Cryptoccoccal meningitis in post-covid 19 patient in the city of manaus: Case report

Cryptococcosis is a cosmopolitan and opportunistic mycosis, caused mainly by the etiological agent Cryptococcus neoformans, through the inhalation of fungal structures, especially in bird feces. The aim of this study was to report a reported case of cryptococcal meningitis in an immunosuppressed patient due to previous COVID-19 infection in the city of Manaus-AM, as well as to implement health education actions to prevent cryptococcosis in the region of the disease. Information about the case was obtained through access to the database of the Information System for Notifiable Diseases (SINAN), made available by the Center for Control of Zoonoses Dr. Carlos Durand (CCZ), an agency belonging to the Municipal Health Department of Manaus (SEMSA). The case patient, male, presented symptoms such as headache, fever, vomiting, seizures, neck stiffness, petechiae and hemorrhagic suffusions, hearing loss and signs of Kernig and Brudzinski. In a zoosanitary visit to the site of the injury, the presence of pigeon excreta on the walls of the residence was found, and cleaning was carried out without the use of personal protective equipment (PPE’s). The contact with the residents evidenced the lack of information about the zoonosis addressed, including the risk of transmission of cryptococcosis by pigeons, facts that make necessary more sanitary actions on zoonoses among the population of Manaus.

Integrating Insights About Human Movement Patterns From Digital Data Into Psychological Science

Understanding people’s movement patterns has many important applications, from analyzing habits and social behaviors, to predicting the spread of disease. Information regarding these movements and their locations is now deeply embedded in digital data generated via smartphones, wearable sensors, and social-media interactions. Research has largely used data-driven modeling to detect patterns in people’s movements, but such approaches are often devoid of psychological theory and fail to capitalize on what movement data can convey about associated thoughts, feelings, attitudes, and behavior. This article outlines trends in current research in this area and discusses how psychologists can better address theoretical and methodological challenges in future work while capitalizing on the opportunities that digital movement data present. We argue that combining approaches from psychology and data science will improve researchers’ and policy makers’ abilities to make predictions about individuals’ or groups’ movement patterns. At the same time, an interdisciplinary research agenda will provide greater capacity to advance psychological theory.

Designing and Evaluating an Educational Website for Osteoarthritis

Aim: Using educational websites can be effective in enhancing the health-related knowledge of patients suffering from osteoarthritis. This study aimed to design and evaluate an educational website to improve the awareness of patients with osteoarthritis. Method: This is a descriptive-applied study. Having reviewed valid scientific articles retrieved from Medline (through PubMed), Scopus, and Google Scholar databases, the contents required for the website were identified and classified. Then, the scientific content extracted from the articles was evaluated by general physicians and Ph.D. of physical medicine and rehabilitation. Different sections of the website were designed by "Google sites," and the content was published. In the last stage of the research, the osteoarthritis educational website was evaluated by students of medicine and health information technology in terms of technical performance by a standard questionnaire. Results: In this study, an educational website was designed to educate patients with osteoarthritis. Users can log in to the website and learn about symptoms, consequences, predisposing factors, pain relief exercises, nutritional information, and self-care programs. The content provided on the website includes three main sections of general disease information, clinical information, and disease self-care information, which physicians evaluated in the first phase. According to the content evaluation results extracted from the studies and the questionnaire's analysis, the designed website had a good quality. The average scores of the questions related to website usability, screen capabilities, terminology and information, learning ability, and overall website capability were 7.79, 8.15, 8.4, 8.08, and 8.03, respectively, which were at a "good" level. Conclusion: At the end of this research, an educational website for osteoarthritis was created. Patients can access the site via the link and receive educational information about symptoms, consequences, predisposing factors, exercises to reduce pain, self-care, and nutritional information.

Post-covid syndrome in children

Multisystem inflammatory syndrome in children associated with COVID-19 is a new disease, information first appeared in April 2020. There were reported cases of hospitalized children with unusual symptoms, manifested primarily by fever and multisystem inflammation from the pediatricians in the UK and other countries during the coronavirus infection pandemic (COVID-19). Some of these children were in critical condition with symptoms of shock and multiple organ failure, and some children had manifestations similar to Kawasaki disease. Despite the fact that COVID-19 in children is relatively easy, some of the «convalescents» after 2–6 weeks develop symptoms largely identical to the manifestations of severe forms of new coronavirus infection in adults. The report presents own clinical cases of multisystem inflammatory syndrome that developed in children after acute form of a new coronavirus infection. The authors discuss the possible clinical variants of the syndrome, its origin and outcomes.

