Mediterranean winter rainfall in phase with African monsoons during the past 1.36 million years.

Mediterranean climates are characterized by strong seasonal contrasts between dry summers and wet winters. Changes in winter rainfall are critical for regional socioeconomic development, but are difficult to simulate accurately1 and reconstruct on Quaternary timescales. This is partly because regional hydroclimate records that cover multiple glacial-interglacial cycles2,3 with different orbital geometries, global ice volume and atmospheric greenhouse gas concentrations are scarce. Moreover, the underlying mechanisms of change and their persistence remain unexplored. Here we show that, over the past 1.36 million years, wet winters in the northcentral Mediterranean tend to occur with high contrasts in local, seasonal insolation and a vigorous African summer monsoon. Our proxy time series from Lake Ohrid on the Balkan Peninsula, together with a 784,000-year transient climate model hindcast, suggest that increased sea surface temperatures amplify local cyclone development and refuel North Atlantic low-pressure systems that enter the Mediterranean during phases of low continental ice volume and high concentrations of atmospheric greenhouse gases. A comparison with modern reanalysis data shows that current drivers of the amount of rainfall in the Mediterranean share some similarities to those that drive the reconstructed increases in precipitation. Our data cover multiple insolation maxima and are therefore an important benchmark for testing climate model performance.

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation.

BACKGROUND: Alzheimer's Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. METHODS: We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. RESULTS: Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. CONCLUSIONS: These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders.

Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automated text mining with limited manual curation, opening up new opportunities for generating and modeling chemical toxicology data.

MicroRNAs isolated from peripheral blood in the first trimester predict spontaneous preterm birth.

OBJECTIVE: To predict spontaneous preterm birth among pregnant women in an African American population using first trimester peripheral blood maternal immune cell microRNA. STUDY DESIGN: This was a retrospective nested case-control study in pregnant patients enrolled between March 2006 and October 2016. For initial study inclusion, samples were selected that met the following criteria: 1) singleton pregnancy; 2) maternal body mass index (BMI) <30 kg/m2; 3) blood sample drawn between 6 weeks to 12 weeks 6 days gestation; 4) live born neonate with no detectable birth defects. Using these entry criteria, 486 samples were selected for study inclusion. After sample quality was confirmed, 139 term deliveries (38-42 weeks) and 18 spontaneous preterm deliveries (<35 weeks) were selected for analysis. Samples were divided into training and validation sets. Real time reverse transcription quantitative polymerase chain reaction (rt-qPCR) was performed on each sample for 45 microRNAs. MicroRNA Risk Scores were calculated on the training set and area-under-the-curve receiver-operating-characteristic (AUC-ROC) curves were derived from the validation set. RESULTS: The AUC-ROC for the validation set delivering preterm was 0.80 (95% CI: 0.69 to 0.88; p = 0.0001), sensitivity 0.89, specificity of 0.71 and a mean gestational age of 10.0 ±1.8 weeks (range: 6.6-12.9 weeks). When the validation population was divided by gestational age at the time of venipuncture into early first trimester (mean 8.4 ±1.0 weeks; range 6.6-9.7 weeks) and late first trimester (mean 11.5±0.8 weeks; range 10.0-12.9 weeks), the AUC-ROC scores for early and late first trimester were 0.79 (95% CI: 0.63 to 0.91) and 0.81 (95% CI: 0.66 to 0.92), respectively. CONCLUSION: Quantification of first trimester peripheral blood MicroRNA identifies risk of spontaneous preterm birth in samples obtained early and late first trimester of pregnancy in an African American population.

Deep drilling reveals massive shifts in evolutionary dynamics after formation of ancient ecosystem.

The scarcity of high-resolution empirical data directly tracking diversity over time limits our understanding of speciation and extinction dynamics and the drivers of rate changes. Here, we analyze a continuous species-level fossil record of endemic diatoms from ancient Lake Ohrid, along with environmental and climate indicator time series since lake formation 1.36 million years (Ma) ago. We show that speciation and extinction rates nearly simultaneously decreased in the environmentally dynamic phase after ecosystem formation and stabilized after deep-water conditions established in Lake Ohrid. As the lake deepens, we also see a switch in the macroevolutionary trade-off, resulting in a transition from a volatile assemblage of short-lived endemic species to a stable community of long-lived species. Our results emphasize the importance of the interplay between environmental/climate change, ecosystem stability, and environmental limits to diversity for diversification processes. The study also provides a new understanding of evolutionary dynamics in long-lived ecosystems.

