This work features the development of artificial protein micro-granules for clinical applications, inspired by naturally occurring amyloid structures in bacterial inclusion bodies and mammalian endocrine granules. The authors developed these synthetic granules using a reversible coordination method involving histidine residues and zinc ions (Zn+2). Unlike natural systems, which rely on stereospecificity, the authors demonstrated that their approach allows the formation of hybrid protein materials using two distinct polypeptides, without requiring structural similarities. This method enables the creation of combined protein depots, offering new possibilities for delivering therapeutic proteins in defined ratios and potentially enhancing functional synergies for medical applications.

This study provides replication materials for "Inclusion, Dispersion, and Constraint: Powersharing in the World's States, 1975-2010." It also serves as the public release of the Inclusion, Dispersion, and Constraints dataset, which covers 180 countries from 1975-2010. The creation of this dataset was supported by the National Science Foundation (Grant No. SES-081950766b).

This dataset updates the Inclusion, Dispersion and Constraint power sharing data first introduced by Strøm, Gates, Graham, and Strand (2017). This updated dataset also includes new and improved estimates of power sharing indices.

Team lifting is a complex and collective motor task that possesses both motor and cognitive components. We study the collective load carriage adaptation due to an additional accuracy constraint. Ten dyads performed a first condition in which they collectively transported a load (CC), and a second one in which they transported the same load while maintaining a ball in a target position on its top (PC). The recovery-rate, amplitude, and period of the center-of-mass of the whole system (dyad + table, CoMPACS) were computed. We analyzed the forces and moments exerted at each joint of the upper limbs of the subjects. We observed a decrease in the overall performance of the dyads when the Precision task was added, i.e., i) the velocity and amplitude of CoMPACS decreased by 1,7% and 5,8%, respectively, ii) inter-subject variability of the Moment-Cost-Function decreased by 95% and recovery rate decreased by 19,2% during PC. A kinetic synergy analysis showed that the subjects reorganized their coordinations in the PC. Our results demonstrate that adding a precision task affects the economy of collective load carriage. Notwithstanding, the joint moments at the upper-limbs are better balanced and co-vary more across the paired subjects during the precision task.

Methods We recorded two conditions the first one were the subjects walked side by side at spontaneous speed while carrying a box (CC: Control Condition) and a second one were the individuals were instructed to transport the box, while performing an accuracy task consisting in keeping a ball in the center (PC:Pecision Condition).

Motion capture data were collected using thirteen infrareds (11 MX3 and 2 TS40) transmitter-receiver video cameras (Vicon©, Oxford metric’s, Oxford, United Kingdom) sampled at 200 Hz. Forty-two retro-reflective markers were placed on bony landmarks and on the navel of each subject ( according to Wu et al., 2002, 2005) R. Soc. open sci. and fourteen on the box. The ball used during the PC tests was reflective as well and was tracked by the Vicon© system. In order to record the gait pattern at constant speed (i.e. to exclude the acceleration and deceleration phases at the beginning and end of each trial) the volume calibrated by the Vicon© system (30 m3) was located in the middle of the 20m-long walkway crossed by the subjects. The reflective marks were tracked to define the kinematics of the Poly-Articulated Collective System (PACS) formed by the two individuals and the load they carry (22,23). The data were recorded on one gait cycle defined by the first heel strike of the first subject and the third heel strike of the second subject of the PACS to ensure a cycle of each subject. The 3D reconstruction was performed using Vicon Nexus 1.8.5© software. The two lateral handles used to transport the box were equipped with Sensix® force sensors sampled at 2000 Hz. A 4th order Butterworth filter and a 5 Hz and 10 Hz cut frequency have been applied to analyze the positions of the markers and the forces exerted on the box handles, respectively

The De Leva Anthropometric tables (24) was used to estimate the mass mi and the CoM of each segment i (CoMi) of the PACS and to compute its global CoM (CoMPACS) as follow: ????? = 1 ????? ∑ ???? ?=33 ?=1 with GPACS the 3D position of the CoMPACS in the frame R (the global coordinate system), mPACS the mass of the PACS, n the number of PACS segments (i.e. 16 segments per volunteer plus one segment for the box) and Gi the 3D position of the CoMi in the frame R. The CoM of the box was determined at the intersection point of the vertical lines obtained by hanging it with a thread fixed at different positions. The material used for the box construction, i.e. wood and aluminium, was considered as not deformable. According to Holt et al., (2003), the amplitude (A = Zmax – Zmin, with Z the height of the CoMPACS, in meters,) and the period (peak to peak, in percent of the gait cycle) of the CoMPACS were also assessed. The forward kinetic (Wkf), as well as the vertical (Wv) and external work (Wext) of the CoMPACS were computed according to the method of Bastien et al. (2016). Then based on the external work, the percentage of energy recovered of the CoMPACS in the sagittal plane was computed (called recovery rate RR in Fumery et al., 2018a, 2018b). This parameter assess the amount of energy transferred between the potential and the kinetic energy (Eqn 2). ?? = 100 ?kf+?v−?ext ?kf+?v (2) The closer the value of RR to 100%, the more consistent the locomotor pattern is with the inverted pendulum system (IPS) model of locomotion (26–28,13). In this study, the trajectory of CoMPACS and CoM of an inverted pendulum have been investigated.

