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Abstract Diarrhea caused by Shigella has been associated with high morbidity and mortality in young children worldwide. There are no licensed vaccines, and those clinically advanced have restricted coverage as they elicit serotype-specific immunity while disease is caused by multiple circulating serotypes. Our group had previously reported a close association between serum antibodies to the Shigella virulence factor VirG (or IcsA) and clinical protection in infected individuals. VirG is highly conserved among Shigella strains and appealing as a broad-spectrum vaccine candidate. In this study, we investigated the immunogenicity and protective capacity of VirG as a subunit vaccine in mice. The surface-exposed alpha (α) domain of VirG (VirGα) was produced as a recombinant protein. This region has almost identical immune reactivity to full-length VirG. Administered intramuscularly with alum, VirGα elicited robust immune responses and high protective efficacy against S. flexneri 2a and S. sonnei. Almost complete protection was afforded by VirGα given intranasally with the E. coli double mutant heat-labile toxin (dmLT). VirGα-specific antibodies recognized VirG expressed on live Shigella, and blocked Shigella adhesion and invasion to human colonic cells. These results show for the first time that VirGα is a promising cross-protective vaccine candidate to prevent Shigella infection.

In the title compound, C26H31NO6S, the five-membered pyrrolidine ring adopts an envelope conformation and the six-membered thiazine ring is in a distorted chair conformation. The crystal packing is stabilized through an intermolecular C—H...O interaction, generating inversion-related R22(10) ring motifs.

In the title salt, C11H14N3O+·C7H5O3−, the phenyl ring of the cation is oriented at an angle of 67.0 (1)° with respect to the five-membered pyrazolone ring. The carboxylate plane of the anion is twisted out from the plane of the aromatic ring at an angle of 13.7 (3)°. In the crystal, the cations form hydrogen-bonded dimers with an R22(10) ring motif. The salicylate anion has an intramolecular O—H...O hydrogen bond.

Purpose: To compare the slit-lamp method and wavefront aberrometry method based on outcomes of toric realignment surgeries. Settings: Tertiary care ophthalmic hospital. Design: Retrospective study. Methods: This study included all eyes undergoing toric intraocular lens (TIOL) realignment surgery between January 2019 and December 2021 for which TIOL axis assessment by slit-lamp method and wavefront aberrometry method was available. Data were retrieved from electronic medical records, and we documented demographics, uncorrected visual acuity (UCVA), subjective refraction, and TIOL axis by slit-lamp and wavefront aberrometry methods on postoperative day 1 and day 14. In patients with misalignment, TIOL was realigned to the original position in group 1 (27 patients) and to an axis based on calculations provided by wavefront aberrometer in group 2 (25 patients). Post-realignment surgery, UCVA, subjective refraction, and TIOL axis by slit-lamp and wavefront aberrometry methods were assessed and analyzed. Results: We analyzed 52 eyes and found that the mean preoperative misalignment with the slit-lamp method (44.9° ±20.0°) and wavefront aberrometry (47.1° ±19.5°) was similar. The corresponding degrees of misalignment post-TIOL repositioning surgeries were 5.2° ±5.2° (slit-lamp method) and 4.7° ±5.1° (wavefront aberrometry) (P = 0.615). Both groups showed significant improvement in median log of minimum angle of resolution (logMAR) UCVA and reduction in median refractive cylinder. Conclusions: Slit-lamp method is as good as wavefront aberrometer method to assess TIOL axis. Toric realignment surgery is found to be safe, and realigning TIOL based on either slit-lamp method or wavefront aberrometer method equally improved UCVA and decreased residual refractive cylinder.

The current study deals with the extraction and characterization of natural cellulose fibers from Lycium ferocissimum plant stems. The fibers were retted using a manual retting process and were subjected to benzoylation treatment. The properties namely physio-chemical, thermal, crystalline, and morphological were measured for both untreated and chemical treated Lycium ferocissimum fibers. Then, the epoxy composites were fabricated using chemical treated and untreated Lycium ferocissimum fibers and analyzed for their mechanical performance. The cellulose content was 67.19%, with the crystalline index of 47.7% for the benzoyl chloride treated Lycium ferocissimum fibers, which were substantially higher than untreated Lycium ferocissimum fibers. While the epoxy composites containing benzoyl chloride treated Lycium ferocissimum fibers showed an increase in the ultimate flexural strength of 51.3 MPa, while it was 42 MPa for untreated Lycium ferocissimum fiber-based composite. Thus, the test results elucidated that benzoyl chloride treatment reduced Lycium ferocissimum fibers hydrophilicity that induced fiber wettability with the matrix to better mechanical properties compared to untreated Lycium ferocissimum fiber-based composites.

