Luminescent lanthanide mixed N-phthaloylglycinate and terephthalate coordination polymers: Structural and optical properties.

A new class of lanthanide mixed-carboxylate ligands compounds with formula {[Ln2 (phthgly)4 (bdc)(H2 O)6 ]·(H2 O)4 }∞ , labelled as Ln3+ : Eu (1) and Gd (2) coordination polymers (CP) were synthesized under mild reaction conditions between lanthanide nitrate salts and a solution of N-phthaloylglycine (phthgly) and terephthalic (bdc) ligands. The (1) and (2) coordination polymers were formed by symmetric binuclear units, in which phthgly and bdc carboxylate ligands are coordinated to the lanthanide ions by different coordination modes. Surprisingly, all organic ligands participate in hydrogen bonding interactions, forming an extremally rigid crystalline structure. The red narrow emission bands from the 5 D0 →7 FJ transitions of the Eu3+ ion show a high colour purity. The intramolecular energy transfer process from L→Eu3+ ion has been discussed. The experimental intensity parameters (Ω2,4 ) reflect lower angular distortion and polarizability of the chemical environment around the metal ion compared with other Eu3+ compounds reported in the literature. This novel class of coordination polymer offers a more attractive platform for developing luminescent functional materials for different applications.

Brain Maturation Patterns on Normalized FLAIR MR Imaging in Children and Adolescents.

BACKGROUND AND PURPOSE: Signal analysis of FLAIR sequences is gaining momentum for studying neurodevelopment and brain maturation, but FLAIR intensity varies across scanners and needs to be normalized. This study aimed to establish normative values for standardized FLAIR intensity in the pediatric brain. MATERIALS AND METHODS: A new automated algorithm for signal normalization was used to standardize FLAIR intensity across scanners and subjects. Mean intensity was extracted from GM, WM, deep GM, and cortical GM regions. Regression curves were fitted across the pediatric age range, and ANOVA was used to investigate intensity differences across age groups. Correlations between intensity and regional volume were also examined. RESULTS: We analyzed 429 pediatric FLAIR sequences in children 2-19 years of age with a median age of 11.2 years, including 199 males and 230 females. WM intensity had a parabolic relationship with age, with significant differences between various age groups (P < .05). GM and cortical GM intensity increased over the pediatric age range, with significant differences between early childhood and adolescence (P < .05). There were no significant relationships between volume and intensity in early childhood, while there were significant positive and negative correlations (P < .05) in WM and GM, respectively, for increasing age groups. Only the oldest age group showed significant differences between males and females (P < .05). CONCLUSIONS: This work presents a FLAIR intensity standardization algorithm to normalize intensity across large data sets, which allows FLAIR intensity to be used to compare regions and individuals as a surrogate measure of the developing pediatric brain.

T2-FLAIR Mismatch Sign in Pediatric Low-Grade Glioma.

BACKGROUND AND PURPOSE: No qualitative imaging feature currently predicts molecular alterations of pediatric low-grade gliomas with high sensitivity or specificity. The T2-FLAIR mismatch sign predicts IDH-mutated 1p19q noncodeleted adult gliomas with high specificity. We aimed to assess the significance of the T2-FLAIR mismatch sign in pediatric low-grade gliomas. MATERIALS AND METHODS: Pretreatment MR images acquired between January 2001 and August 2018 in pediatric patients with pediatric low-grade gliomas were retrospectively identified. Inclusion criteria were the following: 1) 0-18 years of age, 2) availability of molecular information in histopathologically confirmed cases, and 3) availability of preoperative brain MR imaging with non-motion-degraded T2-weighted and FLAIR sequences. Spinal cord tumors were excluded. RESULTS: Three hundred forty-nine patients were included (187 boys; mean age, 8.7 [SD, 4.8] years; range, 0.5-17.7 years). KIAA1549-B-Raf proto-oncogene (BRAF) fusion and BRAF p.V600E mutation were the most common molecular markers (n = 148, 42%, and n = 73, 20.7%, respectively). The T2-FLAIR mismatch sign was present in 25 patients (7.2%). Of these, 9 were dysembryoplastic neuroepithelial tumors; 8, low-grade astrocytomas; 5, diffuse astrocytomas; 1, a pilocytic astrocytoma; 1, a glioneuronal tumor; and 1, an angiocentric glioma. None of the 25 T2-FLAIR mismatch pediatric low-grade gliomas were BRAF p.V600E-mutated. Fourteen of 25 pediatric low-grade gliomas with the T2-FLAIR mismatch sign had rare molecular alterations, while the molecular subtype was unknown for 11 tumors. CONCLUSIONS: The T2-FLAIR mismatch sign was not observed in the common molecular alterations, BRAF p.V600E-mutated and KIAA1549-BRAF fused pediatric low-grade gliomas, while it was encountered in pediatric low-grade gliomas with rare pediatric molecular alterations.