Sensix force sensors recorded the forces and moments applied by each individual on the two box handles. Before the computation, the data of the sensors located by specific markers were transfer to the Galilean frame of the laboratory using rotation matrix. A cross correlation method has been applied in order to analyze the coordination between the forces produced by both subjects. To investigate whether the movement of the box results from an action-reaction strategy, we computed the time lag required for the position of the left side and right side of the box to be the same on the medio-lateral, antero-posterior and vertical axis in CC and PC. The coordination was assessed through the forces exerted on three directions (medio-lateral, antero-posterior and vertical axis). This results will reflect the level of coordination of two subjects during a collective transport In order to quantify muscular constraints produced at the upper limb, the Inverse Dynamic Method was used to estimate forces and moments at each joint of the upper limb. The Moment Cost Function was then computed (kg.m2 .s-2 , Costes et al., 2018) as follow : MCF = √??_?? 2 + √??_?? 2 + √??_?? 2 + √??_?? 2 + √??_?ℎ 2 + √??_?ℎ 2 + √????? 2 + √????? Where ML_wt, MR_wt, ML_el, MR_el, ML_sh, MR_sh, Mback and Mneck are the mean values over a PACS gait cycle of the three-dimensional left and right wrist, left and right elbow, left and right shoulder, top of the back and neck moments, respectively. √M2 represents the Euclidian norm of M (i.e. √M2 = √∑ (??) 3 2 ?=1 , with Mi the i-th component of the vector M). Then, the MCF values of each individual was summed to obtain the total moment cost function (Total MCF). This Total MCF allows to quantify the global effort produced at the upper-limbs of the PACS during one gait cycle. Finally, the MCF difference (∆ MCF) was computed as the difference between the two individuals to investigate whether the subjects produced the same effort in the upper limbs during the load transport.

We extracted the synergies by using a principal component analysis (PCA) applied to the wrist, elbow, shoulder, back, and neck joint moment on the right and left sides of the body. The PCA was used to reduce data dimensionality. It consisted in the eigen-decomposition of the co-variance matrix of the joint moment data (Matlab eig function). The joint moments data from one trial per condition were arranged in time × joint moment matrices. In this analysis we only used the y-component which is very close to the norm of the 3D joint moments, except that the y-component (medio-lateral) could be positive and negative. The joint moments were normalized by their amplitude and centered (mean removed) before application of the PCA. We called the eigenvectors extracted from the PCA, dynamic synergy vectors. We computed the VAF (Variance Accounted For) which corresponded to the cumulative sum of the eigenvalues, ordered from the greatest to the lowest value, normalized by the total variance computed as the sum of all eigenvalues. The synergy vectors retained were then rotated using a Varimax rotation method to improve interpretability. We first extracted the synergy vectors for each experimental condition and each participant separately. In this analysis the initial data matrices were constituted of all available time frames in line, concatenated from one trial per condition, and of eight columns corresponding to each joint moment, namely the right wrist, left wrist, right elbow, left elbow, right shoulder, left shoulder, back, and neck. Based on a previous study we extracted 3 synergies in this analysis. We then performed a second analysis to identify possible co-variations between the joint moments of the two participants in each pair. The columns of the initial matrices were thus constituted of the joint moments of the two loaded arms, i.e., the right wrist, elbow, and shoulder joint moments of participant #1, plus the left wrist, elbow and shoulder joint moments of participant #2. Based on a previous study we extracted 2 synergies in this analysis. We used Pearson’s r to order the different synergies similarly between the different subjects and conditions.

A performance score (Scorep) was assigned to each image of the videos captured by the Vicon© system (200 images/s). The score depended on the location of the ball in the target: 1 when the ball was inside the small circle, 0.5 when it was in-between the small and large circle and 0 when it was outside the large circle. The accuracy over the whole gait cycle was measured by an overall score (Scoreaccuracy), expressed in percentage, and calculated as follows: ????????????? = ∑ ?????? ×??? ????? ????? where tgait cycle represents the number of Vicon© images recorded along one gait cycle.

The head, shoulders and pelvis rotation angles were computed around the vertical axis of each individual in the two conditions. The angle was positive when the subjects turned towards the box they carried, otherwise it was negative. The distance between the forehead and the sternum (distance FOR-STE) was also computed in order to investigate the flexion of the cervical spine.

The data were analyzed with Matlab

In project scheduling, resource constraints are usually defined via resource consumption and -availability. Many algorithmic approaches, however, are based on the concept of minimal forbidden sets to represent the resource constraints. Jobs of a forbidden set can be scheduled simultaneously with respect to the precedence constraints, however, they consume more resources than available. Forbidden sets are usually not given explicitly, and by definition even the number of inclusion-minimal forbidden sets may be exponential in the number of jobs. In this paper, we propose a simple branch-and-bound type algorithm to efficiently compute and represent all minimal forbidden sets for a given instance. We evaluate the algorithm on well established test sets of the project scheduling problem library PSPLIB. In addition, we exhibit intimite relations between the different representations of resource constraints and threshold hypergraphs.

The FST-heterozygosity outlier approach has been a popular method for identifying loci under balancing and positive selection since Beaumont and Nichols first proposed it in 1996 and recommended its use for studies sampling a large number of independent populations (at least 10). Since then, their program FDIST2 and a user-friendly program optimized for large datasets, LOSITAN, have been used widely in the population genetics literature, often without the requisite number of samples. We observed empirical datasets whose distributions could not be reconciled with the confidence intervals generated by the null coalescent island model. Here, we use forward-in-time simulations to investigate circumstances under which the FST-heterozygosity outlier approach performs poorly for next-generation single-nucleotide polymorphism (SNP) datasets. Our results show that samples involving few independent populations, particularly when migration rates are low, result in distributions of the FST-heterozygosity relationship that are not described by the null model implemented in LOSITAN. In addition, even under favorable conditions LOSITAN rarely provides confidence intervals that precisely fit SNP data, making the associated p-values only roughly valid at best. We present an alternative method, implemented in a new R package named fsthet, which uses the raw empirical data to generate smoothed outlier plots for the FST-heterozygosity relationship.

