bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plasma exosomal derived CCDC18AS1/miR-6835-5p/CCND2 axis sever as biomarkers for diagnosis and predicting therapeutic effect of Adolescent with MDD
Authors: Xu Yifan , Du Xinzhe , Zhang Rong , Huang Yangxi , Gao Yao , Wen Yujiao , Qiao Dan , Sun Ning , Liu Zhifen 
Published: December 2022

Abstract

Background Major depressive disorder (MDD) in adolescence seriously endangers their mental and physical health and is associated with poor social and scholastic function. However, the diagnosis and therapeutic biomarkers for adolescent with MDD remain unclear. Circulating exosomes could package nucleic acids from host cells and deliver them to recipient cells to play a vital role in intercellular communications, which are widely considered to be crucial for biomarker discovery for clinical diagnostics and therapy. Results In discovery set, we conducted microarray analysis to detect differential expression lncRNAs and mRNAs of plasma exosome and performed bioinformation analysis to construct lncRNAs-miRNAs-mRNAs networks from 10 adolescent MDD patients and 10 healthy controls, identifying 3752 differential expression lncRNAs and 1789 differential expression mRNAs and selecting AC156455.1/miR-126-5p/AAK1 and CCDC18AS1/miR-6835-5p/CCND2 axes from networks as candidate genes. In the validation set, candidate lncRNAs, miRNAs and mRNAs were verified in 64 adolescent MDD patients (MDD group) and 30 healthy controls (HC group) using qrt-PCR. We found that six candidate genes were differential expression between MDD group and HC group, or before and after antidepressant treatment of MDD group. The expression levels of AAK1, CCDC18AS1 and miR6835 were differences in therapeutic effects. We also found that the expression of CCDC18AS1/miR-6835-5p/CCND2 axis at baseline could predicted sertraline therapeutic effects, which may be mediated through improving suicidal ideation and cognitive function. Conclusion Our study identified and validated the plasma exosme derived lncRNAs, miRNAs and mRNAs altered in adolescent with MDD, and provided potential diagnosis and therapeutic biomarkers for adolescent with MDD.
Distance and Weightage-based Identification of Most Critical and Vulnerable locations of Surface Water Pollution in Kabul River Tributaries
Authors: Irfan Muhammad , Alam M. Mahboob , khan Shahbaz , khan Ilyas , Eldin Sayed M 
Published: December 2022

Abstract
Water plays a key role in the economic growth of an agricultural country. Pakistan is a farming country that uses almost 90% of its water resources for agricultural purposes. Khyber Pakhtunkhwa (KPK) province of Pakistan is blessed with extensive surface water resources. In addition to using groundwater resources for irrigation, large parts of its flat plains are irrigated with the Kabul River surface water. Due to large population growth and unregulated small/local scale industries in the region, surface water quality deteriorated with time. Which impacts people's health when polluted surface water is used for irrigation purposes. This research investigates the surface water quality of Kabul River's different tributaries and identifies the most critical locations in terms of water quality. Various physical, chemical, and biological parameters at ten sites on as many Kabul River tributaries are examined to investigate surface water quality. The distance and weightage-based identification method is used to identify the most critical and vulnerable locations for each parameter. The maximum seven critical values determined against the Bara River using the weightage-based method, i.e., 17.5, 5.95, 7.35, 27.65, 1.75, 0.35, and 10.45 for total alkalinity, sodium, total hardness, magnesium, total suspended solids, BOD, and turbidity. In comparison, the distance-based iteration method is used to identify the most vulnerable location against the specific parameter. All the results are finally compared with the interpolated values over the entire region using Kriging interpolation. The areas are mostly the same identified through the distance and weightage-based method. The results will guide the competent authority to install the monitoring station and treatment plants for specific parameters responsible for the critical location and to stop further contamination of the particular parameter near the threshold.
Predictors of exclusive breastfeeding in the first six months: An analytical cross-sectional study in Ardabil health centers, Iran, 2020
Authors: Mashoufi Mehrnaz , Shadman Atefeh , Mardi Afrouz , Gharajedaghy Hadi 
Published: December 2022

