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Abstract Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data. The annotation process is not only costly but also demands substantial time from clinical specialists. Addressing this issue, we introduce the S4MI (Self-Supervision and Semi-Supervision for Medical Imaging) pipeline, a novel approach that leverages advancements in self-supervised and semi-supervised learning. These techniques engage in auxiliary tasks that do not require labeling, thus simplifying the scaling of machine supervision compared to fully-supervised methods. Our study benchmarks these techniques on three distinct medical imaging datasets to evaluate their effectiveness in classification and segmentation tasks. Notably, we observed that self-supervised learning significantly surpassed the performance of supervised methods in the classification of all evaluated datasets. Remarkably, the semi-supervised approach demonstrated superior outcomes in segmentation, outperforming fully-supervised methods while using 50% fewer labels across all datasets. In line with our commitment to contributing to the scientific community, we have made the S4MI code openly accessible, allowing for broader application and further development of these methods. The code can be accessed at https://github.com/pranavsinghps1/S4MI .

BackgroundLung cancer is the foremost cause of cancer-related death globally, with non-small cell lung cancer (NSCLC) accounting for 85–90% of cases. Targeted therapy is the most essential therapeutic option for NSCLC, other common treatments include radiation therapy, surgery, chemotherapy, and immunotherapy.ObjectiveOur study objective was to estimate whether progression-free survival (PFS) is an outcome of NSCLC extracted from 18 randomized control trials (RCTs) with docetaxel as experimental group and antineoplastic agent, kinase inhibitor, and monoclonal antibodies as a control group.MethodsWe selected relevant studies published between 2011 and 2022 using Google Scholar, PubMed, Scopus, Science Direct, and Cochrane Library. Advanced NSCLC, chemotherapy, RCT, docetaxel, and second-line treatment were the terms included in the search. A total of 9738 patients were evaluated from the 18 identified studies. We used the meta package of R Studio to perform the meta-analysis. Graphical funnel plots were used to evaluate publication bias visually.ResultsPatients who underwent docetaxel-based therapy had a considerably longer PFS than those who got antineoplastic agents, kinase inhibitors, or monoclonal antibodies-based treatment. Patients in the standard treatment arm had a slightly longer PFS than those in the experimental therapy arm in the overall meta-analysis.ConclusionDocetaxel outperformed monoclonal antibodies, antineoplastic agents, and kinase inhibitors in the second-line therapy of advanced NSCLC since PFS was extensively utilized.

The main reason for an increase in cartelisation can be attributed to the liberalisation of the economy in India resulting in de-regulation and empowering the enterprises to be at the helm of their affairs. Cartelisation as per UNCTAD impedes healthy competition by fixing prices and restricting supply. The paper gains significance as India aspires to provide housing to all by 2022 but the COVID-19 pandemic coupled with the issue of cartelisation has worsened the situation. The boom in the Corporate Real Estate sector has been coupled with an increase in the anti-competitive practices prevailing in this sector and has negatively impacted the economy. The paper has analysed the provisions in the Indian legal regime as well the legal regimes of the USA and UK regarding cartelization. The Indian regime falls short on various counts when compared with the law of developed nations like the USA and UK, which must be tackled on a war footing. The sector has the potential of opening up numerous opportunities including providing jobs to the Indian youth. The paper aims at providing relevant suggestions in that regard, including the need for whistleblower protection and to have a Cement Regulatory Authority among other things that might prove helpful for the legislators aiming to attract 100 lakh crores in the infrastructure sector in the next five years.

Bacterial infections are one of the leading causes of morbidity, mortality, and healthcare complications in patients. Leptospirosis is found to be the most prevalent, re-emergent, and neglected tropical zoonotic disease worldwide. The adaptation to various environmental conditions has made Leptospira acquire a large genome (~4.6 Mb) and a complex outer membrane, making it unique among bacteria that mimic the symptoms of jaundice and hemorrhage. Sph2 is another important virulence factor that enhances hemolytic sphingomyelinase—capable of moving inside mitochondria—which increases the ROS level and decreases the mitochondrial membrane potential, thereby leading to cell apoptosis. In the present study, 25 suspected bovine serum samples were subjected to the Microscopic Agglutination Test (MAT) across the Mysuru region. Different samples, such as urine, serum, and aborted materials from the confirmed MAT-positive animals, were used for isolation and genomic detection by conventional PCR targeting virulence gene, Lipl32, using specific primers. Further, in vitro and in silico studies were performed on isolated cultures to assess the anti-leptospiral, anti-hemolytic, and sphingomyelinase enzyme inhibition using novel pseudopeptides. The microdilution technique (MDT) and dark field microscope (DFM) assays revealed that at a concentration of 62.5 μg/mL, the pseudopeptide inhibited 100% of the growth of Leptospira spp., suggesting its efficiency in the treatment of leptospirosis. The flow cytometry analyses show the potency of the pseudopeptide against sphingomyelinase enzymes using human umbilical vein endothelial cells (HUVECs). Thus, the present study demonstrated the efficacy of the pseudopeptide in the inhibition of the growth of Leptospira, and therefore, this can be used as an alternative drug for the treatment of leptospirosis.

A comparative study on the morphometric and meristic variables of Barilius bendelisis (Ham.) from two different water bodies, i.e., Khanda Gad, a perennial spring fed stream and fish pond in the Garhwal Himalayan region of Uttarakhand was made during the present study. A total of 100 specimens were analysed for 26 different morphometric variables and 14 meristic counts. The majority of morphometric variables showed linear relationship when expressed in relation to total length and head length, whereas meristic counts remained constant with increasing body length. Standard length was found to be the highly correlated character in samples from both sites. Principal Component Analysis of 10 significant morphometric variables yielded three components accounting for 73.38% of the total variation. Principal Component Analysis of 3 meristic variables yielded single component accounting for 62.3% of total variation. Discriminant Function Analysis for morphometric and meristic variables showed that 98% and 83% of individuals were allocated into their original populations respectively. The cluster analysis for morphometric characters showed of fish populations from both sites formed two major clades, thus significantly differentiating the two stocks of fish population.

The present work describes the chemical preparation of Schiff bases derived from 4,4′-diaminodiphenyl sulfone (L1–L5) and their Co(II) metal complexes. The evaluation of antimicrobial and anticancer activities against MCF-7 cell line and human lung cancer cell line A-549 was performed. The aforementioned synthesized compounds are characterized by spectroscopic techniques and elemental analysis confirms successful synthesis. The results from the above analytical techniques revealed that the complexes are in an octahedral geometry. The antimicrobial activity of the synthesized Schiff base ligands and their metal complexes under study was carried out by using the agar well diffusion method. The ligand and complex interactions for biological targets were predicted using molecular docking and high binding affinities. Further, the anticancer properties of the synthesized compounds are performed against the MCF-7 cell line and human lung cancer cell line A-549 using adriamycin as the standard drug.