Microbiota of spent nuclear fuel pool water with emphasis on their biofilm forming ability on stainless steel (SS-304L) Abstract Spent nuclear fuel (SNF) pool is an essential unit of a nuclear power plant infrastructure, where radioactive fuel rods are kept for cooling and shielding, before reprocessing. This study explored the presence of bacteria in SNF pool water with emphasis on their capability to form biofilms on pool wall cladding material stainless steel (SS-304L). Bacteria were isolated from SNF pool water and were characterized using 16S rRNA gene sequencing. The six bacterial isolates (Bacillus subtilis, Staphylococcus sps., S. arlettae, S. epidermidis, S. auricularis and Chryseobacterium gleum) can grow and form biofilms at very low nutrient condition as well as in chronic radioactivity. The bacterial isolates formed biofilm on SS-304L and glass. However, the biofilm parameters assessed by CLSM microscopy showed that the strains preferred SS-304L surface for biofilm formation. On SS-304L, the maximum biomass (0.45 µm3/µm2) was formed by S. arlettae when compared to maximum biomass (0.054 µm3/µm2) by Staphylococcus sp., on glass. Maximum biofilm thickness on SS-304L was observed by Staphylococcus sp. (8.81 µm) when compared to that of S. epidermidis (4.16 µm) on the glass surface. The biofilm formation on SS-304L surface suggests the possible risk of microbial-induced corrosion of SNF pool cladding material. This study highlights the need for mandatory monitoring of microbial biofilm formation in an extreme environment such as SNF pool.

Genetic relatedness and its causal role in the evolution of insect societies Abstract The role of genetic relatedness in social evolution has recently come under critical attention. These arguments are here critically analyzed, both theoretically and empirically. It is argued that when the conceptual structure of the theory of natural selection is carefully taken into account, genetic relatedness can be seen to play an indispensable role in the evolution of both facultative and advanced eusociality. Although reviewing the empirical evidence concerning the evolution of eusociality reveals that relatedness does not play a role in the initial appearance of helper phenotypes, this follows simply from the fact that natural selection – of which relatedness is a necessary component – does not play a causal role in the origin of any traits. Further, separating two logically distinct elements of causal explanation – necessity and sufficiency – explains why the debate lingers on: although relatedness plays a necessary role in the evolution of helping and advanced eusociality, relatedness alone is not sufficient for their appearance. Therefore, if the relatedness variable in a given data set is held at a uniformly high value, then it indeed may turn out that other factors occupy a more prominent role. However, this does not change the fact that high relatedness functions as a necessary background condition for the evolution of advanced eusociality.

Deconstructing age reprogramming Abstract It has been proposed that age reprogramming enables old cells to be rejuvenated without passage through an embryonic stage (Singh and Zacouto in J Biosci 35:315–319, 2010). As such, age reprogramming stands apart from the induced pluripotent stem (iPS) and nuclear transfer-embryonic stem (NT-ES) cell therapies where histo-compatible cells are produced only after passage through an embryonic stage. It avoids many of the disadvantages associated with iPS and NT-ES cell therapies. Experimental evidence in support of age reprogramming is burgeoning. Here, we discuss possible new approaches to enhance age reprogramming, which will have considerable benefits for regenerative therapies.

Machine-learning techniques for the prediction of protein–protein interactions Abstract Protein–protein interactions (PPIs) are important for the study of protein functions and pathways involved in different biological processes, as well as for understanding the cause and progression of diseases. Several high-throughput experimental techniques have been employed for the identification of PPIs in a few model organisms, but still, there is a huge gap in identifying all possible binary PPIs in an organism. Therefore, PPI prediction using machine-learning algorithms has been used in conjunction with experimental methods for discovery of novel protein interactions. The two most popular supervised machine-learning techniques used in the prediction of PPIs are support vector machines and random forest classifiers. Bayesian-probabilistic inference has also been used but mainly for the scoring of high-throughput PPI dataset confidence measures. Recently, deep-learning algorithms have been used for sequence-based prediction of PPIs. Several clustering methods such as hierarchical and k-means are useful as unsupervised machine-learning algorithms for the prediction of interacting protein pairs without explicit data labelling. In summary, machine-learning techniques have been widely used for the prediction of PPIs thus allowing experimental researchers to study cellular PPI networks.

