bluuebunny/crossref_metadata_2025 huggingface dataset:
The Safety Profile of Acne Supplements: Analysis of Active Ingredients
Authors: Noveir Sasan , Galamgam Jayden , Cheng Carol
Published: January 2025

Introduction: Acne treatment options vary widely, with many patients using dietary supplements. Despite their popularity, these products pose safety concerns due to lack of FDA approval for safety or efficacy before release. The US Institute of Medicine sets Tolerable Upper Intake Levels (ULs) for nutrients, but there are no regulatory limits to prevent supplements from exceeding these ULs.
Methods: On March 3, 2024, active ingredients from the top 50 best-selling acne supplements were collected from Amazon. Data were analyzed to identify ingredients and the frequency at which their dosages surpassed the ULs for different age groups.
Results: The most prevalent active ingredients were zinc (40%), vitamin A (30%), diindolylmethane (DIM) (26%), vitamin E (26%), and selenium (24%). Thirty percent of all supplements contained at least one ingredient exceeding its UL for ages 9 to 13, 20% for ages 14-18, and 16% for ages 19 and older. Twenty-five percent of zinc-containing supplements and 33% of vitamin A-containing supplements exceeded the UL for any all groups.
Discussion: Acne supplements frequently contain ingredients that surpass ULs, particularly zinc and vitamin A. Chronic toxicity from these nutrients can lead to significant health issues. Dermatologists should inquire about supplement use when prescribing treatments like isotretinoin to prevent toxicity risks.
Treatment Preferences, Monthly Injection is the Preferred Frequency of Administration in the Treatment of Moderate to Severe Atopic Dermatitis: Results from a Real-World Survey in the United States
Authors: Malatestinic William , Armstrong April , Geng Bob , Lio Peter , Young Melodie , Chao Tomas , Pierce Evangeline , Dawson Zach
Published: January 2025

None
Comparative Efficacy of Lebrikizumab, Dupilumab, and Tralokinumab in Maintaining Treatment Response in Atopic Dermatitis at Varying Treatment Continuance Rates
Authors: Silverberg Jonathan , Irvine Alan , Foley Peter , Del Rosso James , Puig Luis , Stein Gold Linda , Dossenbach Martin , Casillas Marta , Gallo Gaia , Akmaz Buelent , Rand Kim
Published: January 2025

Introduction: Atopic dermatitis (AD) is a chronic inflammatory skin disease with significant impacts on quality of life. Despite the effectiveness of biologics for moderate to severe AD, long-term treatment adherence can be challenging in clinical practice. This study introduces the “durability index” as a novel estimate of the maintenance of therapeutic effect under varying treatment continuance rates.
Methods: A population-adjusted indirect comparison of placebo-controlled phase 3 trials of dupilumab 300 mg QW/Q2W (SOLO 1, SOLO 2, and SOLO CONTINUE), tralokinumab 300 mg Q2W (ECZTRA1 and ECZTRA 2), and lebrikizumab 250 mg Q4W (ADvocate1 and ADvocate2) was conducted. In these trials, patients who responded at week 16 (IGA 0/1 or EASI 75) were re-randomized to either continue treatment or switch to treatment withdrawal (placebo) until week 52. The durability index was developed to estimate drug performance at varying treatment continuance rates between 100% to 0% on-treatment. Unanchored simulated treatment comparison (STC) was used to estimate odds ratios (OR) adjusting for baseline covariates.
Results: For IGA 0/1, patients receiving lebrikizumab had statistically significantly better odds of maintaining response at week 52 than those on dupilumab for all treatment continuance rates, ranging from 1.730 (p = 0.044) at 100% to 4.690 (p < 0.001) at 0%. ORs comparing lebrikizumab to tralokinumab ranged from 1.787 at 100% continuance to 1.516 at 0%, with significant results favoring continuance rates between 39.5% and 96.9%. For EASI 75, week-52 durability at 100% continuance was non-significantly different between lebrikizumab and dupilumab (OR 0.687, p = 0.183); however, ORs increased in favor of lebrikizumab at lower treatment continuance rates, reaching significance from 64.2% (OR 1.454, p = 0.05) to 0% (OR 3.235, p < 0.001) continuance. ORs comparing lebrikizumab to tralokinumab ranged from 2.132 at 100% to 3.891 at 0% continuance, with significant results favoring lebrikizumab for all treatment continuance rates. ORs comparing dupilumab and tralokinumab showed varying results: tralokinumab was favored for IGA 0/1 at lower continuance rates, while dupilumab was favored for EASI 75 at higher continuance rates.
Conclusions: In this indirect comparative analysis, lebrikizumab had treatment response rates that were comparable to or better than dupilumab and tralokinumab, regardless of treatment continuance rates. This finding suggests that lebrikizumab may offer a more effective long-term management option for AD.
This analysis was funded by Eli Lilly and Company.
Baricitinib Achieved Complete/Near Complete Scalp Coverage in SALT Score ≤20 Responders: 52-Week Findings From BRAVE-AA Trials
Authors: Ko Justin , McMichael Amy , Hordinsky Maria , Passeron Thierry , Shimomura Yutaka , Ogwu Samuel , Chughtai Rukhsar , Somani Najwa , King Brett
Published: January 2025

