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Introduction: Infective endocarditis (IE) is a serious problem with high morbidity and mortality. However, there is a paucity of data regarding its epidemiology in non-high-income settings. Here, we described the characteristics of patients with IE., Methodology: Between March 2012 to March 2020, all adults (≥ 16 years) with a diagnosis of IE who were admitted to a university hospital in Mashhad, Iran, were included in the study., Results: We evaluated 46 cases of IE with a median age of 42 years (interquartile range 31 to 58.3 years), of whom 21 (46%) had a definite diagnosis. The presence of a prosthetic valve or intracardiac device was the leading predisposing factor (N = 14, 30%). The etiology of IE in 22 subjects (48%) remained unknown. Staphylococcus aureus (N = 12, 26%) was the most common causative pathogen. Echocardiography revealed the mitral valve as the most affected valve (N = 18, 39%). Intravenous drug users (IVDU) had a higher chance of right-sided IE, as compared to no IVDU patients (odds ratio: 35, 95% CI: 3.7 to 425.0). The most prevalent complications were lung infarction, acute heart failure, and neurologic involvement (N = 5, 11% for each), and 15 patients (33%) died because of IE., Conclusions: In our study, the median age of IE onset was relatively low. The most frequent predisposing factor was a prosthetic valve or intracardiac device. The proportion of negative blood cultures was unacceptably high. Thus, our findings emphasize promoting laboratory infrastructure, developing a national protocol for early initiation of appropriate treatment, and eliminating predisposing factors., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2023 Ali Shahini, Matin Shirazinia, Raha Jafari, Ali Akbar Heydari.)

Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution, however, enhances our understanding of complex biological systems and diseases, such as cancer, the immune system, and chronic diseases. However, the single-cell technologies generate massive amounts of data that are often high-dimensional, sparse, and complex, thus making analysis with traditional computational approaches difficult and unfeasible. To tackle these challenges, many are turning to deep learning (DL) methods as potential alternatives to the conventional machine learning (ML) algorithms for single-cell studies. DL is a branch of ML capable of extracting high-level features from raw inputs in multiple stages. Compared to traditional ML, DL models have provided significant improvements across many domains and applications. In this work, we examine DL applications in genomics, transcriptomics, spatial transcriptomics, and multi-omics integration, and address whether DL techniques will prove to be advantageous or if the single-cell omics domain poses unique challenges. Through a systematic literature review, we have found that DL has not yet revolutionized the most pressing challenges of the single-cell omics field. However, using DL models for single-cell omics has shown promising results (in many cases outperforming the previous state-of-the-art models) in data preprocessing and downstream analysis. Although developments of DL algorithms for single-cell omics have generally been gradual, recent advances reveal that DL can offer valuable resources in fast-tracking and advancing research in single-cell., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single-cell resolution while maintaining cellular compositions within a tissue. Having both expression profiles and tissue organization enables researchers to better understand cellular interactions and heterogeneity, providing insight into complex biological processes that would not be possible with traditional sequencing technologies. Data generated by ST technologies are inherently noisy, high-dimensional, sparse, and multi-modal (including histological images, count matrices, etc.), thus requiring specialized computational tools for accurate and robust analysis. However, many ST studies currently utilize traditional scRNAseq tools, which are inadequate for analyzing complex ST datasets. On the other hand, many of the existing ST-specific methods are built upon traditional statistical or machine learning frameworks, which have shown to be sub-optimal in many applications due to the scale, multi-modality, and limitations of spatially resolved data (such as spatial resolution, sensitivity, and gene coverage). Given these intricacies, researchers have developed deep learning (DL)-based models to alleviate ST-specific challenges. These methods include new state-of-the-art models in alignment, spatial reconstruction, and spatial clustering, among others. However, DL models for ST analysis are nascent and remain largely underexplored. In this review, we provide an overview of existing state-of-the-art tools for analyzing spatially resolved transcriptomics while delving deeper into the DL-based approaches. We discuss the new frontiers and the open questions in this field and highlight domains in which we anticipate transformational DL applications., Competing Interests: The authors have no conflicts to disclose., (© 2023 Author(s).)

