Blood cellular membrane-coated Au/polydopamine nanoparticle-targeted NIR-II antibacterial therapy.

Bacterial infections are the primary causes of infectious diseases in humans. In recent years, the abuse of antibiotics has led to the widespread enhancement of bacterial resistance. Concerns have been raised about the identification of a common treatment platform for bacterial infections. In this study, a composite nanomaterial was used for near-infrared II (NIR-II) photothermal antibacterial treatment. Red blood cell membrane was peeled and coated onto the surface of the Au/polydopamine nanoparticle-containing aptamer. The composite nanomaterials based on Au/polydopamine exhibit highest photothermal conversion capability. Moreover, these assembled nanoparticles can quickly enter the body's circular system with a specific capability to recognise bacteria. In vivo experiments demonstrated that the composites could kill bacteria from infected blood while significantly reducing the level of bacteria in various organs. Such assemblies offer a paradigm for the treatment of bacterial infections caused by the side effects of antibiotics.

The crosstalk between ferroptosis and anti-tumor immunity in the tumor microenvironment: molecular mechanisms and therapeutic controversy.

The advent of immunotherapy has significantly reshaped the landscape of cancer treatment, greatly enhancing therapeutic outcomes for multiple types of cancer. However, only a small subset of individuals respond to it, underscoring the urgent need for new methods to improve its response rate. Ferroptosis, a recently discovered form of programmed cell death, has emerged as a promising approach for anti-tumor therapy, with targeting ferroptosis to kill tumors seen as a potentially effective strategy. Numerous studies suggest that inducing ferroptosis can synergistically enhance the effects of immunotherapy, paving the way for a promising combined treatment method in the future. Nevertheless, recent research has raised concerns about the potential negative impacts on anti-tumor immunity as a consequence of inducing ferroptosis, leading to conflicting views within the scientific community about the interplay between ferroptosis and anti-tumor immunity, thereby underscoring the necessity of a comprehensive review of the existing literature on this relationship. Previous reviews on ferroptosis have touched on related content, many focusing primarily on the promoting role of ferroptosis on anti-tumor immunity while overlooking recent evidence on the inhibitory effects of ferroptosis on immunity. Others have concentrated solely on discussing related content either from the perspective of cancer cells and ferroptosis or from immune cells and ferroptosis. Given that both cancer cells and immune cells exist in the tumor microenvironment, a one-sided discussion cannot comprehensively summarize this topic. Therefore, from the perspectives of both tumor cells and tumor-infiltrating immune cells, we systematically summarize the current conflicting views on the interplay between ferroptosis and anti-tumor immunity, intending to provide potential explanations and identify the work needed to establish a translational basis for combined ferroptosis-targeted therapy and immunotherapy in treating tumors.

The role of the core microorganisms in the microbial interactions in activated sludge.

In order to gain a deeper understanding of the microbial interactions in wastewater treatment plants (WWTPs) in China and clarify the role of the core community in the microbial interactions in activated sludge (AS), this study used a molecular ecological network approach based on random matrix theory to construct co-occurrence networks of the core microorganisms (CoreN), the whole AS community (WholeN) and the microbial communities without the core microorganisms (OtherN), respectively. It was shown that the WholeN had more complex and tighter connections compared with the OtherN, because of its higher total number of nodes, higher average clustering coefficient, and shorter average geodesic distance. The proportions of positive links in the CoreN, WholeN and OtherN were gradually decreased, indicating that the core microorganisms promoted cooperation between AS microorganisms. Moreover, higher robustness after random removal of 50% of the nodes of the WholeN (0.2836 ± 0.0311) was observed than the robustness of the OtherN (0.1152 ± 0.0263). In addition, the vulnerability of OtherN (0.0514) is significantly higher than WholeN (0.0225). Meanwhile, the average ratio of negative/positive cohesion, was significantly decreased when the core microorganisms were removed. These results demonstrated that core community could strengthen the stability of the ecological network in AS. By discerning the key factors affecting ecological network, AS temperature was observed to have a strong correlation with all three networks. Moreover, pollutants in wastewater shown stronger correlations with the CoreN and WholeN, supporting the point that core community play a critical role in pollutant removal in WWTPs to a certain extent.

