Automated identification of uncertain cases in deep learning-based classification of dopamine transporter SPECT to improve clinical utility and acceptance.

PURPOSE: Deep convolutional neural networks (CNN) are promising for automatic classification of dopamine transporter (DAT)-SPECT images. Reporting the certainty of CNN-based decisions is highly desired to flag cases that might be misclassified and, therefore, require particularly careful inspection by the user. The aim of the current study was to design and validate a CNN-based system for the identification of uncertain cases. METHODS: A network ensemble (NE) combining five CNNs was trained for binary classification of [123I]FP-CIT DAT-SPECT images as "normal" or "neurodegeneration-typical reduction" with high accuracy (NE for classification, NEfC). An uncertainty detection module (UDM) was obtained by combining two additional NE, one trained for detection of "reduced" DAT-SPECT with high sensitivity, the other with high specificity. A case was considered "uncertain" if the "high sensitivity" NE and the "high specificity" NE disagreed. An internal "development" dataset of 1740 clinical DAT-SPECT images was used for training (n = 1250) and testing (n = 490). Two independent datasets with different image characteristics were used for testing only (n = 640, 645). Three established approaches for uncertainty detection were used for comparison (sigmoid, dropout, model averaging). RESULTS: In the test data from the development dataset, the NEfC achieved 98.0% accuracy. 4.3% of all test cases were flagged as "uncertain" by the UDM: 2.5% of the correctly classified cases and 90% of the misclassified cases. NEfC accuracy among "certain" cases was 99.8%. The three comparison methods were less effective in labelling misclassified cases as "uncertain" (40-80%). These findings were confirmed in both additional test datasets. CONCLUSION: The UDM allows reliable identification of uncertain [123I]FP-CIT SPECT with high risk of misclassification. We recommend that automatic classification of [123I]FP-CIT SPECT images is combined with an UDM to improve clinical utility and acceptance. The proposed UDM method ("high sensitivity versus high specificity") might be useful also for DAT imaging with other ligands and for other binary classification tasks.

Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network.

OBJECTIVES: Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, train, and test a deep convolutional neural network (CNN) for single-subject VBM without the need for a NDB (CNN-VBM). MATERIALS AND METHODS: The training dataset comprised 8945 T1w scans from 65 different scanners. The gold standard VBM maps were obtained by conventional VBM with a scanner-specific NDB for each of the 65 scanners. CNN-VBM was tested in an independent dataset comprising healthy controls (n = 37) and subjects with Alzheimer's disease (AD, n = 51) or frontotemporal lobar degeneration (FTLD, n = 30). A scanner-specific NDB for the generation of the gold standard VBM maps was available also for the test set. The technical performance of CNN-VBM was characterized by the Dice coefficient of CNN-VBM maps relative to VBM maps from scanner-specific VBM. For clinical testing, VBM maps were categorized visually according to the clinical diagnoses in the test set by two independent readers, separately for both VBM methods. RESULTS: The VBM maps from CNN-VBM were similar to the scanner-specific VBM maps (median Dice coefficient 0.85, interquartile range [0.81, 0.90]). Overall accuracy of the visual categorization of the VBM maps for the detection of AD or FTLD was 89.8% for CNN-VBM and 89.0% for scanner-specific VBM. CONCLUSION: CNN-VBM without NDB provides a similar performance in the detection of AD- and FTLD-specific atrophy as conventional VBM. CLINICAL RELEVANCE STATEMENT: A deep convolutional neural network for voxel-based morphometry eliminates the need of scanner-specific normal databases without relevant performance loss and, therefore, could pave the way for the widespread clinical use of voxel-based morphometry to support the diagnosis of neurodegenerative diseases. KEY POINTS: • The need of normal databases is a barrier for widespread use of voxel-based brain morphometry. • A convolutional neural network achieved a similar performance for detection of atrophy than conventional voxel-based morphometry. • Convolutional neural networks can pave the way for widespread clinical use of voxel-based morphometry.

Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability.

