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Background Due to the Covid-19 pandemic, on-site classroom teaching became limited at most German medical universities. This caused a sudden demand for digital teaching concepts. How the transfer from classroom to digital teaching or digitally assisted teaching was conducted was decided by each university and/or department individually. As a surgical discipline, Orthopaedics and Trauma have a particular focus on hands-on teaching as well as direct contact to patients. Therefore, specific challenges in designing digital teaching concepts were expected to arise. Aim of this study was to evaluate medical teaching at German universities one year into the pandemic as well as to identify potentials and pitfalls in order to develop possible optimization approaches. Methods A questionnaire with 17 items was designed and sent to the professors in charge of organising the teaching in Orthopaedics and Trauma at each medical university. A differentiation between Orthopaedics and Trauma was not made to allow a general overview. We collected the answers and conducted a qualitative analysis. Results We received 24 replies. Each university reported a substantial reduction of their classroom teaching and efforts to transfer their teaching to digital formats. Three sites were able to switch to digital teaching concepts completely, whereas others tried to enable classroom and bedside teaching at least for students of higher edcuational levels. The online platforms used varied depending on the university as well as the format it was supposed to support. Conclusion One year into the pandemic significant differences concerning the proportions of classroom and digital teaching for Orthopaedics and Trauma can be observed. Simultaneously huge differences in concepts used to create digital teaching are present. Since a complete suspense of classroom teaching was never mandatory, several universities developed hygiene concepts to enable hands-on and bedside teaching. Despite these differences, some similarities were observed: the lack of time and personnel to generate adequate teaching material was reported as the leading challenge by all participants of this study.

Background Due to the global digitalization, implementation of digital elements into daily work can support physiotherapists’ work but may also pose some challenges. Only little is known about physiotherapists’ attitude towards digitalization. This study primarily aimed to analyze physiotherapists’ attitude towards digitalization and to what extend digital tools have been implemented into their daily work. In second analysis, participants’ characteristics such as age, working place, gender and mode of survey participation were assessed. Methods A 12-main-item survey amongst voluntary course participants of one physiotherapeutic training center was conducted via paper-based as well as online questionnaires between July 2018 and June 2019 including questions on participants’ general as well as particular attitude towards digitalization, the use of (mobile) applications and possible advantages and disadvantages of the ongoing digital transformation. Sub-analysis was performed for age (≤40 years versus > 40 years), gender, mode of participation (paper vs. online) and working place (practice vs. hospital). Results Overall, 488 physiotherapists participated in the survey. In comparison of the age groups, younger participants had more concerns about data security (p = 0.042) and insufficient financial remuneration (p p = 0.0001). Physiotherapists working in the outpatient sector, rather than in hospitals, expected digitalization to increase more in relevance (p p = 0.002). 50.4% of the considered digitalization as useful for their job. Conclusions The majority of participants saw high potential for digitalization in the physiotherapy sector. Younger physiotherapists seem to be more concerned about data security and insufficient financial remuneration. Physiotherapists in the outpatient sector seem to see more potential in digital transformations. General concerns like missing reimbursement, lack of data security or knowledge on legal frameworks should be addressed in the future. Further studies should focus on identifying specific digital tools which can support physiotherapists.

Additional file 1.