Pre-cancer and cancer-associated depression and anxiety among older adults with blood cancers in the United States

For patients with blood cancers, comorbid mental health disorders at diagnosis likely affect the entire disease trajectory, as they can interfere with disease information processing, lead to poor coping, and even cause delays in care. We aimed to characterize the prevalence of depression and anxiety in patients with blood cancers. Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified patients 67 years and older diagnosed with lymphoma, myeloma, leukemia, or myelodysplastic syndromes between 2000 and 2015. We determined the prevalence of pre-cancer and cancer-associated (CA) depression and anxiety using claims data. We identified factors associated with CA-depression and CA-anxiety in multivariate analyses. Among 75,691 patients, 18.6% had at least one diagnosis of depression or anxiety. Of the total cohort, 13.7% had pre-cancer depression and/or pre-cancer anxiety, while 4.9% had CA-depression or CA-anxiety. Compared to patients without pre-cancer anxiety, those with pre-cancer anxiety were more likely to have subsequent claims for CA-depression (OR 2.98; 95% CI 2.61-3.41). Other factors associated with higher risk of CA-depression included female sex, non-married status, higher comorbidity, and myeloma diagnosis. Patients with pre-cancer depression were significantly more likely to have subsequent claims for CA-anxiety compared to patients without pre-cancer depression (OR 3.01; 95% CI 2.63-3.44). Female sex and myeloma diagnosis were also associated with CA-anxiety. In this large cohort of older patients with newly diagnosed blood cancers, almost one in five suffered from depression or anxiety, highlighting a critical need for systematic mental health screening and management for this population.

Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization

Among an assortment of genetic variations, Missense are major ones which a small subset of them may led to the upset of the protein function and ultimately end in human diseases. Various machine learning methods were declared to differentiate deleterious and benign missense variants by means of a large number of features, including structure, sequence, interaction networks, gene disease associations as well as phenotypes. However, development of a reliable and accurate algorithm for merging heterogeneous information is highly needed as it could be captured all information of complex interactions on network that genes participate in. In this study we proposed a new method based on the non-negative matrix tri-factorization clustering method. We outlined two versions of the proposed method: two-source and three-source algorithms. Two-source algorithm aggregates individual deleteriousness prediction methods and PPI network, and three-source algorithm incorporates gene disease associations into the other sources already mentioned. Four benchmark datasets were employed for internally and externally validation of both algorithms of our predictor. The results at all datasets confirmed that, our method outperforms most state of the art variant prediction tools. Two key features of our variant effect prediction method are worth mentioning. Firstly, despite the fact that the incorporation of gene disease information at three-source algorithm can improve prediction performance by comparison with two-source algorithm, our method did not hinder by type 2 circularity error unlike some recent ensemble-based prediction methods. Type 2 circularity error occurs when the predictor annotates variants on the basis of the genes located on. Secondly, the performance of our predictor is superior over other ensemble-based methods for variants positioned on genes in which we do not have enough information about their pathogenicity.

Use of Mycophenolate Mofetil for Systemic Sclerosis and Systemic Sclerosis-Associated Interstitial Lung Disease: Information from a Japanese Hospital Claims Database

Objectives Limited information is available on patients with systemic sclerosis (SSc) or SSc-associated interstitial lung disease (SSc-ILD) receiving mycophenolate mofetil (MMF) in Japan. The dose, treatment duration, and patient characteristics of SSc and SSc-ILD patients receiving MMF were investigated. Method We used data from a Japanese hospital claims database (2008–2020). Results Data on 486 SSc patients ≥18 years old receiving MMF were captured; 314 had SSc complicated with ILD. The most common initial daily doses were 1000 mg (SSc, 39.5%; SSc-ILD, 38.1%) and 500 mg (SSc, 36.6%; SSc-ILD, 34.6%). The most common maximum daily doses were 1000 mg (SSc, 33.3%; SSc-ILD, 34.9%), 1500 mg (SSc, 24.4%; SSc-ILD, 23.1%), and 2000 mg (SSc, 23.8%; SSc-ILD, 24.4%). Doses ranged from 250 to 3000 mg/day and were similar for SSc and SSc-ILD patients. Over 27% of patients received treatment for >1 year. There was a gradual decrease in steroid doses during MMF treatment. Conclusions Our study suggests that the off-label use of MMF for SSc and SSc-ILD has been increasing annually since 2015 in Japan. The doses used in patients with SSc and SSc-ILD were similar to the approved doses of MMF for lupus nephritis in Japan.

