bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening of key genes for m6A modification differences in childhood sepsis
Authors: Hong quxiang , Wu WenTao , Li XiaoMin
Published: June 2024

Sepsis in children is a syndrome associated with organ dysfunction caused by immune dysregulation of inflammatory responses in children. According to the latest data, nearly50 million people have been diagnosed with sepsisand nearly10 million have died. M6A methylation has been reported to be associated with sepsis-associated inflammatory response[2],however, the molecular biological mechanism underlying the diagnosis and treatment of m6A related genes in children remains unclear. It provides a new way for clinical incidence prediction and molecular biology diagnosis, and further guides clinical treatment.The GEO database chip dataset GSE66099 was downloaded and annotated by platform files. The m6A related genes were extracted. The data were standardized by R language limma package.181 children with septic shock,18 children with sepsis were selected as sepsis group,47 normal childrenand30 children with common SIRS were selected as control group. The difference of m6A gene expression between control group and sepsis group was analyzed by correlation test. The importance score of m6A-related genes in sepsis was obtained by cross-validation error of random forest tree method, disease-related characteristic genes were screened, the influence of core difference genes on sepsis incidence was analyzed, and nomogram was drawn to predict patient incidence. The number of disease characteristic genes was determined by LASSO model, ROC curve was drawn, and related genes were selected for further analysis. Cluster analysis was performed on sepsis patients according to the expression of biomarkers, and difference and correlation analysis were performed on immune infiltration. Among the first 13 differentially expressed genes, DIGFBP1 and IGFBP2 were up-regulated in sepsis patients, while METTL3, MITTL14, MERTTL16, RBM15, RBM15B, CBLL1, YTHF2, HNRNPC, LRPPRC, ELAVL1 and FTO were down-regulated in sepsis patients. In addition, ROC curve analysis showed that HNRNPC, LRPPRC, FTO andELAVL1 were characteristic genes of the disease. We also identified two m6A genotypes and two differential genotypes. Based on differential gene expression, nine m6A gene expressions were statistically different in a 2-typing pattern, with differences associated with immune infiltration. m6A methylation modification may play a potentially important role in the diagnosis,immune infiltration and treatment of sepsis in children. HNRNPC may be one of the potential molecular markers for predicting sepsis in children. Typing based on m6A gene expression has potential implications for the treatment of sepsis in children.
The Healthy Diet Basket is a comparable global standard for the Cost of a Healthy Diet, meeting nutritional and environmental criteria
Authors: Herforth Anna , Bai Yan , Venkat Aishwarya , Masters William
Published: June 2024

The Healthy Diet Basket (HDB) is a comparable standard of a healthy diet used to calculate the cost and affordability of a healthy diet (CoAHD), a new indicator of food security. Using food prices from 177 countries from the International Comparison Program, this study generates 2,039 least-cost healthy diets following the HDB, national food-based dietary guidelines (FBDG), and the EAT-Lancet reference diet. It compares the cost, nutritional, and environmental characteristics of these diets. The cost of the HDB averaged $3.32 in 2017, slightly lower than most FBDG. Macronutrients fell within the acceptable macronutrient distribution ranges, and the average mean adequacy ratio (MAR) of 15 micronutrients and protein was 94.2% for the HDB, close to the average MAR of 95.0% across FBDG. The HDB was closely aligned with WHO dietary recommendations. The carbon and water footprints of the HDB were equivalent to those of the EAT-Lancet reference diet.
Dynamic Contrast-Enhanced MRA of the aorta using a Golden-Angle Radial Sparse Parallel (GRASP) sequence: comparison with conventional time-resolved Cartesian MRA (TWIST)
Authors: Calastra Camilla , Kleban Elena , Helfenstein Fabrice , Haupt Fabian , Peters Alan Arthur , Huber Adrian , von Tengg-Kobligk Hendrik , Jung Bernd
Published: June 2024

Purpose: to compare the application of two contrast-enhanced time-resolved magnetic resonance angiography sequences on an aortic diseases patient cohort: the conventional Cartesian-sampling-based, TWIST sequence, and the radial-sampling-based GRASP sequence. Radial-sampling-based techniques are less sensitive to motion than cartesian sampling and consequently are expected to improve the image quality in body parts subjected to motion.
Methods: 1.5T magnetic resonance angiography data from thirty patients (60.9±16.1y.o.) were assessed to investigate image quality as well as spatial and temporal blurring in the ascending aorta (AA), descending aorta (DA) and abdominal aorta (AbA).
Results: GRASP offered superior depiction of vascular structures in terms of vascular contrast for qualitative analysis (TWIST, reader 1: 1.6±0.5; reader 2: 1.9±0.4; reader 3: 1.1±0.4; GRASP, reader 1: 1.5±0.5; reader 2: 1.4±0.5; reader 3: 1.0±0.2) and vessel sharpness for qualitative (TWIST, reader 1: 1.9±0.6; reader 2: 1.6±0.6; reader 3: 2.0±0.3; GRASP, reader 1: 1.4±0.6; reader 2: 1.2±0.4; reader 3: 1.3±0.6) and quantitative analysis (TWIST, AA=0.12±0.04, DA=0.12±0.03, AbA=0.11±0.03; GRASP, AA=0.20±0.05, DA=0.22±0.06, AbA=0.20±0.05). Streaking artefacts of GRASP were stronger visible compared to TWIST (TWIST, reader 1: 2.2±0.6; reader 2: 1.9±0.3; reader 3: 2.0±0.5; GRASP, reader 1: 2.6±0.6; reader 2: 2.3±0.5; reader 3: 2.8±0.6).
Conclusion: GRASP outperformed TWIST in SNR, vessel sharpness and reduction in image blurring; streaking artifacts were stronger visible with GRASP, but did not affect diagnostic image quality.
A novel Cu9S8 antibacterial based on magnetic chestnut shell biochar for the removal of sulfonamides in water environment: Differential adsorption and mechanism study
Authors: Li Rui-peng , Hu Zheng-rong , Wang Xing , Chen Jun , Liu Qing-qing , Zhao Ying , Zhao Zhong-bao , Lu Xu-lin , Zhang Zhi-wei
Published: June 2024