OBJECTIVES: To develop an automatic method for accurate and robust thalamus segmentation in T1w-MRI for widespread clinical use without the need for strict harmonization of acquisition protocols and/or scanner-specific normal databases. METHODS: A three-dimensional convolutional neural network (3D-CNN) was trained on 1975 T1w volumes from 170 MRI scanners using thalamus masks generated with FSL-FIRST as ground truth. Accuracy was evaluated with 18 manually labeled expert masks. Intra- and inter-scanner test-retest stability were assessed with 477 T1w volumes of a single healthy subject scanned on 123 MRI scanners. The sensitivity of 3D-CNN-based volume estimates for the detection of thalamus atrophy was tested with 127 multiple sclerosis (MS) patients and a normal database comprising 4872 T1w volumes from 160 scanners. The 3D-CNN was compared with a publicly available 2D-CNN (FastSurfer) and FSL. RESULTS: The Dice similarity coefficient of the automatic thalamus segmentation with manual expert delineation was similar for all tested methods (3D-CNN and FastSurfer 0.86 ± 0.02, FSL 0.87 ± 0.02). The standard deviation of the single healthy subject's thalamus volume estimates was lowest with 3D-CNN for repeat scans on the same MRI scanner (0.08 mL, FastSurfer 0.09 mL, FSL 0.15 mL) and for repeat scans on different scanners (0.28 mL, FastSurfer 0.62 mL, FSL 0.63 mL). The proportion of MS patients with significantly reduced thalamus volume was highest for 3D-CNN (24%, FastSurfer 16%, FSL 11%). CONCLUSION: The novel 3D-CNN allows accurate thalamus segmentation, similar to state-of-the-art methods, with considerably improved robustness with respect to scanner-related variability of image characteristics. This might result in higher sensitivity for the detection of disease-related thalamus atrophy. KEY POINTS: • A three-dimensional convolutional neural network was trained for automatic segmentation of the thalamus with a heterogeneous sample of T1w-MRI from 1975 patients scanned on 170 different scanners. • The network provided high accuracy for thalamus segmentation with manual segmentation by experts as ground truth. • Inter-scanner variability of thalamus volume estimates across different MRI scanners was reduced by more than 50%, resulting in increased sensitivity for the detection of thalamus atrophy.

Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks.

OBJECTIVE: Automated quantification of infratentorial multiple sclerosis lesions on magnetic resonance imaging is clinically relevant but challenging. To overcome some of these problems, we propose a fully automated lesion segmentation algorithm using 3D convolutional neural networks (CNNs). METHODS: The CNN was trained on a FLAIR image alone or on FLAIR and T1-weighted images from 1809 patients acquired on 156 different scanners. An additional training using an extra class for infratentorial lesions was implemented. Three experienced raters manually annotated three datasets from 123 MS patients from different scanners. RESULTS: The inter-rater sensitivity (SEN) was 80% for supratentorial lesions but only 62% for infratentorial lesions. There was no statistically significant difference between the inter-rater SEN and the SEN of the CNN with respect to the raters. For supratentorial lesions, the CNN featured an intra-rater intra-scanner SEN of 0.97 (R1 = 0.90, R2 = 0.84) and for infratentorial lesion a SEN of 0.93 (R1 = 0.61, R2 = 0.73). CONCLUSION: The performance of the CNN improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input and matches the detection performance of experienced raters. Furthermore, for infratentorial lesions the CNN was more robust against repeated scans than experienced raters. KEY POINTS: • A 3D convolutional neural network was trained on MRI data from 1809 patients (156 different scanners) for the quantification of supratentorial and infratentorial multiple sclerosis lesions. • Inter-rater variability was higher for infratentorial lesions than for supratentorial lesions. The performance of the 3D convolutional neural network (CNN) improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input. • The detection performance of the CNN matches the detection performance of experienced raters.

Switching from Heteronuclear Allyl Cations to Vinyl Cations by Using a Chemical Charge Trap.