1. Repository Information

This repository contains the data produced during the work discussed in in the paper "Towards quantum gravity with neural networks: Solving quantum Hamilton constraints of 3d Euclidean gravity in the weak coupling limit". Please refer to this paper for more details on how the data was produced.

2. Citing

In addition to citing this repository, please also cite the paper mentioned above if you use the data. The citation is:

Hanno Sahlmann and Waleed Sherif 2024 Class. Quantum Grav. 41 215006

3. File Description

In this repository, you will find 4 general directories (here called parent directories):

1. Ground Energy + Fluctuations
2. Misc
3. Quantum Constraint
4. Volume

Each of these directories correposnd to different data produced and discussed in the corresponding parts in the paper mentioned above (e.g. the directory "Ground Energy + Fluctuations" contains the data used in Table 1 and Table 2 in the paper while the "Volume" directory contains the data used in Section 4.3 of the paper).

Some of these parent directories, which involve simulations solving constraints, contain within them several sub-directories (child directories) corresponding to different produced data. The raw data of the simulation can be found in a .json file inside the child directories.

4. Usage

4.1 Raw Simulation Data

The .json files include the raw data produced during the study. These files can be easily accessed using a python script, as an example, by using:

import json

filePath = ...

data = json.load(open(filePath))

where filePath should hold the correct path to the local data once downloaded. Once loaded, the data is handled as a python dict.

The dictionary will have at least one parent key called "Energy". The data in the "Energy" key corresponds to the data being minimised. The data in any other parent key correspond to operators which were being observed during the simulation. For example, in the data in the "Quantum Constraint" directory, some .json files will have multiple parent keys such as FG, H, HG, .... Each of these keys correspond to different operators which were observed during that simulation. Each parent key is yet another dictionary in itself. The structure of the dictionaries corresponding to any parent key are always the same and always include the keys:

• iters
• Mean
• Variance
• Sigma
• R_hat
• TauCorr

Hence, to access the "Mean" values, you use data["Energy"]["Mean"] (or alternatively data["FG"]["Mean"] if you wish to observe the value of the F + G operator during the simulation). The data represents the values during a simulation of typically 500 iterations, hence, each of the keys mentioned above will correspond to an array of 500 items. The iters array includes merely the iteration number. The Mean array includes the value of the expectation value of the constraint at the corresponding iteration. The Variance, Sigma, R_hat and TauCorr includes the values of the variance and error in the expectation value at the given iteration as well as the split R-hat diagnostic and the time correlation also in the given iteration.

4.2 Variational State Data

The files for the variational arrays are too large to be uploaded to a general repository hosting service. Therefore, they will be provided directly upon request in a direct download link. Please contact the author of the paper (Waleed Sherif, email: waleed.sherif@fau.de) for accessing the data.

4.3 Fluctuation results

In some child directories, there will be a .txt file which includes the output of the calculation of the expectation value of some operators and their quantum fluctuations. These are only results, and not data, as the data can only be computed during the simulation.

4.4 Probabilities

The "Misc/Probabilities" directory contains .npy files which should be handled in the same manner as the variational states. These files correspond to the probability simulations conducted in section 4.4.4 in the paper.

5. Contact

Shall you have any unanswered questions regarding the usage of the data, please contact the author:

Waleed Sherif

email: waleed.sherif@fau.de

6. References

The data provided in this repository was produced using the NetKet[1] package

[1] doi: 10.21468/SciPostPhysCodeb.7

GundersonLeal15_AmNat_Anole_DataActivity data for Anolis cristatellusChristian varanid spp activityData on activity for Varanids from Christian and Weavers 1996

CERN-LHC. Measurement of semi-inclusive distributions of charged-particle jets recoiling from a high-transverse momentum trigger hadron in p-Pb collisions at sqrt(sNN)=5.02 TeV. Jets are reconstructed from charged-particle tracks using the anti-kT algorithm with resolution parameter R=0.2 and 0.4. A data-driven statistical approach is used to correct the uncorrelated background jet yield. Recoil jet distributions are reported for jet transverse momentum 15<p_{T,jet}^{ch} <50 GeV/c and are compared in various intervals of p-Pb event activity, based on charged-particle multiplicity and zero-degree neutral energy in the forward (Pb-going) direction. Analysis is based on data collected by ALICE in 2013.

Charged tracks are constrained to the pseudorapidity range |eta_{track}| < 0.9. Trigger tracks are required to be in the pT ranges 12 to 50 GeV/c and 6 to 7 GeV/c.

Pseudorapidity of reconstructed jets is constrained by a fiducial cut |eta_{jet}|<0.9 - R. Lowest p_{T} of a jet constituent track is 150 MeV/c. The angle enclosed by a trigger track and a recoiling jet is greater than pi - 0.6 rad.