Introduction: Baricitinib is an approved and widely used treatment option for severe alopecia areata (AA). In the Phase 2/3 BRAVE-AA1 (NCT03570749) and Phase 3 BRAVE-AA2 (NCT03899259) trials, a significant proportion of patients achieved the clinically meaningful endpoint of Severity of Alopecia Tool (SALT) score ≤20, and maintained it through Week 52. While SALT score ≤20 is a standard endpoint, it does not capture the full extent of patient improvement among responders. Many patients who achieved SALT score ≤20 in the BRAVE-AA trials, also achieved complete or nearly complete scalp coverage (SALT score ≤10 or ≤5). The objective of this analysis was to evaluate the proportion of patients achieving SALT score ≤10 or ≤5 among patients treated with baricitinib who achieved SALT score ≤20 through Week 52.  
Methods: This analysis evaluated the proportion of patients achieving SALT score ≤10 or ≤5 among patients with severe AA pooled from the two BRAVE-AA trials who achieved SALT score ≤20 after treatment with baricitinib 4-mg or 2-mg at Weeks (W) 4, 8, 12, 16, 24, 36, and 52. Baseline demographics were evaluated to assess potential differences between patients with different levels of response. As-observed analyses used all collected data.  
Results: Among patients treated with baricitinib 4-mg, the proportions of SALT score ≤20 responders who achieved SALT score ≤10 at W4, 8, 12, 16, 24, 36, and 52 were 0% (0/2), 44.4% (8/18), 46.0% (23/50), 52.4% (55/105), 67.5% (106/157), 74.6% (150/201), and 75.0% (171/228), respectively. The proportions achieving SALT score ≤5 were 0%, 16.7%, 26.0%, 31.4%, 51.6%, 55.2%, and 62.7% at W52, respectively among the SALT score ≤20 responders at each timepoint. 
Among patients treated with baricitinib 2-mg, the proportions of SALT score ≤20 responders who achieved SALT score ≤10 at W4, 8, 12, 16, 24, 36, and 52 were 0% (0/2), 37.5% (3/8), 50.0% (7/14), 48.5% (16/33), 63.5% (33/52), 62.2% (51/82), and 71.0% (66/93), respectively. The proportions achieving SALT score ≤5 were 0%, 12.5%, 28.6%, 24.2%, 34.6%, 42.7%, and 47.3% at W52, respectively among the SALT score ≤20 responders at each timepoint. Patients achieving SALT score ≤10 or ≤5 tended to have less severe baseline disease characteristics relative to the overall population. 
Conclusions: A significant proportion of patients who achieved SALT score ≤20 with baricitinib treatment also achieved complete or nearly complete scalp coverage, with some patients achieving this as early as Week 8. The proportion of complete or nearly complete responders increased over time with continued therapy.
Characterizing Loss of Response Occurring in a Small Number of Patients During 3 Years of Long-Term Maintenance Therapy with Baricitinib 4-mg: Results From BRAVE-AA1 and -AA2 Trials
Authors: Senna Maryanne , Taylor Susan , Piraccini Bianca M. , Shapiro Jerry , Somani Najwa , Jedynak Jakub P. , Ogwu Samuel , Buchanan Andrew , Craiglow Brittany , Ohyama Manabu
Published: January 2025

Introduction: Baricitinib, a approved for adults with severe alopecia areata (AA), demonstrated a high level of sustained efficacy (89.1%) at Week 152 among patients who achieved a Severity of Alopecia Tool (SALT) score ≤20 at Week 52 following one year of treatment with once-daily baricitinib 4 mg in phase 3 trials (BRAVE-AA1, BRAVE-AA2). In this post hoc analysis, we characterize patterns of loss of response during maintenance treatment (Weeks 52–152) among the 10.9% (n=14) of patients who demonstrated loss of response (SALT score >20) at Week 152 and explore differences between patients who lost vs maintained response.
Methods: Patient records were reviewed to identify patients who demonstrated loss of response at Week 152. Descriptive statistics were used to summarize baseline characteristics and the timing and extent of loss for these patients.
Results: Baseline disease characteristics differed between those losing (10.9%, n=14/129) and those maintaining (89.1%, n=115/129) treatment response. Characteristics that were numerically more common among those losing vs maintaining response were a longer baseline duration of current episode (≥4 years; 50.0% vs 20.9%, respectively) and baseline very severe AA (SALT score 95–100; 64.3% vs 35.7%, respectively). Seven patients who lost response had received a COVID-19 vaccination and/or experienced a COVID-19 infection during the maintenance period; four of these patients had a vaccination or infection ≤6 months before their initial loss of response. Overall, time to loss of response varied: six lost response within the first 4 weeks of maintenance treatment (Weeks 52–56); eight lost response at or after Week 88. The magnitude of change in SALT score also varied: 35.7% (n=5) maintained a SALT score ≤30 throughout Weeks 52–152; 21.4% (n=3) worsened to a SALT score >90 at ≥1 maintenance period visit. The median SALT score at Week 152 among patients demonstrating loss of response was 32.5.
Conclusions: A small number of patients demonstrated loss of response at Week 152 during the maintenance phase of the BRAVE trials. A third of those who lost response maintained at least 70% scalp coverage throughout the two-year maintenance period, which followed one year of initial treatment. Future research is needed to confirm what factors potentially trigger loss of response on baricitinib monotherapy and to determine the potential role of adjunctive therapies in mitigating this risk.
A clinical case of elimination of obstructive jaundice caused by Ascaris lumbricoides
Authors:   PhD (Med), Assistant of the Department of Neimark Surgery Faculty, APE, Altai State Medical University of the Ministry of Health of the Russian Federation, Tseimakh A.E. , Kurtukov V.A. ,   PhD (Med), Head of the Endoscopy Department, RSBIH City Hospital No.5, Barnaul, Shoikhet Ya.N. ,   Doct.Sc. (Med), Professor, Corresponding Member of the Russian Academy of Sciences, Head of the Department of Neimark Surgery Faculty, APE, Altai State Medical University of the Ministry of Health of the Russian Federation
Published: January 2025

