bluuebunny/crossref_metadata_2025_split huggingface dataset:
Degree of loss in the tissue thickness, microvascular density, specific perimetry and standard perimetry in early glaucoma
Authors: Hirasawa Kazunori , Yamaguchi Jun , Nagano Koichi , Kanno Junji , Kasahara Masayuki , Shoji Nobuyuki 
Published: April 2023

ObjectiveTo identify the degree of loss of the circumpapillary retinal nerve fibre layer (cpRNFL), the layer from the macular RNFL to the inner plexiform layer (mGCL++), circumpapillary (cpVD) and macular vascular density (mVD), Pulsar perimetry and standard perimetry in early glaucoma.MethodsIn this cross-sectional study, one eye from each of 96 healthy controls and 90 eyes with open-angle glaucoma were measured with cpRNFL, mGCL++, cpVD, mVD, Pulsar perimetry with Octopus P32 test (Pulsar) and standard perimetry with Humphrey field analyser 24-2 test (HFA). For direct comparison, all parameters were converted to relative change values adjusted in both their dynamic range and age-corrected normal value.ResultsThe degree of loss in mGCL++ (−24.7%) and cpRNFL (−25.8%) was greater than that in mVD (−17.3%), cpVD (−14.9%), Pulsar (−10.1%) and HFA (−5.9%) (each p<0.01); the degree of loss in mVD and cpVD was greater than that in Pulsar and HFA (each p<0.01); and the degree of loss in Pulsar was greater than that in HFA (p<0.01). The discrimination ability between glaucomatous and healthy eyes (area under the curve) was higher for mGCL++ (0.90) and cpRNFL (0.93) than for mVD (0.78), cpVD (0.78), Pulsar (0.78) and HFA (0.79).ConclusionThe degree of loss of cpRNFL and mGCL++ thickness preceded by approximately 7%–10% and 15%–20% compared with the micro-VD and visual fields in early glaucoma, respectively.Trial registration numberUMIN Clinical Trials Registry (http://www.umin.ac.jp/; R000046076 UMIN000040372).
Improving type 2 diabetes mellitus management in Ministry of Defense Hospitals in the Kingdom of Saudi Arabia 2018–2021
Authors: Alotaibi Yasser K , Al-Nowaiser Noura , Al Harbi Turki J , Tourkmani Ayla M , Moharram Maha 
Published: April 2023

Diabetes mellitus is a metabolic disease characterised by elevated levels of blood glucose and is a leading cause of disability and mortality. Uncontrolled type 2 diabetes leads to complications such as retinopathy, nephropathy and neuropathy. Improved treatment of hyperglycaemia is likely to delay the onset and progression of microvascular and neuropathic complications.This article describes the efforts of 18 governmental hospitals in the Kingdom of Saudi Arabia that enrolled in a collaborative improvement project to improve the poor glycaemic control (HbA1c >9% to be less than 15%) of patients with diabetes by the end of 2021 among all the chronic illness clinics in the enrolled military hospitals. Enrolled hospitals were required to implement an evidence-based change package that included the implementation of diabetes clinical practice guidelines with standardised assessment and care planning tools. Furthermore, care delivery was standardised using a standard clinic scope of service that focused on multidisciplinary care teams. Finally, hospitals were required to implement diabetes registries that were used by case managers for poorly controlled patients.The project timetable was from October 2018 to December 2021. Diabetes poor control (HbA1c >9%) showed improved mean difference of 12.7% (34.9% baseline, 22.2% after) with a p value of 0.01. Diabetes optimal testing significantly improved from 41% at the start of the project in the fourth quarter of 2018, reaching 78% by the end of the fourth quarter of 2021. Variation between hospitals showed a significant reduction in the first quarter of 2021.The collaborative multilevel approach of standardising the care based on the best available evidence through policies, guidelines and protocols, patient-focused care and integrated care plan by a multidisciplinary team was associated with noticeable improvement in all key performance indicators of the project.
Targeted multiomics in childhood-onset SLE reveal distinct biological phenotypes associated with disease activity: results from an explorative study
Authors: Wahadat Mohamed Javad , van Tilburg Sander J , Mueller Yvonne M , de Wit Harm , Van Helden-Meeuwsen Cornelia G , Langerak Anton W , Gruijters Marike J , Mubarak Amani , Verkaaik Marleen , Katsikis Peter D , Versnel Marjan A , Kamphuis Sylvia 
Published: April 2023

