bluuebunny/crossref_metadata_2025 huggingface dataset:
The Interval Between Elevation of Blood Pressure and Proteinuria in Preeclampsia and Contributing Factors.
Authors: Ren Jie , Zhao Caiyun , Fan Zhuoran , Wang Yanli , Sheng Hongna , Hua Shaofang
Published: June 2023

Purpose: The new-onset proteinuria, as a pivotal sign for the representative renal lesion in preeclampsia, is still the most common diagnostic basis and has been proved relevant to the significantly abnormal sFlt-1/VEGF ratio in circulation. At the same time, the blood pressure control plays an vital role in the occurrence and evolution of proteinuria. Therefore, it is particularly helpful to investigate their internal for not only performing urinalysis for protein more legitimately but also evaluating the blood pressure level as well as the aggravation of illness, while the related research is limited.
Methods:This retrospective study included 515 preeclampsia and 358 normotensive pregnancies who labored in the Second Hospital of Tianjin Medical University from January 2016 to January 2020. At first, we described the onset circumstance of high blood pressure and proteinuria as well as the internal among the case group and the subgroups. Then, we decided the significant difference of the materials about the basic information, laboratory tests as well as the newborns between the case and normal group. Finally, the multi-factor ANOVA was used for the influencing factors of the internal.
Results:1. The two most common complications in preeclampsia were the proteinuria (88.35%) and placental dysfunction (5.05%). Moreover, 77.86% preeclampsia was diagnosed by abnormal blood pressure together with the new-onset proteinuria. 2.The average internal between the high blood pressure and proteinuria was 22 gestational days (from 0 to 106 days), and this interval was not significantly different between the mild and severe PE (26 days vs 21 days, P>0.05) but significantly different between the early-onset and late-onset PE (9 days vs 28 days, P<0.05). 3. The times of prenatal visit, serum creatinine in the early trimester, gestational time and diastolic blood pressure value when the initial high blood pressure appeared may influence the interval between the high blood pressure and proteinuria.
Conclusion:The new-onset proteinuria was still the prime parameter for identifying preeclampsia. The interval between the high blood pressure and proteinuria was probably relevant to the unbalance of sFlt-1/VEGF ratio and we should pay attention to monitor the proteinuria during the prenatal visit, especially for the pregnancies with less frequency of prenatal visits, higher serum creatinine in the early trimester, earlier onset time and higher diastolic blood pressure as the initial high blood pressure happened.
Probing quantum phase transitions via short depth quantum circuits for estimating quantum coherence and discrete Berry phases
Authors: Bowmick Dhiman , Liu Deren , Sengupta Pinaki , Tan Kok Chuan
Published: June 2023

Classical techniques for the simulation of complex many-body systems can be severely limited by the exponentially increasing dimensions of quantum systems, and prior assumptions are often required to efficiently extract information about non-local quantum properties. Short depth quantum algorithms are proposed that efficiently estimate non-local quantum properties such as the quantum coherence and discrete Berry phases to probe the quantum phase transitions in many body systems. The gate complexities of these algorithms scale linearly while the depth complexity scale logarithmically with system size. These algorithms are applied to probe the well-known Haldane to quantum paramagnetic phase transitions in spin-1 Heisenberg antiferromagnetic chains, which are topological phase transitions that cannot be identified via local order parameters. The algorithms are shown to be able to extract non-local information about the system give the correct signatures of topological phase transitions near critical points.
Active Huygens' metasurface based on in-situ grown conductive polymer
Authors: Menezes Leonardo , Tittl Andreas , Ren Haoran , Maier Stefan , Lu Wenzheng
Published: June 2023

Active metasurfaces provide unique advantages for on-demand light manipulation at a subwavelength scale for emerging applications of 3D displays, augmented/virtual reality (AR/VR) glasses, holographic projectors and light detection and ranging (LiDAR). These applications put stringent requirements on switching speed, cycling duration, controllability over intermediate states, modulation contrast, optical efficiency and operation voltages. However, previous demonstrations focus only on particular subsets of these key performance requirements for device implementation, while the other performance metrics have remained too low for any practical use. Here, we demonstrate an active Huygens’ metasurface based on in-situ grown conductive polymer with holistic switching performance, including switching speed of 60 frames per second (fps), switching duration of more than 2000 switching cycles without noticeable degradation, hysteresis-free controllability over intermediate states, modulation contrast of over 1400%, optical efficiency of 28% and operation voltage range within 1 V. Our active metasurface design meets all foundational requirements for display applications and can be readily incorporated into other metasurface concepts to deliver high-reliability electrical control over its optical response, paving the way for compact and robust electro-optic metadevices.
Expert-assisted and sub-unit-based molecular description enables ultra-fast and highly accurate prediction of the energy levels of non-fullerene acceptors in organic solar cells
Authors: Zhang Ting , Lai Joshua Yuk Lin , Shi Mingzhe , Li Qing , Yan He , Zhang Chen
Published: June 2023

