid crystalline properties. The results demonstrated that throughout a wide temperature range, most of the polymers exhibited columnar (CohX) and nematic (N) liquid crystalline phases.
Exploring Quantum and Binary Soft í µí»¼–Open Sets:Practical Applications through Soft Topologies
Authors: M John Peter , R Manoharan
Published: February 2024

This paper presents an exploration of Quantum and Binary Soft 𝛼 –Open Sets, focusing on their practical applications within the framework of soft topologies. In the binary soft topological spaces, binary soft 𝛼-closures, binary soft 𝛼-interiors and binary soft 𝛼-open (closed) sets are defined and study many of their properties along with how these concepts are connected to other soft open (closed) sets via theorems and propositions. The non-coincidence of these soft set theory concepts are proven via the use of counter examples. Further we look into the idea of binary soft 𝛼-continuous function which is described on family of binary soft 𝛼-open (closed) sets referred to as soft class over two starting universes with parameters, as well as their links to other soft continuous and weaker sections of soft continuous functions. The findings of this study represent the beginning of a new soft structure that will work as theoretical base for topological applications on soft sets, and will also act as a springboard for the extension of information systems and other engineering disciplines. Additionally, we demonstrate how binary soft set concept can be applied in medical information system. AMS Subject Classifications: 54A05, 54C08, 54A99
A Trigonometric Approach to the Hardy–Weinberg principle
Authors: Thompson Emanuel Junior
Published: February 2024

Representing, manipulating, and visualizing data is essential when presenting abstract or physical concepts. One representation is the Hardy-Weinberg Model (HWM), which provides a mathematical framework for understanding allele frequencies within large, randomly mating populations absent of evolutionary forces. Conventionally, the HWM is presented through algebraic expression. This paper introduces a modification that integrates trigonometric principles into the HWM’s framework by establishing a trigonometric identity using sine and cosine functions; This modification maintains the mathematical integrity of the algebraic form while also enhancing its utility through the incorporation of the Genetic Phase Angle (GPA) as a common variable between p and q. The use of a GPA to measure allele frequency allows users the ability to introduce mathematical formulae and or derivatives that affect both p and q simultaneously since p and q are dependent on the GPA. This method can also allow the user to map various evolutionary effects or even simulate them by directly affecting the GPA as a variable.
Eine korpuslinguistische Untersuchung zur lexikalischen Vielfalt von direkten und indirekten Redeeinleitern
Authors: Tu Ngoc Duyen Tanja
Published: February 2024

Redeeinleiter sind sprachliche Ausdrücke unterschiedlicher Wortarten, die relativ zur Redewiedergabe in Voran-, Mittel- oder Nachstellung stehen und eine direkte oder indirekte Redewiedergabe einleiten. Dadurch sind Redeeinleiter sehr vielfältig, womit sie sich als Untersuchungsgegenstand einer Analyse zur lexikalischen Vielfalt von Teilwortschätzen eignen.Als Datengrundlage der vorliegenden Untersuchung dienen die manuell annotierten direkten und indirekten Redeeinleiter des Redewiedergabe-Korpus. Dieses setzt sich aus fiktionalen und nicht-fiktionalen Textausschnitten, die zwischen 1840–1920 veröffentlicht wurden, zusammen. Ziel der Analyse ist es, zu ermitteln, wie sich der Teilwortschatz der direkten und der der indirekten Redeeinleiter in ihrer lexikalischen Vielfalt voneinander unterscheiden und wie diese Unterschiede zu begründen sind. Dafür wird ein Set an quantitativen Methoden erarbeitet mit dem die lexikalische Vielfalt von Teilwortschätzen bestimmt werden kann und das in zukünftigen Untersuchungen zur lexikalischen Vielfalt als Standardrepertoire herangezogen werden kann.
Does climate news sway investors away from large financiers of fossil fuel projects?
Authors: Nkwaira Chekani , Margaretha van der Poll Huibrecht
Published: February 2024

Despite rapid growth in climate news coverage, some banks are increasing financing towards greenhouse gas emitters with investors whose decisions intensify climate challenges. This study aims to establish the impact of climate news on investment decisions involving banks’ intensified fossil fuel financing and recommend remedies. Descriptive, linear regression analyses and the two-sample t-test are applied. The list of bank stems from the Consumer News and Business Channel website. Share prices, traded shares and market capitalizations are obtained from Macrotrends and Companies’ market cap websites for computing demand and holding periods. Results reveal more demand for riskier banks after European symposiums in contrast to Asia’s reduction. It is established that no significant linear relationships exist between demand and holding periods with t < T and p-value > 0.05. The null hypothesis of no linear relationship is not rejected. There is more price risk in Europe than in Asia with average volatilies of 0.439871 and 0.067472, respectively, at p-value 0.002117 < 0.05 based on the two-sample t-test. The null hypothesis of no difference in volatility means is rejected. The higher volality risk corresponds to higher demand for riskier bank shares in Europe. Climate news persuades Asian investors to reduce the demand for the banks’ shares. Conversely, European investors demonstrate behaviors incompatible with climate risk mitigation, particularly in periods after symposiums. A Global climate risk blacklisting initiative and a publicised Global climate risk index should accompany downgrades aimed at fossil fuel project financiers. Coverage of these measures at conferences may influence more investors to make correct decisions.
Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning
Authors: Zhang Limin , You Jianing , Huang Yiqing , Jing Ruiqi , He Yifei , Wen Yujie , Zheng Lulu , Zhao Yong
Published: February 2024

