CK Hutchison (China)

Background: Post-traumatic stress disorder (PTSD) is associated with impaired fear extinction and synaptic loss in prefrontal–limbic circuits. Converging evidence implicates glutamatergic dysfunction in these deficits, yet the genetic architecture underlying glutamatergic involvement in PTSD remains incompletely understood. Methods: We applied MAGMA gene-based and competitive gene-set analyses to the largest PTSD GWAS to date (European ancestry, effective N = 638,463; Nievergelt et al., 2024). We tested prespecified gene sets including ionotropic glutamate receptor subunits (AMPA, NMDA, kainate), downstream plasticity mediators, metabolic enzymes (e.g., CYP2D6), and negative control sets (monoaminergic and housekeeping genes). Partitioned heritability was used to assess enrichment of PTSD common-variant risk in functional categories. Results: Genome-wide significant association was observed at GRIA1 (GluA1 AMPA subunit; Z = 5.78, p = 3.77 × 10⁻⁹). Partitioned heritability revealed strong enrichment for AMPA/kainate receptors (enrichment ratio = 1.36, p ≈ 10⁻¹³), NMDA receptor subunits (ratio = 1.25, p ≈ 10⁻⁷), and metabolic enzymes including CYP2D6 (ratio = 2.08, p ≈ 10⁻⁵). A broader glutamate/plasticity gene set (n = 130) showed modest but significant enrichment (mean Z = 1.013 vs genome-wide 0.780; p = 0.024, FDR = 0.048). Negative control sets were not enriched. Conclusion: Common genetic risk for PTSD is disproportionately localized to genes encoding AMPA and NMDA receptor subunits and related metabolic enzymes. These findings provide robust genetic support for glutamatergic mechanisms in PTSD pathophysiology and highlight ionotropic glutamate receptors as promising therapeutic targets for future investigation.

Obsessive-compulsive disorder (OCD) remains treatment-resistant in 40–60 % of patients despite optimised serotonin-reuptake inhibitor therapy and antipsychotic augmentation. Emerging evidence points to glutamatergic dysregulation in cortico-striato-thalamo-cortical circuits as a core driver of rigid, maladaptive synaptic patterns. The Cheung Glutamatergic Regimen (CGR)—a fully oral, low-cost combination of dextromethorphan (NMDA antagonism), a CYP2D6 inhibitor (to prolong DXM exposure), piracetam (AMPA positive allosteric modulation), and optional L-glutamine (glutamate replenishment)—aims to replicate the rapid neuroplastic cascade triggered by intravenous ketamine. Naturalistic case series and individual reports from routine practice describe rapid reductions in obsessive intensity and ritual frequency, often within days to weeks, particularly when CYP2D6 inhibition is sustained and piracetam is added. Most side effects are mild, like temporary tremors, fast heartbeats, and trouble sleeping. However, serotonin toxicity and hypomanic activation need close monitoring. The evidence is uncontrolled and only based on one clinician's experience, though it is promising.

Cognitive impairment—rather than psychosis or mood instability—often drives long-term disability in schizoaffective disorder, yet current antipsychotic and mood-stabilising regimens offer little relief. We describe a 22-year-old man with schizoaffective disorder, bipolar type, whose persistent "brain fog" jeopardised university graduation despite euthymic mood and quiescent psychosis on lurasidone, olanzapine, and valproate. A mechanistically guided add-on protocol was introduced: Deanxit (flupentixol 0.5 mg + melitracen 10 mg once-daily) to provide mild serotonin–noradrenaline enhancement and moderate CYP2D6 inhibition; dextromethorphan 15 mg twice-daily to deliver gentle, σ₁-supported NMDA antagonism; and piracetam 600 mg twice-daily as a positive allosteric modulator of AMPA receptors. Within two weeks the patient reported clearer thinking and sustained reading; family noted coherent conversation and fewer attentional lapses. By six weeks he completed all coursework, passed mid-term examinations, and maintained social engagement—improvements never achieved with previous therapy. Benefits have persisted for three months with no mood destabilisation, psychotic relapse, or significant side-effects apart from transient nausea. We propose that melitracen's CYP2D6 blockade prolonged dextromethorphan exposure, enabling a steady NMDA "priming" signal, while piracetam amplified downstream AMPA throughput to consolidate synaptic plasticity. This case highlights the potential of inexpensive, orally available agents to target the NMDA–AMPA axis and alleviate the cognitive burden of schizoaffective disorder. Controlled trials are warranted.

Background: Eye-tracking systems and gaze targets provide effective immobilization of the eye during ocular radiation therapy treatment. This study proposes a compact-sized eye-tracking system with a gaze target to provide a simple setup in a ring gantry LINAC. The device should have accurate repositioning, while the gaze target should be easily interchangeable.Methods: A compact-sized camera was mounted on a 3D-printed stand integrated with a gaze target. The gaze target can be fixed in different positions using an indexed-positioning system. The repositioning accuracy of this system was evaluated using Computed Tomography (CT) scans. The iris center position of the eye phantom was detected using fast radial symmetry transform. The iris center shift in the camera plane was converted to the 3D absolute displacement using the approximation of the spherical rotation of the eye globe. The tolerance of iris motion from gazing toward the gaze target in the camera plane can be estimated with prior knowledge of the iris center location when gazing toward the camera. The detection accuracy was evaluated on a motorized spherical eye phantom.Results: The mean repositioning errors of the camera and the gaze target were 0.18 mm (Range: 0.08-0.36 mm) and 0.31 mm (Range: 0.03-0.56 mm), respectively. For a typical distance of 200 mm from the camera to the tracked eye, the largest absolute error of iris center detection on a motorized spherical eye phantom was 0.08 mm, while the mean absolute error was less than the resolution of one pixel.Conclusions: This study proposed a compact-sized eye-tracking system with a gaze target with an easily reproducible setup. By converting the displacement of the motorized eye phantom iris center location in the camera plane to 3D coordinate displacement, accurate tolerance of the gaze direction of the eye can be achieved.

