THQ San Diego (formerly known as Midway Studios San Diego) was a game developer based in San Diego, California. It was the successor to Leland Corporation.
The development of neurocognitive biomarkers for schizophrenia (SCZ) has relied on lengthy test batteries that are infeasible to deploy in clinical settings. Using machine learning, we sought to identify a subset of neurocognitive domains that could distinguish between patients with SCZ and healthy comparison subjects (HCS). Leveraging data from 559 patients with SCZ or schizoaffective disorder and 745 HCS who completed 15 neurocognitive assessments spanning a diverse range of neurocognitive domains, we developed a machine learning model that could accurately separate SCZ from HCS (area under the receiver operating characteristic curve of 0.899), and was replicated in an independent cohort. Recursive feature elimination revealed that just two neurocognitive domains—verbal learning and emotion identification—were sufficient to achieve the same classification accuracy. These findings support a ‘less-is-more’ approach to efficient neurocognitive profiling across the schizophreniform spectrum and highlight what may be the most impaired neurocognitive domains in this debilitating disorder. This study identifies key neurocognitive domains that distinguish patients with schizophrenia from healthy individuals using machine learning. Analyzing data from 1,304 participants, it demonstrates that verbal learning and emotion identification effectively classify conditions, promoting efficient neurocognitive profiling strategies.
Blind structured illumination microscopy (blind-SIM) is a valuable tool for achieving super-resolution without the need for known illumination patterns. However, in its current formulation the algorithm requires many iterations to converge, leading to long inference times and limited use for real-time or video-rate imaging. We present unrolled blind-SIM (UBSIM), an algorithm which integrates a learnable neural network inside the unrolled iterations of the blind-SIM algorithm. UBSIM delivers a reconstruction speed two to three orders of magnitude faster than that of current iterative blind-SIM methods, while achieving similar resolution and image quality. Furthermore, we demonstrate that UBSIM can be trained in an unsupervised manner that reduces hallucinations and produces superior generalization capability when compared to benchmark super-resolution networks. We test UBSIM experimentally on live cells and present video-rate super-resolution imaging up to 50 Hz. Using our method, we observe dynamic remodeling of the endoplasmic reticulum with high spatiotemporal resolution. Burns et al. introduce an unrolled, physics-informed machine learning method that speeds up blind structured illumination microscopy by orders of magnitude while preserving generalizability, enabling real-time superresolution imaging in live cells.
The architecture of actin networks at the cell surface is regulated by local membrane topology. However, how actin nucleation can respond sensitively to the degree of membrane curvature remains incompletely understood. Using nanolithography to precisely control local membrane curvature, we reconstituted the dynamic interplay of the tri-component Cdc42/FBP17/N-WASP system on a series of deformed membrane sites, resulting in differential actin nucleation. We found that high-curvature sensing is primarily mediated by FBP17 through its intrinsic BAR-domain activity, which then induces the hierarchical assembly of FBP17/N-WASP clusters to activate N-WASP in synergy with Cdc42. This nucleation boost is fine-tuned by modulating the FBP17-to-N-WASP stoichiometry within multivalent macromolecular assemblies according to local curvature radii. At lower-curvature regions, Cdc42 enhances basal FBP17 recruitment to the membrane, enabling detection of shallow curvatures and initiating actin polymerization before high-curvature effects dominate. This establishes a dynamic, curvature radius-dependent cooperativity that links geometric cues to the regulation of actin polymerization, highlighting their interplay in coordinating membrane and actin morphodynamics during complex cellular processes.
Intercellular mitochondria transfer is an evolutionarily conserved process in which one cell delivers some of their mitochondria to another cell in the absence of cell division. This process has diverse functions depending on the cell types involved and physiological or disease context. Although mitochondria transfer was first shown to provide metabolic support to acceptor cells, recent studies have revealed diverse functions of mitochondria transfer, including, but not limited to, the maintenance of mitochondria quality of the donor cell and the regulation of tissue homeostasis and remodelling. Many mitochondria-transfer mechanisms have been described using a variety of names, generating confusion about mitochondria transfer biology. Furthermore, several therapeutic approaches involving mitochondria-transfer biology have emerged, including mitochondria transplantation and cellular engineering using isolated mitochondria. In this Consensus Statement, we define relevant terminology and propose a nomenclature framework to describe mitochondria transfer and transplantation as a foundation for further development by the community as this dynamic field of research continues to evolve. This Consensus Statement provides a nomenclature framework and experimental recommendations for studying mitochondrial transfer and transplantation.
The dry-process is a sustainable and promising fabrication method for all-solid-state batteries by eliminating solvents. However, a pragmatic fabrication design for thin and robust solid-state electrolyte (SSE) layers has not been established. Herein, we report a dry-process approach that enhances mechanical stability of SSE layers from film fabrication to cell operation. By co-rolling thick SSE and positive electrode feeds, a uniform, thin SSE layer (50 µm) and a high loading positive electrode layer (5 mAh cm-2) with high active material ratio (80 wt%) are simultaneously achieved. This SSE-positive electrode integrated film exhibits enhanced physical properties and cyclability (> 80% retention after 500 cycles) at low stack pressure (2 MPa) compared to the freestanding counterparts, attributed to reinforced and intimate SSE-positive electrode interface constructed during co-rolling process. Additionally, an all-solid-state pouch cell with high stack-level specific energy (310 Wh kg-1) and energy density (805 Wh L-1) operating at 30 °C and 5 MPa is demonstrated.
