Search

Bronchiolitis obliterans syndrome (BOS) is a chronic complication following lung transplantation that limits the long-term survival. Although the enhancer of zeste homolog 2 (EZH2) is involved in post-transplantation rejection, its involvement in BOS pathogenesis remains unclear. We aimed to investigate the therapeutic potential of EZH2 inhibition in BOS. 3-deazaneplanocin A (DZNep) was administered intraperitoneally to heterotopic tracheal transplant recipient model mice. Tracheal allografts were obtained on days 7, 14, 21, and 28 after transplantation. The obstruction ratios of the DZNep and control groups on days 7, 14, 21, and 28 were 15.1% ± 0.8% vs. 20.4% ± 3.6% (p = 0.996), 16.9% ± 2.1% vs. 67.7% ± 11.5% (p < 0.001), 47.8% ± 7.8% vs. 92.2% ± 5.4% (p < 0.001), and 60.0% ± 9.6% vs. 95.0% ± 2.3% (p < 0.001), respectively. The levels of interleukin (IL)-6 and interferon-γ on day 7 and those of IL-2, tumor necrosis factor, and IL-17A on days 14, 21, and 28 were significantly reduced following DZNep treatment. DZNep significantly decreased the number of infiltrating T-cells on day 14. In conclusion, DZNep-mediated EZH2 inhibition suppressed the inflammatory reactions driven by pro-inflammatory cytokines and T cell infiltration, thereby alleviating BOS symptoms.

Objective: Oncological feasibility of segmentectomy for internal non–small cell lung cancer (NSCLC) has not been assessed adequately. We assessed the oncological feasibility of segmentectomy for inner-located NSCLC by investigating surgical margins and patient prognosis after undergoing the procedure. Methods: Of the 3555 patients who underwent resection for lung cancer between 2013 and 2019 at our institution, 659 patients who underwent segmentectomy for clinical stage 0 to stage1A NSCLC were included in this study. Patients were separated into 2 groups according to whether the tumor was in the inner or outer third of the lung area. Clinical characteristics and prognoses were retrospectively compared between the groups. Results: Of the included 659 cases, 183 (27.8%) were inner-located, and 476 (72.2%) had outer-located NSCLC. The surgical margin was significantly shorter in the inner-located group than in the outer group (median, 16 vs 25 mm; P

Abstract As plant distribution and performance are determined by both environmental and genetic factors, clarifying the contribution of these two factors is a key for understanding plant adaptation and predicting their distribution under ongoing global warming. Betula ermanii is an ideal species for such research because of its wide distribution across diverse environments. Stomatal density and size are crucial traits that plants undergo changes in to adapt to different environments as these traits directly influence plant photosynthesis and transpiration. In this study, we conducted a multi‐location common garden experiment using B. ermanii to (1) clarify the contribution of both environmental and genetic factors to the variation in stomatal density and size of B. ermanii, (2) demonstrate the differences in the plasticity of stomatal density and size among B. ermanii populations, and (3) understand how stomatal density and size of B. ermanii would respond to increased temperature and changing precipitation patterns. Genetic factors played a more significant role in stomatal size than environmental factors, suggesting that B. ermanii struggles to adjust its stomatal size in response to a changing environment. Our results also revealed a positive correlation between stomatal size plasticity and original habitat suitability, indicating that in B. ermanii populations in harsh environments exhibit lower adaptability to environmental shifts. Although stomatal density and size of B. ermanii showed the significant responses to increased temperature and shifting precipitation patterns, the response ranges of stomatal density and size to the environmental factors varied among populations. Our findings highlighted the interplay between genetic and environmental factors in determining the intraspecific variation in stomatal density and size in B. ermanii. This indicated that certain populations of B. ermanii exhibit limited stomatal plasticity and adaptability, which could directly affect photosynthesis and transpiration, suggesting potential population‐specific fitness implications for B. ermanii under future climate change.

