bluuebunny/crossref_metadata_2025 huggingface dataset:
Learning Vector Quantization for Robusta and Arabica Coffee Classification
Authors: Jatmoko Cahaya , Sinaga Daurat , Lestiawan Heru , Hadi Heru Pramono
Published: November 2023

ANN or artificial neural network is a way to solve various kinds of problems to make decisions based on training. One of the methods of JSt which contains competitive and supervised learning. Where this layer will automatically learn the classification of the closest input distances and will be distributed to the same class. there are 2 types of coffee beans that are famous in the world, namely arabica and robusta, for some people or the layman it will be very difficult to distinguish these 2 types of coffee beans apart from the fact that the shape is almost the same the color looks almost the same but there are a number of differences in the two coffee beans which we can see from the shape of the seed. Robusta has a shape that tends to be round and smaller in size, and has a rougher texture. Arabica, on the other hand, is slightly flatter and longer in shape. The size is slightly bigger than Robusta but the texture of Arabica is smoother than Robusta. This is the basis of this study where the images of the two coffee beans will be extracted using the first-order texture feature extraction method based on MU parameters, standard deviation, skewness, energy, entropy, and smoothness. The method for collecting data was in the form of a quantitative method using images from each coffee bean, both Arabica and Robusta, with a total of 130 images. The comparison between training_data and test_data is 80:20. Through research conducted in the form of performance parameters with the best accuracy, including: Learning rate 0.01, max epoch or maximum iteration of 10 and 30%, the amount of training data used is 39 training images and 26 test images resulting in an accuracy presentation of 71% for the training process and error with a percentage of 96% for the test process.
Helmet Detection Based on Cascade Classifier and Adaptive Boosting
Authors: Susanto Ajib , Kusumawati Yupie
Published: November 2023

The increasing number of traffic accidents caused by motorcyclists not wearing helmets has led to an increase in the number of studies related to road safety surveillance. The research system used is an automatic system to detect whether the motorcyclist is wearing a helmet or not. Many studies use image processing systems, deep learning and computer vision. In this research, Cascade Classifier and Adaptive Boosting have been implemented for the process of identifying motorcycle riders with helmets and without helmets. The number of datasets used is 500 datasets with labels on the image of the driver with a helmet and the image of the driver without a helmet. Based on the test results, an accuracy of 90% has been obtained
Harnessing Item Features to Enhance Recommendation Quality of Collaborative Filtering
Authors: Isinkaye Folasade Olubusola
Published: November 2023

Recommendation systems provide ways of directing users to items that may be relevant to them by guiding them to relevant items that will be suitable to the users according to their profiles. Collaborative filtering is one of the most successful and mature techniques of recommender system because of its domain independent ability. Bayesian Personalized Ranking Smart Linear Model (BPRSLIM) is model-based collaborative filtering (CF) recommendation algorithm that usually reconstructs a scanty user-item matrix directly; also, using only user-rating matrix usually prevents the algorithm from accessing relevant information that could enhance its recommendation accuracy. Therefore, this work reconstructs BPRSLIM user-item rating matrix via item feature information in order to improve its performance accuracy. Comprehensive experiments were carried out on a real-world dataset using different evaluation metrics.  The performance of the model showed significant improvement in recommendation accuracy when compared with other top-N collaborative filtering-based recommendation algorithms, especially in precision and nDCG with 30.6% and 22.1% respectively.
The Involvement of Local Binary Pattern to Improve the Accuracy of Multi Support Vector-Based Javanese Handwriting Character Recognition
Authors: Sari Christy Atika , Sari Wellia Shinta , Shelomita Viki Ari , Kusuma Mohammad Roni , Puspa Silfi Andriana , Gusta Muhammad Bima
Published: November 2023

Indonesia is a country that is rich in cultural diversity. An example of one such variety is the Javanese language. The letters that are usually used in Javanese are non-Latin letters or are usually known as Javanese script. However, along with advances in technology, the Javanese language is increasingly being forgotten. In the past, the Javanese script was used as a subject in schools, aiming for Indonesian students to continue to gain knowledge about the Javanese script. The initial step in the introduction of the Javanese script starts with the preprocessing process by changing the image of the Javanese script from the RGB image to a grayscale image which is then performed feature extraction, where the feature extraction used in this script recognition is texture extraction with the Local Binary Pattern (LBP) algorithm. The results of this processing are obtained information that can be used as a parameter in the Multi Support Vector Machine (SVM) classification to predict Javanese script images. In this study using the LBP method with the Multi SVM Algorithm as a classification algorithm produces a high accuracy of 90% in the recognition of Javanese script, better than using only Multi SVM with an accuracy of 80%.
Measuring User Experience Of Traveloka Hotel Using User Experience Questionnaire
Authors: Aminurdin Majid , Maulana Donny , Wiyatno Tri Ngudi
Published: November 2023

