UNASSIGNED: This study aimed to detect Toxocara cati in cats by microscopic and molecular analysis using PCR, sequencing, and phylogenetic analysis.
UNASSIGNED: Randomly selected 200 cat feces samples were taken from various private veterinarian clinics in Baghdad. To identify eggs of T. cati by the flotation method, DNA from 100 cat feces was extracted, and one pair of ITS2 region-specific primers was used for polymerase chain reaction, followed by sequencing.
UNASSIGNED: Toxocara cati infection rate was found to be 23 out of 100 fecal samples using PCR. Ten DNA product sequence data studies showed 98%-100% similarity to the 5.8S ribosomal RNA gene sequences found in the Gene Bank. The study incidence showed that the overall infection rate by microscopic examination was 23%, with no significant difference between stray cats (27%), and domestic cats (19%). After studying the effect of several epidemiological parameters on the infection rate, it was found that the infection rates of stray and domestic cats were higher in kittens under six months of age, at 46.1% and 27%, respectively, whereas rates were lower for the adult than six months was 11.5% of domestic cats and 14.7% of stray cats. The percentage of stray and domestic male cats that were registered was 35.5%, whereas the female cats registered were 20.6% and 17.5%, respectively.
UNASSIGNED: Cats are significant clinical reservoirs for zoonotic parasites. In Iraq, Baghdad has a high incidence of T. cati detections. Compared to conventional methods, PCR is thought to be a more sensitive, accurate diagnostic procedure that confirms the species\' identity.

Understanding how neural circuits generate sequential activity is a longstanding challenge. While foundational theoretical models have shown how sequences can be stored as memories in neural networks with Hebbian plasticity rules, these models considered only a narrow range of Hebbian rules. Here, we introduce a model for arbitrary Hebbian plasticity rules, capturing the diversity of spike-timing-dependent synaptic plasticity seen in experiments, and show how the choice of these rules and of neural activity patterns influences sequence memory formation and retrieval. In particular, we derive a general theory that predicts the tempo of sequence replay. This theory lays a foundation for explaining how cortical tutor signals might give rise to motor actions that eventually become \"automatic.\" Our theory also captures the impact of changing the tempo of the tutor signal. Beyond shedding light on biological circuits, this theory has relevance in artificial intelligence by laying a foundation for frameworks whereby slow and computationally expensive deliberation can be stored as memories and eventually replaced by inexpensive recall.

Species belonging to the family Paramphistomidae Fischoeder, 1901, commonly known as \"rumen flukes\", are a group of parasites frequently related to Brazilian livestock production. They inhabit the digestive tract of ruminants and have recognized pathogenicity during the early stages of infection, which can be responsible for economic losses. These trematodes are often associated with Southern Brazil, a region heavily focused on animal farming, which also makes it ideal for the life cycle of paramphistomes. Despite their aforementioned importance, studies regarding their distribution, molecular taxonomy and biology are still scarce in the country. In the present study, rumen flukes collected from cattle (n = 22) and sheep (n = 3) from 9 batches of ruminants from the cities of Jaguarão, Pelotas and Rio Grande, state of Rio Grande do Sul, Brazil, between May and July 2022, were subjected to morphological and molecular study. The microscopic analysis of histological and manual cuts revealed diagnostical traits compatible with Paramphistomum leydeni Näsmark, 1937, including the presence of tegumental papillae, pharynx of the liorchis type and acetabulum of the leydeni type. Molecular data corroborated the morphological identification, with ITS-2 and cox-1 sequences here obtained presenting 100% and 96.8-99.8% similarity, respectively, to P. leydeni samples previously characterized in different countries from Asia, Europe, and South America. Intensity of infection ranged from 5 to 458 and 1 to3 specimens of P. leydeni in sampled cattle and sheep, respectively. The present study contributes to a better understanding of the taxonomy of the flukes involved in cattle and sheep paramphistomosis in Brazil, suggesting that P. leydeni could be the main paramphistome species found in ruminants in the studied region.

By accelerating time-consuming processes with high efficiency, computing has become an essential part of many modern chemical pipelines. Machine learning is a class of computing methods that can discover patterns within chemical data and utilize this knowledge for a wide variety of downstream tasks, such as property prediction or substance generation. The complex and diverse chemical space requires complex machine learning architectures with great learning power. Recently, learning models based on transformer architectures have revolutionized multiple domains of machine learning, including natural language processing and computer vision. Naturally, there have been ongoing endeavors in adopting these techniques to the chemical domain, resulting in a surge of publications within a short period. The diversity of chemical structures, use cases, and learning models necessitate a comprehensive summarization of existing works. In this paper, we review recent innovations in adapting transformers to solve learning problems in chemistry. Because chemical data is diverse and complex, we structure our discussion based on chemical representations. Specifically, we highlight the strengths and weaknesses of each representation, the current progress of adapting transformer architectures, and future directions.

