Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke.

BACKGROUND: A major driver of individual variation in long-term outcomes following a large vessel occlusion (LVO) stroke is the degree of collateral arterial circulation. We aimed to develop and evaluate machine-learning models that quantify LVO collateral status using admission computed tomography angiography (CTA) radiomics. METHODS: We extracted 1116 radiomic features from the anterior circulation territories from admission CTAs of 600 patients experiencing an acute LVO stroke. We trained and validated multiple machine-learning models for the prediction of collateral status based on consensus from two neuroradiologists as ground truth. Models were first trained to predict (1) good vs. intermediate or poor, or (2) good vs. intermediate or poor collateral status. Then, model predictions were combined to determine a three-tier collateral score (good, intermediate, or poor). We used the receiver operating characteristics area under the curve (AUC) to evaluate prediction accuracy. RESULTS: We included 499 patients in training and 101 in an independent test cohort. The best-performing models achieved an averaged cross-validation AUC of 0.80 ± 0.05 for poor vs. intermediate/good collateral and 0.69 ± 0.05 for good vs. intermediate/poor, and AUC = 0.77 (0.67-0.87) and AUC = 0.78 (0.70-0.90) in the independent test cohort, respectively. The collateral scores predicted by the radiomics model were correlated with (rho = 0.45, p = 0.002) and were independent predictors of 3-month clinical outcome (p = 0.018) in the independent test cohort. CONCLUSIONS: Automated tools for the assessment of collateral status from admission CTA-such as the radiomics models described here-can generate clinically relevant and reproducible collateral scores to facilitate a timely treatment triage in patients experiencing an acute LVO stroke.

Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers.

Objective: To devise and validate radiomic signatures of impending hematoma expansion (HE) based on admission non-contrast head computed tomography (CT) of patients with intracerebral hemorrhage (ICH). Methods: Utilizing a large multicentric clinical trial dataset of hypertensive patients with spontaneous supratentorial ICH, we developed signatures predictive of HE in a discovery cohort (n = 449) and confirmed their performance in an independent validation cohort (n = 448). In addition to n = 1,130 radiomic features, n = 6 clinical variables associated with HE, n = 8 previously defined visual markers of HE, the BAT score, and combinations thereof served as candidate variable sets for signatures. The area under the receiver operating characteristic curve (AUC) quantified signatures' performance. Results: A signature combining select radiomic features and clinical variables attained the highest AUC (95% confidence interval) of 0.67 (0.61-0.72) and 0.64 (0.59-0.70) in the discovery and independent validation cohort, respectively, significantly outperforming the clinical (pdiscovery = 0.02, pvalidation = 0.01) and visual signature (pdiscovery = 0.03, pvalidation = 0.01) as well as the BAT score (pdiscovery < 0.001, pvalidation < 0.001). Adding visual markers to radiomic features failed to improve prediction performance. All signatures were significantly (p < 0.001) correlated with functional outcome at 3-months, underlining their prognostic relevance. Conclusion: Radiomic features of ICH on admission non-contrast head CT can predict impending HE with stable generalizability; and combining radiomic with clinical predictors yielded the highest predictive value. By enabling selective anti-expansion treatment of patients at elevated risk of HE in future clinical trials, the proposed markers may increase therapeutic efficacy, and ultimately improve outcomes.

Experimental and computational characterisation of an artificial light harvesting complex.

Photosynthesis has been shown to be a highly efficient process for energy transfer in plants and bacteria. Like natural photosynthetic systems, the artificial light harvesting complex (LHC) BODIPY pillar[5]arene exhibits Förster resonance energy transfer (FRET). However, extensive characterisation of the BODIPY pillar[5]arene LHC to determine its suitability as an artificial LHC has yet to occur. In this paper we experimentally and computationally investigate the photophysical properties of the LHC by comparing the light absorption of the BODIPY LHC to individual BODIPY chromophores. Our results show evidence for quantum coherence, with oscillation frequencies of 100 cm-1 and 600 cm-1, which are attributable to vibronic, or exciton-phonon type coupling. Computational analysis suggests strong couplings of the molecular orbitals of the LHC resulting from the stacking of neighbouring BODIPY chromophore units. Interestingly, we find a 40% reduction in the absorbance of light for the BODIPY LHC compared to the individual chromophores which we attribute to electronic interactions between the conjugated π-systems of the BODIPY chromophores and the pillar[5]arene backbone.

