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by Adam G. Clause, Roberto Luna-Reyes, Oscar M. Mendoza-Velázquez, Adrián Nieto-Montes de Oca, Israel Solano-Zavaleta
The mountain forests of Middle America are renowned for their endemic biodiversity, and arboreal alligator lizards (genus Abronia) are high-profile vertebrates endemic to this region. In this work, we describe a new species of arboreal Abronia that is known only from the type locality in the Northern Highlands of Chiapas, Mexico. The new species is diagnosed from all other members of the genus Abronia by the following combination of characters: lack of protuberant or spine-like supra-auricular scales, lack of protuberant or casque-like posterolateral head scales, dorsum of head pale yellow with distinct dark markings, 35–39 transverse dorsal scale rows, lateralmost row of ventral scales enlarged relative to adjacent medial row, and dorsum brown with darker crossbands that are sometimes reduced to rows of spots. We provisionally include the new species in the subgenus Lissabronia based on genomic and morphological evidence, but our results also suggest a close relationship to the subgenus Abaculabronia. The new species is geographically separated from the nearest Lissabronia and Abaculabronia species by the lowland Central Depression of Chiapas. Ongoing habitat loss and other factors imperil the new species, leading us to propose its listing under multiple threatened species frameworks. Because the Northern Highlands have poor coverage of protected areas, we briefly comment on the potential of this new species for stimulating conservation in the region.by Nene Kaah Keneh, Sebastien Kenmoe, Arnol Bowo-Ngandji, Jane-Francis Tatah Kihla Akoachere, Hortense Gonsu Kamga, Roland Ndip Ndip, Jean Thierry Ebogo-Belobo, Cyprien Kengne-Ndé, Donatien Serge Mbaga, Nicholas Tendongfor, Lucy Mande Ndip, Seraphine Nkie Esemu
BackgroundThe emergence of methicillin-resistant Staphylococcus aureus (MRSA) has increased and poses a significant threat to human and animal health in Cameroon and the world at large. MRSA strains have infiltrated various settings, including hospitals, communities, and livestock, contributing to increased morbidity, treatment costs, and mortality. This evidence synthesis aims to understand MRSA prevalence, resistance patterns, and genetic characterization in Cameroon.
MethodsThe methodology was consistent with the PRISMA 2020 guidelines. Studies of any design containing scientific data on MRSA prevalence, genetic diversity, and antimicrobial resistance patterns in Cameroon were eligible for inclusion, with no restrictions on language or publication date. The search involved a comprehensive search strategy in several databases including Medline, Embase, Global Health, Web of Science, African Index Medicus, and African Journal Online. The risk of bias in the included studies was assessed using the Hoy et al tool, and the results were synthesized and presented in narrative synthesis and/or tables and graphs.
ResultsThe systematic review analyzed 24 studies, mostly conducted after 2010, in various settings in Cameroon. The studies, characterized by moderate to low bias, revealed a wide prevalence of MRSA ranging from 1.9% to 46.8%, with considerable variation based on demographic and environmental factors. Animal (0.2%), food (3.2% to 15.4%), and environmental samples (0.0% to 34.6%) also showed a varied prevalence of MRSA. The genetic diversity of MRSA was heterogeneous, with different virulence gene profiles and clonal lineages identified in various populations and sample types. Antimicrobial resistance rates showed great variability in the different regions of Cameroon, with notable antibiotic resistance recorded for the beta-lactam, fluoroquinolone, glycopeptide, lincosamide, and macrolide families.
ConclusionThis study highlights the significant variability in MRSA prevalence, genetic diversity, and antimicrobial resistance patterns in Cameroon, and emphasizes the pressing need for comprehensive antimicrobial stewardship strategies in the country.
by Priscila Ceolin Meneghetti, Junying Li, Paulo Sérgio Borella, Gustavo Mendonça, Luiz Henrique Burnett Jr
This study aimed to compare the accuracy of full-arch digital implant impressions using seven different scanbodies and four intraoral scanners. A 3D-printed maxillary model with six implants and their respective multi-unit abutments was used for this study. Seven scanbodies (SB1, SB2, SB3, SB4, SB5, SB6, and SB7) and four intraoral scanners (Primescan®, Omnican®, Trios 3®, and Trios 4®) were assessed. Each combination group was scanned ten times and a dental lab scanner (D2000, 3Shape) was used as a reference. All scans were exported as STL files, imported into Convince software (3Shape) for alignment, and later into Blender software, where their 3D positions were analyzed using a Python script. The 3D deviation, angular deviation, and linear distance between implants #3 and #14 were also measured. Accuracy was measured in terms of “trueness” (scanbody 3D deviation between intraoral scan and desktop scan). Kruskal-Wallis followed by the Bonferroni correction was used to analyze the data (⍺ = .05). The study found statistically significant differences in digital impression accuracy among the scanners and scanbodies (pby Danny Xuan-Rong Koh, Mohamed Afiq Hidayat Zailani, Raja Zahratul Azma Raja Sabudin, Sanggari Muniandy, Nur Awatif Akmal Muhamad Hata, Siti Noor Baya Mohd Noor, Norhazilah Zakaria, Ainoon Othman, Endom Ismail
