Hyaluronic acid in tooth extraction: a systematic review and meta-analysis of preclinical and clinical trials.

OBJECTIVES: To assess whether in animals or patients with ≥ 1 tooth extracted, hyaluronic acid (HyA) application results in superior healing and/or improved complication management compared to any other treatment or no treatment. MATERIALS AND METHODS: Three databases were searched until April 2022. The most relevant eligibility criteria were (1) local application of HyA as adjunct to tooth extraction or as treatment of alveolar osteitis, and (2) reporting of clinical, radiographic, histological, or patient-reported data. New bone formation and/or quality were considered main outcome parameters in preclinical studies, while pain, swelling, and trismus were defined as main outcome parameters in clinical studies. RESULTS: Five preclinical and 22 clinical studies (1062 patients at final evaluation) were included. In preclinical trials, HyA was applied into the extraction socket. Although a positive effect of HyA was seen in all individual studies on bone formation, this effect was not confirmed by meta-analysis. In clinical studies, HyA was applied into the extraction socket or used as spray or mouthwash. HyA application after non-surgical extraction of normally erupted teeth may have a positive effect on soft tissue healing. Based on meta-analyses, HyA application after surgical removal of lower third molars (LM3) resulted in significant reduction in pain perception 7 days postoperatively compared to either no additional wound manipulation or the application of a placebo/carrier. Early post-operative pain, trismus, and extent of swelling were unaffected. CONCLUSIONS: HyA application may have a positive effect in pain reduction after LM3 removal, but not after extraction of normally erupted teeth. CLINICAL RELEVANCE: HyA application may have a positive effect in pain reduction after surgical LM3 removal, but it does not seem to have any impact on other complications or after extraction of normally erupted teeth. Furthermore, it seems not to reduce post-extraction alveolar ridge modeling, even though preclinical studies show enhanced bone formation.

Simulation of Tetrahedral Profiled Carbon Rovings for Concrete Reinforcements.

Textile reinforcements are increasingly establishing their position in the construction industry due to their high tensile properties and corrosion resistance for concrete applications. In contrast to ribbed monolithic steel bars with a defined form-fit effect, the conventional carbon rovings' bond force is transmitted primarily by an adhesive bond (material fit) between the textile surface and the surrounding concrete matrix. As a result, relatively large bonding lengths are required to transmit bond forces, resulting in inefficient material utilization. Novel solutions such as tetrahedral profiled rovings promise significant improvements in the bonding behavior of textile reinforcements by creating an additional mechanical interlock with the concrete matrix while maintaining the high tensile properties of carbon fibers. Therefore, simulative investigations of tensile and bond behavior have been conducted to increase the transmittable bond force and bond stiffness of profiled rovings through a defined roving geometry. Geometric and material models were thus hereby developed, and tensile and pullout tests were simulated. The results of the simulations and characterizations could enable the optimization of the geometric parameters of tetrahedral profiled rovings to achieve better bond and tensile properties and provide basic principles for the simulative modeling of profiled textile reinforcements.

Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics.

Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. Nonetheless, and perhaps surprisingly, only few image AI systems are already in routine clinical use. A major reason for this is the missing validation of the robustness of many AI systems: beyond a narrow context, the large variability in digital images due to differences in preanalytical laboratory procedures, staining procedures, and scanners can be challenging for the subsequent image analysis. Resulting faulty AI analysis may bias the pathologist and contribute to incorrect diagnoses and, therefore, may lead to inappropriate therapy or prognosis. In this study, a pretrained AI assistance tool for the quantification of Ki-67, estrogen receptor (ER), and progesterone receptor (PR) in breast cancer was evaluated within a realistic study set representative of clinical routine on a total of 204 slides (72 Ki-67, 66 ER, and 66 PR slides). This represents the cohort with the largest image variance for AI tool evaluation to date, including 3 staining systems, 5 whole-slide scanners, and 1 microscope camera. These routine cases were collected without manual preselection and analyzed by 10 participant pathologists from 8 sites. Agreement rates for individual pathologists were found to be 87.6% for Ki-67 and 89.4% for ER/PR, respectively, between scoring with and without the assistance of the AI tool regarding clinical categories. Individual AI analysis results were confirmed by the majority of pathologists in 95.8% of Ki-67 cases and 93.2% of ER/PR cases. The statistical analysis provides evidence for high interobserver variance between pathologists (Krippendorff's α, 0.69) in conventional immunohistochemical quantification. Pathologist agreement increased slightly when using AI support (Krippendorff α, 0.72). Agreement rates of pathologist scores with and without AI assistance provide evidence for the reliability of immunohistochemical scoring with the support of the investigated AI tool under a large number of environmental variables that influence the quality of the diagnosed tissue images.

Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.

Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance and obtain regulatory approval. This assessment requires appropriate test datasets. However, compiling such datasets is challenging and specific recommendations are missing. A committee of various stakeholders, including commercial AI developers, pathologists, and researchers, discussed key aspects and conducted extensive literature reviews on test datasets in pathology. Here, we summarize the results and derive general recommendations on compiling test datasets. We address several questions: Which and how many images are needed? How to deal with low-prevalence subsets? How can potential bias be detected? How should datasets be reported? What are the regulatory requirements in different countries? The recommendations are intended to help AI developers demonstrate the utility of their products and to help pathologists and regulatory agencies verify reported performance measures. Further research is needed to formulate criteria for sufficiently representative test datasets so that AI solutions can operate with less user intervention and better support diagnostic workflows in the future.

Reactions of Mesityl Azide with Ferrocene-Based N-Heterocyclic Germylenes, Stannylenes and Plumbylenes, Including PPh2 -Functionalised Congeners.

The reactivity of ferrocene-based N-heterocyclic tetrylenes [{Fe(η5 -C5 H4 -NSitBuMe2 )2 }E] (E=Ge, Sn, Pb) towards mesityl azide (MesN3 ) is compared with that of PPh2 -functionalised congeners exhibiting two possible reaction sites, namely the EII and PIII atom. For E=Ge and Sn the reaction occurs at the EII atom, leading to the formation of N2 and an EIV =NMes unit. The germanimines are sufficiently stable for isolation. The stannanimines furnish follow-up products, either by [2+3] cycloaddition with MesN3 or, in the PPh2 -substituted case, by NMes transfer from the SnIV to the PIII atom. Whereas [{Fe(η5 -C5 H4 -NSitBuMe2 )2 }Pb] and other diaminoplumbylenes studied are inert even under forcing conditions, the PPh2 -substituted congener forms an addition product with MesN3 , thus showing a behaviour similar to that of frustrated Lewis pairs. The germylenes of this study afford copper(I) complexes with CuCl, including the first structurally characterised linear dicoordinate halogenido complex [CuX(L)] with a heavier tetrylene ligand L.

A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.

Onychomycosis is common. Diagnosis can be confirmed by various methods; a commonly used method is the histological examination of nail clippings. A deep learning system was developed and its diagnostic accuracy compared with that of human experts. A dataset with annotations for fungal elements was used to train an artificial intelligence (AI) model. In a second dataset (n=199) the diagnostic accuracy of the AI was compared with that of dermatopathologists. The results show a non-inferiority of the deep learning system to that of analogue diagnosis (non-inferiority margin 5%) with respect to specificity and the area under the receiver operating characteristic curve (AUC). The AI achieved an AUC of 0.981. One limitation of this system is the need for a large number of training images. The AI had difficulty recognizing spores and confused serum or aggregated bacteria with fungal elements. Use of this deep learning system in dermatopathology routine might help to diagnose onychomycosis more efficiently.

Directly observed therapy at opioid substitution facilities using sofosbuvir/velpatasvir results in excellent SVR12 rates in PWIDs at high risk for non-adherence to DAA therapy.