IntroductionTreating severely injured patients requires numerous critical decisions within short intervals in a highly complex situation. The coordination of a trauma team in this setting has been shown to be associated with multiple procedural errors, even of experienced care teams. Machine learning (ML) is an approach that estimates outcomes based on past experiences and data patterns using a computer-generated algorithm. This systematic review aimed to summarize the existing literature on the value of ML for the initial management of severely injured patients.MethodsWe conducted a systematic review of the literature with the goal of finding all articles describing the use of ML systems in the context of acute management of severely injured patients. MESH search of Pubmed/Medline and Web of Science was conducted. Studies including fewer than 10 patients were excluded. Studies were divided into the following main prediction groups: (1) injury pattern, (2) hemorrhage/need for transfusion, (3) emergency intervention, (4) ICU/length of hospital stay, and (5) mortality.ResultsThirty-six articles met the inclusion criteria; among these were two prospective and thirty-four retrospective case series. Publication dates ranged from 2000 to 2020 and included 32 different first authors. A total of 18,586,929 patients were included in the prediction models. Mortality was the most represented main prediction group (n = 19). ML models used were artificial neural network ( n = 15), singular vector machine (n = 3), Bayesian network (n = 7), random forest (n = 6), natural language processing (n = 2), stacked ensemble classifier [SuperLearner (SL), n = 3], k-nearest neighbor (n = 1), belief system (n = 1), and sequential minimal optimization (n = 2) models. Thirty articles assessed results as positive, five showed moderate results, and one article described negative results to their implementation of the respective prediction model.ConclusionsWhile the majority of articles show a generally positive result with high accuracy and precision, there are several requirements that need to be met to make the implementation of such models in daily clinical work possible. Furthermore, experience in dealing with on-site implementation and more clinical trials are necessary before the implementation of ML techniques in clinical care can become a reality.

Background Artificial intelligence (AI) is one of the most promising areas in medicine with many possibilities for improving health and wellness. Already today, diagnostic decision support systems may help patients to estimate the severity of their complaints. This fictional case study aimed to test the diagnostic potential of an AI algorithm for common sports injuries and pathologies. Methods Based on a literature review and clinical expert experience, five fictional “common” cases of acute, and subacute injuries or chronic sport-related pathologies were created: Concussion, ankle sprain, muscle pain, chronic knee instability (after ACL rupture) and tennis elbow. The symptoms of these cases were entered into a freely available chatbot-guided AI app and its diagnoses were compared to the pre-defined injuries and pathologies. Results A mean of 25–36 questions were asked by the app per patient, with optional explanations of certain questions or illustrative photos on demand. It was stressed, that the symptom analysis would not replace a doctor’s consultation. A 23-yr-old male patient case with a mild concussion was correctly diagnosed. An ankle sprain of a 27-yr-old female without ligament or bony lesions was also detected and an ER visit was suggested. Muscle pain in the thigh of a 19-yr-old male was correctly diagnosed. In the case of a 26-yr-old male with chronic ACL instability, the algorithm did not sufficiently cover the chronic aspect of the pathology, but the given recommendation of seeing a doctor would have helped the patient. Finally, the condition of the chronic epicondylitis in a 41-yr-old male was correctly detected. Conclusions All chosen injuries and pathologies were either correctly diagnosed or at least tagged with the right advice of when it is urgent for seeking a medical specialist. However, the quality of AI-based results could presumably depend on the data-driven experience of these programs as well as on the understanding of their users. Further studies should compare existing AI programs and their diagnostic accuracy for medical injuries and pathologies., Postprints der Universität Potsdam : Humanwissenschaftliche Reihe; 711

Additional file 5: Supplement 5. Generated by the App ADA for case 5 (“Mild concussion”).

Additional file 2: Supplement 2. Generated by the App ADA for case 2 (“Ankle sprain”)

Additional file 1: Supplement 1. Generated by the App ADA for case 1 (“Tennis elbow”)

Additional file 3: Supplement 3. Generated by the App ADA for case 3 (“Delayed onset of muscle soreness”).

Additional file 4: Supplement 4. Generated by the App ADA for case 4 (“ACL rupture with chronic instability”).

