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Introduction: Adrenocortical carcinoma (ACC) is a rare endocrine malignancy, with very poor prognosis as a majority of the patients have advanced disease at the time of diagnosis. Currently, adjuvant therapy for most patients consists of either mitotane (M) alone or in combination with multi-drug chemotherapeutics such as etoposide (E), doxorubicin (D), and cisplatin (P), known as the Italian protocol (IP, EDPM). This multi-drug treatment regimen, however, carries significant toxicity potential for patients. One way to improve toxicity profiles with these drugs in combination is to understand where their synergy occurs and over what dosing range so that lower dose regimens could be applied in combination with equal or improved efficacy. We hypothesize that a better understanding of the synergistic effects as well as the regulation of steroidogenic enzymes during combination therapy may provide more optimized combinational options with good potency and lower toxicity profiles. Methods: Two human ACC cell lines, NCI-H295R (hormonally active) and SW13 (hormonally inactive), were grown in 2D culture in appropriate growth medium. The viability of the cells after treatment with varying concentrations of the drugs (E, D, and P) either alone or in combinations with M was determined using the CellTiter Glow assay after 72 h, and the combination index for each was calculated using Compusyn by the Chou–Talalay method. The expression levels of enzymes associated with steroidogenesis were evaluated by RT-PCR in NCI-H295R. Results: When both cell lines were treated with M (ranging 25–50 μM), +E (ranging 18.75–75 μM), and +D (ranging 0.625–2.5 μM) we observed a synergistic effect (CI &lt, 1) with potency equivalent to the full Italian protocol (IP), whereas combining M + P + D had an antagonistic effect (CI &gt, 1) indicating the negative effect of adding cisplatin in the combination. Comparing the hormonally active and inactive cell lines, M + P + E was antagonistic in NCI-H295R and synergistic in SW13. Treatment of NCI-H295R cells with antagonistic combinations (M + P + D, M + P + E) resulted in a significant decrease in the levels of steroidogenic enzymes STAR, CYP11A1, and CYP21A2 compared to IP (p &lt, 0.05) while M + E + D resulted in increased expression or no significant effect compared to IP across all genes tested. Conclusions: The synergistic effect for M + E + D was significant and equivalent in potency to the full IP in both cell lines and resulted in a steroidogenic gene expression profile similar to or better than that of full IP, warranting further evaluation. Future in vivo evaluation of the combination of M + E + D (with removal of P from the IP regimen) may lower toxicity while maintaining anticancer efficacy in ACC.

Objective The aim of the study is to survey hand surgeons' perspectives on telemedicine during the coronavirus disease 2019 (COVID-19) pandemic and intended applications after the pandemic. Methods Online surveys were sent to 285 Canadian and American surgeons in late April and early May 2020. Results Response rate was 63% (180)—84% (152) American and 16% (28) Canadian. Forty-three percent (76) of respondents were in private practice, 36% (64) academics, 13% (24) privademics, and 6% (12) hospital employed. The most common telemedicine platform was Zoom. During the pandemic, 42% of patient visits were conducted via telemedicine; however, 37% required a subsequent in-person office visit. The most common complaint by surgeons was the inability to provide routine in-office procedures. The most beneficial feature was ease of use, and the most frustrating feature was connectivity difficulty. Time spent was similar to in-person visits, and surgeons were likely to recommend their platforms. Surgeons were neutral about using telehealth in the future and were most likely to use it for follow-up visits. New patient visits for traumatic injuries or fractures were of limited value. Canadians used telemedicine for a greater proportion than Americans (50 vs. 40%, p Conclusion Telemedicine comprised nearly half of patient encounters during the COVID-19 pandemic, but limitations remain.

