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Virtual reality (VR) applications are developing rapidly, becoming more and more affordable, and offer various advantages for learning contexts. Dynamic visualizations are generally suitable for depicting continuous processes (e.g., different movement patterns), and particularly dynamic virtual 3D-objects can provide different perspectives on the movements. The present study investigated through a low immersive (desktop "VR", Study 1) and a high immersive virtual environment (immersive VR; Study 2) the effectiveness of different interaction formats to view 3D-objects from different perspectives. Participants controlled either the orientation of the 3D-objects (Study 1, mouse interaction; Study 2, hand interaction via VR controllers) or their viewpoint in relation to the 3D-objects (Study 1, camera position; Study 2, position of participants' own body). Additionally, the moderating influence of learners' visuospatial ability was addressed. Dependent variables were pictorial recognition (easy, medium, difficult), factual knowledge, presence, and motion sickness. Results showed that higher-visuospatial-ability learners outperformed lower-visuospatial-ability learners. In Study 1, higher-visuospatial-ability learners showed higher recognition performance (difficult items) by controlling the camera position, whereas lower-visuospatial-ability learners suffered from this interaction format. In Study 2, higher-visuospatial-ability learners achieved better recognition performance (easy items) by controlling the 3D-models, whereas lower-visuospatial-ability learners tended to profit from moving around the 3D-objects (medium items). The immersive VR yielded more presence and higher motion sickness. This study clearly shows that different interaction formats to view 3D-objects from multiple perspectives in Desktop-VR are not transferable on a one-to-one basis into immersive VR. The results and implications for the design of virtual learning environments are discussed.

Abstract Background Lower extremity peripheral artery disease frequently presents with calcifications which reduces the accuracy of computed tomography (CT) angiography, especially below-the-knee. Photon-counting detector (PCD)-CT offers improved spatial resolution and less calcium blooming. We aimed to identify the optimal reconstruction parameters for PCD-CT angiography of the lower legs. Methods Tubes with different diameters (1–5 mm) were filled with different iodine concentrations and scanned in a water container. Images were reconstructed with 0.4 mm isotropic resolution using a quantitative kernel at all available sharpness levels (Qr36 to Qr76) and using different levels of quantum iterative reconstruction (QIR-2–4). Noise and image sharpness were determined for all reconstructions. Additionally, CT angiograms of 20 patients, reconstructed with a medium (Qr44), sharp (Qr60), and ultrasharp (Qr72) kernel at QIR-2-4, were evaluated by three readers assessing noise, delineation of plaques and vessel walls, and overall quality. Results In the phantom study, increased kernel sharpness led to higher image noise (e.g., 16, 38, 77 HU for Qr44, Qr60, Qr72, and QIR-3). Image sharpness increased with increasing kernel sharpness, reaching a plateau at the medium-high level 60. Higher QIR levels decreased image noise (e.g., 51, 38, 25 HU at QIR-2–4 and Qr60) without reducing vessel sharpness. The qualitative in vivo results confirmed these findings: the sharp kernel (Qr60) with the highest QIR yielded the best overall quality. Conclusion The combination of a sharpness level optimized reconstruction kernel (Qr60) and the highest QIR level yield the best image quality for PCD-CT angiography of the lower legs when reconstructed at 0.4-mm resolution. Relevance statement Using high-resolution PCD-CT angiography with optimized reconstruction parameters might improve diagnostic accuracy and confidence in peripheral artery disease of the lower legs. Key Points Effective exploitation of the potential of PCD-CT angiography requires optimized reconstruction parameters. Too soft or too sharp reconstruction kernels reduce image quality. The highest level of quantum iterative reconstruction provides the best image quality. Graphical Abstract

Abstract Preliminary work has shown that portal hypertension plays a key role for the prognosis in patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). Specifically, the presence of ascites appears to be a strong negative predictor for these patients. However, it remains unclear whether different ascites volumes influence prognosis. Therefore, the aim of this work was to investigate the influence of different ascites volumes on survival for patients with HCC undergoing TACE. A total of 327 treatment-naïve patients with HCC undergoing initial TACE at our tertiary care center between 2010 and 2020 were included. In patients with ascites, the fluid was segmented, and the volume quantified by slice-wise addition using contrast-enhanced CT imaging. Median overall survival (OS) was calculated and univariate and multivariate Cox regression analysis has been performed. Ascites was present in 102 (31.9%) patients. Ascites volume as continuous variable was significantly associated with an increased hazard ratio in univariate analysis (p

