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Diffuse large B cell lymphomas (DLBCL) are highly aggressive tumors. Their genetic complexity and heterogeneity have hampered the development of novel approaches for precision medicine. Our study aimed to develop a personalized therapy for DLBCL by utilizing the CRISPR/Cas system to induce knockouts (KO) of driver genes, thereby causing cancer cell death while minimizing side effects. We focused on OCI-LY3 cells, modeling DLBCL, and compared them with BJAB cells as controls. Analysis of whole exome sequencing revealed significant mutations in genes like PAX5, CD79B, and MYC in OCI-LY3 cells. CRISPR/Cas9-mediated KO of these genes resulted in reduced cancer cell viability. Subsequent single and dual gRNA targeting of PAX5 mutations inhibited proliferation specifically in OCI-LY3 cells. Moreover, dual gRNA targeting of PAX5 and MYC induced chromosomal rearrangements, reducing cell proliferation substantially. However, targeting single intronic mutations did not affect cell viability, highlighting the importance of disrupting protein function. Targeting multiple mutations simultaneously addresses intra-tumoral heterogeneity, and the transient delivery of CRISPR/Cas9 allows for permanent gene disruption. While challenges such as incomplete editing efficiency and delivery limitations exist, further optimization may enhance therapeutic efficacy. Overall, our findings demonstrate the efficacy of CRISPR/Cas9 in targeting oncogenic mutations, opening avenues for precision medicine in DLBCL treatment.

Genome editing using the CRISPR/Cas system has revolutionized the field of genetic engineering, offering unprecedented opportunities for therapeutic applications in vivo. Despite the numerous ongoing clinical trials focusing on ex vivo genome editing, recent studies emphasize the therapeutic promise of in vivo gene editing using CRISPR/Cas technology. However, it is worth noting that the complete attainment of the inherent capabilities of in vivo therapy in humans is yet to be accomplished. Before the full realization of in vivo therapeutic potential, it is crucial to achieve enhanced specificity in selectively targeting defective cells while minimizing harm to healthy cells. This review examines emerging studies, focusing on CRISPR/Cas-based pre-clinical and clinical trials for innovative therapeutic approaches for a wide range of diseases. Furthermore, we emphasize targeting cancer-specific sequences target in genes associated with tumors, shedding light on the diverse strategies employed in cancer treatment. We highlight the various challenges associated with in vivo CRISPR/Cas-based cancer therapy and explore their prospective clinical translatability and the strategies employed to overcome these obstacles.

A field experiment was carried out for three crop seasons at Sugarcane Research Station, Nayagarh (Odisha) during spring seasons of 2015-16, 2016-17 and 2017-18 to assess the effect of ethrel and gibberellic acid on growth, yield attributing characters, yield and quality of sugarcane (Saccharum sp. complex). Pooled data of three years study indicated that different treatments with plant growth regulators had significant effect on growth, yield and quality parameters of sugarcane. Germination percent of cane buds was the highest in the treatment involving planting of sugarcane setts after overnight soaking in 100 ppm ethrel solution followed by foliar application of gibberellic acid @35 ppm at 90,120 and 150 days after planting (DAP). Other sugarcane growth parameters, viz. number of tillers and plant heights were significantly higher with the application of growth regulators which produced higher number of millable canes (at harvest) than that of other treatments in the test. Overnight soaking of cane setts in 100 ppm ethrel solution followed by foliar application of gibberellic acid @35 ppm at 90,120 and 150 days after planting also produced significantly higher yield parameters, viz. number of millable cane (84.26’ 000 ha-1), cane length (313.6 cm), cane girth (2.94 cm) and single cane weight (1.64 kg) as compared to conventionally planted sugarcane crop. There was no significant influence on juice quality parameters due to various treatments in this study. However, overnight soaking of setts with 100 ppm ethrel solution followed by foliar application of gibberellic acid @ 35 ppm at 90, 120 and 150 days after planting showed comparatively higher values in all the juice quality parameters. Significantly higher cane and sugar yields of 116.14 t/ha and 12.82 t/ha, respectively were obtained with planting of sugarcane after overnight soaking in 100 ppm ethrel solution followed by gibberellic acid spray @ 35 ppm at 90, 120 and 150 days after planting. The above higher yields were attributed mainly to marked improvement in growth and yield attributes in response to application of plant growth regulators. Therefore, it can be concluded that combined application of ethrel and gibberellic acid had the positive effect to improve the growth parameters, yield and quality of sugarcane.

