bluuebunny/crossref_metadata_2025_split huggingface dataset:
Video Exposure Monitoring and Position Tracking for Evaluating Particulate and Gas Exposures in a Fully Enclosed Small Arms Firing Range
Authors: Parker Ariel , Wardall Austin , Duran Christin 
Published: January 2022

Abstract
The exposure environment in small arms firing ranges is dynamic since ventilation conditions vary in space and time and instructors continuously move around throughout the range. Understanding the impact of engineering controls and instructor behavior on the levels of particulates and gases in the breathing zone is required for providing recommendations to mitigate exposure. In this study, video exposure monitoring (VEM) and position tracking technologies were used in conjunction with real-time measurements of ultrafine particle (UFP) and carbon monoxide (CO) exposures in the breathing zone of instructors in an enclosed small arms firing range. VEM was completed using Enhanced Video Analysis of Dust Exposure 2.1 developed by the National Institute for Occupational Safety and Health. With this program, video recordings of Combat Arms instructor activity were synced with exposure data collected in real-time during small arms training. Position tracking was completed using a system by Pozyx, which uses ultra-wideband (UWB) technology. Position tracking data was aligned with real-time sensor data via time-synchronization. VEM identified that the largest peaks in UFP and CO concentrations generally occurred when instructors were close to the firing line assisting shooters during live fire and when instructors were located near the center of the range near the back wall where the air supplies transition between the Left-Hand-Side (LHS) and Right-Hand-Side (RHS). The UWB position tracking results agreed with the VEM results, confirming that peak exposures occurred when firing range instructors were near the center of the range close to the back wall where the LHS and RHS air supplies transition. Without these exposure visualization technologies, this observation could not have been made. Thus, exposure visualization is a valuable tool to identify gaps in exposure assessment, although future technologies should focus on automation to expedite analysis.
The Plug-in Graft, the Essential Supplement for a Stable Cartilaginous Framework in Rhinoplasty
Authors: Wu Lehao , Wang Huan , Tian Le , Fan Fei , You Jianjun 
Published: January 2022

Abstract

Background
A stable cartilaginous framework establishes the foundation for a successful rhinoplasty procedure. However, the curvature of the anterior septal angle usually does not match the added tip graft, leaving a structural gap that can cause postoperative rotation of the nasal tip. A supplementary graft is required to fill this gap, consolidating this structure in 3 dimensions.

Objectives
The aim of this study was to detail and validate the utilization of a graft that fills the structural gap, producing a more stabilized framework and better-sustained tip position in the long term.

Methods
The counterrotating force applied intraoperatively and the complications that arose were collected retrospectively. Three-dimensional stereophotogrammetric evaluations were performed. Anthropometric points were analyzed in a blinded fashion. Outcome variables were tip projection, nasal length, Goode’s ratio, and tip rotation. Results were compared statistically.

Results
Thirty-one female patients, ranging in age from 18 to 41 years, completed the study. Intraoperative measurements of rotation indicated an unequivocal stabilizing effect of the plug-in graft. Postoperative analysis showed excellent maintenance of the tip position over time. Tip projection and nasolabial angle decreased slightly over time, but the differences were not statistically different.

Conclusions
The plug-in graft evidently consolidates the entire cartilaginous framework in rib-based rhinoplasty procedures. This anatomically integrated structure establishes the fundamental groundwork which provides uncompromising support for the tip graft, thereby achieving an aesthetically pleasing and long-lasting outcome. When executed properly, this graft is effective in maintaining postoperative tip position, justifying the technical challenges involved and the prolonged operating time.