Motivation: Single-cell RNA sequencing (scRNAseq) technologies allow for measurements of gene expression at a single-cell resolution. This provides researchers with a tremendous advantage for detecting heterogeneity, delineating cellular maps or identifying rare subpopulations. However, a critical complication remains: the low number of single-cell observations due to limitations by rarity of subpopulation, tissue degradation or cost. This absence of sufficient data may cause inaccuracy or irreproducibility of downstream analysis. In this work, we present Automated Cell-Type-informed Introspective Variational Autoencoder (ACTIVA): a novel framework for generating realistic synthetic data using a single-stream adversarial variational autoencoder conditioned with cell-type information. Within a single framework, ACTIVA can enlarge existing datasets and generate specific subpopulations on demand, as opposed to two separate models [such as single-cell GAN (scGAN) and conditional scGAN (cscGAN)]. Data generation and augmentation with ACTIVA can enhance scRNAseq pipelines and analysis, such as benchmarking new algorithms, studying the accuracy of classifiers and detecting marker genes. ACTIVA will facilitate analysis of smaller datasets, potentially reducing the number of patients and animals necessary in initial studies., Results: We train and evaluate models on multiple public scRNAseq datasets. In comparison to GAN-based models (scGAN and cscGAN), we demonstrate that ACTIVA generates cells that are more realistic and harder for classifiers to identify as synthetic which also have better pair-wise correlation between genes. Data augmentation with ACTIVA significantly improves classification of rare subtypes (more than 45% improvement compared with not augmenting and 4% better than cscGAN) all while reducing run-time by an order of magnitude in comparison to both models., Availability and Implementation: The codes and datasets are hosted on Zenodo (https://doi.org/10.5281/zenodo.5879639). Tutorials are available at https://github.com/SindiLab/ACTIVA., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: SYNTAX score is one of the risk assessment systems to predict cardiac events in acute coronary syndrome patients. Despite the large number of SYNTAX score benefits, invasive methods such as coronary angiography are necessary to perform the scoring. We hypothesized that ECG parameters could predict the SYNTAX score in unstable angina patients., Methods: During the retrospective cohort study, a total number of 876 patients were diagnosed with unstable angina. After applying the exclusion criteria, 600 patients were divided into tertiles based on the SYNTAX scores as low (0-22), intermediate (23-32), and high (≥ 33). The association between ECG parameters and SYNTAX score was investigated., Results: The study included 65% men and 35% women with a mean age of 62.4 ± 9.97 years. The delayed transition zone of QRS complex, ST-depression in inferior-lateral territories or/and in all three territories, and T-wave inversion in lateral territory were significant (p < 0.05) independent predictors of intermediate SYNTAX score. High SYNTAX score was predicted by the presence of prolonged P wave duration, ST-depression in lateral territory or/and anterior-lateral territories, ST-elevation in aVR-III leads or/and aVR-III-V1 leads. Among those, all three territories ST-depression (AUC: 0.611, sensitivity: 75%, specificity: 51%) and aVR + III ST-elevation (AUC: 0.672, sensitivity: 50.12%, specificity: 80.50%) were the most accurate parameters to predict intermediate and high SYNTAX scores, respectively., Conclusion: The present study demonstrates that accompanying the STE in the right side leads (aVR, III, V1) with ST-depression in other leads indicates the patients with high SYNTAX score; meanwhile, diffuse ST-depression without ST-elevation is a marker for intermediate SYNTAX score in unstable angina patients and can be applied for early risk stratification and intervention., (© 2022. The Author(s).)

Background: Atelectasis and hypoxemia are frequently reported after coronary artery bypass graft surgery (CABG). Some studies confirm the benefits of breathing exercises on pulmonary complications, but the efficacy of preoperative breathing exercises in patients undergoing CABG is controversial. In this study, the effect of preoperative breathing exercises on the incidence of atelectasis and hypoxemia in patients candidate for CABG was examined., Methods: In a single-blinded randomized clinical trial, 100 patients who were undergoing coronary artery bypass graft surgery were randomly allocated into two groups of experimental and control, each consisted of 50 patients. Before the operation, experimental group patients were enrolled in a protocol including deep breathing, cough and incentive spirometer. In the control group, hospital routine physiotherapy was implemented. All the patients received the hospital routine physiotherapy once a day for 2 to 3 minutes in the first four days postoperatively. Arterial blood gases and atelectasis were compared between groups., Results: There was no significant difference between groups in terms of atelectasis and hypoxemia (p Value>0.05)., Conclusion: Preoperative breathing exercise does not reduce pulmonary complications in patients undergoing CABG., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Culture and specific staining (including Zeil-Nelson and fluorescent methods) are standard measures for the diagnosis of tuberculosis (TB). These methods are time-consuming and sometimes have a low level of accuracy. In addition, in some cases obtaining samples for smear and culture involves invasive procedures; while in other cases there is no suitable sample for evaluation. Therefore, there is a need for faster and more accurate diagnostic methods., Objectives: The current study investigated the diagnostic value of tuberculosis-polymerase chain reaction (TB-PCR) of urine in the diagnosis of pulmonary tuberculosis (PTB)., Patients and Methods: This case-control study included; 77 proven pulmonary tuberculosis cases (according to the national TB protocol), and 30 subjects who were completely healthy. The urine samples (50 mL) were mixed with 0.5 mL Ethylene diamine tetraacetic acid. DNA extraction and PCR testing were performed on all blood samples using SI 6110 primers. Mycobacterium tuberculosis was also cultivated in the sputum and urine samples of the patients., Results: Results of the current study indicated that 48 (62.3%) patients out of 77 had a positive sputum culture. Urine cultures and acid-fast smears were negative. Urine PCR-TB was positive in 48.0% (37/77) of the patients. The specific TBPCR complex was positive in 56.2% (27/48) of the positive cultures and 34.4% (10/29) of the negative culture PTB patients. The control group had negative urine PCR (sensitivity 56.2% and specificity 100%)., Conclusions: With regard to the ease of urine sample preparation and the 100% specificity the PCR method, performing urine PCR could be used as a diagnostic aid in PTB cases obtaining sputum samples is problematic.

