bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Silver Nanoparticles‐Decorated Metal‐Organic Framework with Rapid and Sustained Antimicrobial Activity against Drug‐Resistant Candida albicans through Synergistic Chemodynamic and Sonodynamic Therapy
Authors: Zhang Hong , Zhang Yuanfei , Li Yiyang , Hu Min , Rong Zihan , Meng Lingjie , Zhang Xiaofei , Wen Luan , Liang Xiumin , Chen Zhaopeng , Liu Chengcheng 
Published: May 2023

AbstractVaginal candidiasis caused by Candida albicans is a chronic, recurrent disease that is difficult to treat. Current available antifungal drugs have limited efficacy and cause adverse effects necessitating novel therapeutic options. In this study, a novel metal‐organic framework (MOF) containing the sonosensitizer rose bengal (RB) and decorated with silver nanoparticles (AgNPs), Fe–MOF(RB)@AgNPs (MRA), is developed which integrates chemodynamic therapy (CDT) and sonodynamic therapy (SDT) with the long‐term antifungal effects of AgNPs into a single nanoscale entity. MRA exhibited low cytotoxicity in mammalian cells and strong catalytic activity for the conversion of H2O2 to •OH under acidic conditions, similar to those found in vaginal candidiasis. When exposed to ultrasound, MRA generated 1O2 and offered rapid synergistic fungicidal effects through CDT and SDT, as well as long‐lasting antifungal benefits through AgNPs, leading to the complete eradication of drug‐resistant C. albicans. Moreover, MRA exhibited 99.999% efficacy against a clinical isolate of drug‐resistant C. albicans at 120 µg mL−1. Hence, MRA has considerable potential for clinical applications in the treatment of drug‐resistant C. albicans‐induced vaginal candidiasis.
Beyond the usual climate? Factors determining flowering and fruiting phenology across a genus over 117 years
Authors: Bartlett Kelsey B. , Austin Matthew W. , Beck James B. , Zanne Amy E. , Smith Adam B. 
Published: May 2023

AbstractPremiseAlthough changes in plant phenology are largely attributed to changes in climate, the roles of other factors such as genetic constraints, competition, and self‐compatibility are underexplored.MethodsWe compiled >900 herbarium records spanning 117 years for all eight nominal species of the winter‐annual genus Leavenworthia (Brassicaceae). We used linear regression to determine the rate of phenological change across years and phenological sensitivity to climate. Using a variance partitioning analysis, we assessed the relative influence of climatic and nonclimatic factors (self‐compatibility, range overlap, latitude, and year) on Leavenworthia reproductive phenology.ResultsFlowering advanced by ~2.0 days and fruiting by ~1.3 days per decade. For every 1°C increase in spring temperature, flowering advanced ~2.3 days and fruiting ~3.3 days. For every 100 mm decrease in spring precipitation, each advanced ~6–7 days. The best models explained 35.4% of flowering variance and 33.9% of fruiting. Spring precipitation accounted for 51.3% of explained variance in flowering date and 44.6% in fruiting. Mean spring temperature accounted for 10.6% and 19.3%, respectively. Year accounted for 16.6% of flowering variance and 5.4% of fruiting, and latitude for 2.3% and 15.1%, respectively. Nonclimatic variables combined accounted for <11% of the variance across phenophases.ConclusionsSpring precipitation and other climate‐related factors were dominant predictors of phenological variance. Our results emphasize the strong effect of precipitation on phenology, especially in the moisture‐limited habitats preferred by Leavenworthia. Among the many factors that determine phenology, climate is the dominant influence, indicating that the effects of climate change on phenology are expected to increase.
Compartmentalization of specialized metabolites across vegetative and reproductive tissues in two sympatric Psychotria species
Authors: Schneider Gerald F. , Carlson Cole A. , Jos Elsa M. , Beckman Noelle G. 
Published: May 2023

