bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue and symptom-based clusters in post COVID-19 patients: a multicentre, prospective, observational cohort study
Authors: Cornelissen Merel E. B. , Bloemsma Lizan D. , Vaes Anouk W. , Baalbaki Nadia , Deng Qichen , Beijers Rosanne J. H. C. G. , Noij Lieke C. E. , Houweling Laura , Bazdar Somayeh , Spruit Martijn A. , Maitland-van der Zee Anke H. ,   on behalf of the P4O2 Consortium
Published: February 2024

Abstract
Background
In the Netherlands, the prevalence of post COVID-19 condition is estimated at 12.7% at 90–150 days after SARS-CoV-2 infection. This study aimed to determine the occurrence of fatigue and other symptoms, to assess how many patients meet the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) criteria, to identify symptom-based clusters within the P4O2 COVID-19 cohort and to compare these clusters with clusters in a ME/CFS cohort.

Methods
In this multicentre, prospective, observational cohort in the Netherlands, 95 post COVID-19 patients aged 40–65 years were included. Data collection at 3–6 months after infection included demographics, medical history, questionnaires, and a medical examination. Follow-up assessments occurred 9–12 months later, where the same data were collected. Fatigue was determined with the Fatigue Severity Scale (FSS), a score of ≥ 4 means moderate to high fatigue. The frequency and severity of other symptoms and the percentage of patients that meet the ME/CFS criteria were assessed using the DePaul Symptom Questionnaire-2 (DSQ-2). A self-organizing map was used to visualize the clustering of patients based on severity and frequency of 79 symptoms. In a previous study, 337 Dutch ME/CFS patients were clustered based on their symptom scores. The symptom scores of post COVID-19 patients were applied to these clusters to examine whether the same or different clusters were found.

Results
According to the FSS, fatigue was reported by 75.9% of the patients at 3–6 months after infection and by 57.1% of the patients 9–12 months later. Post-exertional malaise, sleep disturbances, pain, and neurocognitive symptoms were also frequently reported, according to the DSQ-2. Over half of the patients (52.7%) met the Fukuda criteria for ME/CFS, while fewer patients met other ME/CFS definitions. Clustering revealed specific symptom patterns and showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort, where 2 clusters had > 10 patients.

Conclusions
This study shows persistent fatigue and diverse symptomatology in post COVID-19 patients, up to 12–18 months after SARS-CoV-2 infection. Clustering showed that post COVID-19 patients occurred in 11 of the clusters that have been observed in the ME/CFS cohort.
A proteomic classifier panel for early screening of colorectal cancer: a case control study
Authors: Hua Hanju , Wang Tingting , Pan Liangxuan , Du Xiaoyao , Xia Tianxue , Fa Zhenzhong , Gu Lei , Gao Fei , Yu Chaohui , Gao Feng , Liao Lujian , Shen Zhe 
Published: February 2024

Abstract
Background
Diagnosis of colorectal cancer (CRC) during early stages can greatly improve patient outcome. Although technical advances in the field of genomics and proteomics have identified a number of candidate biomarkers for non-invasive screening and diagnosis, developing more sensitive and specific methods with improved cost-effectiveness and patient compliance has tremendous potential to help combat the disease.

Methods
We enrolled three cohorts of 479 subjects, including 226 CRC cases, 197 healthy controls, and 56 advanced precancerous lesions (APC). In the discovery cohort, we used quantitative mass spectrometry to measure the expression profile of plasma proteins and applied machine-learning to select candidate proteins. We then developed a targeted mass spectrometry assay to measure plasma concentrations of seven proteins and a logistic regression classifier to distinguish CRC from healthy subjects. The classifier was further validated using two independent cohorts.

Results
The seven-protein panel consisted of leucine rich alpha-2-glycoprotein 1 (LRG1), complement C9 (C9), insulin-like growth factor binding protein 2 (IGFBP2), carnosine dipeptidase 1 (CNDP1), inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3), serpin family A member 1 (SERPINA1), and alpha-1-acid glycoprotein 1 (ORM1). The panel classified CRC and healthy subjects with high accuracy, since the area under curve (AUC) of the training and testing cohort reached 0.954 and 0.958. The AUC of the two independent validation cohorts was 0.905 and 0.909. In one validation cohort, the panel had an overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 89.9%, 81.8%, 89.2%, and 82.9%, respectively. In another blinded validation cohort, the panel classified CRC from healthy subjects with a sensitivity of 81.5%, specificity of 97.9%, and overall accuracy of 92.0%. Finally, the panel was able to detect APC with a sensitivity of 49%.