Halide abstraction of the carbene-coordinated pnictinidenes (MecAAC)EGa(Cl)L (E = As 1, Sb 2, Bi 3, MecAAC = [H2C(CMe2)2NDipp]C; L = HC[C(Me)NDipp]2; Dipp = 2,6-i-Pr2C6H3) yielded the series of cationic group 15 compounds [(MecAAC)EGaL][Al(ORF)4] (E = As 4, Sb 5; Al(ORF)4 = Al(OC(CF3)3)4) and [(MecAAC)EGaL][B(ArF)4] (E = Sb 6, Bi 7; B(ArF)4 = B[C6H3(CF3)2]4), which were characterized by heteronuclear NMR spectroscopy and sc-XRD. The electronic nature of the cations [(MecAAC)EGaL]+ is controlled by the central pnictogen atom, according to quantum chemical calculations. The calculations furthermore demonstrated that compounds containing the lighter pnictogens (E = N, P) are best described as heteronuclear allyl cations, whereas heavier pnictogen atoms (E = As, Sb, Bi) serve as a trap for the positive charge, resulting in carbene-stabilized heterovinyl-type structures.

Single-Electron Oxidation of Carbene-Coordinated Pnictinidenes-Entry into Heteroleptic Radical Cations and Metalloid Clusters.

Stable heavy main group element radicals are challenging synthetic targets. Although several strategies have been developed to stabilize such odd-electron species, the number of heavier pnictogen-centered radicals is limited. We report on a series of two-coordinated pnictogen-centered radical cations [(MecAAC)EGa(Cl)L][B(C6F5)4] (MecAAC = [H2C(CMe2)2NDipp]C; Dipp = 2,6-i-Pr2C6H3; E = As 1, Sb 2, Bi 3; L = HC[C(Me)NDipp]2) synthesized by one-electron oxidation of L(Cl)Ga-substituted pnictinidenes (MecAAC)EGa(Cl)L (E = As I, Sb II, Bi III). 1-3 were characterized by electron paramagnetic resonance (EPR) spectroscopy and single crystal X-ray diffraction (sc-XRD) (1, 2), while quantum chemical calculations support their description as carbene-coordinated pnictogen-centered radical cations. The low thermal stability of 3 enables access to metalloid bismuth clusters as shown by formation of [{LGa(Cl)}3Bi6][B(C6F5)4] (4).

X-Band Parallel-Mode and Multifrequency Electron Paramagnetic Resonance Spectroscopy of S = 1/2 Bismuth Centers.

The recent successes in the isolation and characterization of several bismuth radicals inspire the development of new spectroscopic approaches for the in-depth analysis of their electronic structure. Electron paramagnetic resonance (EPR) spectroscopy is a powerful tool for the characterization of main group radicals. However, the large electron-nuclear hyperfine interactions of Bi (209Bi, I = 9/2) have presented difficult challenges to fully interpret the spectral properties for some of these radicals. Parallel-mode EPR (B1∥B0) is almost exclusively employed for the study of S > 1/2 systems but becomes feasible for S = 1/2 systems with large hyperfine couplings, offering a distinct EPR spectroscopic approach. Herein, we demonstrate the application of conventional X-band parallel-mode EPR for S = 1/2, I = 9/2 spin systems: Bi-doped crystalline silicon (Si:Bi) and the molecular Bi radicals [L(X)Ga]2Bi• (X = Cl or I) and [L(Cl)GaBi(MecAAC)]•+ (L = HC[MeCN(2,6-iPr2C6H3)]2). In combination with multifrequency perpendicular-mode EPR (X-, Q-, and W-band frequencies), we were able to fully refine both the anisotropic g- and A-tensors of these molecular radicals. The parallel-mode EPR experiments demonstrated and discussed here have the potential to enable the characterization of other S = 1/2 systems with large hyperfine couplings, which is often challenging by conventional perpendicular-mode EPR techniques. Considerations pertaining to the choice of microwave frequency are discussed for relevant spin-systems.

Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment.