AbstractPremiseThe specialized metabolites of plants are recognized as key chemical traits in mediating the ecology and evolution of sundry plant–biotic interactions, from pollination to seed predation. Intra‐ and interspecific patterns of specialized metabolite diversity have been studied extensively in leaves, but the diverse biotic interactions that contribute to specialized metabolite diversity encompass all plant organs. Focusing on two species of Psychotria shrubs, we investigated and compared patterns of specialized metabolite diversity in leaves and fruit with respect to each organ's diversity of biotic interactions.MethodsTo evaluate associations between biotic interaction diversity and specialized metabolite diversity, we combined UPLC‐MS metabolomic analysis of foliar and fruit specialized metabolites with existing surveys of leaf‐ and fruit‐centered biotic interactions. We compared patterns of specialized metabolite richness and variance among vegetative and reproductive tissues, among plants, and between species.ResultsIn our study system, leaves interact with a far larger number of consumer species than do fruit, while fruit‐centric interactions are more ecologically diverse in that they involve antagonistic and mutualistic consumers. This aspect of fruit‐centric interactions was reflected in specialized metabolite richness—leaves contained more than fruit, while each organ contained over 200 organ‐specific specialized metabolites. Within each species, leaf‐ and fruit‐specialized metabolite composition varied independently of one another across individual plants. Contrasts in specialized metabolite composition were stronger between organs than between species.ConclusionsAs ecologically disparate plant organs with organ‐specific specialized metabolite traits, leaves and fruit can each contribute to the tremendous overall diversity of plant specialized metabolites.
Increased oligomeric TDP‐43 in the plasma of Korean frontotemporal dementia patients with semantic dementia
Authors: Jamerlan Angelo M. , Shim Kyu Hwan , Youn Young Chul , Teunissen Charlotte , An Seong Soo A. , Scheltens Philip , Kim SangYun 
Published: May 2023

AbstractINTRODUCTIONSemantic dementia (SD) is a progressive neurodegenerative disease associated with impaired vocabulary that progresses to memory impairment. Post‐mortem immunohistochemical analysis is the current reliable method of differentiating TDP‐43 deposits in cortical tissue; no means of antemortem diagnosis exists in biofluids, let alone in plasma.METHODSHere the multimer detection system (MDS) was used to quantify the oligomeric TDP‐43 (o‐TDP‐43) concentrations in plasma of Korean SD patients (n = 16, 6 male, 10 female, ages 59–87). The o‐TDP‐43 concentrations were compared with the total TDP‐43 (t‐TDP‐43) concentrations quantified through conventional enzyme‐linked immunosorbent assay (ELISA).RESULTS AND DISCUSSIONOnly MDS showed a significant increase in o‐TDP‐43 concentrations in the plasma of patients with SD compared to other neurodegenerative disorders and normal controls (p < 0.05). Based on these results, o‐TDP‐43 concentrations through the application of MDS may be a useful plasma biomarker in SD‐FTD (frontotemporal dementia) diagnosis.
Foliar spraying of potassium gluconate promotes the synthesis of the seed oil of Styrax tonkinensis
Authors: Zheng Lihong , Hao Xianqin , Liu Zemao , Peng Huiwu , Chen Juan , Huang Weihe , Yu Fangyuan 
Published: May 2023

AbstractStyrax tonkinensis is a promising woody biodiesel species. In this experiment, we investigated how foliar spraying of potassium gluconate solution affected the production of seed oil in S. tonkinensis. Leaf spraying of potassium gluconate solution appreciably promoted the photosynthesis of S. tonkinensis leaves through both the light reaction and the dark reaction. By boosting the activity of enzymes involved in glucose metabolism and seed oil synthesis, foliar spraying of potassium gluconate solution also dramatically enhanced glucose metabolism and seed oil synthesis in the S. tonkinensis seeds. This indicates that foliar spraying with potassium gluconate solution discernibly improved the synthesis of seed oil in S. tonkinensis by encouraging the transit of photosynthetic products from the source to the reservoir and the flow of carbon into the seed oil synthesis in the seeds. Overall, the medium concentration of potassium gluconate solution (4 g/L) was found to be the most effective for increasing the oil content of S. tonkinensis seeds. While higher potassium gluconate solution concentrations (6 g/L) had a slight inhibitory effect on specific indicators (ACCase) during specific seed development periods. This study highlighted the importance of potassium for seed oil synthesis in woody plants and provided a useful foundation for future cultivation practices aimed at enhancing seed oil synthesis in woody plants.
Community psychoanalysis and the generative landscape of our times
Authors: Chow Lani , Gaspar Sandra , Kassoff Betsy , Leavitt Julie , Peltz Rachael 
Published: May 2023

