Background: and Purpose Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. Methods: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. Results: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%–60.7% and 73.7%–74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen’s kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. Conclusion Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has led to high levels of burnout among nurses. Information and communication technology (ICT) may offer a solution to prevent a potential collapse in healthcare. The aim of this study was to identify areas where ICT could provide support, by analyzing the work of nurses during the COVID-19 pandemic. Methods: This retrospective exploratory descriptive study analyzed qualitative data from the activity diaries of seven nurses working in COVID-19 wards or intensive care units. Results: The nursing work process during COVID-19 involved “added tasks,” “changed tasks,” and “reduced tasks” compared to the pre-COVID-19 situation. Nurses reported difficulties in communicating with other healthcare professionals both inside and outside the isolation room, as well as with patients. The use of various ICT solutions, such as real-time video-conferencing systems or mobile robots, could enhance patient monitoring in the isolation room and improve the quality and efficiency of communication. Conclusions The changes in work tasks not only led to nurse exhaustion but also negatively impacted the quality of care. ICT solutions should be explored to minimize the time spent in the isolation room, thereby reducing the risk of infection spread. This could also enhance communication among patients, family caregivers, and healthcare professionals.

Secukinumab is an anti-interleukin 17A monoclonal antibody used for treating chronic plaque psoriasis. Eczematous eruption is a relatively unknown adverse effect of secukinumab. A 32-year-old man developed eczematous eruptions on both lower extremities following secukinumab treatment for severe plaque psoriasis. The lesions were clinically diagnosed as a nummular eczema-like eruption and were treated with topical corticosteroids without switching or stopping secukinumab. Considering the increased use of secukinumab and other interleukin-17A inhibitors, dermatologists should be aware of the cutaneous side effects of the drug.

BACKGROUND/OBJECTIVES: While many obesity studies have pointed out the importance of meal regularity, few have conducted empirical analyses using data from food diaries. We examined the association between meal regularity (i.e., meal time regularity [MTR] and calorie intake regularity [CIR]) and weight loss. SUBJECTS/METHODS: We collected food diary data from 637 women who had participated in commercial weight loss programs for 28–168 days (4–24 weeks). This study defined “meal regularity” in terms of two concepts: MTR and CIR. MTR refers to how regularly people eat their meals (i.e., at certain times each day), whereas CIR refers to how regularly people consume a certain amount of calories at each meal. We conducted multiple regression analyses. RESULTS: MTR (model 1: β = −2,576.526, P < 0.001; model 2: β = −1511.447, P < 0.05; model 3: β = −1,721.428, P < 0.05) and CIR (model 1: β = −1,231.551, P < 0.01; model 2: β = −2,082.353, P < 0.001; model 3: β = −1,343.490, P < 0.01) turned out to be significant determinants of the amount of weight loss in breakfast, lunch, and dinner contexts. While meal regularity (i.e., MTR and CIR) was significantly associated with weight loss, daily calorie intake from meals was not significantly associated with the amount of weight loss (model 1: β = 0.13, P > 0.05; model 2: β = 0.11, P > 0.05; model 3: β = 0.14, P > 0.05). Subjects who consumed an equal amount of calories per meal throughout the day lost more weight than those who did not (model 4: β = −3,675.51, P < 0.001). CONCLUSIONS Eating each meal (i.e., breakfast, lunch, and dinner) at a certain time every day may increase weight loss success. Also, consuming the same amount of calories at each meal may help weight loss success.

Many packages for a meta-analysis of genome-wide association studies (GWAS) have beendeveloped to discover genetic variants. Although variations across studies must be considered, there are not many currently-accessible packages that estimate between-study heterogeneity. Thus, we propose a python based application called Beta-Meta which can easilyprocess a meta-analysis by automatically selecting between a fixed effects and a randomeffects model based on heterogeneity. Beta-Meta implements flexible input data manipulation to allow multiple meta-analyses of different genotype-phenotype associations in asingle process. It provides a step-by-step meta-analysis of GWAS for each association inthe following order: heterogeneity test, two different calculations of an effect size and ap-value based on heterogeneity, and the Benjamini-Hochberg p-value adjustment. Thesemethods enable users to validate the results of individual studies with greater statisticalpower and better estimation precision. We elaborate on these and illustrate them with examples from several studies of infertility-related disorders.

Cystic echinococcosis is a zoonotic parasitic disease caused by Echinococcus species. Tanzania is one of the endemic countries with cystic echinococcosis. This study focussed on identifying genotypes of Echinococcus spp. in Tanzania. We collected 7 cysts from cattle in Mwanza municipal (n=4) and Loliondo district (n=3). The cysts from Mwanza were all E. ortleppi and fertile. In contrast, the cysts from Loliondo were all E. granulosus sensu stricto and sterile. Two from the 4 cysts were a new haplotype of E. ortleppi (G5). These results can improve the preventive and control programs for humans and livestock in Tanzania. To our knowledge, this study is considered the first to identify the genotype and haplotype of Echinococcus spp. in Tanzania.

