bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiology of influenza over a ten-year period in Belgium: overview of the historical and current evidence
Authors: Prezzi A. , Saelens X. , Vandijck D. 
Published: November 2023

Abstract
Background
Generally influenza, a contagious respiratory disease, leads to mild illness, but can present as a severe illness with significant complications for some. It entails significant health challenges and an economic burden. Annual vaccination is considered the most effective preventive measure against influenza, especially in high-risk groups.

Method
Epidemiological, demographic and vaccination data of influenza from 2009-to-2019 is collected from Sciensano, the Belgian Institute for Health. Sciensano monitors influenza virus through two surveillances: the Influenza-Like Illness (ILI) surveillance in primary care and the Severe Acute Respiratory Infections (SARI) surveillance in hospital settings.

Results
49.6% [± 8.5] of all ILI-samples tested positive in this period. Influenza A was the dominant circulating type, accounting for 73.7% [± 27.5] of positive samples, while influenza B accounted for 24.3% [± 26.7]. For SARI-surveillance, the average rate of samples tested positive was 36.3% [± 9.3]. Influenza A was responsible for respectively 77.7% [± 23.8] of positive samples and influenza B for 22.2% [± 23.7]. Since 2010, epidemics typically lasted about 9.3 weeks [± 2.7]. From 2012 to 2019 the average vaccine effectiveness was 34.9% [± 15.3].

Conclusion
Influenza is quickly considered a trivial disease, but can have substantial repercussions. It remains difficult to identify the level of treat of influenza due to antigenic evolution. Measures to prevent, control and treat are needed. Vaccines that provide broader and more durable protection that can be produced more rapidly could be a potential solution.
An individualized nomogram for predicting and validating spread through air space (STAS) in surgically resected lung adenocarcinoma: a single center retrospective analysis
Authors: Wang Jing , Yao Yuanshan , Tang Dongfang , Gao Wen 
Published: November 2023

Abstract
Objective
A single-center study was conducted to explore the association between STAS and other clinical features in surgically resected adenocarcinoma to enhance our current understanding of STAS.

Methods
We retrospectively enrolled patients with lung adenocarcinoma (n = 241) who underwent curative surgeries. Patients undergoing surgery in 2019 were attributed to the training group (n = 188) and those undergoing surgery in January 2022 to June 2022 were attributed to the validation (n = 53) group. Univariate and multivariate logistic regression analyses were used to identify predictive factors for STAS, which were used to construct a simple nomogram. Furthermore, ROC and calibration curves were used to evaluate the performance of the nomogram. In addition, we conducted decision curve analysis (DCA) to assess the clinical utility of this nomogram.

Results
In our cohort, 52 patients were identified as STAS-positive (21.6%). In univariate analysis, STAS was significantly associated with age, surgical approach, CEA, CTR (Consolidation Tumor Ratio), TNM stage, tumor grade, gross tumor size, resection margin, vessel cancer embolus, pleural invasion, lymph node metastasis, high ki67 and positive PD-L1 staining (P < 0.05). Lower age, CTR > 0.75, vessel cancer embolus, high Ki67 and PD-L1 stain positive were significant predictors for STAS during multivariate logistics analysis. A simple nomogram was successfully constructed based on these five predictors. The AUC values of our nomogram for the probability of tumor STAS were 0.860 in the training group and 0.919 in the validation group. In addition, the calibration curve and DCA validated the good performance of this model.