Ontology mapping for semantically enabled applications.

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential of semantically enabled or enriched applications and for meaningful insights, such as drug discovery, using machine-learning technologies. We discuss challenges and solutions for better ontology mappings, as well as how to select ontologies before their application. In addition, we describe tools and algorithms for ontology mapping, including evaluation of tool capability and quality of mappings. Finally, we outline the requirements for an ontology mapping service (OMS) and the progress being made towards implementation of such sustainable services.

Peripheral blood cell microRNA quantification during the first trimester predicts preeclampsia: Proof of concept.

OBJECTIVE: We investigated the capacity of microRNAs isolated from peripheral blood buffy coat collected late during the first trimester to predict preeclampsia. STUDY DESIGN: The cohort study comprised 48 pregnant women with the following pregnancy outcomes: 8 preeclampsia and 40 with normal delivery outcomes. Quantitative rtPCR was performed on a panel of 30 microRNAs from buffy coat samples drawn at a mean of 12.7±0.5 weeks gestation. MicroRNA Risk Scores were calculated and AUC-ROC calculations derived. RESULTS: The AUC-ROC for preeclampsia risk was 0.91 (p<0.0001). When women with normal delivery and high-risk background (those with SLE/APS, chronic hypertension and/or Type 2 Diabetes) were compared to women who developed preeclampsia but with a normal risk background (without these mentioned risk factors), preeclampsia was still predicted with an AUC-ROC of 0.92 (p<0.0001). CONCLUSION: MicroRNA quantification of peripheral immune cell microRNA provides sensitive and specific prediction of preeclampsia in the first trimester of pregnant women. With this study, we extend the range during which disorders of the placental bed may be predicted from early to the end of the first trimester. This study confirms that buffy coat may be used as a sample preparation.

Impacts of landscape remediation on the heavy metal pollution dynamics of a lake surrounded by non-ferrous smelter waste.

Heavy metal concentrations and potential bioavailability are reported for sediment in a shallow flood detention lake surrounded by reclaimed, smelter-contaminated land. A range of sediment column proxy indicators is used to explore changes in pollution dynamics with remediation. Sediment concentrations of Pb and Zn are high at approximately 600 and 20,000 mg kg(-1), respectively. Less than 7% of total Pb is potentially bioavailable following sequential extraction as opposed to 47% of Zn. Metal transfer mechanisms to lake sediment include detrital inputs, scavenging by particulates and biogeochemical precipitation. Sedimentary evidence indicates that detrital inputs to the lake declined following land reclamation after which it is proposed that dissolved inputs increased with leaching of reworked waste material. Whilst downcore metal profiles may be subject to post-depositional change, diatom analysis suggests more recent improvements in water quality. The potential for post-remediation pollution episodes relating to metal release from historic sedimentary stores should be considered in future remediation strategies.

Early first trimester peripheral blood cell microRNA predicts risk of preterm delivery in pregnant women: Proof of concept.

OBJECTIVE: We investigated the capacity of first trimester peripheral blood mononuclear cell (PBMC) microRNA to determine risk of spontaneous preterm birth among pregnant women. STUDY DESIGN: The study included 39 pregnant women with the following delivery outcomes: 25 with a full term delivery (38-42 weeks gestation) 14 with spontaneous preterm birth (<38 weeks gestation). Of the 14 women experiencing spontaneous preterm birth, 7 delivered at 34-<38 weeks gestation (late preterm) and 7 delivered at <34 weeks gestation (early preterm). Samples were collected at a mean of 7.9±3.0 weeks gestation. Quantitative rtPCR was performed on 30 selected microRNAs. MicroRNA Risk Scores were calculated and Area-Under the Curve-Receiver-Operational-Characteristic (AUC-ROC) curves derived. RESULTS: The AUC-ROC for the group delivering preterm (<38 weeks) was 0.95 (p>0.0001). The AUC-ROC for early preterm group (<34 weeks) was 0.98 (p<0.0001) and the AUC-ROC for the late preterm group (34-<38 weeks) was 0.92 (p<0.0001). CONCLUSION: Quantification of first trimester peripheral blood PBMC MicroRNA may provide sensitive and specific prediction of spontaneous preterm birth in pregnant women. Larger studies are needed for confirmation.

Developing timely insights into comparative effectiveness research with a text-mining pipeline.