In this study, hollow nanoflower spherical Cu9S8 and Cu9S8/Fe3O4@BC with adsorption and antibacterial properties was prepared by coprecipitation and solvothermal method, respectively. The adsorption results showed that the Cu9S8 exhibited excellent adsorption performance on sulfonamide antibiotics (SAs), especially for sulfamethoxazole (SMZ). The highest adsorption capacity of SMZ on Cu9S8 was 33.4 mg/g within 120 min. The fitting results of adsorption and desorption kinetics and thermodynamics, as well as the conditions such as pH value and ionic strength were compared. It was found that different interactions led to the differential adsorption of SAs by Cu9S8. The desorption experiment further elucidated its adsorption mechanism. The large desorption capacity indicates that SAs on Cu9S8 can be further recovered and treated. The auto-deposition characteristics of Cu9S8 and the hysteresis loop of Cu9S8/Fe3O4@BC were studied to effectively recover Cu9S8 from aquatic environments. Additionally, more than 99% of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coil) were exterminated by Cu9S8 and Cu9S8/Fe3O4@BC within 20 min. The above results suggested that the hollow nanoflower spherical Cu9S8 and Cu9S8/Fe3O4@BC composite materials can provide a new strategy for solving pollution problems and waste treatment.
Diversity and abundance of hopper complex in rice agroecosystems under natural farming
Authors: Sharma Aarushi , Sharma Pawan kumar , Sharma Prem chand , Sood Ajay k , Kumar Arun
Published: June 2024

Rice, a staple food for half of the world's population, faces various pest problems, of which hoppers complex, infests all crop stages posing significant threat to rice production in many parts of India. Field surveys conducted in low and mid hills of Himachal Pradesh identified nine hopper species across five localities, with Cofana spectra exhibiting highest relative abundance and emerging as the eudominant species in Zone I, and dominant in Zone II followed by Sogatella furcifera and Nephotettix nigropictus. The species diversity and evenness was more in Zone II, while Zone I boasted higher species richness. Peak species richness occurred during heading, with maximum diversity and evenness being observed at tillering stage. Population dynamics fluctuated across growth stages, with hopper count in 2022 being notably higher particularly in Shahpur. S. furcifera peaked with 8.00 hoppers/5 sweeps during tillering, N. nigropictus with 6.50 hoppers/5 sweeps during heading, and C. spectra with 11.31 hoppers/5 sweeps during the heading stage. Temperature strongly influenced the hoppers activity, with S. furcifera primarily associated with maximum temperature, and N. nigropictus and C. spectra with minimum temperature and rainfall. This study provides essential insights for effective pest management in rice cultivation under natural farming conditions in Himachal Pradesh.
Building Climate Resilient Health Systems: Panacea for Mitigating Climate Change Effects in Nigeria
Authors: Schrage Pia , Adeyanju Gbadebo Collins
Published: June 2024

Background
Climate change has devastating effects on human health as well as the functioning and effectiveness of health systems, because it acts as a multiplier of existing stressors, intensifying pressure and exposing vulnerabilities. In the Sub-Saharan Africa region, Nigeria is projected to suffer from a variety of detrimental effects of climate change, leading to poor population health outcomes. Since 2007, climate change effects have led to over 800,000 deaths and affects the life expectancy of over 26 million people annually. Her health system is considered most vulnerable to the effects of climate change due to the accumulation of its vulnerability, leading to food insecurity, extreme weather and spread of diseases. Building climate resilience health system is key to combating the effects on health, hence the goal of this study.
Methods
The method design was qualitative using Key Informant Interviews. Participants were purposively included through a criterion-based snowball sampling approach. They were recruited through referrals and search on “LinkedIn” based on predefined inclusion criteria. A total of eighteen participants were recruited: representing government, civil society organizations and academia. Data were collected using a semi-structured interview guide and audio recorded using the Zoom online communication software. Data were analyzed deductively and inductively using MAXQDA software.
Results
Although adequate knowledge of the effects of climate change on health was noticeable such as heat wave, drought, flooding, irregular rainfall, climate-induced spread of diseases. However, there were: absence of consideration for climate risks and vulnerability in the health policies and plans; mitigation of climate change effects was not articulated in the health policies or programs; inadequate knowledge of and capacity to support climate resilience health system; climate-informed or resilient health policies and programs are not priority in view of other equally competing healthcare challenges. Other outcomes included insufficient funding, inadequate trained healthcare workers, overburdened healthcare system, knowledge gap between the scientific and policymaking communities.
Conclusion
Climate change is a multiplier of current health system stressors. Therefore, building climate resilient health system is as a firewall against those stressors long-term. A climate resilient health system is cost-effective, but the up-front investments need to be made now.
Exploring the Challenges Faced by Tertiary Students in Developing Formal Presentation Skills and Possible Solutions in an EFL Context
Authors: Hassan S. M. Razib , Roy Sukanto
Published: June 2024