Level of Evidence: 4
Towards routine employment of computational tools for antimicrobial resistance determination via high-throughput sequencing
Authors: Marini Simone , Mora Rodrigo A , Boucher Christina , Robertson Noyes Noelle , Prosperi Mattia 
Published: January 2022

AbstractAntimicrobial resistance (AMR) is a growing threat to public health and farming at large. In clinical and veterinary practice, timely characterization of the antibiotic susceptibility profile of bacterial infections is a crucial step in optimizing treatment. High-throughput sequencing is a promising option for clinical point-of-care and ecological surveillance, opening the opportunity to develop genotyping-based AMR determination as a possibly faster alternative to phenotypic testing. In the present work, we compare the performance of state-of-the-art methods for detection of AMR using high-throughput sequencing data from clinical settings. We consider five computational approaches based on alignment (AMRPlusPlus), deep learning (DeepARG), k-mer genomic signatures (KARGA, ResFinder) or hidden Markov models (Meta-MARC). We use an extensive collection of 585 isolates with available AMR resistance profiles determined by phenotypic tests across nine antibiotic classes. We show how the prediction landscape of AMR classifiers is highly heterogeneous, with balanced accuracy varying from 0.40 to 0.92. Although some algorithms—ResFinder, KARGA and AMRPlusPlus—exhibit overall better balanced accuracy than others, the high per-AMR-class variance and related findings suggest that: (1) all algorithms might be subject to sampling bias both in data repositories used for training and experimental/clinical settings; and (2) a portion of clinical samples might contain uncharacterized AMR genes that the algorithms—mostly trained on known AMR genes—fail to generalize upon. These results lead us to formulate practical advice for software configuration and application, and give suggestions for future study designs to further develop AMR prediction tools from proof-of-concept to bedside.
Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning
Authors: Zhang Biao , Liu Dong , Zhang Yang , Shen Hong-Bin , Zhang Gui-Jun 
Published: January 2022

Abstract
With the rapid progress of deep learning in cryo-electron microscopy and protein structure prediction, improving the accuracy of the protein structure model by using a density map and predicted contact/distance map through deep learning has become an urgent need for robust methods. Thus, designing an effective protein structure optimization strategy based on the density map and predicted contact/distance map is critical to improving the accuracy of structure refinement. In this article, a protein structure optimization method based on the density map and predicted contact/distance map by deep-learning technology was proposed in accordance with the result of matching between the density map and the initial model. Physics- and knowledge-based energy functions, integrated with Cryo-EM density map data and deep-learning data, were used to optimize the protein structure in the simulation. The dynamic confidence score was introduced to the iterative process for choosing whether it is a density map or a contact/distance map to dominate the movement in the simulation to improve the accuracy of refinement. The protocol was tested on a large set of 224 non-homologous membrane proteins and generated 214 structural models with correct folds, where 4.5% of structural models were generated from structural models with incorrect folds. Compared with other state-of-the-art methods, the major advantage of the proposed methods lies in the skills for using density map and contact/distance map in the simulation, as well as the new energy function in the re-assembly simulations. Overall, the results demonstrated that this strategy is a valuable approach and ready to use for atomic-level structure refinement using cryo-EM density map and predicted contact/distance map.
ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images
Authors: Zhang Xiao-Chen , Yi Jia-Cai , Yang Guo-Ping , Wu Cheng-Kun , Hou Ting-Jun , Cao Dong-Sheng 
Published: January 2022

Abstract
Structural information for chemical compounds is often described by pictorial images in most scientific documents, which cannot be easily understood and manipulated by computers. This dilemma makes optical chemical structure recognition (OCSR) an essential tool for automatically mining knowledge from an enormous amount of literature. However, existing OCSR methods fall far short of our expectations for realistic requirements due to their poor recovery accuracy. In this paper, we developed a deep neural network model named ABC-Net (Atom and Bond Center Network) to predict graph structures directly. Based on the divide-and-conquer principle, we propose to model an atom or a bond as a single point in the center. In this way, we can leverage a fully convolutional neural network (CNN) to generate a series of heat-maps to identify these points and predict relevant properties, such as atom types, atom charges, bond types and other properties. Thus, the molecular structure can be recovered by assembling the detected atoms and bonds. Our approach integrates all the detection and property prediction tasks into a single fully CNN, which is scalable and capable of processing molecular images quite efficiently. Experimental results demonstrate that our method could achieve a significant improvement in recognition performance compared with publicly available tools. The proposed method could be considered as a promising solution to OCSR problems and a starting point for the acquisition of molecular information in the literature.
Arab Social Workers’ Burnout in Welfare Bureaus: Expressions, Reasons, Implications and Coping-Mechanisms
Authors: Mahajne Ibrahim 
Published: January 2022