Nowadays, there are many online travel agencies (OTAs) in Indonesia that provide various options for their customers. Before choosing which OTA to use, customers usually check each platform to ensure that they offer the best service. Traveloka is the most preferred OTA app by 67.5% of respondents. Google Play Store reviews show that users are still confused with information such as pricing and proper payment. Some features do not work properly when making hotel reservations. User Experience Questionnaire is used to quickly measure the user experience level of the product. Attractiveness, perspiculty, efficiency, accuracy, stimulation, and novelty were the six UEQ scales used. A random sample of one hundred app users was selected. The results showed that each scale was overall excellent. The criteria of attractiveness 2.485 ? 1.750, perspiculty 2.290 ? 1.900, efficiency 2.448 ? 1.780, dependability 2.338 ? 1.650, stimulation 2.393 ? 1.550, and novelty 2.293 ? 1.400. This research achieves the objectives or features of the application in terms of design, systems, and services. the result is that the Traveloka application can improve perspiculty with existing functions, so that the hotel booking process becomes easier to understand, easy to learn, simple, and clear.
INTERNATIONAL AND FOREIGN ECONOMIC RELATIONS AGREEMENTS OF THE SUBJECTS OF THE RUSSIAN FEDERATION: PROBLEMS OF LEGAL REGULATION
Authors:   Moscow Metropolitan Governance University, Moscow, Russian Federation, LOGVINOVA I.V.
Published: November 2023

The article analyzes the legal nature of the agreements of the subjects of the Russian Federation in the sphere of international relations and foreign economic activity. Using analytical methods, formal-legal and historical-legal approaches, the author has come to a number of conclusions of practical importance for the improvement of federal relations in the field of coordination of international activities of Russian regions. In particular, the problem of ensuring control over such forms of international interaction as agreements and other bilateral acts of international cooperation between the subjects of the Russian Federation and foreign partners is posed.
CIRCULAR ECONOMY IN CONDITIONS OF LOCALIZED PRODUCTION
Authors:   Financial University under the Government of the Russian Federation, Moscow, Russian Federation, KOSTYGOVA L.A.
Published: November 2023

The purpose of writing a research paper is to analyze the current state of the circulating economy of Russia and determine the potential for its development in modern conditions of localization of production. As a result of the research, the problem of implementing the concept of a circular economy in the context of the need to localize the production of critical products is considered. It is determined that a careful attitude focused on a closed cycle of using such resources is currently particularly important for the Russian economy. The potential of production localization processes is characterized. The role of the digital economy and ecosystems based on industrial symbiosis in the implementation of the circular economy in localized production is established.
THE NEED FOR INTERNATIONAL COOPERATION IN THE FIELD OF FINTECH DEVELOPMENT
Authors:   Moscow State Institute of International Relations (University) Russian Foreign Ministry, Moscow, Russian Federation, RAZLETOVSKAIA V.V.
Published: November 2023

The main trend in the field of financial technologies (fintech) is their increasing influence on the global economic order, international relations, as well as changes in organizational and managerial decisions related to their development at the national level. The article proves that these processes are not just a «reassembly» of the financial system on a new technological basis2, but have all the signs and forms of regular international financial integration. The active introduction of financial technologies into the practice of financial integration justifies the need for international cooperation in this area at a qualitatively different level, taking into account the convergence of technologies and the specifics of national models of fintech development. The results of the study of trends in international relations and forms of their coordination in the field of fintech development are presented: from the formation of intersectoral and interregional ecosystems to international agreements, alliances and coalitions. The stages of international financial integration and their corresponding forms and areas of coordination are highlighted.
Implementation Of The KWL Strategy (Know,Want And Learned) On Reading Comprehension Skills Of Students In Class IV Islamic Elementary School
Authors: Yaskuri Amin Wahyu , Marzuki Ismail
Published: November 2023

Reading is a very important aspect of Indonesian language skills. The ability of students after reading will obtain information and understand the meaning contained in the reading text is called reading comprehension skills. Not all students are able to read and understand the contents of the text they have read. One way of handling this problem is implementing the KWL strategy (Know, Want and  learned). Through this strategy, students are expected to be active in the learning process. In this study, the researcher used a qualitative descriptive study which had the aim of explaining the process, results and difficulties experienced by students in implementing the KWL strategy.Know, Want, and Learned). In this study using data collection techniques in the form of interviews and documentation. In addition, researchers used data analysis in the form of data reduction, data presentation, and drawing conclusions. And the results of this study will show differences in student activity from the first meeting to the second meeting. Furthermore, it was found that 10 out of 12 students could implement fairly good reading comprehension skills, and 2 out of 12 students had poor reading comprehension skills. Students experience difficulties in making conclusions and filling in KWL worksheets. This is the conclusion of this research.
Case Report: Pre-emptive intra-aortic balloon counterpulsation in patients with aortic regurgitation initiated after cross-clamping during cardiopulmonary bypass
Authors: Hirschl David , Muras Lennart , Schemke Simon , Vondran Maximilian , Heringlake Matthias
Published: November 2023

Preoperative implantation of an intra-aortic balloon pump has been shown to reduce mortality in high-risk cardiac surgery cases. However, one main contraindication for its use is severe aortic regurgitation. We describe a case of safe and beneficial use in a patient presenting with moderate to severe aortic regurgitation and highly reduced ejection fraction undergoing aortic valve replacement.
Feasibility and safety of left bundle branch area pacing for patients with stable coronary artery disease
Authors: Shan Yu , Lin Maoning , Sheng Xia , Zhang Jiefang , Sun Yaxun , Fu Guosheng , Wang Min
Published: November 2023

Aims

Stable coronary artery disease (CAD) is a prevalent comorbidity among patients requiring pacemaker implantation. This comorbidity may have an impact on the safety and prognosis of traditional right ventricular pacing (RVP). Left bundle branch area pacing (LBBaP) is a new physiological pacing modality. Our aim was to investigate the feasibility and safety of LBBaP in patients with the stable CAD.