Conclusions
This seven-protein classifier is a clear improvement compared to previously published blood-based protein biomarkers for detecting early-stage CRC, and is of translational potential to develop into a clinically useful assay.
Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions
Authors: Trinkley Katy E. , An Ruopeng , Maw Anna M. , Glasgow Russell E. , Brownson Ross C. 
Published: February 2024

Abstract
Background
The field of implementation science was developed to address the significant time delay between establishing an evidence-based practice and its widespread use. Although implementation science has contributed much toward bridging this gap, the evidence-to-practice chasm remains a challenge. There are some key aspects of implementation science in which advances are needed, including speed and assessing causality and mechanisms. The increasing availability of artificial intelligence applications offers opportunities to help address specific issues faced by the field of implementation science and expand its methods.

Main text
This paper discusses the many ways artificial intelligence can address key challenges in applying implementation science methods while also considering potential pitfalls to the use of artificial intelligence. We answer the questions of “why” the field of implementation science should consider artificial intelligence, for “what” (the purpose and methods), and the “what” (consequences and challenges). We describe specific ways artificial intelligence can address implementation science challenges related to (1) speed, (2) sustainability, (3) equity, (4) generalizability, (5) assessing context and context-outcome relationships, and (6) assessing causality and mechanisms. Examples are provided from global health systems, public health, and precision health that illustrate both potential advantages and hazards of integrating artificial intelligence applications into implementation science methods. We conclude by providing recommendations and resources for implementation researchers and practitioners to leverage artificial intelligence in their work responsibly.

Conclusions
Artificial intelligence holds promise to advance implementation science methods (“why”) and accelerate its goals of closing the evidence-to-practice gap (“purpose”). However, evaluation of artificial intelligence’s potential unintended consequences must be considered and proactively monitored. Given the technical nature of artificial intelligence applications as well as their potential impact on the field, transdisciplinary collaboration is needed and may suggest the need for a subset of implementation scientists cross-trained in both fields to ensure artificial intelligence is used optimally and ethically.
Atypical social cognition processing in bulimia nervosa: an fMRI study of patients thinking of others’ mental states
Authors: Kamashita Rio , Setsu Rikukage , Numata Noriko , Koga Yasuko , Nakazato Michiko , Matsumoto Koji , Ando Hiroki , Masuda Yoshitada , Maral Sertap , Shimizu Eiji , Hirano Yoshiyuki 
Published: February 2024

Abstract
Background
Feeding and eating disorders are severe mental disorders that gravely affect patients’ lives. In particular, patients with anorexia nervosa (AN) or bulimia nervosa (BN) appear to have poor social cognition. Many studies have shown the relationship between poor social cognition and brain responses in AN. However, few studies have examined the relationship between social cognition and BN. Therefore, we examined which brain regions impact the ability for social cognition in patients with BN.

Methods
We used task-based functional magnetic resonance imaging (fMRI) to examine brain responses during a social cognition task and the Reading Mind in the Eyes Test (RMET). During the fMRI, 22 women with BN and 22 healthy women (HW) took the RMET. Participants also completed the eating disorder clinical measures Bulimic Investigatory Test, Edinburgh (BITE) and Eating Disorders Examination Questionnaire (EDE-Q), the Patient Health Questionnaire (PHQ-9) measure of depression; and the Generalized Anxiety Disorder (GAD-7) measure of anxiety.

Results
No difference was observed in the RMET scores between women with BN and HW. Both groups showed activation in brain regions specific to social cognition. During the task, no differences were shown between the groups in the BOLD signal (p < 0.05, familywise error corrected for multiple comparisons). However, there was a tendency of more robust activation in the right angular gyrus, ventral diencephalon, thalamus proper, temporal pole, and middle temporal gyrus in BN (p < 0.001, uncorrected for multiple comparisons). Moreover, HW showed a positive correlation between RMET scores and the activation of two regions: medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC); however, no significant correlation was observed in women with BN.