The questionnaire, which served as a survey instrument (the text was translated from German into English). It was made available to the addressed medical schools in Austria, Germany and Switzerland with the online program SurveyMonkeyÂŽ (SurveyMonkey, Oregon, USA). The survey consisted of 49 items, with 27 closed questions and 22 questions for free text answers. (DOCX 30 kb)

Original answers (n = 21) of the participating medical schools to the question “Which challenges do you see in the field of e-learning for your medical school in the next years?” (This was translated from German into English.) Each number represents commentaries of one medical school (anonymous). (DOCX 23 kb)

Das Bisphosphonat Zoledronat (ZOL) wird gegenwärtig zur Behandlung von Tumor assoziierter Hyperkalzämie, Knochenmetastasen und Osteoporose eingesetzt. Es wurde in der Literatur gezeigt, dass Zoledronat die Aktivität von Osteoklasten hemmt und die der Osteoblasten in-vitro positiv beeinflusst. Diese Eigenschaften könnten sich vorteilhaft auf die Behandlung von Frakturen durch eine lokale Applikation auswirken. Die Fragestellung der vorliegenden Dissertation war, ob es unter lokaler Applikation des Bisphosphonat Zoledronat durch eine biodegradierbare Poly(D,L-Laktid)-Beschichtung von Implantaten zu einer - gemessen an der biomechanischen Stabilität - früheren und verbesserten Frakturheilung kommt. An einem Rattenfrakturmodell wurde eine Applikationsdosis von 50µM Zoledronat untersucht. Die radiologische Auswertung zeigte signifikant erhöhte Frakturkonsolidierungen der ZOL-Gruppe bei 42 Tagen ohne signifikante Unterschiede zu Vergleichsgruppen bei 28 und 84 Tagen. Die Kallusfläche wie auch das polare Flächenträgheitsmoment waren zu allen Zeitpunkten in der ZOL-Gruppe signifikant erhöht. Bei der biomechanischen Testung waren nach 42 Tagen das maximale Drehmoment und die torsionale Steifigkeit in der ZOL-Gruppe im Vergleich zu den Kontrollgruppen signifikant erhöht. Während nach 84 Tagen das maximale Drehmoment der Kontrollgruppen die Werte der ZOL-Gruppe erreichte, blieb die torsionale Steifigkeit der ZOL- Gruppe signifikant erhöht gegenüber der Gruppe ohne Beschichtung. Aus den Ergebnissen kann man schließen, dass die lokale Applikation von Zoledronat aus einer PDLLA-Beschichtung das Wiedererlangen biomechanischer Stabilität nach Fraktur beschleunigen und verbessern kann. In dieser Studie konnten keine systemischen Nebenwirkungen durch die lokale Applikation von PDLLA oder Zoledronat beobachtet werden. Der Einsatz von Bisphosphonaten bei der Frakturheilung ist noch Gegenstand der aktuellen Forschung. Diese Studie liefert Hinweise darauf, dass bei der möglichen Behandlung von Frakturen in Zukunft die lokale Anwendung von Zoledronat als Alternative zu einer systemischen Applikation in Betracht gezogen werden kann., BACKROUND AND PURPOSE: Zoledronic acid (ZOL) has been shown in vitro and in vivo to inhibit osteoclastic activity and to regulate osteoblasts. Its antiresorptive effect is used clinically in the treatment of bone-consuming pathologies to prevent skeletal complications. Because of its impact on bone cells, there might be a possible benefit in treatment of fractures by local application from a biodegradable poly(D,L-lactide) (PDLLA) coating of osteosynthetic implants. The effect of locally applied ZOL from a PDLLA coating of intramedullary implants on fracture healing was analyzed in this study. MATERIAL AND METHODS: Standardized midshaft fractures of the right tibia of 5-month-old rats were stabilized either with uncoated, PDLLA-coated and ZOL-coated implants. Blood serum analysis, body weight and body temperature and X-ray examinations were taken regularly. Animals were sacrificed 42 or 84 days after fracture. Tibiae were dissected and biomechanically tested for torsional stiffness and maximum load, which were determined in percentage of the contralateral, non-fractured side. RESULTS: X-rays demonstrated 42 days after fracture at least unilateral fracture consolidation in all groups. Biomechanical testing revealed a significantly higher maximum load and torsional stiffness in the group treated with ZOL in comparison to the controls. 84 days after fracture the torsional stiffness of the ZOL treated group remained significantly higher than the uncoated group whereas the maximum load of the control groups reached the results of the ZOL coated group. INTERPRETATION: Presented results suggest that local application of ZOL from the PDLLA coating accelerates the achievement of biomechanical stability in fractures.

