Even forests that look green from space can show symptoms of impending decline.

Mathematical modeling and AI can pick out patterns preceding epidemics that human brains can’t readily discern.

Veteran guard Reggie Jackson always wanted to play alongside Paul George. He gets his chance now with a Clippers team aiming for an NBA title.

A model predicts COVID-19 deaths in the U.S. will drop to zero by June. Another suggests without a vaccine, the coronavirus will be with us for years.

The NHL hopes to complete its season after suspending play because of the coronavirus, but playing into the middle of the summer creates complications.

As U.S. faces its most trying coronavirus pandemic days, industry leaders imagine the future of travel.

With Tom Brady out of the picture, how will the Jets fare this season?

With Tom Brady out of the picture, how will the Jets fare this season?

Predicting the four acting races for the 2020 Oscars is easy this year, but there's still drama in the best picture race and others

Boss of Britain's busiest air hub calls for 'a common international standard for healthcare screening in airports'

'There is a large amount of pent-up demand, should health and travel restrictions allow it to return to the market,' said IATA's chief economist, Brian Pearce

Rangers take on Kilmarnock in the Scottish Premiership on Wednesday night, with Steven Gerrard looking to keep within touching distance of rivals Celtic. Express Sport delivers you all of the team news for the Gers, as well as the predicted line up for the clash, as Ryan Jack returns from injury.

Leeds face Huddersfield in the Championship on Saturday, as Marcelo Bielsa aims to continue his the Whites' superb form at Elland Road. We bring you the latest team news and predicted line up, as the manager makes a key decision on whether to drop striker Patrick Bamford, as Kiko Casilla remains banned.

NOSTRADAMUS is hailed as the world's greatest prophetic mind, with three predictions people think he got right. Did he predict the coronavirus outbreak?

Rangers take on Hamilton as boss Steven Gerrard will be looking to keep the pressure on Celtic in the Scottish Premiership.

Lewis Hamilton has enjoyed six years of success with Mercedes but Eddie Jordan thinks it's time for them to sell their F1 team.

Leeds United take on Hull City on Saturday and Whites boss Marcelo Bielsa faces an important decision after Kiko Casilla was issued an eight-match ban.

Celtic host Hearts as top takes on bottom in the Scottish Premiership, with Neil Lennon hoping to maintain his seven-point lead over title rivals Rangers. Express Sport is on hand to provide all of the Hoops' team news, as well the predicted line-up, as two stars return from injury.

Manchester City face Sheffield Wednesday in the FA Cup fifth round at Hillsborough on Wednesday night, and Pep Guardiola has a number of injury concerns for his starting XI. This is the Citizens' predicted line up, as Sergio Aguero could feature, while Claudio Bravo starts in goal.

The Masters was scheduled to take place this weekend until it was called off due to the coronavirus outbreak - but would Tiger Woods have defended his title?

Steven Gerrard believes Ryan Kent will get even better for Rangers as he’s not even fully fit yet.

BRITAIN'S summer holiday destinations will face some of the biggest economic hits of the coronavirus pandemic with fears of massive job losses in coastal communities, a study has claimed.

Leeds face Middlesbrough in the Championship on Wednesday evening, with Marcelo Bielsa hoping to continue the Whites' good form after back-to-back wins. Express Sport brings you the latest team news and injury updates, with concerns over the inclusion of Kalvin Phillips and Kiko Casilla in the manager's starting XI.

THE SPFL title race is hotting up and a super computer has given us an idea of how the season may pan out.

HOROSCOPE: Horoscopes for this week for all 12 star signs have been shared by Russell Grant. What does the astrology forecast for your sign predict? Check the reading here.

Leeds United's promotion hopes have been thrown into chaos after the coronavirus caused the EFL to suspend all leagues, but the final Championship table has been predicted by a supercomputer. Will Marcelo Bielsa's side finally return to the Premier League, and who will be relegated?

Scientists are tracing infections by analysing sewage samples from water treatment works.

Digital transformation has just begun.

Not a single industry is safe from the unstoppable wave of digitization that is sweeping through finance, retail, healthcare, and more.

In 2020, we expect to see even more transformative developments that will change our businesses, careers, and lives.

To help you stay ahead of the curve, Business Insider Intelligence has put together a list of 30 Big Tech Predictions for 2020 across Banking, Connectivity & Tech, Digital Media, Payments & Commerce, Fintech, and Digital Health.