Cancer-associated fibroblasts contribute to the immunosuppressive landscape and influence the efficacy of the combination therapy of PD-1 inhibitors and antiangiogenic agents in hepatocellular carcinoma.

BACKGROUND: Chronic inflammation is considered the most critical predisposing factor of hepatocellular carcinoma (HCC), with inflammatory cell heterogeneity, hepatic fibrosis accumulation, and abnormal vascular proliferation as prominent features of the HCC tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) play a key role in HCC TME remodeling. Therefore, the level of abundance of CAFs may significantly affect the prognosis and outcome in HCC patients. METHODS: Unsupervised clustering was performed based on 39 genes related to CAFs in HCC identified by single-cell RNA sequencing data. Patients of bulk RNA were grouped into CAF low abundance cluster and high abundance clusters. Subsequently, prognosis, immune infiltration landscape, metabolism, and treatment response between the two clusters were investigated and validated by immunohistochemistry. RESULTS: Patients in the CAF high cluster had a higher level of inflammatory cell infiltration, a more significant immunosuppressive microenvironment, and a significantly worse prognosis than those in the low cluster. At the metabolic level, the CAF high cluster had lower levels of aerobic oxidation and higher angiogenic scores. Drug treatment response prediction indicated that the CAF high cluster could have a better response to PD-1 inhibitors and conventional chemotherapeutic agents for HCC such as anti-angiogenic drugs, whereas CAF low cluster may be more sensitive to transarterial chemoembolization treatment. CONCLUSIONS: This study not only revealed the TME characteristics of HCC with the difference in CAF abundance but also further confirmed that the combination therapy of PD-1 inhibitors and anti-angiogenic drugs may be more valuable for patients with high CAF abundance.

Artificial intelligence: opportunities and challenges in the clinical applications of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) accounts for 15-20% of all invasive breast cancer subtypes. Owing to its clinical characteristics, such as the lack of effective therapeutic targets, high invasiveness, and high recurrence rate, TNBC is difficult to treat and has a poor prognosis. Currently, with the accumulation of large amounts of medical data and the development of computing technology, artificial intelligence (AI), particularly machine learning, has been applied to various aspects of TNBC research, including early screening, diagnosis, identification of molecular subtypes, personalised treatment, and prediction of prognosis and treatment response. In this review, we discussed the general principles of artificial intelligence, summarised its main applications in the diagnosis and treatment of TNBC, and provided new ideas and theoretical basis for the clinical diagnosis and treatment of TNBC.

Motion-resolved real-time 4D flow MRI with low-rank and subspace modeling.

PURPOSE: To develop a new motion-resolved real-time four-dimensional (4D) flow MRI method, which enables the quantification and visualization of blood flow velocities with three-directional flow encodings and volumetric coverage without electrocardiogram (ECG) synchronization and respiration control. METHODS: An integrated imaging method is presented for real-time 4D flow MRI, which encompasses data acquisition, image reconstruction, and postprocessing. The proposed method features a specialized continuous ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space acquisition scheme, which collects two sets of data (i.e., training data and imaging data) in an interleaved manner. By exploiting strong spatiotemporal correlation of 4D flow data, it reconstructs time-series images from highly-undersampled ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space measurements with a low-rank and subspace model. Through data-binning-based postprocessing, it constructs a five-dimensional dataset (i.e., x-y-z-cardiac-respiratory), from which respiration-dependent flow information is further analyzed. The proposed method was evaluated in aortic flow imaging experiments with ten healthy subjects and two patients with atrial fibrillation. RESULTS: The proposed method achieves 2.4 mm isotropic spatial resolution and 34.4 ms temporal resolution for measuring the blood flow of the aorta. For the healthy subjects, it provides flow measurements in good agreement with those from the conventional 4D flow MRI technique. For the patients with atrial fibrillation, it is able to resolve beat-by-beat pathological flow variations, which cannot be obtained from the conventional technique. The postprocessing further provides respiration-dependent flow information. CONCLUSION: The proposed method enables high-resolution motion-resolved real-time 4D flow imaging without ECG gating and respiration control. It is able to resolve beat-by-beat blood flow variations as well as respiration-dependent flow information.