The article presents a clinical case of elimination of obstructive jaundice caused by Ascaris lumbricoides. The patient was admitted with a clinic of obstructive jaundice, presumably caused by choledocholithiasis against the background of a long history of cholelithiasis, chronic calculous cholecystitis. After two attempts of lithoextraction in the lumen of the common bile duct, a round parasite was detected, which extracted and sent for laboratory was testing, where the diagnosis of ascariasis was confirmed. The clinic of obstructive jaundice was dropped out.
Keywords: ascariasis, obstructive jaundice.
РАСПРЕДЕЛЕНИЕ ВАЛОВОЙ ФОРМЫ МЕДИ В ПОЧВЕННОМ ПРОФИЛЕ ДЕРНОВО-ПОДЗОЛИСТЫХ СУПЕСЧАНЫХ И ПЕСЧАНЫХ ПОЧВ
Authors: ПАВЛОВ А А.
Published: January 2025

Исследование направлено на изучение особенностей распределения валовой формы меди по генетическим горизонтам почвенного профиля дерново-подзолистых супесчаных и песчаных почв земель сельскохозяйственного назначения Рязанской области и определение современной фоновой концентрации. Для решения поставленных задач было заложено 10 шурфов глубиной до 150 см в Касимовском, Ермишинском, Шиловском, Сасовском, Клепиковском, Кадомском районах Рязанской области в период с 2016 по 2023 гг., проанализирована глубина и особенности строения почвенных слоев, влияние на условия миграции меди. По результатам определения содержания меди выполнен расчет фоновой концентрации. Проведен сравнительный анализ предлагаемого современного регионального фонового значения с общеизвестными значениями мировых и отечественных исследователей: ориентировочными фоновыми концентрациями для средней полосы России по СП 502.1325800.2021, гигиеническими нормативами характеризующими ориентировочную допустимую концентрацию вещества в почве по СанПиН 1.2.3685-21, почвами мира по материалам международного геохимического атласа, почвами мира по А.П...

The .study is aimed at studying the distribution features of the gross form of copper in the genetic horizons of the soil profile of sod-podzolic sandy loam and sandy soils of agricultural lands in the Ryazan region and determining the current background concentrations. To solve the tasks, 10 pits up to 150 cm deep were dug in Kasimovsky, Ermishinsky, Shilovsky, Sasovsky, Klepikovsky, Kadomsky districts of the Ryazan region in the period from 2016 to 2023, the depth and structural features of the soil layers, the impact on the conditions of copper migration were analyzed. Based on the results of determining the copper content, the background concentration was calculated. A comparative analysis of the proposed modern regional background value was carried out with well-known values of world and domestic researchers: approximate background concentrations for the middle zone of Russia according to SP 502.1325800.2021, hygienic standards characterizing the approximate permissible concentration of a substance in the soil according to SanPiN 1.2.3685-21, soils of the world according to the materials of the international geochemical atlas, soils of the world according to A.P...
ЗАЩИТА ПРИРОДНЫХ И ИСКУССТВЕННЫХ ОБЪЕКТОВ ОТ ВОЗДЕЙСТВИЯ ИМПУЛЬСА ДАВЛЕНИЯ С ПОМОЩЬЮ НАСЫПНОЙ ПОРИСТОЙ ПРЕГРАДЫ
Authors: ГИМАЛТДИНОВ И К. , ХУСАИНОВ И Г. , ГАЛИЕВ А Л.
Published: January 2025

В работе исследовано отражение импульса давления от насыпной пористой преграды, расположенной в жидкости. Сама преграда насыщена газом Рассмотрены два варианта: а) поры на границе «жидкость - пористая преграда» «открыты»; б) поры - «закрыты». Написаны граничные условия и получены коэффициенты прохождения и отражения волны от первой и второй границ преграды. В математической постановке учитываются межфазные силы взаимодействия, а также тепловой обмен между материалом скелета пористой среды и насыщающим среду газом. Построены графики исходного, отраженного и прошедшего через преграду импульса. Установлено, что поведение импульса сильно зависит от значения начальной объемной доли газовой фазы В частности, при уменьшении объемной доли газа с 0,9 до 0,5 происходит увеличение амплитуды прошедшего через вторую границу импульсы в четыре раза. Эволюция импульса давления слабо зависит от начального радиуса пор среды, теплообменных процессов и сил взаимодействия между газом и скелетом. Полученные результаты могут быть применены при создании искусственных средств из пористых материалов с целью защиты различных объектов от разрушения при воздействии импульсом давления.

The work investigated the reflection of a pressure pulse from a bulk porous barrier located in a liquid. The barrier itself is saturated with gas. Two options are considered: a) the pores at the "liquid - porous barrier" boundary are "open"; b) pores -"closed". Boundary conditions are written and the coefficients of transmission and reflection of the wave from the first and second boundaries of the obstacle are obtained. The mathematical formulation takes into account interfacial interaction forces, as well as heat exchange between the skeleton material of the porous medium and the gas saturating the medium. Graphs of the initial, reflected and transmitted impulses were constructed. It has been established that the behavior of the pulse strongly depends on the value of the initial volume fraction of the gas phase. In particular, when the gas volume fraction decreases from 0.9 to 0.5, the amplitude of the pulses passing through the second boundary increases fourfold. The evolution of the pressure pulse weakly depends on the initial radius of the pores of the medium, heat exchange processes and interaction forces between the gas and the skeleton. The results obtained can be used to create artificial means from porous materials in order to protect various objects from destruction when exposed to a pressure pulse.
The multiclass ARKA framework for developing improved quantitative RASAR models
Authors: Banerjee Arkaprava , Roy Kunal
Published: January 2025