ObjectiveTo combine targeted transcriptomic and proteomic data in an unsupervised hierarchical clustering method to stratify patients with childhood-onset SLE (cSLE) into similar biological phenotypes, and study the immunological cellular landscape that characterises the clusters.MethodsTargeted whole blood gene expression and serum cytokines were determined in patients with cSLE, preselected on disease activity state (at diagnosis, Low Lupus Disease Activity State (LLDAS), flare). Unsupervised hierarchical clustering, agnostic to disease characteristics, was used to identify clusters with distinct biological phenotypes. Disease activity was scored by clinical SELENA-SLEDAI (Safety of Estrogens in Systemic Lupus Erythematosus National Assessment-Systemic Lupus Erythematosus Disease Activity Index). High-dimensional 40-colour flow cytometry was used to identify immune cell subsets.ResultsThree unique clusters were identified, each characterised by a set of differentially expressed genes and cytokines, and by disease activity state: cluster 1 contained primarily patients in LLDAS, cluster 2 contained mainly treatment-naïve patients at diagnosis and cluster 3 contained a mixed group of patients, namely in LLDAS, at diagnosis and disease flare. The biological phenotypes did not reflect previous organ system involvement and over time, patients could move from one cluster to another. Healthy controls clustered together in cluster 1. Specific immune cell subsets, including CD11c+ B cells, conventional dendritic cells, plasmablasts and early effector CD4+ T cells, differed between the clusters.ConclusionUsing a targeted multiomic approach, we clustered patients into distinct biological phenotypes that are related to disease activity state but not to organ system involvement. This supports a new concept where choice of treatment and tapering strategies are not solely based on clinical phenotype but includes measuring novel biological parameters.
Moving Spatially Resolved Multiplexed Protein Profiling toward Clinical Oncology
Authors: Pourmaleki Maryam , Socci Nicholas D. , Hollmann Travis J. , Mellinghoff Ingo K. 
Published: April 2023

Summary:The shift in cancer therapy from broadly cytotoxic agents toward “personalized” treatments that target specific alterations in each patient's tumor requires diagnostic pathology approaches that are quantitative and biospecimen-friendly. Novel multiplexed antibody-based imaging technologies can measure single-cell expression of over 60 proteins in intact tumor sections and hold promise for clinical oncology.
Adiabatic technique based low power synchronous counter design
Authors: Sanadhya Minakshi , Sharma Devendra Kumar , Hameed Chyad Alfilh Raed 
Published: April 2023

<p>The performance of integrated circuits is evaluated by their design architecture, which ensures high reliability and optimizes energy. The majority of the system-level architectures consist of sequential circuits. Counters are fundamental blocks in numerous very large-scale integration (VLSI) applications. The T-flip-flop is an important block in synchronous counters, and its high-power consumption impacts the overall effectiveness of the system. This paper calculates the power dissipation (PD), power delay product (PDP), and latency of the presented T flip-flop. To create a 2-bit synchronous counter based on the novel T flip-flops, a performance matrix such as PD, latency, and PDP is analyzed. The analysis is carried out at 100 and 10 MHz frequencies with varying temperatures and operating voltages. It is observed that the presented counter design has a lesser power requirement and PDP compared to the existing counter architectures. The proposed T-flip-flop design at the 45 nm technology node shows an improvement of 30%, 76%, and 85% in latency, PD, and PDP respectively to the 180 nm node at 10 MHz frequency. Similarly, the proposed counter at the 45 nm technology node shows 96% and 97% improvement in power dissipation, delay, and PDP respectively compared to the 180 nm at 10 MHz frequency.</p>
Design and performance analysis of front and back Pi 6 nm gate with high K dielectric passivated high electron mobility transistor
Authors: Gowthami Yadala , Balaji Bukya , Srinivasa Rao Karumuri 
Published: April 2023