AbstractIn this paper five members of the “Community Psychoanalytic Track and Consortium” (CPT&C) in San Francisco, California, each holding different positionalities and functioning in different roles, come together in dialog with the shared aim to bring themselves and their readers inside the CPT&C. This writing project recapitulates principles of the CPT&C's vision itself: to form polyvocal groups with the shared task of supporting each other in our various roles, and members of community mental health organizations in their work and lives. From that effort new forms of psychoanalytic learning and work are generated; in this instance the process translates into a new writing form.
Simultaneous confidence intervals from randomization tests with application in testing bioequivalence with multiple endpoints
Authors: Dufera Abdisa G. , Xiong Cui , Xu Jin 
Published: May 2023

AbstractWe propose a method to construct simultaneous confidence intervals for a parameter vector from inverting a series of randomization tests (RT). The randomization tests are facilitated by an efficient multivariate Robbins–Monro procedure that takes the correlation information of all components into account. The estimation method does not require any distributional assumption of the population other than the existence of the second moments. The resulting simultaneous confidence intervals are not necessarily symmetric about the point estimate of the parameter vector but possess the property of equal tails in all dimensions. In particular, we present the constructing the mean vector of one population and the difference between two mean vectors of two populations. Extensive simulation is conducted to show numerical comparison with four methods. We illustrate the application of the proposed method to test bioequivalence with multiple endpoints on some real data.
A Bayesian adaptive design for dual‐agent phase I–II oncology trials integrating efficacy data across stages
Authors: Jiménez José L. , Zheng Haiyan 
Published: May 2023

AbstractCombination of several anticancer treatments has typically been presumed to have enhanced drug activity. Motivated by a real clinical trial, this paper considers phase I–II dose finding designs for dual‐agent combinations, where one main objective is to characterize both the toxicity and efficacy profiles. We propose a two‐stage Bayesian adaptive design that accommodates a change of patient population in‐between. In stage I, we estimate a maximum tolerated dose combination using the escalation with overdose control (EWOC) principle. This is followed by a stage II, conducted in a new yet relevant patient population, to find the most efficacious dose combination. We implement a robust Bayesian hierarchical random‐effects model to allow sharing of information on the efficacy across stages, assuming that the related parameters are either exchangeable or nonexchangeable. Under the assumption of exchangeability, a random‐effects distribution is specified for the main effects parameters to capture uncertainty about the between‐stage differences. The inclusion of nonexchangeability assumption further enables that the stage‐specific efficacy parameters have their own priors. The proposed methodology is assessed with an extensive simulation study. Our results suggest a general improvement of the operating characteristics for the efficacy assessment, under a conservative assumption about the exchangeability of the parameters a priori.
Teaching Python programming for bioinformatics with Jupyter notebook in the Post‐COVID‐19 era
Authors: Gupta Yash Munnalal , Kirana Satwika Nindya , Homchan Somjit , Tanasarnpaiboon Supatcharee 
Published: May 2023

AbstractThe COVID‐19 pandemic has forced the Bioinformatics course to switch from on‐site teaching to remote learning. This shift has prompted a change in teaching methods and laboratory activities. Students need to have a basic understanding of DNA sequences and how to analyze them using custom scripts. To facilitate learning, we have modified the course to use Jupyter Notebook, which offers an alternative approach to writing custom scripts for basic DNA sequence analysis. This approach allows students to acquire the necessary skills while working remotely. It is a versatile and user‐friendly platform that can be used to combine explanations, code, and results in a single document. This feature enables students to interact with the code and results, making the learning process more engaging and effective. Jupyter Notebook provides a hybrid approach to learning basic Python scripting and genomics that is effective for remote teaching and learning during the COVID‐19 pandemic.
Deep convolutional architecture‐based hybrid learning for sleep arousal events detection through single‐lead EEG signals
Authors: Foroughi Andia , Farokhi Fardad , Rahatabad Fereidoun Nowshiravan , Kashaninia Alireza 
Published: May 2023