Abstract Gastric cancer (GC) incidence rates are amongst the highest in Asian countries including; China, Japan and Korea(1). 5-year survival rates in early stage disease have improved through aggressive combinations of surgery and chemo/radiotherapy. In late stage disease however, despite Her2 molecular segmentation and trastuzumab therapy, prognosis remains dismal and novel therapeutic options are urgently required(2). The MET oncogene encodes the receptor tyrosine kinase for hepatocyte growth factor and controls genetic programs leading to cell growth, invasion and survival. Dysregulation of MET signaling is a common feature of a diverse range of human tumor types and thus represents a highly competitive and attractive therapeutic target. Volitinib (HMPL-504) is an orally bioavailable, highly selective and potent small molecule ATP-competitive inhibitor, which inhibits cMET autophosphorylation and downstream signaling (3). Volitinib is currently in Phase I clinical development. To evaluate the utility of volitinib in treating patients with GC, we established the incidence of cMET amplification and overexpression and attempted to correlate this with response to volitinib in primary GC tumor models. Elevated cMET gene copy number (amplification 5%, high polysomy 13%), and protein overexpression (12%, cases > IHC 2+, 16% > IHC1+) were detected in a cohort of 217 Chinese GC samples using fluorescent in situ hybridization (FISH) and immunohistochemical (IHC) approaches. In vitro proliferation assays were performed on a panel of 26 GC cell lines and profound sensitivity to volitinib was demonstrated in lines harboring elevated cMET gene copy number (GI50 range 6 to 49nM). In the cMET amplified GC xenograft model, Hs746t, once-daily oral dosing of volitinib (2.5mg/kg) elicited potent anti-tumour activity at well-tolerated doses (97% tumour growth inhibition after 16 days dosing, P<0.0001) which correlated well with pharmacodynamic modulation of phospho-cMET signaling. To strengthen the translational relevance of these data, a panel of cMET amplified primary GC models were identified and established. In these models, volitinib demonstrated potent tumor growth inhibition or regressions (90% and 84% TGI at 10mg/kg/qd, all P<0.0001), correlated with pharmacodynamic modulation of tumor phospho-cMET. In contrast, 10mg/kg/qd volitinib was inactive (18% TGI, P=0.2405) in a cMET non-amplified control model. We also evaluated the activity of volitinib in combination with docetaxel, a standard of care chemotherapeutic commonly used in the treatment of gastric cancer. In model Hs746t, volitinib demonstrated additive benefit when used with docetaxel at well tolerated doses. These data support the potential clinical utility of volitinib as a selective agent for the therapeutic treatment of gastric cancers harboring dysregulated cMET signaling. Citation Format: Paul R. Gavine, Shiming Fan, Haihua Fu, Lu Han, Yuan Jie Liu, Jing Lv, Weiguo Qing, Yongxin Ren, Weiguo Su, Xinying Su, Huiying Wang, Liang Xie, Shirlian Xu, Wen Xu, XiaoLu Yin, Yongjuan Yu, Tianwei Zhang, Q.May Wang. Volitinib (HMPL504), a novel, selective and potent cMET inhibitor, is efficacious in primary tumor models of cMET-driven gastric cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 928. doi:10.1158/1538-7445.AM2013-928

The Computational Fluid Dynamics (CFD) techniques are currently widely adopted to simulate the behaviour of fire. The major shortcoming of the CFD is the requirements of extensive computer storage and lengthy computational time. In actual applications, although comprehensive field information of velocities, temperature, pressure, fraction of different constitutes etc. can be obtained from the CFD simulation, the user may be only interested in few important parameters which index the performance of the compartment design in the event of fire. Height of thermal interface (HTI) is one of the key indices. It is the average height above the floor level inside the fire compartment at which the temperature gradient is the highest. In practice, the fire compartment is considered untenable when the HTI descends lower than the respiratory level of the occupants. In the course of fire system design optimization, if the resultant HTI of a fire compartment design evaluated by the CFD is too low, another set of the design parameters (e.g. width of the door opening) are required to be tried. This trial and error exercise continues until a close optimum set of the design parameter achieved. This approach is theoretically feasible but requires lengthy computational time. This paper proposes to apply Artificial Neural Network (ANN) approach as a fast alternative to the CFD models to simulate the behaviour of the compartment fire. A novel ANN model denoted as GRNNFA has been developed particular for fire studies. It is a hybrid ANN model combining the General Regression Neural Network (GRNN) and the Fuzzy ART (FA). The GRNNFA model owns the features of incremental growth of network structure, stable learning and removal of the noise embedded in the experimental fire data. It has been employed to establish a system response surface based on the knowledge of the available training samples. Since the available training samples may not be sufficient to describe the system behaviour especially for fire data, it is proposed to acquire extra knowledge of the system from human expert knowledge. The human expert intervened network training was developed to remedy the established system response surface. After the transformation of the remedied system response surface to the problem domain, Genetic Algorithm (GA) is applied to evaluate the close optimum set of the design parameters.