Conclusions
While activation in the mPFC and ACC positively correlated to the RMET scores in HW, no correlation was observed in BN patients. Therefore, women with BN might display modulated neural processing when thinking of others’ mental states. Further examination is needed to investigate neural processing in BN patients to better understand their social cognition abilities.

Trial registration
UMIN, UMIN000010220. Registered 13 March 2013, https://rctportal.niph.go.jp/s/detail/um?trial_id=UMIN000010220
A tumor suppressor protein encoded by circKEAP1 inhibits osteosarcoma cell stemness and metastasis by promoting vimentin proteasome degradation and activating anti-tumor immunity
Authors: Zhang Ying , Liu Zhaoyong , Zhong Zhigang , Ji Yanchen , Guo Huancheng , Wang Weidong , Chen Chuangzhen 
Published: February 2024

Abstract
Background
Osteosarcoma (OS) is one of most commonly diagnosed bone cancer. Circular RNAs (circRNAs) are a class of highly stable non-coding RNA, the majority of which have not been characterized functionally. The underlying function and molecular mechanisms of circRNAs in OS have not been fully demonstrated.

Method
Microarray analysis was performed to identify circRNAs that are differentially-expressed between OS and corresponding normal tissues. The biological function of circKEAP1 was confirmed in vitro and in vivo. Mass spectrometry and western blot assays were used to identify the circKEAP1-encoded protein KEAP1-259aa. The molecular mechanism of circKEAP1 was investigated by RNA sequencing and RNA immunoprecipitation analyses.

Results
Here, we identified a tumor suppressor circKEAP1, originating from the back-splicing of exon2 of the KEAP1 gene. Clinically, circKEAP1 is downregulated in OS tumors and associated with better survival in cancer patients. N6-methyladenosine (m6A) at a specific adenosine leads to low expression of circKEAP1. Further analysis revealed that circKEAP1 contained a 777 nt long ORF and encoded a truncated protein KEAP1-259aa that reduces cell proliferation, invasion and tumorsphere formation of OS cells. Mechanistically, KEAP1-259aa bound to vimentin in the cytoplasm to promote vimentin proteasome degradation by interacting with the E3 ligase ARIH1. Moreover, circKEAP1 interacted with RIG-I to activate anti-tumor immunity via the IFN-γ pathway.

Conclusion
Taken together, our findings characterize a tumor suppressor circKEAP1 as a key tumor suppressor regulating of OS cell stemness, proliferation and migration, providing potential therapeutic targets for treatment of OS.
Extracorporeal cardiopulmonary resuscitation versus conventional CPR in cardiac arrest: an updated meta-analysis and trial sequential analysis
Authors: Low Christopher Jer Wei , Ling Ryan Ruiyang , Ramanathan Kollengode , Chen Ying , Rochwerg Bram , Kitamura Tetsuhisa , Iwami Taku , Ong Marcus Eng Hock , Okada Yohei 
Published: February 2024

Abstract
Background
Extracorporeal cardiopulmonary resuscitation (ECPR) may reduce mortality and improve neurological outcomes in patients with cardiac arrest. We updated our existing meta-analysis and trial sequential analysis to further evaluate ECPR compared to conventional CPR (CCPR).

Methods
We searched three international databases from 1 January 2000 through 1 November 2023, for randomised controlled trials or propensity score matched studies (PSMs) comparing ECPR to CCPR in both out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA). We conducted an updated random-effects meta-analysis, with the primary outcome being in-hospital mortality. Secondary outcomes included short- and long-term favourable neurological outcome and survival (30 days–1 year). We also conducted a trial sequential analysis to evaluate the required information size in the meta-analysis to detect a clinically relevant reduction in mortality.

Results
We included 13 studies with 14 pairwise comparisons (6336 ECPR and 7712 CCPR) in our updated meta-analysis. ECPR was associated with greater precision in reducing overall in-hospital mortality (OR 0.63, 95% CI 0.50–0.79, high certainty), to which the trial sequential analysis was concordant. The addition of recent studies revealed a newly significant decrease in mortality in OHCA (OR 0.62, 95% CI 0.45–0.84). Re-analysis of relevant secondary outcomes reaffirmed our initial findings of favourable short-term neurological outcomes and survival up to 30 days. Estimates for long-term neurological outcome and 90-day–1-year survival remained unchanged.