Methods

This study included 309 patients with symptomatic bradycardia who underwent LBBaP from September 2017 to October 2021. We included 104 patients with stable CAD (CAD group) and 205 patients without CAD (non-CAD group). Additionally, 153 stable CAD patients underwent RVP, and 64 stable CAD patients underwent His-bundle pacing (HBP) were also enrolled in this study. The safety and prognosis of LBBaP was assessed by comparing pacing parameters, procedure-related complications, and clinical events.

Results

During a follow-up period of 17.4 ± 5.3 months, the safety assessment revealed that the overall rates of procedure-related complications were similar between the stable CAD group and the non-CAD group (7.7% vs. 3.9%). Likewise, similar rates of heart failure hospitalization (HFH) (4.8% vs. 3.4%, stable CAD vs. non-CAD) and the primary composite outcome including death due to cardiovascular disease, HFH, or the necessity for upgrading to biventricular pacing (6.7% vs. 3.9%, stable CAD vs. non-CAD), were observed. In stable CAD patients, LBBaP demonstrated lower pacing thresholds and higher R wave amplitudes when compared to HBP. Additionally, LBBaP also had significantly lower occurrences of the primary composite outcome (6.7% vs. 19.6%, P = 0.003) and HFH (4.8% vs. 13.1%, P = 0.031) than RVP in stable CAD patients, particularly among patients with the higher ventricular pacing (VP) burden (>20% and >40%).

Conclusion

Compared with non-CAD patients, LBBaP was found to be attainable in stable CAD patients and exhibited comparable mid-term safety and prognosis. Furthermore, in the stable CAD population, LBBaP has demonstrated more stable pacing parameters than HBP, and better prognostic outcomes compared to RVP.
Study protocol of a clinical randomized controlled trial on the efficacy of an innovative Digital thErapy to proMote wEighT loss in patients with obesity by incReasing their Adherence to treatment: the DEMETRA study
Authors: Castelnuovo Gianluca , Capodaglio Paolo , De Amicis Ramona , Gilardini Luisa , Mambrini Sara Paola , Pietrabissa Giada , Cavaggioni Luca , Piazzolla Giuseppina , Galeone Carlotta , Garavaglia Giacomo , Bertoli Simona ,   the DEMETRA Study Group
Published: November 2023

Despite the increasing importance of innovative medications and bariatric surgery for the treatment of obesity, lifestyle interventions (diet and physical activity) remain the first-line therapy for this disease. The use of digital devices in healthcare aims to respond to the patient's needs, in order to make obesity treatment more accessible, so our study aims to assess the safety and efficacy of a Digital Therapy for Obesity App (DTxO) for achieving weight loss and its maintenance in patients affected with obesity undergoing an experimental non-pharmacological treatment. Here we present the study protocol of a prospective, multicenter, pragmatic, randomized, double-arm, placebo-controlled, parallel, single-blind study on obese patients who will be treated with a new digital therapy to obtain an improvement in their disease condition through the application of different simultaneous strategies (a dietary regimen and personalized advice program, a tailored physical exercise program, a cognitive–behavioural assessment and program, alerts and reminders, dedicated section on prescribed drugs intake, and chat and online visits with clinical professionals). We believe that DTxO will offer a promising intervention channel and self-regulation tool holding the potentiality to decrease treatment burden and treat more patients thanks to the partial replacement of traditional medical consultation with digital or telephone management, improving self- engagement and reducing the high demands the “obesity pandemic” for both patients and national health services in terms of time, cost, and effort.

Clinical trial registration: clinicaltrials.gov, identifier, NCT05394779.
Wind power output prediction: a comparative study of extreme learning machine
Authors: Wang Zheng-Chuang , Niu Jin-Cai
Published: November 2023

This study aims to propose a wind power prediction method that achieves high accuracy in order to minimize the impact of wind power on the power system and reduce scheduling difficulties in systems incorporating wind power. The importance of developing renewable energy has been recognized by society due to the increasing severity of the energy crisis. Wind energy offers advantages such as efficiency, cleanliness, and ease of development. However, the random nature of wind energy poses challenges to power systems and complicates the scheduling process. Therefore, accurate wind power prediction is of utmost importance. A wind power prediction model was constructed based on an improved tunicate swarm algorithm–extreme learning machine (ITSA-ELM). The improved tunicate swarm algorithm (ITSA) optimizes the random parameters of extreme learning machine (ELM), resulting in the best prediction performance. ITSA is an enhancement of the tunicate swarm algorithm (TSA), which introduces a reverse learning mechanism, a non-linear self-learning factor, and a Cauchy mutation strategy to address the drawbacks of poor convergence and susceptibility to local optima in TSA. Two different scenarios were used to verify the effectiveness of ITSA-ELM. The results showed that ITSA-ELM has a decrease of 1.20% and 21.67% in MAPE, compared with TSA-ELM, in May and December, respectively. This study has significant implications for promoting the development of renewable energy and reducing scheduling difficulties in power systems.
Did the “double carbon” policy improve the green total factor productivity of iron and steel enterprises? a quasi-natural experiment based on carbon emission trading pilot
Authors: Xu Weilong , Jiang Chenjiu , Jia Kaiwei , Yu Xiaoyi
Published: November 2023

