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Z Malezijo sta imeli s Tino neporavnane račune, saj je obisk leta 2020 preprečil nanometrski velikan znan pod imenom SARS-CoV-2. Letos spomladi pa je končno poletela v Kuala Lumpur, kjer se je tritedenska avantura začela. Po zaužitju nekaj čarov ikonske arhitekture jo je mahnila v višavje s precej bolj prijetno klimo in neskončnimi plantažami čaja, med katerimi kraljujejo rastlinjaki z jagodami in drugimi kulturami, ki jim tropska vlaga in vročina ne ustrezata. Pot nadaljuje proti severovzhodu dežele na rajske otoke Perhentian. Načrtovala je sicer oddih, a so jo lepote koralnih grebenov, pisane ribice, morske želve, skati in celo (vegetarijanski) morski psi vedno znova vabili v svoj objem pod vodo. Večino časa tako preživi s potapljaško masko na glavi. Vrne se na celino in poleti v svetovljanski Georgetown, kjer se znajde v »mali Kitajski« in se zabava ob iskanju uličnih grafitov. A vročina in vlaga sta tukaj še bolj ubijalski kot v prestolnici, zato se umakne na Penang Hill, kjer nekoliko lažje zadiha. Sledi let v Kuching in raziskovanje Bornea, kjer jo navduši na novo odprt Muzej bornejskih kultur, še bolj pa stik z naravo. Obišče divje orangutane in nacionalni park Bako, ker se sreča z makaki, opicami rilčarji, srebrnolistnimi opicami, bornejskimi divjimi prašiči, pa tudi s strupeno zeleno suličarko. Po siloviti tropski nevihti komaj posuši obleke in gojzarje, ko je že čas za vrnitev na celino, ogled zgodovinskega mesta Melaka, zadnje nakupe in let proti Evropi...

Dataset name: regularn_dataset_metropolitana.xls and regularn_dataset_oeste.xls Version:1.0 Data collection period: 04/30/2020 - 08/02/2022 Dataset Characteristics: Multivalued Number of Instances: 25,366 Number of Attributes: 20 Missing Values: Yes Area(s):Health Sources: RegulaRN (https://regulacao.saude.rn.gov.br/sala-situacao/sala_publica/). Descriptions: The regularn_dataset_metropolitana.xls and regularn_dataset_oeste.xls dataset is part of a range of data from the RegulaRN platform. This was the platform used by the Brazilian state of Rio Grande do Norte, consisting of data involving the hospitalization process of patients with covid-19 and the respective regulation of beds for hospitalization of this patient. In addition to understanding all these aspects, the database also contains the patient's discharge or death information. Table 1: Description of Dataset Features. Database description: Collected data on the RegulaRN platform. Field Data type Description data_solicitacao object Represents the date a bed request was registered. municipio_paciente object Represents the patient's municipality. uf_paciente object Represents the patient's federal unit. gestante object 1 if the patient is pregnant; 0 if the patient is not pregnant. idade_gestacional float64 Describe how far along the pregnancy is, measured in weeks. idade float64 Represents patient age. tipo_caso object Represents whether the patient was "suspected", "confirmed" or "discarded" for covid-19. eup float64 Represents the EUP score value. com_iot object Represents whether or not the patient was in orotracheal intubation when requesting a bed. tp_leito_solicitado object Represents the type of bed that was selected by the regulation center for a patient. dt_entrada object Represents the date that the patient was allocated in the health unit (hospital). tp_leito_entrada object Represents the type of bed that the patient was allocated in the health unit (hospital). dt_saida object Represents the date that patient left the bed after the outcome. tp_leito_saida object Represents the type of bed the patient was in before the outcome. ti float64 Hospital length of stay, measured in days. desfecho object Represents the final outcome of the patient in bed solicitante object Represents the unit health that solicit a bed to the patient municipio_solicitante object Represents the municipality of the health unit that solicit the bed prestador object Represents the unit health that receive and internal the patient in the bed municipio_prestador object Represents the municipality of the health unit that receive and internal the patient in the bed

