dataesr/scientific-paragraphs-categorization huggingface dataset:
Distant off-targets To illustrate PatchSearch effectiveness, we present an example of the identification of distant off-targets from the TOUGH-M1 dataset  (46). The TOUGH-M1 dataset contains proteins with dissimilar global sequences and structures. The structural dissimilarity was measured by the TMscore  (47). In this dataset, off-targets share no significant sequence (sequence identity < 30. 0%) or fold similarity (TMscore < 0. 4). This dataset is divided in two lists: a 'positive' list with proteins able to bind a chemically similar ligands and a 'negative' list in which the proteins interact with dissimilar ligands. Considering as input the binding site around Adenosine DiPhosphate (ADP) molecule in a myosin structure (PDB ID: 1lkx), we used the server to rank 20 proteins in 'positive' list and 20 proteins in 'negative' list for ADP.
GTPase HRas protein is able to bind to Guanosine TriPhosphate (GTP) or Guanosine DiPhosphate (GDP). In this structure, GT-Pase HRas protein has been co-crystallized with Phosphoaminophosphonic Acid Guanylate Ester (ligand identifier for the PDB: GNP), a non-hydrolyzable analog of GTP, and the N-[1-(1H-indol-3-ylmethyl)piperidin-4-yl]-Ltryptophanamide (ligand identifier for the PDB: RND), a small molecule, altering experimentally the GTPase HRas activity. Logically, 4nym structure is considered as a negative protein for the binding site comparison between ADP  The patch was extracted around ADP in the 1lkx myosin structure. Structural similarities between the patch and the entire surface of 40 PDB structures known to be able to interact, i. e. 'positive', or not, 'negative', with ADP or similar ligands, according to the TOUGH1-dataset.
The sequence identity and the structure similarity were calculated between 1lkx against the each 40 PDB structures. The estimated affinity reported is the best score, computed by Smina program with Vinardo scoring function, between ADP and the five potential sites with the highest structural similarities according to the rBC score. and RND, because these molecules are chemically dissimilar. However, the PatchSearch web server searches structural similarities onto the entire surface of the protein. The favorable computed binding affinity is basically due to the fact that PatchSearch has retrieved the GTP/GDP binding site of GTPase HRas protein (Figure  3 ). This unexpected result can be explained by the high chemical similarities between ADP and GDP. It reinforces strengthens the interest of taking into account the entire surface protein, not only comparing predetermined binding sites for the finding of new off-targets.
5 KCl, 26 NaHCO 3 , 10 D-glucose, 1. 25 Na 2 HPO 4 , 1. 2 MgSO 4 , 2. 5 CaCl 2, 315 Osm, pH 7. 4. Slices were then transferred to 100% ACSF solution at room temperature for 0. 5-5 h before recording. One to three recordings were obtained per mouse with a minimum of two mice studied per group; variation within a mouse was not less than that within a group. For experiments with control and drug treatment within the same cell, only one cell per slice was studied. Recording solutions and data acquisition. The pipette solution consisted of the following (in mM): 130 K gluconate, 15 KCl, 10 HEPES, 5 EGTA, 0. 1 CaCl 2 , 4 MgATP and 0. 4 NaGTP, 305 mOsm, pH 7. 2 with NaOH; this solution is based on the native intracellular chloride concentration in arcuate kisspeptin neurons determined using gramicidin perforatedpatch recordings.
(DeFazio et al. , 2014). A 15 mV liquid junction potential was negated before each recording  (Barry, 1994). During all recordings, slices were continuously superfused at 2 ml/min with ACSF bubbled with 95% O 2 5% CO 2 and kept at 30 -31°C with an inlineheating unit (Warner Instruments). GFP-positive cells were visualized with a combination of infrared differential interference contrast and fluorescence microscopy on an Olympus BX50WI microscope. Recordings were made with an EPC-10 patch-clamp amplifier and a computer running Patchmaster software (HEKA Elektronik). For dynamic clamp ex-periments, membrane voltage was filtered at 10 kHz and digitized at 20 kHz for data analysis. For voltage-clamp recordings of GABA and AMPA PSCs and potassium currents, membrane current was digitized at 10 kHz and filtered at 7 kHz.