AbstractIntroductionDetecting arousal events during sleep is a challenging, time‐consuming, and costly process that requires neurology knowledge. Even though similar automated systems detect sleep stages exclusively, early detection of sleep events can assist in identifying neuropathology progression.MethodsAn efficient hybrid deep learning method to identify and evaluate arousal events is presented in this paper using only single‐lead electroencephalography (EEG) signals for the first time. Using the proposed architecture, which incorporates Inception‐ResNet‐v2 learning transfer models and optimized support vector machine (SVM) with the radial basis function (RBF) kernel, it is possible to classify with a minimum error level of less than 8%. In addition to maintaining accuracy, the Inception module and ResNet have led to significant reductions in computational complexity for the detection of arousal events in EEG signals. Moreover, in order to improve the classification performance of the SVM, the grey wolf algorithm (GWO) has optimized its kernel parameters.ResultsThis method has been validated using pre‐processed samples from the 2018 Challenge Physiobank sleep dataset. In addition to reducing computational complexity, the results of this method show that different parts of feature extraction and classification are effective at identifying sleep disorders. The proposed model detects sleep arousal events with an average accuracy of 93.82%. With the lead present in the identification, the method becomes less aggressive in recording people's EEG signals.ConclusionAccording to this study, the suggested strategy is effective in detecting arousals in sleep disorder clinical trials and may be used in sleep disorder detection clinics.
Impact of new‐onset and preexisting neurological disorders in COVID‐19 patients
Authors: Lindemann Sarah , Böhm Markus , Gonnert Falk , Bösel Julian , Schubert Roger , Musleh Rita , Günther Albrecht 
Published: May 2023

AbstractBackground and PurposeCoronavirus disease (COVID‐19) is still considered a global pandemic. The prognosis of COVID‐19 patients varies greatly. We aimed to assess the impact of preexisting, chronic neurological diseases (CNDs) and new‐onset acute neurological complications (ANCs) on the disease course, its complications, and outcomes.MethodsWe conducted a monocentric retrospective analysis from all hospitalized COVID‐19 patients between May 1, 2020 and January 31, 2021. Employing multivariable logistic regression models, we explored the association of CNDs and ANCs separately with hospital mortality and functional outcome.ResultsA total of 250 among 709 patients with COVID‐19 had CNDs. We found a 2.0 times higher chance of death (95% confidence interval [CI]: 1.37–2.92) for CND patients than for non‐CND patients. The chance for an unfavorable functional outcome (modified Rankin Scale > 3 at discharge) was 1.67 times higher in patients with CNDs than those without (95% CI: 1.07–2.59). Furthermore, 117 of all patients had 135 ANCs in total. We observed a 1.86 times higher chance to die (95% CI: 1.18–2.93) for patients with ANCs than without. The chance for a worse functional outcome was 3.6‐fold higher in ANC patients than without (95% CI: 2.22–6.01). Patients with CNDs had 1.73 times higher odds for developing ANCs (95% CI: 0.97–3.08).ConclusionPreexisting neurologic disorders or ANCs in COVID‐19 patients were associated with higher mortality and poorer functional outcome at discharge. Furthermore, development of acute neurologic complications was more frequent in patients with preexisting neurologic disease. Early neurological evaluation appears to be an important prognostic factor in COVID‐19 patients.
Human body donors at academic institutions in the United States of America: An investigative study
Authors: Wyatt Taylor B. , Bagian Lauren K. , Balta Joy Y. 
Published: May 2023

