Plasmids are extrachromosomal genetic elements that reside in prokaryotes. The acquisition of plasmids encoding beneficial traits can facilitate short-term survival in harsh environmental conditions or long-term adaptation of new ecological niches. Due to their ability to transfer between cells, plasmids are considered agents of gene transfer. Nonetheless, the frequency of DNA transfer between plasmids and chromosomes remains understudied. Using a novel approach for detection of homologous loci between genome pairs, we uncover gene sharing with the chromosome in 1,974 (66%) plasmids residing in 1,016 (78%) taxonomically diverse isolates. The majority of homologous loci correspond to mobile elements, which may be duplicated in the host chromosomes in tens of copies. Neighboring shared genes often encode similar functional categories, indicating the transfer of multigene functional units. Rare transfer events of antibiotics resistance genes are observed mainly with mobile elements. The frequent erosion of sequence similarity in homologous regions indicates that the transferred DNA is often devoid of function. DNA transfer between plasmids and chromosomes thus generates genetic variation that is akin to workings of endosymbiotic gene transfer in eukaryotic evolution. Our findings imply that plasmid contribution to gene transfer most often corresponds to transfer of the plasmid entity rather than transfer of protein-coding genes between plasmids and chromosomes.

The sensing responses of SARS-CoV-2 spike protein using top-down-fabricated Si-based electrolyte-gated transistors (EGTs) have been investigated. An aptamer was employed as a receptor for the SARS-CoV-2 spike protein. The EGT demonstrated excellent intrinsic characteristics and higher sensitivity in the subthreshold regime compared to the linear regime. The limit of detection (LOD) was achieved as low as 0.94 pg/mL and 20 pg/mL for the current and voltage sensitivity, respectively. To analyze the sensing responses of EGT in detecting the aptamer-SARS-CoV-2 spike protein conjugate, a lumped-capacitive model with the presence of an effective dipole potential and an effective capacitance of the functionalized layer component was employed. The aptamer-functionalized EGT showed high sensitivity even in 10 mM phosphate-buffered saline (PBS) solution. These results suggest that Si-based EGTs are a highly promising method for detecting SARS-CoV-2 spike proteins.

The advent of immunotherapies with biological drugs has revolutionized the treatment of cancers and auto-immune diseases. However, in some patients, the production of anti-drug antibodies (ADAs) hampers the drug efficacy. The concentration of ADAs is typically in the range of 1-10 pm; hence their immunodetection is challenging. ADAs toward Infliximab (IFX), a drug used to treat rheumatoid arthritis and other auto-immune diseases, are focussed. An ambipolar electrolyte-gated transistor (EGT) immunosensor is reported based on a reduced graphene oxide (rGO) channel and IFX bound to the gate electrode as the specific probe. The rGO-EGTs are easy to fabricate and exhibit low voltage operations (≤ 0.3 V), a robust response within 15 min, and ultra-high sensitivity (10 am limit of detection). A multiparametric analysis of the whole rGO-EGT transfer curves based on the type-I generalized extreme value distribution is proposed. It is demonstrated that it allows to selectively quantify ADAs also in the co-presence of its antagonist tumor necrosis factor alpha (TNF-α), the natural circulating target of IFX.

Semiconducting single walled carbon nanotubes (SWCNTs) are promising materials for biosensing applications with electrolyte-gated transistors (EGT). However, to be employed in EGT devices, SWCNTs often require lengthy solution-processing fabrication techniques. Here, we introduce a simple solution-based method that allows fabricating EGT devices from stable dispersions of SWCNTs/bovine serum albumin (BSA) hybrids in water. The dispersion is then deposited on a substrate allowing the formation of a SWCNTs random network as the semiconducting channel. We demonstrate that this methodology allows the fabrication of EGT devices with electric performances that allow their use in biosensing applications. We demonstrate their application for the detection of cortisol in solution, upon gate electrode functionalization with anti-cortisol antibodies. This is a robust and cost-effective methodology that sets the ground for a SWCNT/BSA-based biosensing platform that allows overcoming many limitations of standard SWCNTs biosensor fabrications.

Electrochemotherapy (ECT) is a standard of care in veterinary and human oncology. The treatment induces a well-characterized local immune response which is not able to induce a systemic response. In this retrospective cohort study, we evaluated the addition of gene electrotransfer (GET) of canine IL-2 peritumorally and IL-12 intramuscularly to enhance the immune response. Thirty canine patients with inoperable oral malignant melanoma were included. Ten patients received ECT+GET as the treatment group, while twenty patients received ECT as the control group. Intravenous bleomycin for the ECT was used in both groups. All patients had compromised lymph nodes which were surgically removed. Plasma levels of interleukins, local response rate, overall survival, and progression-free survival were evaluated. The results show that IL-2 and IL-12 expression peaked around days 7-14 after transfection. Both groups showed similar local response rates and overall survival times. However, progression-free survival resulted significantly better in the ECT+GET group, which is a better indicator than overall survival, as it is not influenced by the criterion used for performing euthanasia. We can conclude that the combination of ECT+GET using IL-2 and IL-12 improves treatment outcomes by slowing down tumoral progression in stage III-IV inoperable canine oral malignant melanoma.