Abstract
The research investigated expressions of, reasons, implications and coping strategies for burnout according to twenty-three Arab ethnic-national minority social workers in Arab welfare bureaus in Israel. Interview data indicated that burnout is expressed in somatisation and interpersonal behaviours with clients and colleagues. As in Arab culture, personal emotional suffering is not mentioned. Micro- and meso-level factors were ignored. Macro-level dependence on the establishment includes professional training and government policies inappropriate for the Arab population’s unique needs. Interviewees mentioned only minor consequences, ensuring their continued employment. They rationalised and universalised burnout as normative, sufficing with indirect coping strategies, for example social events.
Peripheral neuropathy in Parkinson’s disease: prevalence and functional impact on gait and balance
Authors: Corrà Marta Francisca , Vila-Chã Nuno , Sardoeira Ana , Hansen Clint , Sousa Ana Paula , Reis Inês , Sambayeta Firmina , Damásio Joana , Calejo Margarida , Schicketmueller Andreas , Laranjinha Inês , Salgado Paula , Taipa Ricardo , Magalhães Rui , Correia Manuel , Maetzler Walter , Maia Luís F 
Published: January 2022

Abstract
Peripheral neuropathy is a common problem in patients with Parkinson’s disease. Peripheral neuropathy’s prevalence in Parkinson’s disease varies between 4.8–55%, compared with 9% in the general population. It remains unclear whether peripheral neuropathy leads to decreased motor performance in Parkinson’s disease, resulting in impaired mobility and increased balance deficits. We aimed to determine the prevalence and type of peripheral neuropathy in Parkinson’s disease patients and evaluate its functional impact on gait and balance.
A cohort of consecutive Parkinson’s disease patients assessed by movement disorders specialists based on the UK Brain Bank criteria underwent clinical, neurophysiological (nerve conduction studies and quantitative sensory testing) and neuropathological (intraepidermal nerve fibre density in skin biopsy punches) evaluation to characterize the peripheral neuropathy type and aetiology using a cross-sectional design. Gait and balance were characterized using wearable health-technology in OFF and ON medication states, and the main parameters were extracted using validated algorithms.
A total of 99 Parkinson’s disease participants with a mean age of 67.2 (±10) years and mean disease duration of 6.5 (±5) years were assessed. Based on a comprehensive clinical, neurophysiological and neuropathological evaluation, we found that 40.4% of Parkinson’s disease patients presented peripheral neuropathy, with a predominance of small fibre neuropathy (70% of the group). In the OFF state, the presence of peripheral neuropathy was significantly associated with shorter stride length (P = 0.029), slower gait speed (P = 0.005) and smaller toe-off angles (P = 0.002) during straight walking; significantly slower speed (P = 0.019) and smaller toe-off angles (P = 0.007) were also observed during circular walking. In the ON state, the above effects remained, albeit moderately reduced. With regard to balance, significant differences between Parkinson’s disease patients with and without peripheral neuropathy were observed in the OFF medication state during stance with closed eyes on a foam surface. In the ON states, these differences were no longer observable.
We showed that peripheral neuropathy is common in Parkinson’s disease and influences gait and balance parameters, as measured with mobile health-technology. Our study supports that peripheral neuropathy recognition and directed treatment should be pursued in order to improve gait in Parkinson’s disease patients and minimize balance-related disability, targeting individualized medical care.
Efficacy of probiotics or synbiotics for critically ill adult patients: a systematic review and meta-analysis of randomized controlled trials
Authors: Wang Kai , Zeng Qin , Li Ke-xun , Wang Yu , Wang Lu , Sun Ming-wei , Zeng Jun , Jiang Hua 
Published: January 2022

Abstract

Background
Microbial dysbiosis in critically ill patients is a leading cause of mortality and septic complications. Probiotics and synbiotics have emerged as novel therapy on gut microbiota to prevent septic complications. However, current evidence on their effects is conflicting. This work aims to systematically review the impact of probiotics or synbiotics in critically ill adult patients.