Currently, over 70% of global marine bathymetry information is primarily estimated using marine gravity data derived from satellite altimetry and a substantial amount of single-beam bathymetric data in specific regions. The accuracy of these depth estimates is influenced by the abundance of prior bathymetry information and the algorithms used for estimation. This study proposes a method that, in addition to using single-beam bathymetric data as the primary depth constraint, incorporates nautical chart depths and multi-beam bathymetric control point information as further constraints. The bathymetry estimation method combines the Gravity-Geologic Method (GGM) and Deep Neural Network (DNN) techniques for retraining to derive three 1′×1′ grid bathymetric models for the South China Sea region between 112°E-118°E and 10°N-18°N. We selected additional multi-beam bathymetric data check points within the GEBCO2023 model in the study area as the benchmark for external accuracy assessment. Compared to the model constructed solely from single-beam bathymetric data (GGM_A), the multi-source data-constrained depth model (GGM_B) and the depth model combining GGM with short-wavelength gravity anomalies retrained using DNN (GGM_C) showed reductions in the Root Mean Square (RMS) error of 16.66m and 17.42m, respectively, when compared to the extracted multi-beam check point data. The Standard Deviation (STD) was reduced by 17.26m and 18.03m, respectively. The relative precision of the model has improved by approximately 13%. Compared to the latest internationally released bathymetric models DTU21, topo_27.1, SRTM15_V2.5.5, SRTM15_V2.6, ETOPO2022, and GEBCO2022, the GGM_C model showed reductions in RMS error of 132.30m, 74.43m, 60.58m, 75.01m, 65.85m, and 65.85m, respectively, and reductions in STD of 130.85m, 70.59m, 58.61m, 70.97m, 62.23m, and 62.23m, respectively, when compared with the multi-beam check point data. Compared to the aforementioned models, the relative precision of the GGM_C model has improved by approximately 52%, 38%, 33%, 38%, 35%, and 35%, respectively. The GGM method effectively leverages the correlation between gravity anomalies and prior bathymetric information, resulting in a seafloor topography model in the South China Sea region that is significantly superior to other models. In summary, the GGM, which makes full use of multi-source bathymetric data as constraints, is one of the effective means for inverting high-precision seafloor topography. The integration of the DNN with GGM can further enhance the inversion accuracy to a certain extent.

IntroductionUnderstanding the impacts of climate change and land use dynamics on parasitic plants is crucial for ecological restoration and sustainable resource management in arid regions. This study proposes a two-dimensional modeling framework that integrates parasitic constraints and land use dynamics to predict the potential suitable habitat of Cistanche deserticola, a medicinal plant obligately parasitic on Haloxylon ammodendron.MethodsUsing an optimized MaxEnt model, host suitability probability was incorporated as a continuous probabilistic constraint, and high-resolution land use data were coupled to enhance ecological realism. The framework was applied to assess habitat suitability under current (1970-2000) and future climate scenarios (2050s, 2070s, 2090s, SSP126, SSP370, SSP585).ResultsThe inclusion of parasitic constraints reduced the suitable habitat area by 4.5% (from 138.20 × 104 km² to 131.92 × 104 km²) and exacerbated habitat fragmentation, particularly in Northwest China. Future projections reveal a decrease in the total suitable habitat area but an increase in the area of highly suitable regions, with the centroid shifting towards the northwest. Land use analysis demonstrated that unused land (70.21%) and grassland (13.81%) constitute the primary habitats, highlighting their significance for sustainable cultivation. Key environmental drivers identified include July precipitation, soil pH, and temperature of the warmest quarter. The model exhibited high predictive accuracy (AUC: 0.947-0.949).DiscussionThe framework provides a reliable tool for assessing host-parasite interactions and land use impacts. These findings offer valuable insights for adaptive management strategies that balance ecological restoration and the sustainability of medicinal resources in arid ecosystems.

1. Thermal constraints imposed by the environment limit the activity time of ectotherms and have been a central issue in ecophysiology. Assessing these restrictions is key to determining the vulnerability of species to changing thermal niches and developing conservation strategies. 2. We generate an explicit tortoise model of thermal constraints at both micro and macroclimate scales based on thermophysiology parameters and environmental operative temperatures during a biologically significant period. As a study model, we use a vulnerable species of gopher tortoise (Gopherus evgoodei), whose primary habitat is the tropical dry forests in northwestern Mexico. 4. Our mechanistic model is based on a monitoring of 5-years of environmental operative temperatures (Te). Here, we use the hours of activity (ha) and hours of thermal restriction (hr), calculated from the voluntary temperature range of G. evgoodei with respect to Te, to project and compare the thermal constraints across space and time. In addition, this model was projected using a pessimistic climate change scenario for 2070 (RCP 8.5). 5. The results show that the period of activity of G. evgoodei, predicted by ha and hr, is limited by the frequency and availability of Te and differs significantly throughout the year and among years. In addition, under the RCP 8.5 scenario, we predict that hr will increase considerably and exceed the critical value (3.11 hr) placing this species as highly vulnerable. 6. We discuss and compare the period of potential activity, thermoregulation strategies, and costs and benefits with other Gopherus species. Finally, we identify critical areas to develop management strategies for protecting this Mexican endemic tortoise. Methods The data correspond to the hours of activity and restriction throughout the distribution of the tortoise Gopherus evgoodei according to our ecophysiological models. These data were calculated according to the protocol of Sinervo et al 2010. Science. 328(5980), 894-899. A detailed description of the data collection can be seen in Lara-Reséndiz, et al. 2022. Journal of Thermal Biology, 104, 103192. In addition, a polygon of this gopher tortoise's distribution and layers with ecophysiological models is included here. Which were developed with R and QGIS software.

