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Abstract Traumatic brain injury (TBI) has been found to be associated with certain peripheral organ injuries; however, a few studies have explored the chronological influences of TBI on multiple organs and the systemic effects of therapeutic interventions. Particularly, high-mobility group box 1 (HMGB1) is a potential therapeutic target for TBI; however, its effects on peripheral organs remain unclear. Therefore, this study aimed to determine whether severe TBI can lead to multiple organ injury and how HMGB1 inhibition affects peripheral organs. This study used a weight drop-induced TBI mouse model and found that severe TBI can trigger short-lived systemic inflammation, in the lungs and liver, but not in the kidneys, regardless of the severity of the injury. TBI led to an increase in circulating HMGB1 and enhanced gene expressions of its receptors in every organ. Anti-HMGB1 antibody treatment reduced neuroinflammation but increased inflammation in peripheral organs. This study also found that HMGB1 inhibition appears to have a beneficial role in early neuroinflammation but could lead to detrimental effects on peripheral organs through decreased peripheral immune suppression. This study provides novel insights into the chronological changes in multiple organs due to TBI and the unique roles of HMGB1 between the brain and other organs.

Abstract The analysis of cells frozen within the International Space Station (ISS) will provide crucial insights into the impact of the space environment on cellular functions and properties. The objective of this study was to develop a method for cryopreserving blood cells under the specific constraints of the ISS. In a ground experiment, mouse blood was directly mixed with a cryoprotectant and gradually frozen at −80 °C. Thawing the frozen blood sample resulted in the successful recovery of viable mononuclear cells when using a mixed solution of dimethylsulfoxide and hydroxyethyl starch as a cryoprotectant. In addition, we developed new freezing cases to minimize storage space utilization within the ISS freezer. Finally, we confirmed the recovery of major mononuclear immune cell subsets from the cryopreserved blood cells through a high dimensional analysis of flow cytometric data using 13 cell surface markers. Consequently, this ground study lays the foundation for the cryopreservation of viable blood cells on the ISS, enabling their analysis upon return to Earth. The application of this method in ISS studies will contribute to understanding the impact of space environments on human cells. Moreover, this method may find application in the cryopreservation of blood cells in situations where research facilities are inadequate.

Abstract Sphingosine 1-phosphate receptor 1 (S1PR1), a G protein-coupled receptor, is required for lymphocyte trafficking, and is a promising therapeutic target in inflammatory diseases. Here, we synthesize a competitive S1PR1 antagonist, KSI-6666, that effectively suppresses pathogenic inflammation. Metadynamics simulations suggest that the interaction of KSI-6666 with a methionine residue Met124 in the ligand-binding pocket of S1PR1 may inhibit the dissociation of KSI-6666 from S1PR1. Consistently, in vitro functional and mutational analyses reveal that KSI-6666 causes pseudoirreversible inhibition of S1PR1, dependent on the Met124 of the protein and substituents on the distal benzene ring of KSI-6666. Moreover, in vivo study suggests that this pseudoirreversible inhibition is responsible for the persistent activity of KSI-6666.

Proportions of monomers in a copolymer will greatly affect the properties of materials. However, due to a phenomenon known as composition drift, the proportions of monomers in a copolymer can deviate from the value expected from the raw monomer ratio because of differences in monomer reactivity. It is therefore necessary to optimize the polymerization process to account for such composition drift. In the present study, styrene-methyl methacrylate copolymers were generated using a flow synthesis system and the processing variables were tuned employing Bayesian optimization (BO) to obtain a target composition. First trials of BO with generation of four candidate points per cycle, completed the optimization within five cycles. Subsequent Bayesian Optimization (BO) trial, using 40 points per cycle, identified several sets of processing conditions that could achieve the desired copolymer composition, accompanied by variations in other physical properties. To optimize the monomer composition ratio in the polymer, it was discovered from a data science perspective that the solvent-to-monomer ratio was as crucial as the styrene proportions. The role of each variable in the radical polymerization reaction was elucidated by assessing the extensive array of processing conditions while evaluating several broad trends. The proposed model confirms that specific monomer proportions can be produced in a copolymer using machine learning while investigating the reaction mechanism. In the future, the use of multi-objective BO to fine-tune the processing conditions is expected to allow optimization of the copolymer composition together with adjustment of physical properties.

Phenol, a corrosive aromatic compound, is used in many polymers and plastics for industrial purposes. It has previously been used as an antiseptic agent. Phenol burns are partially thick and may cause skin hyperpigmentation. Surgical intervention, including debridement, is often unnecessary. We report the case of a resin industrial worker who sustained phenol burns in both lower extremities due to a work accident. The estimated total body surface area (TBSA) was 11 %. His wound showed signs of epithelialization 7 days after the burn injury without debridement or skin grafting, with daily water irrigation and dressing alone. The patient was discharged from the hospital on day 23 after the accident with no residual organ damage or functional impairment. A conservative approach to phenol burns would be of great benefit to patients in terms of functional prognosis.