V 0. 5 parameters and k are reported as means of values obtained from fits to data from each cell. After normalization to the peak value, inactivation and recovery time course [tau, ()] curves for each cell in each group were fit with single exponential decay or recovery equations. It was not possible to quantify all parameters from every cell, because not all cells remained within our quality control standards long enough for inclusion in the analysis of the time dependence of activation and inactivation. The OVX groups thus contained 9 cells for voltage dependence, 6 for recovery from inactivation and 5 for inactivation time course; the OVXϩE groups contained 12, 9, and 9 cells, respectively. Action potential properties. To characterize action potential properties, current-clamp recordings were obtained in the presence of antagonists of receptors for fast synaptic transmission (in M: 20 D-APV, 10 CNQX, 50 picrotoxin).
5 mM (S)-MCPG, Tocris Bioscience] were blocked. A pipette containing 100 M glutamate in a solution containing the following (in mM): 150 NaCl, 3. 5 KCl, 2. 5 CaCl 2 , 1. 3 MgCl 2 , 10 HEPES, and 10 D-glucose was positioned 10 -50 m from the cell. A baseline measure of membrane potential was obtained, then a 10 -40 ms, 4 -20 PSI pressure application of glutamate was triggered 50 ms before a second ramp was initiated. Data were analyzed as described previously  (DeFazio et al. , 2014). Determination of synaptic conductances and time courses for dynamicclamp studies. The decay time constant of GABA PSCs is relatively independent of membrane potential in the range (Ϫ60 to Ϫ75 mV) used in these studies, but is strongly dependent on the pipette chloride concentration  (Houston et al. , 2009). It is thus important to use a physiologic chloride concentration to determine the conductance time course for use in dynamic clamp studies.
Whole-cell voltage-clamp recordings of miniature GABA or AMPA receptor-mediated PSCs were obtained using a physiologic 15 mM Cl Ϫ pipette solution at a holding potential of Ϫ75 mV in ACSF containing 1 M TTX. To isolate GABA A receptor-mediated miniature PSCs (GABA mPSCs), 20 M D-APV, 10 M CNQX were added to block NMDA and AMPA receptors, respectively. To isolate AMPA receptor-mediated miniature PSCs (AMPA mPSCs), 20 M D-APV, 100 M picrotoxin were added to block NMDA and GABA A, receptors, respectively. After detection and visual verification of each event using custom software in Igor Pro (WaveMetrics), conductance was calculated from the mean PSC amplitude and the maximum PSC amplitude for each recording by dividing current by the driving force, V Ϫ E rev. The decay time constant was estimated using a monoexponential fit from 80 to 20% of the peak of the averaged mPSC for each cell.
3 GHz, 8-core processors, 8x16Gb DDR3-1866 SDRAM, ASLabs) and data acquisition system (PCIe-6361 Multifunction DAQ card with a BNC interface, National Instruments) interacting with the Patchmaster EPC10 patch-clamp amplifier system as described. Dynamic clamp was implemented using freely available QuB software (MLab edition, https://milesculabs. biology. missouri. edu/QuB. html), as described previously  (Milescu et al. , 2008). The digital outputs of the EPC10 were used to trigger independent GABA and AMPA synaptic conductances in the dynamic-clamp system. The time course of the GABA and AMPA receptor-mediated postsynaptic conductances ( g syn ) was modeled based on the mPSC data in Table  1 using a monoexponential of 9  and 2. 3 ms, respectively. The input to the dynamic clamp system is the membrane potential of the cell (V m ), read from the EPC10 patch-clamp amplifier in current-clamp mode; the output from the system is the computed command current (I dc ), which drives the current command input of the EPC10.
To test the effect of blocking voltage-dependent potassium and calcium channels, some experiments included 4AP (0. 5 mM) and/or Ni 2ϩ (300 M) as detailed below. Before each acquisition series, series resistance (R s Ͻ 20 M⍀) was estimated as above and compensated 95% using the C slow and R s compensation circuitry of the amplifier. Bridge balance was confirmed in current-clamp mode by manually adjusting the bridge to cancel the fast transient voltage deflection in response to a 5 ms duration 5 pA hyperpolarizing current step. In most cases, R s estimated in voltage clamp from the peak current in response to a 20 ms, 5 mV hyperpolarizing step in voltage-clamp, corresponded well with R s estimated by the automatic C slow compensation circuitry of the EPC10/Patchmaster software. In rare cases of discrepancy, we considered the manual bridge balance in current-clamp mode to be more accurate.