Over the last decade, the field of Cheminformatics has witnessed a significant advancement in developing more robust and predictive quantitative structure-activity relationship (QSAR) models. Recently, the quantitative Read-Across Structure-Activity Relationship (q-RASAR) modeling has been reported to enhance the external predictivity of QSAR models. However, in some studies, the cross-validation metrics of the q-RASAR models show compromised values compared to the corresponding QSAR models. In this background, we have reported here an improved q-RASAR workflow coupled with the Arithmetic Residuals in K-groups Analysis (ARKA) framework. This improved workflow (ARKA-RASAR) considers two important aspects – the contribution of different QSAR descriptors to different experimental response ranges, and the identification of the similarity among close congeners based on both the selected QSAR descriptors and the contribution of different QSAR descriptors to different experimental response ranges. In this study, five different toxicity datasets that had been previously used for the development of QSAR and q-RASAR models were considered. We have developed hybrid ARKA models (consisting of a combination of QSAR descriptors and ARKA descriptors). These hybrid feature spaces were used to compute RASAR descriptors and develop ARKA-RASAR models. We have used the same modeling strategies (Partial Least Squares and Multiple Linear Regression) used to develop the previously reported QSAR and q-RASAR models for a fair comparison. In addition, these modeling algorithms are simple, reproducible, and transferable. The multi-criteria decision-making statistical approach, the Sum of Ranking Differences (SRD), inferred that the ARKA-RASAR models are the best-performing models, considering training, test, and cross-validation statistics. Two-way ANOVA was performed to show that the SRD values for the models from selected datasets and the four different modeling algorithms are significantly different. The least significant difference procedure ensures that the SRD values were significantly different for most models, presenting an unbiased workflow. A simple, free, and user-friendly Java-based tool – Multiclass ARKA-v1.0- has been developed to quickly and efficiently compute multiple ARKA descriptors based on the user's choice. The promising results and the ease of computation of ARKA and RASAR descriptors using our tools suggest that the ARKA-RASAR modeling framework may be a potential choice for developing highly robust and predictive models.
Holistic Lignin Valorization via Flow Photocatalysis towards vanillin and bioplasticizers
Authors: Marset Xavier , Montilla-Verdú Salvador , Rico Elio , Gómez-Caturla Jaume , Miranda Pinzón Mario , Balart Rafael , Aschauer Ulrich , Guijarro Néstor
Published: January 2025

Lignin valorization has become an urgent priority due to its status as the most abundant natural biopolymer containing aromatic structures, yet industrially unexploited. In this study, we present a photocatalytic method using a simple anthraquinone catalyst to break down lignin's recalcitrant structure into valuable monomers. Notably, this process is described under flow conditions for the first time. The monomer yields achieved are the highest reported in literature, although lignin is not fully depolymerized. However, the remaining oligomers can be effectively repurposed as polylactic acid (PLA) plasticizers, significantly enhancing PLA's mechanical properties and imparting shape-memory behavior. Thus, by processing lignin through a photochemical flow reactor, it is fully converted either into industrially relevant monomers, such as vanillin and syringaldehyde, or fragmented sufficiently for use as PLA plasticizers. This approach ensures that no wasteful by-products are generated, offering a sustainable pathway for lignin valorization.
Isayama–Mukaiyama Peroxidation Eschews Ozonolysis in Hydrodealkenylation
Authors: Kwon Ohyun , Dworkin Jeremy , Chen Zhuoxi , Cheasty Kathleen , Rubio Aris
Published: January 2025

Advancements in radical capture strategies have expanded the range of products accessible from alkenes through dealkenylative synthesis. These methods, however, are still limited, as they rely on ozonolysis to generate the key peroxide intermediates from alkenes. Ozonolysis has specific limitations: it is incompatible with alkenes containing electronrich aromatics, unproductive alkene substitution patterns, sterically hindered alkenes, internal nucleophiles and electrophiles, and allylic alcohols. In this paper, using Isayama–Mukaiyama peroxidation (IMP), we address the limitations of ozonolysis to rescue previously inaccessible alkene substrates and broaden the applicability of dealkenylative functionalization. In addition, we describe a novel reductive hydrogenation—employing catalytic [FeIII], catalytic benzenethiol, and γ-terpinene in refluxing methanol—to resolve β-scission issues associated with IMP-generated alkyl silylperoxides.
Dysfunction of perivascular adipose tissue in metabolic syndrome and obesity: the role of the gasotransmitter hydrogen sulfide (review)
Authors: Birulina J. G. , Voronkova O. V. , Ivanov V. V. , Buyko E. E. , Chernyshov N. A. , Gusakova S. V. , Kovalev I. V.
Published: January 2025

The development of novel strategies for diagnosing, treating, and preventing cardiovascular diseases (CVDs) linked to metabolic syndrome and obesity presents a significant challenge for the scientific community. There is a pressing need to identify effective compounds that target the underlying pathogenic mechanisms of these disorders. Increasing knowledge about the pathogenesis of CVDs has highlighted the crucial role of perivascular adipose tissue (PVAT) in maintaining cardiovascular homeostasis. PVAT is a metabolically active endocrine organ that plays a key role in regulating blood vessel tone, endothelial function, and the growth and proliferation of vascular smooth muscle cells. However, in metabolic disorders, there is a disruption in the functional activity of PVAT cellular components and an imbalance in the production of vasoactive substances, leading to the development and progression of CVDs. This review systematically examines the morphofunctional changes in PVAT associated with metabolic syndrome and obesity, emphasizes the dysfunction of PVAT as a key pathogenetic factor in cardiovascular disease, and evaluates the potential of hydrogen sulfide (H2S) produced by PVAT as a promising vasoregulatory agent based on existing data.
FoxP3+ T-regulatory lymphocytes in adipose tissue of cardiac surgery patients with different severity of coronary atherosclerosis
Authors: Dmitriukov A. A.
Published: January 2025

Introduction. T-regulatory (T-reg) lymphocytes as the main modulators of immunity, present in ectopic adipose tissue focuses, may be involved in the pathogenesis of atherosclerosis. Currently there is a lack of data regarding T-reg lymphocyte counts, particularly in epicardial (EAT) and thymic adipose tissue (TAT) in patients with coronary atherosclerosis.