This research aims to identify Bangladeshi undergraduates’ weaknesses in formal presentations and to discern feasible ways to enhance their formal presentation skills. The study is both quantitative and qualitative in nature where the data were collected through the questionnaire responses of 311 randomly selected Bangladeshi undergraduates, the formal presentations observations of 140 randomly selected Bangladeshi undergraduates, and the semi-structured interviews of 18 randomly selected faculty members and employers. Results show that the tertiary level learners of Bangladesh perform poorly in formal presentations mainly because they do not know how to consolidate an argument, and they do not know how to communicate with the audience. The paper recommends as well how tertiary students can sincerely communicate something valuable when they know and believe what they want to say, and they know the audience and care about them.
The effect of geomorphic and anthropogenic factors on the karst spring occurrence (case studies of central Zagros Mountain Range, Iran)
Authors: Ghadimi Mehrnoosh , Esmaili Samaneh , Hosseini Seyedmoosa , Kiani Mohammadali
Published: June 2024

Karst groundwaters are vulnerable and essential resources that require comprehensive management for protection and preservation. For this purpose, awareness of effective factors are required for the development of karst water resources and their quality management. Identifying the spatial distribution of springs in karst settings is important for a better understanding of groundwater flow because springs are the terminal sites of karst flow networks which are understudied. This study aims to identify the location of karst spring occurrence with an emphasis on geomorphic factors using the Analytical Hierarchy Process (AHP) and Logistic Regression (LR) model. As the case studies in this research, the Lordegan and Shahrekord karst basins located in Iran’s Zagros Mountains were selected. Nine factors influencing spring occurrence are considered and classified into four major groups: geological layer (lithology and distance from fault), hydrology layer (distance from river and drainage density), geomorphological layer (slope, aspect, elevation, and plan curvature), and anthropogenic layer (land use/land cover). The potential map of karst groundwater spring weighed by AHP was classified into five classes (very low, low, moderate, high, and very high) and both basins were in very high to moderate class. The geological layer (i.e., lithology and distance from faults) was the most significant geomorphological factor in the Lordegan basin, with the weight of 56.3%, whereas the topographical layer (i.e., slope, aspect, elevation, and curvature) was in the Shahrekord basin, with the weight of 38.4%. Due to the high-altitude of the studied basins (1944 to 3297 m), the land use/land cover layer had the lowest weight. According to the AHP results, 76.9% of the springs in the Lordegan basin and 60% in the Shahrekord basin are in the very high class spring groundwater potential zone. The LR model was also used to simulate the appearance of springs. The Relative Operating Characteristics (ROC) of the LR model in the Lordegan and Shahrekord basins were 0.9 and 0.85, respectively. Also, the LR results show that 38.4% of the springs in the Lordegan basin and 60% of the springs in the Shahrekord basin are in the very high class spring groundwater potential zone.
WITHDRAWN: Rare metal mineralization and geochemical characterization of El Mansouri Ring Complex, Northern Arabian Nubian Shield: Implications for petrogenesis and tectonic setting
Authors: SALEH Gehad M. , EMAD Baaha M. , NASR T.
Published: June 2024

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Exact Solution of Vinti Orbital Motion
Authors: Shepperd Stanley
Published: June 2024

The Elliptic Integrals of the Vinti analytic satellite orbital motion theory are converted to a form suitable for computer evaluation. This advance will facilitate closed-form Vinti algorithms that are more compact, more accurate (i.e. exact to machine accuracy), and valid over a wider range of orbits than series expansion techniques.
The Impact of Hyperbaric Oxygen Therapy Combined with High-Intensity Interval Training on Pulmonary and Diaphragmatic Function in Sedentary Young Adults
Authors: Luo Yu , Yang Fangjuan , Ma Tian , Guo Junxia , Ren Zhe , Wu Hao
Published: June 2024

Background: Hyperbaric oxygen (HBO) provides significant adjunctive benefits in treating various diseases. However, some studies suggest that HBO may impair pulmonary function. A sedentary lifestyle contributes to declines in both pulmonary and diaphragmatic functions, while physical activity might mitigate these effects. This study aims to explore the combined effects of HBO and high-intensity interval training (HIIT) on pulmonary and diaphragmatic functions in sedentary young adults.
Methods: Fifty-four sedentary young adults (27 males, 27 females) were randomly assigned to one of three groups: the hyperbaric oxygen intervention group (HBO group, n=18), the high-intensity interval training group (HIIT group, n=18), and the combined hyperbaric oxygen and high-intensity interval training group (HBO-HIIT group, n=18). Pulmonary and diaphragmatic functions were assessed using specific metrics before and after an 8-week intervention.
Results: Significant differences in forced expiratory volume in one second (FEV1), peak inspiratory flow (PIF), and diaphragm thickness during inspiration (DT-Edi) were observed across all three groups pre- and post-intervention (P < 0.05). The HBO-HIIT group exhibited significant improvements in pulmonary function metrics and DT-Edi compared to the HBO group (P < 0.05 for all metrics). Moreover, the HBO-HIIT group showed substantial differences in PIF and DT-Edi compared to the HIIT group (P < 0.05 for all). The HIIT group displayed significant improvements in forced vital capacity (FVC) and maximum expiratory pressure (MEP) compared to the HBO group (P < 0.05).
Conclusion: This study demonstrates that HBO intervention does not impair pulmonary function. Combining HBO with HIIT significantly enhances pulmonary and diaphragmatic functions in sedentary young adults, with superior results to either intervention alone.
LeafGenEx-A Novel Method for Generating Healthy and Diseased Wheat Leaf Images using CycleGAN
Authors: Patel Jigna , Pachchigar Aditya , Patel Jitali
Published: June 2024