Non-fullerene acceptors (NFAs) have recently emerged as an important class of materials enabling high-efficiency organic solar cells. However, most research activities on NFAs are carried out through a time-consuming trial-and-error experimental process with limited predictability. Therefore, there is a pressing need to develop a fast and efficient computational method to predict their properties, particularly their energy levels. Unfortunately, conventional computational or machine learning methods tend to produce large errors (0.2 - 0.5 eV) in energy level prediction. Moreover, the commonly used experimental method is also prone to large errors in determining the energy levels of NFAs. This paper introduces a novel ultra-fast machine learning method that accurately predicts NFA energy levels within only one second of computation on a common laptop computer. The method consists of two components: data cleansing and an expert-assisted sub-unit-based molecular description, which simplifies the complexity of molecular computation. Despite the limited data available for NFAs (less than a thousand), the method achieves a small average prediction error of 0.06 eV for energy levels, significantly outperforming known computational methods and even surpassing the classic experimental method, cyclic voltammetry (CV). This method is expected to accelerate NFA research and inspire the development of similar computation approaches to solve other material or molecular science problems.
Evaluation of Using Small Volume of Interest Regions for Clinical Kidney Dosimetry in 177Lu-DOTATATE Treatments
Authors: Khan Jehangir , Rydèn Tobias , Essen Martijn Van , Svensson Johanna , Bernhardt Peter
Published: June 2023

Introduction: A small volume of interest (SV) method has been proposed and used to obtain time-effective kidney dosimetry protocols for 177Lu-DOTATATE treatments. However, SV methods show only modest precision and accuracy compared to the whole-kidney parenchyma (WKP) segmentation approach. Here we aim to evaluate the influence of patient-specific partial volume effect corrections on kidney dosimetry calculations based on the WKP method, to perform a comparative analysis between the WKP and SV methods, and to determine how the use of multiple SVs affected the accuracy of clinical kidney dosimetry.
Methods: We obtained SPECT/CT of 18 patients at 24, 48, and 168 hours after injection of 177Lu-DOTATATE (7.3–7.8 GBq). The SPECTs were corrected for attenuation, scatter, and collimator detector response with Monte Carlo-based OSEM reconstruction (ASCC-SPECT) and post-filtered with a 0- to 12-mm Gaussian filter, or were only attenuation corrected with a Hann post-filter (AC-SPECT) as described in the first application of the SV method. Kidney dosimetry based on the manually segmented WKP was used as the golden standard. Recovery coefficients (RCs) for each WKP were determined by Monte Carlo simulations, and RCs for SVs were determined relative to the WKP method. Kidney absorbed doses were estimated based on measured activity concentrations fitted using the mono-exponential function. Uncertainties were measured for kidney dosimetry calculated based on the SV method with 1–5 VOIs with sizes of 4 mL (SV4), 2 mL (SV2), and 0.6 mL (SV0.6).
Results: The mean RCs of the WKP volumes (31–243 mL) in non-filtered ASCC-SPECT and AC-SPECT were 0.85 (0.73–0.90) and 0.62 (0.46–0.51), respectively. The uncertainty in the kidney dosimetry calculation based on one SV4 on each SPECT data-point was 10.4%, and decreased as the number of VOIs was increased from 1 to 5. With the SV2 method, using a mean of 5 VOIs per kidney parenchyma, the uncertainty decreased to 6.3%. The uncertainty of the WKP method was 5.5%.
Conclusion: Kidney dosimetry based on RC-corrected multiple SVs located on representative uptake regions in the kidney parenchyma is a fast approach that can provide satisfactory accuracy as compared to a single SV method.
Associations of Diverse Internet Device Use and Activities with Depression in Chinese Adolescents: Gender and Geographical Differences
Authors: Wang Sasa , Gao Chenzhuo , Yang Xueyan
Published: June 2023

Background After the COVID-19 outbreak, Chinese adolescents are increasingly dependent on the Internet. They use multiple devices and engage in various Internet activities. This study explored the associations of mobile/desktop device use and five popular activities with depression in different subgroups of Chinese adolescents. The classification of subgroups was based on gender and geographic disparities in digital technology use.
Methods Data were from China Family Panel Studies (CFPS) in 2020 and included 2,877 primary and secondary school students aged 10-19 years. We employed the ordinary least squares regression models with interaction terms to observe the gender and geographical differences in the relationship between diverse Internet device use and activities and depression.
Results Only prolonged Internet use, whether on all devices or either one, was found to be positively associated with their risk of depression; using the desktop device for less than 1 hour was found to have the opposite effect. Online learning and gaming occasionally, shopping, and posting WeChat Moments frequently were positively linked with depression. Subsequently, mobile device usage time and the frequency of viewing short videos were positively associated with girls’ risk of depression, while in boys, opposite associations were observed. Furthermore, for rural adolescents, despite the adverse effects of prolonged desktop device use, using mobile devices for 1 to 3 hours or desktop devices for less than 1 hour was associated with their reduced risk of depression. Less frequency of online learning, games, and posting WeChat Moments, or increased frequency of watching short videos, could mitigate their risk of depression. These Internet use variables exhibited different associations with depression risk among adolescents in provincial capitals, prefecture-level cities, and counties.
Conclusion Our study demonstrates that using mobile/desktop devices and engaging in various online activities can lead to disparate benefits and risks for Chinese adolescents, depending on their gender and geographic location. Findings guide parents and caregivers in helping children develop healthy and balanced Internet usage habits, considering children’s gender and residential area.
Design and Validation of a Medication Assessment Tool to Assess Prescribing Practice in The Management of Type 2 Diabetes: A Quality Improvement Study
Authors: Al-Sejari Fajer , Al-Taweel Dalal
Published: June 2023

