Results showed statistically significant reductions among sports bettors wagering in online casinos. This indicates that there was no conversion of money spent from sports betting to online casino games, at least for this particular online gambling operator. The findings suggest that there was a significant decrease in the amount of money wagered by sports bettors during the COVID-19 pandemic (compared with before it) and that sports bettors did not switch to playing more online casino games and that there was also a significant reduction in playing online casino games among sports bettors.The novel coronavirus-2019 (COVID-19) pandemic has had major impacts on most societies worldwide including the cancelation and postponement of sports events. This has had a major impact on the sports betting industry. The present study is first to investigate the behavior of a sample of online sports bettors before and after COVID-19 measures were put in place by European governments. The authors were given access to the player data by a large European online gambling operator comprising players from Sweden, Germany, Finland, and Norway. The behavioral change of the sports bettors before March 7 and after March 7 (2020) was computed. All sports bettors who placed at least one wager in at least 5 calendar weeks out of the 10 possible calendar weeks between January 1 and March 7 ( The World Health Organization 2020) declared the outbreak of the novel coronavirus-2019 (COVID-19) a pandemic on March 11 (2020) (Cucinotta and Vanelli  declaredThe cancelation and postponement of sports events in Europe (and elsewhere) has consequently had a major impact on the sports betting industry. Regulators and business experts have speculated about how players are reacting towards the fact they can no longer bet on sports games. Some regulators, policymakers, and treatment organizations have speculated in the mass media that individuals will gamble more online because of being in lockdown and spending so much of their daily lives at home and indoors Davis . The samBehavioral tracking data is increasingly being used for research purposes in the gambling studies field  was computed. In order to select regular sports bettors, the authors selected all sports bettors who placed at least one wager in at least 5 calendar weeks out of the 10 possible calendar weeks between January 1 (2020) and March 7 (2020). This resulted in a sample of 5396 sports bettors. The amount of money wagered on sports events and online casino games before and after March 7 (2020) was computed.The product portfolio consists of sports betting and online casino games. Behavioral tracking data were available for a 4-month period from January 1 (2020) to April 30 (2020). The dataset allowed the authors to identify players who had wagered on sports or played online casino games. The authors computed the number of active sports betting players as well as the daily total bet across all sports betting players for each day between January 1 and April 30 (2020). The authors analyzed the data between January 1 and March 7 before the COVID-19 pandemic and data between March 7 and April 20 during the COVID-19 pandemic. The authors used the McNemar test to compare the changes in gambling participation before and after COVID-19. The McNemar test results in a chi-square test statistic and is applied for repeated measure comparisons with categorical data  was computed. In order to select regular sports bettors, the authors selected all players who placed at least one wager in at least 5 calendar weeks out of the 10 possible calendar weeks between January 1 (2020) and March 7 (2020). This resulted in a sample of 5396 sports bettors. The amount of money wagered on sports events and online casino games before and after March 7 (2020) was computed.Table p -values from the respective McNemar tests for the six groups are as follows: sports wagers during 5 separate calendar weeks, χ2 = 83.59, p < 0.001; 6 weeks, χ2 = 56.99, p < 0.001, 7 weeks, χ2 = 45.66, p < 0.001; 8 weeks, χ2 = 18.04, p < 0.001; 9 weeks, χ2 = 13.32, p < 0.001; and 10 weeks, χ2 = 5.05, p = 0.025. Table The changes between the two percentages (sports bettors playing online casino games before and after March 7) showed a statistically significant reduction in wagering among sports bettors in online casino games for all six groups. The chi-square values and p values from the respective McNemar tests are as follows: group 1, χ2 = 12.34, p < 0.001; group 2, χ2 = 16.44, p < 0.001; group 3 χ2 = 22.48, p < 0.001; group 4 χ2 = 12.99 p = 0.0003; group 5 χ2 = 23.47, p < 0.0001; group 6 χ2 = 28.84, p < 0.0001; group 7 χ2 = 22.36, p < 0.0001; group 8 χ2 = 42.17, p < 0.0001; group 9 χ2 = 13.51, p = 0.0002; and group 10 χ2 = 11.82, p = 0.0005. Table Table The present study investigated the online casino gambling behavior of a European online gambling operator’s sports bettors before and during the COVID-19 pandemic. Results clearly showed that the daily active number of sports bettors and amount wagered on sports significantly decreased at around March 10  to be defined as a regular sports bettor. In all of the groups, the percentage of sports bettors who played online casino games was significantly lower after March 7 compared with before March 7. This means that not only did players wager less on sports (most events had been canceled by March 7), but they also wagered less on online casino games. This indicates that there was no conversion of money spent from sports betting to online casino, at least for this particular online gambling operator.The lowest difference between percentage of online casino players before and after March 7 occur red among the two groups of sports bettors who wagered for 9 out of 10 calendar weeks and all 10 calendar weeks. The percentage of sports bettors who played online casino games before March 7 was 78% and after March 7 was 71% for those who wagered in 9 calendar weeks. The percentage of sports bettors who played online casino games before March 7 was 79% and after March 7 was 76% for the ones who wagered in 10 calendar weeks. Both differences were statistically significant, but of lower significance than for sports bettors who wagered in only 5 calendar weeks. The respective percentages for those who only wagered in 5 out of 10 calendar weeks were 76% before March 7 and 60% after March 7.Although online casino gambling did not become more frequent, it appears that more frequent sports bettors also maintained their online casino gambling, whereas less frequent sports bettors were more likely to stop gambling altogether. This conclusion does not apply to sports betting gambling intensity. Table The ratio of the amount of money wagered on online casino games per player before and after March 7 was also computed. Table The present study includes some limitations that should be taken into account when interpreting the findings. Firstly, the results of present study were derived from data from a single European online gambling operator’s player base comprising four European nationalities . This online gambling operator’s player base is from specific countries, and players from other countries might have gambled differently during the COVID-19 lockdown and the lack of sports events to wager upon. Secondly, the totality of gambling behavior among the participants is unknown because the dataset only includes the gambling behavior of the participants at this specific online gambling operator. Thirdly, there is a possibility that some accounts may have been used by more than one gambler  although the number of occurrences is likely to be low. Fourthly, the study’s dataset is derived from the time period from January to April 2020 (inclusive). Because the lockdown as a consequence of the COVID-19 pandemic was still active in many countries as of April 30 (and most sports events were still postponed or canceled), sports bettors may have started to play casino games more intensely after April 30.Findings from the present study suggest that there is no relationship between the lack of sports betting events for gamblers to wager upon and increased frequency and intensity of online casino gambling. Overall, the frequency of wagering upon online casino games by online sports bettors before COVID-19-related lockdown significantly decreased during the COVID-19 pandemic period. However, less frequent (but regular) online sports bettors significantly decreased the amount of money wagered upon online casino games more than more frequent (regular) online sports bettors. Frequent online sports bettors wagering upon online casino games stayed approximately the same before and during the COVID-19 pandemic.These findings suggest that the speculations that individuals may spend more time and money gambling online as a consequence of being confined in their house for long periods of time appear unfounded. The decrease in overall gambling might be due to a number of factors including individuals having less money to gamble because their occupational earning potential has been lower during the pandemic, individuals not wanting to gamble in front of their family members, or individuals spending more time on other activities such as spending “quality time” with their families or finally having the time to do bigger jobs around the house and garden . The present study is the first to empirically investigate whether wagering increases or decreases among gamblers  during a period when many individuals are housebound during the COVID-19 pandemic-related lockdowns.