Progress in the treatment of urethral adenocarcinoma.

BACKGROUND: Urothelial adenocarcinoma (UA) is a rare subtype of primary urothelial carcinoma, which is more common in women and has a poor prognosis. Because of their low incidence, most of the existing literature is based on case reports and there is a lack of comprehensive literature on this type of tumor. PURPOSE: This article provides a comprehensive and systematic review of the epidemiology, pathological types, treatment, and prognosis of UA. Especially in the treatment section, we reviewed the various treatment methods including surgery, radiotherapy, chemotherapy, immunotherapy and molecular targeted therapy. This review aims to provide a theoretical basis for the clinical diagnosis and management of UA. METHODS: We reviewed the relevant literature of UA from Pubmed. CONCLUSION: There is no standard treatment for UA. Multidisciplinary therapy, including surgery, radiotherapy and chemotherapy, is the current trend. Immunotherapy and molecular targeted therapy will also become viable options for the treatment of UA in future.

Recombination, selection, and the evolution of tandem gene arrays.

Multigene families-immunity genes or sensory receptors, for instance-are often subject to diversifying selection. Allelic diversity may be favored not only through balancing or frequency-dependent selection at individual loci but also by associating different alleles in multicopy gene families. Using a combination of analytical calculations and simulations, we explored a population genetic model of epistatic selection and unequal recombination, where a trade-off exists between the benefit of allelic diversity and the cost of copy abundance. Starting from the neutral case, where we showed that gene copy number is Gamma distributed at equilibrium, we derived also the mean and shape of the limiting distribution under selection. Considering a more general model, which includes variable population size and population substructure, we explored by simulations mean fitness and some summary statistics of the copy number distribution. We determined the relative effects of selection, recombination, and demographic parameters in maintaining allelic diversity and shaping the mean fitness of a population. One way to control the variance of copy number is by lowering the rate of unequal recombination. Indeed, when encoding recombination by a rate modifier locus, we observe exactly this prediction. Finally, we analyzed the empirical copy number distribution of 3 genes in human and estimated recombination and selection parameters of our model.

Capturing response differences of species distribution to climate and human pressures by incorporating local adaptation: Implications for the conservation of a critically endangered species.

Considering local adaptation has been increasingly involved in forecasting species distributions under climate change and the management of species conservation. Herein, we take the critically endangered Chinese giant salamander (Andrias davidianus) that has both a low dispersal ability and distinct population divergence in different regions as an example. Basin-scale models that represent different populations in the Huanghe River Basin (HRB), the Yangtze River Basin (YRB), and the Pearl River Basin (PRB) were established using ensemble species distribution models. The species ranges under the future human population density (HPD) and climate change were predicted, and the range loss was evaluated for local basins in 2050 and 2070. Our results showed that the predominant factors affecting species distributions differed among basins, and the responses of the species occurrence to HPD and climate factors were distinctly different from northern to southern basins. Future HPD changes would be the most influential factor that engenders negative impacts on the species distribution in all three basins, especially in the HRB. Climate change will likely be less prominent in decreasing the species range, excluding in the YRB and PRB under the highest-emissions scenario in 2050. Overall, the high-emissions scenario would more significantly aggravate the negative impacts produced by HPD change in both 2050 and 2070, with maximum losses of species ranges in the HRB, YRB, and PRB of 83.4%, 60.0%, and 53.5%, respectively, under the scenarios of the combined impacts of HPD and climate changes. We proposed adapted conservation policies to effectively protect the habitat of this critically endangered animal in different basins based on the outcomes. Our research addresses the importance of incorporating local adaptation into species distribution modeling to inform conservation and management decisions.

Species range shifts in response to climate change and human pressure for the world's largest amphibian.