Background: Prescribing is the number one therapeutic intervention made by physicians. There is an increase in both the number of medicines and the complexity of dosage regimens that patients are taking. This is in addition to the introduction of novel medications with new adverse effects’ profiles complicated by drug-drug or drug-disease interactions. Developing tools, based on evidence-based guidelines, will assist practitioners in identifying the best therapeutic management options, particularly for chronic diseases, and ensures quality care is provided to patients. This study aimed to develop and validate a medication assessment tool (MAT) to evaluate the quality of medication prescribing for patients with type 2 diabetes mellitus.
Methods: The development process of the MAT was based on three stages: i) development stage – which led to instrument construction; ii) judgment-quantifying stage (with the participation of 12 experts) - which involved two different approaches to quantify content validity of the instrument, where any criteria with a CVR < 0.566 and/or a I-CVI <78% were considered for removal; and iii) a feasibility stage - to ensure the tool’s fitness for purpose.
Results: The development stage resulted in the construction of the initial MAT, with 42 criteria. This draft went through a judgment-quantifying stage which resulted in 8 criteria having a CVR ≤0.566 and I-CVI<78%. Three criteria were removed, and five were retained. As a result, the final draft - MATDM2 - was developed with 39 criteria. A feasibility study on 30 electronic patient medication records revealed a total prescribing adherence score of 50.5% and a 61.6% documentation gap.
Conclusions: MATDM2 frames clinical guideline recommendations into a holistic set of criteria that are patient-centered and quantifiable. It serves as a quality assurance tool for prescribers in managing type 2 diabetes and offers a systematic approach to detect opportunities in improving prescribing in this complex disease.
Municipal-Level Variations in Violence Perpetration among Norwegian Adolescents and its Association with Health-Risk Behaviours, Family Predictors, and Municipal Characteristics: A Cross-Sectional Multilevel Study
Authors: Wondemu Michael Yisfashewa , Frøyland Lars Roar
Published: June 2023

Background
While studies have documented the prevalence and risk factors for adolescent violence, little is known about local differences and the combined impact of socioecological correlates on the perpetration of violence. This study examined municipal-level variation in violence perpetration among Norwegian adolescents. Drawn from the socio-ecological model, it investigated the variation in individual health-risk behaviours, family predictors and municipal characteristics associated with violence perpetration.
Methods
The study was based on data from Norway’s nationwide Ungdata surveys. It included data from students in lower secondary schools from surveys conducted in the years 2014 to 2016, in total containing responses from 119,346 students nested within 309 municipalities. A multilevel (two-level) logistic regression was used to estimate between-municipal differences in the perpetration of violence and its associated socio-ecological correlates.
Results
The results showed a small variation (1.58%) in violence perpetration between municipalities. Individual- and family-level predictors did not explain this difference. The addition of municipal-level factors marginally reduced the municipal-level variance, indicating that the factors, to a slight extent, explained the small variation in violence perpetration among Norwegian municipalities. All individual and family factors were associated with violence perpetration. A high proportion of higher education accomplishment was the only municipal factor for violence perpetration.
Conclusion
The findings may be important for policymakers seeking to reduce acts of violence, as they call for a greater focus on individual- and family-level factors than municipal characteristics.
The Effect of Newly Developed Home Bleaching Gels on Tooth Colour and Mineral Alteration
Authors: Kervancıoğlu Görkem , Sürmelioğlu Derya Gürsel
Published: June 2023

Objectives This study aimed to compare tooth mineralization and colour changes achieved with two newly developed experimental bleaching gels containing 16% CP or 6% HP with the FGM Whiteness Perfect (16% CP) and BioWhiten ProHome (6% HP) at-home bleaching systems.
Material and methods:Ninety-six maxillary central teeth extracted for periodontal reasons without defects, cracks, or caries were included. All samples were standardized for enamel-dentin thickness by cone-beam computed tomography (CBCT). The samples were divided into 2 groups for colour (n=48) and mineral (n=48) change evaluations. These groups were then further divided into 4 subgroups according to the bleaching agent to be applied (n=12). Mineral analysis was performed with the SEM-EDX (SEM, Zeiss Gemini) device before the bleaching treatment, at the end of the treatment, and 2 weeks after the treatment ended to assess changes. Colour measurement was performed with a spectrophotometer device (VITA EasyShade, Zahnfabrik) before the bleaching treatment, on the 7th day of treatment, 24 hours after the final treatment, and 2 weeks after the treatment ended. Colour change values were calculated with the CIEDE2000 formula. Paired t tests/Wilcoxon signed-rank tests and ANOVA/Kruskal–Wallis tests were used for the statistical analysis. p < 0.05 was considered to indicate significance.
Results: Effective bleaching was achieved in all groups in the study. No significant difference among the groups was found in the colour change (p>0.05), while mineralization differed significantly (p<0.05).
Conclusions: The colour and mineral change assessment revealed that the ideal bleaching agent was ECP (Group 1).
Clinical Relevance: With the increased demand for conservative aesthetic treatments, dental bleaching technologies have become increasingly popular. However, bleaching agents lead to the formation of reactive oxygen species, which have genotoxic effects. The use of theobromineand chitosan can provide clinicians with positive results for bleaching treatments, such as the ability to use lower HP concentrations and avoid side effects.
Application nano fruit tree hole storage brick fertilizer is beneficial to increase the nitrogen utilization of grape plants under subsurface drip irrigation
Authors: Dongdong Yao , Jianli Yang , Haifeng Jia , Yufan Zhou , Qi Lv , Xujiao Li , Riye Sha , Huanhuan Zhang , Fangxia Wang , Fesobi Phillip , Huaifeng Liu , Fengyun Zhao , Yu Kun
Published: June 2023