Using a numerical approach in QuB  (Milescu et al. , 2008; Navarro et al. , 2018; Salari et al. , 2018) , each Kv model type (mh, OSI, and CSI) was optimized to the OVX and OVXϩE datasets separately resulting in six models. During optimization, the same voltage protocols used in the potassium current characterization studies were run through each Kv model, and resulting open probability was converted to current using the I Kv equation in the previous paragraph. For each model optimization, errors for different parameters (e. g. , V 1/2 activation curve) were weighted. As the optimization proceeded, the weighted sum of squares differences between the model and data for each parameter were summed to make a single error for that model. This weighted sum of errors was minimized by iteratively altering the model parameters  (Milescu et al.
, 2008). The Davidon-Fletcher-Powell (DFP) algorithm was used to search for minima in the parameter set. Optimized Kv models for each of the OVX and OVXϩE datasets were tested in silico using experimentally-determined mean R in (OVX: 0. 78 G⍀, OVXϩE: 0. 87 G⍀) modeled as a leak conductance with a reversal potential of Ϫ75 mV, and C m (OVX: 14. 5 pF, OVXϩE: 11. 8 pF), as well as the overall mean R in and C m (OVX: 0. 83 G⍀, OVXϩE: 13. 2 pF). These values were the means of the passive properties of cells in the dcPSP experiments without 4AP plus those of cells in the action potential study. Because the Kv models had a non-zero open probability near Ϫ75 mV, the leak conductance and holding current (Ͻ1. 6 pA) were adjusted to maintain the apparent input resistance at the above values and the initial membrane potential at Ϫ75 mV for each Kv model.
I Kv ϭ P open͑V, t͒ Perm maxD P openmax GHK͑V͒, where P open is the output of the Kv model as a function of V and time, Perm maxD is defined in the Voltage-gated potassium current characterization section. I leak ϭ g leak ͑V Ϫ E leak ͒, where g leak is the linear leak conductance expressed as density and E leak is Ϫ75 mV. To establish control PSP values, Perm maxD was set to 0 to eliminate the influence of the Kv model. For each Kv model, the leak conductance and holding current were adjusted to set the initial conditions of simulation at Ϫ75 mV and R in for OVX or OVXϩE. Input resistance was confirmed in silico for each model using a 100 ms, Ϫ5 pA current injection via I command. Statistics. Data are reported as mean Ϯ SEM with individual values shown where practical. Statistical comparisons were made using Prism 7 or Prism 8 (GraphPad Software).
Under these conditions, Ni 2ϩ had no effect on GABA or AMPA dcPSP amplitude or time course; further studies with blockers of specific calcium channel subtypes were thus not pursued. In silico analysis of the interaction of PSP and passive cellular properties These results suggest that estradiol-dependent suppression of a transient potassium current leads to an increased response to synaptic conductances. Passive properties of these cells were also altered and the possible contribution of these changes needed to be considered. To test this we used an in silico approach. For this, we combined the input resistance and capacitance values from the action potential and dcPSP studies to increase the statistical power as both studies were conducted under similar conditions. In this combined dataset, estradiol increased input resistance (OVX: n ϭ 50, 0.
Each of the models reproduced the basic voltage dependence and shape of the potassium currents from the representative OVX and OVXϩE datasets (Fig. 7 ; Table  10 ). These Kv models were next combined in silico with the singlecompartment model cell representing an arcuate kisspeptin neuron with OVX, OVXϩE, or overall mean capacitance and input resistance and a Ϫ75 mV baseline membrane potential as above. Because some of the Kv models had non-zero open probabilities at Ϫ75 mV, leak conductance and holding current were adjusted to set the input resistance and baseline membrane potential at the specified values before testing the response to the synaptic conductance (Table  11 ). The time course of the PSPs and the resulting potassium currents are shown in Figure  8 ; PSP amplitudes with different combinations of passive and Kv models are shown in Table  9.
To overcome the challenges of studying potassium currents in the subthreshold range where they are likely to sculpt response to synaptic input, we optimized and tested three different Kv models of representative transient potassium currents from OVX and OVXϩE mice using the current density determined in our studies. The estradiol-dependent decrease in capacitance not only increased the passive responsiveness of the cell, but also reduced the magnitude of the potassium current. In silico studies of the interaction between these Kv models and synaptic conductance-induced PSPs revealed that both the type of the Kv model (mh, OSI, CSI) and optimization to OVX versus OVXϩE parameters affected the outcome. mh and OSI models optimized to the OVX dataset reproduced the blunting of PSPs observed in the dynamic clamp study, whereas the CSI model had a smaller effect.
