bluuebunny/crossref_metadata_2025_split huggingface dataset:
Komodifikasi Kehidupan di Desa pada Akun Instagram @hidupdidesa_
Authors: Wardani Ayu , Misbah Nuril Ashivah , Hayati Kumala 
Published: February 2024

Platform instagram merupakan media yang digunakan untuk berbagi informasi dari penggunanya. Informasi yang dibagikan dalam setiap akun memiliki ciri khas dan tujuan masing-masing. Akun @hidupdidesa_ merupakan salah satu akun instagram yang menggunakan representasi kehidupan di desa sebagai ciri khasnya. Kehidupan alami di desa dengan ciri khas pertanian merupakan hal utama yang ditampilkan dalam setiap konten @hidupdidesa_. Penelitian ini bertujuan untuk menganalisis komodifikasi kehidupan di desa pada akun instagram @hidupdidesa_ melalui analisis semiotika Roland Barthes. Dalam membedah komodifikasi yang digunakan oleh akun instagram @hidupdidesa_ digunakan metode analisis semiotika Roland Barthes. Komodifikasi merupakan suatu usaha yang digunakan untuk menciptakan suatu komoditas, yang kemudian berujung pada keinginan untuk mendapatkan keuntungan. Akun @hidupdidesa_ pada platform instagram menjadikan arena kehidupan di desa sebagai suatu bentuk komodifikasi konten. Di dalam unggahan @hidupdidesa_, direpresentasikan mengenai kehidupan di desa yang nyaman, subur, asri, dan jauh dari modernisasi perkotaan. Berdasarkan analisis penanda dan petanda (semiotika) Roland Barthes, ditemukan pemaknaan bahwa terdapat beragam pesan mengenai kehidupan pedesaan yang tak biasa pada konten instagram @hidupdidesa_, di mana pesan-pesan yang dikonstruksi dalam kehidupan pedesaan tersebut berujung pada makna pesan mengenai kehidupan yang berkelanjutan (sustainable). Adapun makna pesan kehidupan berkelanjutan tergambar dalam representasi gaya hidup cooking from scratch, Do It Yourself, serta gaya hidup ramah lingkungan.
Assessing the impact of gait speed on gait stability using multi-scale entropy fused with plantar pressure signals
Authors: Hu Zilei , Li Miaomiao , Wei Jiale , Zhao Jing , Tang Xiaojing , Wei Haicheng 
Published: February 2024

Introduction: Walking speed can affect gait stability and increase the risk of falling.Methods: In this study, we design a device to measure the distribution of the plantar pressure to investigate the impact of the walking speed on the stability of the human gait and movements of the body. We fused the entropy acquired at multiple scales with signals of the plantar pressure to evaluate the effects of the walking speed on the stability of the human gait. We simultaneously collected data on the motion-induced pressure from eight plantar regions to obtain the fused regional pressure. To verify their accuracy, we obtained data on the plantar pressure during walking by using the force table of the Qualisys system. We then extracted the peak points and intervals of the human stride from pressure signals fused over three regions, and analyzed the mechanics of their regional fusion by using the regional amplitude–pressure ratio to obtain the distribution of the plantar pressure at an asynchronous walking speed. Furthermore, we introduced multi-scale entropy to quantify the complexity of the gait and evaluate its stability at different walking speeds.Results: The results of experiments showed that increasing the speed from 2 to 6 km/h decreased the stability of the gait, with a 26.7% increase in the amplitude of pressure in the region of the forefoot. The hindfoot and forefoot regions were subjected to the minimal pressure at a speed of 2 km/h, while the most consistent stress was observed in regions of the forefoot, midfoot, and hindfoot. Moreover, the curve of entropy at a speed of 2 km/h exhibited a slow decline at a small scale and high stability at a large scale.Discussion: The multi-scale entropy increased the variation in the stability of the synchronous velocity of walking compared with the sample entropy and the analysis of regional fusion mechanics. Multi-scale entropy can thus be used to qualitatively assess the relationship between the speed and stability of the gait, and to identify the most stable gait speed that can ensure gait stability and posture control.
Metabolic engineering of Streptomyces peucetius for biosynthesis of N,N-dimethylated anthracyclines
Authors: Hulst Mandy B. , Zhang Le , van der Heul Helga U. , Du Chao , Elsayed Somayah S. , Koroleva Arina , Grocholski Thadee , Wander Dennis P. A. , Metsä-Ketelä Mikko , Neefjes Jacques J. C. , van Wezel Gilles P. 
Published: February 2024