The Chinese giant salamander, Andrias davidianus, the world's largest amphibian, is critically endangered and has an extremely unique evolutionary history. Therefore, this species represents a global conservation priority and will be impacted by future climate and human pressures. Understanding the range and response to environmental change of this species is a priority for the identification of targeted conservation activities. We projected future range shifts of the Chinese giant salamander under the independent and combined impacts of climate change and human population density (HPD) variations by using ensemble species distribution models. We further evaluated the sustainability of existing nature reserves and identified priority areas for the mitigation or prevention of such pressures. Both climate change and increasing HPD tended to reduce the species range, with the latter leading to greater range losses and fragmentation of the range. Notably, 65.6%, 18.0% and 18.4% of the range loss were attributed solely to HPD change, solely to climate change and to their overlapping impacts, respectively. Overall, the average total and net losses of the species range were 52.5% and 23.4%, respectively, and HPD and climate changes were responsible for 71.4% and 28.6% of the net losses, respectively. We investigated the stability of the remaining species range and found that half of the nature reserves are likely vulnerable, with 57.1% and 66.7% of them likely to lose their conservation value in 2050 and 2070, respectively. To effectively protect this salamander, conservation policies should address both pressures simultaneously, especially considering the negative impact of human pressures in both contemporary periods and the near future. The species range shifts over space and time projected by this research could help guide long-term surveys and the sustainable conservation of wild habitats and populations of this ancient and endangered amphibian.

The Laboratory Domestication of Zebrafish: From Diverse Populations to Inbred Substrains.

We know from human genetic studies that practically all aspects of biology are strongly influenced by the genetic background, as reflected in the advent of "personalized medicine." Yet, with few exceptions, this is not taken into account when using laboratory populations as animal model systems for research in these fields. Laboratory strains of zebrafish (Danio rerio) are widely used for research in vertebrate developmental biology, behavior, and physiology, for modeling diseases, and for testing pharmaceutic compounds in vivo. However, all of these strains are derived from artificial bottleneck events and therefore are likely to represent only a fraction of the genetic diversity present within the species. Here, we use restriction site-associated DNA sequencing to genetically characterize wild populations of zebrafish from India, Nepal, and Bangladesh, and to compare them to previously published data on four common laboratory strains. We measured nucleotide diversity, heterozygosity, and allele frequency spectra, and find that wild zebrafish are much more diverse than laboratory strains. Further, in wild zebrafish, there is a clear signal of GC-biased gene conversion that is missing in laboratory strains. We also find that zebrafish populations in Nepal and Bangladesh are most distinct from all other strains studied, making them an attractive subject for future studies of zebrafish population genetics and molecular ecology. Finally, isolates of the same strains kept in different laboratories show a pattern of ongoing differentiation into genetically distinct substrains. Together, our findings broaden the basis for future genetic, physiological, pharmaceutic, and evolutionary studies in Danio rerio.

Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps.

Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this "temporal misclassification". Similarly, "spatial misclassification (softening)" can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings.

Clinical Observation of Patients with Leber's Hereditary Optic Neuropathy Before Gene Therapy.

BACKGROUND: Leber's hereditary optic neuropathy is a hereditary mitochondrial disease. No effective treatment has so far been established, with gene therapy currently being the most promising. Because of the possibility of spontaneous visual acuity recovery in this disease, we screened patients before gene therapy, excluding those with spontaneous visual acuity improvement, and prepared for the subsequent gene therapy. OBJECTIVE: To clinically observe the course of Leber's hereditary optic neuropathy for 6 months prior to gene therapy. METHODS: Sixty-six patients with Leber's hereditary optic neuropathy were enrolled in the study. Patients were classified based on the duration of disease: less than 24 months and over 24 months. Three clinical follow-up examinations were conducted over 1 year. We assessed intraocular pressure, visual acuity, visual field, retinal nerve fiber layer thickness, fundus photographs, and visual evoked potential. RESULTS: Eighty-two eyes displayed stable visual acuity, including both eyes in 34 patients and one eye in 14 patients; 33 eyes of 22 patients displayed decrease in visual acuity (less than 24 months: 24 eyes; over 24 months: nine eyes); and 17 eyes of 12 patients showed improvement in visual acuity (less than 24 months: four eyes; over 24 months: 13 eyes). Visual acuity and visual field indices decreased over 24 months from disease onset and appeared stable after 24 months. CONCLUSION: Most patients with Leber's hereditary optic neuropathy gradually stabilize visual function with prolonged onset time, and the lower possibility of spontaneous vision recovery provides a basis for future evaluation of the effectiveness of gene therapy.

A novel method of vehicle-pedestrian near-crash identification with roadside LiDAR data.

