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OBJECTIVE: Deep brain stimulation (DBS) studies have shown that stimulation of the motor segment of the thalamus based on probabilistic tractography is predictive of improvement in essential tremor (ET). However, probabilistic methods are computationally demanding, requiring the need for alternative tractography methods for use in the clinical setting. The purpose of this study was to compare probabilistic vs deterministic tractography methods for connectivity-based targeting in patients with ET. METHODS: Probabilistic and deterministic tractography methods were retrospectively applied to diffusion-weighted data sets in 36 patients with refractory ET. The thalamus and precentral gyrus were selected as regions of interest and fiber tracking was performed between these regions to produce connectivity-based thalamic segmentations, per prior methods. The resultant deterministic target maps were compared with those of thresholded probabilistic maps. The center of gravity (CG) of each connectivity map was determined and the differences in spatial distribution between the tractography methods were characterized. Furthermore, the intersection between the connectivity maps and CGs with the therapeutic volume of tissue activated (VTA) was calculated. A mixed linear model was then used to assess clinical improvement in tremor with volume of overlap. RESULTS: Both tractography methods delineated the region of the thalamus with connectivity to the precentral gyrus to be within the posterolateral aspect of the thalamus. The average CG of deterministic maps was more medial-posterior in both the left (3.7 ± 1.3 mm3) and the right (3.5 ± 2.2 mm3) hemispheres when compared to 30 %-thresholded probabilistic maps. Mixed linear model showed that the volume of overlap between CGs of deterministic and probabilistic targeting maps and therapeutic VTAs were significant predictors of clinical improvement. CONCLUSIONS: Deterministic tractography can reconstruct DBS thalamic target maps in approximately 5 min comparable to those produced by probabilistic methods that require > 12 h to generate. Despite differences in CG between the methods, both deterministic-based and probabilistic targeting were predictive of clinical improvement in ET.

Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.

BackgroundThe efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.ObjectiveLeverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.MethodsEvoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.ResultsEvoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.ConclusionThe two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Increased protein translation in cells and various factors in the tumor microenvironment can induce endoplasmic reticulum (ER) stress, which initiates the unfolded protein response (UPR). We have previously reported that factors released from cancer cells mounting a UPR induce a de novo UPR in bone marrow-derived myeloid cells, macrophages, and dendritic cells that facilitates protumorigenic characteristics in culture and tumor growth in vivo. We investigated whether this intercellular signaling, which we have termed transmissible ER stress (TERS), also operates between cancer cells and what its functional consequences were within the tumor. We found that TERS signaling induced a UPR in recipient human prostate cancer cells that included the cell surface expression of the chaperone GRP78. TERS also activated Wnt signaling in recipient cancer cells and enhanced resistance to nutrient starvation and common chemotherapies such as the proteasome inhibitor bortezomib and the microtubule inhibitor paclitaxel. TERS-induced activation of Wnt signaling required the UPR kinase and endonuclease IRE1. However, TERS-induced enhancement of cell survival was predominantly mediated by the UPR kinase PERK and a reduction in the abundance of the transcription factor ATF4, which prevented the activation of the transcription factor CHOP and, consequently, the induction of apoptosis. When implanted in mice, TERS-primed cancer cells gave rise to faster growing tumors than did vehicle-primed cancer cells. Collectively, our data demonstrate that TERS is a mechanism of intercellular communication through which tumor cells can adapt to stressful environments.

Monocyte and dendritic cell (DC) development was evaluated using in vivo BrdU pulse-chase analyses in rhesus macaques, and phenotype analyses of these cells in blood also were assessed by immunostaining and flow cytometry for comparisons among rhesus, cynomolgus, and pigtail macaques, as well as African green monkeys and humans. The nonhuman primate species and humans have three subsets of monocytes, CD14(+)CD16(-), CD14(+)CD16(+), and CD14(-)CD16(+) cells, which correspond to classical, intermediate, and nonclassical monocytes, respectively. In addition, there exist presently two subsets of DC, BDCA-1(+) myeloid DC and CD123(+) plasmacytoid DC, that were first confirmed in rhesus macaque blood. Following BrdU inoculation, labeled cells first appeared in CD14(+)CD16(-) monocytes, then in CD14(+)CD16(+) cells, and finally in CD14(-)CD16(+) cells, thus defining different stages of monocyte maturation. A fraction of the classical CD14(+)CD16(-) monocytes gradually expressed CD16(+) to become CD16(+)CD14(+) cells and subsequently matured into the nonclassical CD14(-)CD16(+) cell subset. The differentiation kinetics of BDCA-1(+) myeloid DC and CD123(+) plasmacytoid DC were distinct from the monocyte subsets, indicating differences in their myeloid cell origins. Results from studies utilizing nonhuman primates provide valuable information about the turnover, kinetics, and maturation of the different subsets of monocytes and DC using approaches that cannot readily be performed in humans and support further analyses to continue examining the unique myeloid cell origins that may be applied to address disease pathogenesis mechanisms and intervention strategies in humans.