Ensuring privacy protection in the era of big laparoscopic video data: development and validation of an inside outside discrimination algorithm (IODA).

BACKGROUND: Laparoscopic videos are increasingly being used for surgical artificial intelligence (AI) and big data analysis. The purpose of this study was to ensure data privacy in video recordings of laparoscopic surgery by censoring extraabdominal parts. An inside-outside-discrimination algorithm (IODA) was developed to ensure privacy protection while maximizing the remaining video data. METHODS: IODAs neural network architecture was based on a pretrained AlexNet augmented with a long-short-term-memory. The data set for algorithm training and testing contained a total of 100 laparoscopic surgery videos of 23 different operations with a total video length of 207 h (124 min ± 100 min per video) resulting in 18,507,217 frames (185,965 ± 149,718 frames per video). Each video frame was tagged either as abdominal cavity, trocar, operation site, outside for cleaning, or translucent trocar. For algorithm testing, a stratified fivefold cross-validation was used. RESULTS: The distribution of annotated classes were abdominal cavity 81.39%, trocar 1.39%, outside operation site 16.07%, outside for cleaning 1.08%, and translucent trocar 0.07%. Algorithm training on binary or all five classes showed similar excellent results for classifying outside frames with a mean F1-score of 0.96 ± 0.01 and 0.97 ± 0.01, sensitivity of 0.97 ± 0.02 and 0.0.97 ± 0.01, and a false positive rate of 0.99 ± 0.01 and 0.99 ± 0.01, respectively. CONCLUSION: IODA is able to discriminate between inside and outside with a high certainty. In particular, only a few outside frames are misclassified as inside and therefore at risk for privacy breach. The anonymized videos can be used for multi-centric development of surgical AI, quality management or educational purposes. In contrast to expensive commercial solutions, IODA is made open source and can be improved by the scientific community.

Video-based learning of coping strategies for common errors improves laparoscopy training-a randomized study.

AIMS: The aim of this study was to investigate whether shifting the focus to solution orientation and developing coping strategies for common errors could increase the efficiency of laparoscopic training and influence learning motivation. The concept of coping has been particularly defined by the psychologist Richard Lazarus [Lazarus and Folkman in Stress, appraisal, and coping, Springer publishing company, New York, 1984]. Based on this model, we examined the use of observational learning with a coping model for its effectiveness as a basic teaching model in laparoscopic training. METHODS: 55 laparoscopically naive medical students learned a standardized laparoscopic knot tying technique with video-based instructions. The control group was only offered a mastery video that showed the ideal technique and was free from mistakes. The intervention group was instructed on active error analysis and watched freely selectable videos of common errors including solution strategies (coping model) in addition to the mastery videos. RESULTS: There was no statistically significant difference between the intervention and control groups for number of knot tying attempts until proficiency was reached (18.8 ± 5.5 vs. 21.3 ± 6.5, p = 0.142). However, there was a significantly higher fraction of knots achieving technical proficiency in the intervention group after first use of the coping model (0.7 ± 0.1 vs. 0.6 ± 0.2, p = 0.026). Additionally, the proportion of blinded attempts that met the criteria for technical proficiency was significantly higher for the intervention group at 60.9% vs. 38.0% in control group (p = 0.021). The motivational subscore "interest" of the validated score on current motivation (QCM) was significantly higher for the intervention group (p = 0.032), as well as subjective learning benefit (p = 0.002) and error awareness (p < 0.001). CONCLUSION: Using video-based learning of coping strategies for common errors improves learning motivation and understanding of the technique with a significant difference in its qualitative implementation in laparoscopy training. The ability to think in a solution-oriented, independent way is necessary in surgery in order to recognize and adequately deal with technical difficulties and complications.

