伊朗传统医学治疗牙周疾病

目的:牙周疾病非常普遍,尽管有各种特定的治疗方法,但我们始终面临治疗方法有限的问题。考虑到世界组织十分关注传统医学在医疗服务中的发展和应用,我们在一直考察研究伊朗传统医学中药物对牙周疾病的治疗作用。方法:此项研究是一个对有关方面书籍的综合论述,伊朗传统医学内容是经过对重量级作者如Avicenna和Alzahrawy所著的有价值的书籍修订,收集了各医学院校馆藏图书和医药公司的有关信息编辑而成,因为在伊朗传统医学中牙周疾病分成不同目类,对有关药物的研究也被分成8个大组63个题目。(1)缓解牙龈肿胀药物(2)治疗牙龈恶化药物(3)治疗口疮腐烂药物(4)治疗牙龈肥大药物(5)利于伤口康复药物(6)利于牙龈加固的药物(7)阻止牙龈出血的药物(8)防止牙齿松动药物。结果结论:伊朗传统医学在准确的观察和实践的基础上来描述和治疗牙周疾病的。在制药学、有效治疗方面、科学研究手段等领域,伊朗传统医学在以下几个方面可作为现代制药研究的重要资源:(1)纯天然资源(2)容易获得(3)相对比较安全。     

An Overview of the Stability and Fretting Corrosion of Microgrooved Necks in the Taper Junction of Hip Implants

Fretting corrosion at the head–neck interface of modular hip implants, scientifically termed trunnionosis/taperosis, may cause regional inflammation, metallosis, and adverse local tissue reactions. The severity of such a deleterious process depends on various design parameters. In this review, the influence of surface topography (in some cases, called microgrooves/ridges) on the overall performance of the microgrooved head–neck junctions is investigated. The methodologies together with the assumptions and simplifications, as well as the findings from both the experimental observations (retrieval and in vitro) and the numerical approaches used in previous studies, are presented and discussed. The performance of the microgrooved junctions is compared to those with a smooth surface finish in two main categories: stability and integrity; wear, corrosion, and material loss. Existing contradictions and disagreements among the reported results are reported and discussed in order to present a comprehensive picture of the microgrooved junctions. The current research needs and possible future research directions on the microgrooved junctions are also identified and presented.     

SARS-CoV-2 Genetic Diversity and Lineage Dynamics in Egypt during the First 18 Months of the Pandemic

COVID-19 was first diagnosed in Egypt on 14 February 2020. By the end of November 2021, over 333,840 cases and 18,832 deaths had been reported. As part of the national genomic surveillance, 1027 SARS-CoV-2 near whole-genomes were generated and published by the end of July 2021. Here we describe the genomic epidemiology of SARS-CoV-2 in Egypt over this period using a subset of 976 high-quality Egyptian genomes analyzed together with a representative set of global sequences within a phylogenetic framework. A single lineage, C.36, introduced early in the pandemic was responsible for most of the cases in Egypt. Furthermore, to remain dominant in the face of mounting immunity from previous infections and vaccinations, this lineage acquired several mutations known to confer an adaptive advantage. These results highlight the value of continuous genomic surveillance in regions where VOCs are not predominant and the need for enforcement of public health measures to prevent expansion of the existing lineages.     

The Effect of Dietary Carbohydrate and Fat Manipulation on the Metabolome and Markers of Glucose and Insulin Metabolism: A Randomised Parallel Trial

High carbohydrate, lower fat (HCLF) diets are recommended to reduce cardiometabolic disease (CMD) but low carbohydrate high fat (LCHF) diets can be just as effective. The effect of LCHF on novel insulin resistance biomarkers and the metabolome has not been fully explored. The aim of this study was to investigate the impact of an ad libitum 8-week LCHF diet compared with a HCLF diet on CMD markers, the metabolome, and insulin resistance markers. n = 16 adults were randomly assigned to either LCHF (n = 8, <50 g CHO p/day) or HCLF diet (n = 8) for 8 weeks. At weeks 0, 4 and 8, participants provided fasted blood samples, measures of body composition, blood pressure and dietary intake. Samples were analysed for markers of cardiometabolic disease and underwent non-targeted metabolomic profiling. Both a LCHF and HCLF diet significantly (p < 0.01) improved fasting insulin, HOMA IR, rQUICKI and leptin/adiponectin ratio (p < 0.05) levels. Metabolomic profiling detected 3489 metabolites with 78 metabolites being differentially regulated, for example, an upregulation in lipid metabolites following the LCHF diet may indicate an increase in lipid transport and oxidation, improving insulin sensitivity. In conclusion, both diets may reduce type 2 diabetes risk albeit, a LCHF diet may enhance insulin sensitivity by increasing lipid oxidation.     