Approximately 6.3 million fractures occur in the U.S. annually, with 5–10% resulting in debilitating nonunions. A major limitation to achieving successful bony union is impaired neovascularization. To augment fracture healing, we designed an implantable drug delivery technology containing the angiogenic stimulant, deferoxamine (DFO). DFO activates new blood vessel formation through iron chelation and upregulation of the HIF-1α pathway. However, due to its short half-life and rapid clearance, maintaining DFO at the callus site during peak fracture angiogenesis has remained challenging. To overcome these limitations, we composed an implantable formulation of DFO conjugated to hyaluronic acid (HA). This compound immobilizes DFO within the fracture callus throughout the angiogenic window, making it a high-capacity iron sponge that amplifies blood vessel formation and prevents nonunions. We investigated implanted HA-DFO’s capacity to facilitate fracture healing in the irradiated rat mandible, a model whereby nonunions routinely develop secondary to obliteration of vascularity. HA-DFO implantation significantly improved radiomorphometrics and metrics of biomechanical strength. In addition, HA-DFO treated mandibles exhibited a remarkable 91% bone union rate, representing a 3.5-fold improvement over non-treated/irradiated controls (20% bone union rate). Collectively, our work proposes a unique methodology for the targeted delivery of DFO to fracture sites in order to facilitate neovascularization. If these findings are successfully translated into clinical practice, millions of patients will benefit from the prevention of nonunions.

ObjectiveLow-Intensity Focused Ultrasound Pulsations (LIFUP) is a promising new potential neuromodulation tool. However, the safety of LIFUP neuromodulation has not yet been adequately assessed. Patients with refractory temporal lobe epilepsy electing to undergo an anterior temporal lobe resection present a unique opportunity to evaluate the safety and efficacy of LIFUP neuromodulation. Because the brain tissue in these patients will be removed, histological changes in tissue after LIFUP can be examined. Evidence of effective neuromodulation was assessed using functional MRI and EEG, while further potential safety concerns were assessed using neuropsychological testing.MethodsEEG, functional MRI, and neuropsychology were assessed in six patients before and after focused ultrasound sonication of the temporal lobe at intensities up to 5760 mW/cm2. Using the BrainSonix Pulsar 1002, LIFUP was delivered under MR guidance, using the Siemens Magnetom 3T Prisma scanner. Neuropsychological changes were assessed using various batteries. EEG was recorded using the Electrical Geodesics EGI 256 channel system. Histological changes were assessed using hematoxylin and eosin staining, among others.ResultsLIFUP was not able to modulate the BOLD signal on fMRI in a reliable and consistent manner. The EEG data that was available did not demonstrate a change in activity after LIFUP in all but one subject. Likewise, the neuropsychology testing did not show any statistically significant changes in any test, except for a slight decrease in performance on the one test after LIFUP. Lastly, the histology did not reveal any detectable damage to the tissue, except for one subject for whom the histology findings were inconclusive.SignificanceThe safety in the histology was the primary endpoint, and as such, longer exposure at the highest intensity levels will be administered moving forward.Key PointsLIFUP is a novel brain stimulation technique with not yet fully established safety guidelines.LIFUP was administered to patients electing to undergo resective brain surgery.LIFUP does not appear to cause damage to tissue.Longer exposure times are needed to further show safety at these intensity levels.

INTRODUCTION: Binimetinib is an uncompetitive, small molecule inhibitor of selective mitogen-activated protein kinase (MEK1/2) and was recently approved in 2018 in combination with encorafenib for the treatment of metastatic melanomas. Preclinical and clinical trial data on the drug demonstrate its potent efficacy in cancers, especially melanomas with BRAF and NRAS mutations. AREAS COVERED: The authors review the preclinical as well as clinical Phase 1, 2 and 3 trial data leading to its FDA approval in 2018 for metastatic melanoma. Phase 3 data in combination with encorafenib demonstrated double the PFS (14.9 months) compared to vemurafenib alone (7.3 months) in patients with BRAF-mutated metastatic melanoma. EXPERT OPINION: No longer-term data is available yet to demonstrate any durable complete responses to therapy with binimetinib or improvements in overall survival compared to other FDA approved therapies including immunotherapy or vemurafenib. Treatment approaches to patients with BRAF mutated metastatic melanoma should be individualized and binimetinib in combination with encorafenib is a reasonable oral strategy with a reasonably tolerated toxicity profile. Cost of treatment and durability of response should be incorporated into the discussion as part of the overall medical decision making.