Polyploidy is thought to enable species diversification and adaptation to extreme environments. Resolving the ecological differences between a taxon's ploidy levels would therefore provide important insights into local adaptation and speciation. The genus Betula includes many polyploids, but estimates of their phylogenetic relationships and evolutionary history are uncertain because of cryptic lineages and species. As one of the southern boundary populations of Betula ermanii in Japan has been shown to have distinctive genetic characteristics and traits, the differences in ploidy levels between three southern boundary and various other Japanese B. ermanii populations were investigated using flow cytometry. Leaf and seed morphologies were also compared. Apart from individuals in southern boundary populations, all those sampled were tetraploid. Individuals from the southern boundary populations were mostly diploid, apart from a few from lower altitude Shikoku populations, which were tetraploid. Leaf and seed morphologies differed between tetraploids and diploids. Diploid individuals were characterized by leaves with a heart-shaped base and many leaf teeth, and seeds with relatively longer wings. The diploid populations could be considered a cryptic relict lineage of B. ermanii, and there is a possibility that this lineage is a diploid ancestor of B. ermanii and a relict population of the Sohayaki element. Further investigation of the Japanese Betula phylogenetic relationships would enable an informed discussion of taxonomic revisions.

Recoverin is a neuron-specific calcium-binding protein that is mainly located in the retina and pineal gland. Few reports have described patients with anti-recoverin antibody-positive encephalitis, and no cases of psychosis associated with this encephalitis have been reported. We report a patient with anti-recoverin antibody-positive encephalitis with Cotard and Capgras delusions who was successfully treated with electroconvulsive therapy (ECT). The patient was a 25-year-old woman. She exhibited disorientation, executive function deficits, tremors in the upper limbs, generalized athetoid-like involuntary movements, hallucinations, incontinence, and fever, which led to her admission to our hospital. Upon admission, she complained of Cotard delusions. Various diagnostic tests, including cerebrospinal fluid analysis, antibody screening, and brain imaging, were unremarkable, except for positivity for serum anti-recoverin antibodies, non-specific general slowing on electroencephalography and decreased regional cerebral blood flow (rCBF) in the frontal and occipital lobes, and increased rCBF in the basal ganglia and pons on single-photon emission computed tomography. She was eventually diagnosed with encephalitis positive for anti-recoverin antibodies and treated with immunoglobulins and steroids. Her neurological symptoms improved temporarily, but three months later, psychiatric symptoms, i.e., suicidal thoughts and Cotard and Capgras delusions, were exaggerated. After ECT, her condition significantly improved. In conclusion, the present report suggests that pineal gland dysfunction due to anti-recoverin antibody or its cross-reactivity with neuron-specific calcium-binding proteins may contribute to the neuropsychiatric symptoms observed in anti-recoverin antibody-positive encephalitis and that ECT can be a viable treatment option if immunotherapy proves ineffective. Additionally, decreased rCBF in the prefrontal cortex may be associated with the clinical features of Capgras and Cotard delusions.

Abstract Background We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10−4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10−4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10−3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10−8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10−5). Conclusions Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

Abstract The Harrow, Hassidim, Lloyd (HHL) algorithm, known as the pioneering algorithm for solving linear equations in quantum computers, is expected to accelerate solving large-scale linear ordinary differential equations (ODEs). To efficiently combine classical and quantum computers for high-cost chemical problems, non-linear ODEs (e.g., chemical reactions) must be linearized to the highest possible accuracy. However, the linearization approach has not been fully established yet. In this study, Carleman linearization was examined to transform nonlinear first-order ODEs of chemical reactions into linear ODEs. Although this linearization theoretically requires the generation of an infinite matrix, the original nonlinear equations can be reconstructed. For the practical use, the linearized system should be truncated with finite size and the extent of the truncation determines analysis precision. Matrix should be sufficiently large so that the precision is satisfied because quantum computers can treat such huge matrix. Our method was applied to a one-variable nonlinear $$\dot{y}=-{y}^{2}$$ y ˙ = - y 2 system to investigate the effect of truncation orders and time step sizes on the computational error. Subsequently, two zero-dimensional homogeneous ignition problems for H2–air and CH4–air gas mixtures were solved. The results revealed that the proposed method could accurately reproduce reference data. Furthermore, an increase in the truncation order improved accuracy with large time-step sizes. Thus, our approach can provide accurate numerical simulations rapidly for complex combustion systems.

