bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the soft tissue facial profile in different skeletal malocclusions in relation to age
Authors: Kiełczykowski Michał , Perkowski Konrad , Kamiński Konrad , Zadurska Małgorzata , Czochrowska Ewa 
Published: June 2024

Abstract
Background
The aim of the study was to assess the thickness of the soft tissue facial profile (STFP) in relation to the skeletal malocclusion, age and gender.

Methods
All patients, aged 7–35 years, who were seeking orthodontic treatment at the Department of Orthodontics, Medical University of Warsaw between 2019 and 22 were included in the study. All patients had lateral head radiographs taken before the treatment. The cephalometric analysis was performed including the STFP analysis. The patients were allocated to one of six groups based on age and skeletal relations (ANB angle). The minimum number of patients in each group was 60 with equal gender distribution. The STFP analysis included ten linear measurements.

Results
A total of 300 patients were included in the study and allocated to five groups. Group 6 (growing patients with skeletal Class III malocclusion) was not included in the study as it failed to achieve the assumed group size. There were significant differences in the thickness of the STFP in relation to the skeletal malocclusions. Adults with skeletal Class III malocclusion had significantly thicker subnasal soft tissues compared to patients with skeletal Class I and Class II malocclusions. The thickness of the lower lip in patients with Class II skeletal malocclusion was significantly bigger compared to the other groups. Children and adolescents with Class II malocclusions had thicker lower lip in comparison to the group with Class I malocclusion. The majority of the STFP measurements were significantly smaller in children and adolescents compared to adults. The thickness of the STFP in males was significantly bigger in all age groups compared to females.

Conclusions
The thickness of facial soft tissues depends on the patient’s age and gender. The degree of compensation of the skeletal malocclusion in the STFP may be a decisive factor during orthodontic treatment planning regarding a surgical approach or a camouflage treatment of skeletal defects.
“I feel like I’m walking on eggshells”: a qualitative study of moral distress among Chinese emergency doctors
Authors: Liu Jiajun , Dai Fengling , Song Qitai , Sun Jian , Liu Yao 
Published: June 2024

Abstract
Background
While the number of emergency patients worldwide continues to increase, emergency doctors often face moral distress. It hampers the overall efficiency of the emergency department, even leading to a reduction in human resources.

Aim
This study explored the experience of moral distress among emergency department doctors and analyzed the causes of its occurrence and the strategies for addressing it.

Method
Purposive and snowball sampling strategies were used in this study. Data were collected through in-depth, semi-structured interviews with 10 doctors working in the emergency department of a tertiary general hospital in southwest China. The interview data underwent processing using the Nvivo 14 software. The data analysis was guided by Colaizzi’s phenomenological analysis method.

Study findings
This study yielded five themes: (1) imbalance between Limited Medical Resources and High-Quality Treatment Needs; (2) Ineffective Communication with Patients; (3) Rescuing Patients With no prospect of treatment; (4) Challenges in Sustaining Optimal Treatment Measures; and (5) Strategies for Addressing Moral Distress.

Conclusion
The moral distress faced by emergency doctors stems from various aspects. Clinical management and policymakers can alleviate this distress by enhancing the dissemination of emergency medical knowledge to the general public, improving the social and economic support systems, and strengthening multidisciplinary collaboration and doctors’ communication skills.
Nursing students’ willingness to respond in disasters: a cross sectional study of facilitators and barriers
Authors: Tayebi Zahra , Norouzinia Roohangiz , Moatadelro Zahra , Pour Ashkan Farokhi , Nourian Bahar 
Published: June 2024

Abstract
Introduction
The preparedness of the healthcare system to address emergency situations is contingent on the inclination of healthcare personnel. Nursing students can serve as valuable resources to supplement the workforce during major incidents and disasters. This study investigated the facilitators and barriers of nursing students’ willingness to respond to disasters at the Alborz University of Medical Sciences in 2022.