Summary: Safe, effective, and low-cost oral antiviral therapies are needed to treat those at high risk for developing severe COVID-19. To that end, we performed a high-throughput screen to identify non-peptidic, non-covalent inhibitors of the SARS-CoV-2 main protease (Mpro), an essential enzyme in viral replication. NZ-804 was developed from a screening hit through iterative rounds of structure-guided medicinal chemistry. NZ-804 potently inhibits SARS-CoV-2 Mpro (0.009 μM IC50) as well as SARS-CoV-2 replication in human lung cell lines (0.008 μM EC50) and primary human airway epithelial cell cultures. Antiviral activity is maintained against distantly related sarbecoviruses and endemic human CoV OC43. In SARS-CoV-2 mouse and hamster disease models, NZ-804 therapy given once or twice daily significantly diminished SARS-CoV-2 replication and pathogenesis. NZ-804 synthesis is low cost and uncomplicated, simplifying global production and access. These data support the exploration of NZ-804 as a therapy for COVID-19 and future emerging sarbecovirus infections.

Abstract Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Abstract Objectives Artificial intelligence (AI) has tremendous potential to help radiologists in daily clinical routine. However, a seamless, standardized, and time-efficient way of integrating AI into the radiology workflow is often lacking. This constrains the full potential of this technology. To address this, we developed a new reporting pipeline that enables automated pre-population of structured reports with results provided by AI tools. Methods Findings from a commercially available AI tool for chest X-ray pathology detection were sent to an IHE-MRRT-compliant structured reporting (SR) platform as DICOM SR elements and used to automatically pre-populate a chest X-ray SR template. Pre-populated AI results could be validated, altered, or deleted by radiologists accessing the SR template. We assessed the performance of this newly developed AI to SR pipeline by comparing reporting times and subjective report quality to reports created as free-text and conventional structured reports. Results Chest X-ray reports with the new pipeline could be created in significantly less time than free-text reports and conventional structured reports (mean reporting times: 66.8 s vs. 85.6 s and 85.8 s, respectively; both p

Abstract During the Omicron wave, previous variants such as BA.2, BA.4, and BA.5 were replaced by newer variants with additional mutations in the spike protein. These variants, BA.4.6, BQ.1.1, and XBB, have spread in different countries with different degrees of success. Here, we evaluated the replicative ability and pathogenicity of BA.4.6, BQ1.1, and XBB clinical isolates in male Syrian hamsters. Although we found no substantial differences in weight change among hamsters infected with these Omicron subvariants, the replicative ability of BQ.1.1 and XBB in lung tissue was higher than that of BA.4.6 and BA.5. Of note, BQ.1.1 was lethal in both male and female transgenic human ACE2 hamsters. In competition assays, XBB replicated better than BQ.1.1 in the nasal turbinate tissues of female hamsters previously infected with Omicron BA.2. These results suggest that newer Omicron subvariants in the XBB family are still evolving and should be closely monitored.

Abstract The 2002 SARS outbreak, the 2019 emergence of COVID-19, and the continuing evolution of immune-evading SARS-CoV-2 variants together highlight the need for a broadly protective vaccine against ACE2-utilizing sarbecoviruses. While updated variant-matched formulations are a step in the right direction, protection needs to extend beyond SARS-CoV-2 and its variants to include SARS-like viruses. Here, we introduce bivalent and trivalent vaccine formulations using our spike protein nanoparticle platform that completely protect female hamsters against BA.5 and XBB.1 challenges with no detectable virus in the lungs. The trivalent cocktails elicit highly neutralizing responses against all tested Omicron variants and the bat sarbecoviruses SHC014 and WIV1. Finally, our 614D/SHC014/XBB trivalent spike formulation completely protects human ACE2-transgenic female hamsters against challenges with WIV1 and SHC014 with no detectable virus in the lungs. Collectively, these results illustrate that our trivalent protein-nanoparticle cocktail can provide broad protection against SARS-CoV-2-like and SARS-CoV-1-like sarbecoviruses.