Dataset on acute stroke risk stratification from CT angiographic radiomics.

With advances in high-throughput image processing technologies and increasing availability of medical mega-data, the growing field of radiomics opened the door for quantitative analysis of medical images for prediction of clinically relevant information. One clinical area in which radiomics have proven useful is stroke neuroimaging, where rapid treatment triage is vital for patient outcomes and automated decision assistance tools have potential for significant clinical impact. Recent research, for example, has applied radiomics features extracted from CT angiography (CTA) images and a machine learning framework to facilitate risk-stratification in acute stroke. We here provide methodological guidelines and radiomics data supporting the referenced article "CT angiographic radiomics signature for risk-stratification in anterior large vessel occlusion stroke." The data were extracted from the stroke center registry at Yale New Haven Hospital between 1/1/2014 and 10/31/2020; and Geisinger Medical Center between 1/1/2016 and 12/31/2019. It includes detailed radiomics features of the anterior circulation territories on admission CTA scans in stroke patients with large vessel occlusion stroke who underwent thrombectomy. We also provide the methodological details of the analysis framework utilized for training, optimization, validation and external testing of the machine learning and feature selection algorithms. With the goal of advancing the feasibility and quality of radiomics-based analyses to improve patient care within and beyond the field of stroke, the provided data and methodological support can serve as a baseline for future studies applying radiomics algorithms to machine-learning frameworks, and allow for analysis and utilization of radiomics features extracted in this study.

CT angiographic radiomics signature for risk stratification in anterior large vessel occlusion stroke.

BACKGROUND AND PURPOSE: As "time is brain" in acute stroke triage, the need for automated prognostication tools continues to increase, particularly in rapidly expanding tele-stroke settings. We aimed to create an automated prognostication tool for anterior circulation large vessel occlusion (LVO) stroke based on admission CTA radiomics. METHODS: We automatically extracted 1116 radiomics features from the anterior circulation territory on admission CTAs of 829 acute LVO stroke patients who underwent mechanical thrombectomy in two academic centers. We trained, optimized, validated, and compared different machine-learning models to predict favorable outcome (modified Rankin Scale ≤ 2) at discharge and 3-month follow-up using four different input sets: "Radiomics", "Radiomics + Treatment" (radiomics, post-thrombectomy reperfusion grade, and intravenous thrombolysis), "Clinical + Treatment" (baseline clinical variables and treatment), and "Combined" (radiomics, treatment, and baseline clinical variables). RESULTS: For discharge outcome prediction, models were optimized/trained on n = 494 and tested on an independent cohort of n = 100 patients from Yale. Receiver operating characteristic analysis of the independent cohort showed no significant difference between best-performing Combined input models (area under the curve, AUC = 0.77) versus Radiomics + Treatment (AUC = 0.78, p = 0.78), Radiomics (AUC = 0.78, p = 0.55), or Clinical + Treatment (AUC = 0.77, p = 0.87) models. For 3-month outcome prediction, models were optimized/trained on n = 373 and tested on an independent cohort from Yale (n = 72), and an external cohort from Geisinger Medical Center (n = 232). In the independent cohort, there was no significant difference between Combined input models (AUC = 0.76) versus Radiomics + Treatment (AUC = 0.72, p = 0.39), Radiomics (AUC = 0.72, p = 0.39), or Clinical + Treatment (AUC = 76, p = 0.90) models; however, in the external cohort, the Combined model (AUC = 0.74) outperformed Radiomics + Treatment (AUC = 0.66, p < 0.001) and Radiomics (AUC = 0.68, p = 0.005) models for 3-month prediction. CONCLUSION: Machine-learning signatures of admission CTA radiomics can provide prognostic information in acute LVO stroke candidates for mechanical thrombectomy. Such objective and time-sensitive risk stratification can guide treatment decisions and facilitate tele-stroke assessment of patients. Particularly in the absence of reliable clinical information at the time of admission, models solely using radiomics features can provide a useful prognostication tool.

