Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany).

BACKGROUND: Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES: We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. METHODS: To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS: In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 µg/m3 to 15.98 µg/m3. CONCLUSIONS: Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

A Bayesian approach to determine the composition of heterogeneous cancer tissue.

BACKGROUND: Cancer Tissue Heterogeneity is an important consideration in cancer research as it can give insights into the causes and progression of cancer. It is known to play a significant role in cancer cell survival, growth and metastasis. Determining the compositional breakup of a heterogeneous cancer tissue can also help address the therapeutic challenges posed by heterogeneity. This necessitates a low cost, scalable algorithm to address the challenge of accurate estimation of the composition of a heterogeneous cancer tissue. METHODS: In this paper, we propose an algorithm to tackle this problem by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework. RESULTS: The algorithm is analyzed and validated using synthetic data and experimental data. The experimental data is obtained from mixtures of three separate human cancer cell lines, HCT116 (Colorectal carcinoma), A2058 (Melanoma) and SW480 (Colorectal carcinoma). CONCLUSION: The algorithm provides a low cost framework to determine the composition of heterogeneous cancer tissue which is a crucial aspect in cancer research.

An in-silico study examining the induction of apoptosis by Cryptotanshinone in metastatic melanoma cell lines.

BACKGROUND: Metastatic melanoma is an aggressive form of skin cancer that evades various anti-cancer treatments including surgery, radio-,immuno- and chemo-therapy. TRAIL-induced apoptosis is a desirable method to treat melanoma since, unlike other treatments, it does not harm non-cancerous cells. The pro-inflammatory response to melanoma by nF κB and STAT3 pathways makes the cancer cells resist TRAIL-induced apoptosis. We show that due to to its dual action on DR5, a death receptor for TRAIL and on STAT3, Cryptotanshinone can be used to increase sensitivity to TRAIL. METHODS: The development of chemoresistance and invasive properties in melanoma cells involves several biological pathways. The key components of these pathways are represented as a Boolean network with multiple inputs and multiple outputs. RESULTS: The possible mutations in genes that can lead to cancer are captured by faults in the combinatorial circuit and the model is used to theoretically predict the effectiveness of Cryptotanshinone for inducing apoptosis in melanoma cell lines. This prediction is experimentally validated by showing that Cryptotanshinone can cause enhanced cell death in A375 melanoma cells. CONCLUSION: The results presented in this paper facilitate a better understanding of melanoma drug resistance. Furthermore, this framework can be used to detect additional drug intervention points in the pathway that could amplify the action of Cryptotanshinone.

Dynamical modeling of uncertain interaction-based genomic networks.

BACKGROUND: Most dynamical models for genomic networks are built upon two current methodologies, one process-based and the other based on Boolean-type networks. Both are problematic when it comes to experimental design purposes in the laboratory. The first approach requires a comprehensive knowledge of the parameters involved in all biological processes a priori, whereas the results from the second method may not have a biological correspondence and thus cannot be tested in the laboratory. Moreover, the current methods cannot readily utilize existing curated knowledge databases and do not consider uncertainty in the knowledge. Therefore, a new methodology is needed that can generate a dynamical model based on available biological data, assuming uncertainty, while the results from experimental design can be examined in the laboratory. RESULTS: We propose a new methodology for dynamical modeling of genomic networks that can utilize the interaction knowledge provided in public databases. The model assigns discrete states for physical entities, sets priorities among interactions based on information provided in the database, and updates each interaction based on associated node states. Whenever uncertainty in dynamics arises, it explores all possible outcomes. By using the proposed model, biologists can study regulation networks that are too complex for manual analysis. CONCLUSIONS: The proposed approach can be effectively used for constructing dynamical models of interaction-based genomic networks without requiring a complete knowledge of all parameters affecting the network dynamics, and thus based on a small set of available data.

Dioxygen reactivity of biomimetic Fe(II) complexes with noninnocent catecholate, o-aminophenolate, and o-phenylenediamine ligands.