Introduction: Daunorubicin and doxorubicin, two anthracycline polyketides produced by S. peucetius, are potent anticancer agents that are widely used in chemotherapy, despite severe side effects. Recent advances have highlighted the potential of producing improved derivatives with reduced side effects by incorporating l-rhodosamine, the N,N-dimethyl analogue of the native amino sugar moiety.Method: In this study, we aimed to produce N,N-dimethylated anthracyclines by engineering the doxorubicin biosynthetic pathway in the industrial Streptomyces peucetius strain G001. To achieve this, we introduced genes from the aclarubicin biosynthetic pathway encoding the sugar N-methyltransferases AclP and AknX2. Furthermore, the native gene for glycosyltransferase DnrS was replaced with genes encoding the aclarubicin glycosyltransferases AknS and AknT. Additionally, the gene for methylesterase RdmC from the rhodomycin biosynthetic pathway was introduced.Results: A new host was engineered successfully, whereby genes from the aclarubicin pathway were introduced and expressed. LC-MS/MS analysis of the engineered strains showed that dimethylated sugars were efficiently produced, and that these were incorporated ino the anthracycline biosynthetic pathway to produce the novel dimethylated anthracycline N,N-dimethyldaunorubicin. Further downstream tailoring steps catalysed by the cytochrome P450 monooxygenase DoxA exhibited limited efficacy with N,N-dimethylated substrates. This resulted in only low production levels of N,N-dimethyldaunorubicin and no N,N-dimethyldoxorubicin, most likely due to the low affinity of DoxA for dimethylated substrates.Discussion:S. peucetius G001 was engineered such as to produce N,N-dimethylated sugars, which were incorporated into the biosynthetic pathway. This allowed the successful production of N,N-dimethyldaunorubicin, an anticancer drug with reduced cytotoxicity. DoxA is the key enzyme that determines the efficiency of the biosynthesis of N,N-dimethylated anthracyclines, and engineering of this enzyme will be a major step forwards towards the efficient production of more N,N-dimethylated anthracyclines, including N,N-dimethyldoxorubicin. This study provides valuable insights into the biosynthesis of clinically relevant daunorubicin derivatives, highlighting the importance of combinatorial biosynthesis.
Enhancing blockchain scalability with snake optimization algorithm: a novel approach
Authors: Taher Shimal S. H. , Ameen Siddeeq Y. , Ahmed Jihan A. 
Published: February 2024

Scalability remains a critical challenge for blockchain technology, limiting its potential for widespread adoption in high-demand transactional systems. This paper proposes an innovative solution to this challenge by applying the Snake Optimization Algorithm (SOA) to a blockchain framework, aimed at enhancing transaction throughput and reducing latency. A thorough literature review contextualizes our work within the current state of blockchain scalability efforts. We introduce a methodology that integrates SOA into the transaction validation process of a blockchain network. The effectiveness of this approach is empirically evaluated by comparing transaction processing times before and after the implementation of SOA. The results show a substantial reduction in latency, with the optimized system achieving lower average transaction times across various transaction volumes. Notably, the latency for processing batches of 10 and 100 transactions decreased from 30.29 ms to 155.66 ms–0.42 ms and 0.37 ms, respectively, post optimization. These findings indicate that SOA is exceptionally efficient in batch transaction scenarios, presenting an inverse scalability behavior that defies typical system performance degradation with increased load. Our research contributes a significant advancement in blockchain scalability, with implications for the development of more efficient and adaptable blockchain systems suitable for high throughput enterprise applications.
When belief becomes research: conspiracist communities on the social web
Authors: Greer Katie , Beene Stephanie 
Published: February 2024

