Utilizing deep learning via the 3D U-net neural network for the delineation of brain stroke lesions in MRI image

The segmentation of acute stroke lesions plays a vital role in healthcare by assisting doctors in making prompt and well-informed treatment choices. Although Magnetic Resonance Imaging (MRI) is a time-intensive procedure, it produces high-fidelity images widely regarded as the most reliable diagnostic tool available. Employing deep learning techniques for automated stroke lesion segmentation can offer valuable insights into the precise location and extent of affected tissue, enabling medical professionals to effectively evaluate treatment risks and make informed assessments. In this research, a deep learning approach is introduced for segmenting acute and sub-acute stroke lesions from MRI images. To enhance feature learning through brain hemisphere symmetry, pre-processing techniques are applied to the data. To tackle the class imbalance challenge, we employed a strategy of using small patches with balanced sampling during training, along with a dynamically weighted loss function that incorporates f1-score and IOU-score (Intersection over Union). Furthermore, the 3D U-Net architecture is used to generate predictions for complete patches, employing a high degree of overlap between patches to minimize the requirement for subsequent post-processing steps. The 3D U-Net model, utilizing ResnetV2 as the pre-trained encoder for IOU-score and Seresnext101 for f1-score, stands as the leading state-of-the-art (SOTA) model for segmentation tasks. However, recent research has introduced a novel model that surpasses these metrics and demonstrates superior performance compared to other backbone architectures. The f1-score and IOU-score were computed for various backbones, with Seresnext101 achieving the highest f1-score and ResnetV2 performing the highest IOU-score. These calculations were conducted using a threshold value of 0.5. This research proposes a valuable model based on transfer learning for the classification of brain diseases in MRI scans. The achieved f1-score using the recommended classifiers demonstrates the effectiveness of the approach employed in this study. The findings indicate that Seresnext101 attains the highest f1-score of 0.94226, while ResnetV2 achieves the best IOU-score of 0.88342, making it the preferred architecture for segmentation methods. Furthermore, the study presents experimental results of the 3D U-Net model applied to brain stroke lesion segmentation, suggesting prospects for researchers interested in segmenting brain strokes and enhancing 3D U-Net models.

Medical plants for lung cancer: an overview of current knowledge

Lung cancer is an uncontrolled cell growth in lung tissue, with changes in the cellular, epigenetic and genetic alterations, oncogenes activation and clonal evolution of malignant cells. The most critical risk factor for lung cancer is cigarette smoking (80-85%). Other reasons for lung cancer (15-20%) include genetic factors, exposure to secondhand smoke, air pollution, radiation, hazardous gases and foreign chemical agents. The most widely used strategies in lung cancer treatment are chemotherapy, radiotherapy and surgery. However, there are various adverse effects, such as significant toxicity, limited efficiency and multidrug resistance. Plants and plant-derived products have proven to have a role in lung cancer therapy and prevention through sensitizing conventional factors, extending patient survival time, avoiding adverse effects of chemotherapy, promoting physiological improvement and ameliorating quality of life in pulmonary malignancy cases. For this review article, we searched Web of Science, EBSCO, Scopus, PubMed/Medline, DOAJ (Directory of Open Access Journals), Embase, and Google Scholar, using various keywords. There are several natural product molecules with anticancer properties through many molecular mechanisms, including, inducing apoptosis, inhibition of angiogenesis and metastasis, reversion of multidrug resistance and also targeting reactive oxygen species signaling. Some phytochemical compounds are discussed as anticancer agents for lung cancer.