Abstract Introduction and aim Bioaerosols contaminate the personal protective equipment (PPE), especially masks. The PPE harbors microorganisms from various sources. However, no previous studies have investigated the specific sources of bacteria found on used masks and their correlation with those from the treated patient. Setting, design, material and methods Intraoral samples from the patient were collected prior to dental aerosol-producing treatments using a nylon flock fiber swab. After treatment, the practitioner’s mask was imprinted onto agar plates. Main outcome methods Following cultivation, colony forming units were counted and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). After the samples were analyzed, the intraoral samples as well as the mask samples were assessed for the presence of identical species, which were subsequently quantified. Results 126 treatments were included. One species match occurred most frequently (26.2%), followed by two (11.9%%) and three or more (3.97%). In the intraoral samples, Neisseria subflava occurred most often, within mask samples Staphylococcus epidermidis were detected most. Staphylococcus aureus could be cultivated three times more often in intraoral samples than on the mask. Discussion and conclusion Oral microorganisms originating from the patient’s oral cavity can be found on the outside of masks. When using PPE during treatments, it should therefore always be in mind that potentially pathogenic microorganisms may land on the mask becoming a source of for itself.

Summary: Background: World Health Organisation (WHO) and USA Centers for Disease Control and Prevention (U.S. CDC) recommendations now allow simultaneous administration of COVID-19 and other vaccines. We compared antibody responses after coadministration of influenza and bivalent COVID-19 vaccines in the same (ipsilateral) arm vs. different (contralateral) arms. Methods: Pre- and post-vaccination serum samples from individuals in the Prospective Assessment of COVID-19 in a Community (PACC) cohort were used to conduct haemaglutination inhibition (HI) assays with the viruses in the 2022–2023 seasonal influenza vaccine and focus reduction neutralisation tests (FRNT) using a BA.5 SARS-CoV-2 virus. The effect of ipsilateral vs. contralateral vaccination on immune responses was inferred in a model that accounted for higher variance in vaccine responses at lower pre-vaccination titers. Findings: Ipsilateral vaccination did not cause higher influenza vaccine responses compared to contralateral vaccination. The response to SARS-CoV-2 was slightly increased in the ipsilateral group, but equivalence was not excluded. Interpretation: Coadministration of influenza and bivalent COVID-19 vaccines in the same arm or different arms did not strongly influence the antibody response to either vaccine. Funding: This work was supported by the U.S. CDC (grant number: 75D30120C09259).

The global emergence of many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants jeopardizes the protective antiviral immunity induced after infection or vaccination. To address the public health threat caused by the increasing SARS-CoV-2 genomic diversity, the National Institute of Allergy and Infectious Diseases within the National Institutes of Health established the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme. This effort was designed to provide a real-time risk assessment of SARS-CoV-2 variants that could potentially affect the transmission, virulence, and resistance to infection- and vaccine-induced immunity. The SAVE programme is a critical data-generating component of the US Government SARS-CoV-2 Interagency Group to assess implications of SARS-CoV-2 variants on diagnostics, vaccines and therapeutics, and for communicating public health risk. Here we describe the coordinated approach used to identify and curate data about emerging variants, their impact on immunity and effects on vaccine protection using animal models. We report the development of reagents, methodologies, models and notable findings facilitated by this collaborative approach and identify future challenges. This programme is a template for the response to rapidly evolving pathogens with pandemic potential by monitoring viral evolution in the human population to identify variants that could reduce the effectiveness of countermeasures.

