Articles

Introduction: Hypoglycemia affects patient safety and glycemic control during insulin treatment of both type 1 (T1DM) and type 2 diabetes mellitus (T2DM). It is still a major clinical problem in the treatment of type 1 diabetes that impairs metabolic control. This study aimed to assess hypoglycemia and associated factors among type 1 diabetes mellitus patients attending the outpatient clinics of Debra–Tabor Comprehensive and Specialized Hospital, in 2021.Method: institutional-based cross-sectional study design was conducted among 204 selected type I DM, from June 1/2021 to August 30/2021. The study participants were selected by systematic sampling method from monthly follow-up lists and lists of registration. Data were cleaned and entered into Epi Data and then exported into SPSS version 20 for analysis. Data were presented with texts, graphs, diagrams, and tables but an analytic form of findings will be presented by text form of the odds ratio. Bivariable and multivariable binary logistic regression models were fitted to identify factors associated with hypoglycemia p – value < 0.05 was considered statistically significant and reported as a 95% confidence interval (CI).Results: A total of 204 participants participated with a response rate of 100%, and prevalence of self-reported hypoglycemia was 88.7% (95%, CI: 83.8-92.6) and the prevalence of hypoglycemia was significantly associated with occupation [AOR: 4.01 (95% CI:1.86-9.35)], higher educational status [AOR: 2.13 (95% CI:1.92-13.15)], diabetic duration < 1 [AOR: 3.80 (95% CI:1.32-9.28)], poor knowledge [AOR: 4.91 (95% CI:1.09-11.06)] and favorable attitude [AOR: 5.86 (1.10-6.07)]. The current study revealed that the knowledge, attitude, and practice of respondents were 81.9% (95%, CI, 76-86.8), 73% (95% CI, 66.7-78.9), and 91.2% (95% CI, 86.8-94.6) respectively.Conclusion and recommendation: Hypoglycemia was highly prevalent among diabetic patients treated at Debra-Tabor Comprehensive and Specialized Referral Hospital. To reduce the higher prevalence of hypoglycemia the health professionals working in the hospital had better provide appropriate patient advice about, BGL monitoring, medication adherence, self-injection as well as oral hypoglycemic agent administrations.

Biofungicides are prepared based on living micro/organisms or on matters prepared from them. They are based on the antagonism of fungal pathogens and their antagonists. Their effect depends on weather conditions (temperature and moisture) in comparison with chemical fungicides which are effective in all conditions but they let the residues in plants, animals, and men. The future of agriculture will be pure food without chemicals.

Los Reyes, Michoacán, Mexico, is one of the main blackberry-producing places in the world, however, the disease located at the root level has caused important economic losses. Currently has been reported that the fungus Fusarium spp., is the main causal agent but actions to control it have failed. The objective of this work was to identify the possible presence of unreported pathogenic fungi in the root system of the blackberry and identify them molecularly. It was sampled in a commercial open-air orchard from Los Reyes, pieces of roots were taken from symptomatic plants with wilting and decay. The fungi were isolated in the laboratory, identified with taxonomic keys, extraction was performed, and the sequences obtained were compared with those reported in the NCBI gene bank. Among the results obtained were Kalmusia italica, Epicoccum nigrum, Microsphaeropsis arundinis, Achizophyllum commune, and, as expected, some species of Fusarium spp.

Today, it is well known that Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has four types of proteins within its structure, between them the spike protein (S). The infection mechanism is carried out by the entry of the virus into the human host cell through the S protein, which strongly interacts with the human cell receptor angiotensin-converting enzyme 2 (ACE2). In this work, we propose an atomic model of the Receptor Binding Domain (RBD) of the S spike protein of the wild-type SARS-CoV-2 virus. The molecular structure of the model was composed of 50 amino acids that were chemically bonded, starting with Leucine and ending with one amino acid Tyrosine. The novelty of our work lies in the importance of knowing the sites and zones of maximum reactivity of the RBD from the fundamental levels of quantum mechanics considering the atomic structure of matter. For this, the local and global reactivity indices of the RBD were calculated, such as frontier orbitals, Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO), Fukui indices, chemical potential, chemical hardness, electrophilicity index; with this, it will be possible to know what type of molecules are more likely to interact with the RBD structure, and in this way, new knowledge will be generated at the quantum, atomic and molecular level to inhibit the virulent effects of wild-type SARS-CoV-2. Finally, in order to identify the functional groups within the most stable structure and thereby verify the future reactions that can be carried out between the RBD structure and biomolecules, the Infrared (IR) absorption spectrum was calculated. For this work, we used Material Studio v6.0 which uses the density functional theory (DFT) implemented in its DMol3 computational code. The IR spectrum was obtained using the Spartan ‘94 computer code. One novelty would be that we found nine amino acids more that could make the RBD and ACE2 binding further the already known. Thus, the Mulliken charge distribution indicates that the highest concentrations of positive and negative charge are found in the zones 477S, 478T, 484E, and 501N amino acids letting ionic or Van der Waals possible interactions with other structures.

