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IntroductionTraumatic brain injury (TBI) is a heterogeneous condition with a broad spectrum of injury severity, pathophysiological processes and variable outcomes. For moderate-to-severe TBI survivors, recovery is often protracted and outcomes can range from total dependence to full recovery. Despite advances in medical treatment options, prognosis remains largely unchanged. The objective of this study is to develop a machine learning predictive model for neurological outcomes at 6 months in patients with a moderate-to-severe TBI, incorporating longitudinal clinical, multimodal neuroimaging and blood biomarker predictor variables.Methods and analysisA prospective, observational, cohort study will enrol 300 patients with moderate-to-severe TBI from seven Australian hospitals over 3 years. Candidate predictors including demographic and general health variables, and longitudinal clinical, neuroimaging (CT and MRI), blood biomarker and patient-reported outcome measures will be collected at multiple time points within the acute phase of injury. The predictor variables will populate novel machine learning models to predict the Glasgow Outcome Scale Extended 6 months after injury. The study will also expand on current prognostic models by including novel blood biomarkers (circulating cell-free DNA), and the results of quantitative neuroimaging such as Quantitative Susceptibility Mapping and Dynamic Contrast Enhanced MRI as predictor variables.Ethics and disseminationEthical approval has been obtained by the Royal Brisbane and Women’s Hospital Human Research Ethics Committee, Queensland. Participants or their substitute decision-maker/s will receive oral and written information about the study before providing written informed consent. Study findings will be disseminated by peer-review publications and presented at national and international conferences and clinical networks.Trial registration numberACTRN12620001360909.

Dual-task is the concurrent performance of two independent single tasks (ST) that have distinct goals. Daily variations in performance of singular cognitive or motor tasks are reported in the literature.To investigate whether performance of a dual-task (DT) varies based on the time of day and whether there is interference between the motor and cognitive aspect of DT.Participants performed a 10 Meter Walk Test (10MWT) for motor and a Stroop Test for cognitive task. The DT activity combined both STs. All participants performed three trials for all three conditions at three different times of the day (morning, noon, afternoon), on separate testing days.Data were collected on 42 participants. Most participants were female (28/42), average age of 27.95 ± 9.28 years, and BMI of 25.58 ± 4.49 Kg/m2. Walking velocities in ST were consistently faster than in DT, p .0005. In DT conditions, the participants walked faster at noon (1.21 ± 0.13 m/s) compared to the morning (1.16 ± 0.15 m/s, p = 0.01) or the afternoon (1.16 ± 0.18 m/s, p = 0.04). The participants' score on the DT-Stroop test were only different at noon (11.43 ± 2.28) when compared to morning (10.67 ± 1.34, p = 0.006). The percentage DT-Cognitive interference effect was 26.1 % in the morning, 11.8 % at noon and 13.4 % in the afternoon. The Motor interference was -14.6 % in the morning, -12.2 % at noon and -13.8 % in the afternoon.Noon is the best time to perform a dual task condition. Noon consistently exhibited the least motor or cognitive interference. Conversely, the maximum boost in cognitive performance was observed in the mornings.

COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint servers. Much of the research effort has focused on the discovery of novel drug candidates or repurposing of existing drugs against COVID-19, and many such projects have been either exclusively computational or computer-aided experimental studies. Herein, we provide an expert overview of the key computational methods and their applications for the discovery of COVID-19 small-molecule therapeutics that have been reported in the research literature. We further outline that, after the first year the COVID-19 pandemic, it appears that drug repurposing has not produced rapid and global solutions. However, several known drugs have been used in the clinic to cure COVID-19 patients, and a few repurposed drugs continue to be considered in clinical trials, along with several novel clinical candidates. We posit that truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19., We cover diverse methodologies, computational approaches, and case studies illustrating the ongoing efforts to develop viable drug candidates for treatment of COVID-19.

The objective of this study was to characterize head biomechanics of video-recorded falls involving young children in a licensed childcare setting. Children 12 to 2, max linear head velocity was 3.8 m/s and max rotational head velocity was 21.6 rad/s. Falls with head impact had significantly higher biomechanical measures. There was no correlation between head acceleration and fall height. No serious injuries resulted from falls—only 1 child had a minor injury. In conclusion, wearable sensors enabled characterization of head biomechanics during video-recorded falls involving young children in a childcare setting. Falls in this setting did not result in serious injury.

Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation.