BACKGROUND & AIMS: We evaluated the effectiveness of sofosbuvir/velpatasvir (SOF/VEL) in difficult-to-treat PWIDs with presumed high risk for non-adherence to antiviral therapy using an innovative concept involving their opioid agonist therapy (OAT) facility. METHODS: N = 221 patients (m/f: 168/53; median age: 44.7 years (IQR 16.9); HCV-genotype 3: 45.2%; cirrhosis: 33.9%) treated with SOF/VEL were included. PWIDs at high risk for non-adherence to DAA therapy (n = 122) received HCV treatment alongside OAT under the supervision of medical staff ("directly observed therapy", DOT). These patients were compared to patients with presumed excellent drug compliance, who were treated in a "standard setting" (SS) of SOF/VEL prescription at a tertiary care center (n = 99). RESULTS: DOT-patients (n = 122/221; 55.2%) were younger than SS-patients (median age: 41.3 vs. 53.0 years), all had psychiatric comorbidities and most had a poor socioeconomic status. 83/122 (68.0%) reported ongoing intravenous drug use. Within the DOT-group, SVR12 was achieved in 99.1% (95% CI: 95.0-100; n = 109/110) with one patient experiencing treatment failure, while n = 12/122 (9.8%) patients were excluded due to loss of follow-up (FU). 5 patients showed HCV reinfection after achieving SVR12. SS-patients achieved SVR in 96.6% (95% CI: 90.3-99.3%; n = 84/87) after exclusion of 10/99 (10.1%) patients who were lost to FU and 2 patients who died prior to SVR12 due to reasons not related to DAA therapy. CONCLUSIONS: SOF/VEL given as DOT along with OAT in PWIDs at high risk of non-adherence to antiviral therapy including those with ongoing intravenous drug use resulted in excellent SVR rates similar to patients with presumed "excellent compliance" under standard drug intake.

Acute changes of global and longitudinal right ventricular function: an exploratory analysis in patients undergoing open-chest mitral valve surgery, percutaneous mitral valve repair and off-pump coronary artery bypass grafting.

BACKGROUND: Right ventricular (RV) function is an important prognostic indicator. The acute effects of cardiac interventions or cardiac surgery on global and longitudinal RV function are not entirely understood. In this study, acute changes of RV function during mitral valve surgery (MVS), percutaneous mitral valve repair (PMVR) and off-pump coronary artery bypass surgery (OPCAB) were investigated employing 3D echocardiography. METHODS: Twenty patients scheduled for MVS, 23 patients scheduled for PMVR and 25 patients scheduled for OPCAB were included retrospectively if patients had received 3D transesophageal echocardiography before and immediately after MVS, PMVR or OPCAB, respectively. RV global and longitudinal function was assessed using a 3D multiparameter set consisting of global right ventricular ejection fraction (RVEF), tricuspid annular plane systolic excursion (TAPSE), longitudinal contribution to RVEF (RVEFlong) and free wall longitudinal strain (FWLS). RESULTS: Longitudinal RV function was significantly depressed immediately after MVS, as reflected by all parameters (RVEFlong: 20 ± 5% vs. 13 ± 6%, p <  0.001, TAPSE: 13.1 ± 5.1 mm vs. 11.0 ± 3.5 mm, p = 0.04 and FWLS: -20.1 ± 7.1% vs. -15.4 ± 5.1%, p <  0.001, respectively). The global RVEF was slightly impaired, but the difference did not reach significance (37 ± 13% vs. 32 ± 9%, p = 0.15). In the PMVR group, both global and longitudinal RV function parameters were unaltered, whereas the OPCAB group showed a slight reduction of RVEFlong only (18 ± 7% vs. 14 ± 5%, p <  0.01). RVEFlong yielded moderate case-to-case but good overall reproducibility. CONCLUSIONS: TAPSE, FWLS and RVEFlong reflect the depression of longitudinal compared to global RV function initially after MVS. PMVR alone had no impact, while OPCAB had a slight impact on longitudinal RV function. The prognostic implications of these phenomena remain unclear and require further investigation.