This exclusive report can be yours for FREE today.

Join the conversation about this story »

This past year, I predicted the fall of both Zuck and Trump, not to mention the triumph of cannabis and rationale markets. But in 2019, the sociopaths won – bigly. Damn, was I wrong. One year ago this week, I sat down to write my annual list of ten or so predictions for the coming … Continue reading "Predictions Review: Trump, Zuck Crush My Optimism In 2019"

A new year brings another run at my annual predictions: For 17 years now, I’ve taken a few hours to imagine what might happen over the course of the coming twelve months. And my goodness did I swing for the fences last year — and I pretty much whiffed. Batting .300 is great in the majors, but it … Continue reading "Predictions 2020: Facebook Caves, Google Zags, Netflix Sells Out, and Data Policy Gets Sexy"

The following article, Rush Limbaugh Predicts Joe Biden Won’t Be The Dem Nominee: “Something’s Gonna Happen”, was first published on 100PercentFedUp.com.

Is Joe Biden going to become the Democrat nominee and run against Trump in the fall?

Continue reading: Rush Limbaugh Predicts Joe Biden Won’t Be The Dem Nominee: “Something’s Gonna Happen” ...

Members Event

Event participants

Anders Fogh Rasmussen, Secretary-General, North Atlantic Treaty Organization (NATO)
Chair: Robin Niblett, Director, Chatham House 

Yu Xue
Sep 1, 2008; 7:1598-1608
Research

7 November 2019

1 April 2020

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.

In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.

Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.

Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.

Storm surge is often the most devastating part of a hurricane. Mathematical models used to predict surge must incorporate the effects of winds, atmospheric pressure, tides, waves and river flows, as well as the geometry and topography of the coastal ocean and the adjacent floodplain. Equations from fluid dynamics describe the movement of water, but most often such huge systems of equations need to be solved by numerical analysis in order to better forecast where potential flooding will occur. Much of the detailed geometry and topography on or near a coast require very fine precision to model, while other regions such as large open expanses of deep water can typically be solved with much coarser resolution. So using one scale throughout either has too much data to be feasible or is not very predictive in the area of greatest concern, the coastal floodplain. Researchers solve this problem by using an unstructured grid size that adapts to the relevant regions and allows for coupling of the information from the ocean to the coast and inland. The model was very accurate in tests of historical storms in southern Louisiana and is being used to design better and safer levees in the region and to evaluate the safety of all coastal regions. For More Information: A New Generation Hurricane Storm Surge Model for Southern Louisiana, by Joannes Westerink et al.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

(University of Warwick) A microbial community is a complex, dynamic system composed of hundreds of species and their interactions, they are found in oceans, soil, animal guts and plant roots. Each system feeds the Earth's ecosystem and their own growth, as they each have their own metabolism that underpin biogeochemical cycles. Researchers from the School of Life Sciences at the University of Warwick have produced an extendable thermodynamic model for simulating the dynamics of microbial communities.

(University of Colorado at Boulder) CU Boulder researchers have developed a method that could enable scientists to accurately forecast ocean acidity up to five years in advance. This would enable fisheries and communities that depend on seafood negatively affected by ocean acidification to adapt to changing conditions in real time, improving economic and food security in the next few decades.

Abby Joseph Cohen and Alexis Crow share insights on the economic impact of COVID-19 in a discussion moderated by Pierre Yared. 

9 August 2019

The use of AI in counterterrorism is not inherently wrong, and this paper suggests some necessary conditions for legitimate use of AI as part of a predictive approach to counterterrorism on the part of liberal democratic states.

