Biological neurons act as generalization filters in reservoir computing

Reservoir computing is a machine learning paradigm that transforms the transient dynamics of high-dimensional nonlinear systems for processing time-series data. Although reservoir computing was initially proposed to model information processing in the mammalian cortex, it remains unclear how the non-random network architecture, such as the modular architecture, in the cortex integrates with the biophysics of living neurons to characterize the function of biological neuronal networks (BNNs). Here, we used optogenetics and fluorescent calcium imaging to record the multicellular responses of cultured BNNs and employed the reservoir computing framework to decode their computational capabilities. Micropatterned substrates were used to embed the modular architecture in the BNNs. We first show that modular BNNs can be used to classify static input patterns with a linear decoder and that the modularity of the BNNs positively correlates with the classification accuracy. We then used a timer task to verify that BNNs possess a short-term memory of ~1 s and finally show that this property can be exploited for spoken digit classification. Interestingly, BNN-based reservoirs allow transfer learning, wherein a network trained on one dataset can be used to classify separate datasets of the same category. Such classification was not possible when the input patterns were directly decoded by a linear decoder, suggesting that BNNs act as a generalization filter to improve reservoir computing performance. Our findings pave the way toward a mechanistic understanding of information processing within BNNs and, simultaneously, build future expectations toward the realization of physical reservoir computing systems based on BNNs.Comment: 31 pages, 5 figures, 3 supplementary figure

Improved Recovery of Exfoliated Colonocytes from Feces Using Newly Developed Immunomagnetic Beads

We demonstrated the feasibility of a new methodology for isolating colonocytes from feces. To reduce costs and improve the recovery rate of colonocytes from feces, we attempted to develop new immunomagnetic beads. Several sizes of magnetic beads were prepared and tagged with a monoclonal antibody against EpCAM. We made several new monoclonal antibodies against EpCAM, and each monoclonal antibody was tagged to the magnetic beads. In the simulation, the most efficient recovery of HT-29 cells was obtained using the smallest size of beads. Also, beads tagged with a monoclonal antibody with a higher affinity against EpCAM had a higher recovery rate. Similar results were obtained when the smallest size of beads with the highest-affinity monoclonal antibody was applied to clinical samples. The newly developed immunomagnetic beads may be useful for isolating colorectal cancer cells from feces, enabling the cytological or molecular biological diagnosis of CRC

End-to-End Joint Target and Non-Target Speakers ASR

This paper proposes a novel automatic speech recognition (ASR) system that can transcribe individual speaker's speech while identifying whether they are target or non-target speakers from multi-talker overlapped speech. Target-speaker ASR systems are a promising way to only transcribe a target speaker's speech by enrolling the target speaker's information. However, in conversational ASR applications, transcribing both the target speaker's speech and non-target speakers' ones is often required to understand interactive information. To naturally consider both target and non-target speakers in a single ASR model, our idea is to extend autoregressive modeling-based multi-talker ASR systems to utilize the enrollment speech of the target speaker. Our proposed ASR is performed by recursively generating both textual tokens and tokens that represent target or non-target speakers. Our experiments demonstrate the effectiveness of our proposed method.Comment: Accepted at Interspeech 202

Theory of orbital state and spin interactions in ferromagnetic titanates

A spin-orbital superexchange Hamiltonian in a Mott insulator with $t_{2g}$ orbital degeneracy is investigated. More specifically, we focus on a spin ferromagnetic state of the model and study a collective behavior of orbital angular momentum. Orbital order in the model occurs in a nontrivial way -- it is stabilized exclusively by quantum effects through the order-from-disorder mechanism. Several energetically equivalent orbital orderings are identified. Some of them are specified by a quadrupole ordering and have no unquenched angular momentum at low energy. Other states correspond to a noncollinear ordering of the orbital angular momentum and show the magnetic Bragg peaks at specific positions. Order parameters are unusually small because of strong quantum fluctuations. Orbital contribution to the resonant x-ray scattering is discussed. The dynamical magnetic structure factor in different ordered states is calculated. Predictions made should help to observe elementary excitations of orbitals and also to identify the type of the orbital order in ferromagnetic titanates. Including further a relativistic spin-orbital coupling, we derive an effective low-energy spin Hamiltonian and calculate a spin-wave spectrum, which is in good agreement with recent experimental observations in YTiO$_3$.Comment: 25 pages, 17 figure