Comparative effectiveness research (CER) provides evidence for the relative effectiveness and risks of different treatment options and informs decisions made by healthcare providers, payers, and pharmaceutical companies. CER data come from retrospective analyses as well as prospective clinical trials. Here, we describe the development of a text-mining pipeline based on natural language processing (NLP) that extracts key information from three different trial data sources: NIH ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP), and Citeline Trialtrove. The pipeline leverages tailored terminologies to produce an integrated and structured output, capturing any trials in which pharmaceutical products of interest are compared with another therapy. The timely information alerts generated by this system provide the earliest and most complete picture of emerging clinical research.

Coastal Evolution in a Mediterranean Microtidal Zone: Mid to Late Holocene Natural Dynamics and Human Management of the Castelló Lagoon, NE Spain.

We present a palaeoenvironmental study of the Castelló lagoon (NE Spain), an important archive for understanding long-term interactions between dynamic littoral ecosystems and human management. Combining geochemistry, mineralogy, ostracods, diatoms, pollen, non-pollen palynomorphs, charcoal and archaeo-historical datasets we reconstruct: 1) the transition of the lagoon from a marine to a marginal environment between ~3150 cal BC to the 17th century AD; 2) fluctuations in salinity; and 3) natural and anthropogenic forces contributing to these changes. From the Late Neolithic to the Medieval period the lagoon ecosystem was driven by changing marine influence and the land was mainly exploited for grazing, with little evidence for impact on the natural woodland. Land-use exploitation adapted to natural coastal dynamics, with maximum marine flooding hampering agropastoral activities between ~1550 and ~150 cal BC. In contrast, societies actively controlled the lagoon dynamics and become a major agent of landscape transformation after the Medieval period. The removal of littoral woodlands after the 8th century was followed by the expansion of agrarian and industrial activities. Regional mining and smelting activities polluted the lagoon with heavy metals from the ~11th century onwards. The expansion of the milling industry and of agricultural lands led to the channelization of the river Muga into the lagoon after ~1250 cal AD. This caused its transformation into a freshwater lake, increased nutrient load, and the infilling and drainage of a great part of the lagoon. By tracking the shift towards an anthropogenically-controlled system around ~750 yr ago, this study points out Mediterranean lagoons as ancient and heavily-modified systems, with anthropogenic impacts and controls covering multi-centennial and even millennial timescales. Finally, we contributed to the future construction of reliable seashell-based chronologies in NE Spain by calibrating the Banyuls-sur-Mer ΔR offset with ceramic imports from the Emporiae archaeological site.

First-trimester maternal cell microRNA is a superior pregnancy marker to immunological testing for predicting adverse pregnancy outcome.

Patients at risk of immune-mediated pregnancy complications have historically relied on the use of peripheral blood immunological assays for diagnosis and pregnancy monitoring. However, these tests often fail to identify many at-risk patients, achieving moderately predictive receiver operating characteristic (ROC) curve AUCs of 0.60-0.70. We previously demonstrated that a microRNA panel comprising 30 microRNAs successfully predicts pregnancy outcome in the first trimester. In our current study we constructed a smaller, more clinically useful seven-microRNA panel from the original panel of 30 microRNAs with equivalent sensitivity and specificity. To select optimal microRNAs for a smaller panel, quantitative RT-PCR on 30 microRNAs was first performed on 48 patients (191 samples) with concurrent immunological testing: TNFα/Il-10 ratio, IFNγ/Il-10, CD56+16+%, NK 50:1 cytotoxicity and T regulatory cells. MicroRNAs were separated into clusters associated with: Th1/Th2 response; T regulatory cell percent; pregnancy risk; treatment response. Seven most differentially expressed microRNAs were selected. The seven microRNA scoring system was then applied to 39 patient samples in the first trimester of pregnancy (19 healthy deliveries, 8 miscarriages, 12 preeclampsia [7 late-onset and 5 early-onset]) and 20 samples in the preconception period (2-10 weeks before conception). Predictive value was assessed. ROC curves for the seven-microRNA panel achieved AUC 0.92 for miscarriage and 0.90 for preeclampsia (blood drawn 34.9±19.2 days post-implantation). For samples measured preconception, ROC curve analysis demonstrated AUC 0.81 for adverse pregnancy outcome. Maternal PBMC microRNA can identify high-risk patients likely to benefit from immunotherapy with improved sensitivity and specificity compared with standard immune assays.

The influence of oxygen and carbon dioxide on diving behaviour of tufted ducks, Aythya fuligula.