This study was carried out to provide information on the taxonomic classification and analysis of mitochondrial genomes of Spirometra theileri. One strobila of S. theileri was collected from the intestine of an African leopard (Panthera pardus) in the Maswa Game Reserve, Tanzania. The complete mtDNA sequence of S. theileri was 13,685 bp encoding 36 genes including 12 protein genes, 22 tRNAs and 2 rRNAs with absence of atp8. Divergences of 12 protein-coding genes were as follow: 14.9% between S. theileri and S. erinaceieuropaei, 14.7% between S. theileri and S. decipiens, and 14.5% between S. theileri with S. ranarum. Divergences of 12 proteins of S. theileri and S. erinaceieuropaei ranged from 2.3% in cox1 to 15.7% in nad5, while S. theileri varied from S. decipiens and S. ranarum by 1.3% in cox1 to 15.7% in nad3. Phylogenetic relationship of S. theileri with eucestodes inferred using the maximum likelihood and Bayesian inferences exhibited identical tree topologies. A clade composed of S. decipiens and S. ranarum formed a sister species to S. erinaceieuropaei, and S. theileri formed a sister species to all species in this clade. Within the diphyllobothridean clade, Dibothriocephalus, Diphyllobothrium and Spirometra formed a monophyletic group, and sister genera were well supported.

This study was carried out to provide information on the taxonomic classification and analysis of mitochondrial genomes of Spirometra theileri. One strobila of S. theileri was collected from the intestine of an African leopard (Panthera pardus) in the Maswa Game Reserve, Tanzania. The complete mtDNA sequence of S. theileri was 13,685 bp encoding 36 genes including 12 protein genes, 22 tRNAs and 2 rRNAs with absence of atp8. Divergences of 12 protein-coding genes were as follow: 14.9% between S. theileri and S. erinaceieuropaei, 14.7% between S. theileri and S. decipiens, and 14.5% between S. theileri with S. ranarum. Divergences of 12 proteins of S. theileri and S. erinaceieuropaei ranged from 2.3% in cox1 to 15.7% in nad5, while S. theileri varied from S. decipiens and S. ranarum by 1.3% in cox1 to 15.7% in nad3. Phylogenetic relationship of S. theileri with eucestodes inferred using the maximum likelihood and Bayesian inferences exhibited identical tree topologies. A clade composed of S. decipiens and S. ranarum formed a sister species to S. erinaceieuropaei, and S. theileri formed a sister species to all species in this clade. Within the diphyllobothridean clade, Dibothriocephalus, Diphyllobothrium and Spirometra formed a monophyletic group, and sister genera were well supported.

Spirometra tapeworms (Cestoda: Diphyllobothriidae) collected from carnivorous mammals in Tanzania were identified by the DNA sequence analysis of the mitochondrial cytochrome c oxidase subunit 1 (cox1) and internal transcribed spacer 1 (ITS1), and by morphological characteristics. A total of 15 adult worms were collected from stool samples and carcasses of Panthera leo, Panthera pardus, and Crocuta crocuta in the Serengeti and Selous ecosystems of Tanzania. Three Spirometra species: S. theileri, S. ranarum and S. erinaceieuropaei were identified based on morphological features. Partial cox1 sequences (400 bp) of 10 specimens were revealed. Eight specimens showed 99.5% similarity with Spirometra theileri (MK955901), 1 specimen showed 99.5% similarity with the Korean S. erinaceieuropaei and 1 specimen had 99.5% similarity with Myanmar S. ranarum. Sequence homology estimates for the ITS1 region of S. theileri were 89.8% with S. erinaceieuropaei, 82.5% with S. decipiens, and 78.3% with S. ranarum; and 94.4% homology was observed between S. decipiens and S. ranarum. Phylogenetic analyses were performed with 4 species of Spirometra and 2 species of Dibothriocephalus (=Diphyllobothrium). By both ML and BI methods, cox1 and ITS1 gave well supported, congruent trees topology of S. erinaceieuropaei and S. theileri with S. decipiens and S. ranarum forming a clade. The Dibothriocephalus species were sisters of each other and collectively forming successive outgroups. Our findings confirmed that 3 Spirometra species (S. theileri, S. ranarum, and S. erinaceieuropaei) are distributed in the Serengeti and Selous ecosystems of Tanzania.

Spirometra tapeworms (Cestoda: Diphyllobothriidae) collected from carnivorous mammals in Tanzania were identified by the DNA sequence analysis of the mitochondrial cytochrome c oxidase subunit 1 (cox1) and internal transcribed spacer 1 (ITS1), and by morphological characteristics. A total of 15 adult worms were collected from stool samples and carcasses of Panthera leo, Panthera pardus, and Crocuta crocuta in the Serengeti and Selous ecosystems of Tanzania. Three Spirometra species: S. theileri, S. ranarum and S. erinaceieuropaei were identified based on morphological features. Partial cox1 sequences (400 bp) of 10 specimens were revealed. Eight specimens showed 99.5% similarity with Spirometra theileri (MK955901), 1 specimen showed 99.5% similarity with the Korean S. erinaceieuropaei and 1 specimen had 99.5% similarity with Myanmar S. ranarum. Sequence homology estimates for the ITS1 region of S. theileri were 89.8% with S. erinaceieuropaei, 82.5% with S. decipiens, and 78.3% with S. ranarum; and 94.4% homology was observed between S. decipiens and S. ranarum. Phylogenetic analyses were performed with 4 species of Spirometra and 2 species of Dibothriocephalus (=Diphyllobothrium). By both ML and BI methods, cox1 and ITS1 gave well supported, congruent trees topology of S. erinaceieuropaei and S. theileri with S. decipiens and S. ranarum forming a clade. The Dibothriocephalus species were sisters of each other and collectively forming successive outgroups. Our findings confirmed that 3 Spirometra species (S. theileri, S. ranarum, and S. erinaceieuropaei) are distributed in the Serengeti and Selous ecosystems of Tanzania.