Based on the data of listed companies in China’s iron and steel industry from 2007 to 2020, the article investigates the impact mechanism and the path of action of China’s carbon emissions trading pilot on the green total factor productivity of iron and steel enterprises by constructing a multi-period difference-in-difference model difference-in-differences. The study finds that: 1) China’s iron and steel enterprises significantly improve their green total factor productivity driven by the carbon trading pilot, and the findings pass the corresponding robustness tests. 2) the mechanism analysis indicates that the carbon trading pilot promotes the green total factor productivity of iron and steel enterprises by forcing the technological progress of enterprises. 3) The heterogeneity analysis shows that the positive effect is more significant for large iron and steel enterprises with high social responsibility rating and high local government competition intensity, but not for small enterprises with low social responsibility rating and low local government competition intensity. 4) the dynamic effect shows that there is a certain lag in the promotion effect of the carbon emission trading pilot on the green total factor productivity of iron and steel enterprises, but its long-term effect is more obvious. This paper puts forward corresponding suggestions for accelerating the construction of a national unified green and low-carbon market system and actively promoting the deepening of the “dual-carbon” goal.
Numerical analysis of thermoelectric power generation coupled with temperature-dependent material properties
Authors: Xu Chaoyang , Huang Shixuan , Luo Hu , Li Guoneng , Fan Yinwei , Wei Shutian , Xu Cheng , Guo Wenwen
Published: November 2023

Thermoelectric generator (TEG) with improved performance is a promising technology in power supply and energy harvesting. Existing studies primarily adopt constant material properties to investigate TEG performance. However, thermoelectric (TE) material properties are subjected to considerable variations with temperature. Thus, reasonable doubts have risen concerning the influence level of temperature-dependent material properties on TEG performance. To solve this problem, an efficient and a comprehensive one-dimensional numerical model is developed to fully consider the third-order polynomial temperature-dependent thermal conductivity, Seebeck coefficient, and electrical resistivity. Control volume and finite difference algorithms are compared, and experiments are conducted to verify the developed numerical model. The temperature distribution along the TE leg obviously differs from the parabolic shape, which is a classic temperature distribution under the assumption of constant material properties. Insights find that the local change rate of thermal conductivity and Thomson effect are the essential reasons for the abovementioned phenomenon. It has been found that Thomson heat is released in the part of the leg near the cold-end, whereas it is absorbed in the remaining parts of the leg near the hot-end. The electric power on the basis of constant material properties is confirmed to be accurate enough by the developed numerical model, but the parabolic shape of the TE efficiency can be only obtained when temperature-dependent material properties are considered. Furthermore, it is wise to improve the TE efficiency by structural optimization. The present work provides an efficient and a comprehensive one-dimensional numerical model to include temperature-dependent material properties. New insights into the temperature and heat flux distribution, Thomson influence, and structural optimization potential are also presented for the in-depth understanding of the TE conversion process.
Unlocking inter-regional flexibility for the HVDC-connected two-area system with a multistage model
Authors: Wei Nan , Zhang Luomeng , Liu Siwei , Ye Hongxing
Published: November 2023

In recent years, the deployment of high-voltage direct current (HVDC) tie-lines in power grids has become a prevalent solution in some countries to transmit renewable energy from remote locations to load centers. However, the variability and uncertainty associated with renewable energy generation pose challenges to effectively utilizing this technology. This work proposes a novel multistage planning-operation model, aiming to unlock the potential flexibility in the HVDC transmission system and increase the renewable penetration. By incorporating flexibility, which is essential for accommodating the uncertainty in renewable generation, our model optimally shares the inter-regional flexibility between the sending- and receiving-end grids. One of the key features of our proposed model is its robustness and non-anticipativity, meaning it can account for different levels of uncertainty and make decisions that are suitable for multiple scenarios. This work develops two solution approaches to solve this challenging multistage model with variable uncertainty sets. We validate the proposed approach through a case study conducted on a real-world inter-regional grid. The numerical results demonstrate that our approach effectively unlocks more inter-regional flexibility and assists in increasing the renewable hosting capacity.
Pressurized metered-dose inhalers using next-generation propellant HFO-1234ze(E) deposit negligible amounts of trifluoracetic acid in the environment
Authors: Tewari Shivendra G. , Bell John P. , Budgen Nigel , Platz Stefan , Gibbs Megan , Newham Peter , Kimko Holly
Published: November 2023