Data set for the article "Break-even point and its impact on profit planning in educational institutions. A study conducted in Lima, Peru, 2022" Abstract: The break-even point is a technique for analyzing the relationship between costs, volumes and profits in organizations, which allows their managers to know quickly and economically the minimum units or amounts that their companies must sell in order not to generate losses, thus allowing them to plan their profits. Due to the pandemic caused by the Sars-Cov-2 (COVID-19 virus), virtual teaching became popular, which served as an opportunity for many teachers to start teaching courses; with time, these entrepreneurs paid attention to the importance of the break-even point for making decisions related to the opening of new sections of existing courses, or the implementation of new study programs. The objective of this study was to determine the impact of the break-even point in profit planning in educational institutions in Lima, 2022. The hypothesis was: the break-even point has an impact on profit planning in educational institutions in Lima, 2022. Through a quantitative approach study, applied type, explanatory level, non-experimental and cross-sectional design, data was collected from 91 entrepreneurs who carried out teaching activities on virtual platforms. The results obtained confirmed the influence of the break-even point calculation on profit planning in this context, modeling it with the following formula: profit planning=0.101+0.979 x break-even point

In the post-pandemic COVID-19 period, human activities have returned to normal and COVID-19 cases are usually mild. However, patients with multiple myeloma (MM) present an increased risk for breakthrough infections and severe COVID-19 outcomes, including hospitalization and death. The European Myeloma Network has provided an expert consensus to guide patient management in this era. Vaccination with variant-specific booster vaccines, such as the bivalent vaccine for the ancestral Wuhan strain and the Omicron BA.4/5 strains, is essential as novel strains emerge and become dominant in the community. Boosters should be administered every 6–12 months after the last vaccine shot or documented COVID-19 infection (hybrid immunity). Booster shots seem to overcome the negative effect of anti-CD38 monoclonal antibodies on humoral responses; however, anti-BCMA treatment remains an adverse predictive factor for humoral immune response. Evaluation of the immune response after vaccination may identify a particularly vulnerable subset of patients who may need additional boosters, prophylactic therapies and prevention measures. Pre-exposure prophylaxis with tixagevimab/cilgavimab is not effective against the new dominant variants and thus is no longer recommended. Oral antivirals (nirmatrelvir/ritonavir and molnupiravir) and remdesivir are effective against Omicron subvariants BA.2.12.1, BA.4, BA.5, BQ.1.1 and/or XBB.1.5 and should be administered in MM patients at the time of a positive COVID-19 test or within 5 days post symptoms onset. Convalescent plasma seems to have low value in the post-pandemic era. Prevention measures during SARS-CoV-2 outbreaks, including mask wearing and avoiding crowded places, seem prudent to continue for MM patients.

Supplemental materials for manuscript entitled: Drinking to Cope Mediates the Association Between Dyadic Conflict and Drinking Behavior: A Study of Romantic Couples During the COVID-19 Pandemic