Methods
In this cross-sectional descriptive study, 234 nursing students were recruited using convenience sampling. A deductive-inductive questionnaire was developed and distributed through an online self-administered survey comprising demographic information and questions on barriers, facilitators, various disaster scenarios, preferred activities, and reasons for pursuing a nursing career.

Results
The mean willingness scores of nursing students in response to various disasters were as follows: 3.15 for natural disasters, 2.60 for man-made disasters, 2.94 for pandemics, and 3.32 overall. Among the disaster scenarios, the earthquake response obtained the highest willingness score, while infectious disease epidemics received the lowest score. The most and least willingness to perform activities during disaster response were related to bedside care and participation in patients’ personal hygiene, respectively. Key determinants of participation included the possibility of immunization and concerns for family safety.

Conclusion
The findings indicated that nursing students are generally willing to assist as members of the healthcare team during disasters. However, the willingness to respond to infectious disease epidemics and man-made disasters was below the norm. Concerns about family health and the risk of disease transmission were identified as primary barriers. Addressing these concerns is crucial to enhance nursing students’ participation in disaster response.
Comparative genomics of the primary endosymbiont Buchnera aphidicola in aphid hosts and their coevolutionary relationships
Authors: Liang Yukang , Dikow Rebecca B. , Su Xu , Wen Jun , Ren Zhumei 
Published: June 2024

AbstractBackgroundCoevolution between modern aphids and their primary obligate, bacterial endosymbiont,Buchnera aphidicola, has been previously reported at different classification levels based on molecular phylogenetic analyses. However, theBuchneragenome remains poorly understood within theRhusgall aphids.ResultsWe assembled the complete genome of the endosymbiontBuchnerain 16 aphid samples, representing 13 species in all six genera ofRhusgall aphids by shotgun genome skimming method. We compared the newly assembled genomes with those from GenBank to comprehensively investigate patterns of coevolution between the bacteriaBuchneraand their aphid hosts.Buchneragenomes were mostly collinear, and the pan-genome contained 684 genes, in which the core genome contained 256 genes with some lineages having large numbers of tandem gene duplications. There has been substantial gene-loss in eachBuchneralineage. We also reconstructed the phylogeny forBuchneraand their host aphids, respectively, using 72 complete genomes ofBuchnera, along with the complete mitochondrial genomes and three nuclear genes of 31 corresponding host aphid accessions. The cophylogenetic test demonstrated significant coevolution between these two partner groups at individual, species, generic, and tribal levels.ConclusionsBuchneraexhibits very high levels of genomic sequence divergence but relative stability in gene order. The relationship between the symbiontsBuchneraand its aphid hosts shows a significant coevolutionary pattern and supports complexity of the obligate symbiotic relationship.
EEG signatures of cognitive decline after mild SARS-CoV-2 infection: an age-dependent study
Authors: Sun Yike , Sun Jingnan , Chen Xiaogang , Wang Yijun , Gao Xiaorong 
Published: June 2024

Abstract
Background
Current research on the neurological impact of SARS-CoV-2 primarily focuses on the elderly or severely ill individuals. This study aims to explore the diverse neurological consequences of SARS-CoV-2 infection, with a particular focus on mildly affected children and adolescents.

Methods
A cohort study was conducted to collect pre- and post-infection resting-state electroencephalogram (EEG) data from 185 participants and 181 structured questionnaires of long-term symptoms across four distinct age groups. The goal was to comprehensively evaluate the impact of SARS-CoV-2 infection on these different age demographics. The study analyzed EEG changes of SARS-CoV-2 by potential biomarkers across age groups using both spatial and temporal approaches.

Results
Spatial analysis indicated that children and adolescents exhibit smaller changes in brain network and microstate patterns post-infection, implying a milder cognitive impact. Sequential linear analyses showed that SARS-CoV-2 infection is associated with a marked rise in low-complexity, synchronized neural activity within low-frequency EEG bands. This is evidenced by a significant increase in Hjorth activity within the theta band and Hjorth mobility in the delta band. Sequential nonlinear analysis indicated a significant reduction in the Hurst exponent across all age groups, pointing to increased chaos and complexity within the cognitive system following infection. Furthermore, linear regression analysis based on questionnaires established a significant positive relationship between the magnitude of changes in these neural indicators and the persistence of long-term symptoms post-infection.