Pressurized metered-dose inhalers (pMDIs) deliver life-saving medications to patients with respiratory conditions and are the most used inhaler delivery device globally. pMDIs utilize a hydrofluoroalkane (HFA), also known as an F-gas, as a propellant to facilitate the delivery of medication into the lungs. Although HFAs have minimal impact on ozone depletion, their global warming potential (GWP) is more than 1,000 times higher than CO2, bringing them in scope of the F-Gas Regulation in the European Union (EU). The pharmaceutical industry is developing solutions, including a near-zero GWP “next-generation propellant,” HFO-1234ze(E). At the same time, the EU is also evaluating a restriction on per-and polyfluoroalkyl substances (PFAS) under the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) regulation. Trifluoroacetic acid (TFA) is a persistent PFAS and a potential degradation product of HFO-1234ze(E). We quantified yield of TFA from HFO-1234ze(E) using a computational model under Europe-relevant atmospheric conditions. The modeling suggests that most HFO-1234ze(E) degrades into formyl fluoride within 20 days (≥85%) even at the highest examined altitude. These results suggest that TFA yield from HFO-1234ze(E) varies between 0%–4% under different atmospheric conditions. In 2022, France represented the highest numbers of pMDI units sold within the EU, assuming these pMDIs had HFO-1234ze(E) as propellant, we estimate an annual rainwater TFA deposition of ∼0.025 μg/L. These results demonstrate negligible formation of TFA as a degradation product of HFO-1234ze(E), further supporting its suitability as a non-persistent, non-bioaccumulative, and non-toxic future propellant for pMDI devices to safeguard access for patients to these essential medicines.
Serum profiling identifies CCL8, CXCL13, and IL-1RA as markers of active disease in patients with systemic lupus erythematosus
Authors: Lindblom Julius , Beretta Lorenzo , Borghi Maria Orietta ,   PRECISESADS Clinical Consortium, Alarcón-Riquelme Marta E. , Parodis Ioannis
Published: November 2023

Introduction

Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease that presents a challenge for clinicians. To identify potential biomarkers for diagnosis and disease activity in SLE, we investigated a selected yet broad panel of cytokines and autoantibodies in patients with SLE, healthy controls (HC), and patients with other autoimmune diseases (AIDs).

Methods

Serum samples from 422 SLE patients, 546 HC, and 1223 other AIDs were analysed within the frame of the European PRECISESADS project (NTC02890121). Cytokine levels were determined using Luminex panels, and autoantibodies using different immunoassays.

Results

Of the 83 cytokines analysed, 29 differed significantly between patients with SLE and HC. Specifically, CCL8, CXCL13, and IL-1RA levels were elevated in patients with active, but not inactive, SLE versus HC, as well as in patients with SLE versus other AIDs. The levels of these cytokines also correlated with SLE Disease Activity Index 2000 (SLEDAI-2K) scores, among five other cytokines. Overall, the occurrence of autoantibodies was similar across SLEDAI-2K organ domains, and the correlations between autoantibodies and activity in different organ domains were weak.

Discussion

Our findings suggest that, upon validation, CCL8, CXCL13, and IL-1RA could serve as promising serum biomarkers of activity in SLE.
Latent tuberculosis infection (LTBI) in health-care workers: a cross-sectional study at a northern Peruvian hospital
Authors: Meregildo-Rodriguez Edinson Dante , Yuptón-Chávez Verónica , Asmat-Rubio Martha Genara , Vásquez-Tirado Gustavo Adolfo
Published: November 2023

Background

Healthcare workers (HCWs) have a higher risk of latent tuberculosis infection (LTBI) and active tuberculosis than the general population. In HCWs, the risk of tuberculosis infection depends on the local tuberculosis prevalence, HCWs’ characteristics, the healthcare facility, and prevention and control measures. We aimed to estimate the prevalence and risk factors for LTBI in HCWs at a northern Peruvian hospital.

Methods

This study had two phases: (1) a cross-sectional phase involving recruitment, history taking, and sampling for the Interferon-Gamma Release Assays (IGRA test), and (2) a prospective follow-up of IGRA-positive participants. We enrolled direct and non-direct patient caregivers among HCWs. We defined an LTBI case if the IGRA test was positive and clinical, laboratory, and radiological evaluations for active tuberculosis were negative.

Results

We recruited 308 participants between November 2022 and May 2023. The mean age was 38.6 ± 8.3 years. Over 75% of the participants were female. The most common job category was technicians (30.5%), physicians (22.7%), nurses (20.5%), and other HCWs groups (17.5%). Most participants worked in hospital wards (28.2%), diagnostics departments (16.9%), and critical care departments (15.6%). The LTBI prevalence among HCWs was 17.86% (95% CI 13.84–22.70). In multivariate analysis, after adjusting for age, time working in our hospital, and family history of tuberculosis, males had a higher risk of LTBI (aPR 1.69, 95% CI 1.01–2.77) than females. Working for more than 10 years increased the risk of LBTI (aPR 2.4, 95% CI 1.44–3.97) compared to working for ≤10 years. Even further, participants who had worked for more than 20 years had an aPR of 4.31 (95% CI 1.09–13.65) compared to those with ≤10 years. Similarly, occupational exposure increased the risk of LTBI (aPR 2.21, 95% CI 1.27–4.08) compared to those HCWs not occupationally exposed.