Dynamic alpha factor prediction with operating data - a machine learning approach to model oxygen transfer dynamics in activated sludge.

Aeration is an energy-intensive process of aerobic biological wastewater treatment. An accurate model of oxygen transfer dynamics in activated sludge tanks would improve design and operation of aeration systems. Such a model should consider spatial and diurnal variation of α-factor as well as site-specific conditions that impact oxygen transfer. For this dynamic prediction a machine learning approach was used for the first time. The data-driven method was based on long-term ex-situ off-gas measurements with pilot-scale reactors (5.8 m height, 8.3 m3 vol) coupled to full-scale activated sludge tanks on the sites of two conventional and a two-stage activated sludge treatment plant. The ex-situ off-gas method allowed to quantify theoretical off-gas parameters in non-aerated zones and thus consider the whole activated sludge tank. We introduced the α0-factor to compare aerated and non-aerated zones under nonsteady-state conditions. Like the established α-factor for steady-state conditions, the α0-factor describes oxygen transfer inhibiting effects in activated sludge. α0-factor was lowest in upstream denitrification zones. This indicates an anoxic elimination of oxygen transfer inhibiting wastewater contaminants which improved oxygen transfer in subsequent aerobic zones. Random Forest models predicted α0-factor reliably in all examined activated sludge tanks even for stormwater events and seasonal variation. Model development only required online sensor data already available to operators. Our results suggest that machine learning models can dynamically predict α-factors in a variety of activated sludge processes, thus considering site-specific conditions in model training without manual calibration.

Serious gaming and virtual reality in the multimodal training of laparoscopic inguinal hernia repair: a randomized crossover study.

BACKGROUND: The aim of this study was to assess the transferability of surgical skills for the laparoscopic hernia module between the serious game Touch Surgery™ (TS) and the virtual reality (VR) trainer Lap Mentor™. Furthermore, this study aimed to collect validity evidence and to discuss "sources of validity evidence" for the findings using the laparoscopic inguinal hernia module on TS. METHODS: In a randomized crossover study, medical students (n = 40) in their clinical years performed laparoscopic inguinal hernia modules on TS and the VR trainer. TS group started with "Laparoscopic Inguinal Hernia Module" on TS (phase 1: Preparation, phase 2: Port Placement and Hernia Repair), performed the module first in training, then in test mode until proficiency was reached. VR group started with "Inguinal Hernia Module" on the VR trainer (task 1: Anatomy Identification, task 2: Incision and Dissection) and also performed the module until proficiency. Once proficiency reached in the first modality, the groups performed the other training modality until reaching proficiency. Primary endpoint was the number of attempts needed to achieve proficiency for each group for each task/phase. RESULTS: Students starting with TS needed significantly less attempts to reach proficiency for task 1 on the VR trainer than students who started with the VR trainer (TS = 2.7 ± 0.6 vs. VR = 3.2 ± 0.7; p = 0.028). No significant differences for task 2 were observed between groups (TS = 2.3 ± 1.1 vs. VR = 2.1 ± 0.8; p = 0.524). For both phases on TS, no significant skill transfer from the VR trainer to TS was observed. Aspects of validity evidence for the module on TS were collected. CONCLUSION: The results show that TS brought additional benefit to improve performances on the VR trainer for task 1 but not for task 2. Skill transfer from the VR trainer to TS could not be shown. VR and TS should thus be used in combination with TS first in multimodal training to ensure optimal training conditions.

Nurse Preceptors' Experiences of an Online Strength-Based Nursing Course in Clinical Teaching.

Background: Online educational programs for nurse preceptors have been created based on various theoretical frameworks; however, no programs using a Strengths-Based Nursing (SBN) approach could be located. Purpose: This qualitative descriptive study explored the nurse preceptors' experiences in using a SBN approach to provide clinical teaching to nursing students after completing an online SBN clinical teaching course. Methods: Semi-structured interviews were conducted with six nurses. Data was thematically analyzed. Findings: Although their levels of familiarity with SBN varied, all preceptors acknowledged that using a SBN approach in clinical teaching benefits both students and educators. They reported that it empowered students and that it allowed them to discover their strengths. Getting to know their students helped the preceptors provide tailored learning experiences and feedback. Using the SBN approach simultaneously enhanced the preceptors' self-confidence and created opportunities for shared learning. Conclusion: Using a strengths' approach offers nurse preceptors a powerful tool to facilitate student learning and skills development in clinical practice.