Abstract
Background
Mother’s own milk has been considered the perfect food for babies for the first 6 months. Several factors predict the successful continuation of breastfeeding. The aim of this study was to determine the predictors of exclusive breastfeeding in the first six months among infants in Ardabil health centers in Iran, 2020.
Methods
An analytical cross-sectional study was conducted on 379 lactating women who had infants over 6 months and attended in health care centers of Ardabil city in 2020. Health centers were selected by cluster-stratified method. Convenience sample approach was used to recruit the eligible lactating mothers. The information of mothers and their infants was included in the pre-prepared checklists. This information was statistically analyzed by SPSS 23 software. Logistic regression analysis was used to determine the predictive power of related factors.
Results
The results showed that more than half of the infants (51.71%) were exclusively breastfed for 6 months, and the majority (46.9%) of these infants were the first child in the family, the majority (85.2%) were born by vaginal birth and the first feeding in 98% of cases was in the first half hour after birth. Among the variables related to exclusive breastfeeding, only the predictive power of breastfeeding in the first half hour after birth was confirmed (p = 0.002). In other words, breastfeeding soon after birth increased almost 6 times the probability of exclusive breastfeeding up to six months.
Conclusions
Based on the results, breastfeeding soon after birth had a high predictive power in the continuation of exclusive breastfeeding up to six months. Considering the very important role of exclusive breastfeeding in maintaining and ensuring of the maternal and child health, it is suggested to emphasize and pay more attention to initiation of breastfeeding in newborn infant as soon as possible.
PKC-ζ is in charge of Extracellular Vesicles-associated TGF-β1 secretion for radiotherapy resistance in breast cancer
Authors: Zhang Fayun , Zheng Zifeng , Wang Luoyang , Zeng Wenfeng , Wei Wenjing , Zhang Chunling , Zhao Ziran , Liang Wei 
Published: December 2022

Abstract
Background: Radiotherapy is widely applied to breast cancer treatment, while the resistance to radiotherapy is inevitable. TGF-β1 has been considered to be an endogenous factor for RT resistance. As a large portion of TGF-β1 is secreted associating with the extracellular vesicles (TGF-β1EV), to understand the regulation mechanisms and the immunosuppressive function of TGF-β1EV in the radiated tumors will pay a way for overcoming radiotherapy resistance.
Methods: Based on TCGA database of 958 samples, the intratumoral TGF-β1 expression and the Tregs production were compared between patients received and unreceived radiotherapy. The superoxide-Zinc-PKC-ζ-TGF-β1EV pathway in breast cancer cells were identified through sequence alignments of different PKC isoforms, speculation and experimental confirmation. A series of functional and molecular studies were performed by quantitative real-time PCR, western blot and flow cytometry analysis. Mice survival and tumor growth was determined using observation of the animals and tumor growth measurement. Student’s t test or type II ANOVA with correction was used for comparisons of groups.
Results: The radiotherapy brought the increased intratumoral TGF-β1 expression and the Tregs production in the breast cancer tissues, and patients with higher TGF-β1 expression are associated with a poor survival. The increased intratumoral TGF-β mainly exists in the extracellular vesicles associated form both in the murine breast cancer model and in the human lung cancer tissues. Furthermore, radiation induced the more secretion of the TGF-β1EV and the higher percentage of Tregs by promoting protein kinase C zeta (PKC-ζ) expression and phosphorylation. Importantly, we found that naringenin rather than 1D11 significantly improve radiotherapy efficacy with low side effects. The underlying mechanism of naringenin is via downregulating radiation activated the superoxide-Zinc-PKC-ζ-TGF-β1EV pathway, which is distinct from TGF-β1 neutralizing antibody 1D11.
Conclusions: The superoxide-zinc-PKC-ζ-TGF-β1EV release pathway was elucidated to induce the accumulation of Tregs resulting in radiotherapy resistance in the TME. Therefore, targeting PKC-ζ to counteract TGF-β1EV function could represent a novel strategy to overcome radioresistance in breast cancer treatment or other cancers.
Trial registration: Using of tissues from patients with malignant Non-Small Cell Lung Cancer (NSCLC) was approved by the ethics committees at Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (NCC2022C-702, from June 8th, 2022).
Blended bismuth-based Cs3 Bi2 I9 /Ag2 BiI5 perovskite films incorporated potassium iodide for high-efficiency carbon electrode solar cells
Authors: Hamukwaya Shindume Lomboleni , Hao Huiying , Mashingaidze Melvin Mununuri , Zhong Tingting , Tang Shu , Dong Jingjing , Xing Jie , Liu Hao , Zhao Zengying 
Published: December 2022