Safety evaluation based on historical crashes usually has a lot of limitations. In previous studies, near-crashes are considered as surrogate data for safety evaluation. One challenge for the use of near-crashes data is the difficulty of data collection. The driving simulators and naturalistic driving data may not be suitable for safety evaluation at specific sites. The observational site-based methods such as human observers and video analysis also suffer from some limitations such as long time data processing or reduced performance influenced by weather or light condition. The roadside Light Detection and Ranging (LiDAR)-enhanced infrastructure provides a new solution for real-time data collection without the impact from weather or light. The high-resolution trajectories of all road users can be obtained from roadside LiDAR data. This paper aims to fill these gaps by presenting a method for near-crash identification based on the trajectories of road users extracted from roadside LiDAR data. This paper focused on vehicle-pedestrian near-crash identification particularly considering the increased risk of vehicle-pedestrian conflicts. Three parameters: Time Difference to the Point of Intersection (TDPI); Distance between Stop Position and Pedestrian (DSPP); Vehicle-pedestrian speed-distance profile, were developed for vehicle-pedestrian near-crash identification. The authors also recommended the thresholds for risk assessment of pedestrian safety. This method was coded into an automatic procedure for near-crash identification. This method is expected to significantly improve the current evaluation of pedestrian safety.

The Evolution of Small-RNA-Mediated Silencing of an Invading Transposable Element.

Transposable elements (TEs) are genomic parasites that impose fitness costs on their hosts by producing deleterious mutations and disrupting gametogenesis. Host genomes avoid these costs by regulating TE activity, particularly in germline cells where new insertions are heritable and TEs are exceptionally active. However, the capacity of different TE-associated fitness costs to select for repression in the host, and the role of selection in the evolution of TE regulation more generally remain controversial. In this study, we use forward, individual-based simulations to examine the evolution of small-RNA-mediated TE regulation, a conserved mechanism for TE repression that is employed by both prokaryotes and eukaryotes. To design and parameterize a biologically realistic model, we drew on an extensive survey of empirical studies of the transposition and regulation of P-element DNA transposons in Drosophila melanogaster. We observed that even under conservative assumptions, where small-RNA-mediated regulation reduces transposition only, repression evolves rapidly and adaptively after the genome is invaded by a new TE in simulated populations. We further show that the spread of repressor alleles through simulated populations is greatly enhanced by two additional TE-imposed fitness costs: dysgenic sterility and ectopic recombination. Finally, we demonstrate that the adaptive mutation rate to repression is a critical parameter that influences both the evolutionary trajectory of host repression and the associated proliferation of TEs after invasion in simulated populations. Our findings suggest that adaptive evolution of TE regulation may be stronger and more prevalent than previously appreciated, and provide a framework for interpreting empirical data.

Correlated Selection on Amino Acid Deletion and Replacement in Mammalian Protein Sequences.

A low ratio of nonsynonymous and synonymous substitution rates (dN/dS) at a codon is an indicator of functional constraint caused by purifying selection. Intuitively, the functional constraint would also be expected to prevent such a codon from being deleted. However, to the best of our knowledge, the correlation between the rates of deletion and substitution has never actually been estimated. Here, we use 8595 protein-coding region sequences from nine mammalian species to examine the relationship between deletion rate and dN/dS. We find significant positive correlations at the levels of both sites and genes. We compared our data against controls consisting of simulated coding sequences evolving along identical phylogenetic trees, where deletions occur independently of substitutions. A much weaker correlation was found in the corresponding simulated sequences, probably caused by alignment errors. In the real data, the correlations cannot be explained by alignment errors. Separate investigations on nonsynonymous (dN) and synonymous (dS) substitution rates indicate that the correlation is most likely due to a similarity in patterns of selection rather than in mutation rates.

Gene flow analysis method, the D-statistic, is robust in a wide parameter space.

BACKGROUND: We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. RESULT: The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. CONCLUSIONS: The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.

Speciation Generates Mosaic Genomes in Kangaroos.