Background:

Dysmenorrhea is one of the most common ailments affecting young and
middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine
(TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is
essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with
modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea
syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning

Methods:

A total of 853 effective cases of dysmenorrhea were retrieved from the CNKI database,
including patients’ syndrome types, symptoms, and features, to establish the TCM information
database of dysmenorrhea. Subsequently, 42 critical features were isolated from a potential
set of 86 using a selection procedure augmented by Python's Scikit-Learn Library. Various
machine learning models were employed, including Logistic Regression, Random Forest Classifier,
Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Artificial Neural Networks
(ANN), each chosen for their potential to unearth complex patterns within the data.

Results:

Based on accuracy, precision, recall, and F1-score metrics, SVM emerged as the most
effective model, showcasing an impressive precision of 98.29% and an accuracy of 98.24%.
This model's analytical prowess not only highlighted the critical features pivotal to the syndrome
differentiation process but also stands to significantly aid clinicians in formulating personalized
treatment strategies by pinpointing nuanced symptoms with high precision.

Conclusion:

The study paves the way for a synergistic approach in TCM diagnostics, merging
ancient wisdom with computational acuity, potentially innovating the diagnosis and treatment
mode of TCM. Despite the promising outcomes, further research is needed to validate these
models in real-world settings and extend this approach to other diseases addressed by TCM.
Determination of Ideal Factors for Early Adoption and Standardization of Metagenomic Next-generation Sequencing for Respiratory System Infections
Authors: Zhao Lei , Formslag Cole R. , Zhang Qing , Cowan Braydon C. , Mayberry Trenton G. , Barnhill Aaron R. , Wang Yongsheng , Fang Yujiang
Published: February 2024

Background:

Metagenomic next-generation sequencing (mNGS) demonstrates great promise as a
diagnostic tool for determining the cause of pathogenic infections. The standard diagnostic procedures (SDP)
include smears and cultures and are typically viewed as less sensitive and more time-consuming when compared
to mNGS. There are concerns about the logistics and ease of transition from SDP to mNGS. mNGS
lacks standardization of collection processes, databases, and sequencing. Additionally, there is the burden of
training clinicians on interpreting mNGS results.

Objective:

Until now, few studies have explored factors that could be used as early adoption candidates to
ease the transition between SDP and mNGS. This study evaluated 123 patients who had received both SDP
and mNGS and compared several variables across a diagnostic test evaluation.

Methods:

The diagnostic test evaluation observed metrics such as sensitivity, specificity, positive and negative
likelihood ratios (PLR, NLR), positive and negative predictive values (PPV, NPV), and accuracy. Factors
included various sample sources such as bronchoalveolar lavage fluid (BALF), lung tissue, and cerebral
spinal fluid (CSF). An additional factor observed was the patient's immune status.

Results:

Pathogen detection was found to be significantly greater for mNGS for total patients, BALF sample
source, CSF sample source, and non-immunocompromised patients (p< 0.05). Pathogen detection was found
to be insignificant for lung tissue sample sources and immunocompromised patients. Sensitivity, PLR, NLR,
PPV, NPV, and accuracy appeared to be higher with mNGS for the total patients, BALF sample source, and
non-immunocompromised patients when compared with SDP (p< 0.05).

Conclusion:

With higher metrics in sensitivity, specificity, PLR, NLR, PPV, NPV, and accuracy for overall
patients, mNGS may prove a better diagnostic tool than SDP. When addressing sample sources, mNGS for
BALF-collected samples appeared to have higher scores than SDP for the same metrics. When patients were
in a non-immunocompromised state, mNGS also demonstrated greater diagnostic benefits to BALF and
overall patients compared to SDP. This study demonstrates that using BALF as a sample source and selecting
non-immunocompromised patients may prove beneficial as early adoption factors for mNGS standard
protocol. Such a study may pave the road for mNGS as a routine clinical method for determining the exact
pathogenic etiology of lung infections.
Implementation of Silver Nanoparticles Green Synthesized with Leaf Extract of Coccinia grandis as Antimicrobial Agents Against Head and Neck Infection MDR Pathogens
Authors: Lenka Smarita , Dubey Debasmita , Swain Santosh Kumar , Rath Goutam , Mishra Ajit , Bishoyi Ajit Kumar , Purohit Gopal Krishna
Published: February 2024

Background:

Head and neck infections (HNI) associated with multidrug resistance
(MDR) offer several health issues on a global scale due to inaccurate diagnosis.