Molecular prognostic assays, such as Oncotype DX, are increasingly incorporated into the management of patients with invasive breast carcinoma. BreastPRS is a new molecular assay developed and validated from a meta-analysis of publically available genomic datasets. We applied the assay to matched fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tumor samples to translate the assay to FFPE. A linear relationship of the BreastPRS prognostic score was observed between tissue preservation formats. BreastPRS recurrence scores were compared with Oncotype DX recurrence scores from 246 patients with invasive breast carcinoma and known Oncotype DX results. Using this series, a 120-gene Oncotype DX approximation algorithm was trained to predict Oncotype DX risk groups and then applied to series of untreated, node-negative, estrogen receptor (ER)-positive patients from previously published studies with known clinical outcomes. Correlation of recurrence score and risk group between Oncotype DX and BreastPRS was statistically significant (P

Virtual reality simulation is a promising alternative to training surgical residents outside the operating room. It is also a useful aide to anatomic study, residency training, surgical rehearsal, credentialing, and recertification. Surgical simulation is based on a virtual reality with varying degrees of immersion and realism. Simulators provide a no-risk environment for harmless and repeatable practice. Virtual reality has three main components of simulation: graphics/volume rendering, model behavior/tissue deformation, and haptic feedback. The challenge of accurately simulating the forces and tactile sensations experienced in neurosurgery limits the sophistication of a virtual simulator. The limited haptic feedback available in minimally invasive neurosurgery makes it a favorable subject for simulation. Virtual simulators with realistic graphics and force feedback have been developed for ventriculostomy, intraventricular surgery, and transsphenoidal pituitary surgery, thus allowing preoperative study of the individual anatomy and increasing the safety of the procedure. The authors also present experiences with their own virtual simulation of endoscopic third ventriculostomy.

Many medicinal chemistry-relevant structures and core scaffolds tend toward geometric planarity, which hampers the optimization of physicochemical properties desirable in drug-like molecules. As challenging drug target classes emerge, the exploitation of molecular three-dimensionality in lead optimization is becoming increasingly important. While recent interest has emphasized the importance of enhanced three-dimensionality in molecular fragment designs, the extent to which this is required in core scaffolds remains unclear.Three computational methods, Scaffold Tree deconstruction, Synthetic Disconnection Rules retrosynthetic deconstruction and virtual library enumeration, are applied, together with the descriptors plane of best fit and principal moments of inertia, to investigate the origins of three-dimensionality in drug-like molecules.This study informs on the stage at which molecular three-dimensionality should be considered in drug design.

Human cytomegalovirus (CMV) is a large enveloped virus that encodes multiple glycoproteins required for virus-cell binding and fusion. To assess the binding properties of antibodies with target glycoprotein in a natural context of infection, we investigated the feasibility of using the surface plasmon resonance (SPR) technique for studying the direct binding of antibodies with CMV virions. Direct immobilization of whole virions to sensor surface and a surface regeneration procedure allowed for quantitative and reproducible measurements of binding affinity and binding kinetics of antibody-whole virion interactions. The conformational and functional integrity of viral particles was not compromised by the regeneration condition as evaluated with antibodies recognizing conformational epitopes and by electron microscopy. Binding of an irrelevant antibody was not observed, indicating the high specificity of the method. A panel of anti-gB antibodies was measured and the binding affinities correlated fairly well with those determined by ELISA. These data demonstrated that the interaction of anti-gB antibody with whole virion of large enveloped CMV can be quantitatively studied using SPR. This method has been successfully applied for screening and selection of anti-CMV antibodies and can be potentially extended to study antibody-glycoprotein interactions of other related herpesviruses.

We recently showed that increasing Wnt/beta-catenin signalling in the bone marrow microenvironment or in multiple myeloma (MM) cells clearly suppresses osteoclastogenesis in SCID-hu mice; however, this regulation of osteoclastogenesis could result directly from activation of Wnt/beta-catenin signalling in osteoclasts or indirectly from effects on osteoblasts. The present studies characterized Wnt/beta-catenin signalling and its potential role in osteoclasts. Systematic analysis of expression of WNT, FZD, LRP and TCF gene families demonstrated that numerous Wnt-signalling components were expressed in human osteoclasts from patients with MM. Functional Wnt/beta-catenin signalling was identified by accumulation of total and active beta-catenin and increases in Dvl-3 protein in response to Wnt3a or LiCl. Furthermore, Wnt-induced increases in beta-catenin and Dvl-3 were attenuated by Wnt antagonists Dkk1 and sFRP1. Finally, Wnt3a-induced TCF/LEF transcriptional activity suggests that canonical Wnt signalling is active in osteoclasts. Supernatants from dominant-negative-beta-catenin-expressing osteoblast clones significantly stimulated tartrate-resistant acid phosphatase-positive osteoclast formation from primary MM-derived osteoclasts, compared with supernatants from control cells. These results suggested that Wnt/beta-catenin signalling is active in osteoclasts in MM and is involved in osteoclastogenesis in bone marrow, where it acts as a negative regulator of osteoclast formation in an osteoblast-dependent manner in MM.