Age-related topographic map of magnetic resonance diffusion metrics in neonatal brains.

Accelerated maturation of brain parenchyma close to term-equivalent age leads to rapid changes in diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) metrics of neonatal brains, which can complicate the evaluation and interpretation of these scans. In this study, we characterized the topography of age-related evolution of diffusion metrics in neonatal brains. We included 565 neonates who had MRI between 0 and 3 months of age, with no structural or signal abnormality-including 162 who had DTI scans. We analyzed the age-related changes of apparent diffusion coefficient (ADC) values throughout brain and DTI metrics (fractional anisotropy [FA] and mean diffusivity [MD]) along white matter (WM) tracts. Rate of change in ADC, FA, and MD values across 5 mm cubic voxels was calculated. There was significant reduction of ADC and MD values and increase of FA with increasing gestational age (GA) throughout neonates' brain, with the highest temporal rates in subcortical WM, corticospinal tract, cerebellar WM, and vermis. GA at birth had significant effect on ADC values in convexity cortex and corpus callosum as well as FA/MD values in corpus callosum, after correcting for GA at scan. We developed online interactive atlases depicting age-specific normative values of ADC (ages 34-46 weeks), and FA/MD (35-41 weeks). Our results show a rapid decrease in diffusivity metrics of cerebral/cerebellar WM and vermis in the first few weeks of neonatal age, likely attributable to myelination. In addition, prematurity and low GA at birth may result in lasting delay in corpus callosum myelination and cerebral cortex cellularity.

Similar admission NIHSS may represent larger tissue-at-risk in patients with right-sided versus left-sided large vessel occlusion.

BACKGROUND: We investigated the effects of the side of large vessel occlusion (LVO) on post-thrombectomy infarct volume and clinical outcome with regard to admission National Institutes of Health Stroke Scale (NIHSS) score. METHODS: We retrospectively identified patients with anterior LVO who received endovascular thrombectomy and follow-up MRI. Applying voxel-wise general linear models and multivariate analysis, we assessed the effects of occlusion side, admission NIHSS, and post-thrombectomy reperfusion (modified Thrombolysis in Cerebral Infarction, mTICI) on final infarct distribution and volume as well as discharge modified Rankin Scale (mRS) score. RESULTS: We included 469 patients, 254 with left-sided and 215 with right-sided LVO. Admission NIHSS was higher in those with left-sided LVO (median (IQR) 16 (10-22)) than in those with right-sided LVO (14 (8-16), p>0.001). In voxel-wise analysis, worse post-thrombectomy reperfusion, lower admission NIHSS score, and poor discharge outcome were associated with right-hemispheric infarct lesions. In multivariate analysis, right-sided LVO was an independent predictor of larger final infarct volume (p=0.003). There was a significant three-way interaction between admission stroke severity (based on NIHSS), LVO side, and mTICI with regard to final infarct volume (p=0.041). Specifically, in patients with moderate stroke (NIHSS 6-15), incomplete reperfusion (mTICI 0-2b) was associated with larger final infarct volume (p<0.001) and worse discharge outcome (p=0.02) in right-sided compared with left-sided LVO. CONCLUSIONS: When adjusted for admission NIHSS, worse post-thrombectomy reperfusion is associated with larger infarct volume and worse discharge outcome in right-sided versus left-sided LVO. This may represent larger tissue-at-risk in patients with right-sided LVO when applying admission NIHSS as a clinical biomarker for penumbra.

The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volume.