Objectives:

This study aimed to identify the bacteria and Candidal isolates and implement the
silver nanoparticles green synthesized with leaf extract of Coccinia grandis (Cg-AgNPs) as a
therapeutic approach against HNI pathogens.

Methods:

The Cg-AgNPs were characterized by the UV-visible spectrophotometer, FT-IR analysis,
Zeta particle size, Zeta potential, and field emission scanning electron microscope (FESEM)
analysis to validate the synthesis of nanoparticles. Additionally, the antimicrobial activity
of Cg-AgNPs was presented by the zone of inhibition (ZOI), minimum inhibitory concentration
(MIC), minimum bactericidal/fungicidal concentration (MBC/MFC), and antibiofilm assay.
Moreover, the cell wall rupture assay was visualized on SEM for the morphological study of
antimicrobial activities, and the in-vivo toxicity was performed in a swiss mice model to evaluate
the impact of Cg-AgNPs on various biological parameters.

Results:

Different bacterial strains (Staphylococcus aureus, Acinetobacter baumannii, Klebsiella
pneumoniae, and Pseudomonas aeruginosa) and Candida sp. (Candida albicans, Candida tropicalis,
Candida orthopsilosis, and Candida glabrata) were identified. The MIC, MBC, and antibiofilm
potential of Cg-AgNPs were found to be highest against A. baumannii: 1.25 μg/ml, 5
μg/ml, and 85.01±5.19% respectively. However, C. albicans and C. orthopsilosis revealed
23mm and 21mm of ZOI. Subsequently, the micromorphology of the cell wall rupture assay
confirmed the efficacy of Cg-AgNPs, and no significant alterations were seen in biochemical and
hematological parameters on the swiss mice model in both acute and subacute toxicity studies.

Conclusion:

The green synthesized Cg-AgNPs have multifunctional activities like antibacterial,
anticandidal, and antibiofilm activity with no toxicity and can be introduced against the HNI
pathogens.
Spectroscopic Analysis of the Effect of Ibuprofen Degradation Products on
the Interaction between Ibuprofen and Human Serum Albumin
Authors: Ploch-Jankowska Anna
Published: February 2024

Background:

Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) are one of the most
commonly used groups of medicinal compounds in the world. The wide access to NSAIDs and the
various ways of storing them due to their easy accessibility often entail the problem with the stability and durability resulting from the exposure of drugs to external factors.
The aim of the research was to evaluate in vitro the mechanism of competition between ibuprofen
(IBU) and its degradation products, i.e., 4'-isobutylacetophenone (IBAP) and (2RS)-2-(4-
formylphenyl)propionic acid (FPPA) during transport in a complex with fatted (HSA) and defatted
(dHSA) human serum albumin.

Methods:

The research was carried out using spectroscopic techniques, such as spectrophotometry, infrared spectroscopy and nuclear magnetic resonance spectroscopy

Results:

The comprehensive application of spectroscopic techniques allowed, among others, for
the determination of the binding constant, the number of classes of binding sites and the cooperativeness constant of the analyzed systems IBU-(d)HSA, IBU-(d)HSA-FPPA, IBU-(d)HSA-IBAP;
the determination of the effect of ibuprofen and its degradation products on the secondary structure of albumin; identification and assessment of interactions between ligand and albumin; assessment of the impact of the presence of fatty acids in the structure of albumin and the measurement temperature on the binding of IBU, IBAP and FPPA to (d)HSA.

Conclusion:

The conducted research allowed us to conclude that the presence of ibuprofen degradation products and the increase in their concentration significantly affect the formation of the
IBU-albumin complex and thus, the value of the association constant of the drug, changing the
concentration of its free fraction in the blood plasma. It was also found that the presence of an ibuprofen degradation product in a complex with albumin affects its secondary structure.
Timing of Surgery for Asymptomatic Primary Mitral Regurgitation:
Possible Value of Early, Serial Measurements of Left Ventricular Sphericity
Authors: Stanley Alfred , Athanasuleas Constantine
Published: February 2024

