bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis
Authors: He Libing , Chen Meining , Li Hongjian , Shi Xiran , Qiu Zhiqiang , Xu Xiaoxue 
Published: October 2024

Background and purposeDifferentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), incomparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs.MethodsIn total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student’s t-test or the Mann–Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves.ResultsIsotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p &lt; 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897).ConclusionsAdvanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment.
Predictive diagnostic value of mean platelet volume to platelet count and neutrophil to lymphocyte ratios in the gray zone of prostate cancer with tPSA between 4 to 10 ng/mL
Authors: Yi Xinyu , Li Jin , Li Yilin , Huang Tao , Xiong Baiyi , Zhang Feng , Zhao Zhaoyi 
Published: October 2024

ObjectiveExploration of the Predictive Diagnostic Value of Mean Platelet Volume to Platelet Count Ratio (MPV/PLT,PVI) and Neutrophil-to-Lymphocyte Ratio (NLR) in the tPSA Gray Zone of Prostate CancerMethodsA retrospective study was conducted on 65 prostate cancer (Pca) patients and 52 benign prostatic hyperplasia (BPH) patients who underwent transperineal prostate biopsy at Xiangtan Central Hospital from December 2021 to December 2023. Descriptive statistics and logistic regression models were used to investigate the predictive diagnostic value of PVI and NLR in the tPSA gray zone of prostate cancer. Receiver operating characteristic (ROC) curves were constructed based on PVI and NLR values to determine the classification thresholds.ResultsA total of 117 patients were enrolled, including 65 cases of prostate cancer (PCa) and 52 cases of benign prostatic hyperplasia (BPH). There were no statistically significant differences in age, BMI, history of hypertension, history of diabetes, history of coronary heart disease, pre-biopsy white blood cell count, history of drinking, history of smoking, and tPSA between the PCa and BPH patients. The results of logistic regression analysis showed that PVI (OR=2.03, 95%CI: 1.34~3.07, P&lt;0.00) and NLR (OR=0.32, 95%CI: 0.18~0.58, P&lt;0.00) were independent predictors for diagnosing prostate cancer in the tPSA gray zone (VIF=1.04).The maximum area under the curve (AUC) for PVI was 0.70, with an optimal cut-off value of 0.05 (P ≤ 0.01). The maximum AUC for NLR was 0.76, with an optimal cut-off value of 2.86 (P ≤ 0.01).The calibration curve showed good consistency between the predicted and actual outcomes in both the PCa and BPH groups, indicating that the nomogram model had good predictive performance.When using PVI and NLR to plot the receiver operating characteristic (ROC) curves to predict the assessment of PCa in the tpsa gray zone, the area under the curve (AUC) for PVI was the largest at 0.70, with an optimal cutoff value of 0.05 (P ≤ 0.01). The AUC for NLR was the largest at 0.76, with an optimal cutoff value of 2.86 (P ≤ 0.01).ConclusionPVI and NLR have certain predictive diagnostic value for Pca in the tPSA gray zone, and appropriate use of PVI and NLR can improve the positive rate of early screening for Pca in the gray zone.
Enhancing analgesia in acute renal colic pain: a randomized controlled trial of gabapentin adjunct to ketorolac-based regimen
Authors: Kianpour Parisa , Valavioun Parmis , Payandemehr Pooya , Safaei Arash , Borhani Yasaman , Honarmand Hooshyar , Mojtahedzadeh Mojtaba , Basiri Kamal , karimpour-Razkenari Elahe , Najmeddin Farhad 
Published: October 2024