Secondary prevention in diabetic and nondiabetic coronary heart disease patients: Insights from the German subset of the hospital arm of the EUROASPIRE IV and V surveys.

BACKGROUND: Patients with coronary heart disease (CHD) with and without diabetes mellitus have an increased risk of recurrent events requiring multifactorial secondary prevention of cardiovascular risk factors. We compared prevalences of cardiovascular risk factors and its determinants including lifestyle, pharmacotherapy and diabetes mellitus among patients with chronic CHD examined within the fourth and fifth EUROASPIRE surveys (EA-IV, 2012-13; and EA-V, 2016-17) in Germany. METHODS: The EA initiative iteratively conducts European-wide multicenter surveys investigating the quality of secondary prevention in chronic CHD patients aged 18 to 79 years. The data collection in Germany was performed during a comprehensive baseline visit at study centers in Würzburg (EA-IV, EA-V), Halle (EA-V), and Tübingen (EA-V). RESULTS: 384 EA-V participants (median age 69.0 years, 81.3% male) and 536 EA-IV participants (median age 68.7 years, 82.3% male) were examined. Comparing EA-IV and EA-V, no relevant differences in risk factor prevalence and lifestyle changes were observed with the exception of lower LDL cholesterol levels in EA-V. Prevalence of unrecognized diabetes was significantly lower in EA-V as compared to EA-IV (11.8% vs. 19.6%) while the proportion of prediabetes was similarly high in the remaining population (62.1% vs. 61.0%). CONCLUSION: Between 2012 and 2017, a modest decrease in LDL cholesterol levels was observed, while no differences in blood pressure control and body weight were apparent in chronic CHD patients in Germany. Although the prevalence of unrecognized diabetes decreased in the later study period, the proportion of normoglycemic patients was low. As pharmacotherapy appeared fairly well implemented, stronger efforts towards lifestyle interventions, mental health programs and cardiac rehabilitation might help to improve risk factor profiles in chronic CHD patients.

The Evolution of Feeding Mechanics in the Danioninae, or Why Giant Danios Don't Suck Like Zebrafish.

By linking anatomical structure to mechanical performance we can improve our understanding of how selection shapes morphology. Here we examined the functional morphology of feeding in fishes of the subfamily Danioninae (order Cypriniformes) to determine aspects of cranial evolution connected with their trophic diversification. The Danioninae comprise three major lineages and each employs a different feeding strategy. We gathered data on skull form and function from species in each clade, then assessed their evolutionary dynamics using phylogenetic-comparative methods. Differences between clades are strongly associated with differences in jaw protrusion. The paedomorphic Danionella clade does not use jaw protrusion at all, members of the Danio clade use jaw protrusion for suction production and prey capture, and members of the sister clade to Danio (e.g., Devario and Microdevario) use jaw protrusion to retain prey after capture. The shape of the premaxillary bone is a major determinant of protrusion ability, and premaxilla morphology in each of these lineages is consistent with their protrusion strategies. Premaxilla shapes have evolved rapidly, which indicates that they have been subjected to strong selection. We compared premaxilla development in giant danio (Devario aequipinnatus) and zebrafish (Danio rerio) and discuss a developmental mechanism that could shift danionine fishes between the feeding strategies employed by these species and their respective clades. We also identified a highly integrated evolutionary module that has been an important factor in the evolution of trophic mechanics within the Danioninae.

Relationship between psychological characteristics, personality traits, and training on performance in a neonatal resuscitation scenario: A machine learning based analysis.