Purpose The aim of this study was to identify the relative anatomic locations of relevant vital structures at risk for injury during posterior iliac crest bone graft procurement. Materials and Methods Twenty-one cadavers yielded 39 intact posterior ilia for dissection. The posterior superior iliac spine (PSIS) was used as the primary reference landmark. Measurements were made to the medial branch of the superior cluneal nerves, the superior branch of the middle cluneal nerves, the sciatic notch, and the superior gluteal vessels. Distances from the spinal midline to the superior cluneal nerves were recorded. Results The average distances from the PSIS to the superior and middle cluneal nerves, greater sciatic notch, and superior gluteal vessels were 5.7 cm (standard deviation, 1.22 cm), 6.55 cm (standard deviation, 1.53 cm), 5.3 cm (standard deviation, 0.71 cm), and 5.4 cm (standard deviation, 0.95 cm), respectively. The most medial superior cluneal nerve was identified at 3.0 to 4.9 cm from the PSIS in 23% of cases, at 5.0 to 6.9 cm from the PSIS in 61.5% of cases, and farther than 7.0 cm from the PSIS in 15.4% of cases. Conclusions This study illustrates that the most medial superior cluneal nerve is often closer to the PSIS than previously described and the same holds true for the greater sciatic notch and superior gluteal vessels. Knowledge of the anatomic locations of these important structures should allow the surgeon to avoid or decrease the complication rate of bone procurement from the posterior ilium.

Human cytomegalovirus (HCMV) enters cells through a complex pathway involving the interaction of multiple viral glycoproteins and cellular receptors. While HCMV clinical isolates enter a wide range of cell types, entry has historically been studied using a laboratory strain of virus that can only infect fibroblasts. Herein, we have constructed a HCMV reporter strain that contains GFP fused to the abundant tegument protein pp65 to allow for the direct visualization of virus attachment and entry. Furthermore, the UL131 gene of this strain was restored to clinical isolate sequence to expand our studies of entry into physiologically relevant epithelial cell types. Using the HCMV-GFP reporter virus, we developed an image-based assay and screened a library containing 65,000 compounds for the inhibition of virus entry into fibroblasts. In addition to assessing the effect on virus entry, automated image analysis provided information on compound toxicity and whether the compounds acted as attachment or post-attachment inhibitors. To identify therapeutically viable inhibitors capable of blocking entry in multiple cell types, the inhibitors were screened further for their ability to inhibit virus entry into epithelial cells. Compounds were identified that were able to inhibit virus entry into both cell types at either attachment or post-attachment steps.

Chemogenomics knowledge-based drug discovery approaches aim to extract the knowledge gained from one target and to apply it for the discovery of ligands and hopefully drugs of a new target which is related to the parent target by homology or conserved molecular recognition. Herein, we demonstrate the potential of knowledge-based virtual screening by applying it to the MDM4-p53 protein-protein interaction where the MDM2-p53 protein-protein interaction constitutes the parent reference system; both systems are potentially relevant to cancer therapy. We show that a combination of virtual screening methods, including homology based similarity searching, QSAR (Quantitative Structure-Activity Relationship) methods, HTD (High Throughput Docking), and UNITY pharmacophore searching provide a successful approach to the discovery of inhibitors. The virtual screening hit list is of the magnitude of 50,000 compounds picked from the corporate compound library of approximately 1.2 million compounds. Emphasis is placed on the facts that such campaigns are only feasible because of the now existing HTCP (High throughput Cherry-Picking) automation systems in combination with robust MTS (Medium Throughput Screening) fluorescence-based assays. Given that the MDM2-p53 system constitutes the reference system, it is not surprising that significantly more and stronger hits are found for this interaction compared to the MDM4-p53 system. Novel, selective and dual hits are discovered for both systems. A hit rate analysis will be provided compared to the full HTS (High-throughput Screening).