To evaluate an algorithm for calibrationless parallel imaging to reconstruct undersampled parallel transmit field maps for the body and brain.Using a combination of synthetic data and in vivo measurements from brain and body, 3 different approaches to a joint transmit and receive low-rank tensor completion algorithm are evaluated. These methods included: 1) virtual coils using the product of receive and transmit sensitivities, 2) joint-receiver coils that enforces a low rank structure across receive coils of all transmit modes, and 3) transmit low rank that uses a low rank structure for both receive and transmit modes simultaneously. The performance of each is investigated for different noise levels and different acceleration rates on an 8-channel parallel transmit 7 Tesla system.The virtual coils method broke down with increasing noise levels or acceleration rates greater than 2, producing normalized RMS error greater than 0.1. The joint receiver coils method worked well up to acceleration factors of 4, beyond which the normalized RMS error exceeded 0.1. Transmit low rank enabled an eightfold acceleration, with most normalized RMS errors remaining below 0.1.This work demonstrates that undersampling factors of up to eightfold are feasible for transmit array mapping and can be reconstructed using calibrationless parallel imaging methods. To generate subject-specific pulse designs, the transmit fields are measured for each subject and transmit channel, a time-consuming process in cardiac imaging, for example.8 This work investigates the acceleration of pTx field mapping for streamlining the use of pTx in MR imaging.Parallel transmit (pTx) technology mitigates transmit field heterogeneity11 Relative mapping is only valid when the excitation flip angle is both large enough to generate sufficient signal (greater than the noise) and small enough that the signal is proportional to B1+.12 Whereas this requires fewer images than absolute B1+ mapping,10 it still typically results in a scan time cost that scales with the number of transmit channels.The minimum requirement for field mapping is to characterize the relative magnitudes and phases of the transmit channels (relative maps). Relative maps are analogue to coil sensitivities in parallel imaging and are measured by transmitting in different transmit configurations, usually 1 channel at a time, while acquiring data on all receive channels simultaneously.13). In the heart, gating to cardiorespiratory motion increases the measurement time by at least fivefold for mapping transmit fields (assuming a respiratory efficiency of 50% and cardiac acquisition window of 400 ms). Either multiple breathholds or freebreathing using self-gating14 can be used to cover the whole heart, which takes about 3 and 6 min, respectively.As demonstrated by Padormo et al., the same k-space calibration data can be used to estimate both receive sensitivities and transmit sensitivities 17 method uses a projection-onto-sets algorithm with singular value thresholding to recover missing k-space data by alternating between enforcing data consistency and low-rank Hankel matrix structure without the need of any fully sampled calibration region. Simultaneous autocalibrating and k-space estimation (SAKE), and related methods such as Low-rank modeling of local k-space neighborhoods with parallel imaging (P-LORAKS)16 or annihilating filter based low-rank Hankel matrix approach (ALOHA),19 exploit redundancies that are present when Hankel matrices are combined across multiple coils. This enables a low-rank representation of the data to effectively constrain undersampled data recovery. In fact, these approaches are also similar to methods such as parallel imaging using eigenvector maps (ESPIRiT)20 and PRIMO,13 which form very similar low-rank Hankel-structured matrices, except that these latter methods work on fully sampled data. A comprehensive review of low-rank Hankel methods in MR image reconstruction can be found in Ref. 21.To reduce measurement times, accelerated imaging techniques can be used to recover pTx field maps from under-sampled (k-space) measurements. Accelerating the pTx field calibration will both increase the scan time available for diagnostic imaging and streamline the pTx adjustments. In order to recover missing k-space data, a calibrationless parallel imaging approach can be used, for example, with prior knowledge about the low-rank Hankel (or block-Hankel) structure of matrices formed from local k-space neighborhoods.24 In this work a multi-dimensional tensor representation of both transmit and receive field dimensions is evaluated. This approach exploits varying undersampling patterns across different transmit encodings and enables information sharing across these encodings. We investigate, in simulations and experimental data in the body and the brain, the acceleration factors achievable with this approach and demonstrate that undersampling factors of up to 8× are feasible with our proposed method.In this work, we investigate the extension of these calibrationless parallel imaging approaches to recover undersampled relative transmit field maps using structured low rank tensor completion. We build on previous work that leverages image redundancy across multiple dimensions or encodings, for example.22.120 take k-space data and through the application of a kernel transform form a block-Hankel matrix representation. Subspace identification is performed through low-rank reconstruction of missing samples  or SVD-based singular value truncation (ESPIRiT). PRIMO13 extends ESPIRiT to include transmit (Tx) sensitivities, which is achieved by concatenating the transmit and receive sensitives along different axes of the block-Hankel matrix. The time interleaved acquisition of modes (TIAMO)25 method harnesses transmit sensitives in the image reconstruction using different transmit modes (sensitives) as virtual receive channels, which results in a number of virtual receiver channels that are the product of receive channels and transmit modes. We refer to these methods below as virtual coil (VC) for the latter and PRIMO for the former.Simultaneous autocalibrating and k-space estimation and the subspace identification part of ESPIRiT𝒟 ∈ ℂkxN ×kyN ×RxN ×TxN, where the fourth-order tensor  𝒟 is transformed to another fourth-order tensor ℋ ∈ ℂN1 ×N2 ×RxN ×TxN with block-Hankel frontal slices. That is, for each transmit and receive pair, the 2D k-space is transformed to a 2D block-Hankel matrix for which the “frontal slices” refers to the fact that the block-Hankel matrix is defined by the first 2 indices of the tensor.Here we consider the VC and PRIMO representations to be special cases of a block-Hankel tensor formed from the multi-dimensional data N1 × N2 matrix by rastering over k-space with a kernel of dimension N1 = m × n , resulting in N2 = (kxN − m + 1) · (kyN − n + 1) distinct kernel vectors. This is done for every transmit and receive pair, which results in the tensor ℋ =T (𝒟), as demonstrated in The linear operator: We considered 3 different unfoldings of this tensor:ℋ, we can construct the matrix corresponding to the interpretation of every transmit and receive pair as a unique receive map by applying a particular unfolding of the tensor 𝒞𝒱 = U0ℋ : From the tensor  = U0ℋ .calibration matrix in the PRIMO relative transmit mapping approach by applying the following unfolding of the tensor 𝒞ℛ = U2ℋ , we should also be able to form a symmetrical unfolding: 𝒞𝒯 = U1ℋ  but also the use of both representations and the simultaneous enforcement of low-rank structure in both 2.2We can formulate the reconstruction problem as a convex problem using a sum-of-nuclear norms approach as follows: 17 It also has a more intuitive constraint parameterization (discrete rank thresholds rather than continuous regularization parameter λ): However, in this work we choose to employ an alternative non-convex formulation with strict rank constraints, which performs well in this context, and non-convex formulations have been used effectively in previous applications.M is the k-space sampling mask (applied to 𝓏 as an element-wise Hadamard product); 𝓏 is the reconstructed k-space tensor; 𝒟 is the undersampled k-space data; 𝒞𝒯 = U1T𝓏 ; 𝒞ℛ = U2T𝓏; ir are the rank thresholds; and ∥·∥F denotes the Frobenius norm. We will refer to this method for accelerated relative parallel transmit mapping as the transmit low rank (TxLR) method, which we can also reference using the constraint shorthand 𝒞𝒯 + 𝒞ℛ.Here, 𝒞𝒱 = U0T𝓏.Using the same reconstruction framework, with only changes to the number of constraints and the type of unfolding operator used, we can formulate a VC reconstruction that is the analogue of the virtual coil (VC) approach: 𝒞ℛ-constrained reconstruction as the PRIMO approach due to the correspondence between the transmit and receive concatenation order in 𝒞ℛ and the relative transmit mapping calibration matrix defined by PRIMO. This is formulated as: 𝒞ℛ = U2T𝓏. The difference between the proposed TxLR approach and the PRIMO approach is the additional simultaneously enforced 𝒞𝒯 constraint in the TxLR formulation.We will refer to the 33.126 algorithm: 𝓎1 and 𝓎2 are auxiliary variables; andρ is the ADMM penalty parameter. The final output n𝓏 after n iterations is a k-space by transmit and receive tensor with the same dimensions as the undersampled 𝒟. Γr is a singular value hard-thresholding operator that performs an SVD and discards all singular values with index i > r when ordered in decreasing magnitude. The algorithm is initialised with all variables, including 𝓏0, The constrained optimisation problem in U0 or U2. In practice, the algorithm also uses a varying penalty parameter ρ, with ρ0 = 10−6 and scaling factor τ = 1.1, and takes advantage of over-relaxation with parameter α = 1.5 to improve convergence26 . The VC  and PRIMiσ is the noise variance from the thi receive channel (obtained from a separately acquired noise reference scan), and υ is the total number of sampled data points. This expression is the well-known chi-square goodness-of-fit test, and we use it here to provide a parameter-free stopping criterion.Reconstructions were run to a fixed number of iterations or using a chi-square heuristic based on receive array noise characteristics. The chi-square heuristic checks, at every iteration, the condition: 3.227 at the 7 Tesla frequency of 298 MHz, centred over the heart of Duke28 . The maximum resolution around the conductors was set to 0.5 mm, 1.0 mm, or 2.0 mm as required to capture the geometry. A synthetic proton density image was generated by setting the proton density equal to the tissue density, with tissue densities greater than 1200 kg/m3 (bone) or less than 400 kg/m3 (lung) set to 80 (a/u) to make them resemble an MR image. The FOV was 278 × 356 × 248 mm3 (AP/LR/HF), and data were re-sampled onto a uniform grid of 2 × 2 × 2 mm3. This data were Fourier-transformed to form a k-space dataset, and 48 central slices located in the body were used for reconstruction simulations.In-silico data were simulated in Sim4Life 3.4  using an 8-channel transmit/receive dipole array27 and 2D images were acquired in a horizontal long axis orientation. Receive array noise measurements were also collected to generate noise covariance matrices for the chi-square convergence heuristic.In vivo data were acquired on a 7 Tesla Magnetom , and all volunteers provided written informed consent and were scanned in accordance with local ethics. Data were acquired using a spoiled low flip angle gradient echo acquisition, which transmitted on 1 channel at a time while receiving on all channels  of 60 dB in k-space unless otherwise noted. Retrospective undersampling using a uniform density pseudo-random Poisson disc distribution was employed to assess reconstruction performance at acceleration factors ranging from 3.3Reconstructions were performed using a  kernel, and rank thresholds were set to 50 unless otherwise stated. The number of iterations was set to 50 for the TxLR reconstructions, and 100 for the VC and PRIMO methods in all synthetic data reconstructions, except in the cases where the chi-square heuristic was evaluated. See In all cases, the k-space data were cropped to a matrix size of 24 × 24, except where the impact of k-space matrix size was explicitly evaluated, which examined crop sizes of 18 × 18, 24 × 24, 36 × 36, and 48 × 48. For the 3D datasets , reconstruction was performed slice by slice on hybrid space kx-ky-z data.