The 90-kDa heat shock protein (Hsp90) is a molecular chaperone that ensures cellular proteostasis by maintaining the folding, stabilization, activation, and degradation of over 400 client proteins. Hsp90 is not only critical for routine protein maintenance in healthy cells, but also during states of cellular stress, such as cancer and neurodegenerative diseases. Due to its ability to affect phosphorylation of numerous client proteins, inhibition of Hsp90 has been an attractive anticancer approach since the early 1990’s, when researchers identified a druggable target on the amino terminus of Hsp90 for a variety of cancers. Since then, 17 Hsp90 inhibitors that target the chaperone’s Nterminal domain, have entered clinical trials. None, however, have been approved thus far by the FDA as a cancer monotherapy. In these trials, a major limitation observed with Hsp90 inhibition at the N-terminal domain was dose-limiting toxicities and relatively poor pharmacokinetic profiles. Despite this, preclinical and clinical research continues to show that Hsp90 inhibitors effectively target cancer cell death and decrease tumor progression supporting the rationale for the development of novel Hsp90 inhibitors. Here, we present an in-depth overview of the Hsp90 inhibitors used in clinical trials. Finally, we present current shifts in the field related to targeting the carboxy-terminal domain of Hsp90 as well as to the development of isoform-selective inhibitors as a means to bypass the pitfalls of current Hsp90 inhibitors and improve clinical trial outcomes.

The 90 kDa heat shock protein (Hsp90) is a molecular chaperone responsible for folding proteins that are directly associated with cancer progression. Consequently, inhibition of the Hsp90 protein folding machinery results in a combinatorial attack on numerous oncogenic pathways. Seventeen small-molecule inhibitors of Hsp90 have entered clinical trials, all of which bind the Hsp90 N-terminus and exhibit pan-inhibitory activity against all four Hsp90 isoforms. pan-Inhibition of Hsp90 appears to be detrimental as toxicities have been reported alongside induction of the pro-survival heat shock response. The development of Hsp90 isoform-selective inhibitors represents an alternative approach towards the treatment of cancer that may limit some of the detriments. Described herein is a structure-based approach to design isoform-selective inhibitors of Hsp90β, which induces the degradation of select Hsp90 clients without concomitant induction of Hsp90 levels. Together, these initial studies support the development of Hsp90β-selective inhibitors as a method to overcome the detriments associated with pan-inhibition., The molecular chaperone Hsp90 oversees the folding of many proteins associated with cancer progression but existing small-molecule inhibitors of this pathway are not isoform-selective. Here, the authors rationally design an Hsp90 inhibitor that displays high selectivity for the Hsp90β isoform.

Introduction: COVID-19 has created experiential barriers for surgical learners to interact at the bedside for teaching/case presentations. We hypothesized that an international Grand Rounds using the Microsoft HoloLens2 extended reality (XR) headset creates an improved bedside-learning experience compared with traditional Grand Rounds formats. Methods: In December 2020, we hosted (through partnership with the University of Michigan and Imperial College of London) the world’s first International Grand Rounds experience using the HoloLens2 XR headset broadcasting transatlantic bedside rounding on 3 complex surgical patients to an international audience of 154 faculty, residents, and medical trainees. Participants completed qualitative pre- and post-event surveys. Results: Of the 154 participants, 96 (62%) completed pre-surveys and 70 (45%) completed both the pre-and post-surveys. Respondents (average age 39.3 years [43% women;57% men;80 US;16 UK]) included 30 medical students, 30 faculty, 7 residents, and 29 hospital administrators. Pre-event survey: 76% had little or no experience before with XR devices;92% thought development/implementation of XR medical curricula was valuable;and 96% felt tele-rounding using XR technology was important for the current era. Post survey: 98% respondents thought the ability to visualize bedside clinical findings, imaging, and lab-tests via XR rounding was highly valuable and this novel XR international Grand Rounds format was superior to traditional Grand Rounds. Conclusion: Almost all (98%) participants in the world’s first International Grand Rounds on a Mixed Reality Headset felt this immersive extended reality virtual experience allowed visualization of clinical findings, imaging, and labs at the patient’s bedside and was superior to a traditional Grand Rounds format.