Aim: To study the contents of FoxP3+ T-regulatory lymphocytes of peripheral blood, epicardial and thymic adipose tissue in patients with coronary atherosclerosis.

Materials and Methods. The study included a total of 26 cardiosurgical profile patients with coronary atherosclerosis. Patients were divided into two groups via Gensini Score (GS): first group with severe coronary atherosclerosis (GS > 26.5; n = 15) and second group without severe coronary atherosclerosis (GS ≤ 26.5; n = 11). In all patients, the levels of FoxP3 nuclear translocation and the relative content of CD4+CD25hiFoxP3 and CD4+CD25loFoxP3 T-reg lymphocytes in peripheral blood, epicardial, thymic, and subcutaneous adipose tissue (SAT) were determined by flow cytometry with imaging.

Results. The group of patients with severe coronary atherosclerosis was characterised by a statistically significant higher median of relative content of CD4+CD25hiFoxP3 T-lymphocytes (12.0 (6.5; 17.4) vs. 6.82 (3.32; 12.4) %; p = 0.031) and statistically significant lower median of nuclear translocation level of FoxP3 in CD4+CD25hiFoxP3 T-lymphocytes in TAT (30.82 (18.50; 40.80) vs. 51.91 (25.9; 71.00) %; p = 0.048). Statistically significant correlations between FoxP3 T-reg lymphocyte parameters in different adipose depots and lipid spectrum markers (TC, HDL-C) were found. There were inverse correlations found between EAT and TAT, in particular, between the relative contents of T-reg lymphocytes and of the FoxP3 nuclear translocation level.

Conclusion. Patients with severe coronary atherosclerosis (GS > 26.5 points) were characterised by an increased relative content of CD4+CD25hiFoxP3 T-lymphocytes in thymic adipose tissue and a decreased level of FoxP3 nuclear translocation in this cell subpopulation compared to patients with moderate atherosclerosis (GS ≤ 26.5 points). Identified correlations between relative content of T-reg lymphocytes and the level of FoxP3 nuclear translocation in thymic and epicardial adipose tissues suggest potential existence of T-reg lymphocyte recirculation in-between these ectopic adipose depots.
The Relationship Among Maximal Aerobic Capacity, Pulmonary Function Tests, and Cognitive Functions in Healthy Middle-Aged Adults
Authors: Canlı Umut , Kurt Cem , Özkan Mazhar , Yılmazer Kayatekin Ayşe Zeynep
Published: January 2025

Aim: This study aimed to investigate if maximal aerobic capacity and pulmonary function tests can be a predictor of cognitive function including
selective attention and inhibitory response in healthy middle-aged adults.
Material and Methods: The study involved 43 people, comprising 31 females and 12 males. The research included evaluations of maximal
aerobic capacity (VO2max), pulmonary function tests, and cognitive assessments. VO2max was assessed by the 1-mile Endurance Run/
Walk Test, and pulmonary function evaluations were conducted via a spirometer. Selective attention was measured via the d2 test, whilst
inhibitory response was evaluated using a computer-based Go/No-Go test.
Results: The TM parameter was not significantly predicted by TM Model 1 (F(4, 38) = 1.324, p = 0.279) or TM Model 2 (F(8, 34) = 1.752, p
= 0.122). Similarly, E1 Model 1 did not show statistical significance in predicting the E1 parameter. Analysis of the inhibitory parameters GCR
and NGRC also revealed no significant associations, as indicated by GCR Model 1 (F(4, 38) = 0.389, p = 0.815), GCR Model 2 (F(8, 34)
= 0.333, p = 0.947), NGRC Model 1 (F(4, 38) = 1.917, p = 0.128), and NGRC Model 2 (F(8, 34) = 2.042, p = 0.071). However, a moderate
positive correlation was observed between TM and FEV1 (r = 0.35, p < 0.05).
Conclusion: It can be concluded from these results that the VO2max test and the outcomes of the pulmonary function tests are not
reliable indicators of cognitive abilities in middle-aged, healthy persons. Nonetheless, FEV1 may function as a marker of selective attention.
Additional research involving a larger sample size is needed to better understand the relationship between maximal aerobic capacity,
pulmonary function tests, and cognitive performance
Identification of Risk Factors and Mortality Score Values Predicting Mortality in Pneumonia Patients Monitored in Intensive Care Units
Authors: Bayındır Serpil , Karatepe Ümit
Published: January 2025

Aim: Predicting the mortality risk of pneumonia patients in the intensive care unit is an important step in the treatment process. A number
of scoring systems have been developed to assess the severity of patients and predict prognosis. The aim of this study was to determine
the risk factors predicting mortality and mortality score values of pneumonia patients in intensive care unit in clinical prognostic evaluation.
Material and Methods: It was a single-center and retrospective study. Mechanical ventilation, hemodialysis requirement, inotrope support,
chest tube insertion, duration of intensive care unit stay, length of hospital stay, and 6-month mortality rates were recorded. SOFA, APACHE
II and PSI, CURB-65 and I-ROAD scores were calculated. Procalcitonin, C-reactive protein, albumin, creatinine, urea and lactate values
were evaluated by scoring.
Results: Of the 143 patients, 94 (65.7%) were discharged (Group 1: survivors), while 49 (34.2%) died (Group 2: exitus). Urea and lactate
showed a stronger correlation with mortality (p
Hemodiyaliz Hastalarında Semptom Yükü Deprem Sonrasında Artar mı? Prospektif Bir Kohort Çalışması
Authors: Yasar Emre , Karaaslan Tahsin , Pembegül İrem
Published: January 2025

