Molecular Diagnostics of Fine Needle Aspiration for the Presurgical Screening of Thyroid Nodules

“The incidence of thyroid cancer, the most common endocrine malignancy, is rising. The two most common types of thyroid cancer are papillary and follicular” thyroid carcinomas. “Fine-needle aspiration (FNA) of thyroid nodules” can permit to detect many genetic mutations and other molecular alterations, including RAS and BRAF point mutations, PAX8/peroxisome proliferator-activated receptor (PPAR)γ and “RET/PTC rearrangements, occurring in thyroid papillary and follicular carcinomas” (more than 70% of cases), which can be used successfully to improve the diagnosis “and the management of patients with thyroid nodules”. The most extensive experience has been accumulated with “the diagnostic use of BRAF mutation”, which is highly specific for malignancy. “Testing FNA samples for a panel of mutations” that typically includes RAS, BRAF, PAX8/PPARγ and RET/PTC could permit to achieve the biggest diagnostic impact. “The accuracy of cancer diagnosis in thyroid nodules could be improved significantly using these and other emerging molecular markers”.     

Putting the brakes on phagocytosis: “don't‐eat‐me” signaling in physiology and disease

Timely removal of dying or pathogenic cells by phagocytes is essential to maintaining host homeostasis. Phagocytes execute the clearance process with high fidelity while sparing healthy neighboring cells, and this process is at least partially regulated by the balance of “eat‐me” and “don''t‐eat‐me” signals expressed on the surface of host cells. Upon contact, eat‐me signals activate “pro‐phagocytic” receptors expressed on the phagocyte membrane and signal to promote phagocytosis. Conversely, don''t‐eat‐me signals engage “anti‐phagocytic” receptors to suppress phagocytosis. We review the current knowledge of don''t‐eat‐me signaling in normal physiology and disease contexts where aberrant don''t‐eat‐me signaling contributes to pathology.     

Nucleosomes,transcription, and probability

Speaking of current measurements on single ion channel molecules, David Colquhoun wrote in 2006, “Individual molecules behave randomly, so suddenly we had to learn how to deal with stochastic processes.” Here I describe theoretical efforts to understand recent experimental observations on the chromatin structure of single gene molecules, a molecular biologist''s path toward probabilistic theories.     

Do we still need animals? Surveying the role of animal‐free models in Alzheimer’s and Parkinson’s disease research

The use of animals in neuroscience and biomedical research remains controversial. Policy is built around the “3R” principle of “Refining, Reducing and Replacing” animal experiments, and across the globe, different initiatives stimulate the use of animal‐free methods. Based on an extensive literature screen to map the development and adoption of animal‐free methods in Alzheimer''s and Parkinson''s disease research, we find that at least two in three examined studies rely on animals or on animal‐derived models. Among the animal‐free studies, the relative contribution of innovative models that may replace animal experiments is limited. We argue that the distinction between animal research and alternative models presents a false dichotomy, as the role and scientific value of both animal and animal‐free approaches are intertwined. Calls to halt all animal experiments appear premature, as insufficient non‐animal‐based alternatives are available and their development lags behind. In light of this, we highlight the need for objective, unprejudiced monitoring, and more robust performance indicators of animal‐free approaches.     

Are British urban foxes (Vulpes vulpes) “bold”? The importance of understanding human–wildlife interactions in urban areas

Human–wildlife interactions are believed to be increasing in urban areas. In Britain, numerous media reports have stated that urban foxes (Vulpes vulpes) are becoming “bolder,” thereby posing a risk to public safety. However, such claims overlook how an individual''s personality might influence urban fox behavior. Personality determines multiple aspects of an animal''s interactions with both conspecifics and its environment, and can have a significant impact on how people perceive wildlife. Furthermore, describing urban foxes as “bold” confounds two different but inter‐related behaviors, both of which influence an animal''s propensity to take risks. Neophobia affects an animal''s reaction to novelty, wariness its reaction to potential threats. Since urban wildlife frequently encounters both novel and threatening stimuli, a highly adaptable species such as the red fox might be predicted to exhibit reduced neophobia and wariness. We investigated how social status influenced both behaviors in Bristol''s fox population. Dominant foxes were significantly more neophobic and warier than subordinates, which adopt a more exploratory and risk‐taking lifestyle to meet their energetic and other needs. We found no seasonal effect on neophobia and wariness, although this may be due to sample size. The presence of conspecifics decreased neophobia for dominants, and wariness for both dominants and subordinates. We highlight the importance of considering animal social status and personality when planning management protocols, since interventions that destabilize fox social groups are likely to increase the number of subordinate foxes in the population, thereby increasing rather than decreasing the number of interactions between humans and urban foxes.     