Asymptomatic primary mitral regurgitation due to myxomatous degeneration of the
mitral valve leaflets may remain so for long periods, even as left ventricular function progresses
to a decompensated stage. During the early compensated stage, the ventricle’s initial response to
the volume overload is an asymmetric increase in the diastolic short axis dimension, accomplished
by a diastolic shift of the interventricular septum into the right ventricular cavity, creating
a more spherical left ventricular diastolic shape, increasing diastolic filling and stroke volume.
Early valve repair is recommended to reduce postoperative left ventricular dysfunction.
Early serial measurements of left ventricular sphericity index [LV-Si]. during the compensated
stage of mitral regurgitation might identify subtle changes in left ventricular shape and assist in
determining the optimal earliest timing for surgical intervention.
Synthesis, Antimicrobial Evaluation, and Interaction of Emodin Alkyl
Azoles with DNA and HSA
Authors: Zhou Yu-Hang , Wang Ying , Zhang Hui-Zhen
Published: February 2024

Objective:

This study aimed to overcome the growing antibiotic resistance. Moreover,
the new series of emodin alkyl azoles were synthesized.

Method:

The novel emodin alkyl azoles were synthesized using commercial emodin and azoles by
alkylation. The NMR and HRMS spectra were employed to confirm the structures of novel prepared
compounds. The in vitro antibacterial and antifungal activities of the prepared emodin compounds
were studied by the 96-well plate method. The binding behavior between emodin 4-nitro
imidazole compound 3c and S. aureus DNA was researched using an ultraviolet-visible spectrophotometer.
Furthermore, fluorescence spectrometry was used to explore the interaction with human
serum albumin (HSA).

Results:

The in vitro antimicrobial results displayed that compound 3c gave relatively strong activities
with MIC values of 4−16 μg/mL. Notably, this compound exhibited 2-fold more potent activity
against S. aureus (MIC = 4 μg/mL) and E. coli (MIC = 8 μg/mL) strains than clinical drug Chloromycin
(MIC = 8 and 16 μg/mL). The UV-vis absorption spectroscopy showed that 4-nitro imidazole
emodin 3c could form the 3c-DNA complex by intercalating into S. aureus DNA, inhibiting
antimicrobial activities. The simulation results displayed that the emodin 3c and DNA complex
were formed by hydrogen bonds. The spectral experiment demonstrated that compound 3c could be
transported by human serum albumin (HSA) via hydrogen bonds. The molecular simulation found
that the hydroxyl group and the nitroimidazole ring of the emodin compound showed an important
role in transportation behavior.

Conclusion:

This work may supply useful directions for the exploration of novel antimicrobial
agents.
Ocular Findings and Blurring of Vision Associated with COVID-19 Virus during Pandemics in Iraq
Authors: Hashim Zainab Adel , Salih Suzan Kahatan M. , Abdulla Marwan Younis
Published: February 2024

Background

Coronavirus disease 2019 (COVID-19) emerged with a number of ophthalmologic manifestations. The most significant ocular symptoms included conjunctival discharge, redness, tears, itching, and a feeling of a foreign body in the eye.

Aim

To review and critically appraise ophthalmologic manifestations of COVID-19 in the form of rate and severity of visual impairment following ocular and systemic COVID-19 infections.

Methods

A cross-sectional study that was carried out at the outpatients’ clinic in Al-Diwaniyah Teaching Hospital from October 2020 to October 2022 were 135 patients seeking advice regarding their ocular complaints. They are PCR and /or CT-scan approved COVID-19 infection. Comprehensive eye examination done for these patients started with visual acuity assessment by Snellen chart, then refraction followed by examination of the eye and its adnexa by slit lamp for signs of inflammation.

Results

The patients had a mean age of 47.5 years, and the rate of blurring of vision was 39.3%, whether they had ocular manifestation or not, and it showed substantial association with disease severity.

Conclusion

COVID-19 infection was associated with visual impairment, and the ophthalmologic manifestations severity was related to systemic morbidity.
Modelling Exchange with Blockchain for the Collaborative Design of a Building Envelope in BIM
Authors: Hsu Chih Lin , Wang Jui Tang , Xie Huang Jun
Published: February 2024

Introduction

The main challenge in using building information modelling (BIM) is the centralised collaborative framework in the various design software (e.g., AutoCAD, Revit, RHINO, and ArchiCAD) used by professionals across various disciplines, which causes difficulties during data exchange.

Methods

The existing framework may increase the project lead time, require more effort, and result in design conflicts and misunderstandings. Thus, this paper has proposed a dynamic information storage with blockchain system (DISBS) using a physical curtain wall project for practical implementation. In addition, this paper has further discussed the linkages and verified and analysed the effectiveness of the proposed methodology.

Results

Through the DISBS proposed in this research, the characteristics and achievable functions of blockchain technology are presented. Various applications for the field of construction engineering are highly developable within this research.