Purpose
Nitrogen (N) is a key factor that limits plant growth in most terrestrial ecosystems. However, N leaching is still serious. Our study sought to provide theoretical basis for improving N fertilizer efficiency by using nano materials in the cultivation of fruit trees.
Methods
We invented a new type of nano fruit tree hole storage brick (NFTHSB) by using natural nano-materials, biochar and organic fertilizers, designed a new fertilization strategy-application NFTHSB under subsurface drip irrigation to characterise the effects of NFTHSB addition on grape N absorption at three different treatments [ “CK”, “NFTHSB A (T1)” and “NFTHSB B (T2)” ].
Results
Results showed that the pore number and pore size of NFTHSB A (T1) were significantly higher than NFTHSB B (T2). Compared with CK, T1 and T2 significantly increased the accumulation of biomass in different organs of plants, N absorption and 15N content in the roots, stems and leaves. When the soil depth was 15–30 cm, the NFTHSB increased the soil 15N content substantially. When the soil depth was 30–45 cm, it reduced the soil 15N content greatly. It obviously increased the activities of nitrite reductase (NR) and glutamine synthetase (GS) in grape leaves, also the activity of the urease (UR) in soil 30 cm.
Conclusion
NFTHSBs have special pore structure and adsorption, application NFTHSB could effectively absorb N in soil, reduce N loss, significantly improve plant N utilization rate and soil N residual rate, significantly promote the growth of grape. In this experiment, T1 treatment has the best effect.
Sociocultural factors affecting first-year medical students' adjustment to a PBL program at an African medical school
Authors: Kebaetse Masego B. , Griffiths Dominic , Mokone Gaonyadiwe G. , Mogodi Mpho S. , Conteh Brigid G. , Nkomazana Oathokwa , Wright John , Falama Rosemary , Kebaetse Maikutlo
Published: June 2023

Background
Besides regulatory learning skills, learning also requires students to relate to their social context and negotiate it as they transition and adjust to medical training. As such, there is a need to consider and explore the role of social and cultural aspects in student learning, particularly in problem-based learning, where the learning paradigm is different from what most students have previously experienced. This article explores two significant sociocultural factors contextualized in an African setting that may conflict with effective problem-based learning implementation: the socialization of schooling before medical training and the cultural socialization relating to speaking and silence.
Method
We employed a qualitative case study approach using in-depth interviews with 23 first-year students. Participants ranged in age from 18 to 25 years. All students were bi/multilingual (some spoke three to five languages), with English as the learning language. We conducted an inductive thematic analysis to systematically identify and analyze patterns in the data using the Braun and Clarke framework.
Results
Before medical school, students worked hard to compete for admission to medical school, were primarily taught using a teacher-centered approach, and preferred working independently. At the beginning of medical school, students found it difficult to understand the problem-based learning process, the role of the case, speaking and working effectively in a group, managing a heavy workload, and taking increased responsibility for their learning. By the end of the first semester, most students were managing the workload better, were more comfortable with their peers and facilitators, and appreciated the value of the problem-based learning approach.
Conclusions
In the sub-Saharan African context, sociocultural factors provide another lens for understanding students' learning experiences in a problem-based learning program. Adjustment to problem-based learning requires a conceptual and pedagogic shift towards learner-centered practice, particularly concerning self-direction, the role of the case, and collaborative learning.
Embracing the Promise of Open Educational Resources: Faculty Insights and Implications in Higher Education
Authors: Al-Zahrani Abdulrahman
Published: June 2023

This study examines faculty perceptions, awareness, and utilization of Open Educational Resources (OER) in higher education and identifies barriers hindering their adoption. The research encompasses multiple perspectives, including demographic information, teaching practices involving technology, familiarity and opinions regarding OER, types of OER utilized by faculty, ease of searching for OER, a comparison between open and traditional resources, intentions to use OER in the future, and factors deterring the adoption of OER. The study employed a quantitative approach using an online survey questionnaire to gather data. Using descriptive and MANOVA tests, the findings highlight a diverse gender distribution among respondents, a combination of teaching roles and administrative responsibilities, varying levels of teaching experience, a preference for blended teaching styles, significant awareness of OER, ease in searching for OER, and a strong intention to use OER in the future. The results emphasize the importance of addressing concerns related to institutional support, intellectual property policies, recognition of contributions, and creating a supportive environment to enhance faculty engagement with OER. The study implications suggest comprehensive and targeted approaches to support faculty members in adopting and utilizing OER effectively, including promoting gender equity, enhancing ease of adoption, considering workload impact, recognizing differences based on teaching experience, tailoring support based on teaching style, and actively promoting the benefits and opportunities of OER. The study acknowledges limitations regarding sample size and demographics and suggests future research directions to enhance generalizability, incorporate qualitative approaches, and investigate the pedagogical impact of OER adoption on student outcomes.
An Intelligent Long-Term Care Information Platform using Machine Learning and Semantic Web
Authors: Hsu I-Ching , Chen Shih-Hsuan
Published: June 2023