Recent population differentiation in the habitat specialist Glossy Antshrike (Aves: Thamnophilidae) across Amazonian seasonally flooded forests

We assessed population structure and the spatio‐temporal pattern of diversification in the Glossy Antshrike Sakesphorus luctuosus (Aves, Thamnophilidae) to understand the processes shaping the evolutionary history of Amazonian floodplains and address unresolved taxonomic controversies surrounding its species limits. By targeting ultraconserved elements (UCEs) from 32 specimens of S. luctuosus, we identified independent lineages and estimated their differentiation, divergence times, and migration rates. We also estimated current and past demographic histories for each recovered lineage. We found evidence confirming that S. luctuosus consists of a single species, comprising at least four populations, with some highly admixed individuals and overall similar levels of migration between populations. We confirmed the differentiation of the Araguaia River basin population (S. l. araguayae) and gathered circumstantial evidence indicating that the taxon S. hagmanni may represent a highly introgressed population between three distinct phylogroups of S. luctuosus. Divergences between populations occurred during the last 1.2 mya. Signs of population expansions were detected for populations attributed to subspecies S. l. luctuosus, but not for the S. l. araguayae population. Our results support that S. luctuosus has had a complex population history, resulting from a high dependence on southeastern “clear water” seasonally flooded habitats and their availability through time. Spatial and demographic expansions toward the western “white water” flooded forests might be related to recent changes in connectivity and availability of these habitats. Our study reinforces the view that isolation due to absence of suitable habitat has been an important driver of population differentiation within Amazonian flooded forests, but also that differences between várzeas (“white water” floodplains, mostly in southwestern Amazonia) and igapós (“clear water” floodplains, especially located in the east) should be further explored as drivers of micro‐evolution for terrestrial species.     

The “Genetic Program”: Behind the Genesis of an Influential Metaphor

The metaphor of the “genetic program,” indicating the genome as a set of instructions required to build a phenotype, has been very influential in biology despite various criticisms over the years. This metaphor, first published in 1961, is thought to have been invented independently in two different articles, one by Ernst Mayr and the other by François Jacob and Jacques Monod. Here, after a detailed analysis of what both parties meant by “genetic program,” I show, using unpublished archives, the strong resemblance between the ideas of Mayr and Monod and suggest that their idea of genetic program probably shares a common origin. I explore the possibility that the two men met before 1961 and also exchanged their ideas through common friends and colleagues in the field of molecular biology. Based on unpublished correspondence of Jacob and Monod, I highlight the important events that influenced the preparation of their influential paper, which introduced the concept of the genetic program. Finally, I suggest that the genetic program metaphor may have preceded both papers and that it was probably used informally before 1961.     

Will the clinical development of 4th-generation “double mutant active” ALK TKIs (TPX-0131 and NVL-655) change the future treatment paradigm of ALK+ NSCLC?

Our current treatment paradigm of advanced anaplastic lymphoma kinase fusion (ALK+) non-small cell lung cancer (NSCLC) classifies the six currently approved ALK tyrosine kinase inhibitors (TKIs) into three generations. The 2nd-generation (2G) and 3rd-generation (3G) ALK TKIs are all “single mutant active” with varying potencies across a wide spectrum of acquired single ALK resistance mutations. There is a vigorous debate among clinicians which is the best upfront ALK TKI is for the first-line (1L) treatment of ALK+ NSCLC and the subsequent sequencing strategies whether it should be based on the presence of specific on-target ALK resistance mutations or not. Regardless, sequential use of “single mutant active” ALK TKIs will eventually lead to double ALK resistance mutations in cis. This has led to the creation of fourth generation (4G) “double mutant active” ALK TKIs such as TPX-0131 and NVL-655. We discuss the critical properties 4G ALK TKIs must possess to be clinically successful. We proposed conceptual first-line, second-line, and molecularly-based third-line registrational randomized clinical trials designed for these 4G ALK TKIs. How these 4G ALK TKIs would be used in the future will depend on which line of treatment the clinical trial design(s) is adopted provided the trial is positive. If approved, 4G ALK TKIs may usher in a new treatment paradigm for advanced ALK+ NSCLC that is based on classifying ALK TKIs based on the intrinsic functional capabilities (“singe mutant active” versus “double mutant active”) rather than the loosely-defined “generational” (first-, second-,third-,fourth-) classification and avoid the current clinical approaches of seemingly random sequential use of 2G and 3G ALK TKIs.     