Conclusion
A nomogram was successfully constructed to identify the presence of STAS in surgically resected lung adenocarcinoma patients.
Genitourinary cancers updates: highlights from ASCO 2023
Authors: Qin Qian , Sheffield Hollie , Taasan Sean M. , Wang Andrew Z. , Zhang Tian 
Published: November 2023

AbstractSignificant scientific advances in immunotherapy and targeted therapy approaches have improved clinical outcomes and increased treatment options for patients with genitourinary (GU) malignancies. We highlight the clinical trial developments released at the ASCO 2023 annual meeting, including PARP inhibitors for prostate cancer, antibody drug conjugates and fibroblast growth factor receptor inhibitors for urothelial cancer, and HIF2a inhibitors for renal cell carcinoma. Novel agents such as bispecific antibodies, chimeric antigen receptor T-cells, and radiopharmaceuticals are currently in early phase development and also have high potential impact for the GU cancer landscape. With more treatment options, the field will need to define best treatment sequencing to optimize outcomes for each patient.
A flexible dose-response modeling framework based on continuous toxicity outcomes in phase I cancer clinical trials
Authors: Lee Se Yoon 
Published: November 2023

AbstractBackgroundThe past few decades have seen remarkable developments in dose-finding designs for phase I cancer clinical trials. While many of these designs rely on a binary toxicity response, there is an increasing focus on leveraging continuous toxicity responses. A continuous toxicity response pertains to a quantitative measure represented by real numbers. A higher value corresponds not only to an elevated likelihood of side effects for patients but also to an increased probability of treatment efficacy. This relationship between toxicity and dose is often nonlinear, necessitating flexibility in the quest to find an optimal dose.MethodsA flexible, fully Bayesian dose-finding design is proposed to capitalize on continuous toxicity information, operating under the assumption that the true shape of the dose-toxicity curve is nonlinear.ResultsWe conduct simulations of clinical trials across varying scenarios of non-linearity to evaluate the operational characteristics of the proposed design. Additionally, we apply the proposed design to a real-world problem to determine an optimal dose for a molecularly targeted agent.ConclusionsPhase I cancer clinical trials, designed within a fully Bayesian framework with the utilization of continuous toxicity outcomes, offer an alternative approach to finding an optimal dose, providing unique benefits compared to trials designed based on binary toxicity outcomes.
Mediating effect of self-concealment between non-suicidal self-injury and internet addiction in college students: a cross-sectional study
Authors: Chen Xushu , Ma Qin , Peng Xueping , Yang Haijun , Ye Zixiang , Yang Cui , He Changjiu 
Published: November 2023

Abstract
Background
Internet addiction, defined as uncontrolled behaviour resulting from the use of the Internet without the influence of addictive substances, which can seriously impair academic, occupational and social functioning. Non-suicidal self-injury, defined as self-injurious behaviour without the intent to die, and its addictive characteristics are similar to those of Internet addiction. Currently, there is a lack of research on the relationship between non-suicidal self-injury and Internet addiction. The purpose of this study was to examine the relationship between non-suicidal self-injury and internet addiction among college students and the role of self-concealment in this relationship.

Methods
In this study, data were collected online between December 2022 and January 2023 from 600 university students in Chengdu, Sichuan Province, China, using purposive sampling. The questionnaires included the Non-Suicidal Self-Injury Inventory (NSSI), the Self-Concealment Scale (SCS) and the Internet Addiction Test (IAT).

Results
A total of 573 valid questionnaires were recovered, with a valid recovery rate of 95.50%.

Conclution
The results suggest that self-concealment plays a partial mediating role between non-suicidal self-injury and internet addiction among college students. The authors emphasized the importance of internet addiction. In order to reduce the occurrence of internet addiction, schools should provide targeted interventions to promote the psychological health of college students’ internet addictive behaviours.
A chronological study of gunshot residue (GSR) detection techniques: a narrative review
Authors: Krishna Sreelakshmi , Ahuja Pooja 
Published: November 2023

Abstract
Background
The investigation and reconstruction of firearm-related crimes for the determination of the shooting distance, time since fire, and gunshot residue (GSR) persistence using the analysis of GSR comprising organic and inorganic components are crucial. However, the conventional color tests and allied techniques for GSR analysis are destructive and have limited sensitivity and selectivity.