This study describes the O2 reactivity of a series of high-spin mononuclear Fe(II) complexes each containing the facially coordinating tris(4,5-diphenyl-1-methylimidazol-2-yl)phosphine ((Ph2)TIP) ligand and one of the following bidentate, redox-active ligands: 4-tert-butylcatecholate ((tBu)CatH(-)), 4,6-di-tert-butyl-2-aminophenolate ((tBu2)APH(-)), or 4-tert-butyl-1,2-phenylenediamine ((tBu)PDA). The preparation and X-ray structural characterization of [Fe(2+)((Ph2)TIP)((tBu)CatH)]OTf, [3]OTf and [Fe(2+)((Ph2)TIP)((tBu)PDA)](OTf)2, [4](OTf)2 are described here, whereas [Fe(2+)((Ph2)TIP)((tBu2)APH)]OTf, [2]OTf was reported in our previous paper [Bittner et al., Chem.-Eur. J. 2013, 19, 9686-9698]. These complexes mimic the substrate-bound active sites of nonheme iron dioxygenases, which catalyze the oxidative ring-cleavage of aromatic substrates like catechols and aminophenols. Each complex is oxidized in the presence of O2, and the geometric and electronic structures of the resulting complexes were examined with spectroscopic (absorption, EPR, Mössbauer, resonance Raman) and density functional theory (DFT) methods. Complex [3]OTf reacts rapidly with O2 to yield the ferric-catecholate species [Fe(3+)((Ph2)TIP)((tBu)Cat)](+) (3(ox)), which undergoes further oxidation to generate an extradiol cleavage product. In contrast, complex [4](2+) experiences a two-electron (2e(-)), ligand-based oxidation to give [Fe(2+)((Ph2)TIP)((tBu)DIBQ)](2+) (4(ox)), where DIBQ is o-diiminobenzoquinone. The reaction of [2](+) with O2 is also a 2e(-) process, yet in this case both the Fe center and (tBu2)AP ligand are oxidized; the resulting complex (2(ox)) is best described as [Fe(3+)((Ph2)TIP)((tBu2)ISQ)](+), where ISQ is o-iminobenzosemiquinone. Thus, the oxidized complexes display a remarkable continuum of electronic structures ranging from [Fe(3+)(L(2-))](+) (3(ox)) to [Fe(3+)(L(•-))](2+) (2(ox)) to [Fe(2+)(L(0))](2+) (4(ox)). Notably, the O2 reaction rates vary by a factor of 10(5) across the series, following the order [3](+) > [2](+) > [4](2+), even though the complexes have similar structures and Fe(3+/2+) redox potentials. To account for the kinetic data, we examined the relative abilities of the title complexes to bind O2 and participate in H-atom transfer reactions. We conclude that the trend in O2 reactivity can be rationalized by accounting for the role of proton transfer(s) in the overall reaction.

Comparison of Hemodynamics in Jet Ventilation vs. Intermittent Apnea for Airway Stenosis Surgery.

OBJECTIVE: The objective of this study is to assess the impact of two different ventilation techniques, jet ventilation and apneic anesthesia with intermittent ventilation (AAIV), on patient hemodynamics and operative time during endoscopic laryngotracheal stenosis surgery. METHODS: Retrospective chart review of patients who underwent airway dilation for laryngotracheal stenosis by a single surgeon at a single institution from October 1, 2000 through January 2, 2020. Logistic regression, Mann-Whitney U tests and chi square analysis were used to determine statistical significance. RESULTS: A total of 157 patients, 43 (27.4%) male and 114 (72.6%) female, and 605 total encounters were included for analysis. There were no significant differences in hemodynamic outcomes when comparing the AAIV and jet ventilation groups. Specifically, there was no significant difference in either peak end-tidal CO2 or nadir O2 saturation between the AAIV and jet ventilation groups (p = 0.4016) and (p = 0.1357), respectively. The patients in the AAIV group had a significantly higher median BMI 32.93 (27.40-39.40) compared with 28.80 (24.1-32.65) (p = 0.0001). Although not necessarily clinically significant, patients with higher BMI had lower median O2 nadirs (97.8%) than non-obese patients (99.2%) (p < 0.0001). The median total procedure time was equivalent when comparing the two ventilation techniques. CONCLUSION: AAIV is a safe method of ventilation for patients undergoing endoscopic laryngotracheal stenosis surgery with no significant differences in patient hemodynamics or procedure time when compared with jet ventilation. AAIV was the preferred method of ventilation for obese patients undergoing endoscopic laryngotracheal stenosis surgery. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:1343-1348, 2024.

Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany).

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone ( O 3 ), nitrogen dioxide ( NO 2 ), particulate matter ( P M 2.5 , P M 10 ) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (-0.84), April (-0.47), and October (-0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O 3 and NO 2 . Spatially, NO 2 , P M 2.5 , and P M 10 concentrations were significantly higher in urban than rural regions. For O 3 , this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

Learning contextual gene set interaction networks of cancer with condition specificity.

BACKGROUND: Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. RESULTS: In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. CONCLUSIONS: The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes.

Identifying mechanistic similarities in drug responses.

MOTIVATION: In early drug development, it would be beneficial to be able to identify those dynamic patterns of gene response that indicate that drugs targeting a particular gene will be likely or not to elicit the desired response. One approach would be to quantitate the degree of similarity between the responses that cells show when exposed to drugs, so that consistencies in the regulation of cellular response processes that produce success or failure can be more readily identified. RESULTS: We track drug response using fluorescent proteins as transcription activity reporters. Our basic assumption is that drugs inducing very similar alteration in transcriptional regulation will produce similar temporal trajectories on many of the reporter proteins and hence be identified as having similarities in their mechanisms of action (MOA). The main body of this work is devoted to characterizing similarity in temporal trajectories/signals. To do so, we must first identify the key points that determine mechanistic similarity between two drug responses. Directly comparing points on the two signals is unrealistic, as it cannot handle delays and speed variations on the time axis. Hence, to capture the similarities between reporter responses, we develop an alignment algorithm that is robust to noise, time delays and is able to find all the contiguous parts of signals centered about a core alignment (reflecting a core mechanism in drug response). Applying the proposed algorithm to a range of real drug experiments shows that the result agrees well with the prior drug MOA knowledge. AVAILABILITY: The R code for the RLCSS algorithm is available at http://gsp.tamu.edu/Publications/supplementary/zhao12a.

Synthetic, spectroscopic, and DFT studies of iron complexes with iminobenzo(semi)quinone ligands: implications for o-aminophenol dioxygenases.

The oxidative C-C bond cleavage of o-aminophenols by nonheme Fe dioxygenases is a critical step in both human metabolism (the kynurenine pathway) and the microbial degradation of nitroaromatic pollutants. The catalytic cycle of o-aminophenol dioxygenases (APDOs) has been proposed to involve formation of an Fe(II)/O2/iminobenzosemiquinone complex, although the presence of a substrate radical has been called into question by studies of related ring-cleaving dioxygenases. Recently, we reported the first synthesis of an iron(II) complex coordinated to an iminobenzosemiquinone (ISQ) ligand, namely, [Fe((Ph2)Tp)((tBu)ISQ)] (2a; where (Ph2)Tp=hydrotris(3,5-diphenylpyrazol-1-yl)borate and (tBu)ISQ is the radical anion derived from 2-amino-4,6-di-tert-butylphenol). In the current manuscript, density functional theory (DFT) calculations and a wide variety of spectroscopic methods (electronic absorption, Mössbauer, magnetic circular dichroism, and resonance Raman) were employed to obtain detailed electronic-structure descriptions of 2a and its one-electron oxidized derivative [3a](+). In addition, we describe the synthesis and characterization of a parallel series of complexes featuring the neutral supporting ligand tris(4,5-diphenyl-1-methylimidazol-2-yl)phosphine ((Ph2)TIP). The isomer shifts of about 0.97 mm s(-1) obtained through Mössbauer experiments confirm that 2a (and its (Ph2)TIP-based analogue [2b](+)) contain Fe(II) centers, and the presence of an ISQ radical was verified by analysis of the absorption spectra in light of time-dependent DFT calculations. The collective spectroscopic data indicate that one-electron oxidation of the Fe(II)-ISQ complexes yields complexes ([3a](+) and [3b](2+)) with electronic configurations between the Fe(III)-ISQ and Fe(II)-IBQ limits (IBQ=iminobenzoquinone), highlighting the ability of o-amidophenolates to access multiple oxidation states. The implications of these results for the mechanism of APDOs and other ring-cleaving dioxygenases are discussed.

A transforming mutation in the pleckstrin homology domain of AKT1 in cancer.