Biosensor design using an electroactive label-based aptamer to detect bisphenol A in serum samples Abstract A new and simple procedure was applied to detect bisphenol A (BPA) based on a BPA aptamer and its complementary strand (Comp. Str.). An electrode was modified with a mixture of carboxylated multiwalled carbon nanotubes and chitosan. The Comp. Str. was immobilized on a modified-glassy carbon electrode (GCE) surface via covalent binding. After the incubation of the aptamer with the electrode surface, it could interact with the Comp. Str. In the presence of BPA, its aptamer will interact with the analyte, resulting in some changes in the configuration and leading to separation from the electrode surface. Due to the attached ferrocene (Fc) group on the 5′ head of the aptamer, the redox current of Fc has reduced. This aptasensor can sense the level of BPA in the linear range of 0.2–2 nM, with a limit of detection of 0.38 nM and a sensitivity of 24.51 μA/nM. The proposed aptasensor showed great reliability and selectivity. The acceptable selectivity is due to the specificity of BPA binding to its aptamer. The serum sample was used as a real sample; the aptasensor was able to effectively recover the spiked BPA amounts. It can on-site monitor the BPA in serum samples with acceptable recoveries.

Correction to: Development of typological classification and its relationship to microdifferentiation in ethnic India In the July 2019 issue of the Journal of Biosciences.

Down-regulation effects of IFN-α on p11, 5-htr1b and 5-HTR4 protein levels were affected by NH 4 CL or MG132 treatment in SH-sy5y cells Abstract In previous studies, we found interferon-α (IFN-α) could reduce protein levels of p11, 5-hydroxytryptamine receptor 1b (5-HT1b) and 5-hydroxytryptamine receptor 4 (5-HT4), but does not influence their messenger RNA levels in SH-sy5y cells. Thus, we investigated the post-transcriptional modulation of these molecules by IFN-α. SH-sy5y cells were treated with IFN-α, NH4Cl or MG132 alone or in combination, and then the protein levels of p11, 5-HT1b and 5-HT4 were analyzed by western blots. The regulatory effects of p11 on 5-HT1b and 5-HT4 were also determined in p11 knock-down cells. NH4Cl but not MG132 could reverse the protein level of p11 in IFN-α-treated SH-sy5y cells. MG132 could recover the protein levels of 5-HT1b and 5-HT4 in p11 knock-down cells. The down-regulation effects of IFN-α on p11, 5-HT1b and 5-HT4 were associated with the lysosome and ubiquitin–proteasome-mediated pathways. p11 was identified as a potent regulator to modulate the ubiquitination of 5-HT1b and 5-HT4. Therefore, it could be potential target therapies in IFN-α-induced depression.

Does cartilage ERα overexpression correlate with osteoarthritic chondrosenescence? Indications from Labisia pumila OA mitigation Abstract Chondrosenescence (chondrocyte senescence) and subchondral bone deterioration in osteoarthritic rats were analyzed after treatment with the estrogenic herb Labisia pumila (LP) or diclofenac. Osteoarthritis (OA) was induced in bilaterally ovariectomized (OVX) rats by injecting mono-iodoacetate into the right knee joints. Rats were grouped (n = 8) into non-treated OVX+OA control, OVX+OA + diclofenac (5 mg/kg) (positive control), OVX+OA + LP leaf extract (150 and 300 mg/kg) and healthy sham control. After 8 weeks’ treatment, their conditions were evaluated via serum biomarkers, knee joint histology, bone histomorphometry, protein and mRNA expressions. The LP significantly reduced cartilage erosion, femur bone surface alteration, bone loss and porosity and increased trabecular bone thickness better than diclofenac and the non-treated OA. The cartilage catabolic markers’ (matrix metalloproteinase (MMP)-13, RUNX2, COL10α, ERα, CASP3 and HIF-2α) mRNA expressions were down-regulated and serum bone formation marker, PINP, was increased by LP in a dose-dependent manner. The LP (containing myricetin and gallic acid) showed protection against chondrosenescence, chondrocyte death, hypoxia-induced cartilage catabolism and subchondral bone deterioration. The bone and cartilage protective effects were by suppressing proteases (collagen break-down), bone resorption and upregulating subchondral bone restoration. The cartilage ERα over-expression showed a strong positive correlation with MMP-13, COL10α1, histological, micro-computed tomography evidence for cartilage degradation and chondrosenescence.