BackgroundRenal colic is characterized by severe pain that is highly disabling. Gabapentin, an antiepileptic medication, is often recommended as a first-line therapy for neuropathic pain. However, its effectiveness in managing somatic pain, which is defined as the result of activity by pain receptors in the deep tissues, such as renal colic pain, is not as well-established.MethodA phase 3 randomized clinical trial was conducted to evaluate the adjuvant analgesic effects of gabapentin on acute renal colic pain. Eligible patients participated in the study via random allocation to the control or gabapentin groups using the block randomization method. All patients received a shared regimen of ketorolac and rescue morphine as the conventional analgesic treatment for renal colic pain. Gabapentin was added as an adjuvant analgesic for the gabapentin group.ResultA total of 63 individuals with an average age of 41.35 ± 13.08, were enrolled and completed the study. At the time of admission, there were no significant differences between the baseline characteristics of two groups, with exception of weight. The gabapentin group showed a significantly higher percentage of patients with pain severity of less than 5 after 60 and 90 min, as well as a significantly lower percentage of morphine rescue requirement and total morphine intake (mg) and mg/kg.ConclusionIn cases of acute renal colic, gabapentin significantly decreases both the amount of morphine required and the degree of pain, indicating that it may be a useful adjutant to standard analgesic regimens. Treatment regimens that include gabapentin may help individuals manage their pain and become less reliant on opioids.
Clinical Trial Registrationhttps://irct.behdasht.gov.ir/trial/56066, identifier: IRCT20200322046833N2.
Processing of prosodic cues of uncertainty in autistic and non-autistic adults: a study based on articulatory speech synthesis
Authors: Bellinghausen Charlotte , Schröder Bernhard , Rauh Reinhold , Riedel Andreas , Dahmen Paula , Birkholz Peter , Tebartz van Elst Ludger , Fangmeier Thomas 
Published: October 2024

IntroductionWe investigated the prosodic perception of uncertainty cues in adults with Autism Spectrum Disorder (ASD) compared to neurotypical adults (NTC).MethodWe used articulatory synthetic speech to express uncertainty in a human-machine scenario by varying the three acoustic cues pause, intonation, and hesitation. Twenty-eight adults with ASD and 28 NTC adults rated each answer for uncertainty, naturalness, and comprehensibility.ResultsBoth groups reliably perceived different levels of uncertainty. Stimuli were rated as less uncertain by the ASD group, but not significantly. Only when we pooled the recipients’ ratings for all three cues, did we find a significant group difference. In terms of reaction time, we observed longer reaction times in the ASD group compared to the neurotypical comparison group for the uncertainty level hesitation &amp; strong intonation, but the differences were not significant after Bonferroni correction. Furthermore, our results showed a significant group difference between the correlation of uncertainty and naturalness, i.e. the correlation in the ASD group is significantly lower than in the NTC group. Obtained effect size estimates can inform sample size calculations in future studies for the reliable identification of group differences.DiscussionIn future work, we would like to further investigate the interaction of all three cues and uncertainty perception. It would be interesting to further vary the duration of the pause and also to use different types of fillers. From a developmental perspective, uncertainty perception should also be investigated in children and adolescents with ASD.
Psychological barriers to adherence to pharmacological treatment of cardiovascular risk conditions in healthcare workers
Authors: Flores-Mendoza Jessica Berenice , Robles García Rebeca , García-Méndez Mirna , Rodríguez-Argüelles Norma Liliana 
Published: October 2024