The HIV-1 Rev protein expressed in the early stage of virus replication is involved in the nuclear export of some forms of virus RNA. Naturally occurring polymorphisms in the Rev protein could influence its activity. The association between the genetic features of different virus variants and HIV infection pathogenesis has been discussed for many years. In this study, Rev diversity among HIV-1 group M clades was analyzed to note the signatures that could influence Rev activity and, subsequently, clinical characteristics. From the Los Alamos HIV Sequence Database, 4962 Rev sequences were downloaded and 26 clades in HIV-1 group M were analyzed for amino acid changes, conservation in consensus sequences, and the presence of clade-specific amino acid substitutions (CSSs) and the Wu-Kabat protein variability coefficient (WK). Subtypes G, CRF 02_AG, B, and A1 showed the largest amino acid changes and diversity. The mean conservation of the Rev protein was 80.8%. In consensus sequences, signatures that could influence Rev activity were detected. In 15 out of 26 consensus sequences, an insertion associated with the reduced export activity of the Rev protein, 95QSQGTET96, was identified. A total of 32 CSSs were found in 16 clades, wherein A6 had the 41Q substitution in the functionally significant region of Rev. The high values of WK coefficient in sites 51 and 82, located on the Rev interaction surface, indicate the susceptibility of these positions to evolutionary replacements. Thus, the noted signatures require further investigation.

UNASSIGNED: Dural sinus thrombosis is considered as a one of the clinical and radiological emergencies that require special attention and high index of suspicion and needs combined effort of both the treating physician and the radiologist to obtain proper diagnosis and subsequently proper management.
UNASSIGNED: The aim of this article was to compare the accuracy of MRV TOF and post contrast MP-RAGE sequences in diagnosis of cerebral sinus venous thrombosis.
UNASSIGNED: After all informed consents were obtained and upon ethical committee approval from the ethical committee in Joradanian Royal medical services in Amman we perform this study as a retrospective study done on 50 patients with cerebral sinus venous thrombosis with 50 pateints control group done at king Hussein medical center in Amman Jordan.
UNASSIGNED: The guidelines and regulations of studies conducted in Royal medical services were followed. 68 females and 32 males with age range between 19 and 52 years. All patients underwent brain MRI for evaluation of cerebral sinus thrombosis, all studies were done on seimens skyra 3 Tesla machine with standardized protocol including 2 D TOF MRV, axial T2WI, axial FLAIR, Axial T1, SWI and diffusion weighted images along with 3D MP-RAGE post contrast. Images were reviewed by two well experienced neuroradiologists (Maysoon and Qamar) in separate sessions, each MRI sequence was reported separately without knowing patients name or clinical history. Conclusion: The results for T2 WI, SWI, MRV TOF and MP-RAGE post contrast were reported. We used a confidence level score to standardize the results. Then the results were analyzed using simple statistical methods.

The aim of the study was to externally validate two AI models for the classification of prostate mpMRI sequences and segmentation of the prostate gland on T2WI.
MpMRI data from 719 patients were retrospectively collected from two hospitals, utilizing nine MR scanners from four different vendors, over the period from February 2018 to May 2022. Med3D deep learning pretrained architecture was used to perform image classification,UNet-3D was used to segment the prostate gland. The images were classified into one of nine image types by the mode. The segmentation model was validated using T2WI images. The accuracy of the segmentation was evaluated by measuring the DSC, VS,AHD.Finally,efficacy of the models was compared for different MR field strengths and sequences.
20,551 image groups were obtained from 719 MR studies. The classification model accuracy is 99%, with a kappa of 0.932. The precision, recall, and F1 values for the nine image types had statistically significant differences, respectively (all P < 0.001). The accuracy for scanners 1.436 T, 1.5 T, and 3.0 T was 87%, 86%, and 98%, respectively (P < 0.001). For segmentation model, the median DSC was 0.942 to 0.955, the median VS was 0.974 to 0.982, and the median AHD was 5.55 to 6.49 mm,respectively.These values also had statistically significant differences for the three different magnetic field strengths (all P < 0.001).
The AI models for mpMRI image classification and prostate segmentation demonstrated good performance during external validation, which could enhance efficiency in prostate volume measurement and cancer detection with mpMRI.
These models can greatly improve the work efficiency in cancer detection, measurement of prostate volume and guided biopsies.