Advanced high electron mobility transistor (HEMT) with dual front gate, back gate with silicon nitride/aluminum oxide (Si3N4/Al2O3) as passivation layer, has been designed. The dependency on DC characteristics and radio frequency characteristics due to GaN cap layers, multi gate (FG and BG), and high K dielectric material is established. Further compared single gate (SG) passivated HEMT, double gate (DG) passivated HEMT, double gate triple (DGT) tooth passivated HEMT, high K dielectric front Pi gate (FG) and back Pi gate (BG) HEMT. It is observed that there is an increased drain current (Ion) of 5.92 (A/mm), low leakage current (Ioff) 5.54E-13 (A) of transconductance (Gm) of 3.71 (S/mm), drain conductance (Gd) of 1.769 (S/mm), Cutoff frequency (fT) of 743 GHz maximum oscillation frequency (Fmax) 765 GHz, minimum threshold voltage (V<sub>th</sub>) of -4.5 V, on resistance (Ron) of 0.40 (Ohms) at V<sub>gs</sub>=0 V. These outstanding characteristics and transistor structure of proposed HEMT and materials involved to apply for upcoming generation high-speed GHz frequency applications.
Modeling and simulation of the two-tank system within a hybrid framework
Authors: Yaakoubi Hanen , Haggège Joseph 
Published: April 2023

<p><span lang="EN-US">Most real-world dynamical systems are often involving continuous behaviors and discrete events, in this case, they are called hybrid dynamical systems (HDSs). To properly model this kind of systems, it is necessary to consider both the continuous and the discrete aspects of its dynamics. In this paper, a modeling framework based on the hybrid automata (HA) approach is proposed. This hybrid modeling framework allows combining the multi-state models of the system, described by nonlinear diﬀerential equations, with the system’s discrete dynamics described by ﬁnite state machines. To attest to the efficiency of the proposed modeling framework, its application to a two-tank hybrid system (TTHS) is presented. The TTHS studied is a typical benchmark for HDSs with four operating modes. The MATLAB Simulink and Stateflow tools are used to implement and simulate the hybrid model of the TTHS. Different simulations results demonstrate the efficiency of the proposed modeling framework, which allows us to appropriately have a complete model of an HDS.</span></p>
Detection of chest pathologies using autocorrelation functions
Authors: Abdikerimova Gulzira , Shekerbek Ainur , Tulenbayev Murat , Beglerova Svetlana , Zakharevich Elena , Bekmagambetova Gulmira , Manbetova Zhanat , Baibulova Makbal 
Published: April 2023

<p><span lang="EN-US">An important feature of image analysis is texture, seen in all images, from aerial and satellite images to microscopic images in biomedical research. A chest X-ray is the most common and effective method for diagnosing severe lung diseases such as cancer, pneumonia, and tuberculosis. The lungs are the largest X-ray object. The correct separation of the shapes and sizes of the contours of the lungs is an important reason for diagnosis, because of which an intelligent information environment can be created. Despite the use of X-rays, to identify the diagnosis, there is a chance that the disease will not be detected. In this sense, there is a risk of development, which may be fatal. The article deals with the problems of pneumonia clustering using the autocorrelation function to obtain the most accurate result. This provides a reliable tool for diagnosing lung radiographs. Image pre-processing and data shaping play an important role in revealing a well-functioning basis of the nervous system. Therefore, images from two classes were selected for the task: healthy and with pneumonia. This paper demonstrates the applicability of the autocorrelation function for highlighting interest in lung radiographs based on the fineness of textural features and k-means extraction.</span></p>
Implementation of recurrent neural network for the forecasting of USD buy rate against IDR
Authors: Moonlight Lady Silk , Trilaksono Bambang Riyanto , Harianto Bambang Bagus , Faizah Fiqqih 
Published: April 2023

<span lang="EN-US">This study implements a recurrent neural network (RNN) by comparing two RNN network structures, namely Elman and Jordan using the backpropagation through time (BPTT) programming algorithm in the training and forecasting process in foreign exchange forecasting cases. The activation functions used are the linear transfer function, the tan-sigmoid transfer function (Tansig), and the log-sigmoid transfer function (Logsig), which are applied to the hidden and output layers. The application of the activation function results in the log-sigmoid transfer function being the most appropriate activation function for the hidden layer, while the linear transfer function is the most appropriate activation function for the output layer. Based on the results of training and forecasting the USD against IDR currency, the Elman BPTT method is better than the Jordan BPTT method, with the best iteration being the 4000<sup>th</sup> iteration for both. The lowest root mean square error (RMSE) values for training and forecasting produced by Elman BPTT were 0.073477 and 122.15 the following day, while the Jordan backpropagation RNN method yielded 0.130317 and 222.96 also the following day.</span><p> </p>
Towards a new intelligent traffic system based on deep learning and data integration
Authors: Slimani Nadia , Yousfi Siham , Amghar Mustapha , Sbiti Nawal 
Published: April 2023