Although AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a central member of possibly the most frequently activated proliferation and survival pathway in cancer, mutation of AKT1 has not been widely reported. Here we report the identification of a somatic mutation in human breast, colorectal and ovarian cancers that results in a glutamic acid to lysine substitution at amino acid 17 (E17K) in the lipid-binding pocket of AKT1. Lys 17 alters the electrostatic interactions of the pocket and forms new hydrogen bonds with a phosphoinositide ligand. This mutation activates AKT1 by means of pathological localization to the plasma membrane, stimulates downstream signalling, transforms cells and induces leukaemia in mice. This mechanism indicates a direct role of AKT1 in human cancer, and adds to the known genetic alterations that promote oncogenesis through the phosphatidylinositol-3-OH kinase/AKT pathway. Furthermore, the E17K substitution decreases the sensitivity to an allosteric kinase inhibitor, so this mutation may have important clinical utility for AKT drug development.

Assessing the efficacy of molecularly targeted agents on cell line-based platforms by using system identification.

BACKGROUND: Molecularly targeted agents (MTAs) are increasingly used for cancer treatment, the goal being to improve the efficacy and selectivity of cancer treatment by developing agents that block the growth of cancer cells by interfering with specific targeted molecules needed for carcinogenesis and tumor growth. This approach differs from traditional cytotoxic anticancer drugs. The lack of specificity of cytotoxic drugs allows a relatively straightforward approach in preclinical and clinical studies, where the optimal dose has usually been defined as the "maximum tolerated dose" (MTD). This toxicity-based dosing approach is founded on the assumption that the therapeutic anticancer effect and toxic effects of the drug increase in parallel as the dose is escalated. On the contrary, most MTAs are expected to be more selective and less toxic than cytotoxic drugs. Consequently, the maximum therapeutic effect may be achieved at a "biologically effective dose" (BED) well below the MTD. Hence, dosing study for MTAs should be different from cytotoxic drugs. Enhanced efforts to molecularly characterize the drug efficacy for MTAs in preclinical models will be valuable for successfully designing dosing regimens for clinical trials. RESULTS: A novel preclinical model combining experimental methods and theoretical analysis is proposed to investigate the mechanism of action and identify pharmacodynamic characteristics of the drug. Instead of fixed time point analysis of the drug exposure to drug effect, the time course of drug effect for different doses is quantitatively studied on cell line-based platforms using system identification, where tumor cells' responses to drugs through the use of fluorescent reporters are sampled over a time course. Results show that drug effect is time-varying and higher dosages induce faster and stronger responses as expected. However, the drug efficacy change along different dosages is not linear; on the contrary, there exist certain thresholds. This kind of preclinical study can provide valuable suggestions about dosing regimens for the in vivo experimental stage to increase productivity.

A synthetic model of the putative Fe(II)-iminobenzosemiquinonate intermediate in the catalytic cycle of o-aminophenol dioxygenases.

The oxidative ring cleavage of aromatic substrates by nonheme Fe dioxygenases is thought to involve formation of a ferrous-(substrate radical) intermediate. Here we describe the synthesis of the trigonal-bipyramdial complex Fe((Ph2)Tp)(ISQ(tBu)) (2), the first synthetic example of an iron(II) center bound to an iminobenzosemiquinonate (ISQ) radical. The unique electronic structure of this S = 3/2 complex and its one-electron oxidized derivative ([3](+)) have been established on the basis of crystallographic, spectroscopic, and computational analyses. These findings further demonstrate the viability of Fe(2+)-ISQ intermediates in the catalytic cycles of o-aminophenol dioxygenases.

Cancer therapy design based on pathway logic.

MOTIVATION: Cancer encompasses various diseases associated with loss of cell cycle control, leading to uncontrolled cell proliferation and/or reduced apoptosis. Cancer is usually caused by malfunction(s) in the cellular signaling pathways. Malfunctions occur in different ways and at different locations in a pathway. Consequently, therapy design should first identify the location and type of malfunction to arrive at a suitable drug combination. RESULTS: We consider the growth factor (GF) signaling pathways, widely studied in the context of cancer. Interactions between different pathway components are modeled using Boolean logic gates. All possible single malfunctions in the resulting circuit are enumerated and responses of the different malfunctioning circuits to a 'test' input are used to group the malfunctions into classes. Effects of different drugs, targeting different parts of the Boolean circuit, are taken into account in deciding drug efficacy, thereby mapping each malfunction to an appropriate set of drugs.

