Recognition of moyamoya disease and its hemorrhagic risk using deep learning algorithms:sourced from retrospective studies

Although intracranial hemorrhage in moyamoya disease can occur repeatedly,predicting the disease is difficult.Deep learning algorithms developed in recent years provide a new angle for identifying hidden risk factors,evaluating the weight of different factors,and quantitatively evaluating the risk of intracranial hemorrhage in moyamoya disease.To investigate whether convolutional neural network algorithms can be used to recognize moyamoya disease and predict hemorrhagic episodes,we retrospectively selected 460 adult unilateral hemispheres with moyamoya vasculopathy as positive samples for diagnosis modeling,including 418 hemispheres with moyamoya disease and 42 hemispheres with moyamoya syndromes.Another 500 hemispheres with normal vessel appearance were selected as negative samples.We used deep residual neural network(ResNet-152)algorithms to extract features from raw data obtained from digital subtraction angiography of the internal carotid artery,then trained and validated the model.The accuracy,sensitivity,and specificity of the model in identifying unilateral moyamoya vasculopathy were 97.64±0.87%,96.55±3.44%,and 98.29±0.98%,respectively.The area under the receiver operating characteristic curve was 0.990.We used a combined multi-view conventional neural network algorithm to integrate age,sex,and hemorrhagic factors with features of the digital subtraction angiography.The accuracy of the model in predicting unilateral hemorrhagic risk was 90.69±1.58%and the sensitivity and specificity were 94.12±2.75%and 89.86±3.64%,respectively.The deep learning algorithms we proposed were valuable and might assist in the automatic diagnosis of moyamoya disease and timely recognition of the risk for re-hemorrhage.This study was approved by the Institutional Review Board of Huashan Hospital,Fudan University,China(approved No.2014-278)on January 12,2015.

Nonlinear finite element analysis of three implant-abutment interface designs

The objective of this study was to investigate the mechanical characteristics of implant-abutment interface design in a dental implant system, using nonlinear finite element analysis （FEA） method. This finite element simulation study was applied on three commonly used commercial dental implant systems： model I, the reduced-diameter 3i implant system （West Palm Beach, FL, USA） with a hex and a 12-point double internal hexagonal connection; model II, the Semados implant system （Bego, Bremen, Germany） with combination of a conical （45° taper） and internal hexagonal connection; and model III, the Br,~nemark implant system （Nobel Biocare, Gothenburg, Sweden） with external hexagonal connection. In simulation, a force of 170 N with 45°oblique to the longitudinal axis of the implant was loaded to the top surface of the abutment. It has been found from the strength and stiffness analysis that the 3i implant system has the lowest maximum yon Mises stress, prirlcipal stress and displacement, while the Br^nemark implant system has the highest. It was concluded from our preliminary study using nonlinear FEA that the reduced-diameter 3i implant system with a hex and a 12-point double internal hexagonal connection had a better stress distribution, and produced a smaller displacement than the other two implant systems.

Bilateral maxillary fused second and third molars:a rare occurrence

This case report describes the diagnosis and endodontic therapy of maxillary fused second and third molars, using cone-beam computed tomography （CBCT）. A 31-year-old Chinese male, with no contributory medical or family/social history, presented with throbbing pain in the maxillary right molar area following an unsuccessful attempted tooth extraction. Clinical examination revealed what appeared initially to be a damaged large extra cusp on the buccal aspect of the distobuccal cusp of the second molar. However, CBCT revealed that a third molar was fused to the second molar. Unexpectedly, the maxillary left third molar also was fused to the second molar, and the crown of an unerupted supernumerary fourth molar was possibly also fused to the apical root region of the second molar. Operative procedures should not be attempted without adequate radiographic investigation. CBCT allowed the precise location of the root canals of the right maxillary fused molar teeth to permit successful endodontic therapy, confirmed after 6 months.

Adult stem cell-based apexogenesis

Generally, the dental pulp needs to be removed when it is infected, and root canal therapy(RCT) is usually required in which infected dental pulp is replaced with inorganic materials(paste and gutta percha). This treatment approach ultimately brings about a dead tooth. However, pulp vitality is extremely important to the tooth itself, since it provides nutrition and acts as a biosensor to detect the potential pathogenic stimuli. Despite the reported clinical success rate, RCT-treated teeth are destined to be devitalized, brittle and susceptible to postoperative fracture. Recently, the advances and achievements in the field of stem cell biology and regenerative medicine have inspired novel biological approaches to apexogenesis in young patients suffer-ing from pulpitis or periapical periodontitis. This review mainly focuses on the benchtop and clinical regeneration of root apex mediated by adult stem cells. Moreover, current strategies for infected pulp therapy are also discussed here.

Role of anthropogenic forcing and atmospheric circulation in a lowtemperature event in February 2022 in eastern China

In February 2022,eastern China experienced prolonged low temperatures,with significant impacts on agriculture,transportation,and power supply.The regional average temperature anomaly for February 2022 was-0.65℃,making it the third coldest February from 2000 to 2022.Understanding the influence of anthropogenic forcing and atmospheric circulation on low-temperature events is important for climate change adaptation and mitigation in the region.This study used observational and model data from the Coupled Model Intercomparison Project Phase 6 to conduct an extreme event attribution study.The results showed that anthropogenic forcing led to a 1.5-fold decrease in the probability of 2022-like events,with anthropogenic greenhouse gases being the primary contributors to this reduction.Conversely,aerosols slightly increased the likelihood of such events.To evaluate the role of atmospheric circulation in this event,we chose Siberian High as the key circulation system and employed circulation similarity,intensity classification,and regression methods to estimate the impacts of circulation patterns,circulation in-tensity,and human-induced circulation change.The results demonstrated that under the influence of the same anthropogenic forcing,the presence of an anomalous Siberian High and anomalously enhanced intensity of the Siberian High both increased the likelihood of such a cold event occurrence.However,anthropogenic forcing exerts a negligible effect on such cold events via anomalous circulation.