1 April 2020

The purpose of this study was to assess the predictive and prognostic value of interim FDG PET (iPET) in evaluating early response to immuno-chemotherapy after two cycles (PET-2) in diffuse large B-cell lymphoma (DLBCL) by applying two different methods of interpretation: the Deauville visual five-point scale (5-PS) and a change in standardised uptake value by semi-quantitative evaluation. Methods: 145 patients with newly diagnosed DLBCL underwent pre-treatment PET (PET-0) and PET-2 assessment. PET-2 was classified according to both the visual 5-PS and percentage SUV changes (SUV). Receiver operating characteristic (ROC) analysis was performed to compare the accuracy of the two methods for predicting progression-free survival (PFS). Survival estimates, based on each method separately and combined, were calculated for iPET-positive (iPET+) and iPET-negative (iPET–) groups and compared. Results: Both with visual and SUV-based evaluations significant differences were found between the PFS of iPET– and iPET+ patient groups (p<0.001). Visually the best negative (NPV) and positive predictive value (PPV) occurred when iPET was defined as positive if Deauville score 4-5 (89% and 59%, respectively). Using the 66% SUV cut-off value, reported previously, NPV and PPV were 80 and 76%, respectively. SUV at 48.9% cut-off point, reported for the first time here, produced 100% specificity along with the highest sensitivity (24%). Visual and semi-quantitative SUV<48.9% assessment of each PET-2 gave the same PET-2 classification (positive or negative) in 70% (102/145) of all patients. This combined classification delivered NPV and PPV of 89% and 100% respectively, and all iPET+ patients failed to achieve or remain in remission. Conclusion: In this large consistently treated and assessed series of DLBCL, iPET had good prognostic value interpreted either visually or semi-quantitatively. We determined that the most effective SUV cut-off was at 48.9%, and that when combined with visual 5-PS assessment, a positive PET-2 was highly predictive of treatment failure.

Purpose: The aim of this retrospective multicentric study was to develop and evaluate a prognostic FDG PET/CT radiomics signature in early-stage non-small cell lung cancer (NSCLC) patients treated with stereotactic radiotherapy (SBRT). Material and Methods: Patients from 3 different centers (n = 27, 29 and 8) were pooled to constitute the training set, whereas the patients from a fourth center (n = 23) were used as the testing set. The primary endpoint was local control (LC). The primary tumour was semi-automatically delineated in the PET images using the Fuzzy locally adaptive Bayesian algorithm, and manually in the low-dose CT images. A total of 184 IBSI-compliant radiomic features were extracted. Seven clinical and treatment parameters were included. We used ComBat to harmonize radiomic features extracted from the four institutions relying on different PET/CT scanners. In the training set, variables found significant in the univariate analysis were fed into a multivariate regression model and models were built by combining independent prognostic factors. Results: Median follow-up was 21.1 (1.7 – 63.4) and 25.5 (7.7 – 57.8) months in training and testing sets respectively. In univariate analysis, none of the clinical variables, 2 PET and 2 CT features were significantly predictive of LC. The best predictive models in the training set were obtained by combining one feature from PET, namely information correlation 2 (IC2) and one from CT (Flatness), reaching a sensitivity of 100% and a specificity of 96%. Another model combining 2 PET features (IC2 and Strength), reached sensitivity of 100% and specificity of 88%, both with an undefined hazard ratio (HR) (p<0.001). The latter model obtained an accuracy of 0.91 (sensitivity 100%, specificity 81%), with a HR undefined (P = 0.023) in the testing set, however other models relying on CT radiomics features only or the combination of PET and CT features failed to validate in the testing set. Conclusion: We showed that two radiomic features derived from FDG PET were independently associated with LC in patients with NSCLC undergoing SBRT and could be combined in an accurate predictive model. This model could provide local relapse-related information and could be helpful in clinical decision-making.

We performed post-hoc analyses on the utility of pre-therapeutic and early interim ⁶⁸Ga-DOTA-Tyr3-octreotide (⁶⁸Ga-DOTATOC) positron emission tomography (PET) tumor uptake and volumetric parameters and a recently proposed biomarker, the inflammation-based index (IBI), for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumor (NET) patients treated with ⁹⁰Y-DOTATOC in the setting of a prospective phase II trial. Methods: Forty-three NET patients received up to four cycles of 1.85 GBq/m²/cycle ⁹⁰Y-DOTATOC with a maximal kidney biologic effective dose of 37 Gy. All patients underwent a ⁶⁸Ga-DOTATOC PET/computed tomography (CT) at baseline and seven weeks after the first PRRT cycle. ⁶⁸Ga-DOTATOC-avid tumor lesions were semi-automatically delineated using a customized standardized uptake value (SUV) threshold-based approach. PRRT response was assessed on CT using RECIST 1.1. Results: Median progression-free survival (PFS) and overall survival (OS) were 13.9 and 22.3 months, respectively. An SUVmean higher than 13.7 (75th percentile (P75)) was associated with better survival (hazard ratio (HR) 0.45; P = 0.024), whereas a ⁶⁸Ga-DOTATOC-avid tumor volume higher than 578 ml (P75) was associated with worse OS (HR 2.18; P = 0.037). Elevated baseline IBI was associated with worse OS (HR 3.90; P = 0.001). Multivariate analysis corroborated independent associations between OS and SUVmean (P = 0.016) and IBI (P = 0.015). No significant correlations with PFS were found. A composite score based on SUVmean and IBI allowed to further stratify patients in three categories with significantly different survival. On early interim PET, a decrease in SUVmean of more than 17% (P75) was associated with worse survival (HR 2.29; P = 0.024). Conclusion: Normal baseline IBI and high ⁶⁸Ga-DOTATOC tumor uptake predict better outcome in NET patients treated with ⁹⁰Y-DOTATOC. This can be used for treatment personalization. Interim ⁶⁸Ga-DOTATOC PET does not provide information for treatment personalization.