This was reflected in the size and timing of the Kv current: the mh and OSI models produced faster and larger currents in response to PSPs. The failure of Kv models optimized to the OVXϩE dataset to blunt the PSPs was associated with smaller, slower model currents during the PSPs. These in silico conditions neutralized the effects of cellto-cell variation in input resistance and capacitance observed in the dynamicclamp studies and the influence of other voltage-gated channels. Together, these observations further support the hypothesis that estradiol-dependent functional suppression of transient potassium currents drives the increased response to both GABA and AMPA synaptic conductances, and revealed an additional role for passive properties in regulating response to AMPA. These studies also emphasize the importance of as-   sessing multiple Markov model structures when testing hypotheses in silico, as model structure had as much effect on the output of the system as the experimental data to which the models are optimized.
5, 2, 6 and 24 hours time-points post exposure. The foci sizes were analyzed using the Analyze Particles plugin in the ImageJ software. At least 100 foci for each data point were evaluated and the results are shown in Fig. 6b. We found a time dependent increase in the foci size from 0. 5 to 24 hours, with a statistical significance of p = 0. 0005 and p < 0. 0001 for 225 kVp X-rays and 10 MeV protons, respectively. Overall the size of the foci induced by the laser-accelerated protons and X-rays showed a close similarity indicating the low LET nature of the laser-accelerated protons. The increased foci size observed at 24 hours, is mainly due to the presence of some of the unrepaired DSB repair foci still persisting at 24 hrs although the frequency of such cells is very low at this time point.
Following irradiation, fresh cell culture media was added back to the cell dish and the cell dish was placed back into the incubator until time of fixation. Reference X-rays induced DSB damage kinetics was obtained by irradiating similar passage cells with 225 kVp X-rays using an XRAD225 X-ray cabinet (Precision X-ray Inc. N. Branford, CT, USA) fitted with a 2 mm copper filter, at the Public Health England (Chilton, Oxford) radiation facility. 53BP1 foci formation data used in Fig. 7. Data for the cyclotron accelerated protons at similar energies to the laser accelerated protons was taken from our previously published paper  17  where the proton beam of 60 MeV was generated at the Douglas Cyclotron of the Clatterbridge Centre for Oncology, Wirral, Liverpool, UK and was degraded using PMMA beam degraders to obtain 10 MeV energy.
Image acquisition and Foci quantification. Images were acquired using a Carl Zeiss Axiovert 200 M Fluorescence Microscope (Carl Zeiss, Germany) with a 63X magnification oil immersion objective (numerical aperture of 1. 4). The samples were imaged in 122 µm × 139 µm steps along the region exposed to 10 MeV protons and the number of 53BP1 foci were scored manually using ImageJ 39 inside the field encompassing the 10 MeV energy. For each data point at least 50-100 cells were scored randomly in two independent sets of images for each time point. 53BP1 foci were scored in the nucleus of each cell in the field of view and the results were expressed as average foci per cell per Gy with error bars representing the standard error of the mean of two independent replicates.
Acknowledgements The authors acknowledge funding from  Engineering and Physical Sciences Research Council Program Advanced Strategies for Accelerating Ions with Laser (ASAIL)  grant no  EP/K022415/1. In addition, would like to acknowledge the support of the mechanical engineering staff of the  Central Laser Facility, STFC , the staff at the  Research complex, Harwell, STFC  and the staff at  Public Health England. We gratefully acknowledge suggestions from  Prof. F. J. Currell  regarding the authomated cell media removal procedure.
We then collected pilot data that replicated these findings in hospitals (secondary and tertiary care), indicating that a significant proportion of patients with symptomatic severe AS were not being referred for consideration of aortic valve intervention in a timely fashion. Simple, low-cost facilitated data relay (FDR) interventions may help. We hypothesized that using a dedicated nurse to inform referring physicians of a finding of severe AS in a prompt and structured manner might increase the rate of referral of patients for intervention and timeliness thereof. 14.
Data Collection Data collected at baseline for all patients included demographics, medical history, and symptoms (chest pain, shortness of breath, and dizziness on exertion/syncope). Severe symptoms were defined as the presence of Canadian Cardiovascular Society class III or IV angina, New York Heart Association functional class III or IV, and/or dizziness on exertion/syncope. The logistic EuroScore I and the EuroScore II were calculated as an indication of surgical risk. Frailty was assessed according to the ability of the patient to walk 5 meters in <6 s and to perform activities of daily living. 16 Activities of daily living and life expectancy were assessed by the dedicated nurses or physicians, but no specific list of activities of daily living or risk calculator was recommended. The results of the echocardiographic assessment were recorded, including the presence of  coexisting aortic regurgitation, mitral or tricuspid valve disease; transvalvular gradient; left ventricle dimensions; and left ventricular ejection fraction.