Rui Kuai,1,2,* Chitra Subramanian,3,* Peter T White,3,* Barbara N Timmermann,4 James J Moon,1,2,5 Mark S Cohen,3,6 Anna Schwendeman1,2 1Department of Pharmaceutical Sciences, College of Pharmacy, 2Biointerfaces Institute, University of Michigan, 3Department of Surgery, University of Michigan, Ann Arbor, MI, 4Department of Medicinal Chemistry, University of Kansas, Lawrence, KS, 5Department of Biomedical Engineering, 6Department of Pharmacology, University of Michigan, Ann Arbor, MI, USA *These authors contributed equally to this work Abstract: Adrenocortical carcinoma (ACC) is a rare endocrine malignancy and has a 5-year survival rate of

The underlying mechanisms of alpha band (8–12 Hz) neural oscillations are of importance to the functioning of attention control systems as well as to neuropsychiatric conditions that are characterized by deficits of that system, such as attention deficit hyperactivity disorder (ADHD). The objectives of the present study were to test if visual encoding-related alpha event-related desynchronization (ERD) correlates with fronto-parieto-occipital connectivity, and whether this is disrupted in ADHD during spatial working memory (SWM) performance. We acquired EEG concurrently with fMRI in thirty boys (12–16 yrs. old, 15 with ADHD), during SWM encoding. Psychophysiological connectivity analyses indicated that alpha ERD during SWM encoding was associated with both occipital activation and fronto-parieto-occipital functional connectivity, a finding that expands on prior associations between alpha ERD and occipital activation. This finding provides novel support for the interpretation of alpha ERD (and the associated changes in occipital activation) as a phenomenon that involves, and perhaps arises as a result of, top-down network interactions. Alpha ERD was associated less strongly with occipital activity, but associated more strongly with fronto-parieto-occipital connectivity in ADHD, consistent with a compensatory attentional response. Additionally, we illustrate that degradation of EEG data quality by MRI-amplified motion artifacts is robust to existing cleaning algorithms and is significantly correlated with hyperactivity symptoms and the ADHD Combined Type diagnosis. We conclude that persistent motion-related MR artifacts in EEG data can increase variance and introduce bias in interpretation of group differences in populations characterized by hypermobility — a clear limitation of current-state EEG-fMRI methodology., Graphical abstract, Highlights • We measure neural activity and connectivity of alpha ERD. • We employ concurrent EEG-fMRI recordings. • Alpha ERD predicts occipital activation and fronto-parieto-occipital connectivity. • ADHD participants show weaker alpha ERD occipital effects. • ADHD participants show stronger alpha ERD connectivity effects.

Functional magnetic resonance imaging (fMRI) adaptation (also known as fMRI repetition suppression) has been widely used to characterize stimulus selectivity in vivo, a fundamental feature of neuronal processing in the brain. We investigated whether SZ patients and BD patients show aberrant fMRI adaptation for object perception. About 52 SZ patients, 55 BD patients, and 53 community controls completed an object discrimination task with three conditions: the same object presented twice, two exemplars from the same category, and two exemplars from different categories. We also administered two functional localizer tasks. A region of interest analysis was employed to evaluate a priori hypotheses about the lateral occipital complex (LOC) and early visual cortex (EVC). An exploratory whole brain analysis was also conducted. In the LOC and EVC, controls showed the expected reduced fMRI responses to repeated presentation of the same objects compared with different objects (i.e., fMRI adaptation for objects, p