𝓏 is the ground truth. Empirically, we found that an RMSE < 0.1 generated small errors in relative transmit sensitivity maps . Relative transmit sensitivity maps were estimated using the PRIMO extension to ESPIRiT after under-sampled tensor reconstruction.Reconstruction fidelity was evaluated using a normalized RMSE metric: 4R = 2 to R = 12 for the VC approach (𝒞𝒱 constraint), PRIMO approach (𝒞ℛ constraint), and the proposed TxLR approach (𝒞𝒯 + 𝒞ℛ constraints). Mean RMSEs for all methods are shown, along with their SDs across all 48 reconstructed slices. Whereas the VC reconstruction reaches RMSE > 0.1 at R = 2, the PRIMO reconstruction achieves R = 6 undersampling before reaching that error threshold. In comparison, the TxLR reconstruction manages to reach acceleration factors of R = 8 before showing the same error levels. Furthermore, both the VC and PRIMO reconstructions suffer from very poor reconstruction fidelity as acceleration factors increase, whereas the proposed TxLR approach shows a much lower rate of error increase with increasing R.Reconstruction performance on the synthetic body dataset is shown in R = 4 and R = 8. Reconstructions in the synthetic dataset were assessed at varying noise levels, with peak SNR ranging from 50 dB to 70 dB across acceleration factors of R = 8. 𝒞𝒯 and 𝒞ℛ constraints. In 𝒞𝒯 and 𝒞ℛ terms independently, indicating that RMSE is minimized when both rank constraints are the same and equal to 50 in this data. An evaluation of reconstruction performance for different matrix sizes and acceleration factors can be found in In 𝒞𝒯 or 𝒞ℛ constraints individually, or simultaneously as proposed, evaluated again in the synthetic body dataset at R = 8. In 𝒞𝒯- or 𝒞ℛ-only reconstructions (where 𝒞ℛ only is the same as the PRIMO approach). Whereas in this case, vertical concatenation of the transmit dimension (to form the 𝒞𝒯 matrix) slightly outperforms the 𝒞ℛ-based PRIMO approach , the difference is relatively small. However, reconstruction fidelity is significantly better for the TxLR approach, which uses the simultaneous 𝒞𝒯 + 𝒞ℛ constraints.To further assess the value of the proposed approach, 𝒞𝒯 + 𝒞ℛ case. 𝒞𝒯 + 𝒞ℛ (TxLR) reconstruction produces the smallest errors.In An evaluation of the chi-square stopping heuristic is shown in Supporting Information optimal rank constraint between 5 and 50, as indicated by the black dot. For the best performing subject, RMSE remained below 0.1 for the proposed TxLR method even at R = 8 acceleration, whereas in the worst performing subject RMSE reached as high as 0.2 at R = 8. However, in all subjects and all acceleration factors, the TxLR reconstructions produced lower RMSE than the VC or PRIMO methods, although the differences between TxLR and PRIMO were relatively small for R ≤ 4. This relative performance held for both the fixed rank constraint of 50 and the retrospectively chosen optimal rank thresholds. In subjects 1 to 5, the rank constraint of 50 was optimal or close to optimal for the VC and TxLR reconstructions, whereas the PRIMO data benefitted from reduced rank thresholds. In subject 6, lower rank thresholds produced considerably lower RMSE for all methods, which may reflect orientation differences in that dataset compared to the others.In Reconstruction times  in the body dataset were 0.18 s/iteration/slice (VC), 0.16 s/iteration/slice (PRIMO), and 0.20 s/iteration/slice (TxLR) for overall reconstruction times of approximately 10 to 20 s/slice. In the brain dataset, with 32 receive channels instead of 8, reconstruction times were 0.7 s/iteration/slice  and 1.0 s/iteration/slice (TxLR) for total reconstruction times of approximately 50 to 70 s/slice.5TxN transmit channel and RxN receive channels results in TxN · RxN images, but only at most TxN + RxN of them are linearly independent.This work investigated the use of Hankel-structured low rank tensor completion to reconstruct undersampled parallel transmit field maps. This leverages the fact that both transmit and receive sensitivity maps possess low rank properties when represented as a Hankel-structured matrix. Redundancy in a dataset in which every transmit sensitivity is modulated by every receive sensitivity is intuitively evident, as data with TxN by RxN), with the 3 approaches differing in how the low-rank constraints are imposed onto the tensor (via different matricizations or tensor-unfoldings).We investigated 3 different approaches for simultaneously reconstructing transmit and receive sensitivity maps in a single rank-constrained reconstruction. We formulated these all in a comprehensive multi-dimensional tensor model . This is also reflected in the SNR performance, where the virtual coils approach shows significantly worse RMSE with lower SNR.The first method investigated (VC) is similar to the virtual coils approach in time interleaved acquisition of modes,13 with the low-rank constraint enforced on a matrix formed by vertically concatenating the block-Hankel matrices from each receive channel and horizontally concatenating each transmit channel. This results in a matrix with similar height and width and a more effective low-rank representation. This approach performed significantly better than the VC method at lower acceleration factors (R ≤ 4) but exhibited similar or worse performance at high acceleration factors.The second method (PRIMO) uses the same transmit and receive channel concatenation scheme as PRIMO,different low-dimensional features in the tensor data and are not trivially related through a transpose operation; therefore, leveraging the low-rankness of both of the unfoldings simultaneously constitutes a more powerful constraint, leading to dramatically improved reconstruction fidelity as assessed by RMSE.The third proposed transmit low-rank method (TxLR) makes use of the symmetry in the transmit and receive array data by employing simultaneous low-rank constraints on 2 different unfoldings of the tensor data. One constraint is identical to the PRIMO constraint, whereas the second constraint enforces low-rankness on a matrix formed by horizontal receive concatenation and vertical transmit concatenation. The use of both these constraints is based on the recognition of the interchangeable nature of the transmit and receive sensitivities, where we demonstrated that each of these unfoldings individually have low-rank structure and perform similarly using an 8-channel transmit and 8-channel receive system. However, the 2 unfoldings capture 0 calibration. The reconstruction performance in the brain data suggested that TxLR benefits from additional receive channels (32 in the brain compared to 8 in the body), although this is difficult to determine with only a single brain dataset.In all cases, the TxLR approach clearly performed better than the other methods, particularly at higher acceleration factors. At lower acceleration factors, RMSEs were similar to those produced by the PRIMO method; however, dramatic differences were observed at R = 6 and R = 8. TxLR reconstructions in an 8-channel transmit system achieved acceleration factors of R = 8 with low RMSE in the body  and the brain . These results indicate that relative transmit calibration can be achieved in the same amount of time or faster than BReconstruction hyperparameters  were selected based on the synthetic dataset. These hyperparameters were able to robustly produce high-fidelity reconstructions in the in vivo body and brain datasets without any tuning to the specific coil geometries or organ. However, the parameters determined here are not universal recommendations. Different resolutions, matrix sizes, SNR regimes, and coil configurations may require different kernel sizes and rank thresholds; and context-specific parameter tuning will likely be required for optimized reconstructions. In the body dataset, for example, we did show that the chosen rank threshold of 50 was not always optimal, suggesting that data-specific hyperparameter tuning could lead to further reductions in RMSE. This subject-to-subject variation is likely driven by the slice orientation and not the FOV, as evidenced in 29 would take 65 s (24 × 24 × 32 × 3.5 ms), or 161 heartbeats; accelerating by a factor of 6 would bring this down to only 11 s, or 27 heartbeats.Accelerations of eightfold (matching the number of transmit states) worked best for an image matrix of 36 × 36; however, a 24 × 24 matrix is sufficient to capture the dominant transmit modes in the heart see  and S5, 15 which could further improve performance by exploiting low-rank properties of conjugate symmetric k-space locations under smooth phase assumptions.The results presented here, although showing a clear benefit of the proposed approach for accelerated parallel transmit mapping, have several limitations that could be addressed in further development of the method. For example, the current study only examined uniform density Poisson disc k-space sampling, given the relatively small, central k-space sampling windows used for sensitivity mapping. Exploration of variable density sampling schemes would be a natural extension of this work, and initial simulations suggest that both convergence speed and lower RMSE could improve with such schemes 9 or interferometry methods32 by accelerating the relative mapping part of the acquisition and applying these maps to reconstruct undersampled absolute maps.The TxLR approach could also be applied to absolute B1+ mapping of pTx systems by reconstructing multiple transmit configurations together (see supporting informatin “Simulation of accelerated absolute B1+ mapping” and Using TxLR in practice may be limited by the reconstruction time of the current implementation; although not prohibitively long, care must ensure that further data can be acquired while reconstruction is in process. A rapid acquisition time will improve the robustness of the acquisition by reducing its susceptibility to motion and may further enable the characterisation of motion-induced field changes.6Calibrationless low-rank image reconstruction can be used to reconstruct transmit array sensitivity maps in highly accelerated conditions. Transmit low rank method harness redundancies in both transmit and receive coil profiles to enable reliable acceleration of transmit maps without the need for a calibration scan. The method enables acceleration factors of 8, equal to the number of transmit coils.Supporting InfoAppendix