Conclusions
The findings underscore the enduring neurological impacts of SARS-CoV-2 infection, marked by cognitive decline and increased EEG disarray. Although children and adolescents experienced milder effects, cognitive decline and heightened low-frequency electrical activity were evident. These observations might contribute to understanding potential anxiety, insomnia, and neurodevelopmental implications.
Radiomics based on HRCT can predict RP-ILD and mortality in anti-MDA5 + dermatomyositis patients: a multi-center retrospective study
Authors: He Wenzhang , Cui Beibei , Chu Zhigang , Chen Xiaoyi , Liu Jing , Pang Xueting , Huang Xuan , Yin Hongkun , Lin Hui , Peng Liqing 
Published: June 2024

Abstract
Objectives
To assess the effectiveness of HRCT-based radiomics in predicting rapidly progressive interstitial lung disease (RP-ILD) and mortality in anti-MDA5 positive dermatomyositis-related interstitial lung disease (anti-MDA5 + DM-ILD).

Methods
From August 2014 to March 2022, 160 patients from Institution 1 were retrospectively and consecutively enrolled and were randomly divided into the training dataset (n = 119) and internal validation dataset (n = 41), while 29 patients from Institution 2 were retrospectively and consecutively enrolled as external validation dataset. We generated four Risk-scores based on radiomics features extracted from four areas of HRCT. A nomogram was established by integrating the selected clinico-radiologic variables and the Risk-score of the most discriminative radiomics model. The RP-ILD prediction performance of the models was evaluated by using the area under the receiver operating characteristic curves, calibration curves, and decision curves. Survival analysis was conducted with Kaplan-Meier curves, Mantel-Haenszel test, and Cox regression.

Results
Over a median follow-up time of 31.6 months (interquartile range: 12.9–49.1 months), 24 patients lost to follow-up and 46 patients lost their lives (27.9%, 46/165). The Risk-score based on bilateral lungs performed best, attaining AUCs of 0.869 and 0.905 in the internal and external validation datasets. The nomogram outperformed clinico-radiologic model and Risk-score with AUCs of 0.882 and 0.916 in the internal and external validation datasets. Patients were classified into low- and high-risk groups with 50:50 based on nomogram. High-risk group patients demonstrated a significantly higher risk of mortality than low-risk group patients in institution 1 (HR = 4.117) and institution 2 cohorts (HR = 7.515).

Conclusion
For anti-MDA5 + DM-ILD, the nomogram, mainly based on radiomics, can predict RP-ILD and is an independent predictor of mortality.
Chronic obstructive pulmonary disease affects outcome in surgical patients with perioperative organ injury: a retrospective cohort study in Germany
Authors: Hochhausen Nadine , Mechelinck Mare , Kroh Andreas , Rossaint Rolf , Kork Felix 
Published: June 2024

Abstract
Background
The impact of chronic obstructive pulmonary disease (COPD) on outcome in perioperative organ injury (POI) has not yet been investigated sufficiently.

Methods
This retrospective cohort study analysed data of surgical patients with POI, namely delirium, stroke, acute myocardial infarction, acute respiratory distress syndrome, acute liver injury (ALI), or acute kidney injury (AKI), in Germany between 2015 and 2019. We compared in-hospital mortality, hospital length of stay (HLOS) and perioperative ventilation time (VT) in patients with and without COPD.

Results
We analysed the data of 1,642,377 surgical cases with POI of which 10.8% suffered from COPD. In-hospital mortality was higher (20.6% vs. 15.8%, p < 0.001) and HLOS (21 days (IQR, 12–34) vs. 16 days (IQR, 10–28), p < 0.001) and VT (199 h (IQR, 43–547) vs. 125 h (IQR, 32–379), p < 0.001) were longer in COPD patients. Within the POI examined, AKI was the most common POI (57.8%), whereas ALI was associated with the highest mortality (54.2%). Regression analysis revealed that COPD was associated with a slightly higher risk of in-hospital mortality (OR, 1.19; 95% CI:1.18–1.21) in patients with any POI.