LeafGenEx, an innovative approach to wheat leaf disease detection, uses data augmentation, deep learning, and explainable AI to improve disease detection accuracy. The procedure starts with preprocessing methods, such as image flipping, rotation, and cropping, to extend the original dataset. Segmentation is eventually carried out utilising a pre-trained ResNet network and GradCAM, allowing for exact identification of disease-affected regions. An upgraded CycleGAN model is used to produce synthetic images of healthy and diseased leaves, yielding a higher Fréchet Inception Distance (FID) score than previous DCGAN and CycleGAN models. The generated images are combined with the original dataset to form a comprehensive dataset for training a deep learning detection model. To categorise leaf images according to their different diseases, the authors use a method based on transfer learning with InceptionV3. GradCAM, an explainable AI approach, is used to evaluate the deep learning model's results and determine the most important leaf sections for disease detection. LeafGenEx's effectiveness is proved by its capacity to generate high-quality synthetic images, improve disease detection accuracy, and produce interpretable data, making it an important tool for precision agriculture and early disease intervention.
“I will fight tooth and nail for my recovery”: A typology of individuals in long-term recovery from addiction
Authors: Elbaz Ayala , Gueta Keren , Ronel Natti
Published: June 2024

Recovery from addiction is a complex process that involves changes in an individual’s environment, behavior patterns, and self-perception. Long-term recovery (LTR) denotes enduring changes that occur over a period of five years or longer. While previous research has focused mainly on the typology of substance users, the present study sought to establish the typology of individuals in LTR from the perspective of various stakeholders. Accordingly, using a qualitative phenomenological approach, it examined the perceptions of individuals who have recovered from substance and behavioral addictions (n = 30), family members (n = 8), and professional therapists (n = 9), to gain a diverse and integrated perspective of LTR. To this end, participants were recruited from a therapeutic community, outpatient clinics, and NA fellowships, and took part in a semi-structured, in-depth interview. Findings suggest there are five distinct types of individuals in LTR, that we have dubbed the Fighter, the Avoidant, the Wanderer, the Devout, and the Comrade. These five types are differentiated by three primary parameters: identity, recovery goals, and central recovery strategies. Based on these findings, it appears that this recovery identity serves as a transitional stage, that helps individuals resume their typical course of action in sustained recovery once it becomes more stable. This typology highlights the multifaceted nature of the addiction recovery phenomenon, and incorporates distinct insights from previous research about identity changes and recovery strategies, by presenting them as distinct recovery types. Therapeutic interventions at various stages of recovery may utilize this typology to tailor treatment to the unique needs of individual clients.
A method for size estimation of bearing faults from vibration signals based on denoising, envelope and WPD
Authors: Muñoz Manuel , Vicuña Cristian , Leaman Félix
Published: June 2024

An efficient fault prognosis for bearings remains still as an open challenge within the industry. Bearing damage is primarily derived from wear or surface fatigue in rotational machinery. This damage especially at early stages , is difficult to characterize due to the weakness of the vibration signal and external interferences, which is why advanced signal processing is required. To tackle this challenge, this study introduces the DEW method, a combination of Wavelet Denoising, Envelope, and Wavelet Packet Decomposition, to estimate the size of a bearing fault located in inner and/or outer races. This method is validated with a dataset of varying rotational speeds, loads, and fault sizes obtained from open-access sources. The application of the method enabled the estimation of a confidence interval for fault size under different conditions. Despite some observed inconsistencies, the method showed more accurate results with increased load, fault size, or decreased speed. In the case of simulated signals , good results were achieved even in scenarios with up to 10 [dB] of signal-to-noise ratio. However, for the evaluation with the dataset, this estimation proved insufficient due to the amount of noise present, which attenuated the components of interest, especially the input peak.
Constructing a prognostic model based on MPT-related genes and investigate the characteristics of immune infiltration in bladder cancer
Authors: Yang Lei , Zhang Zhiqiang , Xu Mengfan , Shang Muhan , Wang Haibing
Published: June 2024

Purpose: Exploring the expression of Mitochondrial Permeability Transition Dependent Necrosis lncRNAs (MPTDNLs) in bladder cancer and elucidate their precise function within the tumor microenvironment and impact on prognosis.
Methods: We employed a comprehensive bioinformatics approach to investigate MPTDNLs in bladder cancer. Gene expression data, clinical data, and mutation data of bladder cancer were obtained from TCGA database.
Results: We developed a new prognostic model incorporating 6 lncRNAs. The predictive efficacy of this model for bladder cancer prognosis was validated. Furthermore, through this prognostic model, we investigated the influence of MPTDNLs on the tumor microenvironment and drug sensitivity.
Conclusion: This study presents a novel prognostic framework for bladder cancer that holds great potential for enhancing prognostic prediction accuracy and optimizing treatment strategies for patients with this disease.
Impacts of Anxiety Levels and Personality Traits on Patient Cooperation during Small Incision Lenticule Extraction (SMILE): A Nested Case-Control Study
Authors: Li Ao-Ling , Li Jing , Pu Qi , Guo Xiao-Xiao , Chang Xue-Jiao , Li Xin-Yu
Published: June 2024