Conclusion

The LTBI prevalence in HCWs at a northern Peruvian hospital was lower compared to other Peruvian cities. Males, more experienced, and occupational exposed HCWs are at higher risk of LTBI. LTBI prevalence in Peruvian HCWs is still high. More studies are needed to address some aspects this study has not examined.
Network meta-analysis of antibiotic resistance patterns in gram-negative bacterial infections: a comparative study of carbapenems, fluoroquinolones, and aminoglycosides
Authors: Muteeb Ghazala
Published: November 2023

Introduction

Antimicrobial resistance poses a grave global threat, particularly with the emergence of multidrug-resistant gram-negative bacterial infections, which severely limit treatment options. The increasing global threat of antimicrobial resistance demands rigorous investigation, particularly concerning multidrug-resistant gram-negative bacterial infections that present limited therapeutic options. This study employed a network meta-analysis, a powerful tool for comparative effectiveness assessment of diverse antibiotics. The primary aim of this study was to comprehensively evaluate and compare resistance patterns among widely used antibiotic classes, namely carbapenems, fluoroquinolones, and aminoglycosides, for combating gram-negative pathogens.

Methods

We searched PubMed, Web of Sciences, Scopus, Scholarly, Medline, Embase, and Cochrane databases up to August 27, 2023. Studies showing antibiotic resistance in clinical isolates of Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii exposed to carbapenems, fluoroquinolones, and aminoglycosides were included. This study determined treatment-specific resistance percentages and ranked these treatments based on resistance using a random-effects network meta-analysis technique. To investigate the impact of the study and pathogen features, subgroup and meta-regression analyses were performed. Risk ratios and 95% confidence intervals (CIs) were calculated using a network meta-analysis (NMA) incorporating both direct and indirect evidence. Clinical improvement, cure, microbiological eradication, and death from any cause were the primary outcomes. Nephrotoxicity was a secondary result.

Results

The analysis included 202 publications and 365,782 gram-negative isolates. The NMA included data from 20 studies and 4,835 patients. Carbapenems had the lowest resistance rates throughout the pathogen spectrum, with resistance percentages of 17.1, 22.4, and 33.5% for Enterobacteriaceae, P. aeruginosa, and A. baumannii, respectively. For the same infections, aminoglycosides showed resistance rates of 28.2, 39.1, and 50.2%, respectively. Fluoroquinolones had the highest resistance rates at 43.1, 57.3, and 65.7%, respectively. Unexpectedly, resistance to all three antibiotic classes has increased over time, with multidrug resistance being the most prevalent.

Conclusion

This extensive network meta-analysis provides an overview of the patterns of resistance throughout the world and how they are changing. The most effective choice is still carbapenems, but the increasing resistance highlights the critical need for multimodal therapies to protect antibiotic effectiveness against these powerful gram-negative infections.
Cranberry, but not D-mannose and ibuprofen, prevents against uropathogenic Escherichia coli-induced cell damage and cell death in MDCK cells
Authors: Konesan Jenane , Wang Jenny , Moore Kate H. , Mansfield Kylie J. , Liu Lu
Published: November 2023

Introduction

The main function of the urinary tract is to form an impermeable barrier against urinary solutes and bacteria. However, this barrier can be compromised by urinary tract infections, most commonly caused by uropathogenic Escherichia coli (UPEC). This can result in damage to the epithelial barrier, leading to decreased epithelial thickness, loss of tight junctions, loss of epithelial integrity, and apoptosis. Due to the rise in antimicrobial resistance, there is worldwide interest in exploring non-antibiotic agents as alternative therapy.

Methods

Using the Madin-Darby canine kidney (MDCK) cell line, a widely accepted epithelial cell model for the urinary tract, and the UPEC strain UTI89, this paper aimed to investigate the impact of UPEC on cell integrity, permeability, and barrier functions, and determine whether cranberry, D-mannose and ibuprofen could counteract the effects induced by UPEC. Furthermore, the study examined the protective potential of these agents against UPEC-induced increase in reactive oxygen species (ROS) production and programmed death-ligand 1 (PD-L1) expression.

Results

The results demonstrated that UTI89 caused a marked reduction in cell viability and monolayer integrity. Cranberry (3 mg/mL) was protective against these changes. In addition, cranberry exhibited protective effects against UPEC-induced damage to cell barrier integrity, escalation of oxidative stress, and UPEC/TNFα-triggered PD-L1 expression. However, no effect was observed for D-mannose and ibuprofen in alleviating UPEC-induced cell damage and changes in ROS and PD-L1 levels.

Conclusion

Overall, cranberry, but not D-mannose or ibuprofen, has a protective influence against UPEC associated damage in urinary epithelial cells.
NMR-based metabolomics in Alzheimer’s disease research: a review
Authors: Vignoli Alessia , Tenori Leonardo
Published: November 2023

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and represents the most common cause of dementia in the elderly population worldwide. Currently, there is no cure for AD, and the continuous increase in the number of susceptible individuals poses one of the most significant emerging threats to public health. However, the molecular pathways involved in the onset and progression of AD are not fully understood. This information is crucial for developing less invasive diagnostic instruments and discovering novel potential therapeutic targets. Metabolomics studies the complete ensemble of endogenous and exogenous metabolites present in biological specimens and may provide an interesting approach to identify alterations in multiple biochemical processes associated with AD onset and evolution. In this mini review, we summarize the results from metabolomic studies conducted using nuclear magnetic resonance (NMR) spectroscopy on human biological samples (blood derivatives, cerebrospinal fluid, urine, saliva, and tissues) from AD patients. We describe the metabolic alterations identified in AD patients compared to controls and to patients diagnosed with mild cognitive impairment (MCI). Moreover, we discuss the challenges and issues associated with the application of NMR-based metabolomics in the context of AD research.
Spinal cord stimulation in severe pharmacoresistant restless legs syndrome—two case reports
Authors: Hackethal Sandra , Maino Paolo , Koetsier Eva , Manconi Mauro
Published: November 2023