Abstract Autophagy is primarily activated by cellular stress, such as starvation or mitochondrial damage. However, stress-independent autophagy is activated by unclear mechanisms in several cell types, such as thymic epithelial cells (TECs). Here we report that the mitochondrial protein, C15ORF48, is a critical inducer of stress-independent autophagy. Mechanistically, C15ORF48 reduces the mitochondrial membrane potential and lowers intracellular ATP levels, thereby activating AMP-activated protein kinase and its downstream Unc-51-like kinase 1. Interestingly, C15ORF48-dependent induction of autophagy upregulates intracellular glutathione levels, promoting cell survival by reducing oxidative stress. Mice deficient in C15orf48 show a reduction in stress-independent autophagy in TECs, but not in typical starvation-induced autophagy in skeletal muscles. Moreover, C15orf48 –/– mice develop autoimmunity, which is consistent with the fact that the stress-independent autophagy in TECs is crucial for the thymic self-tolerance. These results suggest that C15ORF48 induces stress-independent autophagy, thereby regulating oxidative stress and self-tolerance.

Abstract A 62‐year‐old female experienced an extensive cerebral contusion in the left frontotemporal lobe due to an acute subdural hematoma at the age of 44 years. Six months after the injury, the patient developed epileptic seizures. The seizures were generalized with right cervical rotation and fencing posture. Despite prescriptions for four antiepileptic drugs, partial seizures occurred several times a month and focal to bilateral tonic‐clonic seizures once every 2 months. Video‐electroencephalography showed epileptic discharges in the left frontal lobe. The patient was subsequently referred to our department for palliative surgery. The patient underwent a left Forel‐H‐tomy. The prescription of antiepileptic drugs was not changed, and the patient was seizure free for 1 year. Forel‐H‐tomy, a surgical procedure for intractable epilepsy, was pioneered by Dennosuke Jinnai. Despite its previously reported remarkable efficacy, Forel‐H‐tomy has not been performed for several decades. Nevertheless, it remains a potential alternative treatment option for drug‐resistant epilepsy.

Purpose: Proximal tibial plateau/distal tibial rotational realignment, which is defined as tibial rotational realignment (TRR), is uncertain in open-wedge high tibial osteotomy (OWHTO). This study descriptively analysed TRR outliers in OWHTO, and also examined influence of TRR on the patellar cartilage at a 1-year postoperative examination. Methods: In total, 206 consecutive cases with computer-navigated OWHTO were reviewed. Patellar cartilage aggravation was evaluated in reference to the International Cartilage Repair Society grade (ICRS) at a 1-year postoperative arthroscopic view. Also, the lateral patella tilt correction and the Iwano classification deterioration grades were examined using axial radiographic views at a 1-year postoperative follow-up visit. Results: The TRR ranged from −12° (the distal tibia was externally rotated based on the proximal tibia) to 13° (internal rotation (IR): the distal tibia was internally rotated based on the proximal tibia) with mean 1.9° IR and standard deviation 5.4°. The inter-quantile range (IQR) was 8°, suggesting that there was no outlier in this cohort, (outliers were defined as either more than Q3+1.5IQR (upper limit: 18°), or Q1-1.5IQR (lower limit: −14°)). In univariate regression models, the TRR did not exhibit any significant influence to the patellar cartilage damage (odds ratio (OR) 1.047, 95% confidence interval (95%CI) 0.976–1.122), the patella tilt correction (OR 1.010, 95%CI 0.953–1.071), or the Iwano classification degradation scale (OR 1.041, 95%CI 0.971–1.116). Conclusion: We found no outlier in the TRR with OWHTO, and an insignificant negative impact of the TRR with OWHTO on the patellar cartilage in the 1-year follow-up examinations.

Abstract We propose a method to explore the flavor structure of quarks and leptons with reinforcement learning. As a concrete model, we utilize a basic value-based algorithm for models with U(1) flavor symmetry. By training neural networks on the U(1) charges of quarks and leptons, the agent finds 21 models to be consistent with experimentally measured masses and mixing angles of quarks and leptons. In particular, an intrinsic value of normal ordering tends to be larger than that of inverted ordering, and the normal ordering is well fitted with the current experimental data in contrast to the inverted ordering. A specific value of effective mass for the neutrinoless double beta decay and a sizable leptonic CP violation induced by an angular component of flavon field are predicted by autonomous behavior of the agent. Our finding results indicate that the reinforcement learning can be a new method for understanding the flavor structure.