Effect of surfactant concentration on the evaporation-driven deposition of carbon nanotubes: from coffee-ring effect to strain sensing

Carbon nanotubes (CNTs) as electrically conductive materials are of great importance in the fabrication of flexible electronic devices and wearable sensors. In this regard, the evaporation-driven self-assembly of CNTs has attracted increasing attention. CNT-based applications are mostly concerned with the alignment of CNTs and the density of CNT films. In the present work, we focus on the latter by trying to achieve an optimal evaporation-driven deposition with the densest CNT ring. Although surfactants are used for effective dispersion and colloidal stabilization of CNTs in the aqueous phase, their excessive usage induces Marangoni eddies in the evaporating sessile droplets, leading to poor ring depositions. Thus, there is an optimum surfactant concentration that contributes to CNTs deagglomeration and results in the densest ring-like deposition with relatively high thickness. We report that this optimum concentration for sodium dodecyl sulfate (SDS) as a surfactant can be approximately considered as much as the concentration of multi-walled carbon nanotubes (MWCNTs) as the colloidal nanoparticles. Optimal depositions show the lowest electrical resistances for each CNT concentration, making them suitable for electronic applications. We also propose the multiple depositions method in which a new droplet is printed after the complete evaporation of the previous droplet. This method can lead to denser rings with a higher conductivity using lower concentrations of CNTs. Lastly, we fabricate strain sensors based on the optimal evaporation-driven deposition of CNTs which show higher gauge factors than the commercial strain gauges, corroborating the applicability of our method.

Our discovery reveals the existence of an optimum SDS/CNT concentration ratio to achieve the highest conductivity of ring deposition for strain sensing.     

Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements

The rapid spread of the coronavirus disease COVID-19 has imposed clinical and financial burdens on hospitals and governments attempting to provide patients with medical care and implement disease-controlling policies. The transmissibility of the disease was shown to be correlated with the patient’s viral load, which can be measured during testing using the cycle threshold (Ct). Previous models have utilized Ct to forecast the trajectory of the spread, which can provide valuable information to better allocate resources and change policies. However, these models combined other variables specific to medical institutions or came in the form of compartmental models that rely on epidemiological assumptions, all of which could impose prediction uncertainties. In this study, we overcome these limitations using data-driven modeling that utilizes Ct and previous number of cases, two institution-independent variables. We collected three groups of patients (n = 6296, n = 3228, and n = 12,096) from different time periods to train, validate, and independently validate the models. We used three machine learning algorithms and three deep learning algorithms that can model the temporal dynamic behavior of the number of cases. The endpoint was 7-week forward number of cases, and the prediction was evaluated using mean square error (MSE). The sequence-to-sequence model showed the best prediction during validation (MSE = 0.025), while polynomial regression (OLS) and support vector machine regression (SVR) had better performance during independent validation (MSE = 0.1596, and MSE = 0.16754, respectively), which exhibited better generalizability of the latter. The OLS and SVR models were used on a dataset from an external institution and showed promise in predicting COVID-19 incidences across institutions. These models may support clinical and logistic decision-making after prospective validation.     

Impact of IFN‐β1a in treatment of a COVID‐19 patient with beta thalassemia and diabetes mellitus: A case report

Patients with chronic diseases are severely affected by acute coronavirus syndrome. In this regard, patients with beta thalassemia intermedia and diabetes mellitus (DM) are also at high risk for coronavirus‐induced respiratory failure. The present study aimed to report a case with COVID‐19 with a history of chronic diseases, beta thalassemia intermedia, and DM. A 25‐year‐old man visited with complaints of severe shortness of breath, fever, cough without sputum, and tachypnea and admitted to the Intensive Care Unit. The patient had a history of DM, beta thalassemia intermedia, and pervious history of the splenectomy. In peripheral complete blood count (CBC diff), the number of white blood cell count was 41,100 of which 38.6% were lymphocytes. We measured the normal platelet count, hemoglobin level (9.4), and red blood cell count (3.56). ESR was 97, CRP = pos+++ and PCR was positive. The high‐resolution lung CT indicated ground glass opacities in peripheral areas. The patient underwent 13 days of oxygen therapy with reservoir bag‐mask, non‐invasive ventilation, nasal oxygen, and pharmacological treatment with IFN‐β1a and meropenem, and finally discharged with an improvement of the clinical condition. Timely initiation of treatment is very important and significant for patients with beta thalassemia intermedia with COVID‐19, especially despite the underlying disease of DM. According to the present report, the use of IFN‐β1a was effective as a treatment option for COVID‐19.