The iconic Australasian kangaroos and wallabies represent a successful marsupial radiation. However, the evolutionary relationship within the two genera, Macropus and Wallabia, is controversial: mitochondrial and nuclear genes, and morphological data have produced conflicting scenarios regarding the phylogenetic relationships, which in turn impact the classification and taxonomy. We sequenced and analyzed the genomes of 11 kangaroos to investigate the evolutionary cause of the observed phylogenetic conflict. A multilocus coalescent analysis using ∼14,900 genome fragments, each 10 kb long, significantly resolved the species relationships between and among the sister-genera Macropus and Wallabia. The phylogenomic approach reconstructed the swamp wallaby (Wallabia) as nested inside Macropus, making this genus paraphyletic. However, the phylogenomic analyses indicate multiple conflicting phylogenetic signals in the swamp wallaby genome. This is interpreted as at least one introgression event between the ancestor of the genus Wallabia and a now extinct ghost lineage outside the genus Macropus. Additional phylogenetic signals must therefore be caused by incomplete lineage sorting and/or introgression, but available statistical methods cannot convincingly disentangle the two processes. In addition, the relationships inside the Macropus subgenus M. (Notamacropus) represent a hard polytomy. Thus, the relationships between tammar, red-necked, agile, and parma wallabies remain unresolvable even with whole-genome data. Even if most methods resolve bifurcating trees from genomic data, hard polytomies, incomplete lineage sorting, and introgression complicate the interpretation of the phylogeny and thus taxonomy.

An evolutionary classification of genomic function.

The pronouncements of the ENCODE Project Consortium regarding "junk DNA" exposed the need for an evolutionary classification of genomic elements according to their selected-effect function. In the classification scheme presented here, we divide the genome into "functional DNA," that is, DNA sequences that have a selected-effect function, and "rubbish DNA," that is, sequences that do not. Functional DNA is further subdivided into "literal DNA" and "indifferent DNA." In literal DNA, the order of nucleotides is under selection; in indifferent DNA, only the presence or absence of the sequence is under selection. Rubbish DNA is further subdivided into "junk DNA" and "garbage DNA." Junk DNA neither contributes to nor detracts from the fitness of the organism and, hence, evolves under selective neutrality. Garbage DNA, on the other hand, decreases the fitness of its carriers. Garbage DNA exists in the genome only because natural selection is neither omnipotent nor instantaneous. Each of these four functional categories can be 1) transcribed and translated, 2) transcribed but not translated, or 3) not transcribed. The affiliation of a DNA segment to a particular functional category may change during evolution: Functional DNA may become junk DNA, junk DNA may become garbage DNA, rubbish DNA may become functional DNA, and so on; however, determining the functionality or nonfunctionality of a genomic sequence must be based on its present status rather than on its potential to change (or not to change) in the future. Changes in functional affiliation are divided into pseudogenes, Lazarus DNA, zombie DNA, and Jekyll-to-Hyde DNA.

Preparation and characterization of TiO2 barrier layers for dye-sensitized solar cells.

A TiO2 barrier layer is critical in enhancing the performance of dye-sensitized solar cells (DSSCs). Two methods to prepare the TiO2 barrier layer on fluorine-doped tin dioxide (FTO) surface were systematically studied in order to minimize electron-hole recombination and electron backflow during photovoltaic processes of DSSCs. The film structure and materials properties were correlated with the photovoltaic characteristics and electrochemical properties. In the first approach, a porous TiO2 layer was deposited by wet chemical treatment of the sample with TiCl4 solution for time periods varying from 0 to 60 min. The N719 dye molecules were found to be able to insert into the porous barrier layers. The 20 min treatment formed a nonuniform but intact TiO2 layer of ∼100-300 nm in thickness, which gave the highest open-circuit voltage VOC, short-circuit photocurrent density JSC, and energy conversion efficiency. But thicker TiO2 barrier layers by this method caused a decrease in JSC, possibly limited by lower electrical conductance. In the second approach, a compact TiO2 barrier layer was created by sputter-coating 0-15 nm Ti metal films on FTO/glass and then oxidizing them into TiO2 with thermal treatment at 500 °C in the air for 30 min. The dye molecules were found to only attach at the outer surface of the barrier layer and slightly increased with the layer thickness. These two kinds of barrier layer showed different characteristics and may be tailored for different DSSC studies.