Sixteen Meloidogyne isolates from tomato fields in California grown with resistant cultivars were multiplied on resistant tomato in a greenhouse. Of these resistance-breaking isolates, one was identified as M. javanica, and all others as M. incognita. The reproduction of the M. javanica isolate and four M. incognita isolates on six resistant tomato cultivars and on susceptible and resistant cultivars of pepper, sweetpotato, green bean, cotton, and cowpea was evaluated and compared to an avirulent M. incognita population in greenhouse pot trials. On resistant tomato cultivars, there were minor but significant differences between the resistance-breaking Meloidogyne isolates and between the different tomato cultivars. Of the other resistant crop cultivars, pepper was resistant to all isolates and green bean to all M. incognita isolates, while cotton and cowpea allowed reproduction of one of the resistance-breaking M. incognita isolates. The resistant sweetpotato cv. Bonita behaved like resistant tomato, allowing reproduction of all five resistance-breaking isolates but not of the avirulent M. incognita. Our results showed that variability exists among resistance-breaking Meloidogyne isolates, and that isolates overcoming resistance in tomato may also be virulent on resistant sweetpotato.

Abstract This cross-sectional study of 136 patients with chronic obstructive pulmonary disease (COPD) investigated the mechanism underlying overlap syndrome, defined as coexisting COPD and obstructive sleep apnea (OSA). OSA was defined as a respiratory event index (REI) ≥ 5 events/h, determined using type-3 portable monitors. The mean REI was 12.8 events/h. Most participants (60.1%) had mild OSA (REI: 5–15 events/h). The REI was positively correlated with forced expiratory volume in one second (%FEV1) (r = 0.33, p

Abstract Since the discovery of the quasicrystal, approximately 100 stable quasicrystals are identified. To date, the existence of quasicrystals is verified using transmission electron microscopy; however, this technique requires significantly more elaboration than rapid and automatic powder X‐ray diffraction. Therefore, to facilitate the search for novel quasicrystals, developing a rapid technique for phase‐identification from powder diffraction patterns is desirable. This paper reports the identification of a new Al–Si–Ru quasicrystal using deep learning technologies from multiphase powder patterns, from which it is difficult to discriminate the presence of quasicrystalline phases even for well‐trained human experts. Deep neural networks trained with artificially generated multiphase powder patterns determine the presence of quasicrystals with an accuracy >92% from actual powder patterns. Specifically, 440 powder patterns are screened using the trained classifier, from which the Al–Si–Ru quasicrystal is identified. This study demonstrates an excellent potential of deep learning to identify an unknown phase of a targeted structure from powder patterns even when existing in a multiphase sample.

Clinical trials of anti-CD19 chimeric antigen receptor T (CART19) cell therapy have shown high overall response rates in patients with relapsed/refractory B-cell malignancies. CART19 cell therapy has been approved by the US Food and Drug Administration for patients who relapsed less than 12 months after initial therapy or who are refractory to first-line therapy. However, durable remission of CART19 cell therapy is still lacking, and 30%–60% of patients will eventually relapse after CART19 infusion. In general, the prognosis of patients who relapse after CART19 cell therapy is poor, and various strategies to treat this patient population have been investigated extensively. CART19 failures can be broadly categorized by the emergence of either CD19-positive or CD19-negative lymphoma cells. If CD19 expression is preserved on the lymphoma cells, a second infusion of CART19 cells or reactivation of previously infused CART19 cells with immune checkpoint inhibitors can be considered. When patients develop CD19-negative relapse, targeting different antigens (e.g., CD20 or CD22) with CAR T cells, investigational chemotherapies, or hematopoietic stem cell transplantation are potential treatment options. However, salvage therapies for relapsed large B-cell lymphoma after CART19 cell therapy have not been fully explored and are conducted based on clinicians' case-by-case decisions. In this review, we will focus on salvage therapies reported to date and discuss the management of relapsed/refractory large B-cell lymphomas after CART19 cell therapy.

We conducted a subgroup analysis of a study on the long-term effects of COVID-19 (long COVID) in Japan to assess the effect of vaccination on long COVID symptoms. We assessed the clinical course of 111 patients with long COVID at the time of vaccination. The follow-up period was one year from the onset of COVID-19 or until the administration of the third vaccine dose. Of the 111 patients, 15 (13.5%) reported improvement, four (3.6%) reported deterioration, and 92 (82.9%) reported no change in their long COVID symptoms after vaccination. The most common long COVID symptoms before vaccination were alopecia, dyspnea, muscle weakness, fatigue, and headache among participants whose symptoms improved. Reduced dyspnea and alopecia were the most frequently reported improvements in symptoms after vaccination. Some symptoms persisted, including sleep disturbance, myalgia, and hypersensitivity. Vaccination did not appear to have a clinically important effect on patients with long COVID symptoms.