BACKGROUND: Among prognostic imaging variables, the hematoma volume on admission computed tomography (CT) has long been considered the strongest predictor of outcome and mortality in intracerebral hemorrhage. AIMS: To examine whether different features of hematoma shape are associated with functional outcome in deep intracerebral hemorrhage. METHODS: We analyzed 790 patients from the ATACH-2 trial, and 14 shape features were quantified. We calculated Spearman's Rho to assess the correlation between shape features and three-month modified Rankin scale (mRS) score, and the area under the receiver operating characteristic curve (AUC) to quantify the association between shape features and poor outcome defined as mRS>2 as well as mRS > 3. RESULTS: Among 14 shape features, the maximum intracerebral hemorrhage diameter in the coronal plane was the strongest predictor of functional outcome, with a maximum coronal diameter >∼3.5 cm indicating higher three-month mRS scores. The maximum coronal diameter versus hematoma volume yielded a Rho of 0.40 versus 0.35 (p = 0.006), an AUC[mRS>2] of 0.71 versus 0.68 (p = 0.004), and an AUC[mRS>3] of 0.71 versus 0.69 (p = 0.029). In multiple regression analysis adjusted for known outcome predictors, the maximum coronal diameter was independently associated with three-month mRS (p < 0.001). CONCLUSIONS: A coronal-plane maximum diameter measurement offers greater prognostic value in deep intracerebral hemorrhage than hematoma volume. This simple shape metric may expedite assessment of admission head CTs, offer a potential biomarker for hematoma size eligibility criteria in clinical trials, and may substitute volume in prognostic intracerebral hemorrhage scoring systems.

Early head CT in post-cardiac arrest patients: A helpful tool or contributor to self-fulfilling prophecy?

OBJECTIVE: Neuroprognostication guidelines suggest that early head computed tomography (HCT) might be useful in the evaluation of cardiac arrest (CA) patients following return of spontaneous circulation. We aimed to determine the impact of early HCT, performed within the first 6 h following CA, on decision-making following resuscitation. METHODS: We identified a cohort of initially unconscious post-CA patients at a tertiary care academic medical center from 2012 to 2017. Variables pertaining to demographics, CA details, post-CA care, including neuroimaging and neurophysiologic testing, were abstracted retrospectively from the electronic medical records. Changes in management resulting from HCT findings were recorded. Blinded board-certified neurointensivists adjudicated HCT findings related to hypoxic-ischemic brain injury (HIBI) burden. The gray-white matter ratio (GWR) was also calculated. RESULTS: Of 302 patients, 182 (60.2%) underwent HCT within six hours of CA (early HCT group). Approximately 1 in 4 early HCTs were abnormal (most commonly HIBI changes; 78.7%, n = 37), which resulted in a change in management in nearly half of cases (46.8%, n = 22). The most common changes in management were de-escalation in care [including transition to do not resuscitate status), withholding targeted temperature management, and withdrawal of life sustaining therapy (WLST)]. In cases with radiographic HIBI, mean [standard deviation] GWR was lower (1.20 [0.10] vs 1.30 [0.09], P < 0.001) and progression to brain death was higher (44.4% vs 2.9%; P < 0.001). The inter-rater reliability (IRR) of early HCT to determine presence of HIBI between radiology and three neurointensivists had a wide range (κ 0.13-0.66). CONCLUSION: Early HCT identified abnormalities in 25% of cases and frequently influenced therapeutic decisions. Neuroimaging interpretation discrepancies between radiology and neurointensivists are common and agreement on severity of HIBI on early HCT is poor (k 0.11).

Molecular Aggregation of Naphthalene Diimide(NDI) Derivatives in Electron Transport Layers of Inverted Perovskite Solar Cells and Their Influence on the Device Performance.

One of key factors to design applicable electron transport layers (ETLs) for perovskite solar cells is the morphology of ETLs since a good morphology would help to facilitate the carrier transport at two interfaces (perovskite\ETL and ETL\cathode). However, one drawback of most organic ETL small molecules is the internal undesired accumulation, which would cause the formation of inappropriate morphology and rough ETL surface. Here, by elaborately designing the side chains of NDI derivatives, the molecular interaction could be modified to achieve the aggregation in different degrees, which would eventually affect the accumulation of molecules and surface qualities of ETLs. By speculating from the comparison between the absorption spectra of solutions and films, the sequence of extent of molecule interaction and aggregation was built among three NDI derivatives, which is further confirmed by direct evidence of atomic force microscopy (AFM) images. Then, carrier exaction abilities are simply studied by steady-state photoluminescence spectroscopy. The carrier transport process is also discussed based on cyclic voltammetry, time-resolved photoluminescence spectroscopy and mobility. NDIF1 are proven to have the appropriate internal aggregation to smooth the contact with cathode and low series resistance, and a device performance of 15.6 % is achieved. With the ability of preventing the thermal diffusion of Ag towards the perovskite surface due to the strong interaction between molecules, NDIF2 at high concentration shows the highest fill factor (80 %).