The STEREO experiment is a very short baseline reactor antineutrino experiment. It is designed to test the hypothesis of light sterile neutrinos being the cause of a deficit of the observed antineutrino interaction rate at short baselines with respect to the predicted rate, known as the Reactor Antineutrino Anomaly. The STEREO experiment measures the antineutrino energy spectrum in six identical detector cells covering baselines between 9 and 11 m from the compact core of the ILL research reactor. In this article, results from 179 days of reactor turned on and 235 days of reactor turned off are reported at a high degree of detail. The current results include improvements in the modelling of detector optical properties and the gamma-cascade after neutron captures by gadolinium, the treatment of backgrounds, and the statistical method of the oscillation analysis. Using a direct comparison between antineutrino spectra of all cells, largely independent of any flux prediction, we find the data compatible with the null oscillation hypothesis. The best-fit point of the Reactor Antineutrino Anomaly is rejected at more than 99.9% C.L. To allow inclusion of this work into global oscillation analyses and further works, we provide various results of our analysis in digitised form.

In this contribution, a scattered data approximation problem, chosen from the literature and using the Radial Basis Function (RBF) approach, is considered for the application of point cloud modelling. Three solutions are investigated for the approximation problem. First, a technique known from the literature is investigated using a linear combination of thin-plate splines and linear polynomials, with additional constraint equations. Then, using the same approximation function as before, a technique is developed for a rigorous consideration of the constraint equations. Finally, a technique is presented in which the approximation function consists only of a linear combination of thin-plate splines, without the introduction of linear polynomials and constraint equations. In addition, some interpolation problems with the RBF approach are discussed to present the differences between an interpolation with thin-plate splines only and an interpolation with thin-plate splines together with linear polynomials and constraint equations. Numerical examples are given to illustrate and discuss the solutions from the different techniques.

Mass Spectrometry Imaging and Serial Block-Face Electron Microscopy raw data of centipede (Scolopendra morsitans) venom glands. Comparison of venom glands by mass spectrometry imaging (MSI): Complementing our analyses of secreted venom, we also examined the effect of secretion on the relative abundance and distribution of venom components within full three-dimensionally (3D) reconstructed venom glands imaged by mass spectrometry imaging. Venom glands were dissected from S. morsitans after four different experimental treatments: after a starving period of five weeks to ensure that the venom gland was fully replenished (“full”); after venom was collected using electrostimulation (“electro”); after venom was collected using the defensive milking technique described above (“defensive”); or after envenoming a cricket (“predatory”). Dissected venom glands were fixed in RCL2, dehydrated in a graded ethanol series and embedded in paraffin as described previously9,41. Importantly, this sample preparation protocol depletes lipids and other small molecules, making it likely that the species observed are peptides or small proteins. Each gland was sectioned at 7 µm, transferred to microscope slides and washed with xylene to remove paraffin. The sections were then sprayed with CHCA (0.7 mg/mL in 50% ACN [vol/vol] and 0.2 % TFA [vol/vol]), using a Bruker ImagePrep automated matrix sprayer. Samples were analysed using a Bruker Autoflex Speed MALDI-TOF/TOF MS with Flex Imaging v4.1 and Flex Control v3.4 software. Spectra were acquired in linear positive mode over a mass range of 1000–20000 m/z using a medium laser spot size for a spatial resolution of 50 µm, and acquiring 600 shots at 2000 Hz. The data was analyzed, normalised, aligned, visualised, and 3D reconstructed using SCiLS Lab MVS premium (Bruker Daltonics) In total, seven venom glands were used to create three-dimensional reconstructions of MSI data. In addition, we collected MSI spectra from at least 4 glands and 100 slices per treatment (full: 8 glands, 166 slices, 152079 spectra, area 380.197 mm2; electro: 6 glands, 104 slices, 84115 spectra, area 210.287 mm2; defensive: 4 glands, 155 slices, 87081 spectra, area 217.702 mm2; predatory: 4 glands, 112 slices, 557701 spectra; all regions combined: 380976 spectra, area 952.44 mm2) and used these to generate venom gland-wide mean spectra (with one standard deviation) in SCiLS Lab MVS premium. The in SCiLS Lab integrated pLSA component analysis13 was used to look for distribution patterns. Serial Block-Face Electron Microscopy: For serial block-face EM (SBEM), samples were fixed overnight at 4°C in a solution containing 2.5% glutaraldehyde in 0.1 M sodium cacodylate buffer. The next day, samples were postfixed in a solution comprising 2% osmium tetroxide and 1% potassium ferricyanide in 0.1 M cacodylate buffer. Samples were then microwave processed (BioWave, Pelco, Clovis, USA) using a 2 min on–2 min off–2 min on cycle repeated twice at 80W under vacuum. Following this, samples were washed three times in ddH20; once on the bench and twice in the microwave at two cycles of 40 seconds at 80W under vacuum. Sequentially, samples were then immersed in 1% thiocarbohydrazide in ddH20, 2% osmium tetroxide in ddH20, 1% uranyl acetate in ddH20, and then in lead aspartate solution following the same microwave incubation and rinse cycle as described above, except for uranyl acetate incubation, during which the microwave temperature was raised from 22°C to 45°C. The lead aspartate solution was made by adding 0.066 g lead nitrate to 10 ml 0.03 M aspartic acid then adjusting pH to 5 by adding 1 N KOH. Subsequently, samples were dehydrated in ethanol at increasing concentrations (50%, 60%, 70%, 80%, 90%, 100%, 100%), employing microwave processing in cycles of 1 minute on, 1 minute off, and 1 minute on at 150W, without vacuum for each concentration. Samples were then embedded in Durcupan resin (Sigma Aldrich) at increasing concentrations (1:3, 1:2, 1:1, 2:1, 3:1, 100%, 100%, 100%) using a microwave cycle of 3 minutes at 150W with vacuum application for each concentration and left to polymerise in a 60°C oven for 48 hours. Following polymerisation, hardened samples were trimmed and polished using an ultramicrotome (Leica UC6) and mounted on a SBEM stub using conductive epoxy. A 50 µm x 100 µm x 65 µm image volume comprising several venom gland subunits was acquired using a VolumeScope SBEM (Thermo Fisher). During acquisition, the sample was cut at 50 nm thickness and imaged in low vacuum (10 Pa) at a pixel scale of 9 nm x 9 nm with a landing beam energy of 2 kV, 0.1 nA current, and pixel dwell time of 2 µs. The resulting image stack was then contrast adjusted, denoised, and aligned using the TrakEM2 plugin in FIJI47,48. To reconstruct the venom gland subunit, the aligned image stack was down-sampled to 1 µm x 1 µm x 1 µm voxel size using Amira (2020.2, ThermoFischer Scientific) and manually segmented using the segmentation editor. The resulting labels were then converted into surface meshes and visualised in different transparencies. To reconstruct neurons, annotate synapses, and generate connectivity graphs, we used CATMAID, an open source and web-based software49. Synapses were identified by the presence of a presynaptic cloud of vesicles adjacent to a synaptic cleft (Fig. 4H-I). Only connections that contained greater than a single synapse were included in our connectivity analysis (SI Fig. 25C-D).