Multiple myeloma (MM) is characterized by osteolytic bone lesions (OBL) that arise as a consequence of osteoblast inactivation and osteoclast activation adjacent to tumor foci within bone. Wnt signaling in osteoblasts regulates osteoclastogenesis through the differential activation and inactivation of Receptor Activator of Nuclear factor Kappa B Ligand (RANKL) and osteoprotegerin (OPG), positive and negative regulators of osteoclast differentiation, respectively. We demonstrate here that MM cell–derived DKK1, a soluble inhibitor of canonical Wnt signaling, disrupted Wnt3a-regulated OPG and RANKL expression in osteoblasts. Confirmed in multiple independent assays, we show that pretreatment with rDKK1 completely abolished Wnt3a-induced OPG mRNA and protein production by mouse and human osteoblasts. In addition, we show that Wnt3a-induced OPG expression was diminished in osteoblasts cocultured with a DKK1-expressing MM cell line or primary MM cells. Finally, we show that bone marrow sera from 21 MM patients significantly suppressed Wnt3a-induced OPG expression and enhanced RANKL expression in osteoblasts in a DKK1-dependent manner. These results suggest that DKK1 may play a key role in the development of MM-associated OBL by directly interrupting Wnt-regulated differentiation of osteoblasts and indirectly increasing osteoclastogenesis via a DKK1-mediated increase in RANKL-to-OPG ratios.

Although the theoretical concern of genetic recombination has been raised related to the use of live attenuated flavivirus vaccines [Seligman, Gould, Lancet 2004;363:2073-5], it has little foundation [e.g., Monath TP, Kanesa-Thasan N, Guirakhoo F, Pugachev K, Almond J, Lang J, et al. Vaccine 2005;23:2956-8]. To investigate biological effects of recombination between a chimeric yellow fever (YF) 17D/Japanese encephalitis (JE) vaccine virus (ChimeriVax-JE) and a wild-type flavivirus Kunjin (KUN-cDNA), the prM-E envelope protein genes were swapped between the two viruses, resulting in new YF 17D/KUN(prM-E) and KUN/JE(prM-E) chimeras. The prM-E genes are easily exchangeable between flavivirues, and thus the exchange was expected to yield the most replication-competent chimeras, while other rationally designed recombinants would be more likely to be crippled or non-viable. The new chimeras proved highly attenuated in comparison with the KUN-cDNA parent, as judged by plaque size and growth kinetics in cell culture, low viremia in hamsters, and reduced neurovirulence/neuroinvasiveness in mice. These data provide strong experimental evidence that the potential of recombinants, should they ever emerge, to cause disease or spread (compete in nature with wild-type flaviviruses) would be indeed extremely low.

A virtual environment-based endoscopic third ventriculostomy simulator is being developed for training neurosurgeons as a standardized method for evaluating competency. Magnetic resonance (MR) images of a patient's brain are used to construct the geometry model, realistic behavior in the surgical area is simulated by using physical modeling and surgical instrument handling is replicate by a haptic interface. The completion of the proposed virtual training simulator will help the surgeon to practice the techniques repeatedly and effectively, serving as a powerful educational tool.

1. 1. An unusual case of esophageal defect is reported due to rupture of the nucleus pulposus between T1 and T2. The only symptoms were a vague pressure sensation in the neck and slight difficulty in swallowing saliva. 2. 2. Review of the literature fails to reveal a similar case. 3. 3. This type of esophageal defect must be rare but should be listed in the differential diagnosis of extrinsic defects of the esophagus.

A case of uremia in which the patient developed a large anterior mediastinal hematoma is presented. Hemorrhage into the anterior mediastinum can be mistaken for acute pericarditis since pericarditis is a relatively common complication of uremia.

Background Widespread adoption of genomic technologies in the management of heterogeneous indications, including Multiple Myeloma, has been hindered by concern over variation between published gene expression signatures, difficulty in physician interpretation and the challenge of obtaining sufficient genetic material from limited patient specimens. Methods Since 2006, the 70-gene prognostic signature, developed by the University of Arkansas for Medical Sciences (UAMS) has been applied to over 4,700 patients in studies performed in 4 countries and described in 17 peer-reviewed publications. Analysis of control sample and quality control data compiled over a 12-month period was performed. Results Over a 12 month period, the 70-gene prognosis score (range 0–100) of our multiple myeloma cell-line control sample had a standard deviation of 2.72 and a coefficient of variance of 0.03. The whole-genome microarray profile used to calculate a patient’s GEP70 score can be generated with as little as 15 ng of total RNA; approximately 30,000 CD-138+ plasma cells. Results from each GEP70 analysis are presented as either low (70-gene score