Conclusion

The DISBS can improve not only the management quality of construction projects, but also promote mutual trust in the construction industry and optimize architecture, engineering, and construction (AECO) productivity.
Red Blood Cell Distribution Width as a Diagnostic Marker of Hepatocellular Carcinoma in Cirrhotic Patients
Authors: Hawash Nehad , Gameaa Reham , Elwy Doaa , Mansour Shimaa
Published: February 2024

Background and Aim

Although α-fetoprotein (AFP) is the main marker used for the diagnosis of hepatocellular carcinoma(HCC), its sensitivity and specificity as a screening tool have been questionable. Red blood cell distribution width (RDW) has been involved as a prognostic tool for many diseases and cancers including liver diseases. Still, its role in the diagnosis of HCC needs to be identified. This study aimed to evaluate the clinical importance of RDW as a novel marker in the diagnosis of HCC in Egyptian cirrhotic patients.

Patients and Methods

This cross-sectional study was carried out on 162 cirrhotic patients who attended Tropical medicine department clinics and inpatient wards at the Faculty of Medicine, Tanta University. Then they were divided into 2 groups of 81 patients each depending on their diagnosis with or without HCC (group I and group II respectively). Complete blood picture (CBC) that included red cell distribution width- coefficient of variation (RDW-CV) and AFP were obtained from all patients.

Results

There was a statistically significant elevation in RDW-CV in the HCC group as its mean± SD was 15.2.± 1.86 in HCC group versus 13.8 ± 1.99 in non HCC group (P<0.001). In addition, AFP was significantly elevated in group I than in group II (P<0.001). RDW-CV at a cut–off >14% had a 66.76%sensitivity and 61.73%specificity while AFP at a cut-off value>20 ng/ml had a 60.49%sensitivity and 79.01%specificity in the diagnosis of HCC. The combination of RDW-CV and AFP increased the sensitivity and specificity for the diagnosis of HCC(72.84% and 87.65% respectively) than each marker alone.

Conclusions

RDW may be considered a novel and cheap biomarker for the diagnosis of HCC either alone or in combination with AFP as it is readily available in CBC and does not need sophisticated techniques.
Phytochemical and Bioactive Profile of Medicinal Plants Used Traditionally
in Bosnia and Herzegovina
Authors: Ibragic Saida , Mesinovic Aisa , Arnaut Selma , Delic Emina , Besta-Gajevic Renata , Dahija Sabina , Dizdar Muamer , Karalija Erna
Published: February 2024

Introduction::

This paper aimed to characterize the phytochemical profile and bioactivities
of 22 plant species used in the traditional medicine of Bosnia and Herzegovina. The utilization of
plants in traditional medicine in Bosnia and Herzegovina holds significant importance, not only as a
reflection of cultural heritage but also as a sustainable and time-tested approach to healthcare, fostering
a harmonious connection between nature and well-being.

Method::

The comprehensive analyses encompassed the determination of total phenolic and flavonoid
content, alongside assessing antioxidant activity using DPPH and FRAP assays. Additionally,
antimicrobial activity was tested against S. aureus. ssp. aureus, MRSA, P. aeruginosa, S. abony and
C. albicans. Many of the analyzed plant extracts showed a high phenolic content (C. avellana, V.
myrtillus) and antioxidant activity (C. avellana, V. myrtillus, B. pendula, S. officinale, E. angustifolium,
J. globifera ssp. hirta).

Result::

The majority of extracts showed good antimicrobial activity for S. aureus ssp. aureus and
MRSA. The E. angustifolium extract was effective against all tested bacterial strains, with MIC values
ranging from 1.25-10 mg/mL. The research identified significant levels of secondary metabolites
and identified plant species with potent antioxidant and antimicrobial activity.

Conclusion::

The study also revealed significant correlations among various phytochemical parameters
and bioactivities.
Rodzicielstwo zawieszone w sytuacji resocjalizacji dziecka przebywającego w młodzieżowym ośrodku wychowawczym
Authors: Roguska Agnieszka
Published: February 2024

Tekst przybliża znaczenie i zadania rodzicielstwa zawieszonego w warunkach przebywania nieletniego w MOW podczas jego resocjalizacji. Publikacja bazuje na ponad 5-letnim doświadczeniu w pracy na stanowisku psychoterapeuty uzależnień autorki tekstu. W ciągu tych kilku lat przeprowadzono wielogodzinne rozmowy z ponad 125 wychowankami podczas sesji terapeutycznych oraz ich rodzicami. Analizie poddano także dokumenty podopiecznych. Nieletni przebywają w ośrodku od kilku tygodni, częściej miesięcy do nawet kilku lat, np. 3-4 lata. W tekście znajdują się zadania stojące przed rodziną dziecka przebywającego w ośrodku oraz nawiązanie i rozumienie takich pojęć, jak: rodzicielstwo zawieszone, resocjalizacja, readaptacja, style przywiązania. Materiał zawiera także infografiki dotyczące przyczyn kierowania nieletnich do MOW oraz możliwości wsparcia dziecka i rodziców/opiekunów z pomocą tego ośrodka. Ponadto zawiera sugestie odnośnie do systemu resocjalizacji nieletnich i wskazówki dla praktyków.
Dietary Intake Assessment Using a Novel, Generic Meal–Based Recall and a 24-Hour Recall: Comparison Study
Authors: O'Hara Cathal , Gibney Eileen R
Published: February 2024

