The scope of computerized simulation in competency-based maxillofacial training: a systematic review

Oral and maxillofacial surgery (OMS) teaching is set to undergo a paradigm shift towards competency-based training. With increasing focus on resident skill development and patient safety, computerized simulators are likely to play a more mainstream role in OMS training. A systematic review of the available literature was conducted, in accordance with the PRISMA guidelines, to highlight the scope of computerized simulation in OMS teaching. A PubMed search was performed by two independent reviewers, and 35 articles published in English between 2010 and 2021 that reported the use of computerized simulation for teaching maxillofacial procedures were included in the analysis. Eight articles on minor oral surgery, seven on orthognathic surgery, five on maxillofacial trauma, five on cleft lip and palate surgery, three articles each on nerve block techniques, endoscopic procedures, and reconstructive surgery, and one article on fibre-optic intubation reported the use of computerized simulation that can be applied to OMS training. Ten randomized controlled trials were identified in the search. However there was marked heterogeneity among the studies. Simulator training for skill acquisition mentored by an expert OMS educator could offer holistic resident training; however more studies that test common themes of resident training such as knowledge acquisition and skill development are necessary.     

Clinical Simulation Augments Traditional Interviewing of Advanced Practice Provider Candidates

An essential role of critical care advanced practice providers—advanced practice registered nurses and physician assistants—is to have knowledge and competency to make accurate and efficient decisions. The ability to manage clinical scenarios involving medically deteriorating patients requires higher-order cognitive thinking and leadership skills that are challenging to extrapolate in traditional interviews. In critical care, advanced practice providers must make rapid clinical assessments and implement appropriate medical interventions to deter progression of life-threatening illnesses. Adding clinical simulation to the traditional interview allows interviewers to evaluate applicants’ crisis resource management skills, leadership, and clinical competency.     

外柱细胞软化对Corti器感音影响的生物力学研究

Corti器的感音过程容易受到内部结构属性变化的影响。外柱细胞血管舒张刺激磷蛋白缺失会减缓肌动蛋白丝的形成,从而产生听力延迟。本研究运用COMSOL建立三维有限元模型研究肌动蛋白缺失导致外柱细胞软化时,Corti器感音过程中基底膜和外毛细胞与Deiters细胞结合点的力学行为变化。结果表明,外柱细胞软化会削弱外毛细胞主动力对基底膜位移增益的放大作用,但削弱作用并不会立即产生,Corti器存在维持正常功能的"缓冲"阶段。在100 dB和120 dB之间可能存在一个声压级临界值,在该临界值两侧外柱细胞软化对基底膜应力变化的影响是截然相反的。另外外柱细胞软化对不同外毛细胞与Deiters细胞结合点力学行为的影响也不同,位移增益优先级会因此产生改变。     

Metabolism of non-steroidal anti-inflammatory drugs (NSAIDs) by Streptomyces griseolus CYP105A1 and its variants

In the field of drug development, technology for producing human metabolites at a low cost is required. In this study, we explored the possibility of using prokaryotic water-soluble cytochrome P450 (CYP) to produce human metabolites. Streptomyces griseolus CYP105A1 metabolizes various non-steroidal anti-inflammatory drugs (NSAIDs), including diclofenac, mefenamic acid, flufenamic acid, tolfenamic acid, meclofenamic acid, and ibuprofen. CYP105A1 showed 4′-hydroxylation activity towards diclofenac, mefenamic acid, flufenamic acid, tolfenamic acid, and meclofenamic acid. It should be noted that this reaction specificity was similar to that of human CYP2C9. In the case of mefenamic acid, another metabolite, 3′-hydroxymethyl mefenamic acid, was detected as a major metabolite. Substitution of Arg at position 73 with Ala in CYP105A1 dramatically reduced the hydroxylation activity toward diclofenac, flufenamic acid, and ibuprofen, indicating that Arg73 is essential for the hydroxylation of these substrates. In contrast, substitution of Arg84 with Ala remarkably increased the hydroxylation activity towards diclofenac, mefenamic acid, and flufenamic acid. Recombinant Rhodococcus erythrocyte cells expressing the CYP105A1 variant R84A/M239A showed complete conversion of diclofenac into 4′-hydroxydiclofenac. These results suggest the usefulness of recombinant R. erythropolis cells expressing actinomycete CYP, such as CYP105A1, for the production of human drug metabolites.     

Photodynamic therapy during second surgery for recurrent gliomas improves survival

BackgroundGlioma accounts for most central nervous system tumors, and the degree of invasion and malignancy are higher in the recurrent glioma. Photodynamic therapy (PDT) is an effective strategy in glioma. This study aimed to explore the risk factors for re-recurrence after a second glioma surgery and the effects of PDT on re-recurrence.MethodsThis was a retrospective study in the Second Affiliated Hospital of Harbin Medical University in China, and 43 patients that received the secondary surgery for recurrent glioma were included. The Kaplan-Meier test and Cox proportional hazard method were used to analyze.ResultsThe total re-recurrence rate after the second surgery for recurrent glioma was 48.84%. When the age increased by 1, the risk of re-recurrence increased 1.065 times (95% CI 1.000–1.134, P = 0.049). High matrix metalloproteinase (MMP) 2 expression was associated with a significantly higher risk of re-recurrence than low MMP2 expression (HR = 25.550, 95% CI 3.190–204.650, P = 0.002). Pathological grades IV and III were associated with a significantly higher risk of re-recurrence than pathological grade II (HR = 17.121, 95% CI 2.345–124.986, P = 0.005; HR = 2863.470, 95% CI 100.697–81,427.197, P < 0.001). PDT decreased the risk of re-recurrence (HR = 25.550, 95% CI 3.190–204.650, P = 0.002) and increased survival time (HR = 3.611, 95% CI 1.012–12.888, P = 0.048).ConclusionThe age, MMP2 expression, and pathological grade are independent risk factors for re-recurrence after a second surgery for recurrent glioma. PDT during the second surgery decreased the risk of re-recurrence and increased survival time.     

Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England

ObjectivesA significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England’s National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025.MethodsA scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals “missed” during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic.ResultsAs a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%.ConclusionsThis study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience.     

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

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Assessment of the Benefits of Targeted Interventions for Pandemic Control in China Based on Machine Learning Method and Web Service for COVID-19 Policy Simulation

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019(COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web inter...