Purpose: During radiation therapy for head and neck cancer using volumetric modulated arc therapy, excessive dosing or underdosing occurs as a result of the decrease in tumor volume and changes in body weight. Adaptive radiation therapy (ART) is performed when significant changes are observed; however, the decision to implement ART depends on the oncologist's subjective judgment. The purpose of this study was to present objective indicators for ART and develop a program to predict the need for ART. Methods and Materials: The study included 47 patients in the non-ART group and 21 patients in the ART group with shape changes. Patients who received ART could not be covered with the prescribed radiation therapy dose due to shape changes. For each patient, 1112 6-dimensional lists were created, including the number of irradiations, amount of change in the clinical target volume (CTV), rate of change in CTV, mean oral cavity dose, age, and body mass index. Support vector machine and k-nearest neighbor were used for machine learning. The random number of test data to be extracted varied from 1 to 9, and a mean accuracy score was calculated. These programs could predict the need for ART if the accuracy score was high. Results: The classification accuracy of the list, including the amount of change in the CTV and rate of change in CTV up to 20 fractions, was 0.963 and 0.967 for support vector machine and k-nearest neighbor, respectively. Conclusions: This program predicted the need for ART with more than 90% accuracy based on shape changes over time in cone beam computed tomography analysis for up to 20 fractions. This may provide significant support for objective decisions to implement ART based on the amount of change over time during treatment.

Island ecosystems are thought to be hotspots of biodiversity but are also susceptible to invasion by alien species. Sado Island in Japan is a habitat for endemic and rare species, such as the endemic Sado wrinkled frog. However, two alien frog species, Bufo japonicus formosus and Lithobates catesbeianus, which have been introduced to the island are threatening the biodiversity of the island and their distribution information is lacking. In this study, we conducted a distribution survey of B. japonicus and L. catesbeianus over Sado Island and predicted their current and future potential distributions using a species distribution model. We found that B. japonicus currently inhabits the southwestern part of the island near its introduction point and is in the process of expansion. Meanwhile, L. catesbeianus has a wider distribution range than B. japonicus and is almost expanding throughout most of its potential suitable habitat. We predict that, in the future, B. japonicus will expand their distribution to the southeastern part of the island. These findings show that it is necessary for B. japonicus to prevent their expansion into further area and L. catesbeianus to reduce the population, considering their distribution status.

An in-silico tool with peak deconvolution for preparative chromatograms was developed for assessing the robustness for peak fluctuations depending on loaded sample quality. The peak positions of high-molecular-weight species (HMWS), target monoclonal antibody (Main), and low-molecular-weight species (LMWS) on a chromatogram of cation-exchange chromatography (CEX) were identified by second derivative processing. The deconvoluted peaks of HWMS, Main, and LMWS were calculated by a fitting algorithm at each identified peak position. The height of deconvolved peaks of each component was varied to mimic the change of loaded sample quality in the chromatogram, and the quality of the pooled fraction obtained from the mimic chromatogram was estimated. In addition, the relationship between the loaded sample quality and the pooled sample quality was shown to evaluate the robustness of chromatographic purification process for peak fluctuations depending on loaded sample quality. A major advantage of this robustness assessment method is to be performed using the results of only a single wet-lab experiment. We considered that it is a useful in-silico tool for rapidly assessing chromatography robustness and also product quality depending on upstream process required to achieve the target quality in the pooled fraction, at the early stage of biological pharmaceutical product development, especially monoclonal antibodies

Monitoring structural integrity has been demanded to achieve a sustainable society against disasters, including seismic and extreme wind events, and thus Structural Health Monitoring (SHM) system is one of the significant technologies. The natural frequency and the yield displacement of structures will be the significant damage indices to assess the structural integrity. However, they would contain variances to the design values. The structural integrity assessments using the SHM should allow for the uncertainties in structural specifications, such as the yield displacement, to improve the assessment accuracy. Additionally, the earthquake ground motion will have uncertainties regarding the acceleration levels, spectral characteristics, and others. These uncertainties can lead to assessment difficulty, reducing the accuracy of the assessment. The authors propose the method using the deep Convolutional Neural Network to overcome this problem. This method using CNN has two features. The first is to suggest using the response spectra as the training data of CNN. The second is to create a simple CNN architecture with a high classifier accuracy using Bayesian optimization. This paper demonstrates that the image features detected by CNN enable us to accurately assess the structural integrity even when uncertainties in structural specifications and seismic motions are superimposed.