Conclusions
We found that ECPR reduces in-hospital mortality, improves neurological outcome, and 30-day survival. We additionally found a newly significant benefit in OHCA, suggesting that ECPR may be considered in both IHCA and OHCA.
Modelling the dynamic basic reproduction number of dengue based on MOI of Aedes albopictus derived from a multi-site field investigation in Guangzhou, a subtropical region
Authors: Guo Xiang , Li Li , Ren Wenwen , Hu Minling , Li Ziyao , Zeng Shu , Liu Xiaohua , Wang Yuji , Xie Tian , Yin Qingqing , Wei Yuehong , Luo Lei , Shi Benyun , Wang Chunmei , Wu Rangke , Yang Zhicong , Chen Xiao-Guang , Zhou Xiaohong 
Published: February 2024

Abstract
Background
More than half of the global population lives in areas at risk of dengue (DENV) transmission. Developing an efficient risk prediction system can help curb dengue outbreaks, but multiple variables, including mosquito-based surveillance indicators, still constrain our understanding. Mosquito or oviposition positive index (MOI) has been utilized in field surveillance to monitor the wild population density of Aedes albopictus in Guangzhou since 2005.

Methods
Based on the mosquito surveillance data using Mosq-ovitrap collection and human landing collection (HLC) launched at 12 sites in Guangzhou from 2015 to 2017, we established a MOI-based model of the basic dengue reproduction number (R0) using the classical Ross-Macdonald framework combined with a linear mixed-effects model.

Results
During the survey period, the mean MOI and adult mosquito density index (ADI) using HLC for Ae. albopictus were 12.96 ± 17.78 and 16.79 ± 55.92, respectively. The R0 estimated from the daily ADI (ADID) showed a significant seasonal variation. A 10-unit increase in MOI was associated with 1.08-fold (95% CI 1.05, 1.11) ADID and an increase of 0.14 (95% CI 0.05, 0.23) in the logarithmic transformation of R0. MOI-based R0 of dengue varied by month and average monthly temperature. During the active period of Ae. albopictus from April to November in Guangzhou region, a high risk of dengue outbreak was predicted by the MOI-based R0 model, especially from August to October, with the predicted R0 > 1. Meanwhile, from December to March, the estimates of MOI-based R0 were < 1.

Conclusions
The present study enriched our knowledge about mosquito-based surveillance indicators and indicated that the MOI of Ae. albopictus could be valuable for application in estimating the R0 of dengue using a statistical model. The MOI-based R0 model prediction of the risk of dengue transmission varied by month and temperature in Guangzhou. Our findings lay a foundation for further development of a complex efficient dengue risk prediction system.

Graphical Abstract
A smartphone-based crowd-sourced real-time surveillance platform (apple snail inspector) for the invasive snails: a design and development study
Authors: Zhang Qiang , Ding Xin , Zhang Yingshu , Yang Yougui , Mao Fanzhen , Ni Bixian , Liu Yaobao , Culleton Richard , Dai Yang , Cao Jun 
Published: February 2024

Abstract
Background
The large amphibious freshwater apple snail is an important invasive species in China, but there is currently no method available for their surveillance. The development and popularization of smartphones provide a new platform for research on surveillance technologies for the early detection and effective control of invasive species.

Methods
The ASI surveillance system was developed based on the infrastructure of the WeChat platform and Amap. The user can directly enter the game interface through the WeChat port on their mobile phone, and the system automatically obtains their location. The user can then report the location of apple snails. The administrator can audit the reported information, and all information can be exported to Microsoft Excel version 2016 for analysis. The map was generated by ArcGIS 10.2 and was used to characterize the spatial and temporal distribution of apple snails in Jiangsu Province.

Results
The architecture of ASI consists of three parts: a mobile terminal, a server terminal and a desktop terminal. We published more than 10 tweets on the official WeChat account of the system to announce it to the public, and a total of 207 users in 2020 and 2021 correctly reported sightings of apple snails. We identified 550 apple snails breeding sites in 2020 and 2021, featuring ponds (81%), parks (17%) and farmland (2%). In addition, most of the locations contained snail eggs, and the reporting times mainly occurred between May and September.