Glucose-6-phosphate dehydrogenase (G6PD) deficiency is an X-linked genetic disorder characterized by reduced G6PD enzyme levels in the blood. This condition is common in populations exposed to malaria; an acute febrile disease caused by Plasmodium parasites. G6PD-deficient individuals may suffer from acute hemolysis following the prescription of Primaquine, an antimalarial treatment. The population at risk for such a condition includes the Senoi group of Orang Asli, a remote indigenous community in Malaysia. This study aimed to elucidate the G6PD molecular heterogeneity in this subethnic group which is important for malaria elimination. A total of 662 blood samples (369 males and 293 females) from the Senoi subethnic group were screened for G6PD deficiency using a quantitative G6PD assay, OSMMR2000-D kit with Hb normalization. After excluding the family members, the overall prevalence of G6PD deficiency in the studied population was 15.2% (95% CI: 11–19%; 56 of 369), with males (30 of 172; 17.4%) outnumbering females (26 of 197; 13.2%). The adjusted male median (AMM), defined as 100% G6PD activity, was 11.8 IU/gHb. A total of 36 participants (9.6%; 26 male and 10 female) were deficient (G)(39.1%; n = 34), G6PD Viangchan (c.871G>A)(25.3%; n = 22), G6PD Union (c.1360C>T)(21.8%; n = 19), c.1311C>T(20.7%; n = 18), G6PD Kaiping (c.1388G>A)(8.0%; n = 7), and G6PD Coimbra (c.592C>T)(2.3%; n = 2). Our analysis revealed 27 hemizygote males, 18 heterozygote females, 7 homozygote females, and 2 compound heterozygote females. This study confirms the high prevalence of G6PD deficiency among the Senoi Malaysian Orang Asli, with a significant degree of molecular heterogeneity. More emphasis should be placed on screening for G6PD status and proper and safe use of Primaquine in the elimination of malaria among this indigenous population.by Leonides Medeiros Neto, Sebastião Rogerio da Silva Neto, Patricia Takako Endo
Tabular data is commonly used in business and literature and can be analyzed using tree-based Machine Learning (ML) algorithms to extract meaningful information. Deep Learning (DL) excels in data such as image, sound, and text, but it is less frequently utilized with tabular data. However, it is possible to use tools to convert tabular data into images for use with Convolutional Neural Networks (CNNs) which are powerful DL models for image classification. The goal of this work is to compare the performance of converters for tabular data into images, select the best one, optimize a CNN using random search, and compare it with an optimized ML algorithm, the XGBoost. Results show that even a basic CNN, with only 1 convolutional layer, can reach comparable metrics to the XGBoost, which was trained on the original tabular data and optimized with grid search and feature selection. However, further optimization of the CNN with random search did not significantly improve its performance.by Frederick P. Rivara, Ashley B. Hink, Deborah Kuhls, Samantha Banks, Lauren L. Agoubi, Shelbie Kirkendoll, Alex Winchester, Christopher Hoeft, Bhavin Patel, Avery Nathens
Firearm deaths continue to be a major public health problem, but the number of non-fatal firearm injuries and the characteristics of patients and injuries is not well known. The American College of Surgeons Committee on Trauma, with support from the National Collaborative on Gun Violence Research, leveraged an existing data system to capture lethal and non-lethal injuries, including patients treated and discharged from the emergency department and collect additional data on firearm injuries that present to trauma centers. In 2020, Missouri had the 4th highest firearm mortality rate in the country at 23.75/100,000 population compared to 13.58/100,000 for the US overall. We examined the characteristics of patients from Missouri with firearm injuries in this cross-sectional study. Of the overall 17,395 patients, 1,336 (7.7%) were treated at one of the 11 participating trauma centers in Missouri during the 12-month study period. Patients were mostly male and much more likely to be Black and uninsured than residents in the state as a whole. Nearly three-fourths of the injuries were due to assaults, and overall 7.7% died. Few patients received post-discharge services.by Jan Maleček, Dan Omcirk, Kateřina Skálová, Jan Pádecký, Martin Tino Janikov, Michael Obrtel, Michal Jonáš, David Kolář, Vladimír Michalička, Karel Sýkora, Michal Vágner, Lubomír Přívětivý, Tomáš Větrovský, Zdeňka Bendová, Vít Třebický, James J. Tufano
IntroductionA lack of sleep can pose a risk during military operations due to the associated decreases in physical and cognitive performance. However, fast-acting ergogenic aids, such as ammonia inhalants (AI), may temporarily mitigate those adverse effects of total sleep deprivation (TSD). Therefore, the present study aimed to investigate the acute effect of AI on cognitive and physical performance throughout 36 hours of TSD in military personnel.
MethodsEighteen male military cadets (24.1 ± 3.0 y; 79.3 ± 8.3 kg) performed 5 identical testing sessions during 36 hours of TSD (after 0 [0], 12 [–12], 24 [–24], and 36 [–36] hours of TSD), and after 8 [+8] hours of recovery sleep. During each testing session, the following assessments were conducted: Epworth sleepiness scale (ESS), simple reaction time (SRT), shooting accuracy (SA), rifle disassembling and reassembling (DAS), and countermovement jump height (JH). Heart rate (HR) was continuously monitored during the SA task, and a rating of perceived exertion (RPE) was obtained during the JH task. At each time point, tests were performed twice, either with AI or without AI as control (CON), in a counterbalanced order.
ResultsThere was faster SRT (1.6%; p 0.05). Independent of AI, the SRT was slower (3.2–9.3%; p Conclusion
Although there were detrimental effects of TSD, the usage of AI did not reduce those adverse effects. However, regardless of TSD, AI did result in a short-term increase in HR, improved SRT without affecting the number of errors, and improved JH while concurrently decreasing the RPE. No changes, yet, were observed in SA and DAS. These results suggest that AI could potentially be useful in some military scenarios, regardless of sleep deprivation.
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