PURPOSE: Total intracranial volume (TIV) is often a nuisance covariate in MRI-based brain volumetry. This study compared two TIV adjustment methods with respect to their impact on z-scores in single subject analyses of regional brain volume estimates. METHODS: Brain parenchyma, hippocampus, thalamus, and TIV were segmented in a normal database comprising 5059 T1w images. Regional volume estimates were adjusted for TIV using the residual method or the proportion method. Age was taken into account by regression with both methods. TIV- and age-adjusted regional volumes were transformed to z-scores and then compared between the two adjustment methods. Their impact on the detection of thalamus atrophy was tested in 127 patients with multiple sclerosis. RESULTS: The residual method removed the association with TIV in all regions. The proportion method resulted in a switch of the direction without relevant change of the strength of the association. The reduction of physiological between-subject variability was larger with the residual method than with the proportion method. The difference between z-scores obtained with the residual method versus the proportion method was strongly correlated with TIV. It was larger than one z-score point in 5% of the subjects. The area under the ROC curve of the TIV- and age-adjusted thalamus volume for identification of multiple sclerosis patients was larger with the residual method than with the proportion method (0.84 versus 0.79). CONCLUSION: The residual method should be preferred for TIV and age adjustments of T1w-MRI-based brain volume estimates in single subject analyses.

Eating disorder related research using Amazon Mechanical Turk (MTurk): Friend or foe?: Commentary on Burnette et al. (2021).

Burnette et al. reported a study that they sought to undertake to validate common eating disorder questionnaires in sexual and gender minorities. The researchers took advantage of the online recruitment platform Amazon Mechanical Turk (MTurk). Contrary to their expectations, the study proved not feasible due to invalid answering. Thus, Burnette et al. raise concerns against the trustworthiness of crowd-sourced data that may be undermined by financial interests and other kinds of motivations. Our commentary highlights the potential of the COVID-19 pandemic to inflate especially those intentions, which are monetary. Against the background of the COVID-19 pandemic, a further problem seems to be that the anonymity of online crowd sourcing platforms might tempt participants to provide inconsistent answers, possibly reflecting tendencies of reactance. The reported pattern of paradoxical responses in Burnette et al.'s work does not reflect malingering; rather we believe that the study might have served some participants as an outlet for negative emotions. We discuss mechanisms of quality control and highlight the lack of interpersonal interaction associated with online data collections.

From π-Bonded Gallapnictenes to Nucleophilic, Redox-Active Metal-Coordinated Pnictanides.

A comprehensive reactivity study of gallapnictenes LGaEGa(Cl)L (E=As, Sb; L=HC[C(Me)N(Ar)]2 , Ar=Dip=2,6-i-Pr2 C6 H3 ) proved the nucleophilic character of the pnictogen and the electrophilic nature of the Ga atom. Reactions of LGaEGa(Cl)L with imidazolium chloride [IPrH][Cl] yielded {[LGa(Cl)]2 E- }{IPrH+ } (E=As 1, Sb 2), and those with HCl and MeI gave pnictanes [LGa(Cl)]2 EH (E=As 5, Sb 6) and L(I)GaE(Me)Ga(Cl)L (E=As 7, Sb 8). Pnictanides 1 and 2 also react with [H(OEt2 )2 ][BArF 4 ] (BArF 4 =B(C6 F5 )4 ) to 5 and 6, while reactions with MeI yielded [LGa(Cl)]2 EMe (E=As 9, Sb 10). Single electron oxidation reactions of pnictanides 1 and 2 gave the corresponding radicals [LGa(Cl)]2 E. (E=As, Sb).

Stepwise Bi-Bi Bond Formation: From a Bi-centered Radical to Bi4 Butterfly and Bi8 Cuneane-Type Clusters.

In contrast to their lighter homologues (P, As, Sb), the synthesis of polybismuthane clusters is still restricted to classical solid-state approaches. We herein report on systematic reduction reactions of different bismuth precursors with Ga(I) and Mg(I) complexes. This study not only yielded the first metal-coordinated tetrabismuthane ([{L1(Cl)Ga}2-µ,η1:1-Bi4] 3, L1 = HC[C(Me)N(2,6-i-Pr2C6H3)]2) and realgar-type bismuth cluster ([(L2Mg)4(µ4,η2:2:2:2-Bi8)] 4, L2 = HC[C(Me)N(2,4,6-Me3C6H2)]2) in addition to the bismuth-centered radical [L1Ga(Cl)]2Bi• 1 and dibismuthene [L1(Cl)GaBi]2 2, but clearly demonstrates the crucial role of the substituents and the oxidation state of the bismuth precursor as well as the specific reduction potential of the main group metal reductants on the product formation. Compounds 3 and 4 were spectroscopically characterized (1H, 13C NMR, IR), and the structures of 1-4 were determined by single-crystal X-ray diffraction. Computational calculations gave deeper insights into the electronic structures of 1', 3', and 4'.

Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics.

PURPOSE: This study investigated the potential of deep convolutional neural networks (CNN) for automatic classification of FP-CIT SPECT in multi-site or multi-camera settings with variable image characteristics. METHODS: The study included FP-CIT SPECT of 645 subjects from the Parkinson's Progression Marker Initiative (PPMI), 207 healthy controls, and 438 Parkinson's disease patients. SPECT images were smoothed with an isotropic 18-mm Gaussian kernel resulting in 3 different PPMI settings: (i) original (unsmoothed), (ii) smoothed, and (iii) mixed setting comprising all original and all smoothed images. A deep CNN with 2,872,642 parameters was trained, validated, and tested separately for each setting using 10 random splits with 60/20/20% allocation to training/validation/test sample. The putaminal specific binding ratio (SBR) was computed using a standard anatomical ROI predefined in MNI space (AAL atlas) or using the hottest voxels (HV) analysis. Both SBR measures were trained (ROC analysis, Youden criterion) using the same random splits as for the CNN. CNN and SBR trained in the mixed PPMI setting were also tested in an independent sample from clinical routine patient care (149 with non-neurodegenerative and 149 with neurodegenerative parkinsonian syndrome). RESULTS: Both SBR measures performed worse in the mixed PPMI setting compared to the pure PPMI settings (e.g., AAL-SBR accuracy = 0.900 ± 0.029 in the mixed setting versus 0.957 ± 0.017 and 0.952 ± 0.015 in original and smoothed setting, both p < 0.01). In contrast, the CNN showed similar accuracy in all PPMI settings (0.967 ± 0.018, 0.972 ± 0.014, and 0.955 ± 0.009 in mixed, original, and smoothed setting). Similar results were obtained in the clinical sample. After training in the mixed PPMI setting, only the CNN provided acceptable performance in the clinical sample. CONCLUSIONS: These findings provide proof of concept that a deep CNN can be trained to be robust with respect to variable site-, camera-, or scan-specific image characteristics without a large loss of diagnostic accuracy compared with mono-site/mono-camera settings. We hypothesize that a single CNN can be used to support the interpretation of FP-CIT SPECT at many different sites using different acquisition hardware and/or reconstruction software with only minor harmonization of acquisition and reconstruction protocols.

A General Pathway for the Synthesis of Gallastibenes containing Ga=Sb Double Bonds.

Reactions of three equivalents of LGa {L=HC[C(Me)N(2,6-iPr2 C6 H3 )]2 } with SbX3 (X=F, Cl, Br, I) proceed with insertion into the Sb-X bond, elimination of LGaX2 , and formation of LGaSbGa(X)L (X=F 1, Cl 2, Br 3, I 4) containing a Ga=Sb double bond. In contrast, the 2:1 molar ratio reaction of LGa and SbCl3 initially gives the twofold insertion product [L(Cl)Ga]2 SbCl 7, which could not be isolated due to its strong tendency toward elimination of LGaCl2 and formation of distibene [L(Cl)GaSb]2 5 at 25 °C or cyclotristibine [L(Cl)GaSb]3 6 at 8 °C. The formation of 1-6 can be rationalized by formation of the Ga-substituted stibinidene L(X)GaSb as reaction intermediate.

Comprehensive Study on Reactions of Group 13 Diyls with Tetraorganodipentelanes.