Human behavior in virtual environments is commonly implemented as a finite state machine. This programming approach can be effective and challenging against human players, but its ability to realistically simulate the behavior of cooperative groups of soldiers is limited. This thesis covers the development of an agent-based system to control the behavior of infantry in 3D virtual environments. The system design divides the cognitive process into four modules: perception, mental model, goal, decision, and action resolution. Each module attempts to simulate both strengths and weaknesses of human perception and cognition, including instinctive reactions, perceptual error, memory degradation, context-dependent decision-making, and inference. Additionally, the soldiers are influenced by the actions and decisions of the agents around them, enabling cooperation. The resultant agent system was incorporated into a game-like interface and compared to a similar commercial game with standard AI. Overall, 72% of the test subjects thought that the agent behaviors were Mostly Realistic or Totally Realistic, and 81% found them to be equal to or better than those in the commercial game. http://archive.org/details/agentbasedsoldie109456095 US Navy (USN) author.

Human immune deficiency virus (HIV) currently affects around 34 million people worldwide, but due to recent advancements in antiretroviral treatments the morbidity and mortality of HIV has greatly improved (UNIAIDS, 2009). Tenofovir (TFV) is a nucleoside reverse transcriptase inhibitor (NRTI) that is currently widely used in most HIV regimens due to its favourable pharmacokinetic and pharmacodynamic properties, which allows for once daily dose (Gallent et al., 2004). TFV is used to treat HIV in both treatment experienced and treatment naive patients; it is also used as a treatment for hepatitis B and has recently been approved for use as a pre-exposure prophylaxis treatment. The preclinical trials for TFV showed that it had a good safety profile, however there has been an increasing number of patients presenting with TFV induced renal damage specifically proximal tubule dysfunction (Cooper et al., 2010). It was hypothesised that TFV was inducing this tubule damage via mitochondrial dysfunction, as this has been widely reported as an adverse reaction associated with NRTI’s (Kontorinis et al., 2003). Within these studies in vitro cell models were modified via culturing them in galactose media in order to probe for mitotoxins (Marroquin et al., 2007). The cytotoxicity and mechanisms of cell death induced via TFV were elucidated within these modified cell lines. Work presented has shown that TFV causes delayed mitochondrial cytotoxicity, which causes a cell cycle arrest within the G2/M phase leading to an accumulation of cell within the S phase. It was shown that the cell cycle arrest is likely due to the inhibition of mitochondrial polymerase γ leading to decreased mitochondrial DNA and ultimately cell death firstly via apoptosis (caused by release of caspase 3/ 7), and then necrosis when cellular ATP levels become too low to sustain apoptosis. Work presented also showed that autophagy induced by TFV, may play a protective role within cells at lower time period. A study within this thesis using patient urine samples was presented to look for a possible biomarker of TFV proximal tubule dysfunction. Kidney injury molecule-1 (KIM-1) was selected as previous studies have shown that it is specific to proximal tubule cells (Ichimura et al., 2008). Results demonstrated that TFV did not significantly alter the KIM-1 / creatinine ratio within patient urine samples. However the data from this pilot study are novel and should be used for future research into the possible use of KIM-1 as a biomarker for TFV induced proximal tubule dysfunction. The biomarker work presented within this thesis should be carried forward to power a future study using a larger and adequate patient cohort. The work presented within this thesis has now opened doors for further study into this subject area especially with regards to the study of KIM-1 as a biomarker, which is a pressing matter as TFV is now widely available for use as a PrEP treatment.