Directly observed therapy for HCV with glecaprevir/pibrentasvir alongside opioid substitution in people who inject drugs-First real world data from Austria.

BACKGROUND: Directly acting antivirals (DAA) against hepatitis C virus (HCV) infection have facilitated sustained virologic response (SVR) rates >90% in clinical studies. Yet, real life data regarding DAA treatment in people who inject drugs (PWIDs) are scarce. We evaluated the effectiveness of glecaprevir/pibrentasvir (G/P) in difficult-to-treat PWIDs with presumed high risk of non-adherence to DAA therapy using the concept of directly observed therapy involving their opioid substitution therapy (OST) facility. METHODS: N = 145 patients (m/f: 91/54; median age: 41.1 (IQR 19.5) years; HCV-genotype (GT) 1/2/3/4: 82/1/56/5, GT3: 38.6%; cirrhosis: n = 6; 4.1%) treated with G/P were included. PWIDs at high risk for non-adherence to DAA therapy received HCV treatment together with their OST under the supervision of medical staff ("directly observed therapy", DOT). The effectiveness of G/P given as DOT in PWIDs with presumed high risk of non-adherence to DAA therapy was compared to patients with suspected "excellent compliance" in the "standard setting" (SS) of G/P prescription at a tertiary care center and self-managed G/P intake at home. Treatment duration was 8-16 weeks according to the G/P drug label. RESULTS: DOT-patients (n = 74/145; 51.0%) were younger than SS-patients (median 38.7, IQR 12.5 vs. median 50.6, IQR 20.3 years), all had psychiatric co-morbidities and most had a poor socioeconomic status. 50/74 (67.6%) reported ongoing intravenous drug use (IDU). SVR was achieved in n = 70/74 (94.6%) patients with n = 3 being lost to follow-up (FU) and n = 1 showing nonresponse to therapy. SS-patients achieved SVR in 97.2% (69/71) with n = 1 patient being lost to FU and n = 1 patient with GT3 showing HCV relapse. CONCLUSION: G/P given as DOT along with OST in PWIDs with high risk of non-adherence to DAA therapy resulted in similarly high SVR rates (94.6%) as in patients with presumed "excellent compliance" under standard drug intake.

Novel mesh-derived right ventricular free wall longitudinal strain analysis by intraoperative three-dimensional transoesophageal speckle-tracking echocardiography: a comparison with conventional parameters.

Longitudinal right ventricular (RV) function is substantial and might be reflected by free wall longitudinal strain (FWLS). Software solutions for FWLS analysis by two-dimensional (2D) and three-dimensional (3D) transesophageal echocardiography (TEE) are available, but data on validation are sparse. In this study, a novel method for FWLS analysis on 3D meshes ("mesh surface", MS-FWLS,) was tested for feasibility and compared to available parameters. 80 patients undergoing left-sided cardiac valve surgery with intraoperative TEE were included retrospectively. 2D-FWLS, 3D-derived (3Dd)-FWLS (assessed in optimized four-chamber views after volume analysis) and MS-FWLS were measured and compared to conventional parameters (3Dd-TAPSE, FAC and RVEF). The mean FWLS values did not differ significantly between methods (- 19.0 ± 6.1%, - 20.0 ± 7.3%, - 19.5 ± 7.3% for 2D-, 3Dd- and MS-FWLS, respectively). No significant differences in the mean FWLS between patients with normal or increased pulmonary artery pressures as well as normal or reduced left ventricular ejection fraction were observed. Agreement was best between 3Dd- and MS-FWLS (r = 0.89, bias = - 1.0%, LOA ± 6.9%). Conventional echocardiographic parameters yielded poorer intermodality agreement. In patients with discrepant results between 2D- and 3Dd-FWLS, 3Dd-FWLS and MS-FWLS yielded similar results (r = 0.82, bias = - 0.3%, LOA ± 8.6%), while 2D-FWLS and MS-FWLS did not. Intra- and interobserver variabilities of strain analyses were low. MS-FWLS might represent a promising method to overcome artefacts associated with 2D analysis. Its prognostic relevance needs to be investigated in prospective studies.