The low use of Long-Term Care (LTC) services in Taiwan is mainly caused by the lack of convenient promotion tools. This study developed a general architecture integrating Clustering Algorithm into Domain Ontology based on Cloud Computing (CADOCC) to provide a cloud computing environment and support the big data required for machine learning. The proposed CADOCC comprised four integrated components: cloud computing, machine learning, data preparation, and semantic web modules. The proposed CADOCC was used to develop an LTC Application Platform (LTCAP) to assist users in automatically classifying and filtering articles related to LTC. Additionally, the LTCAP was used to produce an intelligent mobile app that continually learns from user question–answer interactions through machine learning to facilitate the use of LTC services for personal requirements. The performance and satisfaction scores of classification algorithms running in different spark cloud computing environments were tested and compared. The results revealed that LSI and K-means met requirements in a test scenario, and the total satisfaction score was 4.15, which confirmed the feasibility of CADOCC.
A Nomogram for Predicting Occult Axillary Lymph Node Metastasis: Performance in US-diagnosed N0 Breast Cancer Patients
Authors: Zhang Wuyue , Wang Siying , Wang Yichun , Sun Jiawei , Wei Hong , Xue Weili , Dong Xueying , Wang Xiaolei
Published: June 2023

Background To develop a nomogram model combining gray-scale ultrasound and virtual touch tissue imaging quantification (VTIQ) characteristics to predict axillary lymph node metastasis (ALNM) in ultrasound (US)-diagnosed N0 breast cancer patients.
Methods A total of 567 patients enrolled in this study from April 2017 to May 2022, including 395 patients in the primary cohort and 172 patients in the external validation cohort. These are patients who are undergoing upfront surgery (no neoadjuvant treatment). Their preoperative gray-scale ultrasound images and VTIQ parameters were collected and used to develop a nomogram with internal and external validation for the prediction of occult ALNM.
Results Three gray-scale ultrasound characteristics (age, margin, and distance from the nipple) and one VTIQ parameter (Emax) were identified as independent risk factors in univariate and multivariate analyses. The nomogram showed an area under the curves of 0.843 and 0.869 in the training and external validation cohorts, respectively, indicating good calibration.
Conclusions The nomogram model can predict occult ALNM with relatively high accuracy. It is expected to be a non-invasive, easy, quick, and affordable supplement to traditional axillary ultrasound (AUS), which can help to determine appropriate axillary treatment for US-diagnosed N0 breast cancer patients.
Counting Objects in Images using DeepLearning: Methods and Current Challenges
Authors: D'Alessandro Adriano , Mahdavi-Amiri Ali , Hamarneh Ghassan
Published: June 2023

Object counting is an important computer vision application and research topic, which typically involves enumerating the number of objects in an image. Methodologies spanning a broad set of strategies have been proposed for solving object counting problems. These methods have seen an increase in relevance with the recent emergence of several highly successful deep learning techniques, which have led to significant performance improvements on a growing number of annotated counting benchmark datasets. However, despite the recent advancements in deep learning and computer vision, object counting remains a challenging problem with several open research directions. Datasets often contain objects that are highly occluded and which occur across a range of scales and perspectives. Further, popular annotation strategies, like density map annotations, suffer from annotator noise and inconsistency, which creates a performance bottleneck. These annotation strategies also have a high annotation burden, which leads to datasets that are very small when compared to common benchmark datasets in domains like image classification. Given both the significant progress and continued challenges of object counting, this task continues to be an interesting and ongoing research problem. This overview explores the historical context of object counting methods, the fundamental methodologies driving progress, the state of the art methods, and the significant open problems. In particular, we focus on recent trends that attempt to alleviate the problem of the annotation burden for object counting problems.
Spatial proteomics reveals human microglial states shaped by anatomy and neuropathology
Authors: Mrdjen Dunja , Amouzgar Meelad , Cannon Bryan , Liu Candace , Spence Angie , McCaffrey Erin , Bharadwaj Anusha , Tebaykin Dmitry , Bukhari Syed , Hartmann Felix , Kagel Adam , Vijayaragavan Kausalia , Oliveria John Paul , Yakabi Koya , Serrano Geidy , Corrada Maria , Kawas Claudia H , Fullaway Christine , Bosse Marc , Tibshirani Robert , Beach Thomas , Angelo Michael , Montine Thomas , Bendall Sean
Published: June 2023