Influences of Structural Modification of Naphthalenediimides with Benzothiazole on Organic Field-Effect Transistor and Non-Fullerene Perovskite Solar Cell Characteristics.

Developing air-stable high-performance small organic molecule-based n-type and ambipolar organic field-effect transistors (OFETs) is very important and highly desirable. In this investigation, we designed and synthesized two naphthalenediimide (NDI) derivatives (NDI-BTH1 and NDI-BTH2) and found that introduction of 2-(benzo[d]thiazol-2-yl) acetonitrile groups at the NDI core position gave the lowest unoccupied molecular orbital (LUMO; -4.326 eV) and displayed strong electron affinities, suggesting that NDI-BTH1 might be a promising electron-transporting material (i.e., n-type semiconductor), whereas NDI-BTH2 bearing bis(benzo[d]thiazol-2-yl)methane at the NDI core with a LUMO of -4.243 eV was demonstrated to be an ambipolar material. OFETs based on NDI-BTH1 and NDI-BTH2 have been fabricated, and the electron mobilities of NDI-BTH1 and NDI-BTH2 are 14.00 × 10-5 and 8.64 × 10-4 cm2/V·s, respectively, and the hole mobility of NDI-BTH2 is 1.68 × 10-4 cm2/V·s. Moreover, a difference in NDI-core substituent moieties significantly alters the UV-vis absorption and cyclic voltammetry properties. Thus, we further successfully employed NDI-BTH1 and NDI-BTH2 as electron transport layer (ETL) materials in inverted perovskite solar cells (PSCs). The PSC performance exhibits that NDI-BTH2 as the ETL material gave higher power conversion efficiency as compared to NDI-BTH1, that is, NDI-BTH2 produces 15.4%, while NDI-BTH1 gives 13.7%. The PSC performance is comparable with the results obtained from OFETs. We presume that improvement in solar cell efficiency of NDI-BTH2-based PSCs is due to the well-matched LUMO of NDI-BTH2 toward the conduction band of the perovskite layer, which in turn increase electron extraction and transportation.

Control of Molecular Recognition via Modulation of the Nanoenvironment.

Many biological processes are driven by the interaction of a host with a guest molecule. We show such interactions can be modulated by carefully defining the local molecular environment to give a specific chemical outcome. Particularly, the selectivity of a host toward two different ions (Ca2+ and Al3+) is defined by it being in solution or the physisorbed state. In solution, the host displays greater selectivity toward Ca2+. When physisorbed, the selectivity profile of the host is reversed with enhanced binding of Al3+. This demonstrates a single host molecule can be tailored to selectively bind multiple guests by altering its nanoenvironment.

Nature of halogen bonding involving π-systems, nitroxide radicals and carbenes: a highlight of the importance of charge transfer.

The recently developed adiabatic absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) has proven to be useful in determining the effects of different energy components on the geometries of complexes bound by intermolecular interactions. The authors have applied it to systems such as the water dimer, water-ion complexes, metallocenes and lone-pair type halogen-bonded (XB) dimers. In this study, we have extended the second-generation ALMO-EDA method to 40 different XB complexes by benchmarking against its classical counterpart and symmetry-adapted perturbation theory (SAPT). In addition, we have examined the nature of halogen bonding involving less studied XB acceptors, namely π-systems, radicals and carbenes, using the adiabatic ALMO-EDA analyses, particularly to shed light on how each energy component affects the geometries of the XB complexes. Our results show that the second-generation ALMO-EDA predicts a higher electrostatic energy contribution in all XB complexes compared to SAPT and classical ALMO-EDA schemes. On the other hand, when comparing across different XB acceptors, all three partition schemes produced the same qualitative finding. The adiabatic ALMO-EDA analyses indicate that while the inclusion of a charge transfer contribution is important in achieving accurate XB bond lengths and interaction energies, as well as recovering the binding site specificity of XB involving benzene and naphthalene acceptors, it is sufficient to obtain the linearity of the XB complexes in the frozen approximation.