Abstract Purpose Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its automation are promising but mostly require contrast-enhanced computed tomography (CT) scans. This study aimed at establishing an automated estimation of kidney volume in non-contrast, low-dose CT scans of patients with suspected urolithiasis. Methods The kidney segmentation process was automated with 2D Convolutional Neural Network (CNN) models trained on manually segmented 2D transverse images extracted from low-dose, unenhanced CT scans of 210 patients. The models’ segmentation accuracy was assessed using Dice Similarity Coefficient (DSC), for the overlap with manually-generated masks on a set of images not used in the training. Next, the models were applied to 22 previously unseen cases to segment kidney regions. The volume of each kidney was calculated from the product of voxel number and their volume in each segmented mask. Kidney volume results were then validated against results semi-automatically obtained by radiologists. Results The CNN-enabled kidney volume estimation took a mean of 32 s for both kidneys in a CT scan with an average of 1026 slices. The DSC was 0.91 and 0.86 and for left and right kidneys, respectively. Inter-rater variability had consistencies of ICC = 0.89 (right), 0.92 (left), and absolute agreements of ICC = 0.89 (right), 0.93 (left) between the CNN-enabled and semi-automated volume estimations. Conclusion In our work, we demonstrated that CNN-enabled kidney volume estimation is feasible and highly reproducible in low-dose, non-enhanced CT scans. Automatic segmentation can thereby quantitatively enhance radiological reports.

Abstract Background Photon-counting detector computed tomography (PCD-CT) may influence imaging characteristics for various clinical conditions due to higher signal and contrast-to-noise ratio in virtual monoenergetic images (VMI). Radiomics analysis relies on quantification of image characteristics. We evaluated the impact of different VMI reconstructions on radiomic features in in vitro and in vivo PCD-CT datasets. Methods An organic phantom consisting of twelve samples (four oranges, four onions, and four apples) was scanned five times. Twenty-three patients who had undergone coronary computed tomography angiography on a first generation PCD-CT system with the same image acquisitions were analyzed. VMIs were reconstructed at 6 keV levels (40, 55, 70, 90, 120, and 190 keV). The phantoms and the patients’ left ventricular myocardium (LVM) were segmented for all reconstructions. Ninety-three original radiomic features were extracted. Repeatability and reproducibility were evaluated through intraclass correlations coefficient (ICC) and post hoc paired samples ANOVA t test. Results There was excellent repeatability for radiomic features in phantom scans (all ICC = 1.00). Among all VMIs, 36/93 radiomic features (38.7%) in apples, 28/93 (30.1%) in oranges, and 33/93 (35.5%) in onions were not significantly different. For LVM, the percentage of stable features was high between VMIs ≥ 90 keV (90 versus 120 keV, 77.4%; 90 versus 190 keV, 83.9%; 120 versus 190 keV, 89.3%), while comparison to lower VMI levels led to fewer reproducible features (40 versus 55 keV, 8.6%). Conclusions VMI levels influence the stability of radiomic features in an organic phantom and patients’ LVM; stability decreases considerably below 90 keV. Relevance statement Spectral reconstructions significantly influence radiomic features in vitro and in vivo, necessitating standardization and careful attention to these reconstruction parameters before clinical implementation. Key points • Radiomic features have an excellent repeatability within the same PCD-CT acquisition and reconstruction. • Differences in VMI lead to decreased reproducibility for radiomic features. • VMI ≥ 90 keV increased the reproducibility of the radiomic features. Graphical Abstract

The novel coronavirus SARS-CoV-2 is responsible for the ongoing COVID-19 pandemic and has caused a major health and economic burden worldwide. Understanding how SARS-CoV-2 viral proteins behave in host cells can reveal underlying mechanisms of pathogenesis and assist in development of antiviral therapies. Here, the cellular impact of expressing SARS-CoV-2 viral proteins was studied by global proteomic analysis, and proximity biotinylation (BioID) was used to map the SARS-CoV-2 virus-host interactome in human lung cancer-derived cells. Functional enrichment analyses revealed previously reported and unreported cellular pathways that are associated with SARS-CoV-2 proteins. We have established a website to host the proteomic data to allow for public access and continued analysis of host-viral protein associations and whole-cell proteomes of cells expressing the viral-BioID fusion proteins. Furthermore, we identified 66 high-confidence interactions by comparing this study with previous reports, providing a strong foundation for future follow-up studies. Finally, we cross-referenced candidate interactors with the CLUE drug library to identify potential therapeutics for drug-repurposing efforts. Collectively, these studies provide a valuable resource to uncover novel SARS-CoV-2 biology and inform development of antivirals.

