Background The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to analyze epidemics. Utilizing data mining methods on electronic resources’ data might provide a better insight into the COVID-19 outbreak to manage the health crisis in each country and worldwide. Objective This study aimed to predict the incidence of COVID-19 in Iran. Methods Data were obtained from the Google Trends website. Linear regression and long short-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases. All models were evaluated using 10-fold cross-validation, and root mean square error (RMSE) was used as the performance metric. Results The linear regression model predicted the incidence with an RMSE of 7.562 (SD 6.492). The most effective factors besides previous day incidence included the search frequency of handwashing, hand sanitizer, and antiseptic topics. The RMSE of the LSTM model was 27.187 (SD 20.705). Conclusions Data mining algorithms can be employed to predict trends of outbreaks. This prediction might support policymakers and health care managers to plan and allocate health care resources accordingly.

Metal-organic frameworks (MOFs) are a fascinating class of crystalline porous materials composed of metal ions and organic ligands. Due to their attractive properties, MOFs can potentially offer biomedical field applications, such as drug delivery and imaging. This study aimed to systematically identify the affecting factors on the MOF characteristics and their effects on structural and biological characteristics. An electronic search was performed in four databases containing PubMed, Scopus, Web of Science, and Embase, using the relevant keywords. After analyzing the studies, 20 eligible studies were included in this review. As a result, various factors such as additives and organic ligand can influence the size and structure of MOFs. Additives are materials that can compete with ligand and may affect the nucleation and growth processes and, consequently, particle size. The nature and structure of ligand are influential in determining the size and structure of MOF. Moreover, synthesis parameters like the reaction time and initial reagents ratio are critical factors that should be optimized to regulate the size and structure. Of note is that the nature of the ligand and using a suitable additive can control the porosity of MOF. The more extended ligands aid in forming large pores. The choice of metallic nodes and organic ligand, and the MOF concentration are important factors since they can determine toxicity and biocompatibility of the final structure. The physicochemical properties of MOFs, such as hydrophobicity, affect the toxicity of nanoparticles. An increase in hydrophobicity causes increased toxicity of MOF. The biodegradability of MOF, as another property, depends on the organic ligand and metal ion and environmental conditions like pH. Photocleavable ligands can be served for controlled degradation of MOFs. Generally, by optimizing these affecting factors, MOFs with desirable properties will be obtained for biomedical applications.

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The medial olivocochlear reflex (MOCR) modulates cochlear amplifier gain and is thought to facilitate the detection of signals in noise. High-resolution distortion product otoacoustic emissions (DPOAEs) were recorded in teens, young, middle-aged, and elderly adults at moderate levels using primary tones swept from 0.5 to 4 kHz with and without a contralateral acoustic stimulus (CAS) to elicit medial efferent activation. Aging effects on magnitude and phase of the 2f1-f2 DPOAE and on its components were examined, as was the link between speech-in-noise performance and MOCR strength. Results revealed a mild aging effect on the MOCR through middle age for frequencies below 1.5 kHz. Additionally, positive correlations were observed between strength of the MOCR and performance on select measures of speech perception parsed into features. The elderly group showed unexpected results including relatively large effects of CAS on DPOAE, and CAS-induced increases in DPOAE fine structure as well as increases in the amplitude and phase accumulation of DPOAE reflection components. Contamination of MOCR estimates by middle ear muscle contractions cannot be ruled out in the oldest subjects. The findings reiterate that DPOAE components should be unmixed when measuring medial efferent effects to better consider and understand these potential confounds.

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