Amaç: Hemodiyalize (HD) giren hastalar, hastalığın kendisinden, tedavisinden veya komorbid durumlarından dolayı birçok semptomla
karşılaşırlar. Bu çalışmanın amacı HD hastalarında semptom yükünün deprem öncesi ve deprem sonrası üçüncü ve altıncı aylarda prospektif
olarak değerlendirilmesi ve karşılaştırılmasıdır.
Gereç ve Yöntemler: 6 Şubat 2023 tarihli Kahramanmaraş depremleri öncesi diyaliz semptom indeksi (DSİ) değerlendirmesi yapılmış,
depremlerden üç ve altı ay sonra HD tedavisine ünitemizde devam eden 75 birey dahil edildi. Semptom yükü 30 sorudan oluşan bir anket olan DSİ ile değerlendirildi. Deprem öncesi verileri Kasım-Aralık 2022, deprem sonrası üçüncü ay verileri Mayıs 2023 ve altıncı ay verileri
Ağustos 2023’te toplandı.
Bulgular: Yaş ortalaması 58±14 olan 75 bireyin 26‘sı(%33.8) kadındı. Bireylerin deprem öncesi ortanca 19[12-23] semptomu mevcutken,
deprem sonrası üçüncü ayda ortanca 22[19-25] ve altıncı ayda ortanca 22[17-24] semptomu vardı(p
Rüptüre Abdominal Aort Anevrizmasında Zamanla Yarış: Hayatta Kalma ve Tedavi Sonuçlarının Retrospektif Analizi
Authors: Gür Ali Kemal , Arslantürk Oğuz
Published: January 2025

Amaç: Rüptüre abdominal aort anevrizmaları (rAAA) operasyon öncesi ve sonrası yüksek mortaliteye sahip acil cerrahi bir durumdur. Bu
çalışmanın amacı acil cerrahi tedavi edilen infrarenal abdominal aort anevrizmalarında operasyon öncesi, sırası ve sonrası mortaliteye etki
eden faktörlerin araştırılmasıdır
Gereç ve Yöntemler: Abdominal aort anevrizma rüptürü tanısı ile 2019-2024 yılları arasında acil ve açık cerrahi ile opere edilen 38 hasta
[erkek 34(%89,4), kadın 4(%10,6)] çalışmaya alınmıştır. Hastaların operasyon öncesi ve operasyon sonrası demografik özellikleri retrospektif
olarak incelenmiştir. Semptomların başlamasından sonra tedavi amaçlı gidilen hastanelere göre hastalar iki gruba ayrıldı. Acil servisimize
başvuran veya ambulans ile getirilen hastalar Grup-1 (n=17) ve dış merkezlerden tanı konulup tarafımıza refere edilen hastalar Grup-2
(n=21) olarak ayrıldılar.
Bulgular: Çalışmaya alınan 38 hastanın yaş ortalaması 63,57 ± 13,62 yıldı. Hastaların 34’ü erkek ve dördü kadındı. Eşlik eden risk faktörleri
kronik obstrüktif akciğer hastalığı (n=17, %50), diyabet (n=25, %65,7), hipertansiyon (n=33, %86,8), hiperlipidemi (n=35, %92,1) ve akut
böbrek yetersizliği (n=4, %10,5) idi. Toplam 9 (%23,6) hasta kaybedildi. Mortal seyreden hastaların hepsi yoğun bakım takipleri sırasında
(10 ± 9,6 gün) kaybedildi. Hastanemiz bölgeye hitap etmesi nedeniyle çevre illerden sevk edilen hastalarda mortalite daha yüksek görüldü.
Dokuz hastanın yedisi dış merkezde tanı konularak sevk edilen hastalardı. Mortalite sebepleri renal yetersizlik, multiorgan yetersizliği,
respiratuvar distrest sendromu ve sepsis olarak görüldü.
Sonuç: Karın ağrısı nedeniyle acil servise başvuran hastaların rAAA tanısı konulduktan sonra mümkün olan en kısa sürede opere edildiğinde
ölüm oranlarında önemli oranda azalma görülmektedir. Hipotansiyon, yüksek üre ve kreatinin seviyeleri, kan kaybı, yetersiz kan ve mayi
verilmesi, bilinç kaybı, kardiyak arrest operasyon öncesi mortaliteyi arttırıcı nedenlerdir. Kısa süren aortik kross klemp süresi, intraoperatif
kan kaybının minimum seviyeye indirilmesi, hastaları operasyon sırasında düşük tansiyondan korumak ve iyi bir diürez ile sağ kalım oranı
yükselmektedir.
IMPACT OF SWAMI VIVEKANANDA ON INDIAN POLITICS
Authors: Anu Anamika , Alam Md Jamshaid
Published: January 2025