Abstract Background R gene-mediated resistance is one of the most effective mechanisms of immunity against pathogens in plants. To date some components that regulate the primary steps of plant immunity have been isolated, however, the molecular dissection of defense signaling downstream of the R proteins remains to be completed. In addition, R genes are known to be highly variable, however, the molecular mechanisms responsible for this variability remain obscure. Results To identify novel factors required for R gene-mediated resistance in rice, we used rice insertional mutant lines, induced by the endogenous retrotransposon Tos17, in a genetic screening involving the rice blast fungus Magnaporthe oryzae. We inoculated 41,119 mutant lines with the fungus using a high throughput procedure, and identified 86 mutant lines with diminished resistance. A genome analysis revealed that 72 of the 86 lines contained mutations in a gene encoding a nucleotide binding site (NBS) and leucine rich repeat (LRR) domain-containing (NBS-LRR) protein. A genetic complementation analysis and a pathogenesis assay demonstrated that this NBS-LRR gene encodes Pish, which confers resistance against races of M. oryzae containing avrPish. The other 14 lines have intact copies of the Pish gene, suggesting that they may contain mutations in the signaling components downstream of Pish. The genome analysis indicated that Pish and its neighboring three NBS-LRR genes are high similar to one another and are tandemly located. An in silico analysis of a Tos17 flanking sequence database revealed that this region is a "hot spot" for insertion. Intriguingly, the insertion sites are not distributed evenly among these four NBS-LRR genes, despite their similarity at the sequence and expression levels. Conclusions In this work we isolated the R gene Pish, and identified several other mutants involved in the signal transduction required for Pish-mediated resistance. These results indicate that our genetic approach is efficient and useful for unveiling novel aspects of defense signaling in rice. Furthermore, our data provide experimental evidence that R gene clusters have the potential to be highly preferred targets for transposable element insertions in plant genomes. Based on this finding, a possible mechanism underlying the high variability of R genes is discussed.

The thymus has the ability to regenerate from acute injury caused by radiation, infection, and stressors. In addition to thymocytes, thymic epithelial cells in the medulla (mTECs), which are crucial for T cell self-tolerance by ectopically expressing and presenting thousands of tissue-specific antigens (TSAs), are damaged by these insults and recover thereafter. However, given recent discoveries on the high heterogeneity of mTECs, it remains to be determined whether the frequency and properties of mTEC subsets are restored during thymic recovery from radiation damage. Here we demonstrate that acute total body irradiation with a sublethal dose induces aftereffects on heterogeneity and gene expression of mTECs. Single-cell RNA-sequencing (scRNA-seq) analysis showed that irradiation reduces the frequency of mTECs expressing AIRE, which is a critical regulator of TSA expression, 15 days after irradiation. In contrast, transit-amplifying mTECs (TA-mTECs), which are progenitors of AIRE-expressing mTECs, and Ccl21a-expressing mTECs, were less affected. Interestingly, a detailed analysis of scRNA-seq data suggested that the proportion of a unique mTEC cluster expressing Ccl25 and a high level of TSAs was severely decreased by irradiation. In sum, we propose that the effects of acute irradiation disrupt the heterogeneity and properties of mTECs over an extended period, which potentially leads to an impairment of thymic T cell selection.

Abstract Activity cliffs (AC) are formed by pairs of structural analogues that are active against the same target but have a large difference in potency. While much of our knowledge about ACs has originated from the analysis and comparison of compounds and activity data, several studies have reported AC predictions over the past decade. Different from typical compound classification tasks, AC predictions must be carried out at the level of compound pairs representing ACs or nonACs. Most AC predictions reported so far have focused on individual methods or comparisons of two or three approaches and only investigated a few compound activity classes (from 2 to 10). Although promising prediction accuracy has been reported in most cases, different system set-ups, AC definitions, methods, and calculation conditions were used, precluding direct comparisons of these studies. Therefore, we have carried out a large-scale AC prediction campaign across 100 activity classes comparing machine learning methods of greatly varying complexity, ranging from pair-based nearest neighbor classifiers and decision tree or kernel methods to deep neural networks. The results of our systematic predictions revealed the level of accuracy that can be expected for AC predictions across many different compound classes. In addition, prediction accuracy did not scale with methodological complexity but was significantly influenced by memorization of compounds shared by different ACs or nonACs. In many instances, limited training data were sufficient for building accurate models using different methods and there was no detectable advantage of deep learning over simpler approaches for AC prediction. On a global scale, support vector machine models performed best, by only small margins compared to others including simple nearest neighbor classifiers. Graphical Abstract