Microfluidic processes, mainly for biological and chemical applications, have expanded rapidly in recent years. While the initial focus was on single units, principally microreactors, technological and economic considerations have caused a shift to integrated microchips in which a number of microdevices function coherently. These integrated devices have many advantages over conventional macro-scale processes. However, the small scale of operation, complexities in the underlying physics and chemistry, and differences in the time constants of the participating units, in the interactions among them and in the outputs of interest make it difficult to design and optimize integrated microprocesses. These aspects are discussed here, current research and applications are reviewed, and possible future directions are considered.

Poly-β-hydroxybutyrate (PHB) is an energy-storage polymer whose properties are similar to those of chemical polymers such as polyethylene and polypropylene. Moreover, PHB is biodegradable, absorbed by human tissues and less energy-consuming than synthetic polymers. Although Ralstonia eutropha is widely used to synthesize PHB, it is inefficient in utilizing glucose and similar sugars. Therefore a co-culture of R. eutropha and Lactobacillus delbrueckii is preferred since the latter can convert glucose to lactate, which R. eutropha can metabolize easily. Tohyama et al. [24] maximized PHB production in a well-mixed fed-batch bioreactor with glucose and (NH4)2SO4 as the primary substrates. Since production-scale bioreactors often deviate from ideal laboratory-scale reactors, a large bioreactor was simulated by means of a dispersion model with the kinetics determined by Tohyama et al. [24] and dispersion set at an optimum Peclet number of 20 [32]. The time-dependent feed rates of the two substrates were determined through a genetic algorithm (GA) to maximize PHB production. This bioreactor produced 22.2% more PHB per liter and 12.8% more cell mass than achieved by Tohyama et al. [24]. These results, and similar observations with other fermentations, indicate the feasibility of enhancing the efficiency of large nonideal bioreactors through GA optimizations.

Large-scale fed-batch fermentations are often subject to noise carried by the feed streams. This noise corrupts the process data and may destabilize the fermentation. So it is important to retrieve clear signals from noisy data. This is done by noise filters. The performances of some commonly used filters have been studied for poly-β-hydroxybutyrate production by Ralstonia eutropha. In simulated experiments, Gaussian noise was added to the flow rates of the carbon and nitrogen substrates. The filters were compared by means of the Lyapunov exponents of the outputs and their closeness to the noise-free performance. Negative exponents indicate a stable fermentation. An auto-associative neural filter performed the best, followed by a combination of a cusum filter and an extended Kalman filter. Butterworth filters were inferior and inadequate.

Mamíferos de tipo nutria han sido señalados en el subcontinente Indio desde hace más de un siglo y medio. Los Enhydriodontini son de lejos los más comunes y tienen un mayor registro fósil que los Lutrini o los Aonychini. En este trabajo describimos e interpretamos dos fósiles procedentes del Pleistoceno de Panchkula y Pipalwala, India. El ejemplar de Panchkula representa una especie de talla grande de Amblomyx (Aonychini), mientras que el ejemplar de Pipalwala representa a un individuo de talla grade de Lutra paleoindica (Lutrini).

Microbioreactors offer many advantages over macro-scale reactors for the screening and cultivation of microbial cultures. However, some weaknesses of microbioreactors are yet to be overcome. Optimum mixing under laminar flow, miniaturized on-line measurements and control, integration of upstream and downstream microdevices with the microbioreactor on a single chip, and adequate mathematical models to optimize the performance are some major issues that need to be resolved. Nevertheless, recent research indicates rapidly growing understanding of these problems and it has presented some promising solutions that have led to useful commercial applications. While specialized reviews have covered specific aspects of microbioprocesses exhaustively, the present article reviews microbioreactors per se in a holistic way, analyzing their functions both in a stand-alone setting and in conjunction with other microdevices. We also consider technological developments arising out of the standard microbioreactor and its possible future ramifications.

Despite its superiority over chemically synthesized petroleum-based polymers, poly-?-hydroxybutyrate (PHB) has been less successful commercially. A prime reason is the low productivity of microbial processes for PHB. High fermentation efficiency requires good modelling and optimization. Neither classical mechanistic models nor the recent cybernetic models have resulted in sufficiently high yields of PHB. So a neural network description has been proposed here. Relative to the other two approaches, neural optimization doubled the maximum PHB concentration in fed-batch fermentation with Ralstonia eutropha, the most commonly employed organism for PHB production, and it consumed less of the substrates. This advantage and their model-free nature make neural networks an attractive technique to enhance PHB productivity.