Regional Right Ventricular Volume and Function Analysis Using Intraoperative 3-Dimensional Echocardiography-Derived Mesh Models.

OBJECTIVES: In daily echocardiographic practice, the right ventricle (RV) is assessed using mostly 2-dimensional (2D) echocardiography. Parameters measuring longitudinal shortening (eg, tricuspid annular plane systolic excursion) or changes in areas (eg, fractional area change) are used as surrogates for right ventricular function. Three-dimensional (3D) echocardiography-based techniques allow for cardiac magnetic resonance imaging-validated assessment of the RV. Depiction of regional right ventricular function is of increasing clinical interest. This study aimed to calculate regional volumetric changes in the right ventricular inlet, apical section, and outflow tract. Correlations between traditional parameters and regional right ventricular function were studied. DESIGN: Retrospective cohort study on patients scheduled for cardiac surgery. SETTING: Tertiary care university hospital. PARTICIPANTS: The study comprised 80 patients scheduled for cardiac surgery. MEASUREMENTS AND MAIN RESULTS: Based on 3D echocardiographic datasets, mesh models of the RV were generated on a vendor-independent platform. The meshes were further cut into the following 3 regions: the inlet part, the apical section, and the outflow tract. The regional volumes and ejection fractions were compared with the global right ventricular and left ventricular functions. Regional volumes were correlated linearly with the global end-diastolic volume. The right ventricular outflow tract demonstrated a significantly lower ejection fraction than the inlet part (34% ± 11% v 28% ± 11%; p = 0.0054). The function in the right ventricular outflow tract was reduced significantly compared with the global right ventricular function in patients with severely reduced left ventricular ejection fraction (<20%). CONCLUSION: The different parts of the RV seem to have different ejection fractions. Different regions of the RV are affected differently by reduced left ventricular ejection fraction. Regional right ventricular analyses could help clinicians better understand pathologic states of the RV.

Efficacy of ledipasvir/sofosbuvir plus ribavirin for 12 weeks in patients with chronic hepatitis C genotype 3 and compensated liver disease.

INTRODUCTION: In the era of direct-acting antivirals, hepatitis C virus (HCV) genotype (GT) 3 remains as the most difficult-to-treat HCV-GT. Currently, data on the efficacy of ledipasvir/sofosbuvir plus ribavirin (SOF/LDV+RBV) in GT3-infected patients are limited. We investigated the efficacy of this regimen in a real-life cohort from Austria. PATIENTS AND METHODS: A total of 55 patients with HCV-GT3 and compensated liver disease (20% treatment-experienced, 33% with cirrhosis, 7% with HIV coinfection) from four Austrian hepatitis centers received treatment with SOF/LDV+RBV for 12 weeks. The primary endpoint was sustained virological response 12 weeks after end of therapy (SVR12). RESULTS: In the modified intention-to-treat analysis - excluding patients lost to follow-up - the overall SVR12 rate was 94% (95% confidence interval: 84-99%). In treatment-naive and treatment-experienced patients, SVR12 rates were 95 and 89%, respectively. SVR12 rate was 91% in patients without cirrhosis and 100% in patients with cirrhosis. There were no serious adverse events. Viral sequencing did not show the presence of any resistance-associated substitutions in any of the three relapsed patients. CONCLUSION: Despite a very weak antiviral activity of ledipasvir against HCV-GT3 in vitro, a 12-week course of SOF/LDV+RBV was highly effective, with a 94% SVR12 rate in our cohort of compensated HCV-GT3-infected patients. Thus, if pangenotypic NS5A inhibitors are not available or not reimbursed by insurances, SOF/LDV+RBV seems to be an effective alternative in patients with HCV-GT3 infection.

Feasibility of Active Machine Learning for Multiclass Compound Classification.