Fe(II) complexes that mimic the active site structure of acetylacetone dioxygenase: O2 and NO reactivity.

Acetylacetone dioxygenase (Dke1) is a bacterial enzyme that catalyzes the dioxygen-dependent degradation of ß-dicarbonyl compounds. The Dke1 active site contains a nonheme monoiron(II) center facially ligated by three histidine residues (the 3His triad); coordination of the substrate in a bidentate manner provides a five-coordinate site for O(2) binding. Recently, we published the synthesis and characterization of a series of ferrous ß-diketonato complexes that faithfully mimic the enzyme-substrate intermediate of Dke1 (Park, H.; Baus, J.S.; Lindeman, S.V.; Fiedler, A.T. Inorg. Chem.2011, 50, 11978-11989). The 3His triad was modeled with three different facially coordinating N3 supporting ligands, and substituted ß-diketonates (acac(X)) with varying steric and electronic properties were employed. Here, we describe the reactivity of our Dke1 models toward O(2) and its surrogate nitric oxide (NO), and report the synthesis of three new Fe(II) complexes featuring the anions of dialkyl malonates. Exposure of [Fe((Me2)Tp)(acac(X))] complexes (where (R2)Tp = hydrotris(pyrazol-1-yl)borate with R-groups at the 3- and 5-positions of the pyrazole rings) to O(2) at -70 °C in toluene results in irreversible formation of green chromophores (λ(max) ∼750 nm) that decay at temperatures above -60 °C. Spectroscopic and computational analyses suggest that these intermediates contain a diiron(III) unit bridged by a trans µ-1,2-peroxo ligand. The green chromophore is not observed with analogous complexes featuring (Ph2)Tp and (Ph)TIP ligands (where (Ph)TIP = tris(2-phenylimidazoly-4-yl)phosphine), since the steric bulk of the phenyl substituents prevents formation of dinuclear species. While these complexes are largely inert toward O(2), (Ph2)Tp-based complexes with dialkyl malonate anions exhibit dioxygenase activity and thus serve as functional Dke1 models. The Fe/acac(X) complexes all react readily with NO to yield high-spin (S = 3/2) {FeNO}(7) adducts that were characterized with crystallographic, spectroscopic, and computational methods. Collectively, the results presented here enhance our understanding of the chemical factors involved in the oxidation of aliphatic substrates by nonheme iron dioxygenases.

Wnt5a signaling directly affects cell motility and invasion of metastatic melanoma.

Gene expression profiling identified human melanoma cells demonstrating increased cell motility and invasiveness. The gene WNT5A best determined in vitro invasive behavior. Melanoma cells were transfected with vectors constitutively overexpressing Wnt5a. Consistent changes included actin reorganization and increased cell adhesion. No increase in beta-catenin expression or nuclear translocation was observed. There was, however, a dramatic increase in activated PKC. In direct correlation with Wnt5a expression and PKC activation, there was an increase in melanoma cell invasion. Blocking this pathway using antibodies to Frizzled-5, the receptor for Wnt5a, inhibited PKC activity and cellular invasion. Furthermore, Wnt5a expression in human melanoma biopsies directly correlated to increasing tumor grade. These observations support a role for Wnt5a in human melanoma progression.

Random DNA fragmentation allows detection of single-copy, single-exon alterations of copy number by oligonucleotide array CGH in clinical FFPE samples.

Genomic technologies, such as array comparative genomic hybridization (aCGH), increasingly offer definitive gene dosage profiles in clinical samples. Historically, copy number profiling was limited to large fresh-frozen tumors where intact DNA could be readily extracted. Genomic analyses of pre-neoplastic tumors and diagnostic biopsies are often limited to DNA processed by formalin-fixation and paraffin-embedding (FFPE). We present specialized protocols for DNA extraction and processing from FFPE tissues utilizing DNase processing to generate randomly fragmented DNA. The protocols are applied to FFPE clinical samples of varied tumor types, from multiple institutions and of varied block age. Direct comparative analyses with regression coefficient were calculated on split-sample (portion fresh/portion FFPE) of colorectal tumor samples. We show equal detection of a homozygous loss of SMAD4 at the exon-level in the SW480 cell line and gene-specific alterations in the split tumor samples. aCGH application to a set of archival FFPE samples of skin squamous cell carcinomas detected a novel hemizygous deletion in INPP5A on 10q26.3. Finally we present data on derivative of log ratio, a particular sensitive detector of measurement variance, for 216 sequential hybridizations to assess protocol reliability over a wide range of FFPE samples.