Abstract Background Excellent image quality is crucial for workup of hepatocellular carcinoma (HCC) in patients with liver cirrhosis because a signature tumor signal allows for non-invasive diagnosis without histologic proof. Photon-counting detector computed tomography (PCD-CT) can enhance abdominal image quality, especially in combination with a novel iterative reconstruction algorithm, quantum iterative reconstruction (QIR). The purpose of this study was to analyze the impact of different QIR levels on PCD-CT imaging of HCC in both phantom and patient scans. Methods Virtual monoenergetic images at 50 keV were reconstructed using filtered back projection and all available QIR levels (QIR 1–4). Objective image quality properties were investigated in phantom experiments. The study also included 44 patients with triple-phase liver PCD-CT scans of viable HCC lesions. Quantitative image analysis involved assessing the noise, contrast, and contrast-to-noise ratio of the lesions. Qualitative image analysis was performed by three raters evaluating noise, artifacts, lesion conspicuity, and overall image quality using a 5-point Likert scale. Results Noise power spectra in the phantom experiments showed increasing noise suppression with higher QIR levels without affecting the modulation transfer function. This pattern was confirmed in the in vivo scans, in which the lowest noise levels were found in QIR-4 reconstructions, with around a 50% reduction in median noise level compared with the filtered back projection images. As contrast does not change with QIR, QIR-4 also yielded the highest contrast-to-noise ratios. With increasing QIR levels, rater scores were significantly better for all qualitative image criteria (all p

ABSTRACT: Background: Diagnosing myocarditis relies on multimodal data, including cardiovascular magnetic resonance (CMR), clinical symptoms, and blood values. The correct interpretation and integration of CMR findings require radiological expertise and knowledge. We aimed to investigate the performance of Generative Pre-trained Transformer 4 (GPT-4), a large language model, for report-based medical decision-making in the context of cardiac MRI for suspected myocarditis. Methods: This retrospective study includes CMR reports from 396 patients with suspected myocarditis and eight centers, respectively. CMR reports and patient data including blood values, age, and further clinical information were provided to GPT-4 and radiologists with 1 (resident 1), 2 (resident 2), and 4 years (resident 3) of experience in CMR and knowledge of the 2018 Lake Louise Criteria. The final impression of the report regarding the radiological assessment of whether myocarditis is present or not was not provided. The performance of Generative pre-trained transformer 4 (GPT-4) and the human readers were compared to a consensus reading (two board-certified radiologists with 8 and 10 years of experience in CMR). Sensitivity, specificity, and accuracy were calculated. Results: GPT-4 yielded an accuracy of 83%, sensitivity of 90%, and specificity of 78%, which was comparable to the physician with 1 year of experience (R1: 86%, 90%, 84%, p = 0.14) and lower than that of more experienced physicians (R2: 89%, 86%, 91%, p = 0.007 and R3: 91%, 85%, 96%, p

Background: Healthcare workers and medical students faced new challenges during the COVID-19 pandemic. Processes within many hospitals were completely disrupted. In addition, the face to face teaching of medical students was drastically reduced. Those at risk of developing mental health problems appear to be younger health care workers and women. Objective: To investigate potential COVID-19 pandemic-related gender differences in psychological distress among medical students and physicians in their first years of practice. Design and setting: An anonymous survey was carried out online between December 1, 2021, and March 31, 2022, at the Mannheim Medical Faculty and the Würzburg Medical Faculty, Germany, after obtaining informed consent. Primary outcome measures were changes in anxiety and depression symptoms using the Hospital Anxiety and Depression Scale (HADS), and changes in participants' current quality of life using the WHO Quality of Life BREF. Results: The results show wave-like courses for perceived anxiety and burden overlapping with the course of the COVID-19 incidence. In comparison to men, women showed a significant higher increase in HADS (p = 0.005) and a reduced life quality (p = 0.007) after COVID-19. Both sexes showed different frequencies of the factors influencing quality of life, with the presence of a previous mental illness and mean anxiety having a significant higher negative impact in women. Conclusion: Future and young female physicians reported a disproportionate higher burden during COVID-19 compared to their male colleges. These observations suggest an increased need for support and prevention efforts especially in this vulnerable population.