Background
Small incision lenticule extraction (SMILE) surgery conducted for the correction of myopia and astigmatism exhibits excellent safety, efficacy, and predictability. However, poor intraoperative cooperation may lead to various adverse outcomes, including ablation decentration, suction loss, and incision tear. Moreover, it is difficult for surgeons to predict the occurrence of poor cooperation prior to the surgery. In this context, the present study aimed to analyze the impact of anxiety and personality traits on cooperation during SMILE surgery to assist surgeons in identifying patients at high risk for poor cooperation.
Methods
A nested case-control study was conducted at Tongji Hospital, Huazhong University of Science and Technology, between June 2022 and August 2022. Participants were categorized as those exhibiting excellent or poor cooperation based on their performance during surgery. Anxiety levels were quantified using the State Anxiety Inventory (STAI-S) and Trait Anxiety Inventory (STAI-T). Personality traits were evaluated using the four subscales of the Eysenck Personality Questionnaire (EPQ-RSC), namely, psychoticism (P-scale), extraversion (E-scale), neuroticism (N-scale), and lie scale (L-scale).
Results
The incidence rates were higher for the first-eye procedure compared to the second-eye procedure. The anxiety levels demonstrated an initial trend of increase followed by a decrease, both prior to and after the surgery (P < 0.05). The poor cooperation group presented higher STAI-S scores (P < 0.05) 30 min prior to surgery compared to the excellent cooperation group. Patients with poor cooperation during the procedures for both eyes exhibited higher anxiety levels compared to those with poor cooperation during just the first eye (STAI-S: 11.02 ± 3.05 vs 12.32 ± 3.0, P = 0.016; STAI-T: 10.30 ± 2.87 vs 11.89 ± 2.91, P = 0.002). The binary logistic regression analysis revealed that higher STAI-S and STAI-T scores were associated with a higher risk of poor cooperation (P < 0.05). In the neuroticism scale, scores above 61.5 were associated with a higher risk of poor cooperation (first-eye OR = 1.9; P < 0.05, second-eye OR = 2.395, P < 0.05) compared to scores below 38.5.
Conclusion
Patients with elevated anxiety levels and typical neurotic personality traits are more likely to exhibit poor cooperation during SMILE surgery.
Exploring the inherent resilience of health districts in a context of chronic armed conflict: a case study in Eastern DRCongo
Authors: Makali Samuel Lwamushi , Louis Patricia St , Karemere Hermès , Wautié Alice , Pavignani Enrico , Eboma Christian Molima , Bigirinama Rosine , Lembebu Corneille , Porignon Denis , Balaluka Ghislain Bisimwa , Donnen Philippe , Paul Elisabeth
Published: June 2024

Background
In South Kivu (Eastern Democratic Republic of the Congo (DRC), health districts (HDs) affected by chronic armed conflicts are devising coping mechanisms to continue offering healthcare services to the population. Nonetheless, this alone does not suffice to make them fully resilient to such conflicts. This study aims to explore the characteristics of these HDs resilience.
Methods
This study uses mixed methods and an extreme case study design to compare a HD with no history of armed conflict (Idjwi, case 1) and another one experiencing armed conflict (Fizi, case 2) in South Kivu. The Kruk et al. (2017) index was employed as a theoretical framework for exploring resilience characteristics. Qualitative data were collected through a literature review and semi-structured individual interviews with purposively sampled key stakeholders. They were subjected to deductive-inductive thematic analysis. Quantitative data were collated using a questionnaire (Likert scale) administered to stakeholders in the selected HDs using non- probabilistic methods. These data were subsequently analysed for comparative descriptive purposes.
Results
Recurring short-term shocks as well as chronic stress factors whether or not linked to chronic armed conflicts were identified. According to most respondents (> 98%), essential components of a resilient HDs were prior knowledge of the strengths and weaknesses as well as the public health risk posed by the crisis (Awareness); together with community and non-health actors’ involvement during the crisis (Integration). Common resilience mechanisms (e.g., epidemic management plan, crisis management committee) were identified, and Case 2 implemented additional mechanisms, including DRC armed forces involvement, community healthcare sites and mobile clinics, specific warning system, regular socio-demographic monitoring of displaced persons alongside promotion of activities for social cohesion strengthening.
Conclusions
For meaningful resilience to emerge, HDs need to be better resourced in 'normal' times. With this condition fulfilled, quality of care could improve and spare capacity could be created to withstand disturbances.
Deep Transfer Learning-based 3D super-resolution Radiomics modeling of CT to discriminate Brucella Spondylitis from Tuberculous Spondylitis: A multicenter, retrospective study
Authors: Wang Kaifeng , Qi Lixia , Zhang Tingxin , Li Jing , Zhang Meilan , Du Hai
Published: June 2024