Microglia are implicated in aging, neurodegeneration, and Alzheimer’s disease (AD). Traditional, low-plex, imaging methods fall short of capturing in situ cellular states and interactions in the human brain. We utilized Multiplexed Ion Beam Imaging (MIBI) and data-driven analysis to spatially map proteomic cellular states and niches in healthy human brain, identifying a spectrum of microglial profiles, called the microglial state continuum (MSC). The MSC ranged from senescent-like to active proteomic states that were skewed across large brain regions and compartmentalized locally according to their immediate microenvironment. While more active microglial states were proximal to amyloid plaques, globally, microglia significantly shifted towards a, presumably, dysfunctional low MSC in the AD hippocampus, as confirmed in an independent cohort (n=26). This provides an in situ single cell framework for mapping human microglial states along a continuous, shifting existence that is differentially enriched between healthy brain regions and disease, reinforcing differential microglial functions overall.
WITHDRAWN: Model prediction of suicidal behavior in first hospitalization patients with major depression disorder: a cross-sectional study based on a large sample
Authors: Hu Suoya , Zhang Lin , Liu Xuebing , Li Yi , Ma Jun
Published: June 2023

Background
Major depressive disorder (MDD) is one of the common and major causes of suicidal behavior (SB). The purpose of this study was to determine the prevalence of SB and its factors of influence among first hospitalized MDD patients in China, and to develop a predictive model for SB in the target population.
Methods
This study recruited 981 patients with MDD who were experiencing their first hospitalization. The patients' socio-pathological and general clinical data were gathered, along with common metabolic parameters and thyroid function. In addition, patients were assessed for depressive, anxiety, and psychotic symptoms, as well as the severity of their disease.
Results
Our study revealed a 13.46% prevalence of SB among MDD first hospitalized patients. A variety of clinical symptom scores and metabolic indicators were identified as risk factors for SB, and based on the identified risk factors we further obtained a predictive model with good ability to differentiate SB.
Conclusion
This study provides a validated predictive model for SB in the first hospitalized MDD population and suggests that the factors addressed in our model could be better used for early implementation of preventive measures.
A latent class analysis of psycho-behavioural adaptation in children and its relationship with sense of parenting competence and psychological distress of parents
Authors: Shan Li , Li Mingyu , Cui Dalei , Xu Simeng , Wang Jie , Li lezhi , Zhang Aidi , He Li
Published: June 2023

Background
The healthy development of psychological behaviour among children has been widely concerned by the whole society. However, little is known about different categories or attributes of their psycho-behavioural adaptation. The purpose of this study to identifies the latent classes of psycho-behavioural adaptation in children and explores the relationships of these classes with sense of parenting competence and psychological distress of parents
Methods
The cross-sectional study was conducted in one primary and secondary education school in mainland China from September 2022 to December 2022. The parents of children (3–18 years old) were invited to participate in the study. We used standardized questionnaires to collect data. A latent class analysis was performed to identify children's psycho-behavioural adaptation classes.
Results
The study recruited 242 participants. Two classes of psycho-behavioural adaptation were identified, namely, the psycho-behavioural problems group and the psycho-behavioural health group. The differences between latent classes were statistically significant regarding the child's age and parental health. The differences between latent classes were statistically significant in terms of sense of parenting competence, satisfaction, efficacy, and psychological distress score. The sense of parenting competence and parental psychological distress influenced the latent class of psycho-behavioural adaptation in children.
Conclusion
There is heterogeneity in the psycho-behavioural adaptation of children and differences in the sense of parenting competence and psychological distress of parents in each category. Targeted interventions should be developed and implemented based on the characteristics of each psycho-behavioural adaptation class to maximize interventions' effectiveness and promote parental and child well-being.
Assessing landscape fragmentation and its implications for biodiversity conservation in the Greater Accra Metropolitan Area (GAMA) of Ghana
Authors: Bonsu Kofi , Bonin Olivier
Published: June 2023

Context
This paper discusses the impact of urban expansion on the environment, including its effects on biodiversity conservation. As urban areas develop, natural habitats such as forests and agricultural lands are transformed into industrial, commercial, and residential uses, which alters landscape patterns and can lead to fragmentation. Fragmentation can have negative impacts on biodiversity, such as deforestation, alteration of watercourses leading to flooding, reduced availability of food, and increased pollution.
Objectives
To provide a comprehensive and data-driven analysis of the urban expansion of Greater Accra Metropolitan Area (GAMA) over time, and its effects on biodiversity. The idea is to capture the changes in land cover and landscape patterns in GAMA from 1991 to 2022 and predict the landscape patterns for 2030.
Methods
We perform a land cover change analysis of GAMA from 1991 to 2022. The evolution of the landscape pattern is captured by calculating landscape metrics. Multiradial fractal dimension is used as a transition variable to model and predict the land cover and landscape pattern of GAMA for 2030.
Results
The landscape metrics revealed extensive fragmentation of the Vegetation land cover type of GAMA, indicating a negative impact on biodiversity conservation, species movements, ecosystem functioning, and long-term ecological resilience.
Conclusion
The trends highlight the importance of considering landscape connectivity, habitat fragmentation and spatial arrangement of land cover types for assessing ecological processes and urban development impacts on the environment. Additionally, multiradial fractal dimension of built-up areas is recommended as an explanatory variable for urban growth modelling.
Validity of measures to indirectly determine maximal oxygen uptake in healthy and clinical subjects
Authors: Ribeiro Leonardo , Silva Luan R. S. , Souza Wallace M. M. , Miranda Humberto , Reis Michel S.
Published: June 2023