Abstract Background MRI T2 mapping has been proven to be sensitive to the level of blood oxygenation. We hypothesized that impaired exercise capacity in chronic heart failure is associated with a greater difference between right (RV) to left ventricular (LV) blood pool T2 relaxation times due to a higher level of peripheral blood desaturation, compared to patients with preserved exercise capacity and to healthy controls. Methods Patients with chronic heart failure (n = 70) who had undergone both cardiac MRI (CMR) and a 6-min walk test (6MWT) were retrospectively identified. Propensity score matched healthy individuals (n = 35) served as control group. CMR analyses included cine acquisitions and T2 mapping to obtain blood pool T2 relaxation times of the RV and LV. Following common practice, age- and gender-adjusted nominal distances and respective percentiles were calculated for the 6MWT. The relationship between the RV/LV T2 blood pool ratio and the results from 6MWT were evaluated by Spearman’s correlation coefficients and regression analyses. Inter-group differences were assessed by independent t-tests and univariate analysis of variance. Results The RV/LV T2 ratio moderately correlated with the percentiles of nominal distances in the 6MWT (r = 0.66) while ejection fraction, end-diastolic and end-systolic volumes showed no correlation (r = 0.09, 0.07 and − 0.01, respectively). In addition, there were significant differences in the RV/LV T2 ratio between patients with and without significant post-exercise dyspnea (p = 0.001). Regression analyses showed that RV/LV T2 ratio was an independent predictor of the distance walked and the presence of post-exercise dyspnea (p

Abstract Background To evaluate the implementation process of structured reporting (SR) in a tertiary care institution over a period of 7 years. Methods We analysed the content of our image database from January 2016 to December 2022 and compared the numbers of structured reports and free-text reports. For the ten most common SR templates, usage proportions were calculated on a quarterly basis. Annual modality-specific SR usage was calculated for ultrasound, CT, and MRI. During the implementation process, we surveyed radiologists and clinical referring physicians concerning their views on reporting in radiology. Results As of December 2022, our reporting platform contained more than 22,000 structured reports. Use of the ten most common SR templates increased markedly since their implementation, leading to a mean SR usage of 77% in Q4 2022. The highest percentages of SR usage were shown for trauma CT, focussed assessment with ultrasound for trauma (FAST), and prostate MRI: 97%, 95%, and 92%, respectively, in 2022. Overall modality-specific SR usage was 17% for ultrasound, 13% for CT, and 6% for MRI in 2022. Both radiologists and referring physicians were more satisfied with structured reports and rated SR better than free-text reporting (FTR) on various attributes. Conclusions The increasing SR usage during the period under review and the positive attitude towards SR among both radiologists and clinical referrers show that SR can be successfully implemented. We therefore encourage others to take this step in order to benefit from the advantages of SR. Key points 1. Structured reporting usage increased markedly since its implementation at our institution in 2016. 2. Mean usage for the ten most popular structured reporting templates was 77% in 2022. 3. Both radiologists and referring physicians preferred structured reports over free-text reports. 4. Our data shows that structured reporting can be successfully implemented. 5. We strongly encourage others to implement structured reporting at their institutions.

Recent years have seen an increase in the variety of language names used for the Nuristani languages (Indo-Iranian), which are spoken in Eastern Afghanistan and to some extent across the border in Northern Pakistan. This increase is driven by efforts to recognize local practices, but it has also created confusion and inconsistencies in many areas, making terminological justifications a necessary part of every publication regarding these languages. A unified terminology would not only be convenient for linguists and other researchers - in so far as scientific usage can influence colloquial practices, it would also increase the visibility and recognizability of the languages of this little-known language family on the national and international level, thus also potentially benefiting the native speaking communities. The proposals given in this paper aim to create an internally consistent terminology that is scientifically precise, accurate, and recognizable for speakers, while also being congruent with the naming principles put forward for the Glottolog database.