IntroductionThis article explores two QAnon subgroups that were not active during the initial phase of the movement but now epitomize how QAnon has capitalized on social media to reach more people. We examine these smaller communities through the lens of information literacy and other literacies to identify opportunities for librarians and educators.ResultsThe communities of conspiracy theorists explored here exhibit information behaviors distinct from the initial QAnon community, presenting opportunities for information professionals to employ new models of information literacy, metaliteracy, and other literacies to combat conspiracy ideation. Notable themes evidenced in both samples include an increasing religiosity affiliated with QAnon, affective states that promote conspiracy ideation, faulty hermeneutics and epistemologies, and specific literacy gaps.Methods and discussionWe must update our understanding of QAnon and its adherents' shifting priorities and behaviors. Through investigating these smaller subgroups, researchers and educators can address the evolution of the QAnon movement by teaching to literacy gaps and logical fallacies, and acknowledging the troubling emotions that undergird broader belief systems.
Effects of different traditional Chinese exercise in the treatment of essential hypertension: a systematic review and network meta-analysis
Authors: Zhang Qingyuan , Xu Xiaogang , Wu Qianyan , Zhang Jingwen , Huang Shenghe , Wu Lin , Tian Minping , Zhang Delin 
Published: February 2024

BackgroundAs a therapy to prevent and treat essential hypertension (EH), traditional Chinese exercises (TCEs) were widely used in clinical practice. However, there is a lack of strictly comparison of the antihypertensive efficacy of different TCEs, which not conducive to the selection of the best and most optimal treatment. This study aimed to perform a network meta-analysis to objectively evaluate which TCE has the best effects in assisting with lowering blood pressure.MethodsPubMed, Embase, the Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), VIP, SinoMed and Wanfang Data were searched for all randomized controlled trials (RCTs) on TCEs for the treatment of EH published up to July 10, 2023. RoB2.0 tool was utilized to evaluate the quality of the RCTs. The network meta-analysis was performed by R 4.1.2 and Stata 17.0. Weighted mean difference (WMD) was calculated for continuous outcomes.ResultsA total of 29 studies, including 2,268 patients were included to analyze 6 different interventions. The network meta-analysis results presented that in comparison with control group, Tai Chi + antihypertensive medication [WMD = −10.18, 95% CI, (−14.94, −5.44)] is the most effective intervention for lowering systolic blood pressure (SBP), and Wuqinxi + antihypertensive medication [WMD = −10.36, 95% CI (−18.98, −1.66)] is the most effective intervention for lowering diastolic blood pressure (DBP).ConclusionTCEs combined with antihypertensive medication may be able to achieve more prominent antihypertensive effects with Tai Chi and Wuqinxi potentially being the higher-priority options. However, well-designed randomized studies are warranted to further verify currently conclusion.
Predictive model and risk analysis for peripheral vascular disease in type 2 diabetes mellitus patients using machine learning and shapley additive explanation
Authors: Liu Lianhua , Bi Bo , Cao Li , Gui Mei , Ju Feng 
Published: February 2024