Main text
The review gives an elaborate and chronological description of all the methods used to date along with the future aspects of GSR detection techniques. It highlights the significant methods of spectrometry and spectroscopy applied as analytical techniques for the evaluation of GSR. The study is divided into various sections, ranging from the conventional color tests to the current techniques used in GSR analysis. While there is inconsistency and unreliability in these techniques, the current approaches discussed in this study using laser induced breakdown spectroscopy (LIBS), surface enhanced Raman scattering (SERS), ion mobility spectrometry (IMS), and electrochemical sensor-based methods have significant potential for GSR detection. Addressing such limitations will enhance the forensic capabilities of law enforcement and provide an added advantage to forensic laboratories during an investigation. It will also reinforce the use of such spectroscopic data in a criminal investigation. The techniques discussed here have the capability to detect both organic and inorganic components of GSR that has the potential to link GSR particles to the type of ammunition discharged.

Conclusions
The validity and reliability of these approaches have proved to establish their capability to differentiate between potential false positives known for standard forensic analysis techniques currently used for GSR detection and identification. The paper anticipates a systematic study of the novel methodologies relevant to the current scope of research concerning GSR analysis, when fully developed and implemented in practice will help forensic scientists to detect, identify, and analyze GSR, making it a new and important type of evidence.
Local imperceptible adversarial attacks against human pose estimation networks
Authors: Liu Fuchang , Zhang Shen , Wang Hao , Yan Caiping , Miao Yongwei 
Published: November 2023

AbstractDeep neural networks are vulnerable to attacks from adversarial inputs. Corresponding attack research on human pose estimation (HPE), particularly for body joint detection, has been largely unexplored. Transferring classification-based attack methods to body joint regression tasks is not straightforward. Another issue is that the attack effectiveness and imperceptibility contradict each other. To solve these issues, we propose local imperceptible attacks on HPE networks. In particular, we reformulate imperceptible attacks on body joint regression into a constrained maximum allowable attack. Furthermore, we approximate the solution using iterative gradient-based strength refinement and greedy-based pixel selection. Our method crafts effective perceptual adversarial attacks that consider both human perception and attack effectiveness. We conducted a series of imperceptible attacks against state-of-the-art HPE methods, including HigherHRNet, DEKR, and ViTPose. The experimental results demonstrate that the proposed method achieves excellent imperceptibility while maintaining attack effectiveness by significantly reducing the number of perturbed pixels. Approximately 4% of the pixels can achieve sufficient attacks on HPE.
Structural integrity of grey and white matter in schizophrenic patients by diffusion tensor imaging
Authors: Khalil Aya Mohamed Reda , Samier Heba Mohamed , Dawoud Mahmoud Abdelaziz , Elsharawy Fatma Anas 
Published: November 2023

Abstract
Background
Schizophrenia is a chronic disabling mental illness. A novel magnetic resonance imaging (MRI) technique known as diffusion tensor imaging (DTI) is a non-invasive and does not need external contrast materials. It is capable of identifying anomalies in the white matter micro-structure of the brain. This work conducted the DTI in schizophrenic patients to evaluate altered structural integrity in grey and white matter.

Methods
This prospective case control study was conducted on 25 schizophrenic patients selected from neuropsychiatric department, and 25 age/sex-matched healthy controls.

Results
Schizophrenic patients showed diminished fractional anisotropy in fornix, corpus callosum, right cingulum, right superior and inferior occipito-frontal fasciculi. Increased mean diffusivity in right inferior occipito-frontal fasciculus, corpus callosum, right thalamus and right basal ganglia were noted in schizophrenic patients. Fractional anisotropy and mean diffusivity had a predictive value for detection of schizophrenic patients.