Abstract Background The purpose of this study was to determine the potential of escalated dose radiation (EDR) robust intensity-modulated proton radiotherapy (ro-IMPT) in reducing GI toxicity risk in locally advanced unresectable pancreatic cancer (LAUPC) of the head in term of normal tissue complication probability (NTCP) predictive model. Methods For 9 patients, intensity-modulated radiotherapy (IMRT) was compared with ro-IMPT. For all plans, the prescription dose was 59.4GyE (Gray equivalent) in 33 fractions with an equivalent organ at risk (OAR) constraints. Physical dose distribution was evaluated. GI toxicity risk for different endpoints was estimated using published NTCP Lyman Kutcher Burman (LKB) models for stomach, duodenum, small bowel, and combine stomach and duodenum (Stoduo). A Wilcoxon signed-rank test was used for dosimetry parameters and NTCP values comparison. Result The dosimetric results have shown that, with similar target coverage, ro-IMPT achieves a significant dose-volume reduction in the stomach, small bowel, and stoduo in low to high dose range in comparison to IMRT. NTCP evaluation for the endpoint gastric bleeding of stomach (10.55% vs. 13.97%, P = 0.007), duodenum (1.87% vs. 5.02%, P = 0.004), and stoduo (5.67% vs. 7.81%, P = 0.008) suggest reduced toxicity by ro-IMPT compared to IMRT. ∆NTCP IMRT – ro-IMPT (using parameter from Pan et al. for gastric bleed) of ≥5 to 1) with endpoint grade ≥ 3 GI toxicity (using parameters from Holyoake et al.). Conclusion With similar target coverage and better conformity, ro-IMPT has the potential to substantially reduce the risk of GI toxicity compared to IMRT in EDR of LAUPC of the head. This result needs to be further evaluated in future clinical studies.

Background: Radiobiological model-based studies of photon-modulated radiotherapy for pancreatic cancer have reported reduced gastrointestinal (GI) toxicity, although the risk is still high. The purpose of this study was to investigate the potential of 3D-passive scattering proton beam therapy (3D-PSPBT) in limiting GI organ at risk (OAR) toxicity in localized pancreatic cancer based on dosimetric data and the normal tissue complication probability (NTCP) model.Methods: The data of 24 pancreatic cancer patients were retrospectively analyzed, and these patients were planned with intensity-modulated radiotherapy (IMRT), volume-modulated arc therapy (VMAT), and 3D-PSPBT. The tumor was targeted without elective nodal coverage. All generated plans consisted of a 50.4-GyE (Gray equivalent) dose in 28 fractions with equivalent OAR constraints, and they were normalized to cover 50% of the planning treatment volume (PTV) with 100% of the prescription dose. Physical dose distributions were evaluated. GI-OAR toxicity risk for different endpoints was estimated by using published NTCP Lyman–Kutcher–Burman (LKB) models. Analysis of variance (ANOVA) was performed to compare the dosimetric data, and ΔNTCPIMRT−PSPBT and ΔNTCPVMAT−PSPBT were also computed.Results: Similar homogeneity and conformity for the clinical target volume (CTV) and PTV were exhibited by all three planning techniques (P > 0.05). 3D-PSPBT resulted in a significant dose reduction for GI-OARs in both the low-intermediate dose range (below 30 GyE) and the highest dose region (Dmax and V50 GyE) in comparison with IMRT and VMAT (P < 0.05). Based on the NTCP evaluation, the NTCP reduction for GI-OARs by 3D-PSPBT was minimal in comparison with IMRT and VMAT.Conclusion: 3D-PSPBT results in minimal NTCP reduction and has less potential to substantially reduce the toxicity risk of upper GI bleeding, ulceration, obstruction, and perforation endpoints compared to IMRT and VMAT. 3D-PSPBT may have the potential to reduce acute dose-limiting toxicity in the form of nausea, vomiting, and diarrhea by reducing the GI-OAR treated volume in the low-to-intermediate dose range. However, this result needs to be further evaluated in future clinical studies.