Background: In life-threatening emergency events, prompt decision-making and accurate reactions are essential for saving a human's life. Some of these skills can be improved by regular simulation trainings. However, besides these factors, individual characteristics may play a significant role in the patients' outcome after a resuscitation event. This study aimed to differentiate personality characteristics of team members who take responsibility for their actions, contextualizing the effect of training on resuscitation performance. Methods: Six hundred and two third-year medical students were asked to answer psychological and personality questionnaires. Fifty-five of them performed in a neonatal simulation resuscitation scenario. To assess participants' performances in the NLS scenario, we used a scenario-based designed NLS checklist. A machine learning design was utilized to better understand the interaction of psychological characteristics and training. The first model aimed to understand how to differentiate between people who take responsibility for their actions vs. those who do not. In a second model, the goal was to understand the relevance of training by contextualizing the effect of training to other important psychological and personality characteristics like locus of control, anxiety, emotion regulation, openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. Results: No statistically significant differences were found for psychological characteristics between the training group and the no training group. However, as expected, differences were noted in favor of the training group for performance and within gender for psychological characteristics. When correcting for all these information in a model, anxiety and gender were the most important factors associated with taking responsibility for an action, while training was the only relevant factor in explaining performance during a neonatal resuscitation scenario. Conclusion: Training had a significantly stronger effect on performance in medical students in a neonatal resuscitation scenario than individual characteristics such as demographics, personality, and trait anxiety.

Enhancing the Luminescence of Eu(III) Complexes with the Ruthenocene Organometallic Unit as Ancillary Ligand.

Five novel Eu(III)-ß-diketonate complexes containing ruthenocene ancillary ligands (1,1'-bis(diphenylphosphoryl)ruthenocene─RcBPO) were synthesized and characterized. The coordination compounds presented the general formula [Eu(ß-dik)3(RcBPO)], where ß-dik stands for 2-thenoyltrifluoroacetonate (tta), 3-benzoyl-1,1,1-trifluoroacetone (btf), 2-dibenzoylmethanate (dbm), 2-acetyl-1,3-indandionate (aind), and 2-benzoyl-1,3-indandionate (bind), and RcBPO stands for 1,1'-bis(diphenylphosphoryl)ruthenocene. The [Eu(aind)3(RcBPO)] complex crystallizes in a monoclinic Cc non-centrosymmetric space group with the europium site environment, assuming a bicapped trigonal prism coordination polyhedron with the symmetry point group close to C2v. Photoluminescent properties for the solid-state samples were described in terms of excitation, emission, lifetime decay curves, and intrinsic and overall quantum yields. The replacement of the two coordinated H2O molecules by the RcBPO ancillary ligand leads to great enhancements of the overall quantum yields (QEuL), with the minimum increment by a factor of 5 for the case of [Eu(btf)3(RcBPO)] and the maximum enhancement of 270 times for the case of the [Eu(dbm)3(RcBPO)] complex. In addition, theoretical calculations were carried out to model the spectroscopic properties of the investigated compounds. To obtain theoretical Judd-Ofelt parameters (Ωλ, λ = 2, 4, and 6) and intramolecular energy transfer rates, the JOYSpectra web platform was employed using the structure obtained from density functional theory calculations. Hence, a rate equation model provided theoretical overall quantum yields, which are in great agreement with measured data.

Predicting in vitro fertilization success in the Brazilian public health system: a machine learning approach.

Infertility has become a global health problem, increasing the number of couples looking for in vitro fertilization (IVF). Despite advances and technical improvements, some couples remain childless due to the high complexity of the technique. The use of machine learning (ML) in the prediction of pregnancy, computing factors that could interfere in the effectiveness of the treatment, is an important tool to optimize these factors and reach the success of pregnancy. The aim of this study was to apply ML models to determine variables related to pregnancy after IVF in a public health service, including pre-implantation variables. This study included 771 women who underwent IVF treatment at Hospital das Clínicas, Federal University of Minas Gerais, between 2013 and 2019. We used the following Machine Learning algorithms: Logistic Regression, Random Forest, XG Boost and Support Vector Machines. The Random Forest algorithm achieved the best performance, with better accuracy, sensitivity and area under the ROC curve to predict the success of IVF evaluated by pregnancy frequency. We also trained a specific model only for women older than 35 years old. Variables in the Random Forest model related to pregnancy after in vitro fertilization.

A systematic review and meta-analysis of fusion rate enhancements and bone graft options for spine surgery.