We propose a modified lung ultrasound (LUS) score in neonates with respiratory distress syndrome (RDS), which includes posterior instead of lateral lung fields, and a 5-grade rating scale instead of a 4-grade rating scale. The purpose of this study was to evaluate the reproducibility of the rating scale and its correlation with blood oxygenation and to assess the ability of early post-birth scans to predict the mode of respiratory support on day of life 3 (DOL 3). As a secondary objective, the weight of posterior scans in the overall LUS score was assessed.0) and on days 2, 3, 5, 7, 10, 14, 21 and 28. LUS scores were correlated with oxygen saturation over fraction of inspired oxygen (S/F) and mode of respiratory support. Interrater agreement was determined with the intraclass correlation coefficient (ICC) and Cronbach’s alpha. Probabilities of the need for various respiratory support modes on DOL 3 were assessed with ordinal logistic regression. Least square (ls) means of the posterior and anterior pulmonary field scores were compared.We analyzed 619 serial lung scans performed in 70 preterm infants < 32 weeks gestation and birth weight < 1500 g. Assessments were performed within 24 h of birth (LUSp < 0.0001) and had excellent interrater agreement . Significant predictors of ventilation requirements on DOL 3 were LUS0 (p < 0.016) and birth weight (BW) (p < 0.001). In the ROC analysis, LUS0 had high reliability in prognosing invasive ventilation on DOL 3 ). Invasive ventilation was the most likely mode of respiratory support for LUS0 scores: ≥7 (in infants with BW 900 g), ≥ 10 (in infants with BW 1050 g) and ≥ 15 (in infants with BW 1280 g). Posterior fields exhibited significantly higher average scores than anterior fields. Respective ls means (confidence levels) were 4.0 (3.8–4.1) vs. 2.2 (2.0–2.4); p < 0.001.The LUS score correlated significantly with S/F (Spearman rho = −0.635; Post-birth LUS predicts ventilation requirements on DOL 3. Scores of posterior pulmonary fields have a predominant weight in the overall LUS score. An increasing number of reports have recently been published on the usefulness of lung ultrasound (LUS) to assess lung function in premature infants with respiratory distress syndrome (RDS) –7. In thp = 0.001), and the median score for infants requiring intubation was 9 (IQR 8–12) [The scoring scheme as described initially by the group of DeLuca  was baseas 9 IQR –12 [8].Lung scans in neonatal RDS exhibit a largely homogenous picture, especially during the first h of life, as demonstrated by Reimondi et al.  and in aThus, we propose an alternative approach to lung ultrasound assessment that relies, in short, on (1) scanning posterior rather than lateral fields, (2) evaluating anterior fields as a whole, without division into upper and lower parts and (3) introducing an additional grade to the current scoring scheme.The aim of this study was to confirm the validity of the proposed LUS score in terms of its reproducibility and correlation with blood oxygenation and to assess the ability of early postnatal scans to predict the need for respiratory support on the third day of life (DOL 3). As a secondary analysis, we assessed the weight of posterior vs. anterior field scores in the overall LUS score based on serial scans performed over a period of one month.2 < 50 mm Hg (< 6.6 kPa) in room air, central cyanosis in room air or the need for supplemental oxygen to maintain PaO2 > 50 mm Hg (> 6.6 kPa) . p values less than 0.05 were regarded as significant.To assess the weight of the posterior area scores in the total LUS score, we used linear mixed effects regression. In this analysis, patients were set as a random factor, while the anteroposterior gradient of the LUS and the postnatal day of examination were fixed effects. The obtained least square (ls) means of the posterior and anterior scores were subsequently compared. For all analyses, The study cohort consisted of 70 premature newborns with a median gestational age of 28 weeks (IQR 26–29) and a mean birth weight of 1037 ± 270 g. Baseline characteristics are presented in Table per protocol scans and 22 (3%) complementary scans made for clinical indications beyond the day of life 28. In 6 of 647 (0.9%) examinations, LUS was not calculated because scans revealed pneumothorax (n = 5) or hydrothorax (n = 1). These 6 scans were excluded from the analysis together with the 22 complementary scans. Therefore, analyses were performed based on 619 scans. Baseline sonograms were performed on average 10.7 (7.5–15.5) h after birth .A total of 647 lung sonograms were performed, including 625 (97%) p < 0.001). The distribution of the LUS scores and the corresponding S/F is presented in Fig. LUS scores correlated significantly with S/F  and Cronbach’s alpha equal to 0.99 showed excellent interrater agreement.2 cannula, 6 (4–8) for CPAP, 10 (7–12) for IPPV and 14 (12.5–15.5) for HFOV  LUS of 2 (0–4). Escalation of therapy from oxygen supplementation to CPAP and further to invasive ventilation (IPPV and HFOV as the ultimate option) involved a linear increase in LUS; the respective medians (IQR) were 3 (2-4.5) for O0, birth weight, gestational age, maternal steroids, cesarean section, surfactant therapy), the following variables were significant: LUS0 , birth weight , gestational age  and surfactant . In the final stepwise multivariate regression model, the need for invasive ventilation on DOL 3 was predicted only by LUS0 (p = 0.016) and birth weight (p < 0.0001). LUS0 exhibited high reliability in predicting the need for invasive ventilation on DOL 3, as reflected by logistic regression model for which the area under the ROC curve was equal to 0.845 .In the univariate ordinal logistic analysis of the variables assessed for correlation with the need for invasive ventilation (LUS0 were reached: ≥7 (for BW 900 g), ≥ 10 (for BW 1050 g) and ≥ 15 (for BW 1280 g). The above birth weights are 25th percentile, median and 75th percentile of the cohort studied.The probabilities of various ventilation modes on DOL 3 are presented in Fig. 0.A multiclass area under the curve equal to 0.865 indicated high power of prediction of various respiratory support modes with LUSp < 0.001).The posterior pulmonary field scores were significantly higher compared with the anterior field scores. Based on all scans performed, the posterior fields had an average score  of 4.0 (3.8–4.1), whereas anterior pulmonary fields had an average score of 2.2 (2.0–2.4). The difference was statistically significant  , 21–24. idations , 19. Truidations  and, as We abandoned the division of pulmonary fields into upper and lower sections. Previously, Pang et al.  expandedIn almost all available works, ultrasound examination was limited to the anterior and lateral parts of the lungs. The “anterior-lateral” approach does not take full advantage of lung ultrasound over standard anteroposterior X-ray, namely, the possibility of distinguishing between changes in the anterior and posterior parts of the lungs. Very few studies have reported assessments of posterior pulmonary fields , 23, 24.p < 0.001). We used ls means to compare posterior vs. anterior scores given that, contrary to regular (arithmetic) means, ls-means are based on a linear mixed-effect model and thus adjust for confounding effects, which were repeated examinations in each patient in this case.It is known from daily clinical practice that many pulmonary pathologies tend to have gravitational positioning. Our study confirmed this observation, as a review of serial lung scans performed over a period of 28 days demonstrated that the scores of the posterior pulmonary fields were significantly higher than the anterior field scores  LUS score to predict the need for mechanical ventilation on DOL 3. The need for invasive ventilation on DOL 3 is a widely recognized endpoint in neonatal RDS and is strongly correlated with subsequent adverse outcomes –33. DepeThe analysis also provides an important observation regarding the association of oxygen requirements and the severity of lung changes. As shown in Fig. However, this fact sheds new light on the applied criteria for surfactant treatment. According to the current therapeutic guidelines, the decision of surfactant administration is based on the required level of inspired oxygen . With thIn our study, LUS assessments had a very high interrater agreement, as reflected by the intraclass correlation coefficient and Cronbach’s alpha. Although all scans were assessed by two neonatologists with expert-level skills, lung ultrasound is known to be a diagnostic procedure that is easy to master and has a steep learning curve. Daily observations outside the scope of this study show that lung ultrasound examination can be easily learned during two-day courses and 1–2 months of supervised practice. It is therefore likely that the reproducibility of the LUS assessments carried out by ultrasound experts would be replicated by less experienced sonographers.The current situation of using different scales for assessing the severity of changes in lung ultrasound in newborns is summarized in a meta-analysis published by Razak et al. . In theiIn summary, we proposed a modified LUS, which is characterized by a high correlation with oxygenation parameters and respiratory support modes and a very high consistency of assessments between performers. We also demonstrated the importance of the posterior fields in ultrasound assessment of the lungs. The study showed that LUS is a tool that can be used for the early postnatal identification of infants at risk of invasive ventilation in the subsequent days of life. Finally, the modified LUS is suitable not only in newborns during the first days of life and remaining on noninvasive respiratory support but also in mechanically ventilated infants with various respiratory disorders during the first month of life.