miR-425-5p suppresses tumorigenesis and DDP resistance in human-prostate cancer by targeting GSK3β and inactivating the Wnt/β-catenin signaling pathway Abstract Prostate cancer (PCa) represents the most frequently diagnosed cancer in men. Cisplatin, also known as cis-diamminedichloroplatinum (DDP), is a standard chemotherapeutic agent used to treat PCa, and DDP resistance remains one important obstacle in DDP-based chemotherapy. In our research, we found miR-425-5p was down-regulated in PCa and even lower in DDP-resistant PCa determined by quantitative polymerase chain reaction; in contrast, GSK3β mRNA expression was upregulated in PCa and even higher in DDP-resistant PCa. Moreover, there was a modest but significant inverse correlation between the expression of GSK3β mRNA and miR-425-5p. Functional experiments showed that miR-425-5p mimic inhibited DDP resistance as evidenced by a promoted apoptosis rate (flow cytometry) and suppressed cell viability (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay) and expressions of MDR1 and MRP1 (western blotting) in DU145/DDP and PC3/DDP cells. Luciferase reporter assay and RNA immunoprecipitation identified GSK3β was a potential target of miR-425-5p. The effect of miR-425-5p mimic on DDP resistance was partially reversed by pcDNA-GSK3β. Mechanically, miR-425-5p mimic reduced expression of β-catenin, cyclin D1 and C-myc, which was further blocked when GSK3β overexpressed. In vivo experiments, recovery of GSK3β prevented xenograft tumor growth and DDP resistance in the presence of miR-425-5p mimic. To sum up, miR-425-5p upregulation might sensitize human PCa to DDP by targeting GSK3β and inactivating the Wnt/β-catenin signaling pathway.

Impact of Pseudomonas putida RRF3 on the root transcriptome of rice plants: Insights into defense response, secondary metabolism and root exudation Abstract Pseudomonas putida is widely used as a biocontrol agent, however, mechanisms by which it initiates the plants’ defense response remains obscure. To gain an insight into the molecular changes that occur in plants upon plant growth-promoting rhizobacteria colonization, root transcriptome analysis by using a microarray was performed in rice using P. putida RRF3 (a rice rhizosphere isolate). Data analysis revealed a differential regulation of 61 transcripts (48 h post-treatment), of which, majority corresponded to defense response, cell wall modification and secondary metabolism. Seven genes encoding salicylic acid (SA) responsive pathogenesis-related proteins were up-regulated significantly (fold change ranges from 1 to 4), which suggests that RRF3 has a profound impact on a SA-mediated defense signaling mechanism in rice. Investigations performed at later stages of RRF3 colonization by real-time polymerase chain reaction and high-performance liquid chromatography (HPLC) analysis confirmed the above results, demonstrating RRF3 as a potent biocontrol agent. Further, the impact of RRF3 colonization on root exudation, in particular, exudation of SA was investigated by HPLC. However, analysis revealed RRF3 to have a negative impact on root exudation of SA. Overall, this study shows that P. putida RRF3 immunizes the rice plants by re-organizing the root transcriptome to stimulate plant defense responses (‘priming’), and simultaneously protects itself from the primed plants by altering the rhizosphere chemical constituents.