ABSTRACT The purpose of the present study was to perform a systematic review of the literature to investigate how and with what modifications or adaptations constraint-induced movement therapy has been employed in clinical practice for therapeutic interventions in children with cerebral palsy. Searches were conducted of the CAPES (Brazilian fostering agency) periodical portal, Pubmed, Bireme, Science Direct, Scielo and PEDro databases for relevant articles published between January 2010 and May 2016. The articles retrieved were evaluated, scored and qualified by two blinded reviewers using the Physical therapy Evidence Database Scale. The searches led to the retrieval of 102 articles, 12 of which were included in the present systematic review. A table was created containing information on the study groups, inclusion criteria, intervention, intervention frequency, difficulties encountered, evaluations and outcomes. Considerable variety was found in the therapeutic intervention models. The findings of the present review demonstrate that constraint-induced movement therapy in pediatric clinical practice is not employed in its original form. Although the studies analyzed did not have a common methodology regarding the use of this type of therapy, the method has been adapted with considerable flexibility, providing promising, positive results regarding the therapeutic intervention of the paretic upper limb in children with cerebral palsy.

Body size of life on Earth spans many orders of magnitude, and with it scales the energetic requirements of organisms.  Thus, changes in environmental energy should impact community body-size distributions in predictable ways by reshaping ecological and niche dynamics. We examine how carbon, oxygen, and temperature, three energetic drivers, impact community size-based assembly in deep-sea bivalves. We demonstrate that body-size distributions are influenced by multiple energetic constraints. Relaxation in these constraints leads to an expansion of body-size niche space through the addition of novel large size classes, increasing the standard deviation and mean of the body-size distribution. With continued Anthropogenic increases in temperature and reductions in carbon availability and oxygen in most ocean basins, our results point to possible radical shifts in invertebrate body size with the potential to impact ecosystem function.

Prey alter their foraging when threatened by predators. Two mutually inclusive hypotheses explain this response. The first entails that defense behaviors to minimize exposure to predators prevent prey from achieving their preferred diet, while the second postulates that prey deliberately change their diet to fulfill new stress-induced nutritional demands. We combined field observations and laboratory experiments to determine which hypothesis dictates snail dietary responses to risk of beetle predation. Snails exposed to predation-risk reduced activity, increased climbing, increased respiration, ate distinctively to achieve a certain nutrient target, and preferred eating on the cage floor at the costs of nutritional imbalance and elevated risk. When only carbohydrates-rich food was on the floor, stressed snails reduced activity and foraged less, but when only protein-rich food was on the floor snails increased activity and consumed more carbohydrates than their no-risk conspecifics. This..., Snails' density- counting live snails in 1 square meter, in each microhabitat Snails' activity and vertical location- observations Snails' physiological stress- CO2 respiration rates Snails' macronutrient consumption- weighing artificial food consumption  , , # Data from: Constraints and demands interact to affect prey dietary reaction to predation

https://doi.org/10.5061/dryad.q2bvq83rr

Tha manuscript includes three experimental parts:

1. Measuring snail density and behavior in the field To quantify the snail’s habitat use and activity, we randomly located 34 one square meter plots within the Loess Park Nature Reserve. In each plot, we recorded the number of snails in each patch type ( i.e., biological soil crust, perennial shrubs, or plant litter)  and noted whether snails were active or not. We also noted whether the snails were above or below a threshold height of 2 cm, since beetles pose much lesser risk above this height. In all plots, the relative area of each patch type was evaluated. The overall coverage could exceed 100% since shrubs canopy overlapped with other patch types. Based on these estimations we calculated the snail density in each patch type. During the observations we...