To improve the accuracy in distinguishing between Tuberculosis Spondylitis (TBS) and Brucella spondylitis (BS) through the creation of radiomics deep Learning models. These models incorporate Deep Learning techniques and leverage CT image enhanced by Generative Adversarial Network-based Super-Resolution (GAN-SR).94 patients from Ordos Central and Second People's Hospitals diagnosed with BS or TBS. These patients were divided into a training set (n = 65) and a validation set (n = 29). We utilized conventional CT images to generate SR-CT with twice SR based on GANs-SR. The ROIs underwent manual segmentation, and extraction of Radiomics features, and ResNet18 and ResNet34 were used as Deep Learning models for training and DL feature extraction. Feature fusion and selected were performed, and four models were built based on MLP: clinical; radiomics (Rad); Deep Learning (DL) and combined models. The model efficacy was evaluated using ROC and DCA, etc. In terms of efficacy, the integrated model outperformed others, showing the highest AUC, with the DL model following closely behind. Notably, ResNet34 demonstrated superior performance over ResNet18, SR enhanced model performance across metrics for SR-CT compared to CT. The combination of Rad + ResNet34_SR achieved the best results, with AUC of 0.952, Sensitivity of 0.909, and Specificity of 0.941. DCA curve confirmed the model's clinical decision-making potential.In conclusion, our study creates a 3D Super-Resolution model based on SR-CT images using Deep Learning Radiomics to differentiate between TBS and BS, which is significantly enhanced compared to CT images.
Convolutional neural network-based detection of early-stage Parkinson’s disease using the six-minute walk test
Authors: Choi Hyejin , Youm Changhong , Park Hwayoung , Kim Bohyun , Hwang Juseon , Cheon Sang-Myung , Shin Sungtae
Published: June 2024

The heterogeneity of Parkinson’s disease (PD) generates significant challenges for accurate diagnosis, especially in early-stage disease, when symptoms may be very subtle. This study aimed to determine the accuracy of a convolutional neural network (CNN) technique based on a 6-min walk test (6MWT) using wearable sensors for distinguishing patients with early-stage PD (n = 78) from healthy controls (n = 50). Wearing six sensors, the participants performed the 6MWT, and the time-series data were converted into new images. The main results showed that the gyroscopic vertical component of the lumbar spine had the highest classification accuracy of 83.5%, followed by the thoracic spine (83.1%) and right thigh (79.5%) segment. These results suggest that the 6MWT and CNN models may pave the way for clinicians to diagnose and track PD symptoms earlier and thus provide timely treatment during the golden transition from geriatric to pathologic gait patterns.
Scoping Review: Emerging (Bio)markers for the Early Detection of Breast Cancer Recurrence
Authors: Sallauka Rigon , Horvat Matej , Ravnik Maja , Rashwan Hatem , Arioz Umut , Mlakar Izidor
Published: June 2024

Background The aim of this study is to gain a comprehensive understanding of the latest advancements in breast cancer recurrence markers, with the aim of identifying minimally invasive or minimally intrusive markers as necessary approach for screening for breast cancer recurrence.
Methods We followed PRISMA guidelines, systematically searching Web of Science, Scopus, and PubMed from 2010 to December 2023 for secondary papers on breast cancer markers of recurrence. Keywords used to search the databases include but are not limited to: “breast cancer recurrence”, “markers”, “radiology”, “pathology”, “clinical features”. The search was limited to English language. Selected papers underwent screening process according to inclusion/exclusion criteria, and data extraction included publication details, markers, marker modality, among others.
Results The number of papers considered for this review was 1,138. After two phases of screening process, a total number of 28 reviews were included in this scoping review. We have categorized markers into radiological, clinical, and histopathological types. Among the most relevant clinical markers correlated with breast cancer (BC) recurrence are clinical stage, carcinoembryogenic antigen (CEA), and cancer antigen 15.3 (CA 15.3). We have also identified that the following radiological markers are the most mentioned markers associated with recurrence: mammographic density (MD), tumor heterogeneity, most enhancing tumor volume (METV), radiomic features, and more. Furthermore, we identified nuclear grade, microenvironment heterogeneity, estrogen receptor (ER), androgen receptor (AR), human epidermal growth factor receptor 2 (HER2), Ki-67 antigen, as the most significant histopathological markers of breast cancer recurrence.
Conclusion This review identified promising markers for breast cancer recurrence in three categories: clinical, radiological and histopathological. General practitioners can leverage these insights for enhanced pre-screening, aiding in earlier detection and intervention, thus improving patient outcomes. Unclear cut-off values and disagreement on their use remain obstacles.
Transcriptomic analysis of SEL1L and HRD1 knockout cell lines reveals multifaceted roles of SEL1L beyond the ER quality control
Authors: Badawi Sally , Gariballa Nesrin , Kizhakkedath Praseetha , Ali Bassam R.
Published: June 2024