Analysis and Prediction of the Metabolic Stability of Proteins Based on Their Sequential Features,Subcellular Locations and Interaction Networks

The metabolic stability is a very important idiosyncracy of proteins that is related to their global flexibility, intramolecular fluctuations, various internal dynamic processes, as well as many marvelous biological functions. Determination of protein''s metabolic stability would provide us with useful information for in-depth understanding of the dynamic action mechanisms of proteins. Although several experimental methods have been developed to measure protein''s metabolic stability, they are time-consuming and more expensive. Reported in this paper is a computational method, which is featured by (1) integrating various properties of proteins, such as biochemical and physicochemical properties, subcellular locations, network properties and protein complex property, (2) using the mRMR (Maximum Relevance & Minimum Redundancy) principle and the IFS (Incremental Feature Selection) procedure to optimize the prediction engine, and (3) being able to identify proteins among the four types: “short”, “medium”, “long”, and “extra-long” half-life spans. It was revealed through our analysis that the following seven characters played major roles in determining the stability of proteins: (1) KEGG enrichment scores of the protein and its neighbors in network, (2) subcellular locations, (3) polarity, (4) amino acids composition, (5) hydrophobicity, (6) secondary structure propensity, and (7) the number of protein complexes the protein involved. It was observed that there was an intriguing correlation between the predicted metabolic stability of some proteins and the real half-life of the drugs designed to target them. These findings might provide useful insights for designing protein-stability-relevant drugs. The computational method can also be used as a large-scale tool for annotating the metabolic stability for the avalanche of protein sequences generated in the post-genomic age.     

A Novel Bio-Sensor Based on DNA Strand Displacement

DNA strand displacement technology performs well in sensing and programming DNA segments. In this work, we construct DNA molecular systems based on DNA strand displacement performing computation of logic gates. Specifically, a class of so-called “DNA neurons” are achieved, in which a “smart” way inspired by biological neurons encoding information is developed to encode and deliver information using DNA molecules. The “DNA neuron” is bistable, that is, it can sense DNA molecules as input signals, and release “negative” or “positive” signals DNA molecules. We design intelligent DNA molecular systems that are constructed by cascading some particularly organized “DNA neurons”, which could perform logic computation, including AND, OR, XOR logic gates, automatically. Both simulation results using visual DSD (DNA strand displacement) software and experimental results are obtained, which shows that the proposed systems can detect DNA signals with high sensitivity and accretion; moreover, the systems can process input signals automatically with complex nonlinear logic. The method proposed in this work may provide a new way to construct a sensitive molecular signal detection system with neurons spiking behavior in vitro, and can be used to develop intelligent molecular processing systems in vivo.     

Darwin's Manufactory Hypothesis Is Confirmed and Predicts the Extinction Risk of Extant Birds

In the Origin of Species Darwin hypothesized that the “manufactory” of species operates at different rates in different lineages and that the richness of taxonomic units is autocorrelated across levels of the taxonomic hierarchy. We confirm the manufactory hypothesis using a database of all the world''s extant avian subspecies, species and genera. The hypothesis is confirmed both in correlations across all genera and in paired comparisons controlling for phylogeny. We also find that the modern risk of extinction, as measured by “Red List” classifications, differs across the different categories of genera identified by Darwin. Specifically, species in “manufactory” genera are less likely to be threatened, endangered or recently extinct than are “weak manufactory” genera. Therefore, although Darwin used his hypothesis to investigate past evolutionary processes, we find that the hypothesis also foreshadows future changes to the evolutionary tree.     

Nitrous Oxide Inhalation as a Fad—Dangers in Uncontrolled Sniffing for Psychedelic Effect

“LAUGHING GAS is the newest thing for kids seeking kicks,” the Stanford Daily reports. “They sniff it.”So begins a news story in the Los Angeles Times of 26 January 1967. The story continues:“It''s the latest way to travel, or so say a growing group of devotees on the campus,” the university student paper said. “It can produce much the same effects as psychedelic drugs, they claim, and it''s cheaper to obtain.”“One student said he buys the gas, nitrous oxide, from a medical supply house. `They think I am anesthetizing rats,'' he explained.“Campus medical authorities said the gas, sniffed `in sufficient amounts... could produce all the states of anesthesia, including the final stage—death.''”     