AbstractWork with deceased human bodies to enhance anatomical education was first documented in the 3rd century BCE. However, the development of body donation programs provided many new opportunities for medical education. The aim of this study was to investigate the work supported by human body donors at academic institutions in the United States and to evaluate the ethical oversight process and the preparation methods used. A questionnaire was developed using Qualtrics and sent to 125 body donation programs in the United States. Representatives from a total of 69 institutions completed the questionnaire. The data showed that human body donations across the United States are used in teaching, clinical skills training, research, and educational outreach. Most institutions worked with hard‐fixed donors for teaching and some with soft‐preserved and unembalmed donors for clinical skills training. Among the participating programs, only 33 representatives reported an ethical approval process for conducting research involving human body donors. These findings raise ethical concerns related to the operation of body donation programs due to the lack of oversight. Furthermore, some institutions allowed faculty and staff to take photographs of donated bodies for educational purposes, which is often not disclosed on the consent form. The data also showed the need for more discussion on anatomical legacy collections housed at these institutions in the United States.
Cancer care patterns in South Korea: Types of hospital where patients receive care and outcomes using national health insurance claims data
Authors: Choi Dong‐Woo , Kim Sun Jung , Kim Seungju , Kim Dong Wook , Jeong Wonjeong , Han Kyu‐Tae 
Published: May 2023

AbstractBackgroundAlthough strengthening coverage has improved cancer care, there are concerns related to medical distortion. Previous studies have only examined whether patients visit a specific hospital, and not the continuum of patients with cancer, resulting in a lack of evidence in South Korea. This study aimed to investigate the patterns in hospital type for cancer care and analyze their association with outcomes.MethodsThe data for this study were obtained from the National Health Insurance Services Sampled Cohort database. This study included patients with four types of cancer (top four cancer incidence in 2020): gastric (3353), colorectal (2915), lung (1351), and thyroid (5158) cancer. The latent class mixed model was used to investigate cancer care patterns, and multiple regression or survival analysis was performed to examine medical cost, length of stay (LOS), and mortality.ResultsThe patterns in each cancer type were classified into two to four classes, namely, mainly visited clinics or hospitals, mainly visited general hospitals, mainly visited tertiary hospitals (MT), and tertiary to general hospitals through trajectory modeling based on the utilization of cancer care. Compared to the MT pattern, other patterns were generally associated with higher cost, LOS, and mortality.ConclusionThe patterns found in this study may be a more realistic way of defining patients with cancer in South Korea compared to previous studies, and its association‐related outcomes may be used as a basis to address problems in the healthcare system and prepare alternatives for patients with cancer. Future studies should review cancer care patterns related to other factors such as regional distribution.
Potential noninvasive biomarkers for the malignant transformation of oral leukoplakia: A systematic review and meta‐analysis
Authors: Huang Yan , Zhang Qiufang , Guo Zhenzhen , Deng Guanhong , Chen Ruibin , Zheng Yanfen 
Published: May 2023

AbstractBackgroundThe rising cancer incidence in patients with oral leukoplakia (OL) highlights the importance of identifying potential biomarkers for high‐risk individuals and lesions because these biomarkers are useful in developing personalized management strategies for OL patients.This study systematically searched and analyzed the literature on potential saliva and serum biomarkers for OL malignant transformation.MethodsPubMed and Scopus were searched for studies published up to April 2022. The primary outcome of this study was the difference in biomarker concentrations in saliva or serum samples from healthy control (HC), OL and oral cancer (OC) populations. Cohen's d with 95% credible interval was calculated and pooled using the inverse variance heterogeneity method.ResultsA total of seven saliva biomarkers were analyzed in this paper, including interleukin‐1alpha, interleukin‐6 (IL‐6), interleukin‐6‐8, tumor necrosis factor alpha (TNF‐α), copper, zinc, and lactate dehydrogenase. IL‐6 and TNF‐α exhibited statistically significant deviations in comparisons between HC versus OL and OL versus OC. A total of 13 serum biomarkers were analyzed, including IL‐6, TNF‐α, C‐reactive protein, total cholesterol, triglycerides, high‐density lipoproteins, low‐density lipoproteins, albumin, protein, β2‐microglobulin, fucose, lipid‐bound sialic acid (LSA), and total sialic acid (TSA). LSA and TSA exhibited statistically significant deviations in comparisons between HC versus OL and OL versus OC.ConclusionIL‐6 and TNF‐α in saliva have strong predictive values for OL deterioration, and LSA and TSA concentration levels in serum also have the potential to serve as biomarkers for OL deterioration.