Methods
A comprehensive search of the PubMed, CBM, Embase, CENTRAL, ISI, and CNKI databases was performed to identify randomized controlled trials that evaluate probiotics or synbiotics in critically ill patients. The quality assessment was based on the modified Jadad's score scale and the Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.1. The major outcome measure was mortality. Secondary outcomes included incidence of septic complications, sepsis incidence, length of intensive care unit (ICU) stay, incidence of non-septic complication, and ventilator day. Data synthesis was conduct by Review Manager 5.4.

Results
A total of 25 randomized controlled trials reporting on 5049 critically ill patients were included. In the intervention group, 2520 participants received probiotics or synbiotics, whereas 2529 participants received standard care or placebo. Pooling data from randomized controlled trials demonstrated a significant reduction in the incidence of ventilator-associated pneumonia (VAP) in the treatment group [(risk ratio (RR) 0.86; 95% confidence interval (CI): 0.78–0.95; p &lt; 0.003, I2 = 85%)]. However, in the subgroup analysis, the reduction of incidence of VAP was only significant in patients receiving synbiotics (RR = 0.61, 95% CI: 0.47–0.80, p = 0.0004, I2 = 40%) and not significant in those receiving only probiotics (RR = 0.91, 95% CI: 0.82–1.01, p = 0.07, I2 = 65%). Moreover, sepsis incidence of critically ill patients was only significantly reduced by the addition of synbiotics (RR = 0.41; 95% CI: 0.22–0.72, p = 0.005, I2 = 0%). The incidence of ICU-acquired infections was significantly reduced by the synbiotics therapy (RR = 0.72; 95% CI: 0.58–0.89, p = 0.0007, I2 = 79%). There was no significant difference in mortality, diarrhea, or length of ICU stay between the treatment and control groups.

Conclusions
Synbiotics is an effective and safe nutrition therapy in reducing septic complications in critically ill patients. However, in such patients, administration of probiotics alone compared with placebo resulted in no difference in the septic complications.
A combined treatment with melatonin and andrographis promotes autophagy and anticancer activity in colorectal cancer
Authors: Zhao Yinghui , Wang Chuanxin , Goel Ajay 
Published: January 2022

Abstract
Colorectal cancer (CRC) is one of the most frequent malignancies worldwide and remains one of the leading causes of cancer-related deaths in the USA. The high degree of morbidity and mortality associated with this disease is largely due to the inadequate efficacy of current treatments as well the development of chemoresistance. In recent years, several pharmaceutical agents screened from natural products have shown the promise to offer a safe, inexpensive and synergistically multi-targeted treatment option in various cancers. Given the growing evidence of anti-carcinogenic properties of two natural compounds, melatonin (MLT) and andrographis (Andro), we aimed to evaluate their synergistic anticancer effects in CRC. We demonstrate that indeed these two compounds possessed a synergistic anticancer effect in terms of their ability to inhibit cell viability, suppression of colony-formation and induction of apoptosis (P &lt; 0.05). In line with our in vitro findings, we were able to validate this combinatorial anticancer activity in xenograft animal models (P &lt; 0.001) as well as tumor-derived 3D organoids (P &lt; 0.01). RNA-sequencing analysis revealed candidate pathways and genes that mediated antitumor efficacy of MLT and Andro in CRC, among which autophagy pathway and related genes, including NR4A1, CTSL and Atg12, were found to be primarily responsible for the increased anticancer effect by the two natural products. In conclusion, our data reveal a potent and synergistic therapeutic effect of MLT and Andro in the treatment of CRC and provides a rationale for suppressing autophagy in cancer cells as a potential therapeutic strategy for CRC.
Epidemiological evidence for associations between variants in microRNA and cancer risk
Authors: Tian Jie , Dong Yingxian , Chang Shuai , Wang Yan , Shen Cheng , Che Guowei 
Published: January 2022