IntroductionCardiovascular diseases (CVD) are the leading cause of death globally. This burden of disease is particularly high among healthcare workers (HCW). However, adherence to treatment of well-known cardiovascular risk conditions (CRC) still represents a challenge, even among healthcare workers (HCW). Since the identification of modifiable related factors is a prerequisite for developing effective public health interventions, the purpose of this study was to develop a predictive model for adherence to pharmacological treatment (APT) for CRC in HCW, using psychological variables related to CVD mortality, such as the type A behavior pattern, perceived stress, depression, anxiety and attitudes toward treatment adherence.MethodsAn anonymous online survey was completed by a non-probabilistic sample of 1,377 Mexican HCW from tertiary public hospitals, with a diagnosis of only one of the following CRC: ischemic heart disease, diabetes, high blood pressure or dyslipidemia. Sociodemographic questionnaires and self-reported measures were used to collect data: PSS-14 for perceived stress, Type A Behavior Pattern Withdrawal Scale, HADS for anxiety and depression symptoms, the Attitudes toward Medication Scale and the Therapeutics Adherence Scale for Patients with Chronic Diseases.ResultsAnxiety and depression symptoms were higher in the group with risk for non-adherence, while perceived stress and positive attitudes toward medication were higher in the group with likelihood of adherence (p ≤ 0.05). The Type A behavior pattern and sociodemographic variables did not differ between groups. In a regression model, positive attitudes toward medication and perceived stress doubled APT (OR = 2.04, CI95% = 1.39–2.97; OR = 2.02, CI95% = 1.71–2,39, respectively) whereas depression decreased its likelihood (OR = 0.61, CI95% = 0.58–0.73).DiscussionIn conclusion, psychoeducation for patients with CRC should include information on the advantages of medication for treating their condition, even if they are HCW. Promoting adaptative coping skills to handle daily stressful events, including their CRC, could reduce the level of stress that could increase their APT but also their cardiovascular risk. Moreover, our data provide evidence regarding the importance of identifying and treating depressive symptoms as part of the standard care of this population.
Development of a dry powder formulation for pulmonary delivery of azithromycin-loaded nanoparticles
Authors: Madrid Sani Alison Tatiana , Ramos-Rocha Khellida Loiane V. , Sarcinelli Michelle Alvares , Chaves Marcelo Henrique da Cunha , Rocha Helvécio Vinícius Antunes , Léo Patrícia , Cerize Natália Neto Pereira , Zanin Maria Helena Ambrosio , Feitosa Valker Araujo , Rangel-Yagui Carlota de Oliveira 
Published: October 2024

The COVID-19 pandemic has raised concern regarding respiratory system diseases and oral inhalation stands out as an attractive non-invasive route of administration for pulmonary diseases such as chronic bronchitis, cystic fibrosis, COVID-19 and community-acquired pneumonia. In this context, we encapsulated azithromycin in polycaprolactone nanoparticles functionalized with phospholipids rich in dipalmitoylphosphatidylcholine and further produced a fine powder formulation by spray drying with monohydrated lactose. Nanoparticles obtained by the emulsion/solvent diffusion-evaporation technique exhibited a mean hydrodynamic diameter around 195–228 nm with a narrow monomodal size distribution (PdI &lt; 0.2). Nanoparticle dispersions were spray-dried at different inlet temperatures, atomizing air-flow, aspirator air flow, and feed rate, using lactose as a drying aid, resulting in a maximal process yield of 63% and an encapsulation efficiency of 83%. Excipients and the dry powder formulations were characterized in terms of morphology, chemical structure, thermal analyses and particle size by SEM, FTIR, DSC/TGA and laser light diffraction. The results indicated spherical particles with 90% at 4.06 µm or below, an adequate size for pulmonary delivery. Aerosolization performance in a NGI confirmed good aerodynamic properties. Microbiological assays showed that the formulation preserves AZM antimicrobial effect against Staphylococcus aureus and Streptococcus pneumoniae strains, with halos above 18 mm. In addition, no formulation-related cytotoxicity was observed against the human cell lines BEAS-2B (lung epithelial), HUVEC (endothelial) and HFF1 (fibroblasts). Overall, the approach described here allows the production of AZM-PCL nanoparticles incorporated into inhalable microparticles, enabling more efficient pulmonary therapy of lung infections.
Thermo- and pH-Responsible Gels for Efficient Protein Adsorption and Desorption
Authors: Poplewska Izabela , Strachota Beata , Strachota Adam , Poplewski Grzegorz , Antos Dorota 
Published: October 2024