Hepatitis B virus (HBV) infection is a worldwide public health problem. In this paper, we study the dynamics of hepatitis B virus (HBV) infection which can be controlled by vaccination as well as treatment. Initially we consider constant controls for both vaccination and treatment. In the constant controls case, by determining the basic reproduction number, we study the existence and stability of the disease-free and endemic steady-state solutions of the model. Next, we take the controls as time and formulate the appropriate optimal control problem and obtain the optimal control strategy to minimize both the number of infectious humans and the associated costs. Finally at the end numerical simulation results show that optimal combination of vaccination and treatment is the most effective way to control hepatitis B virus infection.

Presently, clinicians often forget important aspects of fever patterns. This study presents the case of disseminated tuberculosis in a 64-year-old man whose chief complaint was morning fever. He was a kidney transplant patient and presented with productive cough, reverse fever pattern and a nodular pattern in chest radiograph. Clinicians should suspect disseminated tuberculosis in patients who present with reverse fever pattern, especially with compatible radiographic findings., (Copyright © 2012 Asian-African Society for Mycobacteriology. Published by Elsevier Ltd. All rights reserved.)

From January to February 2008, 468 sheep carcasses (335 male and 133 female) in a Khosroshahr (suburb of Tabriz, East Azerbaijan province, Iran) abattoir were randomly selected for inspection. The aim of the study was to estimate the frequency of caseous lymphadenitis (CLA) in sheep and to compare the results of bacterial cultures and histopathology of suspected cases. The mean age of the population was 2.5 years. One hundred ninety-seven cases containing 153 (77.7%) males and 44 (22.3%) females had prominent enlargement of one of the lymph nodes (i.e., prescapular, prefemoral, inguinal, supramammary, or midiastinal); these were removed with the surrounding tissue for further evaluation. For confirmed diagnosis of CLA, samples were sent for microbiology and pathology analysis. Standard bacteriological culture methods for isolation of Corynebacterium pseudotuberculosis and tissue preparations for histopathological sections were performed. To evaluate the effect of age on the frequency of CLA, animals were categorized in four groups: under 1, 1-2, 2-3, and over 3 years of age. Based on the results, in 59 (12.60%) carcasses C. pseudotuberculosis was isolated, and in 94 (20.08%) of the cases histopathological studies revealed pathognomonic signs (lamellated exudates or onion ring) of CLA. The frequency of CLA based on bacteriological culture was 12.60% and on histopathological study 20.08%. In 37 (18.8%) of the carcasses, both bacteriological and histopathological studies confirmed CLA. The frequency of CLA following microscopic examination (20.08%) presented a more precise diagnosis compared to bacteriological culture (12.60%) and macroscopic evaluation of the lymph nodes (P < 0.05). Furthermore, there was a positive correlation rate between the bacteriological culture and histopathological study (r = 0.196, P = 0.006). The prescapular lymph node had the highest infection rate with 54 (1.70 ± 0.97) and supramammary lymph node had the lowest with two (0.07 ± 0.41) (P < 0.05). There was an increase in CLA detection with increasing age (P < 0.05), the mean age of animals with a positive CLA test were 2.92 years and in the oldest age group 31 (47%) cases had the highest infection.

The present study proposes a fuzzy mathematical model of HIV infection consisting of a linear fuzzy differential equations (FDEs) system describing the ambiguous immune cells level and the viral load which are due to the intrinsic fuzziness of the immune system's strength in HIV-infected patients. The immune cells in question are considered CD4+ T-cells and cytotoxic T-lymphocytes (CTLs). The dynamic behavior of the immune cells level and the viral load within the three groups of patients with weak, moderate, and strong immune systems are analyzed and compared. Moreover, the approximate explicit solutions of the proposed model are derived using a fitting-based method. In particular, a fuzzy control function indicating the drug dosage is incorporated into the proposed model and a fuzzy optimal control problem (FOCP) minimizing both the viral load and the drug costs is constructed. An optimality condition is achieved as a fuzzy boundary value problem (FBVP). In addition, the optimal fuzzy control function is completely characterized and a numerical solution for the optimality system is computed.

We present two non-HIV-infected patients with isolated native non-rheumatic tricuspid valve endocarditis who were not intravenous drug abusers. The patients presented with fever and chills. Plain radiography or high-resolution computed tomography of the chest revealed consolidation or infiltrate of the left parenchyma in both patients. Large vegetation located on the tricuspid leaflets was detected by transesophageal echocardiography. Staphylococcus aureus grew in two out of three blood cultures for one patient. Tricuspid valve endocarditis imitates illnesses with fever and pulmonary symptoms or signs of acute or chronic onset, and might be present even without abnormal chest X-rays or intravenous drug addiction.