Restless legs syndrome is a prevalent, sleep-related sensorimotor disorder with relevant impact on the patients’ quality of life. For patients suffering from severe, pharmacoresistant restless legs syndrome, few therapeutic options remain to alleviate symptoms. In this case series, two patients with severe, pharmacoresistant restless legs syndrome were treated with epidural spinal cord stimulation and repeatedly assessed with polysomnography, including sleep structure and periodic limb movements as objective biomarkers not subject to placebo effects, during a 6-month follow-up period. One of the patients experienced excellent short- and long-term efficacy on subjective symptom severity (International RLS Study group rating scale 1 vs. 34 points at 3 months) and objective sleep parameters such as sleep architecture and periodic limb movements during sleep, while the second patient only reported short-term benefits from spinal cord stimulation. Ultimately, both patients opted for removal of the device for inefficacy. Based on the complex pathophysiology of restless legs syndrome and presumed mechanism of action of spinal cord stimulation in chronic pain disorders, we provide a detailed hypothesis on the possible modulating effect of spinal cord stimulation on the key symptoms of restless legs syndrome. Apart from describing a new therapeutic option for pharmacoresistant restless legs syndrome, our findings might also provide further insights into the pathophysiology of the syndrome.
Value of novel thrombotic markers for predicting occurrence of the malignant cerebral artery infarction: a prospective clinical study
Authors: Zhao Xiaoxia , Yang Siyu , Lei Ruining , Liu Yi , Duan Qiaoyan , Li Jundong , Sun Lei
Published: November 2023

Objective

This study investigated the diagnostic performance of thrombin–antithrombin complex (TAT), plasmin–α2 plasmin inhibitor complex (PIC), tissue plasminogen activator–plasminogen activator inhibitor complex (t-PAIC), and thrombomodulin (TM) in predicting the progression of massive cerebral infarction to the malignant cerebral artery infarction.

Method

A total of 71 patients with massive cerebral infarction confirmed by imaging examination were divided into malignant cerebral artery infarction group (MCAI) and non-malignant cerebral artery infarction group (NMCAI) based on whether they progressed to MCAI after admission. TAT, PIC, t-PAIC, and TM were measured immediately after admission. The predictive performance was analyzed by the receiver characteristic operating curve (ROC).

Result

The median plasma concentrations of TM, PIC, TAT, and t-PAIC in the MCAI patients at admission were 10.65 IU/mL, 1.17 μg/mL, 12.25 ng/mL, and 13.85 ng/mL, respectively, which were higher than those in the NMCAI patients (9.00 IU/mL, 1.07 μg/mL, 4.60 ng/mL, and 8.70 ng/mL), and the difference was statistically significant (p = 0.045, p = 0.035, p = 0.004, and p = 0.003). Elevated plasma t-PAIC concentration was shown to be an independent risk factor for progression of massive cerebral infarction to MCAI (OR = 1.131) by multivariate logistic regression analysis. ROC curve analysis showed that t-PAIC was the best predictor of MCAI (AUC = 74.7%), with a sensitivity of 75.0% and specificity of 75.9% when t-PAIC concentration was ≥12.4 ng/mL; TAT had the highest specificity in predicting MCAI, with a specificity of 90.7% when the TAT concentration was ≥13.5 ng/mL.

Conclusion

The detection of PIC, TAT, t-PAIC, and TM is a comprehensive assessment of vascular endothelial damage and activation of the coagulation and fibrinolytic systems and has predictive value for poor prognosis in patients with MCAI. The widespread use of these tests will likely greatly improve the early diagnosis rate of MCAI.
Neuron pruning in temporal domain for energy efficient SNN processor design
Authors: Lew Dongwoo , Tang Hoyoung , Park Jongsun
Published: November 2023

Recently, the accuracy of spike neural network (SNN) has been significantly improved by deploying convolutional neural networks (CNN) and their parameters to SNN. The deep convolutional SNNs, however, suffer from large amounts of computations, which is the major bottleneck for energy efficient SNN processor design. In this paper, we present an input-dependent computation reduction approach, where relatively unimportant neurons are identified and pruned without seriously sacrificing the accuracies. Specifically, a neuron pruning in temporal domain is proposed that prunes less important neurons and skips its future operations based on the layer-wise pruning thresholds of membrane voltages. To find the pruning thresholds, two pruning threshold search algorithms are presented that can efficiently trade-off accuracy and computational complexity with a given computation reduction ratio. The proposed neuron pruning scheme has been implemented using 65 nm CMOS process. The SNN processor achieves a 57% energy reduction and a 2.68× speed up, with up to 0.82% accuracy loss and 7.3% area overhead for CIFAR-10 dataset.
Advances in the study of the effects of gut microflora on microglia in Alzheimer’s disease
Authors: Wu Jin-Jing , Wei Zhe
Published: November 2023