Protein adsorption behavior was examined on poly(N-isopropylacrylamide-co-sodium methacrylate)-based hydrogels at different temperatures: 5, 20, and 37 °C, and pH: 4.5, 7, and 9.2. The hydrogels, whose covalent skeleton contains pendant anionic units due to the presence of the sodium methacrylate co-monomer, exhibited both thermo- and pH-sensitivity with different extents, which depended on the content of ionizable moieties and the cross-linker density. The hydrogel composition, temperature, and pH influenced the zeta potential of the hydrogels and their swelling properties. The proteins selected for the study, i.e., bovine serum albumin (BSA), ovalbumin (OVA), lysozyme (LYZ), and a monoclonal antibody (mAb2), differed in their aminoacidic composition and conformation, thus in isoelectric point, molecular weight, electrostatic charge, and hydrophobicity. Therefore, the response of their adsorption behavior to changes in the solution properties and the hydrogel composition was different. LYZ exhibited the strongest adsorption of all proteins with a maximum at pH 7 (189.5 mg ggel−1); adsorption of BSA and OVA reached maximum at pH 4.5 (24.4 and 23.5 mg ggel−1), whereas mAb2 was strongly adsorbed at 9.2 (21.7 mg ggel−1). This indicated the possibility of using the hydrogels for pH-mediated separation of proteins differing in charge under mild conditions in a water-rich environment of both the liquid solution and the adsorbed phase. The adsorption affinity of all proteins increased with temperature, which was attributed to the synergistic effects of attractive electrostatic and hydrophobic interactions. That effect was particularly marked for mAb2, for which the temperature change from 5 to 37 °C caused a twentyfold increase in adsorption. In all cases, the proteins could be released from the hydrogel surface by a reduction in temperature, an increase in pH, or a combination of both. This allows for the elimination of the use of salt solution as a desorbing agent, whose presence renders the recycling of buffering solutions difficult.
МОДЕЛИРОВАНИЕ СЛОЖНОПОСТРОЕННЫХ ТЕКТОНИЧЕСКИХ ЗОН ПРЕДУРАЛЬСКОГО КРАЕВОГО ПРОГИБА НА ОСНОВЕ РЕШЕНИЯ ОБРАТНЫХ ЗАДАЧ ГЕОФИЗИКИ
Authors: Маракова И.А. , Велыистова О.М. , Сабельников М.Ю. , Нуртазаева М.А. 
Published: October 2024

В статье представлены результаты исследований перспективной на крупные залежи газа Косью-Роговской впадины. В статье объясняется сущность геоплотностного моделирования и его совместимость с результатами интерпретации геолого-геофизических данных. Построение плотностных моделей проводилось с использованием программных средств EvDynlnversion и GCIS методом подбора, что давало возможность учитывать величину отклонения параметра плотности от начального приближения. По результатам обработки полученной информации построена геоплотностная модель исследуемой территории по региональному профилю 13-РС, непротиворечащая структурно-тектоническим и литологическим особенности строения исследуемой территории. В результате анализа комплекса данных построена сейсмогеологическая модель и выполнен палеотектонический анализ исследуемой территории.
The article presents the results of studies on the Kosyu-Rogovskaya depression, which has the potential for large gas deposits. The article explains the concept of geomodeling and its compatibility with the interpretation of geological and geophysical data. Density models were created using EvDynlnversion and GIS software, and the selection method allowed for the deviation of the density parameter to be taken into account. Based on this information, a geomodel of the study area was created according to regional profile 13-RS. This model does not conflict with the structural, tectonic, and lithological characteristics of the area. After analyzing the data, aseismogeological model and paleotectonic analysis were conducted forthe study region.
ДЕТЕРМИНИСТИЧЕСКИЙ АЛГОРИТМ F-X ДЕКОНВОЛЮЦИИ
Authors: Денисов М.С. , Серебряков В.С. 
Published: October 2024