L1Ga {L1 = HC[C(Me)N(2,6- iPr2C6H3)]2} reversibly reacts with E2Ph4 (E = Sb, Bi) in a temperature-dependent equilibrium reaction with insertion into the E-E bond and formation of L1Ga(EPh2)2 (E = Sb 1, Bi 2). Analogous findings were observed in the reactions of L2Ga {L2 = (C6H11)2NC[N(2,6- iPr2C6H3)]2} with E2R4 (R = Ph, Et), yielding L2Ga(EPh2)2 (E = Sb 3, Bi 4) and L2Ga(EEt2)2 (E = Sb 5, Bi 6). 1-3 and 5 were isolated by fractional crystallization at low temperature, whereas 4 and 6 could not be isolated in their pure form even at low temperature. In contrast, reactions of [Cp*Al]4 (Cp* = C5Me5) with Sb2R4 (R = Ph, Et) and Bi2Et4 did not proceed with insertion into the E-E bonds but with formation of (Cp*Al)3E2 (E = Sb, 7; Bi, 8), whereas the reaction with Bi2Ph4 yielded metallic bismuth. 8 was also formed in the reaction of [Cp*Al]4 and BiEt3 at ambient temperature, whereas the analogous reaction of [Cp*Al]4 with SbEt3 did not yield 7 even under drastic reaction conditions (120 °C, 3 days). In contrast, Cp*Ga and Sb2R4 (R = Ph, Et) were found to react only at elevated temperature (120 °C) with formation of antimony metal.

Valence shell threshold photoelectron spectroscopy of C3Hx (x = 0-3).

We present the photoelectron spectra of C3Hx (x = 0-3) formed in a microwave discharge flow-tube reactor by consecutive H abstractions from C3H4 (C3Hx + F → C3Hx-1 + HF (x = 1-4)), but also from F + CH4 schemes by secondary reactions. The spectra were obtained combining tunable VUV synchrotron radiation with double imaging electron/ion coincidence techniques, yielding mass-selected threshold photoelectron spectra. The obtained results complement not only existing ones, but for the first time the photoelectron spectra of C3, cyclic and linear C3H (c,l-C3H) as well as of the excited states of C3H3 are reported. In the case of c-C3H, l,t-C3H2 and C3H3, Franck-Condon simulations have been performed in order to assign the vibrational structure. The adiabatic ionization energies of these radicals are reported and compared to ab initio calculated values as well as to theoretical values using known enthalpies of formation.

Reduction of [Cp*Sb]4 with Subvalent Main-Group Metal Reductants: Syntheses and Structures of [(L1 Mg)4 (Sb4 )] and [(L2 Ga)2 (Sb4 )] Containing Edge-Missing Sb4 Units.

[Cp*Sb]4 (Cp*=C5 Me5 ) reacts with [L1 Mg]2 and L2 Ga with formation of [(L1 Mg)4 (µ4 ,η1:2:2:2 -Sb4 )] (L1 =iPr2 NC[N(2,6-iPr2 C6 H3 )]2 , 1) and [(L2 Ga)2 (µ,η2:2 -Sb4 )] (L2 =HC[C(Me)N(2,6-iPr2 C6 H3 )]2 , 2). The cleavage of the Sb-Sb and Sb-C bonds in [Cp*Sb]4 are the crucial steps in both reactions. The formation of 1 occurred by elimination of the Cp* anion and formation of Cp*MgL1 , while 2 was formed by reductive elimination of Cp*2 and oxidative addition of L2 Ga to the Sb4 unit. 1 and 2 were characterized by heteronuclear NMR spectroscopy and single-crystal X-ray diffraction, and their bonding situation was studied by quantum chemical calculations.

Synthesis, Structure, and Reactivity of Ga-Substituted Distibenes and Sb-Analogues of Bicyclo[1.1.0]butane.

Monovalent gallanediyl LGa {L=HC[C(Me)N(2,6-iPr2 C6 H3 )]2 } reacts with SbX3 to form the Ga-substituted distibenes [(LGaX)2 Sb2 ] (X=NMeEt 1, Cl 2). Upon heating, 2 reacts to the bicyclo[1.1.0]butane analogue [(LGaCl)2 (µ,η1:1 -Sb4 )] 3 containing a [Sb4 ]2- dianion. Moreover, 2 reacts with Li amides LiNR2 in salt elimination reactions that form the corresponding amido-substituted compounds 1 and [(LGaNMe2 )2 Sb2 ] 4, whereas reactions of 4 and [(LGaNMe2 )2 (µ,η1:1 -Sb4 )] 5 with two equivalents of GaCl3 resulted in the formation of 2 and 3, respectively. 1, 2 and 3 were characterized by 1 H and 13 C NMR spectroscopy, elemental analysis, and single crystal X-ray diffraction. In addition, their bonding situation was analyzed by quantum chemical calculations.