Inflammatory biomarkers have been associated with clinical outcomes in non-small cell lung cancer (NSCLC). However, the best prognostic marker(s) has not been identified, and the association between inflammatory markers and clinical characteristics is poorly understood. We selected 1,237 patients with resected NSCLC from Kyushu University (2003-2015) and Kyushu Cancer Center (2009-2015) in Japan. Pearson product-moment correlation coefficient among inflammatory markers and area under curve (AUC) of receiver operating characteristic (ROC) curve analyses for overall survival (OS) were calculated. We analyzed the associations between inflammatory markers and clinical factors using Student's t-test. Univariate and multivariate analyses with Cox proportional hazards regression analyses were performed to evaluate the relationship between survival and clinical factors. The cut-off values for neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-lymphocyte ratio, and derived NLR (dNLR) were determined by ROC curve analyses for OS. We found a strong positive correlation between NLR and dNLR (r = 0.9629). The AUC of LMR was the highest amongst the measured metrics, and the AUC of NLR was higher than dNLR. Levels of some inflammatory markers were associated with sex, smoking, squamous cell carcinoma, and pathological stage. LMR ≥ 5.11 and lactate dehydrogenase (LDH) concentration ≥ 222 (U/L) were independent predictors of both disease-free survival (DFS) and OS (LMR; P = 0.0009 and 0.0008, LDH; P = 0.0195 and 0.0187, respectively). Certain inflammatory markers, potentially linked to smoking, were associated with an advanced pathological stage in NSCLC. LMR and LDH were independent predictors of both DFS and OS.

Abstract The aim of this study was to elucidate the relationship between family‐associated factors and the postoperative prognosis in patients with nonsmall cell lung cancer (NSCLC). Additionally, we investigated whether having children was associated with the postoperative maintenance of the nutritional status. We selected 438 NSCLC patients who had undergone curative lung resection between 2004 and 2011 at Kyushu University (Fukuoka, Japan), whose family‐associated factors were available. Nutritional indices, including the prognostic nutritional index (PNI), were used to estimate the change in the nutritional status for 1 year after surgery. A propensity score analysis was conducted after adjusting the following variables: sex, age, smoking history, performance status, pathological stage, and histological type. Three hundred patients (68.5%) had both children and partners. Forty‐nine patients (11.2%) only had children, and 56 (12.8%) patients only had a partner. Thirty‐three patients (7.5%) did not have a partner or children. The overall survival (OS) and disease‐free survival (DFS) of the partner‐present and partner‐absent patients did not differ to a statistically significant extent (P = .862 and P = .712, respectively). However, childless patients showed significantly shorter OS and DFS in comparison with patients with children (P = .005 and P = .002, respectively). The postoperative exacerbation of PNI was significantly greater in childless patients than in patients with children (P = .003). These results remained after propensity score matching. Childless patients had a significantly poorer postoperative prognosis than those with children. Surgeons caring for childless NSCLC patients should be aware of the poorer postoperative outcomes in this population.

Much of the data produced and consumed by students, teachers, and educational managers is in textual format. Text Mining (TM) and Natural Language Processing (NLP) have been applied in the educational context in different ways. Ideally, such applications combine computational, linguistic, pedagogical, and psychological aspects. This article aims to gather and analyze scientific publications that have applied TM and NLP techniques in textual corpora from distance-higher education through a Systematic Literature Review. Eight scientific databases were searched (ACM DL, Scopus, Web of Science, IEEE Xplore, ArXiv, SpringerLink, ScienceDirect, and ERIC), and publications from 2017 to 2021 were selected. 718 unique publications were screened to identify primary research capable of characterizing this scientific area. 52 resulting publications were fully analyzed, and some consolidated results include: 38% of works had the professors as end users, followed by students (27%) and managers (25%); the English language was present in 50% of publications, followed by the Portuguese language (13,5%) and others languages; the text mining tasks most used were text classification (27%), sentiment analysis (17%), information extraction (15%), chatbot (15%) and topic modeling (13%); LDA (Latent Dirichlet Analysis) was the technique most used (19%); the Python language was the programming language most prevalent (42%), and 54% of works do not mention any educational construct or theory. Thus, this article presents an unprecedented overview of the field of Educational Text Mining (ETM) in distance higher education and analyses the main results obtained, aiming for future research in the area.