Objectives: This study aimed to estimate clinical, economic (including productivity), and health‐related quality of life (HRQoL) outcomes and associated individual characteristics among adults with overweight (OW) or obesity in the United States. Methods: This study included adult respondents with body mass index (BMI) ≥18.5 kg/m2 in the 2017–2018 National Health and Nutrition Examination Survey (NHANES) and 2016 Medical Expenditure Panel Survey. Respondents were classified according to BMI. Individual characteristics were described by BMI categories. Multivariable regression models estimated the association between BMI categories and outcomes, adjusting for individual characteristics. Results: Nearly three‐quarters (73.7%) of NHANES participants were OW or obese. Relative to Normal weight (NW), respondents with Class 3 obesity had more obesity‐related complications (2.07 vs. 4.62, p < 0.001). Higher BMI was associated with significantly lower HRQoL, lower productivity, and higher healthcare expenditures as well as more frequent weight loss attempts in the previous 12 months. Weight loss surgery and prescription anti‐obesity medications (AOMs) were used only by a very small proportion of individuals. Despite frequent weight loss attempts, most respondents did not achieve clinically meaningful weight loss. Conclusions: Adults with OW or obesity experienced worse clinical, economic and HRQoL outcomes than those with NW. Better use of evidence‐based obesity treatments, including prescription AOMs, should be considered to achieve more clinically meaningful weight reduction and improved outcomes in individuals with OW or obesity. [ABSTRACT FROM AUTHOR]

The assessment of cancer patient outcomes is important for any oncology departments. In head and neck cancer, not all patients are suitable for clinical studies. Unfortunately not all oncology centres are well resourced to undertake all available head and neck cancer trials. As a tertiary oncology unit with catchment radius of 50 miles and diverse patient demographics, it remains vital to assess outcomes of patients not included in formal studies. The aim of this study was to gather real world survival data of patients treated with definitive (chemo) radiotherapy. As standard of care, head and neck cancer patients are referred from 7 district general hospitals via 2 regional supra-multidisciplinary teams (sMDT). The data of patients demographics, and the clinical details of the head and neck cancer, are as routine collected prospectively for the institution electronic database. The date of disease recurrence on any patients is prospectively recorded at the sMDT. Non-HPV mucosal head and neck cancer patients who received definitive radiotherapy outside clinical trials between Jan 2018 and May 2022 were retrospectively reviewed. All advanced stage patients (Stages III & IVa/b) were considered concomitant chemotherapy. Radiotherapy volume quality assurance was standard prior to radiation [1]. HPV-mediated oropharynx patients, as well those treated with post-operative or adjuvant radiation, were excluded. The progression free survival (PFS) were calculated from the prospective database, and the overall survival (OS) retrospectively from the institution main death register. A total of 267 patients were identified: 122 (46%) Larynx, 68 (25%) p16- Oropharynx, 34 (13%) Hypopharynx, 33 (12%) Nasopharynx, and 10 (4%) Nasal Cavity/Paranasal sinus patients. In terms of UICC 8th edition staging, there were 33 Stage I (12%), 55 Stage II (21%), 71 Stage III (27%), and 108 Stage IVa/b (40%) cases across all tumour sites. The median age was 65 (range 58 - 72). The male to female ratio was 3.2 to 1. Ninety percent (n = 240) of the patients had performance status of 0 or 1. Majority of the patients (n = 209, 78%) had had exposure to tobacco: 122 (46%) ex-smokers and 87 (33%) current smokers. The median smoking pack years for the tobacco exposed patients was 30 (range 10 - 40). As for alcohol consumption, 130 (49%) patients consumed at least 14 units per week, with 30 (11%) being non-drinkers. All patients received 65Gy in 30 fractions (f) over 6 weeks, unless they were T1/2N0M0 glottic cancer for which they received 55Gy in 20f over 4 weeks. A total of 107 patients (40%) had at least 1 cycle of concomitant chemotherapy with their radiation. The median follow up was 3 years. Across all tumour sites, the 2 and 3 year PFS was 60% and 55% respectively, while the 2 and 3 year OS was 74% and 65% respectively. The OS probability according to the UICC staging across all disease sites is shown in Figure 1. For the Larynx subsite, there were 26 Stage I (21%), 30 Stage II (25%), 51 Stage III (42%), and 15 Stage IVa/b (12%) patients. The 2 and 3 year PFS for larynx patients were 70% and 65% respectively, with the 2 and 3 year OS being 82% and 75% respectively. For the p16- oropharynx cohort, there were 3 Stage I (4%), 12 Stage II (18%), 3 Stage III (4%), and 50 Stage IVa/b (74%) patients. In comparison to the larynx cohort, there were higher proportion of advanced stage patients in the Oropharynx cohort. As a result, the 2 and 3 year PFS for the p16-Oropharynx was 44% and 40% respectively, while the 2 and 3 year OS was 60% and 50% respectively. As for the hypopharynx group, there were no Stage I (0%) but 3 Stage II (9%), 8 Stage III (24%), and 23 Stage IVa/b (68%) cases. The 2 and 3 year PFS was 40% and 25% respectively, while the 2 and 3 year OS was 55% and 42% respectively. Separately, there were 2 Stage I (6%), 8 Stage II (24%), 8 Stage III (24%), and 15 Stage IVa (45%) Nasopharynx patients. The 2 and 3 year PFS for nasopharynx cohort was 75% and 60% respectively, with the 2 and 3 year OS being 78% and 70% respectively. [Display omitted] Despite varying tumour sites, the OS of patients overall corresponded to the UICC Stage of their disease, indicating the importance of accurate initial staging as part of prognostication. [ABSTRACT FROM AUTHOR]