Valence shell threshold photoelectron spectroscopy of the CHxCN (x = 0-2) and CNC radicals.

We present the photoelectron spectroscopy of four radical species, CHxCN (x = 0-2) and CNC, formed in a microwave discharge flow-tube reactor by consecutive H abstractions from CH3CN (CHxCN + F → CHx-1CN + HF (x = 1-3)). The spectra were obtained combining tunable vacuum ultraviolet synchrotron radiation with double imaging electron/ion coincidence techniques, which yielded mass-selected threshold photoelectron spectra. The results obtained for H2CCN complement existing ones while for the other radicals the data represent the first observation of their (single-photon) ionizing transitions. In the case of H2CCN, Franck-Condon calculations have been performed in order to assign the vibrational structure of the X+ 1A1←X 2B1 ionizing transition. A similar treatment for the HCCN, CCN, and CNC radicals appeared to be more complicated mainly because a Renner-Teller effect strongly affects the vibrational levels of the ground electronic state of the HCCN+, CCN, and CNC species. Nevertheless, the first adiabatic ionization energies of these radicals are reported and compared to our ab initio calculated values, leading to new values for enthalpies of formation (ΔfH2980(HCCN+(X2A'))=1517±12kJmol-1,ΔfH2980(CCN(X2Π))=682±13kJmol-1, and ΔfH2980(CNC(X2Πg))=676±12kJmol-1), which are of fundamental importance for astrochemistry.

Bioelectric patterning during oogenesis: stage-specific distribution of membrane potentials, intracellular pH and ion-transport mechanisms in Drosophila ovarian follicles.

BACKGROUND: Bioelectric phenomena have been found to exert influence on various developmental and regenerative processes. Little is known about their possible functions and the cellular mechanisms by which they might act during Drosophila oogenesis. In developing follicles, characteristic extracellular current patterns and membrane-potential changes in oocyte and nurse cells have been observed that partly depend on the exchange of protons, potassium ions and sodium ions. These bioelectric properties have been supposed to be related to various processes during oogenesis, e. g. pH-regulation, osmoregulation, cell communication, cell migration, cell proliferation, cell death, vitellogenesis and follicle growth. Analysing in detail the spatial distribution and activity of the relevant ion-transport mechanisms is expected to elucidate the roles that bioelectric phenomena play during oogenesis. RESULTS: To obtain an overview of bioelectric patterning along the longitudinal and transversal axes of the developing follicle, the spatial distributions of membrane potentials (Vmem), intracellular pH (pHi) and various membrane-channel proteins were studied systematically using fluorescent indicators, fluorescent inhibitors and antisera. During mid-vitellogenic stages 9 to 10B, characteristic, stage-specific Vmem-patterns in the follicle-cell epithelium as well as anteroposterior pHi-gradients in follicle cells and nurse cells were observed. Corresponding distribution patterns of proton pumps (V-ATPases), voltage-dependent L-type Ca(2+)-channels, amiloride-sensitive Na(+)-channels and Na(+),H(+)-exchangers (NHE) and gap-junction proteins (innexin 3) were detected. In particular, six morphologically distinguishable follicle-cell types are characterized on the bioelectric level by differences concerning Vmem and pHi as well as specific compositions of ion channels and carriers. Striking similarities between Vmem-patterns and activity patterns of voltage-dependent Ca(2+)-channels were found, suggesting a mechanism for transducing bioelectric signals into cellular responses. Moreover, gradients of electrical potential and pH were observed within single cells. CONCLUSIONS: Our data suggest that spatial patterning of Vmem, pHi and specific membrane-channel proteins results in bioelectric signals that are supposed to play important roles during oogenesis, e. g. by influencing spatial coordinates, regulating migration processes or modifying the cytoskeletal organization. Characteristic stage-specific changes of bioelectric activity in specialized cell types are correlated with various developmental processes.