Data Dictionary Column Description Type Main ID A unique and primary identification assigned to each individual. Integer Study ID A specific research identification assigned to each patient. String Gender The biological sex of the patient, which can be male or female (M or F). String Severity A measure of the severity of the illness. 1- not infected 2- hospitalized 3- hospitalized ICU Integer Age The age of the patient, usually in completed years. Integer Age_group A category in which the patient's age is grouped, age ranges like 25-34 years or 45-54 years, etc. String Length_of_hospital_stay The amount of time the participant spent hospitalized in days. Integer Hospitalization_and_outcome Information about the participant's hospitalization and the outcome of the hospitalization. Integer Outcome The outcome of the patient, whether there was death or not. String Before_d1 Information about the patient's condition before the first dose of the vaccine. Float Severity_before The measure of the severity of the participant's condition before the first dose of the vaccine. Float t_hospitalized_before The amount of time the participant spent hospitalized before the first dose of the vaccine. Float time_hospitalization_before The total amount of time the participant spent hospitalized in intensive care unit (ICU) before the first dose of the vaccine. Float Between_d1_d2 Information about the patient's condition between dose 1 and dose 2 of the vaccine. Float Severity_between The measure of the severity of the patient's condition between dose 1 and dose 2 of the vaccine. Float t_hospitalized_between The amount of time the patient spent hospitalized between dose 1 and dose 2 of the vaccine. Float time_hospitalization_between The total amount of time the patient spent hospitalized in intensive care unit (ICU) between dose 1 and dose 2 of the vaccine. Float After_d2 Information about the patient's condition after dose 2 of the vaccine. Float Severity_after The measure of the severity of the patient's condition after dose 2 of the vaccine. Float t_hospitalized_after The amount of time the patient spent hospitalized after dose 2 of the vaccine. Float time_hospitalization_after The total amount of time the patient spent hospitalized in intensive care unit (ICU) after dose 2 of the vaccine. Float Date_of_death The date on which the patient died, if applicable. Date Immunization Information about the patient's immunization for example HD - Half Dose and FD - Full Dose String Comorbidity Whether the patient has any pre-existing medical conditions or not. String This database contains information about the administration of the ChAdOx1 nCoV-19 vaccine in half doses and its equivalence in reducing moderate and severe cases of COVID-19 compared to full doses. The ChAdOx1 nCoV-19 vaccine is developed to prevent infection by the SARS-CoV-2 virus, which causes COVID-19. The study analyzed the efficacy of administering the vaccine in half doses compared to full doses. The objective was to evaluate if the half dose would be as effective as the full dose in reducing moderate and severe cases of the disease. Through this database, it is possible to analyze and assess the effectiveness of administering the ChAdOx1 nCoV-19 vaccine in half doses, as well as comparing it to the use of full doses. This information can be used by researchers, healthcare professionals, and authorities responsible for vaccination policies to support decisions and recommendations related to COVID-19 immunization.

This dataset contains the FASTQ files used in the paper Comparison of Oxford Nanopore and Illumina sequencing for SARS-CoV-2 variant monitoring in wastewater. The FASTQ files are classified in 2 different folders: MinION and MiSeq. Inside the MinION folder, there are two more folders, one for the R9.4.1 flow cell data and the other for the R10.4.1 flow cell data. Twist synthetic RNA mixtures are named as mix1, mix2, etc. Twist synthetic RNA corresponding to the Wuhan sequence is named as mix11_WH Wastewater samples are named as WWTP_1, WWTP_2, etc.

The 500-ns CG-MD simulation trajectory towards SARS-CoV-2 virus.

The 500-ns CG-MD simulation trajectory and AA structure towards SARS-CoV-2 virus.

Abstract:Nirmatrelvir/ritonavir (Paxlovid) consists of a peptidomimetic inhibitor (nirmatrelvir) of the SARS-CoV-2 main protease and a pharmacokinetic enhancer (ritonavir). It is approved for the treatment of mild-to-moderate COVID-19. This combination of nirmatrelvir and ritonavir can mediate significant and complex drug-drug interactions (DDIs), primarily due to the ritonavir component. Indeed, ritonavir inhibits the metabolism of nirmatrelvir through cytochrome P450 3A (CYP3A) leading to higher plasma concentrations and a longer half-life of nirmatrelvir. Coadministration of nirmatrelvir/ritonavir with immunosuppressive drugs (ISDs) is particularly challenging given the major involvement of CYP3A in the metabolism of most of these drugs and their narrow therapeutic ranges. Exposure of ISDs will be drastically increased through the potent ritonavir-mediated inhibition of CYP3A, resulting in an increased risk of adverse drug reactions. Although a decrease in the dosage of ISDs can prevent toxicity, an inappropriate dosage regimen may also result in insufficient exposure and a risk of rejection. Here, we provide some general recommendations for therapeutic drug monitoring of ISDs and dosing recommendations when coadministered with nirmatrelvir/ritonavir. Particularly, tacrolimus should be discontinued, or patients should be given a microdose on day 1, whereas cyclosporine dosage should be reduced to 20% of the initial dosage during the antiviral treatment. Dosages of mammalian target of rapamycin inhibitors (m-TORis) should also be adjusted while dosages of mycophenolic acid and corticosteroids are expected to be less impacted.