Alzheimer’s disease (AD) is a central nervous system (CNS) degenerative disorder, is caused by various factors including β-amyloid toxicity, hyperphosphorylation of tau protein, oxidative stress, and others. The dysfunction of microglia has been associated with the onset and advancement of different neurodevelopmental and neurodegenerative disorders, such as AD. The gut of mammals harbors a vast and complex population of microorganisms, commonly referred to as the microbiota. There’s a growing recognition that these gut microbes are intrinsically intertwined with mammalian physiology. Through the circulation of metabolites, they establish metabolic symbiosis, enhance immune function, and establish communication with different remote cells, including those in the brain. The gut microbiome plays a crucial part in influencing the development and performance of microglia, as indicated by recent preclinical studies. Dysbiosis of the intestinal flora leads to alterations in the microglia transcriptome that regulate the interconversion of microglia subtypes. This conversation explores recent research that clarifies how gut bacteria, their byproducts, and harmful elements affect the activation and characteristics of microglia. This understanding opens doors to innovative microbial-based therapeutic strategies for early identification and treatment goals in AD.
Pre-sleep protein supplementation does not improve performance, body composition, and recovery in British Army recruits (part 1)
Authors: Chapman Shaun , Roberts Justin , Roberts Andrew J. , Ogden Henry , Izard Rachel , Smith Lee , Chichger Havovi , Struszczak Lauren , Rawcliffe Alex J.
Published: November 2023

Dietary protein is crucial for optimising physical training adaptations such as muscular strength and mass, which are key aims for athletic populations, including British Army recruits. New recruits fail to meet the recommended protein intake during basic training (BT), with negligible amounts consumed in the evening. This study assessed the influence of a daily bolus of protein prior to sleep on performance adaptations, body composition and recovery in British Army recruits. 99 men and 23 women [mean ± standard deviation (SD): age: 21.3 ± 3.5 years, height: 174.8 ± 8.4 cm, body mass 75.4 ± 12.2 kg] were randomised into a dietary control (CON), carbohydrate placebo (PLA), moderate (20 g) protein (MOD) or high (60 g) protein (HIGH) supplementation group. Supplements were isocaloric and were consumed on weekday evenings between 2000 and 2100 for 12 weeks during BT. Performance tests (mid-thigh pull, medicine ball throw, 2 km run time, maximal push-up, and maximal vertical jump) and body composition were assessed at the start and end of BT. Dietary intake, energy expenditure, salivary hormones, urinary nitrogen balance, perceived muscle soreness, rating of perceived exertion, mood, and fatigue were assessed at the start, middle and end of BT. Protein supplementation increased protein intake in HIGH (2.16 ± 0.50 g⸱kg−1⸱day−1) and MOD (1.71 ± 0.48 g⸱kg−1⸱day−1) compared to CON (1.17 ± 0.24 g⸱kg−1⸱day−1) and PLA (1.31 ± 0.29 g⸱kg−1⸱day−1; p < 0.001). Despite this, there was no impact of supplementation on mid-thigh pull performance (CON = 7 ± 19%, PLA = 7 ± 19%, MOD = 0 ± 16%, and HIGH = 4 ± 14%; p = 0.554) or any other performance measures (p > 0.05). Fat-free mass changes were also similar between groups (CON = 4 ± 3%, PLA = 4 ± 4%, MOD = 3 ± 3%, HIGH = 5 ± 4%, p = 0.959). There was no impact of protein supplementation on any other body composition or recovery measure. We conclude no benefits of pre-bed protein supplementation to improve performance, body composition and recovery during BT. It is possible the training stimulus was great enough, limiting the impact of protein supplementation. However, the high degree of inter-participant variability suggests an individualised use of protein supplementation should be explored, particularly in those who consume sub-optimal (<1.6 g⸱kg−1⸱day−1) habitual amounts of protein.

Clinical trial registration: The study was registered with ClinicalTrials.gov, U.S. national institutes (identifier: NCT05998590).
Assessment of aggressive bladder cancer mutations in plasma cell-free DNA
Authors: Carrasco Raquel , Ingelmo-Torres Mercedes , Oriola Josep , Roldán Fiorella L. , Rodríguez-Carunchio Leonardo , Herranz Sandra , Mellado Begoña , Alcaraz Antonio , Izquierdo Laura , Mengual Lourdes
Published: November 2023

Background and aims

The spatial and temporal genetic heterogeneity of bladder cancer (BC) makes challenging to find specific drivers of metastatic disease, thus preventing to determine those BC patients at high risk of tumor progression. Our aim was to identify DNA mutations providing aggressive behavior to bladder tumors and analyze them in patients’ cell-free DNA (cfDNA) during their follow-up after radical cystectomy (RC) in order to monitor tumor evolution.

Methods

Six BC patients who underwent RC and presented disease progression during their follow-up were included. Next-generation sequencing was used to determine somatic mutations in several primary tumor and metastatic specimens from each patient. Shared DNA mutations between primary bladder tumor and metastatic sites were identified in cfDNA samples through droplet digital PCR.

Results

Besides BC genetic heterogeneity, specific mutations in at least one of these genes —TERT, ATM, RB1, and FGFR3— were found in primary tumors and their metastases in all patients. These mutations were also identified in the patients’ cfDNA at different follow-up time points. Additionally, the dynamic changes of these mutations in cfDNA allowed us to determine tumor evolution in response to treatment.

Conclusion

The analysis of BC mutations associated with poor prognosis in plasma cfDNA could be a valuable tool to monitor tumor evolution, thus improving the clinical management of BC patients.