<span lang="EN-US">Time series forecasting is an important technique to study the behavior of temporal data in order to forecast the future values, which is widely applied in intelligent traffic systems (ITS). In this paper, several deep learning models were designed to deal with the multivariate time series forecasting problem for the purpose of long-term predicting traffic volume. Simulation results showed that the best forecasts are obtained with the use of two hidden long short-term memory (LSTM) layers: the first with 64 neurons and the second with 32 neurons. Over 93% of the forecasts were made with less than ±2.0% error. The analysis of variances is mainly due to peaks in some extreme conditions. For this purpose, the data was then merged between two different sources: electromagnetic loops and cameras. Data fusion is based on a calibration of the reliability of the sources according to the visibility conditions and time of the day. The integration results were then compared with the real data to prove the improvement of the prediction results in peak periods after the data fusion step.</span><p> </p>
3D human hands rendering by a six degrees of freedom collaborative robot and a single 2D camera
Authors: Boyack Michael , Sices Alexsandra , Jo Bruce Woongyeol 
Published: April 2023

Human hands are essential in everyday tasks, mainly manipulating and grasping objects. Thus, accurate and precise three-dimensional (3D) models of digitally reconstructed hands are valuable to the world of ergonomics. A 3D scan-to-render system called the “3D hands model rendering using a 6-degrees of freedom (DoF) collaborative robot” is proposed to ensure that a person receives the best possible outcome for their unique anatomy. The description implies this is using a 6-DoF robot with a two-dimensional (2D) camera sensor that will encompass all forms of the production line in a timely, low-cost, precise, and accurate manner so that an individual can go to and scan their hand and have an actual 3D reconstruction print within the same facility, the same day. It is expected to generate an accurate hand model using structure from motion (SFM) system techniques to create a dense point cloud using photogrammetry. The point cloud is used to develop the tetrahedral mesh of the surface of the hand. This mesh is then refined to filter out the noise of the point cloud. The mesh can produce a precise 3D model that can tailor products to the consumer's needs. The results show the effectiveness of the 3D model of the hand.
Anticancer medicines in Pakistan: An analysis of essential medicines lists
Authors: Shukar Sundus , Anjum Rehan , Zhang Jinwei , Babar Zaheer-Ud-Din , Mobeen Iqra , Yang Caijun 
Published: April 2023

Objective The lack of anticancer drugs for curative and supportive purposes is the critical reason for the low survival rate in low-and-middle-income countries. This study aims to analyze whether the National Essential Medicines List (NEML) and Registered Essential Medicines List (REML) are in concordance with the World Health Organization (WHO) Essential Medicines List (EML) and whether the formularies prevalent in the country are parallel to each other and to the NEML. Method An observational study design was used in which antineoplastic drugs from the 2021 NEML and REML were compared with 2021 WHO EML to evaluate their availability in Pakistan. Market access was determined. Moreover, the formularies of six different hospital types were compared with each other and with the NEML, and REML to estimate the availability within hospitals. Results There were 66 anticancer drugs in 2021 WHO EML and all were found in Pakistan's 2021 NEML but only 48 drugs (73%) were found in the REML. Hydroxycarbamide and dasatinib were two registered drugs absent in all hospitals’ formularies. The market access for anticancer medicines was 73% (48 of 66). Semigovernment hospital (86%) has the highest availability, followed by the government hospital (80%). All the hospitals have unregistered drugs including bortezomib, lenalidomide, and mesna. Conclusion Pakistan's NEML adopts WHO EML abruptly but all medicines are not registered. The hospitals are trying their best to increase availability but optimum drug regulations to revise NEML based on the country's requirements and emphasizing registration of anticancer medicines are needed to improve the country's availability of antineoplastic agents.
Reg3α concentrations at day of allogeneic stem cell transplantation predict outcome and correlate with early antibiotic use
Authors: Weber Daniela , Weber Markus , Meedt Elisabeth , Ghimire Sakhila , Wolff Daniel , Edinger Matthias , Poeck Hendrik , Hiergeist Andreas , Gessner André , Ayuk Francis , Roesler Wolf , Wölfl Matthias , Kraus Sabrina , Zeiser Robert , Bertrand Hannah , Bader Peter , Ullrich Evelyn , Eder Matthias , Gleich Sigrun , Young Rachel , Herr Wolfgang , Levine John E. , Ferrara James L. M. , Holler Ernst 
Published: April 2023