Site specificity of halogen bonding involving aromatic acceptors.

Halogen bonding (XB) has become one of the most studied non-covalent interactions in the past two decades, owing to its wide range of applications in materials and biological applications. Most of the current theoretical and experimental studies focus on XB involving lone-pair acceptors due to its predictability in terms of crystal geometries. However, recent reports have advocated the importance of XB materials involving aromatic-type acceptors because of their relevance in functional materials, catalysis and biological systems. Herein, we report the XB site-specificity in several polycyclic aromatic hydrocarbons (PAHs) and N-heteroaromatic compounds that are ubiquitous in chemical systems. Based on a series of quantum chemical studies of Cl2 and Br2 XB complexes with 14 representative systems, these XB sites can be easily predicted using occupied molecular orbitals and atomic charges. We envisage that the predicted site maps will be useful for materials and drug design involving this class of non-covalent interactions.

Thioamide-Directed Cobalt(III)-Catalyzed Selective Amidation of C(sp3 )-H Bonds.

A mild, oxidant-free, and selective Cp*CoIII -catalyzed amidation of thioamides with robust dioxazolone amidating agents via C(sp3 )-H bond activation to generate the desired amidated products is reported. The method is efficient and allows for the C-H amidation of a wide range of functionalized thioamides with aryl-, heteroaryl-, and alkyl-substituted dioxazolones under the Cp*CoIII -catalyzed conditions. The observed regioselectivity towards primary C(sp3 )-H activation is supported by computational studies and the cyclometalation is proposed to proceed by means of an external carboxylate-assisted concerted metalation/deprotonation mechanism. The reported method is a rare example of the use of a directing group other than the commonly used pyridine and quinolone classes for Cp*CoIII -catalyzed C(sp3 )-H functionalization and the first to exploit thioamides.

Empirical and Computational Insights into N-Arylation Reactions Catalyzed by Palladium meta-Terarylphosphine Catalyst.

An in situ generated Pd-Cy*Phine catalyst has been successfully applied to the N-arylation of primary and secondary amines, and it exhibited high performance across multiple substrate classes. The performance induced by the meta-terarylphosphine motif of the Cy*Phine ligand for C-N cross-coupling displayed only subtle differences to that of its biarylphosphine congener XPhos. DFT studies demonstrated comparable reaction energetics in the catalytic cycle steps for both Pd-Cy*Phine and Pd-XPhos, which was consistent with previous findings. The computational investigation also indicated that a putative rate-determining step occurred after amine binding, which was likely to have annulled the expected benefits of having a meta-terarylphosphine ligand architecture.

Dual sensor for Cd(II) and Ca(II): selective nanoliter-scale sensing of metal ions.

The first selective, dual sensor for Ca(2+) and Cd(2+) capable of detection at 100 pM concentrations was designed and synthesized. The experimental observations made for the MC-cation complexes and the selectivity of compounds 1 and 2 with Ca(2+) and Cd(2+) ions were further explored using density functional theory. A first step toward a nanoliter-scale dip sensor for the dual sensing of Ca(2+) and Cd(2+) was demonstrated using microstructured optical fiber as the sensing platform which is important for ion sensing in confined spaces such as the medium surrounding cell clusters. In addition, this system displays picomolar sensitivity for these ions, with an added ability to reproducibly turn ion-binding on/off.

Quantitative mass spectrometry-based proteomics reveals the dynamic range of primary mouse astrocyte protein secretion.