Conclusions
The ASI is an effective surveillance system that can be used to identify the breeding locations of apple snails and provides the basis of prevention and control for its dispersal. Its successful development and operation provide new potential avenues for surveillance of other public health issues.

Graphical Abstract
Epigenetic regulation and factors that influence the effect of iPSCs-derived neural stem/progenitor cells (NS/PCs) in the treatment of spinal cord injury
Authors: Yang Yubiao , Ma Boyuan , Chen Jinyu , Liu Derong , Ma Jun , Li Bo , Hao Jian , Zhou Xianhu 
Published: February 2024

AbstractSpinal cord injury (SCI) is a severe neurological disorder that causes neurological impairment and disability. Neural stem/progenitor cells (NS/PCs) derived from induced pluripotent stem cells (iPSCs) represent a promising cell therapy strategy for spinal cord regeneration and repair. However, iPSC-derived NS/PCs face many challenges and issues in SCI therapy; one of the most significant challenges is epigenetic regulation and that factors that influence this mechanism. Epigenetics refers to the regulation of gene expression and function by DNA methylation, histone modification, and chromatin structure without changing the DNA sequence. Previous research has shown that epigenetics plays a crucial role in the generation, differentiation, and transplantation of iPSCs, and can influence the quality, safety, and outcome of transplanted cells. In this study, we review the effects of epigenetic regulation and various influencing factors on the role of iPSC-derived NS/PCs in SCI therapy at multiple levels, including epigenetic reprogramming, regulation, and the adaptation of iPSCs during generation, differentiation, and transplantation, as well as the impact of other therapeutic tools (e.g., drugs, electrical stimulation, and scaffolds) on the epigenetic status of transplanted cells. We summarize our main findings and insights in this field and identify future challenges and directions that need to be addressed and explored.
Granulocyte macrophage colony-stimulating factor-induced macrophages of individuals with autism spectrum disorder adversely affect neuronal dendrites through the secretion of pro-inflammatory cytokines
Authors: Takada Ryohei , Toritsuka Michihiro , Yamauchi Takahira , Ishida Rio , Kayashima Yoshinori , Nishi Yuki , Ishikawa Mitsuru , Yamamuro Kazuhiko , Ikehara Minobu , Komori Takashi , Noriyama Yuki , Kamikawa Kohei , Saito Yasuhiko , Okano Hideyuki , Makinodan Manabu 
Published: February 2024

Abstract
Background
A growing body of evidence suggests that immune dysfunction and inflammation in the peripheral tissues as well as the central nervous system are associated with the neurodevelopmental deficits observed in autism spectrum disorder (ASD). Elevated expression of pro-inflammatory cytokines in the plasma, serum, and peripheral blood mononuclear cells of ASD has been reported. These cytokine expression levels are associated with the severity of behavioral impairments and symptoms in ASD. In a prior study, our group reported that tumor necrosis factor-α (TNF-α) expression in granulocyte–macrophage colony-stimulating factor-induced macrophages (GM-CSF MΦ) and the TNF-α expression ratio in GM-CSF MΦ/M-CSF MΦ (macrophage colony-stimulating factor-induced macrophages) was markedly higher in individuals with ASD than in typically developed (TD) individuals. However, the mechanisms of how the macrophages and the highly expressed cytokines affect neurons remain to be addressed.

Methods
To elucidate the effect of macrophages on human neurons, we used a co-culture system of control human-induced pluripotent stem cell-derived neurons and differentiated macrophages obtained from the peripheral blood mononuclear cells of five TD individuals and five individuals with ASD. All participants were male and ethnically Japanese.

Results
Our results of co-culture experiments showed that GM-CSF MΦ affect the dendritic outgrowth of neurons through the secretion of pro-inflammatory cytokines, interleukin-1α and TNF-α. Macrophages derived from individuals with ASD exerted more severe effects than those derived from TD individuals.

Limitations
The main limitations of our study were the small sample size with a gender bias toward males, the use of artificially polarized macrophages, and the inability to directly observe the interaction between neurons and macrophages from the same individuals.

Conclusions
Our co-culture system revealed the non-cell autonomous adverse effects of GM-CSF MΦ in individuals with ASD on neurons, mediated by interleukin-1α and TNF-α. These results may support the immune dysfunction hypothesis of ASD, providing new insights into its pathology.