Our study aimed to evaluate differences in outcomes of patients submitted to spinal fusion using different grafts measuring the effectiveness of spinal fusion rates, pseudarthrosis rates, and adverse events. Applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, this systematic review and meta-analysis identified 64 eligible articles. The main inclusion criteria were adult patients that were submitted to spinal fusion, autologous iliac crest (AIC), allograft (ALG), alloplastic (ALP; hydroxyapatite, rhBMP-2, rhBMP-7, or the association between them), and local bone (LB), whether in addition to metallic implants or not, was applied. We made a comparison among those groups to evaluate the presence of differences in outcomes, such as fusion rate, hospital stay, follow-up extension (6, 12, 24, and 48 months), pseudarthrosis rate, and adverse events. Sixty-four studies were identified. LB presented significantly higher proportions of fusion rates (95.3% CI 89.7-98.7) compared to the AIC (88.6% CI 84.8-91.9), ALG (87.8% CI 80.8-93.4), and ALP (85.8% CI 75.7-93.5) study groups. Pseudarthrosis presented at a significantly lower pooled proportion of ALG studies (4.8% CI 0.1-15.7) compared to AIC (8.6% CI 4.2-14.2), ALP (7.1% CI 0.9-18.2), and LB (10.3% CI 1.8-24.5). ALP and AIC studies described significantly more cases of adverse events (80 events/404 patients and 860 events/2001 patients, respectively) compared to LB (20 events/311 patients) and ALG (73 events/459 patients). Most studies presented high risk-of-bias scores. Based on fusion rates and adverse events proportions, LB showed a superior trend among the graft cases we analyzed. However, our review revealed highly heterogeneous data and a need for more rigorous studies to better address and assist surgeons' choices of the best spinal grafts.

The impact of endoscopic activity on musculoskeletal disorders of high-volume endoscopists in Germany.

Physical stress is common in GI endoscopists, leading to musculoskeletal disorders. Considering the increasing complexity of interventional GI endoscopy with prolonged examination time, work-related musculoskeletal disorders have come into focus. However, data on work-related health stress in German endoscopists are elusive. The aim of this study was therefore to investigate the prevalence and consequences of work-related musculoskeletal disorders in German endoscopists. A 24-item questionnaire on endoscopy-associated musculoskeletal disorders and standardized pain assessment was developed by an interdisciplinary team of endoscopists and sports medics. The survey was distributed online by the leading German societies for gastroenterology and endoscopy. Overall, 151 German practicing endoscopists took part in the study. Regarding the average number of endoscopic procedures per week, the study collective consisted mainly of high-volume endoscopists. The survey showed that most participants suffered from general musculoskeletal disorders (82.8%) and from work-related musculoskeletal disorders (76.8%). The most affected body parts were the neck, low back, thumb, and shoulder. Temporary absence from work due to symptoms was reported by 9.9% of the respondents. Over 30% of participating endoscopists stated the need for analgesics or physiotherapy due to musculoskeletal disorders. Age, professional experience and work time were identified as relevant risk factors for musculoskeletal health issues. A high number of German endoscopists are affected by musculoskeletal disorders due to specific working postures and repetitive movements with a large impact on personal health. Further interventional studies are mandatory to improve the risk prevention of endoscopic activity.

Radiomics Can Distinguish Pediatric Supratentorial Embryonal Tumors, High-Grade Gliomas, and Ependymomas.