Background

Dietary intake assessment is an integral part of addressing suboptimal dietary intakes. Existing food-based methods are time-consuming and burdensome for users to report the individual foods consumed at each meal. However, ease of use is the most important feature for individuals choosing a nutrition or diet app. Intakes of whole meals can be reported in a manner that is less burdensome than reporting individual foods. No study has developed a method of dietary intake assessment where individuals report their dietary intakes as whole meals rather than individual foods.

Objective

This study aims to develop a novel, meal-based method of dietary intake assessment and test its ability to estimate nutrient intakes compared with that of a web-based, 24-hour recall (24HR).

Methods

Participants completed a web-based, generic meal–based recall. This involved, for each meal type (breakfast, light meal, main meal, snack, and beverage), choosing from a selection of meal images those that most represented their intakes during the previous day. Meal images were based on generic meals from a previous study that were representative of the actual meal intakes in Ireland. Participants also completed a web-based 24HR. Both methods were completed on the same day, 3 hours apart. In a crossover design, participants were randomized in terms of which method they completed first. Then, 2 weeks after the first dietary assessments, participants repeated the process in the reverse order. Estimates of mean daily nutrient intakes and the categorization of individuals according to nutrient-based guidelines (eg, low, adequate, and high) were compared between the 2 methods. P values of less than .05 were considered statistically significant.

Results

In total, 161 participants completed the study. For the 23 nutrient variables compared, the median percentage difference between the 2 methods was 7.6% (IQR 2.6%-13.2%), with P values ranging from <.001 to .97, and out of 23 variables, effect sizes for the differences were small for 19 (83%) variables, moderate for 2 (9%) variables, and large for 2 (9%) variables. Correlation coefficients were statistically significant (P<.05) for 18 (78%) of the 23 variables. Statistically significant correlations ranged from 0.16 to 0.45, with median correlation of 0.32 (IQR 0.25-0.40). When participants were classified according to nutrient-based guidelines, the proportion of individuals who were classified into the same category ranged from 52.8% (85/161) to 84.5% (136/161).

Conclusions

A generic meal–based method of dietary intake assessment provides estimates of nutrient intake comparable with those provided by a web-based 24HR but with varying levels of agreement among nutrients. Further studies are required to refine and improve the generic recall across a range of nutrients. Future studies will consider user experience including the potential feasibility of incorporating image recognition of whole meals into the generic recall.
An Entity Extraction Pipeline for Medical Text Records Using Large Language Models: Analytical Study
Authors: Wang Lei , Ma Yinyao , Bi Wenshuai , Lv Hanlin , Li Yuxiang
Published: February 2024

Background

The study of disease progression relies on clinical data, including text data, and extracting valuable features from text data has been a research hot spot. With the rise of large language models (LLMs), semantic-based extraction pipelines are gaining acceptance in clinical research. However, the security and feature hallucination issues of LLMs require further attention.

Objective

This study aimed to introduce a novel modular LLM pipeline, which could semantically extract features from textual patient admission records.

Methods

The pipeline was designed to process a systematic succession of concept extraction, aggregation, question generation, corpus extraction, and question-and-answer scale extraction, which was tested via 2 low-parameter LLMs: Qwen-14B-Chat (QWEN) and Baichuan2-13B-Chat (BAICHUAN). A data set of 25,709 pregnancy cases from the People’s Hospital of Guangxi Zhuang Autonomous Region, China, was used for evaluation with the help of a local expert’s annotation. The pipeline was evaluated with the metrics of accuracy and precision, null ratio, and time consumption. Additionally, we evaluated its performance via a quantified version of Qwen-14B-Chat on a consumer-grade GPU.

Results

The pipeline demonstrates a high level of precision in feature extraction, as evidenced by the accuracy and precision results of Qwen-14B-Chat (95.52% and 92.93%, respectively) and Baichuan2-13B-Chat (95.86% and 90.08%, respectively). Furthermore, the pipeline exhibited low null ratios and variable time consumption. The INT4-quantified version of QWEN delivered an enhanced performance with 97.28% accuracy and a 0% null ratio.