Prediction of post-operative pulmonary function in lung cancer patients before tumor resection is essential for patient selection for surgery and is conventionally done with a non-imaging segment counting method (SC) or a two-dimensional planar lung perfusion scintigraphy (PS). The purpose of this study was to compare quantitative analysis of PS to single photon emission computed tomography/computed tomography (SPECT/CT) and to estimate the accuracy of SC, PS and SPECT/CT in predicting post-operative pulmonary function in patients undergoing lobectomy. Methods: Seventy-five non-small cell lung cancer (NSCLC) patients planned for lobectomy were prospectively enrolled (68% males, average age 68.1±8 years ). All patients completed pre-operative forced expiratory volume capacity (FEV1), diffusing capacity of the lung for carbon monoxide (DLCO), Tc99m-MAA lung perfusion scintigraphy with PS and SPECT/CT quantification. A subgroup of 60 patients underwent video-assisted thoracoscopic (VATS) lobectomy and measurement of post-operative FEV1 and DLCO. Relative uptake of the lung lobes estimated by PS and SPECT/CT were compared. Predicted post-operative FEV1 and DLCO were derived from SC, PS and SPECT/CT. Prediction results were compared between the different methods and the true post-operative measurements in patients who underwent lobectomy. Results: Relative uptake measurements differed significantly between PS and SPECT/CT in right lung lobes, with a mean difference of -8.2±3.8, 18.0±5.0 and -11.5±6.1 for right upper, middle and lower lobes respectively (p<0.001). The differences between the methods in the left lung lobes were minor with a mean difference of -0.4±4.4 (p>0.05) and -2.0±4.0 (p<0.001) for left upper and lower lobes respectively. No significant difference and strong correlation (R=0.6-0.76, p<0.001) were found between predicted post-operative lung function values according to SC, PS, SPECT/CT and the actual post-operative FEV1 and DLCO. Conclusion: Although lobar quantification parameters differed significantly between PS and SPECT/CT, no significant differences were found between the predicted post-operative lung function results derived from these methods and the actual post-operative results. The additional time and effort of SPECT/CT quantification may not have an added value in patient selection for surgery. SPECT/CT may be advantageous in patients planned for right lobectomies but further research is warranted.

Introduction: To use positron emission tomography coupled with computed tomography (¹⁸FDG-PET/CT) to identify a high-risk subgroup requiring therapeutic intensification among patients with locally advanced cervical cancer (LACC) and para-aortic lymph node (PALN) involvement. Methods: In this retrospective multicentric study, patients with LACC and PALN involvement concurrently treated with chemoradiotherapy and extended-field radiotherapy (EFR) between 2006 and 2016 were included. A senior nuclear medicine specialist in PET for gynaecologic oncology reviewed all ¹⁸FDG-PET/CT scans. Metabolic parameters including maximum standardised uptake value (SUV_max), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were determined for the primary tumour, pelvic lymph nodes and PALN. Associations between these parameters and overall survival (OS) were assessed with Cox's proportional hazards model. Results: Sixty-eight patients were enrolled in the study. Three-year OS was 55.5% (95% CI (40.8-68.0)). When adjusted for age, stage and histology, pelvic lymph node TLG, PALN TLG and PALN SUV_max were significantly associated with OS (p<0.005). Conclusion: FDG-PET/CT was able to identify predictors of survival in the homogeneous subgroup of patients with LACC and PALN involvement, thus allowing therapeutic intensification to be proposed.