Background
The peak oxygen uptake (VO2peak) is considered the most reliable parameter for evaluating cardiorespiratory fitness and guiding physical training. However, not everyone has access to VO2peak measurements. As a more accessible alternative, heart rate (HR) variables have emerged.
Aim
To explore the correlation between HR responses during rest, exercise, recovery, and VO2peak.
Methods
Thirteen healthy men participated in the study. Resting HR variability and parameters were recorded for 10 minutes using a heart rate monitor while participants were seated. A maximal intermittent treadmill test was conducted to determine the maximum rate of HR increase (rHRI) and obtain VO2peak data (33.53 ± 8.22 mL/kg/min). The test speed was set based on the International Physical Activity Questionnaire (IPAQ) classification: 8 km/h for inactive or insufficiently active individuals, and 10 km/h for active and highly active individuals. Additionally, HR recovery (HRR) was measured during a 10-minute seated recovery period.
Results
Significant correlations were observed between resting HR (r = -0.78, p = 0.001), average RR interval (iRR) (r = 0.73, p = 0.004), percentage of iRR differences exceeding 50 ms (pNN50) (r = 0.64, p = 0.001), HR (r = -0.60, p = 0.003), and VO2peak. However, no significant correlation was found between rHRI and VO2peak (r = 0.38, p = 0.2).
Conclusion
Resting HR parameters, HR variability, and HRR showed significant associations with VO2peak. These HR variables can be useful alternatives for assessing and prescribing physical training when direct measurement of VO2peak is not feasible.
Risk Prediction of Pneumonia in Maintenance Hemodialysis Patients with COVID-19: A Single-center Retrospective Study in China
Authors: Jiang Zhenbin , Pan Yuejuan , Zhu Jinrong , Bi Shuhong , He Lian , Shi Junbao , Tian Xinkui , Xie Qian , Yang Wenling , Su Chunyan , Wang Song , Wang Yue
Published: June 2023

Objective:
The infection rate and mortality of COVID-19 in hemodialysis patients are extremely high. In this study, we analyzed the risk prediction of pneumonia in Chinese’s hemodialysis patients with COVID-19.
Method:
We conducted a retrospective analysis of maintenance hemodialysis patients with COVID-19 admitted to Peking University Third Hospital from December 1, 2022 to January 31, 2023. We collected demographic data, underlying diseases, dialysis treatment data, and laboratory test results of these patients; logistic regression and ROC curve were used to analyze the risk factors of pneumonia.
Results:
A total of 209 hemodialysis patients with COVID-19 were enrolled in this study, of whom 80(38.3%) had pneumonia and 129(61.7%) normal. Multivariate logistic analysis revealed that older age (OR=1.030, 95%CI 1.002~1.059, p=0.036), lower hemoglobin (OR=0.968, 95%CI 0.942~0.995, p=0.019), lower albumin (OR=0.834, 95%CI 0.738-0.943, p=0.004) were risk factors for pneumonia. Patients with age >65 years old, hemoglobin <115g/L or albumin <36.8g/L had a higher risk of pneumonia, and we combined the three indexes to predict the risk of pneumonia (P= elogit(P) / 1+ elogit(P) , logit(P)=9.593 +0.031×Age (years old) -0.038×Hemoglobin (g/L) -0.210×Albumin (g/L)), drew the ROC curve with the risk P value (AUC=0.756, 95% CI 0.687~0.825, p<0.001), when P=0.575 was selected as the cut-off value, the sensitivity and specificity of the three indexes combined to predict pneumonia were 44.0% and 94.5% respectively.
Conclusion:
Older age, anemia and hypoalbuminemia were risk factors for pneumonia in MHD patients. We could reduce the incidence of pneumonia and improve the prognosis of MHD patients by correcting anemia and hypoalbuminemia.
Five-axis toolpath re-scheduling for facilitating assisted supporting thin-walled blade machining by decreasing axis sensitivity
Authors: Li Pei-Yao , Song De-Ning , Li Jing-Hua , Zhong Yu-Guang , Ma Jian-Wei , Ma Xin
Published: June 2023

Existing works in the optimization of five-axis machining mainly focus on the efficiency, precision, or dynamic performance of the machine tools, while the performance of other equipment which assists the machining process has not been considered. This paper takes the robot assisted supporting machining of thin-walled blades as the research objective, and proposes an axial-sensitivity-reduction based five-axis toolpath re-scheduling method for facilitating the collaborative support machining with a machine-tool and a robot. The input of the method is lenient, merely including the original toolpath and the workpiece point-cloud model. The output of the method is the re-scheduled toolpath which requires lower motion ability of the assisted support equipment. This is realized by the following approaches. First, an axial sensitivity concept is defined, which quantificationally reflects the influence extent of the machine-tool axis motion on the assisted supporter motion, thus the most sensitive axis which affects the assisted process maximally can be identified. Then, an optimal-partition dual-domain-assisted-fitting method is provided to reconstruct the parameterized geometrical model of blades according to the point-cloud model, thus the multi-value property of the blades which troubles the surface construction is solved. After that, a sensitive-axis-calming bidirectional-tangent-bug-searching method is proposed to re-schedule the toolpath of five-axis machining, thus reducing the sensitivity of the most-sensitive axis. The whole method is universal, because a general cutter model is used and the cutter-contact point keeps invariant after re-scheduling. The correctness and effectiveness of the proposed method are verified by illustration machining tests of a steam turbine blade using an AB-type five-axis machine tool.
A Cloud Edge based Intelligent System for Detection of Grape Diseases
Authors: Khan Murtaza Ali , Zakarya Muhammad , Haleem Muhammad
Published: June 2023