Despite considerable effort to remove it, the ballistocardiogram (BCG) remains a major artifact in electroencephalographic data (EEG) acquired inside magnetic resonance imaging (MRI) scanners, particularly in continuous (as opposed to event-related) recordings. In this study, we have developed a new Direct Recording Prior Encoding (DRPE) method to extract and separate the BCG and EEG components from contaminated signals, and have demonstrated its performance by comparing it quantitatively to the popular Optimal Basis Set (OBS) method. Our modified recording configuration allows us to obtain representative bases of the BCG- and EEG-only signals. Further, we have developed an optimization-based reconstruction approach to maximally incorporate prior knowledge of the BCG/EEG subspaces, and of the signal characteristics within them. Both OBS and DRPE methods were tested with experimental data, and compared quantitatively using cross-validation. In the challenging continuous EEG studies, DRPE outperforms the OBS method by nearly sevenfold in separating the continuous BCG and EEG signals. © 2014 Xia, Ruan and Cohen.

The ability to attend to an input selectively while ignoring distracting sensations is thought to depend on the coordination of two processes: enhancement of target signals and attenuation of distractor signals. This implies that attending and ignoring may be dissociable neural processes and that they make separable contributions to behavioral outcomes of attention. In this study, we tested these hypotheses in the context of sustained attention by measuring neurophysiological responses to attended and ignored stimuli in a noncued, continuous, audiovisual selective attention task. We compared these against responses during a passive control to quantify effects of attending and ignoring separately. In both sensory modalities, responses to ignored stimuli were attenuated relative to a passive control, whereas responses to attended stimuli were enhanced. The scalp topographies and brain activations of these modulatory effects were consistent with the sensory regions that process each modality. They also included parietal and prefrontal activations that suggest these effects arise from interactions between top–down and sensory cortices. Most importantly, we found that both attending and ignoring processes contributed to task accuracy and that these effects were not correlated—suggesting unique neural trajectories. This conclusion was supported by the novel observation that attending and ignoring differed in timing and in active cortical regions. The data provide direct evidence for the separable contributions of attending and ignoring to behavioral outcomes of attention control during sustained intersensory attention.

The recent Chu et al. (2012) manuscript discusses two key findings regarding feature selection (FS): (1) data driven FS was no better than using whole brain voxel data and (2) a priori biological knowledge was effective to guide FS. Use of FS is highly relevant in neuroimaging-based machine learning, as the number of attributes can greatly exceed the number of exemplars.We strongly endorse their demonstration of both of these findings, andwe provide additional important practical and theoretical arguments as towhy, in their case, the data-driven FS methods they implemented did not result in improved accuracy. Further, we emphasize that the data-driven FS methods they tested performed approximately as well as the all-voxel case. We discuss why a sparse model may be favored over a complex one with similar performance. We caution readers that the findings in the Chu et al. report should not be generalized to all data-driven FS methods. © 2013 Elsevier Inc.

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject’s decision response to a given propositional statement based on independent component (IC) features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM) results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities.

The application of machine learning to epilepsy can be used both to develop clinically useful computer-aided diagnostic tools, and to reveal pathologically relevant insights into the disease. Such studies most frequently use neurologically normal patients as the control group to maximize the pathologic insight yielded from the model. This practice yields potentially inflated accuracy because the groups are quite dissimilar. A few manuscripts, however, opt to mimic the clinical comparison of epilepsy to non-epileptic seizures, an approach we believe to be more clinically realistic. In this manuscript, we describe the relative merits of each control group. We demonstrate that in our clinical quality FDG-PET database the performance achieved was similar using each control group. Based on these results, we find that the choice of control group likely does not hinder the reported performance. We argue that clinically applicable computer-aided diagnostic tools for epilepsy must directly address the clinical challenge of distinguishing patients with epilepsy from those with non-epileptic seizures.