Growing appreciation for astrocytes as active participants in nervous system development, neurovascular metabolic coupling, and neurological disease progression has stimulated recent investigation into specific astrocyte-secreted proteins that may mediate these functions. The current work utilized SILAC-generated isotope reference proteomes to quantify relative protein abundances between the astrocyte proteome and secretome. Multidimensional GeLC-MS/MS analysis of astrocyte conditioned media and cell lysates resulted in the relative quantification of 516 proteins, 92 of which were greater than 1.5-fold enriched in astrocyte-conditioned media (ACM). Eighty of the ACM-enriched proteins had N-terminal signal peptides, comprising well-known classically secreted proteins, such as apolipoprotein E and SPARC, and several cathepsins that localize to endosomal/lysosomal compartments. The remaining twelve ACM-enriched proteins, such as vimentin, ferritins, and histones, lacked N-terminal signal peptides. Also, 47 proteins contained predicted N-terminal signal peptides but were not enriched in ACM (<1.5-fold), 25 of which were localized to ER, Golgi, or mitochondria membrane-bound compartments. Overall, by combining quantitative proteomics with subcellular localization prediction, an informative description of protein distribution can be obtained, providing insights into protein secretion.

Homolytic S-S bond dissociation of 11 bis(thiocarbonyl)disulfides R-C(=S)-S-S-C(=S)R and prediction of a novel rubber vulcanization accelerator.

The structures and energetics of eight substituted bis(thiocarbonyl)disulfides (RCS(2))(2), their associated radicals RCS(2)(*), and their coordination compounds with a lithium cation have been studied at the G3X(MP2) level of theory for R = H, Me, F, Cl, OMe, SMe, NMe(2), and PMe(2). The effects of substituents on the dissociation of (RCS(2))(2) to RCS(2)(*) were analyzed using isodesmic stabilization reactions. Electron-donating groups with an unshared pair of electrons have a pronounced stabilization effect on both (RCS(2))(2) and RCS(2)(*). The S-S bond dissociation enthalpy of tetramethylthiuram disulfide (TMTD, R = NMe(2)) is the lowest in the above series (155 kJ mol(-1)), attributed to the particular stability of the formed Me(2)NCS(2)(*) radical. Both (RCS(2))(2) and the fragmented radicals RCS(2)(*) form stable chelate complexes with a Li(+) cation. The S-S homolytic bond cleavage in (RCS(2))(2) is facilitated by the reaction [Li(RCS(2))(2)](+)+Li(+)-->2 [Li(RCS(2))](*+). Three other substituted bis(thiocarbonyl) disulfides with the unconventional substituents R = OSF(5), Gu(1), and Gu(2) have been explored to find suitable alternative rubber vulcanization accelerators. Bis(thiocarbonyl)disulfide with a guanidine-type substituent, (Gu(1)CS(2))(2), is predicted to be an effective accelerator in sulfur vulcanization of rubber. Compared to TMTD, (Gu(1)CS(2))(2) is calculated to have a lower bond dissociation enthalpy and smaller associated barrier for the S-S homolysis.

Reaction of the radical pair NO2* and CO3*- with 2-[6-(4'-amino)phenoxy-3H-xanthen-3-on-9-yl]benzoic acid (APF).

The fluorogenic indicator 2-[6-(4'-amino)phenoxy-3H-xanthen-3-on-9-yl]benzoic acid (APF) is used widely to detect and measure reactive nitrogen and oxygen species such as peroxynitrite, ONOO-, both in vivo and in vitro. We present in this work the results of a combined computational and experimental study to provide insights into the mechanism of the reaction of APF with the radical products of ONOO- reaction with CO2, namely NO2* and CO3*-. The experimental study on the inhibition of APF oxidation by HCO3- suggests that a direct reaction of APF with nitrosoperoxycarbonate, ONOOCO2-, is unlikely. The mechanism of APF action on NO2* and CO3*- was investigated using gas-phase and solvent modeled calculations at the MPW1K/6-311+G(d)//MPW1K/6-31G(d) level of theory. Our computational results suggest that two-electron oxidation of APF takes place in two rapid one-electron oxidation steps, the first being a proton-coupled electron transfer (PCET) between APF and NO2*, followed by addition of CO3*- and subsequent decomposition of the adduct to yield fluorescein.