Abstract
Bismuth-based lead-free perovskite solar cells (PSCs) are a non-toxic alternative to lead-based organic-inorganic hybrid PSCs. However, bismuth-based halides PSCs exhibit low power conversion efficiency (PCE) due to the grain boundaries and interfacial defects in the crystalline perovskite film. This discouragingly poor PCE has limited the continued development of bismuth-based PSCs. Herein, for the first time on record, this work fabricated blended, heterojunction, all-inorganic bismuth-based PSCs consisting of Cs3Bi2I9 and Ag2BiI5 perovskite absorber layer components with potassium iodide (KI) incorporation and carbon electrodes. Scanning Electron Microscopy (SEM) and X-ray diffraction spectroscopy (XRD) techniques confirmed that the addition of KI enhances the perovskite’s surface morphology, leading to larger grains and a more uniform distribution of contact potential along the grain boundaries. The Cs3Bi2I9/Ag2BiI5 PSC device with KI incorporation (K-C-ABI) achieved a record PCE of 8.82% and an extraordinary open-circuit voltage of 0.82 V. This record-breaking photovoltaic performance can be traced to the improved grain size of the Cs3Bi2I9/Ag2BiI5 PSCs and effective passivation of the grain boundaries and interfacial defects by KI. These crystallographic phenomena synergistically promoted exciton separation, thus the unprecedented photovoltaic performance. The K-C-ABI device also exhibited comparatively high stability, retaining ~98 % of the initial PCE after 150 days of exposure to ambient conditions (RH: 20–30%, room). The present findings support the results in preceding publications on the potential to enhance the efficiency of all-inorganic PSCs by blending different perovskite precursor solutions. Therefore, this study has effectively demonstrated defect passivation via KI incorporation for high-efficiency lead-free Bi-based PSCs.
Large-scale volumetric particle tracking using a single camera: Analysis of the scalability and accuracy of glare-point particle tracking
Authors: Kaiser Frieder , Rival David E. 
Published: December 2022

Abstract
Recent advances in tracer, illumination, and camera technology, paired with new processing algorithms, have been pushing the limits of scale for three-dimensional flow measurements. The present study explores the state-of-the-art and discusses the current progress towards full-scale, in situ flow measurements in very large measurement volumes of order 10m² or larger. In particular, we focus on industrial and environmental applications, where the measurement time, the processing time, and overall system cost all have to be minimized. With the glare-point particle tracking (GPPT) approach, we present a cost and time-efficient volumetric measurement technique using a single-camera setup, air-filled soap bubbles (AFSBs), and natural illumination. The GPPT approach is tested and characterized in a pyramidal-shaped measurement volume ($V=18m³) in an outdoor, open-jet wind tunnel. Bubbles of uniform size are produced by a bubble-generator prototype and illuminated by the sun. The uniform bubble size enables a depth estimate for each bubble based on the glare-point spacing in the images from a single camera, thereby removing the need for additional cameras and perspectives. The measurement accuracy of the GPPT is then assessed by: (a) characterizing the performance of the bubble-generator prototype; (b) analyzing bubble deformation and its effects; and (c) assessing the accuracy of the depth estimate based on glare-point spacing. Finally, the scalability of the approach is discussed and, based on the light scattering behavior of large AFSBs, a discussion is made of how GPPT will enable three-dimensional flow characterization in very large measurement volumes (V=O(100m³)) in the near future.
Piloting a mHealth follow up program in bariatric surgery via a single-arm cohort study
Authors: Wright Charlene , Kelly Jaimon T , Byrnes Joshua , Campbell Katrina L , Healy Rebecca , Musial Jane , Hamilton Kyra 
Published: December 2022