Importance Treatment of locally advanced head and neck squamous cell carcinoma (HNSCC) uses a multidisciplinary approach often limited by the toxicity and drug resistance of platinum agents. Objectives To test whether a nanocarrier-conjugated cisplatin boosting locoregional drug delivery improves tumor efficacy while decreasing systemic toxicity over systemic cisplatin in a murine model of locally advanced HNSCC. Design A randomized, controlled, in vivo study compared standard cisplatin with nanocarrier (hyaluronan [HA])–conjugated cisplatin (HA-cisplatin) each at 50% of the maximum tolerated doses in a murine model of locally advanced HNSCC (10 mice/arm, each injected with 1 × 106 MDA-1986 HNSCC cells, with phosphate-buffered saline and HA-only control arms). Mice were treated for 3 weeks and observed for 3 additional weeks. Setting Academic medical center. Participants Forty female Nu/Nu mice. Randomization and treatment arms were initiated once tumor volumes reached 30 mm3. Intervention Injection with MDA-1986 HNSCC cells followed by 3 weeks of treatment with cisplatin, HA-cisplatin, phosphate-buffered saline, or HA only. Main Outcomes and Measures Animal weights and tumor volumes were measured 3 times each week (modified RECIST [Response Evaluation Criteria in Solid Tumors]). At necropsy, animal kidneys were examined for nephrotoxic effects and cochleae were examined for ototoxic effects. Results The mice treated with HA-cisplatin showed superior tumor efficacy (1 with complete clinical response, 3 with partial response, 1 with stable disease, and 5 with progressive disease) compared with standard cisplatin (no animals with complete clinical response, 1 with partial response, 1 with stable disease, and 8 with progressive disease), which was statistically significant (P = .003). All control animals developed progressive disease. Weight loss and body score were surrogate measures of treatment toxicity. The HA-cisplatin group had the least weight loss (mean [SD], 10.8% [4.7%]) compared with the cisplatin group (13.6% [5.6%]; P = .25). Body score dropped to 2 or less in all cisplatin-treated mice but not in any HA-cisplatin–treated mice, which also lacked any histologic signs of nephrotoxic or ototoxic effects. Conclusions and Relevance Nanoconjugated HA-cisplatin significantly improves tumor efficacy with lower toxicity compared with standard cisplatin in locally advanced HNSCC in vivo, justifying additional translational studies.

Whether degenerative joint disease of the elbow may be the result of primary or posttraumatic etiologies, arthritis of the elbow commonly leads to pain, loss of motion, and functional disability. A detailed history and focused physical examination, in combination with imaging modalities, can help localize the origin of symptoms and help direct treatment. Although nonoperative treatment is the initial therapy for arthritis of the elbow, surgical interventions may provide substantial relief to the appropriately selected patient.

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multi site collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxel wise global connectivity, and voxel wise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. © 2012 Colby, Rudie, Brown, Douglas, Cohen and Shehzad.

Developing EEG-based computer aided diagnostic (CAD) tools would allow identification of epilepsy in individuals who have experienced possible seizures, yet such an algorithm requires efficient identification of meaningful features out of potentially more than 35,000 features of EEG activity. Mutual information can be used to identify a subset of minimally-redundant and maximally relevant (mRMR) features but requires a priori selection of two parameters: the number of features of interest and the number of quantization levels into which the continuous features are binned. Here we characterize the variance of cross-validation accuracy with respect to changes in these parameters for four classes of machine learning (ML) algorithms. This assesses the efficiency of combining mRMR with each of these algorithms by assessing when the variance of cross-validation accuracy is minimized and demonstrates how naA¯ve parameter selection may artificially depress accuracy. Our results can be used to improve the understanding of how feature selection interacts with four classes of ML algorithms and provide guidance for better a priori parameter selection in situations where an overwhelming number of redundant, noisy features are available for classification.