Abstract
Intestinal microbiome diversity plays an important role in the pathophysiology of acute gastrointestinal (GI) graft-versus-host disease (GVHD) and influences the outcome of patients after allogeneic stem cell transplantation (ASCT). We analyzed clinical data and blood samples taken preconditioning and on the day of ASCT from 587 patients from 7 German centers of the Mount Sinai Acute GVHD International Consortium, dividing them into single-center test (n = 371) and multicenter validation (n = 216) cohorts. Regenerating islet–derived 3α (Reg3α) serum concentration of day 0 correlated with clinical data as well as urinary 3-indoxylsulfate (3-IS) and Clostridiales group XIVa, indicators of intestinal microbiome diversity. High Reg3α concentration at day 0 of ASCT was associated with higher 1-year transplant-related mortality (TRM) in both cohorts (P &lt; .001). Cox regression analysis revealed high Reg3α at day 0 as an independent prognostic factor for 1-year TRM. Multivariable analysis showed an independent correlation of high Reg3α concentrations at day 0 with early systemic antibiotic (AB) treatment. Urinary 3-IS (P = .04) and Clostridiales group XIVa (P = .004) were lower in patients with high vs those with low day 0 Reg3α concentrations. In contrast, Reg3α concentrations before conditioning therapy correlated neither with TRM nor disease or treatment-related parameters. Reg3α, a known biomarker of acute GI GVHD correlates with intestinal dysbiosis, induced by early AB treatment in the period of pretransplant conditioning. Serum concentrations of Reg3α measured on the day of graft infusion are predictive of the risk for TRM of ASCT recipients.
Transmission of oral microbiota to the biliary tract during endoscopic retrograde cholangiography
Authors: Effenberger Maria , Al-Zoairy Ramona , Gstir Ronald , Graziadei Ivo , Schwaighofer Hubert , Tilg Herbert , Zoller Heinz 
Published: April 2023

Abstract
Background
Endoscopic retrograde cholangiography (ERC) possesses a translocation risk of microbes to the biliary system. We studied bile contamination during ERC and its impact on patients’ outcome in a real-life-situation.

Methods
Ninety-nine ERCs were analyzed and microbial samples were taken from the throat before and from bile during ERC and from irrigation fluid of the duodenoscope before and after ERC.

Results
91.2% of cholangitis patients had detectable microbes in the bile (sensitivity 91%), but the same was true for 86.2% in the non-cholangitis group. Bacteroides fragilis (p=0.015) was significantly associated with cholangitis. In 41.7% of ERCs with contaminated endoscopes these microbes were found in the bile after the procedure. Analysis of duodenoscopes’ irrigation liquid after ERC matched the microbial bile analysis of these patients in 78.8%. Identical microbial species were in throat and in bile samples of the same ERC in 33% of all cases and in 45% in the non-cholangitis group. Transmission of microbes to the biliary tract did not result in more frequent cholangitis, longer hospital stays, or worse outcome.

Conclusions
During ERC bile samples are regularly contaminated with microbes of the oral cavity but it did not affect clinical outcome.
Subjective social status and health among older adults in China: the longitudinal mediating role of social trust
Authors: Zhou Jingjing , Guo Wei , Ren Hang 
Published: April 2023

Abstract
Background
From a developmental perspective, this study explored the interplays between subjective social status (SSS), social trust (ST), and health status measured by self-rated health (SRH) among older adults in the context of China. It also tested the longitudinal mediation of ST between SSS and SRH.

Methods
After excluding samples with missing values, we analyzed 4,877 individual responses from those aged 60 years or older, extracted from the China Family Panel Studies (CFPS) data in 2014, 2016, and 2018. We used latent growth modeling to test the hypothesized relationships among their SSS, ST, and SRH.

Results
Latent growth modeling based on bootstrapping showed that the SSS, ST, and SRH of older adults all increased linearly and that the mechanism of SSS acted on the SRH as follows: the initial level of SSS indirectly influenced the initial level and the growth rate of the SRH, respectively, through the initial level of ST, and the initial level and growth rate of SSS played an indirect role in the growth rate of the SRH through the growth rate of ST.

Conclusion
The findings have practical implications for promoting health for older adults and realizing active aging in China. Therefore, we recommend establishing a family-centered and community-supported social support system for those with lower social status among older adults and a friendly community environment with various social, cultural, and recreational activities to improve the ST among older adults, thereby improving their health.