BackgroundPeripheral vascular disease (PVD) is a common complication in patients with type 2 diabetes mellitus (T2DM). Early detection or prediction the risk of developing PVD is important for clinical decision-making.PurposeThis study aims to establish and validate PVD risk prediction models and perform risk factor analysis for PVD in patients with T2DM using machine learning and Shapley Additive Explanation(SHAP) based on electronic health records.MethodsWe retrospectively analyzed the data from 4,372 inpatients with diabetes in a hospital between January 1, 2021, and March 28, 2023. The data comprised demographic characteristics, discharge diagnoses and biochemical index test results. After data preprocessing and feature selection using Recursive Feature Elimination(RFE), the dataset was split into training and testing sets at a ratio of 8:2, with the Synthetic Minority Over-sampling Technique(SMOTE) employed to balance the training set. Six machine learning(ML) algorithms, including decision tree (DT), logistic regression (LR), random forest (RF), support vector machine(SVM),extreme gradient boosting (XGBoost) and Adaptive Boosting(AdaBoost) were applied to construct PVD prediction models. A grid search with 10-fold cross-validation was conducted to optimize the hyperparameters. Metrics such as accuracy, precision, recall, F1-score, G-mean, and the area under the receiver operating characteristic curve (AUC) assessed the models’ effectiveness. The SHAP method interpreted the best-performing model.ResultsRFE identified the optimal 12 predictors. The XGBoost model outperformed other five ML models, with an AUC of 0.945, G-mean of 0.843, accuracy of 0.890, precision of 0.930, recall of 0.927, and F1-score of 0.928. The feature importance of ML models and SHAP results indicated that Hemoglobin (Hb), age, total bile acids (TBA) and lipoprotein(a)(LP-a) are the top four important risk factors for PVD in T2DM.ConclusionThe machine learning approach successfully developed a PVD risk prediction model with good performance. The model identified the factors associated with PVD and offered physicians an intuitive understanding on the impact of key features in the model.
Distinguishing two distinct types of salivary extracellular vesicles: a potential tool for understanding their pathophysiological roles
Authors: Ogawa Yuko , Miura Yuri , Ikemoto Mamoru , Ohnishi Atsushi , Goto Yoshikuni , Aoki Kazuma , Motokurumada Yuki , Akimoto Yoshihiro , Endo Tamao , Tsujimoto Masafumi , Yanoshita Ryohei 
Published: February 2024

Extracellular vesicles (EVs), which are found in almost all cells and human body fluids, are currently being studied as a source of pathophysiological information. Previously, we demonstrated that at least two types of EVs can be isolated from human whole saliva (WS) using enzymatic activity of dipeptidyl peptidase IV (DPP IV) as a marker for differentiating the EV subsets. In the present study, EV fractions, termed EV-I 20 k-ppt and EV-II 100 k-ppt, were prepared by a combination of size-exclusion chromatography of improved condition and sequential centrifugation. The EV-I 20 k-ppt fraction contained medium/large EVs with a diameter of 100–1,000 nm, including aminopeptidase N (APN), mucin 1, ezrin, and Annexin A1. EV-II 100 k-ppt contained small EVs with a diameter of 20–70 nm, with DPP IV and CD9, programmed cell death 6-interacting protein, and tumor susceptibility gene 101 as characteristic proteins. Proteomic analyses also revealed distinctive repertoires of constituent proteins. Immunoprecipitation of several membrane proteins of the EVs with respective antibodies suggested their differential local membrane environment between the two types of salivary vesicles. Thus, we identified two distinctive types of EVs, one is APN/MUC1- rich EVs (EV-I, large/medium EVs) and the other is DPP IV/CD9-rich EVs (EV-II, small EVs). Furthermore, analysis of the binding of the EVs to coronavirus spike proteins showed that EV-II 100 k-ppt, but not EV-I 20 k-ppt, significantly bound to the spike protein of Middle East respiratory syndrome coronavirus (MERS-CoV). Finally, we developed a simple method to prepare two distinctive EVs from only 1 mL of human WS using sequential immunoprecipitation. Elucidating the features and functions of these two types of salivary EVs may help us understand their pathophysiological roles in the oral cavity and gastrointestinal tract.
Adult supratentorial extraventricular anaplastic ependymoma with cerebrospinal fluid dissemination metastases: a case report
Authors: Zhang Daojin , Liu Hongbing , Zhang Maosong , Cao Jun 
Published: February 2024