Influence of air pressure, humidity, solar radiation, temperature, and wind speed on ambulatory visits due to chronic obstructive pulmonary disease in Bavaria, Germany.

Chronic obstructive pulmonary disease (COPD) is one of the most important causes of morbidity and mortality in the world. The disease is often aggravated by periods of increased symptoms requiring medical attention. Among the possible triggers for these exacerbations, meteorological factors are under consideration. The objective of this study was to assess the influence of various meteorological factors on the health status of patients with COPD. For this purpose, the daily number of ambulatory care visits due to COPD was analysed in Bavaria, Germany, for the years 2006 and 2007. The meteorological factors were provided by the model at the European Centre for Medium Range Weather Forecast (ECMWF). For the multivariate analysis, a generalised linear model was used. In Bavaria, an increase of 1% of daily consultations (about 103 visits per day) was found to be associated with a change of 0.72 K temperature, 209.55 of log air surface pressure in Pa, and a decrease of 1% of daily consultations with 1,453,763 Ws m(2) of solar radiation. There also seem to be regional differences between north and south Bavaria; for instance, the effect of wind speed and specific humidity with a lag of 1 day were only significant in the north. This study could contribute to a tool for the prevention of exacerbations. It also serves as a model for the further evaluation of the impact of meteorological factors on health, and could easily be applied to other diseases or other regions.

Anti-tumor effects of cryptotanshinone (C19H20O3) in human osteosarcoma cell lines.

Osteosarcoma is the most prevalent malignant bone tumor and occurs most commonly in the adolescent and young adult population. Despite the recent advances in surgeries and chemotherapy, the overall survival in patients with resectable metastases is around 20%. This challenge in osteosarcoma is often attributed to the drastic differences in the tumorigenic profiles and mutations among patients. With diverse mutations and multiple oncogenes, it is necessary to identify the therapies that can attack various mutations and simultaneously have minor side-effects. In this paper, we constructed the osteosarcoma pathway from literature and modeled it using ordinary differential equations. We then simulated this network for every possible gene mutation and their combinations and ranked different drug combinations based on their efficacy to drive a mutated osteosarcoma network towards cell death. Our theoretical results predict that drug combinations with Cryptotanshinone (C19H20O3), a traditional Chinese herb derivative, have the best overall performance. Specifically, Cryptotanshinone in combination with Temsirolimus inhibit the JAK/STAT, MAPK/ERK, and PI3K/Akt/mTOR pathways and induce cell death in tumor cells. We corroborated our theoretical predictions using wet-lab experiments on SaOS2, 143B, G292, and HU03N1 human osteosarcoma cell lines, thereby demonstrating the potency of Cryptotanshinone in fighting osteosarcoma.

In Silico Modeling of the Induction of Apoptosis by Cryptotanshinone in Osteosarcoma Cell Lines.

Osteosarcoma (OS) is the most common primary malignant bone tumor of both children and pet canines. Its characteristic genomic instability and complexity coupled with the dearth of knowledge about its etiology has made improvement in the current treatment difficult. We use the existing literature about the biological pathways active in OS and combine it with the current research involving natural compounds to identify new targets and design more effective drug therapies. The key components of these pathways are modeled as a Boolean network with multiple inputs and multiple outputs. The combinatorial circuit is employed to theoretically predict the efficacies of various drugs in combination with Cryptotanshinone. We show that the action of the herbal drug, Cryptotanshinone on OS cell lines induces apoptosis by increasing sensitivity to TNF-related apoptosis-inducing ligand (TRAIL) through its multi-pronged action on STAT3, DRP1 and DR5. The Boolean framework is used to detect additional drug intervention points in the pathway that could amplify the action of Cryptotanshinone.