Hyperglobulinaemic Renal Tubular Acidosis: A Report of Nine Cases

Of nine women with hyperglobulinaemic renal tubular acidosis four presented with acidosis and five had the “incomplete” form of the disorder. Seven patients had nephrogenic diabetes insipidus, but none had the Fanconi syndrome. Investigation showed abnormal immunoglobulins and autoantibodies in all nine patients. Diseases coexisting with renal tubular acidosis were Sjögren''s syndrome, hyperglobulinaemic purpura, autoimmune liver and thyroid disease, diffuse pulmonary fibrosis, and a peripheral neuropathy. It is suggested that this type of renal tubular acidosis might be due to an autoimmune process.     

Biomarkers for early detection of high risk cancers: From gliomas to nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NpC) is a malignant disease associated with Epstein-Barr virus infection, and often diagnosed at an advanced stage. This significantly curtails patient survival. We hypothesize that a panel of biomarkers can be assembled to assess NpC incidence, early detection, and tumor progression during therapeutic intervention. Our thesis rests on a model of successfully predicting high-risk gliomas by means of a carefully crafted panel of molecular mitotic biomarkers (i.e., securin, survivin and MCM2). The strategy we propose holds strong promise for prevention and cure of NpC. The approach we propose seeks to identify certain biomarkers from viral materials, patient tissues and assessment of related diseases, whose signatures, taken together, will be endowed with some degree of congruency, or sense of a coordinated language (i.e., “votes”). Biomarker “voting” will then permit to outline a broad coordinated molecular map for the molecular and epigenetic characterization of each individual patient''s NpC tumor. We will draw on the process of contrasting biomarkers in health and disease, which rests on the auto-proteomic concept particularly relevant in high-risk cancer individuals, such as is the case for NpC. In brief we defend, current advances in human proteome profiling proffers the possibility of having individual baseline proteomic profiles using local body fluids (e.g., saliva, nasal secretions, sputum) or systemic fluids (e.g., plasma, serum, cerebrospinal fluid) to unravel a personalized molecular map for high-risk NpC individuals. Regular check-up will monitor for new or impending manifestations of NpC, and provide a secure assessment of incidence and early detection.     

Prediction of MHC class I binding peptides using probability distribution functions

Binding of peptides to specific Major Histo-compatibility Complex (MHC) molecule is important for understanding immunity and has applications to vaccine discovery and design of immunotherapy. Artificial neural networks (ANN) are widely used by predictions tools to classify the peptides as binders or non­binders (BNB). However, the number of known binders to a specific MHC molecule is limited in many cases, which poses a computational challenge for prediction of BNB and hence, needs improvement in learning of ANN. Here, we describe, the application of probability distribution functions to initialize the weights and biases of the artificial neural network in order to predict HLA­A*0201 binders and non­binders. The 10­fold cross validation has been used to validate the results. It is evident from the results that the A_ROC for 90% of test cases for Weibull, Uniform and Rayleigh distributions is in the range 0.90-1.0. Further, the standard deviation for AROC was minimum for Weibull distribution, and may be used to train the artificial neural network for HLA­A*0201 MHC Class­I binders and non­binders prediction.     

Niche theory‐based modeling of assembly processes of viral communities in bats

Understanding the assembly processes of symbiont communities, including viromes and microbiomes, is important for improving predictions on symbionts’ biogeography and disease ecology. Here, we use phylogenetic, functional, and geographic filters to predict the similarity between symbiont communities, using as a test case the assembly process in viral communities of Mexican bats. We construct generalized linear models to predict viral community similarity, as measured by the Jaccard index, as a function of differences in host phylogeny, host functionality, and spatial co‐occurrence, evaluating the models using the Akaike information criterion. Two model classes are constructed: a “known” model, where virus–host relationships are based only on data reported in Mexico, and a “potential” model, where viral reports of all the Americas are used, but then applied only to bat species that are distributed in Mexico. Although the “known” model shows only weak dependence on any of the filters, the “potential” model highlights the importance of all three filter types—phylogeny, functional traits, and co‐occurrence—in the assemblage of viral communities. The differences between the “known” and “potential” models highlight the utility of modeling at different “scales” so as to compare and contrast known information at one scale to another one, where, for example, virus information associated with bats is much scarcer.