Aim: A descriptive-analytical study was done to assess the proportion of the risk of stroke among male patients attending the outpatient department of a tertiary care hospital, in Ernakulam District, Kerala. Objectives: The objectives of the study were to assess the proportion of the risk of stroke among male patients attending outpatient departments and to determine the association of stroke risk level with socio-personal variables. Methods: The research approach of the study is a quantitative approach. The research design selected for the study is a descriptive-analytical design. The convenience sampling method was used for sample selection. The study was done in MOSC Medical College Hospital, Kolenchery among 288 male patients who met the inclusion criteria. Data collection was done using socio-personal proforma and stroke risk scorecards. Results: Collected data were analysed by using descriptive and inferential statistics presented in tables and pie diagrams. The study findings revealed that out of 288 subjects, 43.4% have low stroke risk, 13.9% are in caution and 42.7% have high stroke risk. The findings also revealed that there is a significant association of stroke risk level with age, education, occupation, BMI and place of residence. Statement of the problem: Proportion of risk of stroke among male patients attending outpatient department of a tertiary care hospital, Ernakulam district, Kerala. Proportion of risk of stroke among male patients attending outpatient department of a tertiary care hospital, Ernakulam district, Kerala.

Objective: To identify risk factors among pregnant with COVID-19 for adverse outcomes related to disease severity, maternal mortality, and morbidity.Materials and methods: In this retrospective study, 45 pregnant patients with COVID-19 pneumonia were confirmed by RT-PCR. The inclusion criteria were pregnant patients diagnosed with COVID-19 confirmed by RT-PCR and hospitalized in the gynecology-obstetrics and intensive care unit. Exclusion criteria were non-pregnant patients and pneumonia cases with unconfirmed COVID-19 causes. The study used SPSS software to analyze the data. Results: Our study recorded 45 cases of SARS-CoV-2 infection in pregnant women over 2.5 years. The age group most affected was 20-35 years, with 75% of cases. 57% of patients had no known comorbidities. 88.8% of patients were symptomatic at diagnosis. Almost 30% of patients required admission to the ICU, with 60% requiring oxygen supplementation. The study recorded 36 live births (80%), of which 26 cases (72.2%) required no further care and had a favorable outcome.Conclusion: Pregnant women with medical conditions are at higher risk of severe COVID-19, which can cause respiratory distress syndrome and impact delivery and neonatal outcomes. Preventive measures are important.

Methyl Jasmonate (MeJA) can be used as a signal molecule to regulate the expression of resistance genes in the resistance to abiotic stress, thus improving the salt tolerance of wild jujube. Among the resistance genes combined with methyl jasmonate, transcription factors play an important role in response to salt stress. However, the interaction of transcription factors in different tissues under salt stress and the regulation of transcription factors by MeJA remain unclear. In this study, the effects of MeJA on transcription factor expression in wild jujube under salt stress were investigated, and the differences in transcription factor expression among different tissues were compared. It was found that MeJA could increase the type and quantity of transcription factors responding to salt stress. The types of transcription factors responding to salt stress were roughly the same among different tissues, but the quantity and expression of the transcription factors were significantly different. The results of transcription factor co-expression analysis showed that transcription factors play synergistic roles in the face of abiotic stress, which can provide preferable genes for subsequent transgenic work.

Worldwide, statistical data of people infected by COVID-19 has been taken until March 29, 2023, which, when correlated, showed a predictive logistic  model. The purpose was to determine the predictive model, which was acceptable, in such a way that the proportionality constant and the correlation and determination coefficients are of great importance to estimating epidemiological and pandemic data; coinciding with what was reported by other authors. Bearing in mind that a mathematical model is a mathematical description through a function or equation of a phenomenon in the real world; whose purpose is to understand infections and make predictions for the future. The stages were: to model the number of people infected as a function of time, formulate, and choose the logistic model, determine the model and obtain mathematical conclusions, and make predictions (estimates) about the number of people infected by COVID-19 worldwide. The logistic model was derived to predict the speed of people infected by COVID-19 and the critical time (tc = 733 days) for which the speed was maximum (1694,7209 infected/day). The Pearson correlation coefficient for the time elapsed (t) and the number of people infected (N) worldwide, based on 32 cases, was r = -0.88; the relationship between time and those infected is real, there is a “very strong correlation” between the time elapsed (t) and the number of people infected (N) and 77.03% of the variance in N is explained by t. 

What is time? Is it a physical quantity, illusion, or dimension? Defining time is challenging and fascinating. We often consider time as a dimension to help us understand the concept of space-time. Time undeniably exists, but we can only sense its presence through its effects. For instance, if we take two apples, one bought months ago and the other just a day ago, we can tell that one apple was bought a long time ago because it had rotted. We express time as the effect caused by it. If there were no effects of time on this universe, then the concept of time would not exist [1,2].

Strep throat, a common affliction known for its hallmark symptom of a severe and sudden sore throat, is caused by the bacterium Streptococcus pyogenes, classified under Group-A Streptococcus (GAS) [1]. This condition not only impacts millions globally but also carries the risk of severe complications if left untreated [2]. Understanding strep throat goes beyond recognizing its symptoms; it entails an appreciation of its transmission dynamics, potential complications, and the evolving landscape of treatment and prevention strategies [3].