BACKGROUND: Identification and characterization of the endophytic microorganism, is gaining their underestimated significance in influencing health, performance, and other biological attributions of plants in general and forest tree species in particular. Because of the scarcity of information on the endophytic microbiome of the Hyrcanian forests species, including hornbeam (Carpinus betulus L.) trees, as a major constituent thereof, the present study aimed at the identification and partial characterization of the endophytic Bacillus species of Carpinus betulus as the first step in this context.
RESULTS: Shoot samples were collected from the Hyrcanian forest locations of Mazandaran and Golestan provinces in Iran. Bacterial strains were isolated from the surface-disinfected shoot segments and subjected to phenotypic characterization. Following assessment of the genetic diversity of the isolates by BOX-PCR fingerprinting, the representative isolates of each of the 15 groups were used for further characterization. Analysis of the nucleotide sequences of the 16S rDNA and HSP60 gene of the isolates led to the identification of 10 species. The predominant species was B. cereus followed by B. subtilis. The other species encountered were B. thuringiensis, Priestia filamentosa, B. velezensis, B. mojavensis, B. amyloliquefaciens, B. safensis, P. aryabhattai, and Gottfriedia acidiceleris. Most isolates possessed characteristics which could contribute to the biocontrol potential of the isolates, including formation of biofilm, production of hydrogen cyanide, tolerant to relatively high concentration of sodium chloride, and antibacterial activity.
CONCLUSIONS: Ten Bacillus species were identified as the prevailing endophytic species of C. betulus in the Hyrcanian forest of northern Iran, most turned up to possess biological activities involved in biocontrol capability of the isolates against some plant pathogens. These potentially capable bacteria could be implemented in the promotion of plant growth as well as in the biological control of pathogens. This is the first report on the characterization and elucidation of the diversity of the potentially beneficial endophytic species of Bacillus and the closely related genera living in the internal tissues of hornbeam trees.

Infection by hepatitis B virus (HBV) is responsible for approximately 296 million chronic cases of hepatitis B, and roughly 880,000 deaths annually. The global burden of HBV is distributed unevenly, largely owing to the heterogeneous geographic distribution of its subtypes, each of which demonstrates different severity and responsiveness to antiviral therapy. It is therefore crucial to the global public health response to HBV that the spatiotemporal spread of each genotype is well characterized. In this study, we describe a collection of 133 newly sequenced HBV strains from recent African immigrants upon their arrival in Belgium. We incorporate these sequences-all of which we determine to come from genotypes A, D, and E-into a large-scale phylogeographic study with genomes sampled across the globe. We focus on investigating the spatio-temporal processes shaping the evolutionary history of the three genotypes we observe. We incorporate several recently published ancient HBV genomes for genotypes A and D to aid our analysis. We show that different spatio-temporal processes underlie the A, D, and E genotypes with the former two having originated in southeastern Asia, after which they spread across the world. The HBV E genotype is estimated to have originated in Africa, after which it spread to Europe and the Americas. Our results highlight the use of phylogeographic reconstruction as a tool to understand the recent spatiotemporal dynamics of HBV, and highlight the importance of supporting vulnerable populations in accordance with the needs presented by specific HBV genotypes.

Amylase is an indispensable hydrolase in insect growth and development. Its varied enzymatic parameters cause insects to have strong stress resistance. Amylase gene replication is a very common phenomenon in insects, and different copies of amylase genes enable changes in its location and function. In addition, the classification, structure, and interaction between insect amylase inhibitors and amylases have also invoked the attention of researchers. Some plant-derived amylase inhibitors have inhibitory activities against insect amylases and even mammalian amylases. In recent years, an increasing number of studies have clarified the effects of pesticides on the amylase activity of target and non-target pests, which provides a theoretical basis for exploring safe and efficient pesticides, while the exact lethal mechanisms and safety in field applications remain unclear. Here, we summarize the most recent advances in insect amylase studies, including its sequence and characteristics and the regulation of amylase inhibitors (α-AIs). Importantly, the application of amylases as the nanocide trigger, RNAi, or other kinds of pesticide targets will be discussed. A comprehensive foundation will be provided for applying insect amylases to the development of new-generation insect management tools and improving the specificity, stability, and safety of pesticides.