ObjectivesEpithelial-mesenchymal transition (EMT) and the histone methyltransferase Enhancer of Zeste Homologue 2 (EZH2) are important regulators of lung cancer progression and metastasis. Although recent studies support the correlation between EZH2 expression and EMT, no reports have investigated their association using immunohistochemistry or explored their prognostic impact on lung adenocarcinoma. The aim of this study was to elucidate the association between EZH2 and EMT, and their prognostic significance.MethodsEZH2 and the EMT markers E-cadherin and Vimentin were examined by IHC in lung adenocarcinoma specimens that were resected from 2003-2012. Associations between EZH2 and EMT markers and their correlations with survival were analyzed.ResultsWe enrolled 350 patients, approximately 70% of whom were diagnosed as pathological stage I. The rates of positive E-cadherin, Vimentin, and EZH2 expression were 60.3%, 21.4%, and 52.0%, respectively. There was a significant positive correlation between EZH2 and Vimentin expression (p = 0.008), and EZH2 scores were higher in the Mesenchymal group (p = 0.030). In multivariate analysis, EZH2 was an independent predictor of Vimentin expression, and vice versa. EMT and EZH2 overexpression were significantly correlated with poor disease-free and overall survival. Furthermore, the Epithelial group with high EZH2 expression had significantly worse disease-free and overall survival. Positive staining for EMT markers was unfavorable regarding disease-free survival among patients with low EZH2 expression.ConclusionsEMT and high EZH2 expression were associated with poor NSCLC prognoses. Vimentin is a key factor linking EMT and EZH2 in lung adenocarcinoma.

During learning, synaptic connections between excitatory neurons in the brain display considerable dynamism, with new connections being added and old connections eliminated. Synapse elimination offers an opportunity to understand the features of synapses that the brain deems dispensable. However, with limited observations of synaptic activity and plasticity in vivo, the features of synapses subjected to elimination remain poorly understood. Here, we examined the functional basis of synapse elimination in the apical dendrites of L2/3 neurons in the primary motor cortex throughout motor learning. We found no evidence that synapse elimination is facilitated by a lack of activity or other local forms of plasticity. Instead, eliminated synapses display asynchronous activity with nearby synapses, suggesting that functional synaptic clustering is a critical component of synapse survival. In addition, eliminated synapses show delayed activity timing with respect to postsynaptic output. Thus, synaptic inputs that fail to be co-active with their neighboring synapses or are mistimed with neuronal output are targeted for elimination.

Experience-dependent gene expression reshapes neural circuits, permitting the learning of knowledge and skills. Most learning involves repetitive experiences during which neurons undergo multiple stages of functional and structural plasticity. Currently, the diversity of transcriptional responses underlying dynamic plasticity during repetition-based learning is poorly understood. To close this gap, we analyzed single-nucleus transcriptomes of L2/3 glutamatergic neurons of the primary motor cortex after 3 d motor skill training or home cage control in water-restricted male mice. Train and control neurons could be discriminated with high accuracy based on expression patterns of many genes, indicating that recent experience leaves a widespread transcriptional signature across L2/3 neurons. These discriminating genes exhibited divergent modes of coregulation, differentiating neurons into discrete clusters of transcriptional states. Several states showed gene expressions associated with activity-dependent plasticity. Some of these states were also prominent in the previously published reference, suggesting that they represent both spontaneous and task-related plasticity events. Markedly, however, two states were unique to our dataset. The first state, further enriched by motor training, showed gene expression suggestive of late-stage plasticity with repeated activation, which is suitable for expected emergent neuronal ensembles that stably retain motor learning. The second state, equally found in both train and control mice, showed elevated levels of metabolic pathways and norepinephrine sensitivity, suggesting a response to common experiences specific to our experimental conditions, such as water restriction or circadian rhythm. Together, we uncovered divergent transcriptional responses across L2/3 neurons, each potentially linked with distinct features of repetition-based motor learning such as plasticity, memory, and motivation.

Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10-8 and 4.3 × 10-7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.