PURPOSE: To develop a series of recommendations for the contemporary management management of staghorn calculi and to provide a clinical framework for urologists treating patients with these complex stones.
METHODS: A comprehensive literature search for articles published in English between 01/01/1976 and 31/12/2022 in the PubMed, OVID, Embase and Medline database is performed. A series of recommendations are developed and individually graded following the review of literature and panel discussion.
RESULTS: The definition, pathogenesis, pathophysiology, preoperative evaluation, intraoperative treatment strategies and procedural advice, early postoperative management, follow up and prevention of stone recurrence are summarized in the present document.
CONCLUSION: A series of recommendations regarding the management of staghorn calculi, along with related commentary and supporting documentation offered in the present guideline is intended to provide a clinical framework for the practicing urologists in the management of staghorn calculi.
OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42995-022-00160-z.
METHOD: A cross-sectional study was conducted, using questionnaires sent to selected medical staff in a public hospital in Shandong, China (N = 1012). Multiple regression analysis was used to investigate how psychological strains influencing life satisfactions among medical staff.
RESULTS: The findings indicate that aspiration strain and deprivation strain have significantly negative impact on medical staff's life satisfaction even with other variables controlled for. Weekly working hour was a significant predictor for life satisfaction. Family factors, such as marital status and kids in the family as well as social support were important factors in influencing individuals' life satisfaction.
CONCLUSION: The current study highlights the negative associations between aspiration strain, deprivation strain and life satisfaction. The result underlines the importance of actions taken to prevent and combat psychological strains. It also provides some evidence for policy makers to improve the work environment for medical staff, such as reduce weekly working hours and enhance social support in order to increase medical staff's life satisfaction.
METHODS: Positron emission tomography (PET) and computed tomography (CT) image data from 97 patients with LC and 77 patients with TB nodules were collected. One hundred radiomic features were extracted from both PET and CT imaging using the pyradiomics platform, and 2048 deep learning features were obtained through a residual neural network approach. Four models included traditional machine learning model with radiomic features as input (traditional radiomics), a deep learning model with separate input of image features (deep convolutional neural networks [DCNN]), a deep learning model with two inputs of radiomic features and deep learning features (radiomics-DCNN) and a deep learning model with inputs of radiomic features and deep learning features and clinical information (integrated model). The models were evaluated using area under the curve (AUC), sensitivity, accuracy, specificity, and F1-score metrics.
RESULTS: The results of the classification of TB nodules and LC showed that the integrated model achieved an AUC of 0.84 (0.82-0.88), sensitivity of 0.85 (0.80-0.88), and specificity of 0.84 (0.83-0.87), performing better than the other models.
CONCLUSION: The integrated model was found to be the best classification model in the diagnosis of TB nodules and solid LC.
METHODS: Novel Vibrio phage vB_ValR_NF infecting Vibrio alginolyticus was isolated from the coastal waters of Qingdao during the Ulva prolifera blooms, Characterization and genomic feature of phage vB_ValR_NF has been analysed using phage isolation, sequencing and metagenome method.
RESULTS AND DISCUSSION: Phage vB_ValR_NF has a siphoviral morphology (icosahedral head 114±1 nm in diameter; a tail length of 231±1 nm), a short latent period (30 minutes) and a large burst size (113 virions per cell), and the thermal/pH stability study showed that phage vB_ValR_NF was highly tolerant to a range of pHs (4-12) and temperatures (-20 - 45 °C), respectively. Host range analysis suggests that phage vB_ValR_NF not only has a high inhibitory ability against the host strain V. alginolyticus, but also can infect 7 other Vibrio strains. In addition, the phage vB_ValR_NF has a double-stranded 44, 507 bp DNA genome, with 43.10 % GC content and 75 open reading frames. Three auxiliary metabolic genes associated with aldehyde dehydrogenase, serine/threonine protein phosphatase and calcineurin-like phosphoesterase were predicted, might help the host V. alginolyticus occupy the survival advantage, thus improving the survival chance of phage vB_ValR_NF under harsh conditions. This point can be supported by the higher abundance of phage vB_ValR_NF during the U. prolifera blooms than in other marine environments. Further phylogenetic and genomic analysis shows that the viral group represented by Vibrio phage vB_ValR_NF is different from other well-defined reference viruses, and can be classified into a new family, named Ruirongviridae. In general, as a new marine phage infecting V. alginolyticus, phage vB_ValR_NF provides basic information for further molecular research on phage-host interactions and evolution, and may unravel a novel insight into changes in the community structure of organisms during the U. prolifera blooms. At the same time, its high tolerance to extreme conditions and excellent bactericidal ability will become important reference factors when evaluating the potential of phage vB_ValR_NF in bacteriophage therapy in the future.
RESULTS: Here, we reported the first Oceanospirillum phage, vB_OliS_GJ44, which was assembled into a 33,786 bp linear dsDNA genome, which includes abundant tail-related and recombinant proteins. The recombinant module was highly adapted to the host, according to the tetranucleotides correlations. Genomic and morphological analyses identified vB_OliS_GJ44 as a siphovirus, however, due to the distant evolutionary relationship with any other known siphovirus, it is proposed that this virus could be classified as the type phage of a new Oceanospirivirus genus within the Siphoviridae family. vB_OliS_GJ44 showed synteny with six uncultured phages, which supports its representation in uncultured environmental viral contigs from metagenomics. Homologs of several vB_OliS_GJ44 genes have mostly been found in marine metagenomes, suggesting the prevalence of this phage genus in the oceans.
CONCLUSIONS: These results describe the first Oceanospirillum phage, vB_OliS_GJ44, that represents a novel viral cluster and exhibits interesting genetic features related to phage-host interactions and evolution. Thus, we propose a new viral genus Oceanospirivirus within the Siphoviridae family to reconcile this cluster, with vB_OliS_GJ44 as a representative member.