Optical vortex beam controlling based on fork grating stored in a dye-doped liquid crystal cell

In this paper, we investigate the generation and controlling of the optical vortex beam using a dye-doped liquid crystal (DDLC) cell. The spatial distribution of the quasi-sinusoidal orientation of the liquid crystal molecules creates a quasi-sinusoidal phase grating (PG) in the DDLC cell. Depending on the incident light pattern, Trans to Cis photoisomerization of the dye molecules affects the orientation of the liquid crystal molecules. To do so, an amplitude fork grating (FG) is used as a mask, and its pattern is stored in the cell by a pattern printing method as the PG. One of the particular features of the stored grating in the cell is its capability in the diffraction efficiency controlled by the applied electric field. The results show, based on the central defect in the FG pattern, the diffracted probe beam in different orders is optical vortices. As a new technique, this type of stored pattern acts like an amplitude grating but according to the results, its structure is in fact a PG. This technique leads to the vortex beam switching capability by applying an electric field to the cell. The results show that by applying 22 V, all the diffraction orders vanish. Meanwhile, the vortex beams reappear by removing the applied voltage. The diffraction efficiency of the vortex beams as well as its generation dependency on the polarization of the incident beam studied. The maximum efficiency of the first diffraction order for linear polarized incident beam was obtained at 0 V, about 8%. Based on the presented theory, a simulation has been done which shows the Cis form of the dye molecules has been able to change the angle of LC molecules on average about 12.7°. The study of diffracted beam profiles proves that they are electrically controllable vortex beams.

Comparison of prevalence rates of restless legs syndrome, self-assessed risks of obstructive sleep apnea, and daytime sleepiness among patients with multiple sclerosis (MS), clinically isolated syndrome (CIS) and Neuromyelitis Optica Spectrum Disorder (NMOSD)

BACKGROUND

Prevalence rates for restless legs syndrome (RLS) and risk of Obstructive Sleep Apnea (OSA) in individuals with Neuromyelitis Optica Spectrum Disorder (NMOSD) and Clinically Isolated Syndrome (CIS) are unknown. The aims of the present study were to assess symptoms of RLS and self-assessed risks of OSA in individuals with NMOSD and CIS, to compare these prevalence rates with those of persons with multiple sclerosis (MS), and to associate RLS and OSA with expanded disability status scale (EDSS) scores, daytime sleepiness, fatigue, paresthesia, and medication.

METHODS

A total of 495 individuals (mean age = 34.92 years, 84.9% females) were assessed. Of these, 24 had NMOSD, 112 had CIS and 359 had MS. Trained neurologists ascertained individuals' neurological diagnoses, assessed their EDSS scores, and conducted a clinical interview to assess RLS. Additionally, participants completed questionnaires covering sociodemographic information, risks of snoring and OSA, daytime sleepiness, fatigue, paresthesia and medication.

RESULTS

Prevalence rates of RLS were 45.8% in NMOSD, 41.1% in CIS, and 28.7% in MS. Prevalence rates of self-assessed risks of OSA were 8.3% in NMOSD, 7.7% in CIS, and 7.8% in MS; these rates were not significantly different. Across the entire sample and within the diagnostic groups, RLS and OSA scores were unrelated to EDSS, daytime sleepiness, fatigue or medication.

CONCLUSIONS

Individuals with NMOSD, CIS and MS have high prevalence rates for RLS and self-assessed risks of obstructive sleep apnea syndrome (OSAS), which are unrelated to EDSS, daytime sleepiness, fatigue, paresthesia, or medication. Sleep issues should be monitored during routine check-ups for individuals with NMOSD and CIS.

Decreased serum levels of interleukin-35 among multiple sclerosis patients may be related to disease progression

The regulatory role of interleukin (IL) -35 in the immunopathogenesis of multiple sclerosis (MS) is suggested in very few studies. We aimed to measure serum levels of IL-35 among clinically isolated syndrome (CIS) and relapsing-remitting MS (RRMS) patients and evaluate the associations between this cytokine and the disease clinical course. This cross-sectional study was conducted during 2017 in a referral university clinic. Forty patients and 40 healthy controls were included in the study. The level of IL-35 in the serum of all subjects was determined by ELISA. Serum level of IL-35 was reduced (p = 0.003) in RRMS in comparison with healthy controls. Moreover, the mean serum level of IL-35 among new cases (diagnosed within the 6 months prior to the study) decreased compared to healthy controls but it was not statistically significant (P=0.059). The mean serum level of IL-35 was significantly higher in new cases compared with other cases (p=0.048). Overall, we found decreased serum level of IL-35 among RRMS patients compared to the healthy controls. Our finding provides a view of the possible role of IL-35 in MS pathogenesis and the potential therapeutic targets.