A growing body of theoretical and experimental evidence suggests that intramolecular epistasis is a major determinant of rates and patterns of protein evolution and imposes a substantial constraint on the evolution of novel protein functions. Here, we examine the role of intramolecular epistasis in the recurrent evolution of resistance to cardiotonic steroids (CTS) across tetrapods, which occurs via specific amino acid substitutions to the α-subunit family of Na,K-ATPases (ATP1A). After identifying a series of recurrent substitutions at two key sites of ATP1A that are predicted to confer CTS resistance in diverse tetrapods, we then performed protein engineering experiments to test the functional consequences of introducing these substitutions onto divergent species backgrounds. In line with previous results, we find that substitutions at these sites can have substantial background-dependent effects on CTS resistance. Globally, however, these substitutions also have pleiotropic effects that are consistent with additive rather than background-dependent effects. Moreover, the magnitude of a substitution’s effect on activity does not depend on the overall extent of ATP1A sequence divergence between species. Our results suggest that epistatic constraints on the evolution of CTS-resistant forms of Na,K-ATPase likely depend on a small number of sites, with little dependence on overall levels of protein divergence. We propose that dependence on a limited number sites may account for the observation of convergent CTS resistance substitutions observed among taxa with highly divergent Na,K-ATPases. Methods Construction of expression vectors. ATP1A1 and ATP1B1 wild-type sequences for eight selected tetrapod species were synthesized by InvitrogenTM GeneArt. ATP1A1/B1 sequences used in these constructs can be found under the following accession numbers: Rattus norvegicus (ATP1A1 – X05882 ; ATP1B1 – NM013113.2), Chinchilla lanigera (ATP1A1 – XM005389040; ATP1B1 – XM005398203), Rhabdophis subminiatus (ATP1A1 – MT928191; ATP1B1 – ON168934), Xenodon rhabdocephalus (ATP1A1 – MT928200; ATP1B1 – ON168935), Varanus exanthematicus (ATP1A1 – MT928184; ATP1B1 – ON168936), Tupinambis teguixin (ATP1A1 – MT928189; ATP1B1 – ON168937), Struthio camelus (ATP1A1 – XM009675281; ATP1B1 – XM009675170), Pterocles gutturalis (ATP1A1 – XM010081314; ATP1B1 – XM010078905). The ?1-subunit genes were inserted into pFastBac Dual expression vectors (Life Technologies) at the p10 promoter with XhoI and PaeI (FastDigest Thermo ScientificTM) and then control sequenced. The α1-subunit genes were inserted at the PH promoter of vectors already containing the corresponding ?1-subunit proteins using In-Fusion® HD Cloning Kit (Takara Bio, USA Inc.) and control sequenced. All resulting vectors had the α1-subunit gene under the control of the PH promoter and a ?1-subunit gene under the p10 promoter. The resulting eight vectors were then subjected to site-directed mutagenesis (QuickChange II XL Kit; Agilent Technologies, La Jolla, CA, USA) to introduce the codons of interest. In total, 21 vectors were produced. Generation of recombinant viruses and transfection into Sf9 cells. Escherichia coli DH10bac cells harboring the baculovirus genome (bacmid) and a transposition helper vector (Life Technologies) were transformed according to the manufacturer’s protocol with expression vectors containing the different gene constructs. Recombinant bacmids were selected through PCR screening, grown, and isolated. Subsequently, Sf9 cells (4 x 105 cells*ml) in 2 ml of Insect-Xpress medium (Lonza, Walkersville, MD, USA) were transfected with recombinant bacmids using Cellfectin reagent (Life Technologies). After a three-day incubation period, recombinant baculoviruses were isolated (P1) and used to infect fresh Sf9 cells (1.2 x 106 cells*ml) in 10 ml of Insect-Xpress medium (Lonza, Walkersville, MD, USA) with 15 mg/ml gentamycin (Roth, Karlsruhe, Germany) at a multiplicity of infection of 0.1. Five days after infection, the amplified viruses were harvested (P2 stock). Preparation of Sf9 membranes. For production of recombinant NKA, Sf9 cells were infected with the P2 viral stock at a multiplicity of infection of 103. The cells (1.6 x 106 cells*ml) were grown in 50 ml of Insect-Xpress medium (Lonza, Walkersville, MD, USA) with 15 mg/ml gentamycin (Roth, Karlsruhe, Germany) at 27°C in 500 ml flasks (35). After 3 days, Sf9 cells were harvested by centrifugation at 20,000 x g for 10 min. The cells were stored at -80 °C and then resuspended at 0 °C in 15 ml of homogenization buffer (0.25 M sucrose, 2 mM EDTA, and 25 mM HEPES/Tris; pH 7.0). The resuspended cells were sonicated at 60 W (Bandelin Electronic Company, Berlin, Germany) for three 45 s intervals at 0 °C. The cell suspension was then subjected to centrifugation for 30 min at 10,000 x g (J2-21 centrifuge, Beckmann-Coulter, Krefeld, Germany). The supernatant was collected and further centrifuged for 60 m at 100,000 x g at 4 °C (Ultra- Centrifuge L-80, Beckmann-Coulter) to pellet the cell membranes. The pelleted membranes were washed once and resuspended in ROTIPURAN® p.a., ACS water (Roth) and stored at -20 °C. Protein concentrations were determined by Bradford assays using bovine serum albumin as a standard. Three biological replicates were produced for each NKA construct. Verification by SDS-PAGE/western blotting. For each biological replicate, 10 mg of protein were solubilized in 4x SDS-polyacrylamide gel electrophoresis sample buffer and separated on SDS gels containing 10% acrylamide. Subsequently, they were blotted on nitrocellulose membrane (HP42.1, Roth). To block non-specific binding sites after blotting, the membrane was incubated with 5% dried milk in TBS-Tween 20 for 1 h. After blocking, the membranes were incubated overnight at 4 °C with the primary monoclonal antibody α5 (Developmental Studies Hybridoma Bank, University of Iowa, Iowa City, IA, USA). Since only membrane proteins were isolated from transfected cells, detection of the α subunit also indicates the presence of the β subunit. The primary antibody was detected using a goat-anti-mouse secondary antibody conjugated with horseradish peroxidase (Dianova, Hamburg, Germany). The staining of the precipitated polypeptide-antibody complexes was performed by addition of 60 mg 4-chloro-1 naphtol (Sigma-Aldrich, Taufkirchen, Germany) in 20 ml ice-cold methanol to 100 ml phosphate buffered saline (PBS) containing 60 ml 30% H2O2. Ouabain inhibition assay. To determine the sensitivity of each NKA construct against cardiotonic steroids (CTS), we used the water-soluble cardiac glycoside, ouabain (Acrōs Organics), as our representative CTS. 100 ug of each protein was pipetted into each well in a nine-well row on a 96-well microplate (Fisherbrand) containing stabilizing buffers (see buffer formulas in Petschenka et al. 2013). Each well in the nine-well row was exposed to exponentially decreasing concentrations of ouabain (10-3 M, 10-4 M, 10-5 M, 10-6 M, 10-7 M, 10-8 M, dissolved in distilled H2O), plus distilled water only (experimental control), and a combination of an inhibition buffer lacking KCl and 10-2 M ouabain to measure background protein activity [48]. The proteins were incubated at 37°C and 200 rpms for 10 minutes on a microplate shaker (Quantifoil Instruments, Jena, Germany). Next, ATP (Sigma Aldrich) was added to each well and the proteins were incubated again at 37°C and 200 rpms for 20 minutes. The activity of NKA following ouabain exposure was determined by quantification of inorganic phosphate (Pi) released from enzymatically hydrolyzed ATP. Reaction Pi levels were measured according to the procedure described in Taussky and Shorr (1950) (see Petschenka et al. 2013). All assays were run in duplicate and the average of the two technical replicates was used for subsequent statistical analyses. Absorbance for each well was measured at 650 nm with a plate absorbance reader (BioRad Model 680 spectrophotometer and software package). ATP hydrolysis assay. To determine the functional efficiency of different NKA constructs, we calculated the amount of Pi hydrolyzed from ATP per mg of protein per minute. The measurements (the mean of two technical replicates) were obtained from the same assay as described above. In brief, absorbance from the experimental control reactions, in which 100 mg of protein was incubated without any inhibiting factors (i.e., ouabain or buffer excluding KCl), were measured and translated to mM Pi from a standard curve that was run in parallel (1.2 mM Pi, 1 mM Pi, 0.8 mM Pi, 0.6 mM Pi, 0.4 mM Pi, 0.2 mM Pi, 0 mM Pi). Statistical analyses of functional data.
ATPase activity in the presence and absence of the CTS ouabain was measured following Petschenka et al. (2013). Background phosphate absorbance levels from reactions with inhibiting factors were used to calibrate phosphate absorbance. For ouabain sensitivity measurements, these calibrated absorbance values were converted to percentage non-inhibited NKA activity based on measurements from the control wells (as above). For each of the 3 biological replicates, log10 IC50 values were estimated using a four-parameter logistic curve, with the top asymptote set to 100 and the bottom asymptote set to zero, using the nlsLM function of the minipack.lm library in R. To measure baseline recombinant protein activity, the calculated Pi concentrations of 100 mg of protein assayed in the absence of ouabain were converted to nmol Pi/mg protein/min. 1. Petschenka G, Fandrich S, Sander N, Wagschal V, Boppré M, Dobler S. Stepwise evolution of resistance to toxic cardenolides via genetic substitutions in the Na+/K+‐ATPase of milkweed butterflies (Lepidoptera: Danaini). Evolution. 2013;67: 2753–2761. 2. Taussky HH, Shorr E. A microcolorimetric method for the determination of inorganic phosphorus. J Biol Chem. 1953;202: 675–685.