Conclusions
COPD in patients with POI is associated with higher mortality, longer HLOS and longer VT. Especially patients suffering from ALI are susceptible to the detrimental effects of COPD on adverse outcome.
EfficientNet-based machine learning architecture for sleep apnea identification in clinical single-lead ECG signal data sets
Authors: Liu Meng-Hsuan , Chien Shang-Yu , Wu Ya-Lun , Sun Ting-Hsuan , Huang Chun-Sen , Hsu Kai-Cheng , Hang Liang-Wen 
Published: June 2024

Abstract
Objective
Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data sets.

Methods
We conducted our research using a data set consisting of 1656 patients, representing a diverse demographic, from the sleep center of China Medical University Hospital. To detect apnea ECG segments and extract apnea features, we utilized the EfficientNet and some of its layers, respectively. Furthermore, we compared various training and data preprocessing techniques to enhance the model’s prediction, such as setting class and sample weights or employing overlapping and regular slicing. Finally, we tested our approach against other literature on the Apnea-ECG database.

Results
Our research found that the EfficientNet model achieved the best apnea segment detection using overlapping slicing and sample-weight settings, with an AUC of 0.917 and an accuracy of 0.855. For patient screening with AHI > 30, we combined the trained model with XGBoost, leading to an AUC of 0.975 and an accuracy of 0.928. Additional tests using PhysioNet data showed that our model is comparable in performance to existing models regarding its ability to screen OSA levels.

Conclusions
Our suggested architecture, coupled with training and preprocessing techniques, showed admirable performance with a diverse demographic dataset, bringing us closer to practical implementation in OSA diagnosis.
Trial registration The data for this study were collected retrospectively from the China Medical University Hospital in Taiwan with approval from the institutional review board CMUH109-REC3-018.
Diurnal variation of heart rate variability in individuals with spinal cord injury
Authors: Saengsuwan Jittima , Ruangsuphaphichat Arphatsorn , Brockmann Lars , Sirasaporn Patpiya , Manimmanakorn Nuttaset , Hunt Kenneth J. 
Published: June 2024

Abstract
Background
Heart rate variability (HRV) may provide objective information about cardiogenic autonomic balance in individuals with spinal cord injury (SCI). The aim of this study was to characterize the diurnal variation of HRV in individuals with SCI at lesion level T6 and above and lesion level below T6.

Methods
This was a retrospective analysis of a prior cross-sectional study. Individuals with chronic SCI underwent 24 h recording of the time between consecutive R waves (RR interval) to derive parameters of HRV as follows: standard deviation of all normal-to-normal R–R intervals (SDNN) and square root of the mean of the squared differences between successive R–R intervals (RMSSD) (time domain); and high frequency power (HF), low-frequency power (LF), very low frequency power (VLF), ultra-low frequency power (ULF) and total power (TP) (frequency domain). Changes in the magnitude of HRV outcomes over the 24 h period were investigated using a novel multi-component cosinor model constrained to the form of a three-harmonic Fourier series.

Results
Participants were grouped as lesion level T6 and above (n = 22) or below T6 (n = 36). Most of them were male (n = 40, 69%) and the median age (interquartile range) was 50.5 (28) years. Both groups exhibited similar diurnal patterns in most HRV metrics. The lowest values occurred in the late afternoon (4–6 pm) and gradually increased, peaking around midnight to early morning (1–6 am). Exceptions included RMSSD, which peaked before midnight, and ULF, which showed a double peak pattern that peaked from 11 am to 1 pm and 4–6 am in participants with lesion level at T6 and above. The HRV values in participants with lesion level T6 and above were generally lower than participants with lesion level below T6, except for peak values of RMSSD, HF and LF.