While optimal diving models focus on the diver's oxygen (O(2)) stores as the predominant factor influencing diving behaviour, many vertebrate species surface from a dive before these stores are exhausted and may commence another dive well after their O(2) stores have been resaturated. This study investigates the influence of hypoxia and also hypercapnia on the dive cycle of tufted ducks, Aythya fuligula, in terms of surface duration and dive duration. The birds were trained to surface into a respirometer box after each dive to a feeding tray so that rates of O(2) uptake (VO2) and carbon dioxide output (VCO2) at the surface could be measured. Although Vco2 initially lagged behind Vo2, both respiratory gas stores were close to full adjustment after the average surface duration, indicating that they probably had a similar degree of influence on surface duration. Chemoreceptors, which are known to influence diving behaviour, detect changes in O(2) and CO(2) partial pressures in the arterial blood. Thus, the need to restore blood gas levels appears to be a strong stimulus to continue ventilation. Mean surface duration coincided with peak instantaneous respiratory exchange ratio due to predive anticipatory hyperventilation causing hypocapnia. For comparison, the relationship between surface duration and O(2) uptake in reanalysed data for two grey seals indicated that one animal tended to dive well after fully restocking its O(2) stores, while the other dived at the point of full restocking. More CO(2) is exchanged than O(2) in tufted ducks during the last few breaths before the first dive of a bout, serving to reduce CO(2) stores and suggesting that hypercapnia rather than hypoxia is more often the limiting factor on asphyxia tolerance during dives. Indeed, according to calculations of O(2) stores and O(2) consumption rates over modal diving durations, a lack of O(2) does not seem to be associated with the termination of a dive in tufted ducks. However, factors other than CO(2) are also likely to be important, and perhaps more so, such as food density and rate of food ingestion. Because some predictive success has been demonstrated for optimal diving models, they should continue to incorporate O(2) stores as a variable, but their validity is likely to be improved by also focusing on CO(2) stores.

First trimester PBMC microRNA predicts adverse pregnancy outcome.

PROBLEM: Prior to the end of the first trimester, pathogenic mechanisms may commit pregnancies to adverse outcome such as pre-eclampsia and miscarriage. A long-term search for biomarkers predicting these adverse outcomes has not identified any that reliably succeed prior to the beginning of the second trimester. MicroRNAs, with their important role as regulators of signaling and metabolic pathways within living cells, may offer a new approach. METHODS: Optimal maternal PBMC microRNA markers were investigated using a series of sequential experiments, and 30 microRNAs were selected based on these results. Quantitative RT-PCR was then performed on these 30 microRNAs for 39 patients [19 healthy deliveries, 12 pre-eclampsia (seven late onset and five early onset) and eight miscarriages] during the first trimester of pregnancy. Results were scored, and their predictive values assessed. RESULTS: MicroRNA quantification in the early first trimester (mean 34.9 ± 19.2 days post-implantation) predicted miscarriage and late pre-eclampsia with a P value of P < 0.0001 and achieved an AUC of 0.90 for miscarriage and 0.90 for late pre-eclampsia. CONCLUSION: MicroRNA quantification of maternal blood cells offers the clinician a single test result that is simple to interpret and available much earlier in pregnancy than previously obtainable. In addition, it is the only early pregnancy marker, to date, that can successfully predict late pre-eclampsia. Although the studies that we report are preliminary, we hope that future research will build upon our discoveries and enhance the power of maternal cell microRNA to predict adverse pregnancy outcome in the clinic.

The multiple faces of the decidual natural killer cell.

The decidual NK (dNK) cell is called on to support placental growth by providing an array of growth factors that directly transform the spiral artery and direct trophoblast invasion. Successful transformation is dependent upon adequate stimulation paradoxically stimulating the cell for placental support rather than cytotoxicity. With the identification of its supportive role, the presence of an intact cytotoxic mechanism has been confusing. Investigators have found that the cell remains fully capable of cytotoxic responses particularly in response to pathogen-specific signals. We postulate a dual threshold model where moderate stimulation results in release of stimulatory factors supporting placentation while intense stimulation, particularly triggered through pathogen-specific receptors, restores the cell to its protective, cytotoxic, role. Individual dNK cells mature attaining the capacity to respond to the delivery of cognate signals. The process, known as 'licensing' tunes responsiveness to the degree to which stochastically selected inhibitory receptors block cytotoxic response to self. A changing licensing milieu within the decidua may result in altered and unsuitable receptor expression. We postulate that a heterogeneous population of dNK cells where cells inappropriately licensed for the milieu contributes to pathology.

The adventurous school.