BackgroundEpendymomas mostly locate in the infratentorial region and often occur in children. Anaplastic ependymomas account for 45–47% of supratentorial and 15–17% of infratentorial ependymomas, also known as malignant ependymomas. Adult supratentorial extraventricular anaplastic ependymoma (SEAE) is rare in clinical practice, and only a few cases have been reported so far, and there is no clinical study with large sample size. We report a case of adult supratentorial extraventricular anaplastic ependymoma in the occipital lobe with cerebrospinal fluid dissemination metastases.Case descriptionA 58-year-old female patient presented with unexplained pain in multiple parts of the body for the past half a year, mainly manifested as pain in the head, abdomen and chest. On August, 2022, Head MRI of the patient showed abnormal signal shadow in the left occipital lobe, which was considered a malignant lesion. The patient underwent tumor resection under general anesthesia on September 3, 2022. Postoperative pathological examination showed anaplastic ependymoma. The postoperative follow-up head MRI showed multiple cerebrospinal fluid dissemination metastases in the brain.ConclusionAdult SEAE is a rare tumor with high malignancy and have a tendency to disseminate into the CSF, resulting in drop metastases. Immunohistochemistry is very important for the diagnosis of SEAE. It is recommended to administer adjuvant chemotherapy or radiation therapy appropriately after surgery, based on the tumor being completely resected as much as possible.
Prevalence and factors associated with depressive symptoms among patients with epilepsy in Ethiopia: a national-based systematic review and meta-analysis
Authors: Tadesse Gebresilassie , Tinsae Techilo , Nakie Girum , Rtbey Gidey , Andualem Fantahun , Tadesse Asnake , Melkam Mamaru , Takelle Girmaw Medfu , Fentahun Setegn 
Published: February 2024

BackgroundDepression is a major public health problem and negatively affects the quality of life of patients with epilepsy. Despite multiple studies investigating the magnitude and predictors, the results have been inconsistent. Therefore, this study aimed to estimate the pooled prevalence and factors associated with depressive symptoms among patients with epilepsy in Ethiopia.MethodsThe primary articles were searched using databases like PubMed, Google Scholar, CINAHL, SCOPUS, EMBASE, and African Journal Online. A total of 10 primary articles that assessed the prevalence and factors associated with depressive symptoms among patients with epilepsy in Ethiopia were included. A Microsoft Excel spreadsheet was used to extract the data, which was then exported to Stata version 14 for further analysis. The statistical heterogeneity was evaluated using the I2 test. Due to heterogeneity, a random effect meta-analysis model was employed. Publication bias was checked through Egger’s weighted regression test and funnel plot.ResultsA total of 10 primary studies with 3,532 participants were included. The pooled prevalence of depressive symptoms among patients with epilepsy was found to be 41.69% (95% CI, 37.70, 45.68). The pooled prevalence of depressive symptoms was 48.61, 42.98, 40.68, 38.27, and 34.80% in Oromia, SNNPs, Amhara, Addis Ababa, and Tigray, respectively, based on a sub-group analysis per regional state. Perceived stigma (AOR = 3.30, 95% CI: 1.40, 7.80), seizure frequency (AOR = 3.81, 95% CI: 1.03, 14.09), and perceived stress (AOR = 4.6, 95% CI: 1.05, 20.06) were factors associated with depressive symptoms.ConclusionWe found that depressive symptoms affects at least four out of ten patients with epilepsy, indicating an immense burden. Depressive symptoms were extremely prevalent in those who had high levels of stigma, a monthly seizure frequency of once or more, and perceived stress. Therefore, physicians should take extra precautions when treating patients with epilepsy who have certain conditions.Systematic review registrationThis study was registered according to The International Prospective Register of Systemic Review (PROSPERO) with the registration ID (CRD42023484308).
The silence of the neurons: an application to enhance performance and energy efficiency
Authors: Heidarpur Moslem , Ahmadi Arash , Ahmadi Majid 
Published: February 2024

IntroductionSimulation of biological neural networks is a computationally intensive task due to the number of neurons, various communication pathways, and non-linear terms in the differential equations of the neuron.MethodThis study proposes an original modification to optimize performance and power consumption in systems, simulating or implementing spiking neural networks. First, the proposed modified models were simulated for validation. Furthermore, digital hardware was designed, and both the original and proposed models were implemented on a Field-Programmable Gate Array (FPGA).Results and discussionMoreover, the impact of the proposed modification on performance metrics was studied. The implementation results confirmed that the proposed models are considerably faster and require less energy to generate a spike compared with unmodified neurons.
Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers
Authors: Fan Qingkun , Zhang Xiaoyuan , Dao Riao , Qian Yujia , Zhao Lewei , Li Xiaoqiang , Ding Xuanfeng , Liu Gang , Dai Shuyang 
Published: February 2024

PurposeThis study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM).Material and methodsThe novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method.ResultsThe results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET).ConclusionThis study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.