Abstract
Numerous papers have reported variants in microRNAs (miRNAs) associated with cancer risk; these results, however, are controversial. We seek to offer an updated, comprehensive synopsis of genetic associations between single nucleotide polymorphisms (SNPs) in miRNAs and cancer risk. We did a systematic field synopsis and meta-analysis to investigate 29 SNPs in 24 miRNAs associated with risk of 18 different kinds of cancer based on data from 247 eligible articles. We graded levels of cumulative epidemiological evidence of significant association using Venice criteria and a false-positive report probability (FPRP) test. We constructed functional annotations for these variants using data from the Encyclopedia of DNA Elements Project. We used FPRP to find additional noteworthy associations between 278 SNPs in 117 miRNAs and risk of 26 cancers based on each SNP with one data source. Sixteen SNPs were statistically associated with risk of 17 cancers. We graded the cumulative epidemiological evidence as strong for statistical associations between 10 SNPs in 8 miRNAs and risk of 11 cancers, moderate for 9 SNPs with 12 cancers and weak for 11 SNPs with 11 cancers. Bioinformatics analysis suggested that the SNPs with strong evidence might fall in putative functional regions. In addition, 38 significant associations were observed in 38 SNPs and risk of 13 cancers. This study offered a comprehensive research on miRNA gene variants and cancer risk and provided referenced information for the genetic predisposition to cancer risk in future research.
Differential auditory cortical development in left and right cochlear implanted children
Authors: Wang Yuyang , Wu Meiyun , Wu Kun , Liu Haotian , Wu Shinan , Zhang Zhikai , Liu Min , Wei Chaogang , Zhang Yu-Xuan , Liu Yuhe 
Published: January 2022

Abstract
Unilateral aural stimulation has been shown to cause massive cortical reorganization in brain with congenital deafness, particularly during the sensitive period of brain development. However, it is unclear which side of stimulation provides most advantages for auditory development. The left hemisphere dominance of speech and linguistic processing in normal hearing adult brain has led to the assumption of functional and developmental advantages of right over left implantation, but existing evidence is controversial. To test this assumption and provide evidence for clinical choice, we examined 34 prelingually deaf children with unilateral cochlear implants using near-infrared spectroscopy. While controlling for age of implantation, residual hearing, and dominant hand, cortical processing of speech showed neither developmental progress nor influence of implantation side weeks to months after implant activation. In sharp contrast, for nonspeech (music signal vs. noise) processing, left implantation showed functional advantages over right implantation that were not yet discernable using clinical, questionnaire-based outcome measures. These findings support the notion that the right hemisphere develops earlier and is better preserved from adverse environmental influences than its left counterpart. This study thus provides, to our knowledge, the first evidence for differential influences of left and right auditory peripheral stimulation on early cortical development of the human brain.
Robust Image Hashing With Saliency Map And Sparse Model
Authors: Yu Mengzhu , Tang Zhenjun , Li Zhixin , Liang Xiaoping , Zhang Xianquan 
Published: January 2022

Abstract
Image hashing is an effective technology for extensive image applications, such as retrieval, authentication and copy detection. This paper designs a new image hashing scheme based on saliency map and sparse model. The major contributions are twofold. The first contribution is the construction of a weighted image representation by combining a visual attention model called Itti model and the matrix of color vector angle (CVA). Since the Itti model can efficiently detect saliency map and CVA fully captures color information of image, they contribute to a visually robust and discriminative image representation. The second contribution is the hash extraction from the weighted image representation via sparse model. A classical sparse model called robust principal component analysis is exploited to decompose the weighted image representation into a low-rank component and a sparse component. As the low-rank component can describe intrinsic structure of image, hash calculation with low-rank component can achieve good discrimination. The efficiencies of the proposed scheme are validated by extensive experiments with open databases. The results demonstrate that the proposed scheme is superior to some state-of-the-art schemes in terms of classification performance between robustness and discrimination.