The objective of this study was to describe the real-world treatment and overall survival (OS) of German patients with a diagnosis of advanced non-small cell lung cancer (aNSCLC), and to explore factors associated with the real-world mortality risk.This was a retrospective German claims data analysis of incident aNSCLC patients. Data were available from 01/01/2011 until 31/12/2016. Identification of eligible patients took place between 01/01/2012–31/12/2015, to allow for at least 1-year pre-index and follow-up periods. Inpatient and outpatient mutation test procedures after aNSCLC diagnosis were observed. Further, prescribed treatments and OS since first (incident) aNSCLC diagnosis and start of respective treatment lines were described both for all patients and presumed EGFR/ALK/ROS-1-positive patients. Factors associated with OS were analyzed in multivariable Cox regression analysis.n = 458), 26·6% of these patients (n = 122) received a targeted treatment and were assumed to have a positive EGFR/ALK/ROS-1 test result. Most often prescribed treatments were pemetrexed monotherapy as 1 L  and erlotinib monotherapy as 2 L (25·83%/38·54%). Median OS since incident diagnosis was 351 days in all and 571 days in mutation-positive patients. In a multivariable Cox regression analysis, higher age, a stage IV disease, a higher number of chronic drugs in the pre-index period and no systemic therapy increased the risk of early death since first aNSCLC diagnosis. On the other hand, female gender and treatment with therapies other than chemotherapy were associated with a lower risk of early death.Overall, 1741 aNSCLC patients were observed . The mutation test rate within this population was 26·31% (Despite the introduction of new treatments, the real-world survival prognosis for aNSCLC patients remains poor if measured based on an unselected real-world population of patients. Still, the majority of German aNSCLC patients do not receive a mutation test. Lung cancer is the leading cause of cancer death in men and the third most frequent cause of cancer death in women worldwide, with 2·1 million new cases and 1·7 million deaths estimated for 2018 . Non-smap = 0·003) [The discovery of new molecular alterations and development of respective targeted treatments represents a major improvement over conventional chemotherapy when applied to appropriately selected patient populations –11. A re= 0·003) , 14.In addition to targeted agents, recent development of immune checkpoint inhibitors such as pembrolizumab or nivolumab adds extends treatment options for aNSCLC patients, with reported median OS in clinical trials of 9·2–12·2 months (Nivolumab) and 10·4–12·7 months  versus 6·0–9·4 months (Docetaxel) for chemotherapy –17. On tBased on recent therapy developments, current European and German treatment guidelines recommend testing for mutations/mutation aberrations  and PD-L1 testing, in order to identify those patients who are eligible for targeted/immune checkpoint therapies , 22, 23.This was a retrospective claims-based data analysis of patients diagnosed with aNSCLC, using a cohort design. The study utilized data provided by the statutory German sickness fund AOK PLUS, covering routine data on health of 3.2 million people insured in Germany (regions of Saxony/Thuringia), which is more than 50% of the overall population in these states. This large claims data set includes complete records of a patient’s outpatient and inpatient diagnoses and treatments prescribed by all types of treating physicians and departments within the German healthcare system. Diagnoses were identified based on inpatient and confirmed outpatient ICD-10 codes . Outpatient drug treatment was identified through relevant ATC-codes, and inpatient treatment was identified through relevant operational and procedure codes (OPS). The dataset covered the period 01/01/2011–31/12/2016.Identification and inclusion of eligible patients took place between 01/01/2012–31/12/2015, with a baseline period of one year and a minimum follow-up period of 1 year. Patients were selected in a stepwise procedure based on their diagnoses and treatments  tumor classification, with status IIIb or higher classifying a patient as being advanced within this study. Patients with at least one confirmed inpatient or outpatient diagnosis of tumor stage IIIb or higher between 01/01/2012–31/12/2015, following/concurrent with their first observed general lung cancer diagnosis, were included . In case of data availability, for a subset of patients, 24-month and 36-month follow-up data were analyzed.In this study, we aimed to identify the percentage of patients with a test for an EGFR, ALK or ROS-1 mutation. Within Germany, mutation testing can be carried out in both an outpatient and an inpatient setting. Outpatient mutation tests were identified based on reimbursement codes listed in a German-wide code catalogue (Einheitlicher Bewertungsmaßstab EBM) published by the National Association of Statutory Health Insurance Physicians (Kassenärztliche Bundesvereinigung) . As no uTreatments and treatment patterns were observed for all incident aNSCLC patients, and for the subgroup of mutation-positive aNSCLC patients as defined above. Prescribed treatments were identified based on respective anatomical therapeutic chemical classification (ATC) codes of agents, both in an inpatient and an outpatient setting. Generally, all prescribed outpatient treatments were available in our database, that also applied for inpatient treatments reimbursed separately outside the DRG (diagnosis related groups) system. For mostly older treatments that are not separately reimbursed in an inpatient setting, we used a “general” chemotherapy code (OPS 8–54) which documented a chemotherapy treatment but did not provide the specific agent. The first prescription of an agent after the incident aNSCLC diagnosis was defined as start of the first treatment line (1 L). Any agents prescribed on the same day or within 21 days of starting a treatment line were considered as part of a combination therapy. A start of a new treatment line was identified only when a new agent different from 1 L treatment(s) was observed after that 21 days period. Discontinuation of a treatment/treatment line was assumed if a new treatment line started or if there was a gap in drug availability of at least 45 days. In case a gap in drug availability was observed, the end of the respective gap was considered to be the end of the treatment line. In addition to that, for aNSCLC stage IIIb patients, we also reported the percentage of patients who received a radiotherapy (RT), as in these cases not necessarily a mutation test is recommended.Identification of most frequently prescribed treatment patterns was done by observing the number of patients with a prescription of the respective monotherapy or combination therapy, within each line of therapy. Identification of the most often prescribed agents was based on all patients who received the respective agents, regardless of whether they were used as monotherapy or a combination therapy.OS was described using Kaplan Meier methodology. The proportion of patients alive after 3/6/12 months following their index date (incident aNSCLC diagnosis), and in a subgroup analysis of patients with longer data availability, after 24 and 36 months, was reported. Furthermore, survival analysis was repeated, considering the start of 1 L/2 L/3 L treatment as index date.1, or (5) received chemotherapy only was done, using Log Rank tests in comparison to patient group 5 (chemotherapy only).Mean and median OS in days was estimated based on above assumptions. Moreover, an OS comparison between patients who (1) did not receive any systemic treatment after incident aNSCLC diagnosis, (2) received a mutation test and received a targeted therapy (at any line), (3) received a targeted therapy but never received a mutation test, (4) received an immunotherapyA multivariable Cox regression was additionally performed in order to identify the association of various independent variables such as disease stage and sociodemographic characteristics at baseline with mortality. Furthermore, type of therapy as defined above and year of incident aNSCLC diagnosis were included as independent variables.2, Mann-Whitney-U). A multivariable logistic regression model was used to evaluate any potential explanatory variable for receiving a mutation test. Treatment, duration of treatment and OS were reported using descriptive statistics and applying a Kaplan Meier methodology (using Log rank tests whenever applicable). Finally, multivariable analysis of factors associated with mortality was done using Cox regression analysis, applying a backward elimination method to systematically exclude variables which were deemed insignificant based on a p-value of 0·1 or higher. Software used for data analysis and modeling included Microsoft Office Excel 2016 and Stata version 14·1 software .Most reported data were based on descriptive statistical analyses. Baseline characteristics were compared between not-tested and mutation negative aNSCLC patients and mutation positive patients, using parametric and non-parametric tests  than female patients (29·9%). At date of incident aNSCLC diagnosis, 32·2% of all observed patients received a diagnosis of stage IIIB NSCLC, 42·7% of stage IV and for 24·1% of patients both TNM stages had been documented at index date or within 30 days after index date. The mean Charlson Comorbidity Index (CCI) in the sample was 9·91. Within the 12-month pre-index period, patients received an average of 4·7 chronic drug prescriptions, and 76·0% experienced at least one hospitalization  received a mutation test at any time between first lung cancer diagnosis and end of observational time. Out of these tested patients, 122 patients (26·6%) received a targeted treatment and were thus assumed to be positively tested for EGFR, ALK or ROS-1 mutations. In total, this resulted in a rate of 7·0% mutation-positive patients, out of all identified incident aNSCLC patients .N = 560), corresponding numbers were 16·61% within 3 months and 29·46% within 12 months. 