•Particular life Swami Vivekananda was born on January 12, 1863, in Kolkata (also Calcutta), India. His birth name was Narendranath Datta. He came from a well-respected Bengali family with a strong cultural background. His father, Vishwanath Datta, was an enlightened lawyer, and his mother, Bhuvaneshwari Devi, was a deeply religious woman. Vivekananda grew up in an environment that encouraged learning and spirituality.From a young age, Vivekananda showed an interest in philosophy, spirituality, and different aspects of knowledge. He was known for his inquisitive nature, often asking deep questions about life and existence. His family supported his curiosity, and he received his early education at various schools in Kolkata. He attended the prestigious Presidency College, where he studied a wide range of subjects including philosophy, history, literature, and Western logic. His academic excellence and intellectual abilities were evident early on, and he was admired by his teachers and peers.Despite his academic success, Vivekananda felt that traditional education did not satisfy his deeper questions about life. He wanted to understand the true nature of the soul, God, and the universe. His search for spiritual knowledge led him to meet Sri Ramakrishna Paramahamsa, a great saint and spiritual teacher. Under Ramakrishna’s guidance, Vivekananda began to focus on his spiritual development and eventually became one of his most devoted disciples. This was a turning point in his life, as he decided to dedicate himself to spirituality and service to humanity.Vivekananda’s spiritual journey took him to various parts of India. He traveled extensively to learn from different teachers and to understand the problems facing Indian society. He also spent a lot of time in meditation and prayer, seeking inner peace and wisdom.
Development of an organizational and economic mechanism for the implementation of a product selection recommendation system
Authors: Kosogovskii B.V.
Published: January 2025

The study includes an analysis of existing problems that arise in the process of choosing a product, including complex technical devices. Based on the analysis, the paper proposes an organizational and economic mechanism that allows for the introduction of a recommendation system into the activities of an online store, which simplifies the process of choosing a product for the user. This tool will provide the organization with a competitive advantage and will increase website traffic, sales conversion and customer loyalty, which is especially relevant given the growing competition in online trading.
Mathematical model of work optimisation in the development of automated information systems
Authors: Abildinova G.M. , Aitimova A.M.
Published: January 2025

The paper presents the main components of the mathematical model represent ing the work process when creating an information system. The development of automat ed information systems requires significant expenditure of both resources and time. The process of developing an automated information system consists of numerous stages that require careful planning and management, namely analyzing system requirements, design, programming, debugging, implementation and maintenance. Estimation of the labor inten sity of programming and debugging stages is based on the approach of M. Halstead and amounts to 60-70% of the total cost of information system development. The tasks solved in this study allow us to make a step in the direction of increasing the level of information systems’ automatization. Implementation of the mathematical model of work optimization will allow increasing the overall level of development automation.
Twitter Sentiment Analysis Towards Candidates of the 2024 Indonesian Presidential Election
Authors: Cahyanti Rhoma , Desiana Nurul Maftuhah  , Aris Budi Santoso  , Indra Budi
Published: January 2025

Long before the elections were held, the topic related to elections was widely discussed on news portals and social media, including Twitter. A few studies related to the Indonesian election have tried to predict candidates who will run for the presidential election, but there has been no research that examines public sentiment on social media towards each of the potential candidates. The main objective of this study is to analyze the public sentiment in Twitter towards potential candidates for the 2024 Indonesian presidential election. This research seeks to fill the gaps in previous research and become a reference for further research regarding sentiment analysis for election prediction using Twitter. The presidential candidates used in the research are the top 3 candidates based on the Poltracking survey, namely Ganjar Pranowo, Prabowo Subianto, and Anies Baswedan. The data were taken from January until October 2022, more than a year before the general election began. To predict the sentiment, four different machine-learning methods were used and compared to each other. There are Naïve Bayes, Support Vector Machines, Random Forests, and Neural Networks.  Based on the sentiment results of each candidate, the highest sentiment towards Prabowo is neutral (55.49%), the highest sentiment towards Ganjar is positive (61.34%), and the highest sentiment towards Anies is neutral (44.84%). Results from the study also show that Anies was the presidential candidate who received more negative sentiment than the other two (56.63%). Meanwhile, Ganjar Pranowo got the most positive sentiment of all (42,69%). For the neutral sentiment, Anies Baswedan also got the most results (39,87%), followed by Prabowo (38.99%) and Ganjar Pranowo (21.14%). The result of the study also discovered that random forest and neural networks have the best performance for sentiment analysis.
Skin Cancer Classification Using a Hybrid Pre-trained CNN with Random Forest Classifier
Authors: Kostidjan Okky Darmawan , Purwanto Yudhi , Yuniarti Anny
Published: January 2025

Skin cancer, a leading cause of global mortality with 10 million deaths annually, is projected to increase rapidly if not diagnosed early. Traditional diagnosis relies on visual evaluation and histopathology, which are subjective and time-consuming. Recent advances in Convolutional Neural Networks (CNN) enable automated, accurate image analysis for early identification. This study explores pre-trained CNN models, including DenseNet-201, InceptionV3, MobileNet, ResNet50, and VGG16, by modifying them to better identify skin lesions as malignant or benign. The proposed models outperformed the state-of-the-art CNN models evaluated on publicity with traditional test data. The proposed models achieved 94.20% accuracy, which is higher than that of traditional CNN models.
Optimizing Book Stocktaking Process: Integration of Mobile Robot QRCode Commands with SLiMS
Authors: Mohammad Harry Khomas Saputra  , Pipit Anggraeni  , Wahyu Adhie Candra
Published: January 2025