Conclusion
This study demonstrated substantial diurnal variation of HRV in participants with SCI in both groups of participants. In clinical and research settings, diurnal variations in HRV must be taken into consideration.
Successful management of chromoblastomycosis utilizing conventional antifungal agents and imiquimod therapy
Authors: Zheng Jinjin , Liu Shougang , Xie Zhenmou , Chen Yangxia , Xi Liyan , Liu Hongfang , Liu Yinghui 
Published: June 2024

AbstractChromoblastomycosis (CBM), a chronic fungal infection affecting the skin and subcutaneous tissues, is predominantly caused by dematiaceous fungi in tropical and subtropical areas. Characteristically, CBM presents as plaques and nodules, often leading to scarring post-healing. Besides traditional diagnostic methods such as fungal microscopy, culture, and histopathology, dermatoscopy and reflectance confocal microscopy can aid in diagnosis. The treatment of CBM is an extended and protracted process. Imiquimod, acting as an immune response modifier, boosts the host’s immune response against CBM, and controls scar hyperplasia, thereby reducing the treatment duration. We present a case of CBM in Guangdong with characteristic reflectance confocal microscopy manifestations, effectively managed through a combination of itraconazole, terbinafine, and imiquimod, shedding light on novel strategies for managing this challenging condition.
A novel role for KIFC1-MYH9 interaction in triple-negative breast cancer aggressiveness and racial disparity
Authors: Garlapati Chakravarthy , Joshi Shriya , Yang Chunhua , Chandrashekar Darshan Shimoga , Rida Padmashree , Aneja Ritu 
Published: June 2024

AbstractAfrican American (AA) women are twice as likely to develop triple-negative breast cancer (TNBC) as women of European descent. Additionally, AA women with TNBC present a much more aggressive disease course than their European American (EA) counterparts. Thus, there is an unmet clinical need to identify race-specific biomarkers and improve survival outcomes in AA patients with TNBC. The minus-end directed microtubule motor protein kinesin family member C1 (KIFC1) promotes centrosome clustering and chromosomal instability and is often overexpressed in TNBC. Previous findings suggest that KIFC1 plays a role in cell proliferation and migration in TNBC cells from AAs and that the levels of nuclear KIFC1 (nKIFC1) are particularly high in AA patients with TNBC. The nuclear localization of KIFC1 in interphase may underlie its previously unrecognized race-specific association. In this study, we found that in TNBC cells derived from AAs, nKIFC1 interacted with the tumor suppressor myosin heavy chain 9 (MYH9) over EA cells. Treatment of AA TNBC cells with commercial inhibitors of KIFC1 and MYH9 disrupted the interaction between KIFC1 and MYH9. To characterize the racial differences in the KIFC1-MYH9-MYC axis in TNBC, we established homozygous KIFC1 knockout (KO) TNBC cell lines. KIFC1 KO significantly inhibited proliferation, migration, and invasion in AA TNBC cells but not in EA TNBC cells. RNA sequencing analysis showed significant downregulation of genes involved in cell migration, invasion, and metastasis upon KIFC1 KO in TNBC cell lines from AAs compared to those from EAs. These data indicate that mechanistically, the role of nKIFC1 in driving TNBC progression and metastasis is stronger in AA patients than in EA patients, and that KIFC1 may be a critical therapeutic target for AA patients with TNBC.
Graphical abstract
Integrating DNA/RNA microbe detection and host response for accurate diagnosis, treatment and prognosis of childhood infectious meningitis and encephalitis
Authors: Xing Zhihao , Jiang Hanfang , Liu Xiaorong , Chai Qiang , Xin Zefeng , Zhu Chunqing , Bao Yanmin , Chen Hongyu , Gao Hongdan , Ma Dongli 
Published: June 2024

Abstract
Background
Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity, mortality, and sequelae in childhood. Metagenomic next-generation sequencing (mNGS) can potentially improve IM outcomes by sequencing both pathogen and host responses and increasing the diagnosis accuracy.

Methods
Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL).

Results
Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM.

Conclusions
This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.