Tambar Ni Hulit: An ancient medical manuscript in North Sumatera

Tambar ni hulit, which means skin medicine in Simalungun language, is the title of an old manuscript belonging to the Simalungun tribe. This manuscript is written on laklak material containing medicine information for various diseases. Moreover, this manuscript is relatively rare and written in characters and language that are no longer commonly used. The purpose of this study is to inventory, describe, transliterate, and translate the interpretation of the Tambar Ni Hulit contents. Tambar Ni Hulit is one of the results in searching for old manuscripts in various places in North Sumatra, like museums, libraries, and private collections. The inventory, description, transliteration, and translation were carried out by applying the philological method and content analysis was done to review the content. The result of the inventory described the information of the storage location of Tambar Ni Hulit, namely the North Sumatra Museum. The description analysis described the physical state of the manuscript. From the transliteration and translation results, it is concluded that the Tambar Ni Hulit contains various disease information accompanied by the ingredients of their respective medicine and treatment methods with incantations during the treatment.

An outbreak of SARS-CoV-2 with high mortality in mink (Neovison vison) on multiple Utah farms

The breadth of animal hosts that are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and may serve as reservoirs for continued viral transmission are not known entirely. In August 2020, an outbreak of SARS-CoV-2 occurred on five mink farms in Utah and was associated with high mink mortality (35–55% of adult mink) and rapid viral transmission between animals. The premise and clinical disease information, pathology, molecular characterization, and tissue distribution of virus within infected mink during the early phase of the outbreak are provided. Infection spread rapidly between independently housed animals and farms, and caused severe respiratory disease and death. Disease indicators were most notably sudden death, anorexia, and increased respiratory effort. Gross pathology examination revealed severe pulmonary congestion and edema. Microscopically there was pulmonary edema with moderate vasculitis, perivasculitis, and fibrinous interstitial pneumonia. Reverse transcriptase polymerase chain reaction (RT-PCR) of tissues collected at necropsy demonstrated the presence of SARS-CoV-2 viral RNA in multiple organs including nasal turbinates, lung, tracheobronchial lymph node, epithelial surfaces, and others. Localization of viral RNA by in situ hybridization revealed a more localized infection, particularly of the upper respiratory tract. Whole genome sequencing from multiple mink was consistent with published SARS-CoV-2 genomes with few polymorphisms. The Utah mink SARS-CoV-2 strains fell into Clade GH, which is unique among mink and other animal strains sequenced to date. While sharing the N501T mutation which is common in mink, the Utah strains did not share other spike RBD mutations Y453F and F486L found in nearly all mink from the United States. Mink in the outbreak reported herein had high levels of SARS-CoV-2 in the upper respiratory tract associated with symptomatic respiratory disease and death.

Word-Formation Process on COVID-19 Related Terms as Japanese Language Variation

This research aims to identify the types of vocabulary in Japanese, to explore the word-formation process, and to analyse the function of COVID-19 related terms conveyed by various content creators on YouTube channels, from Japan and Indonesia. The seven YouTube channel accounts are Aki no Sora (Indonesia), po.n.go_id or Pocket Nihongo (Indonesia), Sakura Pinku (Indonesia), Wagomu (Indonesia), Omoshiroi Nihongo (Japan), Japanese Ammo with Misa (Japan), and Coto Academy (Japan that used as the data source. Data were collected using the observation method and analysed by the distribution method. The results showed that the COVID-19 related terms are dominated by the type of vocabulary kango as the form or type of vocabulary that is most widely used in matching the COVID-19 related term. Among all word-formation processes, the COVID-19 terms in Japanese identified as borrowing, compounding, and multiple processes. However, the multiple word-formation processes are dominated on COVID-19 terms in Japanese. It related to the domination of the type of kango used. From that, there are multiple functions that are included in COVID-19 terms in Japanese, namely disease information, preventive action, symptom, and announcement. Therefore, this research can be contributed to data analysis, which used morphological analysis in Japanese terms.