Biological and molecular characterization of lettuce mosaic virus from Tehran province in Iran

In this study, lettuce samples having LMV infection symptoms were collected from Tehran fields during 2003. Samples tested for LMV infection by immuno printing. Three positive samples in immuno printing collected and their characteristics were determined. In mechanical inoculation, these Isolates produced symptoms on Chenopodium quinoa, C. amaranticolor, Gomphrena globosa, Nicotiana benthamiana, Lactuca sativa cv. Mantilia and cv. Terocadero (which contains the mol1 resistance gene and susceptible respectively), but not cv. Salinas 88 (which contains the mol2 resistance gene). LMV was purified and LMV polyclonal antiserum was produced in rabbit by a series of intravenous and intramuscular injections, the precipitin titre of this antiserum was 1:1024. Gel double diffusion test (GDDT) was performed, and precipitin bands appeared. SDS-PAGE and western blotting showed the presence of coat protein 29 kDa. In IC-RT-PCR with on LMV specific primer pair, an approximately 1300 bp fragment was amplified.

Occurrence and distribution of lettuce mosaic disease in Tehran province from Iran

Lettuce mosaic virus (LMV) Cucumber mosaic virus (CMV) and Tomato spotted wilt virus (TSWV) were identified in fields of Tehran province. In this study 452 leaf samples were collected from the fields throughout the Tehran province during 2002 and 2003. Distribution of Lettuce mosaic virus (LMV), Cucumber mosaic virus (CMV), Tomato spotted wilt virus (TSWV)and Arabis mosaic virus (ArMV) was determined with DAS-ELISA. Percentage of single Infection to LMV. CMV or TSWV was 20.58, 15.93 and 9.96% respectively. Also 15.28% of samples were co- infected with LMV+CMV, 8.19% with LMV+TSMV and 7.74% with CMV+TSWV. 4.65% of samples were Infected to all of these three viruses. LMV was found in 48.69%, CMV in 43.59% and TSWV in 30.54% of samples totally. Therefore LMV is major dominant agent of lettuce mosaic disease in Tehran province. This is the first report of occurrence of TSWV on lettuce in Iran and first report of CMV and LMV in Tehran province.

Detection of fungal infectous agent of wheat grains in store-pits of Markazi province, Iran

Wheat is an economic and important crop that provides approximately 20% of food calorie in the world. It is first crop in Iran and cultivated in the most areas of this country. Store-pit fungi make undesirable changes in quality and appearance of wheat grains. Even, some fungi produce different mycotoxins which are toxic to human and livestock's that use wheat grains as source of food. In this study, several samples were randomly collected from each of five store-pits located in different areas of Markazi Province including: Arak, Mahallat, Khomein, Saveh and Sarband. Grains were treated on PDA, and blotter, agar and washing test also used for isolating and detection of fungi. At least 100 grains per each sample were randomly used for each test and treatment. The fungi that determined in this study were Cochliobolus australiensis, Cladosporium herbarum, Epicoccum sp., Tilletia leavis, Aspergillus flavus, A. niger, A. fumigatus, Alternaria alternata, Alternaria sp., Penicillium italicum, P. digitatum, Fusarium sp., Rhizopus sp., Ustilago tritici, Scytalidium sp. Among these fungi the most isolates were belonged to Cladosporium, Alternaria, Rhizopus and Fusarium. Cladosporium herbarum was the most common in different sampling areas. Tilletia laevis and Ustilago tritici were just recovered in washing test. This study revealed that different fungi are associated with wheat grains in store-pits in Markazi Province. Some of them like Aspergillus flavus normally produce aflatoxin, a very toxic and carcinogenic mycotoxin that is harmful for human.