1) Determining the factors governing investment in immunity is critical for understanding host-pathogen ecological and evolutionary dynamics. Studies often consider disease resistance in the context of life-history theory, with the expectation that investment in immunity will be optimized in anticipation of disease risk. Immunity, however, is constrained by context-dependent fitness costs. How the costs of immunity vary across life-history strategies has yet to be considered. 2) Pea aphids are typically unwinged but produce winged offspring in response to high population densities and deteriorating conditions. This is an example of polyphenism, a strategy used by many organisms to adjust to environmental cues. The goal of this study was to examine the relationship between the fitness costs of immunity, pathogen resistance, and the strength of an immune response across aphid morphs that differ in life-history strategy but are genetically identical. 3) We measured fecundity of winged and unwinged aphids challenged with a heat-inactivated fungal pathogen, and found that immune costs are limited to winged aphids. We hypothesized that these costs reflect stronger investment in immunity in anticipation of higher disease risk, and that winged aphids would be more resistant due to a stronger immune response. However, producing wings is energetically expensive. This guided an alternative hypothesis—that investing resources into wings could lead to a reduced capacity to resist infection. 4) We measured survival and pathogen load after live fungal infection, and we characterized the aphid immune response to fungi by measuring immune cell concentration and gene expression. We found that winged aphids are less resistant and mount a weaker immune response than unwinged aphids, demonstrating that winged aphids pay higher costs for a less effective immune response. 5) Our results show that polyphenism is an understudied factor influencing the expression of immune costs. More generally, our work shows that in addition to disease resistance, the costs of immunity vary between individuals with different life-history strategies. We discuss the implications of these findings for understanding how organisms invest optimally in immunity in light of context-dependent constraints.