The endoplasmic reticulum (ER) orchestrates major cellular processes, including protein synthesis, folding, assembly and degradation, to maintain cellular proteostasis. Central to these processes are highly stringent quality control machineries like the ER-associated protein degradation (ERAD). Key players in ERAD include HRD1 and SEL1L, which target misfolded proteins for ubiquitination and facilitate their retro-translocation to the cytosol. Bi-allelic loss-of-function of HRD1 and SEL1L is considered lethal, with hypomorphic variants linked to human diseases, including neurodevelopmental disorders. Despite their well-known roles, a comprehensive transcriptomic characterization of their bi-allelic loss has been lacking. In this study, we employed CRISPR/Cas9 to generate bi-allelic HRD1-KO and SEL1L-KO HEK293 cell models. Through differential gene expression analysis and co-expression network construction, we identified hub genes and novel regulatory networks. HRD1-KO cells displayed enrichment solely in ER-related processes, suggesting its specific role in ER protein quality control. Conversely, SEL1L-KO cells exhibited a broader impact, affecting mitochondrial function, ERAD-ribosomal quality control interactions, ER-Golgi transport, and Wnt signaling pathway. These results highlight the distinct roles of HRD1 and SEL1L in ERAD. By unraveling their whole transcriptome impact, our study sheds light on their potential involvement in diverse cellular processes, potentially enhancing our understanding of their cellular processes and disease mechanisms.
N-acetylcysteine Supplementation Improves Endocrine-Metabolism Profiles and Ovulation Induction Efficacy in Polycystic Ovary Syndrome
Authors: Fang Yu-Qing , Ding Hui , Li Tao , Zhao Xiao-Jie , Luo Dan , Liu Yi , Li Yan-Hui
Published: June 2024

Background
Polycystic ovary syndrome (PCOS) affects 6–20% of women worldwide, with insulin resistance and hyperinsulinemia occurring in 50%-70% of patients. Hyperinsulinemia exacerbates oxidative stress, contributing to PCOS pathogenesis. N-acetylcysteine (NAC) is an antioxidant and insulin sensitizer that shows promise as a therapeutic for PCOS. Our current study aimed to investigate the effects of NAC supplementation on endocrine-metabolic parameters in PCOS mice and its effect on ovulation induction (OI) efficacy in women with PCOS.
Methods:
Female C57BL/6 mice were orally administered letrozole (LE) to induce PCOS and then randomly divided into groups receiving daily oral administration of 160 mg/kg NAC (PCOS + NAC group), 200 mg/kg metformin (PCOS + Met group), or 0.5% carboxymethyl cellulose (drug solvent) (pure PCOS group) for 12 days. Healthy female mice served as pure controls. Estrous cycles were monitored during the intervention. Metabolic and hormone levels, ovarian phenotypes, antioxidant activity in ovarian tissues, and oxidative stress levels in oocytes were assessed postintervention. This pragmatic, randomized, controlled clinical study included 230 women with PCOS who were randomly assigned to the NAC group (1.8 g/day oral NAC, n = 115) or the control group (n = 115). Patients in both groups underwent ≤ 3 cycles of OI with sequential LE and urinary follicle-stimulating hormone (uFSH). Cycle characteristics and pregnancy outcomes were compared between groups.
Results
Similar to metformin, NAC supplementation significantly improved the estrous cycles and ovarian phenotypes of PCOS mice; reduced the LH concentration, LH/FSH ratio, and T level; and increased glucose clearance and insulin sensitivity. Notably, NAC significantly reduced oocyte ROS levels and increased the mitochondrial membrane potential in PCOS mice. Additionally, NAC significantly enhanced enzymatic and nonenzymatic antioxidant activities in PCOS mouse ovaries, whereas metformin had no such effect. In the clinical trial, compared to women in the control group, women receiving NAC had significantly lower average uFSH dosage and duration (p < 0.005) and significantly greater clinical pregnancy rates per OI cycle and cumulative clinical pregnancy rates per patient (p < 0.005).
Conclusion
NAC supplementation improved endocrine-metabolic parameters in PCOS mice and significantly enhanced OI efficacy with sequential LE and uFSH in women with PCOS. Therefore, NAC could be a valuable adjuvant in OI for women with PCOS.
Oral Nonabsorbable Antibiotics for Prevention of Recurrent Cholangitis; a Brief Report Study
Authors: Fortun Jesus , Rodríguez-Gandía Miguel Angel , Pintado Vicente , MartÍn-Dávila Pilar , García-González Miguel , Graus Javier , Martín-Mateos Rosa , Fuente Javier Saez-de la , Muriel Alfonso , Moreno Santiago
Published: June 2024

Background
Patients with recurrent cholangitis are at risk of developing life-threatening sepsis. Selective decontamination of the digestive tract (SDD) involving oral nonabsorbable antibiotics has been primarily applied to children undergoing Kasai portoenterostomy surgery.
Methods
In this study, SDD containing colistin, tobramycin, and nystatin was administered to eight patients with recurrent cholangitis, and the incidence density before and after SDD administration was analyzed.
Results
The overall incidence density of cholangitis requiring hospital admission was 0.37 per 100 patient days during the SDD period and was significantly lower than observed before SDD administration (1.05 per 100 patient days) [RR: 0.35 (95% CI: 0.21–0.59); p: <0.001, two-sided]. This was not associated with an increased risk of resistance during SDD administration.
Conclusion
In this study SDD reduced by 65% the frequency and severity of recurrent cholangitis. In addition, this procedure is patient-friendly and microbiologically safe.
Study on Monitoring Spinal Cord Blood Flow During Spinal Osteotomy Using a Laser Speckle Imaging System
Authors: Ren Zheng , Wang Jing , Guo Le , Ye Xiaolong , Xu Chang , Ma Yuan
Published: June 2024