With the increasingly severe environmental problems, cleaner production has become one of the necessary means to alleviate the problem. The \"near-zero emission\" technology of thermal power generation is an active attempt of traditional power generation enterprises to further improve the level of clean coal utilization and promote the flue gas emission from conventional management to lean management. The analysis and evaluation of \"near-zero emission\" technology of thermal power generation in China are conducive to enhancing the scientific understanding of the overall situation of air pollution in China and thus further analyzing the current situation and future development path of thermal power emissions. In this paper, the intelligent prediction algorithm is used to predict and evaluate the emission scale of soot, sulfur dioxide, nitrogen oxides, and other air pollutants in China and the thermal power industry in the future, which reflects the urgency of the promotion of \"near-zero emission\" of thermal power from the macro level. In addition, based on Evolutionary Game Theory (EGT) and coevolutionary algorithm, the strategy selection of several virtual power generation groups under different policy conditions is simulated around the promotion of \"near-zero emission\" of thermal power. The results show that the policy subsidy plays an important role in promoting technology popularization.

Smart city imaginaries have emerged in southern cities driven by neoliberal logics in the urban space. Scholarly work in India has continued to engage with sweeping accounts of cities as opposed to detailed empirical studies of local projects. This paper attempts to address this gap through an in-depth ethnographic inquiry of a slum redevelopment project in the city of Bhubaneswar, India. The key objective is to understand the ways in which informal residents adapted to and changed smart city policies in India in recent years. Using an evolutionary lens, and drawing on participant observation; document analysis; and semi-structured interviews, the paper puts forth a descriptive cases that advances the notion that smart cities imaginaries have resulted in abrupt changes in the institutional context while getting entangled itself within the legal system. The paper also demonstrates how smart cities discourses counter-intuitively result in emergent spaces of resistance in the form of counter-hegemonic practices, thus allowing spaces for the evolution of new actors and imaginaries from unfamiliar territories. The paper concludes by discussing that city planning and governance pathways in India risk creating complicated path dependencies and rigid governance future pathways that may amplify conflict.

Previous phylogenomic analyses of diatoms have discovered some plastid-targeted genes apparently coming from green algae. Number of these genes varied from less than a half of EGT-compatible genes to an overwhelming majority, and their presence was treated as an evidence of cryptic green plastid. We have performed such an analysis with a novel weighted approach on an extended dataset of diatom genomes and proteomes. Approximately equal evidence was found for red and green algal origins for diatoms genes. Considering that very similar results were obtained on other secondary photosynthetic groups whose endosymbioses were independent from that of the diatom ancestors, we consider the serial plastid replacements unparsimonious. A better explanation of these data can be provided by the shopping bag model, where a future host switches numerous endosymbionts and acquires some genes from each of them. Eventually the host loses the ability to replace endosymbionts (e.g. through the loss of phagotrophy) and whatever symbiont was present at the moment gets fixed and reduced to an organelle.

New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference data set with a 10-fold cross-validation method. EGT segments cells or colonies with resulting Dice accuracy index measurements above 0.92 for all cross-validation data sets. EGT results has also been visually verified on a much larger data set that includes bright field and Differential Interference Contrast (DIC) images, 16 cell lines and 61 time-sequence data sets, for a total of 17,479 images. This method is implemented as an open-source plugin to ImageJ as well as a standalone executable that can be downloaded from the following link: https://isg.nist.gov/.

Several lines of evidence have shown that the deletion of the ecdysteroid UDP-glucosyltransferase gene (egt) from the nucleopolyhedrovirus (NPV) genome increases the killing speed of host lepidopteran larvae. However, it has not been investigated in detail whether the effects of egt deletion depend on the larval stages of the host insect. In this study, we performed bioassays using 10 continuous larval stages of the 4th- or 5th-instar Bombyx mori larvae and B. mori NPV egt mutants. The fast-killing phenotype was observed in the egt mutants only when the infection process progressed through larval-larval transition. All day-2 4th-instar larvae infected with the egt mutants entered the molting stage and died much earlier than wild-type-infected larvae. Bodies of egt mutant-infected larvae were filled with excessive fluid immediately after head capsule slippage, owing presumably to the degeneration of Malpighian tubules. Fourth- or 5th-instar larvae infected with the egt mutants at early stages of each instar died similarly to those infected with the wild-type virus. Under infection in the middle stages of the 5th-instar, the survival time of egt mutant-infected larvae was significantly longer than that of the wild-type virus-infected larvae. These results clearly show that the effects of egt deletion on killing speed of NPV are largely dependent on the developmental stage of the host larvae infected by the virus.