Conclusions

The pipeline exhibited consistent performance across different LLMs and efficiently extracted clinical features from textual data. It also showed reliable performance on consumer-grade hardware. This approach offers a viable and effective solution for mining clinical research data from textual records.
Machine Learning–Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts (Preprint)
Authors: Lee Hojae , Cho Joong Ki , Park Jaeyu , Lee Hyeri , Fond Guillaume , Boyer Laurent , Kim Hyeon Jin , Park Seoyoung , Cho Wonyoung , Lee Hayeon , Lee Jinseok , Yon Dong Keon
Published: February 2024

BACKGROUND

Given the additional risk of suicide-related behaviors in adolescents with allergic rhinitis (AR), it is important to use the growing field of machine learning (ML) to evaluate this risk.

OBJECTIVE

This study aims to evaluate the validity and usefulness of an ML model for predicting suicide risk in patients with AR.

METHODS

We used data from 2 independent survey studies, Korea Youth Risk Behavior Web-based Survey (KYRBS; n=299,468) for the original data set and Korea National Health and Nutrition Examination Survey (KNHANES; n=833) for the external validation data set, to predict suicide risks of AR in adolescents aged 13 to 18 years, with 3.45% (10,341/299,468) and 1.4% (12/833) of the patients attempting suicide in the KYRBS and KNHANES studies, respectively. The outcome of interest was the suicide attempt risks. We selected various ML-based models with hyperparameter tuning in the discovery and performed an area under the receiver operating characteristic curve (AUROC) analysis in the train, test, and external validation data.

RESULTS

The study data set included 299,468 (KYRBS; original data set) and 833 (KNHANES; external validation data set) patients with AR recruited between 2005 and 2022. The best-performing ML model was the random forest model with a mean AUROC of 84.12% (95% CI 83.98%-84.27%) in the original data set. Applying this result to the external validation data set revealed the best performance among the models, with an AUROC of 89.87% (sensitivity 83.33%, specificity 82.58%, accuracy 82.59%, and balanced accuracy 82.96%). While looking at feature importance, the 5 most important features in predicting suicide attempts in adolescent patients with AR are depression, stress status, academic achievement, age, and alcohol consumption.

CONCLUSIONS

This study emphasizes the potential of ML models in predicting suicide risks in patients with AR, encouraging further application of these models in other conditions to enhance adolescent health and decrease suicide rates.
Comparison of Analgesia Methods Through a Web Platform in Patients Undergoing Thoracic Surgery: Pilot Design, Implementation, and Validation Study (Preprint)
Authors: Trò Rosella , Orecchia Angelica , Disma Nicola , Uva Paolo , Cavanna Roberto , Zanardi Nicolò , Torre Michele , Fato Marco Massimo
Published: February 2024

BACKGROUND

Pain management is a vital and essential part of postoperative pectus excavatum (PE) care. Given the lack of an international consensus on guidelines for postoperative handling and evaluation, further research is necessary to compare the efficacy of existing pain management methods regarding pain relief, side effects, and long-term outcomes. In this context, the use of eHealth solutions for data mining can enhance data collection efficiency, reduce errors, and improve patient engagement. However, these digital health care frameworks are currently underused in the context of pain management for PE.

OBJECTIVE

This research is part of the broader Cryoanalgesia for Pain Management After Pectus Excavatum Repair (COPPER) study conducted by Giannina Gaslini Children’s Hospital to address postoperative pain and recovery in PE patients treated with either standard thoracic epidural analgesia or cryoanalgesia, which is considered its innovative alternative approach. Specifically, this work is aimed at introducing a valuable tool for a comprehensive and quantitative comparison of the 2 analgesia strategies. The tool is a web and mobile app designed to facilitate data collection, management, and analysis of clinical data for pain assessment.

METHODS

The adopted approach involves a careful design based on clinician input, resulting in an intuitive app structure with 3 main screens. Digital surveys are borrowed from paper surveys, including medical history and preoperative, postoperative, and follow-up evaluations. XTENS 2.0 was used to manage the data, and Ionic facilitated cross-platform app development, ensuring secure and adaptable data handling.

RESULTS

Preliminary analysis on a pilot cohort of 72 patients (36 treated with standard therapy and 36 treated with cryoanalgesia) indicated successful patient enrollment and balanced representation across treatment groups and genders. Notably, hospital stay was significantly shorter with cryoanalgesia than with standard therapy (Mann-Whitney-Wilcoxon 2-sided test with Bonferroni correction; P<.001; U statistic=287.5), validating its treatment efficacy.