74·64% of aNSCLC patients within stage IIIB did not receive a mutation test. Out of those, 16·27% received a radiation therapy within 3 months (28·95% within 12 months).Among all incident aNSCLC patients, 14·41% received a RT within the first 3 months after diagnosis (26·58% within 12 months). Among patients in stage IIIB at time of incident diagnosis (p < 0·001), whereas at least one hospitalization in the baseline period decreased that probability . TNM status, age, CCI and number of previously prescribed chronic drugs were not associated with the probability to receive a mutation test , 19·5% received 1 L and 2 L treatment (1 L + 2 L), 5·2% received three lines of treatment (1 L + 2 L + 3 L), and 1·2% received more than three lines of treatment  as 1 L treatment was pemetrexed, which was prescribed in 49·0% of aNSCLC patients and 40·2% of mutation positive aNSCLC patients. The most commonly prescribed agent in 2 L/3 L treatment was erlotinib .Most frequently prescribed treatment patterns as 1 L treatment were pemetrexed monotherapy (21·2%), pemetrexed in combination with an unspecified agent  (7·7%), and pemetrexed and bevacizumab combination therapy (7·4%). In mutation positive patients the most commonly prescribed treatment patterns as 1 L were erlotinib (20·5%), pemetrexed (11·1%) and pemetrexed and cisplatin combination (6·8%). Most frequently prescribed treatment patterns as 2 L were erlotinib (25·8%), docetaxel 11·3%) and pemetrexed (8·0%) in all aNSCLC patients, and erlotinib (38·5%), pemetrexed (7·3%) and gefitinib (7·3%) in the subgroup of mutation positive patients , an immunotherapy without a TKI was prescribed in 4·5% of patients (might include chemotherapy at other lines).Based on 1672 patients who started a 1 L treatment, 187 (11·2%) received at least one mutation test between incident aNSCLC diagnosis and start of 1 L treatment, and 197 (11·8%) received at least one test afterwards  and a higher number of prescribed chronic drugs in the 12 months baseline period  increased the probability to receive a chemotherapy as 1 L treatment, whereas female gender  and stage IV disease at index date  were found to be associated with a lower probability to receive it . OS of patients having received a TKI without a mutation test was lower but still significantly higher than in the chemotherapy only group (p = 0·006). Lowest OS was observed for patients who did not receive any therapy (p = 0·001 in comparison to chemotherapy only group) , followed by mutation-positive patients who received a TKI (p = 0 ·011 in comparison to chemotherapy) .In a comparison of different treatment patterns across all lines, patients who received at least once an immunotherapy or a TKI combined with a mutation test had the highest OS since incident aNSCLC diagnosis (up) Fig. . If resppy) Fig. . Survivap = 0·013), a stage IV disease , a higher number of chronic drugs in the pre-index period  and no therapy  increased the risk of early death since incident aNSCLC diagnosis. Conversely, female gender , an incident diagnosis in 2013  and treatment with therapies other than conventional chemotherapy  were associated with a lower risk of early death. Positive mutation status, number of hospitalizations in the pre-index period were not associated with mortality risk and, consequently, excluded from the final regression models.In a multivariable Cox regression analysis Fig.  using tiThe main aim of this study was to analyze the real-world treatment of aNSCLC patients and their OS in Germany. The main strength of this analysis is the unselected nature of the dataset which included all aNSCLC patients and all treating physicians irrespective of their type and willingness to participate in a clinical or observational study, with a resulting high external validity of our results. Moreover, our study completely covered both the inpatient and outpatient treatment of patients and, consequently, all sectors of the German healthcare sector. As we included all patients meeting inclusion criteria, our study was also not affected by any selection bias that would lead to an observation of an above-average treated patient sample only, as it can be expected to be the case in most of conducted observational studies/registries. However, we acknowledge that specifically our treatment-related inclusion criteria might have led to an own selection bias that excluded untreated patients as well as patients receiving treatments approved for SCLC and NSCLC from further observation. Moreover, a substantial proportion of patients was already excluded due to non-continuous insurance. We cannot draw conclusions with regard to these excluded patients, as we aimed to observe aNSCLC patients only. As the characteristics of our sample are well in line with previous clinical and observational studies with respect to age, gender distribution and percentage of IIIb/IV patients –29, we nWith the exception of aNSCLC stage IIIb patients who receive a potentially curative RT, German diagnosis and treatment guidelines recommend testing for mutations for every diagnosed aNSCLC patient before start of a 1 L treatment . However96·7% of observed patients were hospitalized since incident aNSCLC diagnosis at least once, 59·6% of observed patients were hospitalized at date of their incident aNSCLC diagnosis. Mutation tests done during inpatient stays might not have been documented properly in our study even if the specific codes are available, as they are not separately reimbursed within the German diagnosis related groups (DRG) system. That would have led to an underestimation of the mutation test rate. However, as German hospitals currently do not get any reimbursement for those tests on top of the DRGs, we do not expect that a substantial percentage of patients was tested during their inpatient stays.Inclusion of mutation testing into the real-world treatment of aNSCLC patients has been widely discussed in scientific literature –35. For Almost 95% of our sample of German aNSCLC patients received a systemic treatment. This is, compared to previous literature, relatively high. Sacher et al. reported that only 24% of patients from a large scale data registry in Canada received 1 L chemotherapy and only 31% of those patients received 2 L therapy with more patients receiving treatment over time . David eEven if almost all of our observed patients received a systemic treatment, the majority of them only received one systemic treatment line within the first year following incident aNSCLC diagnosis . Albeit difficult to observe from claims data records, the most frequent treatment patterns used in 1 L treatment were pemetrexed and bevacizumab, related combinations (41·93%) and docetaxel 6 ·40%). This is in line with the treatment guidelines, which recommend 1 L treatment with pemetrexed or bevacizumab platinum based combinations in patients without mutation and non-squamous NSCLC , 38. Pem%. This iIn mutation-positive patients, however, a substantial percentage of > 20% of patients received a pemetrexed-based 1 L treatment, which is not according to guidelines. This might be related to the fact that more than half of observed mutation tests were done after start of 1 L therapy. On the other hand, some positively tested patients might still receive non-targeted therapies in clinical practice, which is clearly disadvantageous to patients.We report a general median survival of 11·5 months in our aNSCLC sample. Mutation-positive patients, based on our proxy definition, had a better median OS of 18·8 months in comparison to the 11·1 months in the not tested/negatively tested patients. Our median OS is well in line with what has been reported in previous observational studies. A US study addressing a community oncology setting reported a median OS of 9·7 months for an aNSCLC patient sample without known EGFR mutations . A EuropOur multivariable analysis shows that both immunotherapy treatments and TKI treatments are associated with a better OS. However, this result might be strongly influenced by unobserved differences in characteristics of compared patients, and can thus not be generalized to all aNSCLC patients. On the other hand, as many new treatments became available to patients in recent years, we expected an improvement of median OS for the overall aNSCLC population diagnosed in recent years. However, we could not confirm this. OS of patients diagnosed in later years 2014–2015 was not better than that of patients diagnosed in 2012–2013. In association with the low testing rates this shows that the real-world treatment of aNSCLC patients’ needs to be urgently improved.We acknowledge some limitations which are mostly related to the nature of the analyzed data. Firstly, we used a retrospective anonymous claims data set which combines the advantages of full data coverage over different sectors of healthcare (inpatient and outpatient treatment) and absence of any study site/patient selection bias due to the study itself with the disadvantage of lack of clinical details as mainly data used for reimbursement purposes are available in such a dataset. Nevertheless, claims data are a often used data source for observational research, and have frequently been used in the area of lung cancer as well , 39. In Secondly, as already noted above, our method to identify mutation tests might have led to both an under- and overestimation of testing rates. Thirdly, our method of identifying the index dates of the patients in the included sample might have led to the overestimation of OS. The index date was identified as the first inpatient or outpatient incident aNSCLC diagnosis. Whereas the exact dates of inpatient data were available, for outpatient diagnoses only the respective quarter of the year was available. Here, we used the first day in a quarter as index date. In our dataset, 56·3% of all aNSCLC patients (981 out of 1741 patients) were included based on an inpatient diagnosis as index date. For the remaining 760 patients (43·7%), above mentioned overestimation of up to three months might have occurred.Fourthly, mutation-positive patients were identified based on whether