Purpose: To compare the clinical outcomes of femtosecond laser–assisted cataract surgery (FLACS) versus conventional phacoemulsification (CP) in terms of refractive outcomes, cumulative dissipated energy, and intraoperative complications. Methods: In this retrospective study performed in a tertiary care ophthalmic hospital, we reviewed 2124 eyes that underwent FLACS or CP. Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), cumulative dissipated energy (CDE), and intraoperative complications were analyzed in the study. Results: Out of 2124 eyes, 873 underwent FLACS and 1251 underwent CP. The postoperative mean UCVA after one month was 0.05 ± 0.11 logMAR and 0.14 ± 0.23 logMAR for FLACS and CP, respectively (P < 0.00001). Mean CDVA one month post operation was 0.02 ± 0.07 logMAR and 0.06 ± 0.19 logMAR for FLACS and CP, respectively (P < 0.0001). The CDE for the FLACS group was 6.17 ± 3.86 (P < 0.00001) and it was 9.74 ± 6.02 for the CP group. The intraoperative complication for the FLACS group was 1.60% and the CP group was 2.39% (P < 0.00001). Conclusion: The visual outcomes were better in FLACS compared to CP. The CDE was lower for the FLACS group and FLACS had significantly less intraoperative complications.

A fatty acid alkyl ester can be made from Citrullus Colocynthis oil instead of pure diesel, since it has a higher ratio of triglycerides to monoglycerides. In the current study, the aim of the experimental work was to investigate combustion, emissions, and performance using biodiesel blends derived from Citrullus Colocynthis. A comparison of the qualities of pure Citrullus Colocynthis oil (100% biodiesel), pure diesel (100% diesel), and blended Citrullus Colocynthis and biodiesel (B20, B25, B50, and B75) is presented in the study. The B20 biodiesel blends are the most efficient because of their lower emission concentrations and higher thermal efficiency. Citrullus Colocynthis oil and its blends result in lower in-cylinder pressure and heat release rates. Compared to diesel fuel, a B20 blend performs better and produces less pollution. The test results showed an 18% reduction in HC emissions, a 35% reduction in CO emissions, a 33% reduction in smoke emissions, a 20% reduction in NOx emissions, and a 10% reduction in brake thermal efficiency. [ABSTRACT FROM AUTHOR]

In recent years, finding the optimal solution for image segmentation has become more important in many applications. The whale optimization algorithm (WOA) is a metaheuristic optimization technique that has the advantage of achieving the global optimal solution while also being simple to implement and solving many real-time problems. If the complexity of the problem increases, the WOA may stick to local optima rather than global optima. This could be an issue in obtaining a better optimal solution. For this reason, this paper recommends a hybrid algorithm that is based on a mixture of the WOA and gray wolf optimization (GWO) for segmenting the brain sub regions, such as the gray matter (GM), white matter (WM), ventricle, corpus callosum (CC), and hippocampus (HC). This hybrid mixture consists of two steps, i.e., the WOA and GWO. The proposed method helps in diagnosing Alzheimer’s disease (AD) by segmenting the brain sub regions (SRs) by using a hybrid of the WOA and GWO (H-WOA-GWO, which is represented as HWGO). The segmented region was validated with different measures, and it shows better accuracy results of 92%. Following segmentation, the deep learning classifier was utilized to categorize normal and AD images. The combination of WOA and GWO yields an accuracy of 90%. As a result, it was discovered that the suggested method is a highly successful technique for identifying the ideal solution, and it is paired with a deep learning algorithm for classification.

The present study was undertaken to characterize fowl adenovirus associated with commercial layer grower chicken showed gizzard erosion. Ninety four commercial layer grower chicken flocks from Namakkal districts of Tamil Nadu had shown reduced feed intake, reduced weight gain, uneven growth and mortality of 0.3 to 7.7%. On postmortem examination of affected birds showed mild to severe gizzard erosion, blackish discoloration of gizzard contents, pale liver and no major lesions were seen in other organs. Total DNA was extracted and 897 bp fowl adenovirus specific hexon gene was amplified by PCR. Out of 94 flocks screened seven flocks were found positive of fowl adenovirus. Chicken embryo liver cell culture was prepared to isolate field fowl adenovirus from suspected flocks. Concurrent infection of chicken anaemia virus (CAV) was also screened by PCR for 419 bp VP2 gene of CAV and found that all the seven flocks which were PCR positive for FAdV also found positive for CAV. Sequencing and phylogenetic analysis of 897 bp FAdV hexon gene revealed that, it was belonged to FAdV serotypes 2 and 3 of species D.

In machine learning study proposes an ensemble-based strategy for both feature selection and data standardization to enhance model performance and interpretability. To maintain consistency across datasets, it employ average filling and weighted K-means clustering. Weighted K-means assigns distinct values to samples based on their distances to cluster centers, offering a more precise representation of the data distribution. Meanwhile, average filling replaces missing values with the average of corresponding features, ensuring a complete dataset for subsequent analysis. For feature selection, adopt an ensemble approach that combines Random Forest (RF) with Logistic Regression (LR) and ElasticNet. RF captures feature importance through tree-based analysis, while LR and ElasticNet provide additional insights into feature relevance and coefficients. This amalgamation aims to provide a comprehensive understanding of feature importance within the dataset. Principal Component Analysis (PCA) is employed to reduce dataset complexity while preserving key properties, facilitating more effective feature selection. By identifying orthogonal components that best explain data variation, PCA enables efficient representation and feature selection. In the final stage, Support Vector Machines (SVM) are utilized for categorization. SVM, a powerful classification method, establishes strong decision boundaries that optimize the gap between classes. Leveraging the selected features, the SVM model effectively categorizes new instances. [ABSTRACT FROM AUTHOR]