At 3 months after enrollment, information on vital status (alive/dead), treatment decisions (SAVR, TAVR, balloon aortic valvuloplasty [BAV], active decision not to treat, or watchful waiting/further diagnostics) and the number of interventions performed were documented for all patients enrolled into the study. Watchful waiting was defined as the scheduling of further patient follow-up. Data were entered into a standardized electronic case report form by a dedicated study nurse. The primary outcome measure was the rate of planned and performed SAVR or TAVR within 3 months and the time to intervention.
, 2000). Lipophilicity is generally expressed as the n-octanol/water partition coefficient of the uncharged solute (log Po/w). From the determination of many drug partition coefficients in isotropic biphasic n-octanol/water systems, large data banks have been constituted, now enabling useful in silico prediction of a drug's lipophilicity  (Avdeef, 2003). However, the ability to precisely predict the behavior of drugs in biological systems from log Po/w has some limitations since partitioning in biological membranes is not governed by the same physicochemical forces. In n-octanol/water systems, not all hydrophobic, H-bond, dipole-dipole and electrostatic interactions between drug and membrane can be considered  (Austin et al. , 1995). Liposome model membranes are widely used as a better alternative  (Peetla et al.
Dosage of liposomes by NMR spectroscopy The lipid concentration of the formulated LUVs was quantified by 1 H NMR spectroscopy  (Hein et al. , 2016). 1 H NMR measurements were performed at ambient temperature for SPC, and EPC-based LUVS, or at 50°C for SPC:CHOL, and DPPC-based LUVs on a Bruker Avance III spectrometer (Bruker, Billerica, Massachusetts, USA) equipped with a 5 mm probehead operating at 400 MHz. The instrument's standard settings (90° pulse angle, 2. 72 s acquisition time, 3 s relaxation delay, 15 ppm spectral width) were used. Locking and shimming was performed on the signal of the exchangeable deuterium atoms of the D2O/CD3OD mixtures. 64 scans were performed leading to a total acquisition time of 6 min 20 s. Data processing was performed with Topspin 3. 5 After zerofilling to 64k data points, apodization (exponential and Gaussian functions, 1 Hz), Fourier transformation, phase-and baseline correction, the peak areas were determined by integration.
The corrected absorption spectra of compounds were obtained by subtracting the spectrum of the liposomal solution used at the same concentration. Spectra data recovery was performed using Microsoft ® Excel ® 2016. Second derivative spectra were calculated by using a secondorder polynomial convolution of 9 points with GraphPad Prism (version 6. 01, GraphPad Software, La Jolla, CA, USA)  (Magalhães et al. , 2010). The Nernst partition coefficient in liposome  (Ribeiro et al. , 2010)  is defined as: Kp = , , (1) where ns,i are the number of moles of solute present in the aqueous (i = W) and in the lipid (i = L) phases. From equation 1, the fraction of membrane-bound solute (XL) can be related to Kp, at a given experimental concentration in phospholipids ([L]), by the following equation: ( ) 2 where γ is the phospholipid molar volume.
4. C), and by applying equation 4, the partition coefficient of pyridoclax was found to be equal to 4. 11 ± 0. 09 (Table  3 ). This value is consistent with the experimental log P value of 4. 4 previously reported, and experimentally defined by a chromatographic method  (Groo et al. , 2017). It is smaller than the calculated logP prediction of 5. 83, performed using ChemAxon software (Marvin 16. 1. 4. 0, 2016, ChemAxon (http://www. chemaxon. com/)). Thus, pyridoclax appears as a lipophilic drug, which is relative to the presence of four central pyridines in its scaffold, and that of a lateral styryl hydrophobic group, that reinforces its lipophilic character. Considering that the most basic pKa value is 4. 89 for pyridoclax (calculated using ChemAxon software), the molecule exists in a predominant unionized form at pH 7.
The vector expressing the green fluorescent protein (GFP)-BoNT-A fusion protein, also driven by HCMV promoter, does not encode the IE4/5 promoter-GFP transgene cassette. Due to the reiterative character of the amplicon genome  [20, 21] , each vector particle carries a concatemeric DNA consisting of multiple tandem repeats of the amplicon plasmid. All amplicon plasmids were sequenced to confirm the accuracy of the constructions, and all of them expressed their corresponding BoNT LC mRNA in primary cultures of rat neurons, as assessed by RT-PCR (data not shown).