This paper describes three schools that worked with their local communities to create opportunities for their children to learn how to be skillful adventurers in our complex and ever-changing world. Each involved learners fully in their learning, clarifying what learning means and enabling it to happen through real and purposeful experiences. Each worked proactively with their communities and took local control of designing and developing the curriculum.

Intravenous immunoglobulin for repeated IVF failure and unexplained infertility.

PROBLEM: We set out to determine whether intravenous immunoglobulin (IVIG) improves in vitro fertilization (IVF) success rates in women with a difficult history of multiple (≥ 2) prior IVF failures and /or 'unexplained' infertility. METHOD OF STUDY: A total of 229 women with multiple IVF failures (3.3 ± 2.1) and/or unexplained infertility (3.8 ± 2.7 years) were given IVIG on the day of egg retrieval, and the subsequent IVF success rates were compared with published success rates from the Canadian database (CARTR). RESULTS: The pregnancy rate per IVIG-treated cycle was 60.3% (138/229), and the live birth rate per IVIG-treated cycle was 40.2% (92/229). This is a significantly higher success rate compared to the Canadian average (30% live birth rate; CARTR statistics from 2010; P = 0.0012). In cases where a single embryo was transferred, pregnancy rate using IVIG was almost twofold the CARTR pregnancy rate [(61%(20/33) to 34.9% (428/1225)]. In cases where two high quality (≥ Grade 3) day 5 blastocysts were transferred, nearly a 100% pregnancy rate was achieved using IVIG (30/31). CONCLUSION: IVIG may be a useful treatment option for patients with previous IVF failure and/ or unexplained infertility. The data confirm previously published studies at other centers.

The adventurous school.

This paper describes three schools that worked with their local communities to create opportunities for their children to learn how to be skillful adventurers in our complex and ever-changing world. Each involved learners fully in their learning, clarifying what learning means and enabling it to happen through real and purposeful experiences. Each worked proactively with their communities and took local control of designing and developing the curriculum.

Die-off ratio correlates with increased TNF-α:IL-10 ratio and decreased IVF success rates correctable with humira.

BACKGROUND: Human embryos develop at varying rates in culture, with only a fraction of the eggs retrieved developing to 'transfer quality' embryos. We investigated whether the ratios between the number of eggs retrieved or the number of pro-nucleate embryos formed and the number of Day 3 embryos with ≥5 cells [oocyte 'die-off ratios' (DOR)] were correlated with the chance of IVF success, independent of other factors such as embryo grade score and patient's age. We also investigated what factors may be correlated with this ratio. METHODS: 608 IVF fresh cycles in subfertile women were retrospectively evaluated. For each cycle, an oocyte DOR number was calculated as follows: Number of eggs retrieved divided by the number of Day 3 embryos with ≥5 cells. This number was correlated with the subsequent success rates for the index cycles. A 'post-fertilization' or 'embryo' die-off ratio (EDOR; the number of pro-nucleate embryos/the number of day 3 embryos ≥5 cells) was also calculated. RESULTS: The oocyte DOR showed a reverse linear correlation with IVF live birth rate. Live birth rate = (-5.75; DOR) +71.6 (with DOR > 1; P ≤ 0.005; R = -0.87). In addition, the oocyte DOR continued to show an inverse correlation with success rates even when embryo quality and patient's age were held constant. The post-fertilization or EDOR also continued to show a statistically significant negative correlation with live birth rate (R = -0.91; P ≤ 0.01). The preconception TNF-α:IL-10 ratio, an immmunologic marker (drawn 3.3 ± 2.6 months preconception), was more strongly correlated with high oocyte DOR than either age or number of eggs retrieved (P = 0.04, 0.14, 0.72, respectively). When anti-TNF-α therapy (Humira) was given preconception, the oocyte DOR's negative effect on live birth rate was nearly eliminated (correlation coefficient between oocyte DOR and live birth rate: cycles using no Humira, R = -0.90, P ≤ 0.006; cycles using Humira, R = 0.25, P ≤ 0.55). CONCLUSIONS: In subfertile women undergoing IVF, the oocyte DOR may help predict IVF success rates. This factor may offer an additional tool to help improve implantation rate, clinical pregnancy rate, live birth rate, and live birth rate per embryo transferred for an upcoming IVF cycle. Although many mechanisms may contribute to the oocyte DOR's negative effect on IVF success rates, its correlation with elevated preconception TNF-α:IL-10 ratio and correction with Humira suggests a strong immunologic component that may be treatable.