This study presents a novel approach to enhance efficiency and precision in library management through the utilization of QR code technology. Integration of a mobile robot equipped with a QR code reader into the stocktake process, interfaced with the SliMS framework via an accessible API, lays the groundwork for an automated book inventory management system. This groundbreaking system enables the generation of dynamic QR code commands, facilitating seamless adjustments to bookshelf layouts. The autonomous and accurate movement of the mobile robot significantly reduces the time required for recording, allowing library staff to allocate more time to value-added tasks. The implementation of this method entailed configuring the mobile robot to navigate library aisles, scan QR codes on book spines, and transmit inventory data to the SliMS system in real time. Research findings indicate a notable decrease in inventory processing time, accompanied by an improvement in accuracy resulting from the eradication of manual data entry errors. Specifically, the calculated efficiency gain of approximately 66.81% highlights the substantial benefits of integrating the mobile robot scan QR code process compared to manual methods. In conclusion, the deployment of this automated book inventory management system, driven by QR code technology, marks a positive shift in library management practices, enhancing the efficiency of the book inventory process and overall operational effectiveness.
Improving Diabetes Prediction Accuracy in Indonesia: A Comparative Analysis of SVM, Logistic Regression, and Naive Bayes with SMOTE and ADASYN
Authors: Rahmawati Selly , Wibowo Arief , Masruriyah Anis Fitri Nur
Published: January 2025

This study aims to enhance the accuracy of diabetes prediction models in Indonesia by comparing the performance of Support Vector Machines (SVM), Logistic Regression, and Naïve Bayes algorithms, both with and without synthetic oversampling techniques such as SMOTE and ADASYN. The research addresses the issue of imbalanced datasets in medical diagnostics, specifically in predicting diabetes among Indonesian patients, where such imbalance often leads to biased predictions. A comprehensive dataset comprising 657 patient records from a Regional General Hospital in Indonesia was used, with 70% of the data allocated for training and 30% for testing. The results indicate that the SVM model combined with SMOTE achieved the highest accuracy of 95.8% and an AUC of 99.1, underscoring the effectiveness of these techniques in improving prediction performance. The findings of this study highlight the importance of selecting appropriate oversampling methods and algorithms to optimize diabetes prediction accuracy in the Indonesian context, providing valuable insights for future healthcare strategies.
Utilization of Household Organic Waste into Biogas and Integrated with IoT
Authors: Indra Maulana Bintang , Suryamiharja Andhika , Wisesa Pradipa Catya , Rendy Munadi  , Sussi Sussi
Published: January 2025

The increase in population impacts several environmental sectors, particularly the use of natural gas energy for household needs, such as LPG (Liquefied Petroleum Gas). This has resulted in the depletion of natural gas reserves and a rise in LPG imports. Additionally, the growing population contributes to the accumulation of household waste, which can lead to excessive leachate production and greenhouse gas emissions. This issue is particularly concerning in developing countries like Indonesia due to its negative environmental impact. This research aims to provide a solution and contribute to reducing household waste accumulation by utilizing organic waste to create renewable energy in the form of biogas as an alternative to LPG. Biogas is produced through the fermentation of organic waste. Nutrient-rich fluids containing sugar can enhance the performance of methanogenic bacteria in biogas formation. In this study, we conducted nutritional testing on molasses and coconut water to determine which nutrients optimize biogas production efficiency by monitoring the pressure of the generated biogas. Generally, biogas comprises methane and carbon dioxide. It is important to note that excessive methane can lead to explosions, while high carbon dioxide levels contribute to greenhouse gas emissions. The quantities of methane and carbon dioxide produced during biogas generation can be influenced by temperature and humidity. Therefore, monitoring pressure, temperature, humidity, methane, and carbon dioxide levels in the biogas production process using the Internet of Things (IoT) is a prudent approach. The results indicate that a substrate mixed with molasses produces biogas at twice the pressure compared to coconut water. Furthermore, optimal biogas production with ideal methane and carbon dioxide levels, occurs at temperatures between 25-35°C under high humidity conditions. This suggests that mesophilic methanogenic bacteria thrive in tropical climates.
The Impact of Feature Extraction in Random Forest Classifier for Fake News Detection
Authors: Ariatmanto Dhani , Rifai Anggi Muhammad
Published: January 2025

The pervasive issue of fake news spreading rapidly on online platforms. causing a concerning dissemination of misinformation. The influence of fake news has become a pressing social problem, shaping public opinion in important events such as elections. This research focuses on detecting and classifying fake news using the Random Forest algorithm by investigating the impact of feature extraction techniques on classification accuracy, this study specifically employs the TF-IDF method. For this purpose, we used 44,898 English-language articles from the ISOT fake news dataset. The dataset is cleaned using tokenization and stemming then split into 75% training and 25% testing. The TF-IDF vectorizer technique was applied to convert text into numeric as feature extraction. This study has implemented a Random Forest classifier to predict real and fake news. The proposed model contributes to overall classification precision by comparing it to the existing models. This fake news detection highlights the efficacy of the TF-IDF vectorizer and Random Forest combination which achieved an impressive accuracy rate of 99.0%. This contribution highlights an effective strategy for combating misinformation through precise text classification.
Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification
Authors: Julianto Veri , Ahmad Rusadi Arrahimi  , Oky Rahmanto  , Mohammad Sofwat Aldi
Published: January 2025

Palm oil plantations in Indonesia face challenges in enhancing productivity and profitability, notably due to pest attacks that reduce production. Early identification and classification of plant conditions, particularly palm oil leaves, are crucial for mitigating losses. This study explores the application of artificial intelligence, specifically computer vision and machine learning, for disease detection. Various machine learning techniques, including Local Binary Pattern (LBP), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM), have been used in different studies with varying accuracy. This research focuses on modifying Particle Swarm Optimization (PSO) for feature selection in identifying diseases in palm oil leaves. The PSO modification combined with logistic regression and Bayesian Information Criterion (BIC) significantly enhances KNN performance. Accuracy improved from 95.75% to 97.85%, while precision, recall, and F1-score reached approximately 98.80%. Additionally, the modified KNN+PSO achieved the shortest computation time of 0.0872 seconds, indicating high computational efficiency. These results demonstrate that the PSO modification not only improves accuracy but also computational efficiency, making it an effective method for enhancing KNN performance in detecting palm oil leaf diseases.