A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning classification models from training compounds of each class. Gathering class information for compounds can be cost-intensive as the required data needs to be provided by human experts or experiments. This paper studies whether active machine learning can be used to reduce the required number of training compounds. Active learning is a machine learning method which processes class label data in an iterative fashion. It has gained much attention in a broad range of application areas. In this paper, an active learning method for multiclass compound classification is proposed. This method selects informative training compounds so as to optimally support the learning progress. The combination with human feedback leads to a semiautomated interactive multiclass classification procedure. This method was investigated empirically on 15 compound classification tasks containing 86-2870 compounds in 3-38 classes. The empirical results show that active learning can solve these classification tasks using 10-80% of the data which would be necessary for standard learning techniques.

Spherical sample holders to improve the susceptibility measurement of superparamagnetic materials.

The design of two custom sample holders with a spherical cavity for commercial vibrating sample magnetometer systems is described. For such cavities, the magnetization M[over ->] and the internal magnetic field H(i)[over ->] of a sample are both homogeneous. Consequently, the material parameter M(H(i)) of a sample can be determined even for liquids and powders with a high magnetic susceptibility.

Thermoreversible hydroferrogels with tunable mechanical properties utilizing block copolymer mesophases as template.

Thermoreversible hydroferrogels (FGs) have been prepared via gelation of aqueous maghemite ferrofluids (FFs) using the triblock copolymer Pluronic P123 as gelator. In the investigated concentration range of 28-42 wt % P123, long-term stable homogeneous FGs can be prepared from FFs with a maximum maghemite content of 14 wt %. For higher FF concentrations up to 29 wt %, however, homogeneous FGs were formed only for gelator contents up to ca. 33 wt %. A combination of rheology and µ-DSC was applied as an alternative method to construct the P123 phase diagram, without the need for visual methods or scattering techniques. Using this procedure, we could show that maghemite nanoparticles can be effectively templated by the cubic and hexagonal P123 mesophases in a concentration range of 33-38 wt % P123 and FF concentrations up to 14 wt %, respectively. Most importantly, the phase behavior and the corresponding phase-transition temperatures of P123 were not significantly altered. As a result, the FGs show a reversible temperature-triggered transition from a cubic hard gel to a hexagonal gel, which is linked with a softening of the gel. Furthermore, this concept can be applied to template cobalt ferrite nanoparticle effectively, too. Magnetization experiments revealed that the superparamagnetic behavior of the maghemite nanoparticles, which show a Néel type relaxation, is not altered in the corresponding FGs. In contrast, FGs based on blocked cobalt ferrite nanoparticles show a hysteretic behavior, which indicates a strong mechanical coupling between the P123 mesophase and the magnetic nanoparticles.

Model-based design of growth-attenuated viruses.

Live-virus vaccines activate both humoral and cell-mediated immunity, require only a single boosting, and generally provide longer immune protection than killed or subunit vaccines. However, growth of live-virus vaccines must be attenuated to minimize their potential pathogenic effects, and mechanisms of attenuation by conventional serial-transfer viral adaptation are not well-understood. New methods of attenuation based on rational engineering of viral genomes may offer a potentially greater control if one can link defined genetic modifications to changes in virus growth. To begin to establish such links between genotype and growth phenotype, we developed a computer model for the intracellular growth of vesicular stomatitis virus (VSV), a well-studied, nonsegmented, negative-stranded RNA virus. Our model incorporated established regulatory mechanisms of VSV while integrating key wild-type infection steps: hijacking of host resources, transcription, translation, and replication, followed by assembly and release of progeny VSV particles. Generalization of the wild-type model to allow for genome rearrangements matched the experimentally observed attenuation ranking for recombinant VSV strains that altered the genome position of their nucleocapsid gene. Finally, our simulations captured previously reported experimental results showing how altering the positions of other VSV genes has the potential to attenuate the VSV growth while overexpressing the immunogenic VSV surface glycoprotein. Such models will facilitate the engineering of new live-virus vaccines by linking genomic manipulations to controlled changes in virus gene-expression and growth.