they received a targeted treatment any time following an observed mutation test. In case a patient received a mutation test with a negative result, but still received a targeted treatment at any time after that test, we wrongly assumed that this patient was tested positively. Moreover, it should be noted that according to German treatment guidelines, Erlotinib can also be prescribed as 2 L+ treatment in mutation negative NSCLC patients in case other therapy options are not suitable, which might have led to an overestimation of the percentage of mutation positive patients in the analysis. Furthermore, taking into account targeted treatment as an inclusion criterion for the sample of mutation positive aNSCLC patients, reporting of the most often prescribed agents in 1 L, 2 L or 3 L may have been biased, even if all observed treatments within the selected patient group have been reported.Fifth, as aNSCLC patients are likely to be hospitalized, inpatient chemotherapy treatment had to be considered throughout the analysis. However, for older chemotherapy agents not reimbursed separately by German payors but as part of DRGs, a chemotherapy was identifiable via a specific operational procedure code, but not the type of agent. Thus, we assumed that any unspecified chemotherapy treatment during a hospitalization was the same as the one prior to the inpatient stay, which could have led to an underestimation of lines of therapy patients received if many inpatient hospitalizations were associated with a change of chemotherapy.Sixth, treatments administered within clinical studies might not have been recorded in our claims dataset as study medication is paid by the sponsors of these studies. Moreover, the duration of treatment lines was likely to be overestimated as the end and not the beginning of a time gap (45 days) in treatment prescriptions was assumed to be the end of the treatment line. Finally, identification of treatment lines in this analysis did not take into account maintenance therapies, which might have led to a higher than actual number of treatment lines being reported.Median OS of German aNSCLC patients in the real world is low, but in line with other countries. Patients with a positive EGFR/ALK/ROS-1 mutation test in association with a targeted treatment do have a better OS than those not receiving a targeted treatment and/or those who did not receive a mutation test.Despite the introduction of new treatments in aNSCLC, the real-world survival prognosis for patients in advanced stages of NSCLC did not change in recent years. Mutation testing for aNSCLC patients is still not a common practice, despite clear guideline recommendations and availability of targeted treatments. Therefore, there is an urgent need to improve the real-world treatment of these patients.Additional file 1: Table S1. Treatments approved for NSCLC and/or SCLCAdditional file 2: Table S2. Advanced tumor stage classification descriptions and respective ICD-10 codesAdditional file 3: Table S3. Mutation test codesAdditional file 4: Table S4. Logistic regression model for mutation testingAdditional file 5: Table S5. Logistic regression model for type of 1L treatment


There has been a lack of studies exploring volunteerism from the life span perspective. This study aims to examine the relationship between personality and volunteerism among the oldest old population, using three types of volunteerism: “ever volunteered,” “last volunteered,” and “currently volunteering.” “Ever volunteered” assesses whether individuals ever volunteered in their life. “Last volunteered” examines when an individual last volunteered. “Currently volunteering” explores whether an individual is currently volunteering. By comparing the three volunteerism measures, this study took a life span view of volunteerism. Data of 208 oldest old adults, octogenarians (34.1%) and centenarians (65.9%), from the Georgia Centenarian Study were included in this study. The majority of the sample had volunteered sometime during their lifetime (88.9%), many of them still volunteered when they were in their 80s and 90s (40.4%), and the majority of the sample indicated that they were not currently volunteering (78.8%). Multiple regression analyses indicated that competence (a facet of conscientiousness) significantly predicted “ever volunteered,” and extraversion significantly predicted “last volunteered.” In other words, oldest old adults with high competence levels were more likely to have volunteering experiences in their life. Also, those with high levels of extraversion were likely to have more recent volunteering experiences. None of five personality traits significantly predicted “currently volunteering.” This study sheds light on the importance of different types of volunteerism which enables us to better understand the relationship between volunteerism and personality. We recommend future research to test the link between different types of volunteerism and well-being outcomes.


Oryza sativa make it the most important cereal crop that can gain significantly from improved tolerance to low temperatures. However, mechanisms underlying this complex trait are not fully understood. Oryza sativa has two subspecies with different levels of chilling tolerance, JAPONICA and INDICA, providing an ideal tool to investigate mechanistic differences in the chilling stress tolerance responses within this important crop species.Developing chilling tolerant accessions of domesticated Asian rice is a potential source of significant crop improvement. The uniquely chilling sensitive nature of the tropically originating Oryza sativa accessions. The tools available for this panel allowed for a comprehensive analysis of two chilling tolerance traits at multiple temperatures across a 354-cultivar subset of the RDP1. Chilling tolerance trait values were distributed as mostly subpopulation specific clusters of Tolerant, Intermediate, and Sensitive accessions. Genome-wide association study (GWAS) mapping approaches using all 354 accessions yielded a total of 245 quantitative trait loci (QTL), containing 178 unique QTL covering 25% of the rice genome, while 40 QTL were identified by multiple traits. QTL mappings using subsets of rice accession clusters yielded another 255 QTL, for a total of 500 QTL. The genes within these multiple trait QTL were analyzed for Gene Ontology (GO) term and potential pathway enrichments. Terms related to “carbohydrate biosynthesis”, “carbohydrate transmembrane transport”, “small molecule protein modification”, and “plasma membrane” were enriched from this list. Filtering was done to identify more likely candidate pathways involved in conferring chilling tolerance, resulting in enrichment of terms related to “Golgi apparatus”, “stress response”, “transmembrane transport”, and “signal transduction”.The Rice Diversity Panel 1 (RDP1) was used to investigate a core set of Taken together, these GO term clusters revealed a likely involvement of Golgi-mediated subcellular and extracellular vesicle and intracellular carbohydrate transport as a general cold stress tolerance response mechanism to achieve cell and metabolic homeostasis under chilling stress. It was recently estimated that, by the year 2050, a 50% increase in food production is required to meet the needs of a growing global population (Food and Agriculture Organization of the United Nations (FAO) Oryza sativa L., is a major food source for about half of the world population  and their admixed accessions  developed as part of the Rice Diversity Project is a useful tool. It is a panel of 424 purified, homozygous accessions that are representative of the entire Oryza sativa. We show via genotype-based principal component analyses (PCA) combined with cold tolerance trait phenotyping analyses done at different temperatures that the RDP1 contains three distinct, mostly subpopulation-specific, clusters of accessions classified as chilling tolerant (Tolerant), intermediate chilling tolerant (Intermediate), and chilling sensitive (Sensitive). Through GWAS mapping using all accessions or accessions of the Tolerant and Sensitive clusters and accessions within clusters, we identified 500 QTL and a large number of QTL region-associated chilling tolerance candidate genes. We then used several filtering methods to reduce the number of candidate genes to identify the most probable chilling tolerance response pathways that are significantly altered between the chilling tolerant JAPONICA  and chilling sensitive INDICA  subspecies.The major aim of this study was to help elucidating chilling stress tolerance response mechanisms in the generally cold sensitive crop species JAPONICA subspecies of rice to be more chilling tolerant than the INDICA subspecies, multiple phenotypic analyses on a subset of Rice Diversity Panel 1  had similar chilling tolerance phenotypes, and they followed similar trajectories at every temperature tested. Interestingly, while most members of the JAPONICA subspecies were more chilling tolerant than members of the INDICA subspecies, aromatic accessions which are typically classified as part of the JAPONICA subspecies had chilling tolerance phenotypes that were more similar to admixed INDICA/JAPONICA than to other JAPONICA relatives, most likely because genotypically they also clustered with admixed varieties  cluster, distinct from the “Cold Tolerant”  and “Cold Sensitive”  clusters. Admixed JAPONICA and admixed INDICA accessions predictably had phenotypes in accordance with their JAPONICA and INDICA mixed genotypes, respectively. However, it is interesting to note that admixed JAPONICA accessions were generally a bit less chilling tolerant than either temperate or tropical japonica accession while admixed INDICA accessions were generally a bit more chilling sensitive than either aus or indica accessions  from leaf tissues than cold tolerant accession (low EL scores), due to a higher incidence of membrane lesions after cold exposure. The mean percent EL for Tolerant, Intermediate, and Sensitive clusters generally followed this expectation Fig. . For theThe percent LTSS was determined as a measure