Conclusions
DTI of white and grey matter tracts is considered a promising tool for diagnosis of schizophrenic patients which usually have prolonged illness, chronic course and poor outcome.
Matching barriers and facilitators to implementation strategies: recommendations for community settings
Authors: Balis Laura E. , Houghtaling Bailey 
Published: November 2023

Abstract
Background
Implementation science aims to improve the integration of evidence-based interventions in real-world settings. While its methods and models could potentially apply to any field with evidence-based interventions, most research thus far has originated in clinical settings. Community settings often have fewer resources, missions beyond health, and a lack of support and expertise to implement evidence-based interventions when compared to many clinical settings. Thus, selecting and tailoring implementation strategies in community settings is particularly challenging, as existing compilations are primarily operationalized through clinical setting terminology. In this debate, we (1) share the process of using an existing match tool to select implementation strategies to increase uptake of nutrition and physical activity policy, systems, and environment interventions in community settings and (2) discuss the challenges of this process to argue that selecting implementation strategies in community settings has limited transferability from clinical settings and may require a unique implementation strategy compilation and pragmatic matching tool.

Matching barriers to implementation strategies
The impetus for this debate paper came from our work selecting implementation strategies to improve the implementation and eventual scaling of nutrition and physical activity policy, systems, and environment interventions in a community settings. We conducted focus groups with practitioners and used the Consolidated Framework for Implementation Research-Expert Recommendations for Implementing Change match tool to select potential implementation strategies to overcome prominent barriers. There was limited congruence between tool outputs and optimal strategies, which may in part be due to differences in context between clinical and community settings. Based on this, we outline needs and recommendations for developing a novel and pragmatic matching tool for researchers and practitioners in community settings.

Conclusions
More work is needed to refine the implementation barrier-strategy matching process to ensure it is relevant, rapid, and rigorous. As leading implementation strategy scholars note, as more researchers document contextual factors and strategies selected to address them, the knowledge base will increase, and refined mapping processes can emerge.
Peptide-modified PAMAM-based bone-targeting RNA delivery system
Authors: Patil Suryaji , Gao Yong-Guang , Qian Airong 
Published: November 2023

Abstract
Background
Osteoporosis, among other bone diseases, has become a prevalent cause of decreased quality of life in older and postmenopausal women. Traditional anti-osteoporotic therapies, though widely prescribed, are limited by a lack of cell- or tissue-specific targeting ability and effectiveness without side effects. Gene therapy is rapidly replacing traditional therapeutics, primarily because of its specific targeting ability and efficiency. Among viral- and non-viral-based gene therapies, the latter is often preferred over the former due to lower cytotoxicity, immunogenicity, and ease of modification with different molecules to improve efficiency and extend gene expression. We designed and synthesized a multifunctional bone-targeting ribonucleic acid (RNA) delivery system based on polyamidoamine (PAMAM). PAMAM was modified with the serine-aspartate-serine-serine-aspartate (SDSSD) peptide to deliver antagomir 138-5p to osteoblasts (MC3T3-E1 cell line) in vitro and in vivo using the ovariectomized (OVX) mouse model.

Results
The results showed that this system was less cytotoxic than polyethylenimine (PEI) and could bind to RNA favorably while maintaining gene delivery ability in vitro. In vivo data showed that the distal tibia and femur of the mice in the PAMAM-SDSSD (PS) + RNA group had improved bone mineral density (BMD), bone mineral content (BMC), and bone volume compared to those in the PS + Negative Control (NC) or OVX groups. Moreover, the femurs of the PS + RNA group mice demonstrated a higher breaking point, stress, stiffness, and elasticity than those of the PS + NC or OVX mice, suggesting improved femur strength in the OVX mice treated with RNA delivered through SDSSD-modified PAMAM.

Conclusion
This study shows that SDSSD modification of PAMAM not only improves gene delivery capacity but also enhances the cell targeting efficiency of nanoparticles towards osteoblasts. The successful delivery of antagomir 138-5p to osteoblasts demonstrates cell-specificity and gene delivery to alleviate osteoporotic symptoms.
Comparing Active Surveillance and Watchful Waiting With Radical Treatment Using Machine Learning Models Among Patients With Prostate Cancer
Authors: Hu Siqi , Chang Chun-Pin , Snyder John , Deshmukh Vikrant , Newman Michael , Date Ankita , Galvao Carlos , Porucznik Christina A. , Gren Lisa H. , Sanchez Alejandro , Lloyd Shane , Haaland Benjamin , O'Neil Brock , Hashibe Mia 
Published: November 2023