Objective: This study aims to utilize Laser Speckle Imaging (LSI) technology to thoroughly monitor and analyze the changes in spinal cord hemodynamics in rabbits undergoing Posterior Thoracolumbar Spinal Osteotomy (PTSO) surgery.
Methods: Initially, we prepared the model for posterior thoracolumbar spine osteotomy.Subsequently, rabbits underwent monitoring using a laser speckle imaging system to document the different stages of spinal shortening,encompassing pre-osteotomy, post-osteotomy, post-shortening, and dural removal.
Results: After statistical analysis, the blood perfusion volume of posterior spinal artery before and after osteotomy was significantly different (t=7.413, p=0.001), 95%CI (147.8-280.22). The blood perfusion volume of posterior spinal artery was significantly different before and after osteotomy (t=4.111, p=0.001), 95%CI (55.39 ~ 164.74). There were significant differences in posterior spinal artery perfusion before osteotomy and after dural removal (t=10.472, p=0.001), 95%CI (226.6-336.39). The blood perfusion volume of posterior spinal artery after osteotomy was significantly different from that after osteotomy shortening (t=-6.949, p=0.001), 95%CI (-66.34-6.949). The blood perfusion volume of posterior spinal artery after bone amputation was significantly different from that after dural removal (t=8.167, p=0.001), 95%CI (58.10 ~ 96.85). There were significant differences in posterior spinal artery perfusion between the patients with bone truncation and the patients with dural removal (t=13.227, p=0.001), 95%CI (144.96-197.90).
Conclusion: Spinal cord blood flow can be utilized as a monitoring indicator for early prediction of spinal cord injury, while maintaining stable spinal cord blood flow may be a crucial factor in reducing spinal cord damage.
Mortality trends for colorectal cancer during the COVID-19 pandemic in the US
Authors: Mattiuzzi Camilla , Lippi Giuseppe
Published: June 2024

It can be assumed that a reduction in patient access to colorectal cancer screening and early management during the coronavirus disease 2019 (COVID-19) pandemic could have generated a negative impact on subsequent diagnoses and survival probabilities. We report here the recent statistics on colorectal cancer-related deaths in the US. We searched the CDC online database WONDER database, which reports mortality data for the entire country, using specific ICD-10 codes for colorectal cancer (from C18 to C20). The age-adjusted death rate ×100,000 for colorectal cancer displayed a gradual decrease from 2018 (13.06) to 2019 (12.76) and 2020 (12.55), but then reversed in 2021, when the age-adjusted death rate increased to 12.94, decreasing to 12.58 in 2022 and increasing again to 12.75 in 2023. The results of our analysis suggest that the COVID-19 pandemic has likely had a negative impact on early mortality from colorectal cancer, as shown by the significant increase in the age-adjusted death rate recorded in 2021.
A Novel Outlier-Robust Accuracy Measure for Machine Learning Regression Based on Hassanat Distance Metric
Authors: Hassanat Ahmad , Alqaralleh Mohammad Khaled , Tarawneh Ahmad S. , Almohammadi Khalid , Alamri Maha , Alzahrani Abdulkareem , Altarawneh Ghada A. , Alhalaseh Rania
Published: June 2024

Regression, a supervised machine learning approach, establishes relationships between independent variables and a continuous dependent variable. It is widely applied in areas like price prediction and time series forecasting. The performance of regression models is typically assessed using error metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). However, these metrics present challenges including sensitivity to outliers (notably MSE and RMSE) and scale dependency, which complicates comparisons across different models. Additionally, traditional metrics sometimes yield values that are difficult to interpret across various problems. Consequently, there is a need for a metric that consistently reflects regression model performance, independent of the problem domain, data scale, and outlier presence. To overcome these shortcomings, this paper introduces a new regression model accuracy measure based on Hassanat distance metric. This measure is not only invariant to outliers but also easy to interpret as it provides an accuracy-like value that ranges from 0 to 1 (or 0-100\%). We validate the proposed metric against traditional measures across multiple benchmarks, demonstrating its robustness under various model scenarios and data types. Hence, we suggest it as a new standard for assessing regression models' accuracy.
Compressive strength prediction of basalt fiber reinforced concrete based on Interpretive Machine Learning
Authors: wang xuewei , Ke Zhijie , liu wenjun , Zhang peiqiang , cui Sheng’ai , zhao Ning
Published: June 2024

The compressive strength prediction of Basalt Fiber Reinforced Concrete (BFRC) is a complex task influenced by numerous factors. For traditional empirical formula methods, difficulties such as the limited number of experiments and the time-intensive nature of the process may hinder the accurate prediction of the compressive strength. The compressive strength of BFRC was predicted using a machine learning approach, considering various combinations of characteristics, and the predictive ability of the model was verified using experimental data. A database of 309 sets of BFRC compressive strength data was assembled, and eight sets of BFRC compressive strength experimental data were experimentally obtained. After the hyperparameter optimization four machine learning models were employed to investigate their performances. Combined with the SHAP algorithm, an interpretive analysis of the input parameters of the XGBoost model was specifically conducted, and the predictive ability and interpretability of the model were verified using experimental data. The research results indicated that the XGBoost model surpasses the other three machine learning models in terms of prediction accuracy, achieving an R2 value of 0.9431, RMSE of 3.2325, and MAE of 2.3355. The SHAP analysis revealed that among the basalt fiber (BF) parameters, the volume content of BF had the most significant impact on the XGBoost model output. Furthermore, the optimal range of volume content is 0.1%, the optimal range of diameter is 15–20 µm, and the optimal range of length is 8–15 mm.