of survival of two-week-old seedlings after 1 week of continuous low-temperature stress exposure. The phenotype of plants after a 7-day recovery period from cold stress is shown in Fig. R2 = 0.4620), followed by 10 °C (R2 = 0.3696) and 12 °C (R2 = 0.2869), while there was no correlation at the extreme ends of 4 °C (R2 = 0.0746) and 16 °C (R2 = 0.0098). This indicates that at 8 °C ± 1 °C, the degree of chilling temperature induced membrane damage correlates well with subsequent probability for survival. That is, less membrane damage predicts higher survival rates, however, even at 8 °C, there were several outliers with little membrane damage and low survival rates, and several outliers with a high degree of membrane damage and high survival rates  > 4, and QTL were identified as chromosomal sites containing 3 significant SNPs within a one million base pair (Mbp) region.From the core subset of 354 RDP1 accessions, EL, LTSS, and LT50 data were used to perform GWAS to identify significantly trait associated SNPs. We applied a publicly available GWAS pipeline  and 138 single-trait QTL   Table S, coverinUsing different cold tolerance clusters, additional GWAS-based QTL mappings were done. To identify QTL that control chilling tolerance in accessions of the Tolerant and Sensitive clusters, the Intermediate cluster was removed and GWAS mappings were done for the three high EL-LTSS-correlation temperatures of 8 °C, 10 °C, and 12 °C Table S. The TolqMT QTL regions for chilling tolerance candidate genes  or in helping with improving those traits at more than one temperature. This reduced the total number of genes to be analyzed from 14,710 to 6065 genes associated with the 40 qMT regions, which were further analyzed using gene function and Gene Ontology (GO) term annotations.Within the 178 unique QTL regions obtained using all 354 accessions, 14,710 genes were identified, which is more than 25% of the total number of annotated genes reported by the Rice Genome Annotation Project  within their genomic regions were selected, yielding a list of 220 genes. Significant SNPs with expected percentages of major alleles and direction of allele effect on chilling tolerance trait were used to further filter the gene list. That is, significant SNPs with a major allele frequency at least as much as the percentage of accessions of the Tolerant cluster (205 out of 354 accessions = 58%) and with an allele effect positively correlating with the measured chilling tolerance trait (to decrease EL and to increase LTSS) were selected, yielding a list of 81 candidate genes. Those genes were then used for GO term enrichment analysis and compared to the larger gene list to narrow down possible cold tolerance response pathways. Furthermore, since GWAS-based QTL mapping was also done using accessions from between and within the major cold Tolerant and Sensitive clusters, 35 qMT QTL regions with at least one single QTL using these clusters were identified and used for targeted GO enrichment analysis , and those relevant to plant chilling tolerance were grouped into chilling stress relevant clusters. Within the GO term for Biological Process, three major clusters were identified for “carbohydrate derivative biosynthesis”, “protein modification by small protein conjugation or removal”, “carbohydrate transmembrane transport”, and “hydrogen peroxide mediated signaling pathway”  GO terms: “exonuclease activity”, “cytoplasmic part”, and “extracellular region”. As term enrichment map visualizations were not possible with so few terms, an assessment was done on a larger list of genes from an intermediate filtering protocol. The intermediate filtering of only genes with significant SNPs resulted in 159 non-transposable element genes with significant SNPs from the 35 qMT and Tolerant & Sensitive Cluster QTL. The terms that were enriched at this stage were related to “ubiquitination”, “plant growth”, and “nucleotide binding”  and percent electrolyte leakage (EL) means of different rice accessions at different chilling temperatures generally followed an expected trajectory based on their subpopulation structure, including the recent chilling tolerance reevaluation of ies Fig. . It is iInterestingly, we did not observe a good correlation between LTSS and EL at each chilling temperature, indicating that under certain low-temperature stress conditions, EL cannot be used to predict seedling survivability after stress recovery Fig. . This laaromatic, aus, indica, temperate japonica, tropical japonica) and some admixes between them. Because standard regression techniques used to perform association studies assume that all variables within a data set are mutually independent, genetic relatedness between individuals in a population can generate false positive associations  × 5 temperatures + LT50] we assessed yielded 245 quantitative trait loci (QTL) using 354 rice diversity panel 1 (RDP1) accessions comprising of all five major subpopulations of rice  to other locations in the cell. Together with GO term clusters derived from larger multiple-trait QTL genes, this suggests that the Golgi apparatus where ubiquitination determines the destination of different Golgi-associated proteins has an important function in regulating cold stress tolerance responses. It was previously shown that ubiquitination of proteins in the Golgi can be used as a signal for subcellular localization to many destinations, including, the nucleus, the vacuole, and the plasma membrane  and lowest (4 °C) temperatures tested had the least correlation between membrane damage and seedling survivability, suggesting differences in mechanisms involved in survival at these temperatures compared to 8–12 °C. The 500 QTL controlling membrane integrity and seedling survivability under chilling stress identified in this study cover approximately 25% of the rice genome, while the 40 multiple-trait QTL among them cover approximately 10% of the rice genome. This is in agreement with the notion that cold tolerance is a complex and polygenic trait. Genes within those genomic regions were enriched for terms involved in “carbohydrate biosynthesis and transmembrane transport”, “plasma membrane”, “ubiquitination”, and “ADP binding”. Among them, 71 genes with significant SNPs and allele effects were enriched for “Golgi apparatus”, “transmembrane transport”, “signal transduction”, and “stress response”. These enrichments suggest a likely involvement of the secretory and subcellular localization functions of the Golgi apparatus. With the introduction of QTL derived from cold tolerance cluster-specific mapping, the common themes of “plant growth”, “ubiquitination”, “signaling”, and “transmembrane transport” were highlighted. These terms, along with “Golgi apparatus”, suggest a difference between Tolerant and Sensitive accessions in the function of signaling pathways, possibly involving hormones such as ABA  collection. All of the accessions were all part of the Rice Diversity Panel 1 (RDP1) that were genotyped using the high-density rice array (HDRA) containing 700,000 (700 K) single nucleotide polymorphisms  water with no bleach. After germination, the hydroponics boxes were moved to a chamber with standard growth conditions of 12 h light/12 h dark cycles and 28 °C/25 °C day/night temperatures. The germinated seeds were allowed to grow until 2-weeks of age. At 10 days post germination, the water in the boxes were replaced with ¼-strength Murashige-Skoog basal salt medium  measurements and plants were returned to standard growth conditions  after replacement of hydroponic solution with fresh ¼ x MS media.Plants were allowed to recover for 7 days in normal growth conditions, with watering at least every other day. Low-temperature seedling survivability (LTSS) was recorded, as described below, on day 7.EL was measured after 7 days of chilling stress treatment. For each cultivar, tissue segments were cut from the center of four leaves, washed in DI water, and pooled into glass screw-cap tubes containing 5 mL of DI water having at a conductivity of no more than 1 μS/cm. The tubes were shaken for 1 h and initial conductivity was measured twice using a LAQUA twin B-771 hand-held conductivity meter . The tubes were then boiled for 10 min, shaken for 10 min, and allowed to cool. The total conductivity was measured from cooled tubes. Mean percent EL was then calculated as %EL = [ times 100]. Replicate EL values were averaged, and that average was used for quantitative trait loci (QTL) mapping.LTSS was measured after 7 days of recovery. Alive and dead seedlings were determined by visual inspection as previously described  was calculated using dead and alive counts from LTSS recordings of all five temperatures analyzed. LTSS curves as a function of temperature were calculated using a generalized linear model using a binomial distribution in Cold stress tolerance phenotyping was done on a subset of 354 out of 424 RDP1 accessions that were used for genotyping with the 700 K SNPs of the HDRA  > 4, because most of the Q-Q plots diverged from expected near 4  plots for GWAS mapping.Additional file 2 Figure S2. Approximate genomic locations of 40 Multiple-Trait (qMT) QTL.Additional file 3 Figure S3. Multiple-Trait QTL gene Biological Processes enrichment map.Additional file 4 Figure S4. Multiple-Trait QTL gene Cell Component enrichment map.Additional file 5 Figure S5. Multiple-Trait QTL gene Molecular Function enrichment map.Additional file 6 Figure S6. Filtered Significant SNP Biological Processes enrichment map.Additional file 7 Figure S7. Filtered Significant SNP Cell Component enrichment map.Additional file 8 Figure S8. Filtered Significant SNP Molecular Function enrichment map.Additional file 9 Figure S9. Multiple-Trait+Cluster QTL Biological Process enrichment map.Additional file 10 Figure S10. Multiple-Trait+Cluster QTL Cell Component enrichment map.Additional file 11 Figure S11. Multiple-Trait+Cluster QTL Molecular Function enrichment map.Additional file 12 Figure S12: Model for functional associations of candidate term clusters.Additional file 13 Tables S1-S10. QTL positions resulting from various GWAS mappings.