Independent component analysis (ICA) is a popular method for the analysis of functional magnetic resonance imaging (fMRI) signals that is capable of revealing connected brain systems of functional significance. To be computationally tractable, estimating the independent components (ICs) inevitably requires one or more dimension reduction steps. Whereas most algorithms perform such reductions in the time domain, the input data are much more extensive in the spatial domain, and there is broad consensus that the brain obeys rules of localization of function into regions that are smaller in number than the number of voxels in a brain image. These functional units apparently reorganize dynamically into networks under different task conditions. Here we develop a new approach to ICA, producing group results by bagging and clustering over hundreds of pooled single-subject ICA results that have been projected to a lower-dimensional subspace. Averages of anatomically based regions are used to compress the single subject-ICA results prior to clustering and resampling via bagging. The computational advantages of this approach make it possible to perform group-level analyses on datasets consisting of hundreds of scan sessions by combining the results of within-subject analysis, while retaining the theoretical advantage of mimicking what is known of the functional organization of the brain. The result is a compact set of spatial activity patterns that are common and stable across scan sessions and across individuals. Such representations may be used in the context of statistical pattern recognition supporting real-time state classification. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 223–231, 2011 (This work is supported by the National Institute on Drug Abuse under DA026109 to M.S.C and by WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-2008-000-10008-0) to AY. The grant funding that supported the data collection was: the National Institute on Drug Abuse (A.L.B. [R01 DA20872]), a Veterans Affairs Type I Merit Review Award (A.L.B.), and an endowment from the Richard Metzner Chair in Clinical Neuropharmacology (A.L.B.). We thank Michael Durnhofer for maintaining the systems necessary for these data analyses.)

As part of a program to discover drug leads from plant biodiversity, the present investigation was undertaken to explore the anticancer potential of compounds derived from selected Latin American plants. Bioassay-guided fractionation of a crude extract of the aerial parts of Vassobia breviflora led to the isolation of the withanolide-type steroidal lactone withaferin A (1). This compound was tested for antiproliferative activity against the head and neck squamous cell carcinoma (HNSCC) cell lines, MDA1986, JMAR, UM-SCC-2, and JHU011. The inhibitory concentrations to reduce cell viability to 50% (IC(50)) were determined by the MTS cytotoxicity assay, and 1 reduced cell viability with IC(50) values in the range 0.5-2.2 μM. A mechanistic study showed that 1 induces apoptosis and cell death in HNSCC cells as well as a cell-cycle shift from G(0)/G(1) to G(2)/M. Cells treated with 1 exhibited inactivation of Akt and a reduction in total Akt concentration. This investigation constitutes the first report of the antiproliferative activity of withaferin A (1) against head and neck squamous carcinoma.

Cisplatin (CDDP) is an effective anticancer agent for many solid tumors but has significant systemic toxicity limiting its use in many patients. We have designed a loco-regional delivery system to increase platinum levels in the lymphatics, where early metastasis is most likely to occur, while reducing systemic toxicities. CDDP was conjugated to a biocompatible polymer hyaluronan (HA), with a conjugation degree of approximately 20% (w/w). Conjugates were delivered via subcutaneous injection into the mammary fat pad of rats. Intravenous hyaluronan-cisplatin (HA-Pt) exhibited an increased plasma area under the curve (AUC) 2.7-fold compared to conventional CDDP but with a reduced peak plasma level (C(max)), and HA-Pt increased the ipsilateral lymph node AUC by 3.8-fold compared to CDDP. Urine creatinine was unchanged over 30 days following dosing of HA-Pt. This study demonstrates that intralymphatic drug delivery with polymer-conjugated platinum may provide greater tissue and systemic plasma concentrations of platinum than intravenous CDDP. In addition, localized particle delivery augmented distribution in the loco-regional tissue basin where tumor burden predominates, while renal toxicity compared to standard intravenous CDDP was significantly reduced.