SegmentatFinding plant diseases early on is essential for reducing damage while improving the quality of the yield. This paper describes an intelligent cloud-edge-based system for identifying and categorizing diseases in grape plants. The system is based on the support vector machine (SVM), a supervised machine learning technique to classify data. The traits of healthy and diseased plants are identified using digital photographs of grape plants. To determine color and texture information, we retrieved global features from the grape images. Patterns or structures (such as corners or edges) are discovered using the speeded-up robust features (SURF) method. The K-means clustering approach is used to quantify feature space, which lowers the number of feature descriptors. The training set for the SVM classifier is made up of feature descriptors. The system classified the unlabeled grape images using the trained SVM classifier during testing. 1600 RGB pictures from four classes: Black-rot, Black-measles, Leaf-blight, and Healthy-leaf make up the original data set. To evaluate the system and provide accuracy and confusion matrices, simulations are run in four different color spaces (grayscale, RGB, YCbCr, and L*a*b*). In the L*a*b* color space, the system attained a maximum average accuracy of up to 90.63% at a ratio of 70:30 training to testing data.
Fluvoxamine restores TFEB-mediated autophagy through Sigma-1R-controlled POM121 expression
Authors: Lin Chun-Yu , Wu Hsiang-En , Weng Eddie Feng-Ju , Su Tsung-Ping , Wang Shao-Ming
Published: June 2023

Expansion of the GGGGCC-RNA repeat is a known cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), two conditions that currently have no cure. Recent studies have shown that activation of the Sigma-1 receptor plays an important role in providing neuroprotection, particularly in ALS and Alzheimer’s disease. However, the mechanisms underlying Sigma-1R activation and its effect on (G4C2)n-RNA-induced cell death remain unclear. In this study, we demonstrated that fluvoxamine is a Sigma-1R agonist that can increase chaperone activity and rescue Pom121 intensity in (G4C2)31-RNA-expressing NSC34 cells, thereby stabilizing the protein expression of Pom121. Interestingly, fluvoxamine treatment increased Pom121 protein expression without affecting transcription. In C9orf72-ALS, the TFEB autophagy factor translocation decreased owing to nucleocytoplasmic transport defects. Our results showed that pretreatment of NSC34 cells with fluvoxamine promoted TFEB translocation into the nucleus and increased LC3-II expression compared to the overexpression of (G4C2)31-RNA alone. Collectively, fluvoxamine may act as a promising repurposed medicine for patients with C9orf72-ALS, as it stabilizes the nucleoporin Pom121 and promotes the translocation of TFEB in (G4C2)31-RNA-expressing NSC34 cells.
KLF4 as a Novel Prognostic Biomarker and Its Correlation with Immune Infiltrates in Lung Adenocarcinoma
Authors: Shen Jia-Xin , Wen Xiaofen , Zhu Jian-Ling , Chen Min-Na , Lin Dan-Xia , Xue Wen-Wu
Published: June 2023

Background: Improving the treatment of lung adenocarcinoma (LUAD) requires urgent exploration of molecular mechanisms underlying its progression and new prognostic predictors due to low long-term survival rates. Carcinogenesis studies have highlighted the clinical implications of KLF4, a member of the Krüppel-like transcription factor family. In this study, we aimed to investigate the expression of KLF4 in LUAD, assess its correlation with clinicopathological characteristics, prognosis and tumor immune cell infiltration, and analyze its potential advantages as a prognostic marker for LUAD patients.
Methods: This study examined KLF4 expression and clinical characteristics in normal and LUAD patients using TCGA and GEO datasets. 25 pairs of LUAD and normal tissues were then validated by IHC. Then we utilized analyses including PPI, GO, KEGG, GSEA and assessment of methylation status, to explore the potential mechanism of KLF4 in LUAD. Differences in the abundance of immune cell infiltration with high and low KLF4 expression were assessed by ssGSEA. Finally, univariate and multivariate Cox regression analysis were performed to construct a nomogram for evaluating the correlation between KLF4 expression and clinical prognosis.
Results: KLF4 was downregulated among tumors compared with normal tissue in multiple LUAD cohorts (P < 0.001). KLF4-related genes were then identified through differential analysis, and functional annotation revealed its significant enrichment in the processes of cornification and peptidase activity. GSEA indicated a potential involvement of KLF4 in tumor immunoregulation. Further analysis revealed a significant correlation between the expression of KLF4 and the infiltration levels of neutrophils, mast cells, eosinophils, and NK CD56bright cells (P < 0.001). Additionally, KLF4 in LUAD was found associated with a wide range of immune markers. Notably, higher level of KLF4 significantly reduced prognostic factors including OS, DSS and PFI. Finally, a nomogram incorporating KLF4, pathologic T and N stage, and residual tumor was built and exhibited promising predictive power for assessing the survival outcomes of LUAD patients.
Conclusion: High expression of KLF4 is an independent adverse prognostic factor in LUAD, and is strongly associated with aggressive clinical features and unfavorable immune inﬁltration. Therefore, KLF4 can be used as a novel prognostic biomarker for predicting patient outcomes.