Известно, что традиционная реализация алгоритма f-x деконволюции, разработанного с целью выделения сигнала на фоне случайного некоррелированного шума, может порождать интенсивные артефакты,искажающие волновую картину. Показано,что причина этого эффекта связана с неточностью статистического оценивания корреляционной функции. Предложено использовать вместо статистическогоалгоритма f-xдеконволюции ее детерминистический аналог. Работоспособность такого методадемонстрируется на модельных иреальныхданных.
It is known that the traditional implementation of the f-x deconvolution algorithm, designed to separate a seismic signal from background random noise, can generate intense artifacts that distort the wavefield. It is shown that the reason for this effect is related to the inaccuracy of the statistical estimation of the correlation function. It is proposed to use its deterministic analog instead of the statistical f-x deconvolution algorithm. The performance of this method is demonstrated on both the model and the real seismic data.
ПИКИРОВАНИЕ ПЕРВЫХ ВСТУПЛЕНИЙ СЕЙСМИЧЕСКИХ ВОЛН НА 20-ПРОФИЛЕ ПРИ ПОМОЩИ МАШИННОГО ОБУЧЕНИЯ И ОТОБРАЖЕНИЯ СЕЙСМИЧЕСКИХ ТРАСС В ФАЗОВОЕ ПРОСТРАНСТВО
Authors: Бурцев Г.Е. 
Published: October 2024

В статье предложен способ автоматического определения моментов времени прихода первых вступлений сейсмических волн на исходных сейсмических данных. Исследование ограничено 2D сейсмическими профилями. В основе способа лежит расчет энергии сейсмических трасс в фазовом пространстве с применением машинного обучения. Методика расчета энергии трасс детально описана. Приведена схема нейронной сети и структура сформированного тензора данных. Показана эффективность разработанной модели на примере данных трех разных месторождений Западной Сибири.
The new method of automatic detection of seismic waves first breaks arrival time is introduced in the text. The survey is dedicated to 2D seismic profiles. The core of this method is the calculation of seismic traces energy in their phase space and the usage of deep learning. The methodology of seismic traces energy calculation is explained in details. The scheme of neural network is given and the structure of data tensor is determined. The efficiency of having been developed model is shown using the seismic data from three different Western Siberia oilfields.
Программный алгоритм для определения категории риска объекта защиты с учетом интегрального показателя тяжести потенциальных негативных последствий пожара
Authors: Юркин Г.Ю. , Проскова Н.Ю. , Козлов Д.Ю. 
Published: October 2024

На основе Распоряжения Правительства РФ от 21 декабря 2023 г. № 3745-р “Об утверждении Концепции совершенствования контрольной (надзорной) деятельности до 2026 г. и плана-графика по ее реализации” рассмотрены вопросы актуализации программного обеспечения, используемого контролируемыми лицами при определении категории риска в области пожарной безопасности при применении риск-ориентированного подхода. Рассматриваются вопросы усовершенствованной математической модели, описывающий механизм принятия решений по категорированию объектов контроля в области пожарной безопасности. Получены расчетные математические формулы для определения интегрального показателя тяжести потенциальных негативных последствий пожара с учетом индекса индивидуализации подконтрольного лица. Разработан универсальный программный алгоритм в целях реализации вычислительных процедур для индивидуального объекта надзора с учетом его индекса индивидуализации. Результаты работы являются важными конструктивными компонентами программирования. Созданный программный алгоритм может быть легко детализирован и преобразован. Алгоритм не связан с какими-либо особенностями синтаксиса языков программирования, а также со спецификой функционирования конкретных ЭВМ, что делает его универсальным.Based on the Order of the Government of the Russian Federation dated December 21, 2023 No. 3745-r “On approval of the Concept for improving control (supervisory) activities until 2026 and the schedule for its implementation”, the issues of updating the software used by supervised persons in determining the risk category in the field of fire safety when applying the risk-oriented approach are considered. The issues of an improved mathematical model describing the decision-making mechanism for categorizing supervised objects in the field of fire safety are considered. The objective of the study is to obtain calculation mathematical formulas for determining the integral indicator of the severity of potential negative consequences of a fire, taking into account the individualization index of the supervised person. A universal software algorithm has been developed to implement computational procedures for an individual supervision object taking into account its individualization index. The results of the work are important constructive components of programming. The created software algorithm can be easily detailed and transformed. The algorithm is not associated with any features of the syntax of programming languages, as well as with the specifics of the functioning of specific computers, which makes it universal.