胃がん患者における嗅覚変化が胃切除後の体重減少に与える影響

Patients undergoing gastrectomy for gastric cancer may experience alterations in olfaction, yet the association between olfactory changes and postoperative weight loss remains uncertain. This study aimed to elucidate the relationship between olfactory changes and postoperative weight loss in patients with gastric cancer. Patients who underwent radical gastrectomy for gastric cancer between February 2022 and August 2022 were included in the study. Those experiencing a higher Visual Analog Scale (VAS) score postoperatively compared to preoperatively were deemed to have undergone olfactory changes. Postoperative weight loss was determined using the 75th percentile as a cutoff value, designating patients surpassing this threshold as experiencing significant weight loss. Multivariate logistic regression analysis was employed to identify risk factors for postoperative weight loss, with statistical significance set at p < 0.05. Out of 58 patients, 10 (17.2%) exhibited olfactory changes. The rate of postoperative weight loss at one month was markedly higher in the group with olfactory changes compared to those without (9.6% versus 6.2%, respectively; p = 0.002). In addition, the group experiencing olfactory changes demonstrated significantly lower energy intake compared to the group without such changes (1050 kcal versus 1250 kcal, respectively; p = 0.029). Logistic regression analysis revealed olfactory changes as an independent risk factor for significant weight loss at one month postoperatively (odds ratio: 7.64, 95% confidence interval: 1.09–71.85, p = 0.048). In conclusion, olfactory changes emerged as an independent risk factor for postoperative weight loss at one month in patients with gastric cancer following gastrectomy

Spinless impurities and Kondo-like behavior in strongly correlated electron systems

We investigate magnetic properties induced by a spinless impurity in strongly correlated electron systems, i.e. the Hubbard model in the spatial dimension $D=1,2,$ and 3. For the 1D system exploiting the Bethe ansatz exact solution we find that the spin susceptibility and the local density of states in the vicinity of a spinless impurity show divergent behaviors. The results imply that the induced local moment is not completely quenched at any finite temperatures. On the other hand, the spin lattice relaxation rate obtained by bosonization and boundary conformal field theory satisfies a relation analogous to the Korringa law, $1/T_1T \sim \chi^2$. In the 2D and 3D systems, the analysis based upon the antiferromagnetically correlated Fermi liquid theory reveals that the antiferromagnetic spin fluctuation developed in the bulk is much suppressed in the vicinity of a spinless impurity, and thus magnetic properties are governed by the induced local moment, which leads to the Korringa law of $1/T_1$.Comment: 9pages,1figure, final version accepted for publication in Phys.Rev.B(Jan2001

Molecular Mechanism Responsible for Fibronectin-controlled Alterations in Matrix Stiffness in Advanced Chronic Liver Fibrogenesis

Fibrosis is characterized by extracellular matrix (ECM) remodeling and stiffening. However, the functional contribution of tissue stiffening to noncancer pathogenesis remains largely unknown. Fibronectin (Fn) is an ECM glycoprotein substantially expressed during tissue repair. Here we show in advanced chronic liver fibrogenesis using a mouse model lacking Fn that, unexpectedly, Fn-null livers lead to more extensive liver cirrhosis, which is accompanied by increased liver matrix stiffness and deteriorated hepatic functions. Furthermore, Fn-null livers exhibit more myofibroblast phenotypes and accumulate highly disorganized/diffuse collagenous ECM networks composed of thinner and significantly increased number of collagen fibrils during advanced chronic liver damage. Mechanistically, mutant livers show elevated local TGF-β activity and lysyl oxidase expressions. A significant amount of active lysyl oxidase is released in Fn-null hepatic stellate cells in response to TGF-β1 through canonical and noncanonical Smad such as PI3 kinase-mediated pathways. TGF-β1-induced collagen fibril stiffness in Fn-null hepatic stellate cells is significantly higher compared with wild-type cells. Inhibition of lysyl oxidase significantly reduces collagen fibril stiffness, and treatment of Fn recovers collagen fibril stiffness to wild-type levels. Thus, our findings indicate an indispensable role for Fn in chronic liver fibrosis/cirrhosis in negatively regulating TGF-β bioavailability, which in turn modulates ECM remodeling and stiffening and consequently preserves adult organ functions. Furthermore, this regulatory mechanism by Fn could be translated for a potential therapeutic target in a broader variety of chronic fibrotic diseases