Abstract
Background
Behavioural support via mobile health (mHealth) is emerging. This study aimed to assess the feasibility, acceptability, cost, and effect on weight of a mHealth follow up program in bariatric surgery.
Methods
This was a prospective single-arm cohort study with mixed methods conducted in a Tertiary bariatric surgery service in Australia. The intervention group included individuals who had bariatric surgery (2019–2021) and owned a smart device, and the historical control group received usual post-operative care (2018). The intervention involved usual care plus codesigned bi-weekly text messages, monthly email newsletters, and online resources/videos for six months. The primary outcome measures included feasibility (via recruitment and retention rate), acceptability (via mixed methods), marginal costs, and weight 12-months post-operatively. Quantitative analysis was performed, including descriptive statistics and inferential and regression analysis. Multivariate linear regression and mixed-effects models were undertaken to test the intervention effect. Qualitative analysis was performed using inductive content analysis.
Results
The study included 176 participants (n = 129 historical control, n = 47 intervention group; age 56 years). Intervention recruitment (n = 48/50, 96%) and retention rate (47/48, 98%) were high. The survey response rate was low (n = 16/47, 34%). Participants agreed/strongly agreed that text messages supported new behaviours (n = 13/15, 87%); however, few agreed/strongly agreed they motivated goal setting and self-monitoring (n = 8/15, 53%), dietary or physical activity behaviour change (n = 6/15, 40% and n = 5/15, 33%). Interviews generated four main themes (n = 12): ‘Motivators and expectations’, ‘Preferences and relevance’, ‘Reinforced information”, and ‘Wanting social support’. The intervention reinforced information, email newsletters were lengthy/challenging to read, and text messages were favoured, yet tailoring was recommended. The intervention cost AUD 11.04 per person. The mean 12-month weight was 86 ± 16kg and 90 ± 16 kg (intervention and historical control) with no statistically significant difference. Intervention recipients enrolled at 3-months post-operatively demonstrated a statistically significant difference in 12-month weight (p = 0.014).
Conclusion
A mHealth follow up program in bariatric surgery may be feasible, showing high recruitment and retention rate. Of the various digital strategies, text messages were the most acceptable and suitable for continued use. However, text messaging approaches should strive to tailor information when possible.
Smart fire-safety cotton fabric with fire-warning capability via dual working mechanisms
Authors: Zou Tao , Zhang Dongqiao , Xu Tao , Peng Xiaohong , Zhang He , Du Yanliang 
Published: December 2022

Abstract
Increasing demand for fire safety has aroused the enthusiasm of researchers for exploring early-stage fire-warning materials. Herein, an early-stage fire-warning cotton fabric (denoted as CF-CP-FR) was designed with a two-layered structure: conducting polymer layer and flame-retardant layer, through in-situ chemical oxidation polymerization of polypyrrole (PPy) and dip coating of the compound of montmorillonite and ammonium polyphosphate (MMT@APP), respectively. Based on the thermoelectric effect of the PPy, CF-CP-FR was endowed with accurate temperature sensing capability below 100°C. When encountering fire, CF-CP-FR showed excellent fire-warning response as fast as 1.0 s and displayed repeatable fire-warning capability under the protection of the MMT@APP. Via the mechanism of thermo-induced resistance change, the coated cotton fabric could also trigger the fire warning circuit at ca. 2.0 s. Meanwhile, the flame retardancy and thermal stability of CF-CP-FR were significantly enhanced, owing to the synergetic effect of MMT and APP. This work is promising in fabricating multifunctional clothing with efficient fire safety and smart fire-warning capability.
Faster Quantum State Decomposition with Tucker Tensor Approximation
Authors: Protasov Stanislav , Lisnichenko Marina 
Published: December 2022