BACKGROUND AND PURPOSE: Pediatric supratentorial tumors such as embryonal tumors, high-grade gliomas, and ependymomas are difficult to distinguish by histopathology and imaging because of overlapping features. We applied machine learning to uncover MR imaging-based radiomics phenotypes that can differentiate these tumor types. MATERIALS AND METHODS: Our retrospective cohort of 231 patients from 7 participating institutions had 50 embryonal tumors, 127 high-grade gliomas, and 54 ependymomas. For each tumor volume, we extracted 900 Image Biomarker Standardization Initiative-based PyRadiomics features from T2-weighted and gadolinium-enhanced T1-weighted images. A reduced feature set was obtained by sparse regression analysis and was used as input for 6 candidate classifier models. Training and test sets were randomly allocated from the total cohort in a 75:25 ratio. RESULTS: The final classifier model for embryonal tumor-versus-high-grade gliomas identified 23 features with an area under the curve of 0.98; the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 0.85, 0.91, 0.79, 0.94, and 0.89, respectively. The classifier for embryonal tumor-versus-ependymomas identified 4 features with an area under the curve of 0.82; the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 0.93, 0.69, 0.76, 0.90, and 0.81, respectively. The classifier for high-grade gliomas-versus-ependymomas identified 35 features with an area under the curve of 0.96; the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 0.82, 0.94, 0.82, 0.94, and 0.91, respectively. CONCLUSIONS: In this multi-institutional study, we identified distinct radiomic phenotypes that distinguish pediatric supratentorial tumors, high-grade gliomas, and ependymomas with high accuracy. Incorporation of this technique in diagnostic algorithms can improve diagnosis, risk stratification, and treatment planning.

The novel genus, 'Candidatus Phosphoribacter', previously identified as Tetrasphaera, is the dominant polyphosphate accumulating lineage in EBPR wastewater treatment plants worldwide.

The bacterial genus Tetrasphaera encompasses abundant polyphosphate accumulating organisms (PAOs) that are responsible for enhanced biological phosphorus removal (EBPR) in wastewater treatment plants. Recent analyses of genomes from pure cultures revealed that 16S rRNA genes cannot resolve the lineage, and that Tetrasphaera spp. are from several different genera within the Dermatophilaceae. Here, we examine 14 recently recovered high-quality metagenome-assembled genomes from wastewater treatment plants containing full-length 16S rRNA genes identified as Tetrasphaera, 11 of which belong to the uncultured Tetrasphaera clade 3. We find that this clade represents two distinct genera, named here Ca. Phosphoribacter and Ca. Lutibacillus, and reveal that the widely used model organism Tetrasphaera elongata is less relevant for physiological predictions of this uncultured group. Ca. Phosphoribacter incorporates species diversity unresolved at the 16S rRNA gene level, with the two most abundant and often co-occurring species encoding identical V1-V3 16S rRNA gene amplicon sequence variants but different metabolic capabilities, and possibly, niches. Both Ca. P. hodrii and Ca. P. baldrii were visualised using fluorescence in situ hybridisation (FISH), and PAO capabilities were confirmed with FISH-Raman microspectroscopy and phosphate cycling experiments. Ca. Phosphoribacter represents the most abundant former Tetrasphaera lineage and PAO in EPBR systems in Denmark and globally.

[Technical innovations and future perspectives]. / Technische Innovationen und Blick in die Zukunft.

BACKGROUND: Digital systems have increasingly become integrated into the modern operating room in the last few decades. This has brought about a massive change, especially in minimally invasive surgery. OBJECTIVE: The article provides an overview of the current technical innovations and the perspectives of digitalization and artificial intelligence (AI) in surgery. MATERIAL AND METHODS: The article is based on a literature search via PubMed and research work by the participating coauthors. RESULTS: Current research is increasingly looking at machine learning techniques that take advantage of the complex data in surgery; however, the integration of artificial intelligence systems into the operating room and clinical practice has only just begun. DISCUSSION: Translational research of artificial intelligence in surgery is still in its infancy but has great potential to improve patient care; however, to accelerate the incorporation of intelligent systems into the clinical practice, the creation of interdisciplinary research groups led by surgeons is necessary.

Cortical thickness across the cingulate gyrus in schizophrenia and its association to illness duration and memory performance.

Schizophrenia has been associated with structural brain abnormalities and cognitive deficits that partly change during the course of illness. In the present study, cortical thickness in five subregions of the cingulate gyrus was assessed in 44 patients with schizophrenia-spectrum disorder and 47 control persons and related to illness duration and memory capacities. In the patients group, cortical thickness was increased in the posterior part of the cingulate gyrus and related to illness duration whereas cortical thickness was decreased in anterior parts unrelated to illness duration. In contrast, cortical thickness was related to episodic and working memory performance only in the anterior but not posterior parts of the cingulate gyrus. Our finding of a posterior cingulate increase may point to either increased parietal communication that is accompanied by augmented neural plasticity or to effects of altered neurodegenerative processes in schizophrenia.