PURPOSE In 2021, 59.6% of low-risk patients with prostate cancer were under active surveillance (AS) as their first course of treatment. However, few studies have investigated AS and watchful waiting (WW) separately. The objectives of this study were to develop and validate a population-level machine learning model for distinguishing AS and WW in the conservative treatment group, and to investigate initial cancer management trends from 2004 to 2017 and the risk of chronic diseases among patients with prostate cancer with different treatment modalities. METHODS In a cohort of 18,134 patients with prostate adenocarcinoma diagnosed between 2004 and 2017, 1,926 patients with available AS/WW information were analyzed using machine learning algorithms with 10-fold cross-validation. Models were evaluated using performance metrics and Brier score. Cox proportional hazard models were used to estimate hazard ratios for chronic disease risk. RESULTS Logistic regression models achieved a test area under the receiver operating curve of 0.73, F-score of 0.79, accuracy of 0.71, and Brier score of 0.29, demonstrating good calibration, precision, and recall values. We noted a sharp increase in AS use between 2004 and 2016 among patients with low-risk prostate cancer and a moderate increase among intermediate-risk patients between 2008 and 2017. Compared with the AS group, radical treatment was associated with a lower risk of prostate cancer–specific mortality but higher risks of Alzheimer disease, anemia, glaucoma, hyperlipidemia, and hypertension. CONCLUSION A machine learning approach accurately distinguished AS and WW groups in conservative treatment in this decision analytical model study. Our results provide insight into the necessity to separate AS and WW in population-based studies.
Old “New Media” and Literary Studies before 1960
Authors: Kiséry András , Nee David 
Published: November 2023

Abstract
New media played an important but largely understudied role in the formation of literary studies as a discipline. The dominant tradition of literary criticism has implied that literature was superior to and fully distinct from competing media and that the methods and concepts of literary scholarship were untouched by the emergence of new technological media. This introduction surveys some of the ways in which modern literary scholarship was in fact entangled with new media: from the revolutionary effect of the photostat on textual studies, to the rise of the concept of “orality” in tandem with new techniques for transcribing sound, to twentieth-century literary scholars’ extensive experiments with film and video as novel pedagogical aids. Along with the contributions to this special issue, this introduction shows that revisiting the false starts and dead ends of media-attuned literary scholarship during this formative period can help us defamiliarize our own convictions and open up alternative visions for the place of literary studies in a media-saturated world.
Public Attitudes, Inequities, and Polarization in the Launch of the 988 Lifeline
Authors: Callaghan Timothy , Ferdinand Alva O. , Motta Matt , Lockman Alee , Shrestha Aakriti , Trujillo Kristin Lunz 
Published: November 2023

Abstract
Context: To address the considerable burden of mental health need in the United States, Congress passed the National Suicide Hotline Designation Act in 2020. The act rebranded the national suicide prevention lifeline as 988, a three-digit number akin to 911 for individuals to call in the case of a mental health emergency. Surprisingly little is known about American attitudes toward this new lifeline.
Methods: The authors use a demographically representative survey of 5,482 US adults conducted June 24–28, 2022, to examine the influence of mental health status, partisan identification, and demographic characteristics on public awareness of the new 988 lifeline, public support for the lifeline, and intention to use it.
Findings: The authors find that while only a quarter of Americans are aware of the lifeline, support for the 988 lifeline is widespread, with more than 75% of Americans indicating they would be likely to use the new number if needed. The authors identify key disparities in awareness, support, and intended use, with Republicans, individuals with low socioeconomic status, and Blacks less supportive of the 988 lifeline and in some cases less likely to use it.
Conclusions: The results point to the need for additional interventions that increase public awareness of 988 and reduce disparities in program knowledge, support, and intention to use.