Abstract

Researchers have put a lot of effort into reducing the gap between current quantum processing units (QPU) capabilities and their potential supremacy.One approach is to keep supplementary computations in the CPU, and use QPU only for the core of the problem. In this work, we address the complexity of quantum algorithm of arbitrary quantum state initialization, an important building block of quantum data analysis and machine learning.QPUs do not outperform classical machines with existing precise initialization algorithms.Hence, many studies propose an approximate but robust quantum state initialization.Cutting a quantum state into a product of (almost) independent partitions with the help of CPU reduces the number of two-qubit gates, and correspondingly minimizes the loss of state fidelity in the quantum part of the algorithm.To find the least entangled qubits, current methods compute the singular value decomposition (SVD) for each qubit separately with CPU.In this paper, we optimize CPU usage and memory resource bottlenecks.We consider Tucker tensor decomposition as an alternative to the CPU-based SVD in a single low-entangled qubit detection task without the loss of solution quality.Both proposed methods outperform the SVD in time and memory for systems of at least ten qubits. We achieve an order faster implementation and two orders less memory usage for a system of 15 qubits.
Serum miRNA modulations indicate changes in retinal morphology
Authors: Aggio-Bruce Riemke , Schumann Ulrike , Cioanca Adrian V. , Chen Fred K. , McLenachan Samuel , Jeffery Rachael C. Heath , Das Shannon , Natoli Riccardo 
Published: December 2022

Abstract

Background:Age-related macular degeneration (AMD) is the leading cause of vision loss in the developed world and the detection of its onset and progression are based on retinal morphological assessments. MicroRNA (miRNA) have been explored extensively as biomarkers for a range of neurological diseases including AMD, however differences in experimental design and the complexity of human biology have resulted in little overlap between studies. Using preclinical animal models and clinical samples, this study employs a novel approach to determine a serum signature of AMD progression.Methods:Serum miRNAs were extracted from mice exposed to photo-oxidative damage (PD; 0, 1, 3 and 5 days), and clinical samples from patients diagnosed with reticular pseudodrusen or atrophic AMD. The expression of ~800 miRNAs was measured using OpenArrayTM, and differential abundance from controls was determined using the HTqPCR R package followed by pathway analysis with DAVID. MiRNA expression changes were compared against quantifiable retinal histological indicators. Finally, the overlap of miRNA changes observed in the mouse model and human patient samples was investigated.Results:Differential miRNA abundance was identified at all PD time-points and in clinical samples. Importantly, these were associated with inflammatory pathways and histological changes in the retina. Further, we were able to align findings in the mouse serum to those of clinical patients.Conclusions:In conclusion, serum miRNAs are a valid tool as diagnostics for the early detection of retinal degeneration, as they reflect key changes in retinal health. The combination of pre-clinical animal models and human patient samples led to the identification of a preliminary serum miRNA signature for AMD. This study is an important platform for the future development of a diagnostic serum miRNA panel for the early detection of retinal degeneration.
Clinical prediction rule for identifying older patients with toxigenic Clostridioides difficile at the time of hospital admission
Authors: Lee Ki-Byung , Lee Mina , Suh Jin Woong , Yang Kyung Sook , Chung Youseung , Kim Jeong Yeon , Kim Sun Bean , Sohn Jang Wook , Yoon Young Kyung 
Published: December 2022

Abstract
Background: This study aimed to develop and validate a clinical prediction rule to screen older patients at risk of being toxigenic Clostridioides difficile carriers at the time of hospital admission.
Methods: This retrospective case-control study was performed at a university-affiliated hospital. Active surveillance using a real-time polymerase chain reaction (PCR) assay for the toxin genes of C. difficile was conducted upon admission to the Division of Infectious Diseases among older patients (≥65 years). This rule was drawn from a derivative cohort from October 2019 to April 2021 using a multivariable logistic regression model. Clinical predictability was evaluated in the validation cohort between May 2021 and October 2021.
Results: Of 628 PCR screenings for toxigenic C. difficile infection, 101 (16.1%) yielded positive findings. In the derivation cohort, the formula was derived using significant predictors for toxigenic C. difficile infection at admissions, such as septic shock, connective tissue diseases, anemia, recent use of antibiotics, and recent use of proton-pump inhibitors, to establish clinical prediction rules. In the validation cohort, the sensitivity, specificity, and positive and negative predictive values of the prediction rule, based on a cut-off value of ≥0.45, were 78.3%, 70.8%, 29.5%, and 95.4%, respectively.
Conclusions: This clinical prediction rule for identifying toxigenic C. difficile infection at admission would be helpful for the selective screening of high-risk groups. In order to be implemented in a clinical setting, more patients from other medical institutions need to be prospectively examined.