CONCLUSIONS

This work is a step toward modernizing health care through digital transformation and patient-centered models. The app shows promise in streamlined data collection and patient engagement, although improvements in multilingual support, data validation, and incentivization of questionnaire completion are warranted. Overall, this study highlights the potential of digital health solutions in revolutionizing health care practices, fostering patient involvement, and improving care quality.
Does training of Community Health Workers in diabetes lead to improved outcomes for diabetes, screening and management in low-and-middle-income-countries: A systematic review protocol (Preprint)
Authors: Gudlavalleti Anirudh Gaurang , Babu Giridhara R. , Kamalakannan Suresh Kumar , Murthy G V S , Schaper Nicolaas C , van Schayck Onno
Published: February 2024

BACKGROUND

Diabetes, particularly Type 2 Diabetes Mellitus (T2DM), is a global health crisis disproportionately affecting low- and middle-income countries (LMICs). Task-shifting strategies employing Community Health Workers (CHWs) have emerged as a promising approach to address healthcare barriers in LMICs, although their effectiveness in diabetes management remains uncertain.

OBJECTIVE

To establish the protocols for a systematic review assessing whether training CHWs in diabetes management leads to improved outcomes in screening and managing diabetes in LMICs.

METHODS

The systematic review protocol follows the PRISMA guidelines and has been registered with PROSPERO (CRD42022341717). Eligible studies will include randomised controlled trials and meta-analyses conducted between January 2000 and December 2023, focusing on training CHWs in diabetes management in LMICs. Studies will be searched in various databases, including PubMed, Scopus, Cochrane Central, and others. The review will include studies reporting outcomes such as changes in diabetes referrals, screenings, HbA1c values, and fasting blood glucose levels. Data extraction will be independently conducted by two reviewers using a custom-made form, with discrepancies resolved by a third reviewer. Risk of bias assessment will follow Cochrane and ROBINS tools for randomized and non-randomized studies, respectively. A narrative synthesis will explore the intervention's effects and implementation factors, with subgroup analyses planned based on CHW types and demographic factors. Meta-analysis will be conducted for the outcome measures.

RESULTS

The systematic review aims to provide comprehensive evidence on the effectiveness of training CHWs in diabetes management in LMICs. Findings will be synthesized narratively and, if feasible, through meta-analysis.

CONCLUSIONS

This systematic review protocol outlines a rigorous methodology to evaluate the impact of training CHWs in diabetes management in LMICs. By synthesizing available evidence, this review aims to present scientific evidence of the highest order for CHW training design and associated policies.

CLINICALTRIAL

The trial has been registered with PROSPERO (CRD42022341717)
Classification of Living Kidney Donation Experiences on Reddit: Understanding the Sensitivity of ChatGPT to Prompt Engineering (Preprint)
Authors: Nielsen Joshua , Chen Xiaoyu , Davis LaShara , Waterman Amy , Gentili Monica
Published: February 2024

BACKGROUND

Living kidney donation (LKD), where individuals donate one kidney while alive, plays a critical role in increasing the number of kidneys available for those suffering from kidney failure. Prior studies show that many generous people are interested in becoming living donors, but a huge gap exists between the number of patients on the waiting list and the number of living donors yearly.

OBJECTIVE

To bridge this gap, we investigated how to identify potential living donors from discussion on public social media forums so that educational interventions could later be directed to them.

METHODS

Utilizing Reddit forums as an example, this study describes the classification of Reddit content shared about LKD into three classes: (1) Present (presently dealing with LKD personally), (2) Past (dealt with LKD personally in the past), and Other (LKD general comments). An evaluation comparing a fine-tuned DistilBERT model (hereafter written BERT for simplicity) and inference with GPT-3.5 (ChatGPT) occurred. To systematically evaluate ChatGPT’s sensitivity to distinguishing between the three prompt categories, we employed a comprehensive prompt engineering strategy encompassing a full factorial analysis in 48 runs. A novel prompt engineering approach, Dialogue Until Classification Consensus (DUCC), was introduced to simulate a deliberation between two domain experts until a consensus on classification was achieved.

RESULTS

BERT and GPT-3.5 exhibited classification accuracies of approximately 75% and 78%, respectively. Recognizing the inherent ambiguity between classes, a post-hoc analysis of incorrect predictions was performed, revealing sensible reasoning and acceptable errors from the predictive models. Considering these acceptable mis-matched predictions, the accuracy improved to 89.33% for BERT, 90.67% for GPT-3.5, and 92.67% for GPT-4.

CONCLUSIONS

Large Language Models (LLMs) like GPT-3.5 are highly capable of detecting and categorizing LKD targeted content on social media forums. They are sensitive to instructions, and the introduced DUCC method exhibited superior performance over standalone reasoning, highlighting the merit in advancing prompt engineering methodologies. The models can produce appropriate contextual reasoning, even when final conclusions differ from human counterparts.
Solar Panel Cleaning System
Authors: Wagh Arpita
Published: February 2024

Abstract: The goal of Project SPACE is to create an automated solar panel cleaner that will address the adverse impact of soiling on commercial photovoltaic cells. Specifically, we hoped to create a device that increases the maximum power output of a soiled panel by 10% (recovering the amount of power lost) while still costing under $500 and operating for up to 7.0 years. A successful design should operate without the use of water.