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"Abe, M."
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Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors
Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present an avenue for further investigation. This study employed advanced machine learning techniques to classify major depressive disorders based on clinical indicators and mitochondrial oxidative stress markers. Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. Results indicate promising accuracy and precision, particularly with Random Forest on balanced data. RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. Including only oxidative stress markers resulted in accuracy and an F1 score of 79.52% and 80.56%, respectively. Notably, including mitochondrial peptides alongside clinical factors significantly enhances predictive capability, shedding light on the interplay between depression severity and mitochondrial oxidative stress pathways. These findings underscore the potential for machine learning models to aid clinical assessment, particularly in individuals with comorbid conditions such as hypertension, diabetes mellitus, and cardiovascular disease.
Journal Article
Incipient Space Weathering Observed on the Surface of Itokawa Dust Particles
The reflectance spectra of the most abundant meteorites, ordinary chondrites, are different from those of the abundant S-type (mnemonic for siliceous) asteroids. This discrepancy has been thought to be due to space weathering, which is an alteration of the surfaces of airless bodies exposed to the space environment. Here we report evidence of space weathering on particles returned from the S-type asteroid 25143 Itokawa by the Hayabusa spacecraft. Surface modification was found in 5 out of 10 particles, which varies depending on mineral species. Sulfur-bearing Fe-rich nanoparticles exist in a thin (5 to 15 nanometers) surface layer on olivine, low-Ca pyroxene, and plagioclase, which is suggestive of vapor deposition. Sulfur-free Fe-rich nanoparticles exist deeper inside (<60 nanometers) ferromagnesian silicates. Their texture suggests formation by metamictization and in situ reduction of Fe2+.
Journal Article
Touchdown of the Hayabusa Spacecraft at the Muses Sea on Itokawa
After global observations of asteroid 25143 Itokawa by the Hayabusa spacecraft, we selected the smooth terrain of the Muses Sea for two touchdowns carried out on 19 and 25 November 2005 UTC for the first asteroid sample collection with an impact sampling mechanism. Here, we report initial findings about geological features, surface condition, regolith grain size, compositional variation, and constraints on the physical properties of this site by using both scientific and housekeeping data during the descent sequence of the first touchdown. Close-up images revealed the first touchdown site as a regolith field densely filled with size-sorted, millimeter- to centimeter-sized grains.
Journal Article
Monolithic Multi Degree of Freedom (MDoF) Capacitive MEMS Accelerometers
With the continuous advancements in microelectromechanical systems (MEMS) fabrication technology, inertial sensors like accelerometers and gyroscopes can be designed and manufactured with smaller footprint and lower power consumption. In the literature, there are several reported accelerometer designs based on MEMS technology and utilizing various transductions like capacitive, piezoelectric, optical, thermal, among several others. In particular, capacitive accelerometers are the most popular and highly researched due to several advantages like high sensitivity, low noise, low temperature sensitivity, linearity, and small footprint. Accelerometers can be designed to sense acceleration in all the three directions (X, Y, and Z-axis). Single-axis accelerometers are the most common and are often integrated orthogonally and combined as multiple-degree-of-freedom (MDoF) packages for sensing acceleration in the three directions. This type of MDoF increases the overall device footprint and cost. It also causes calibration errors and may require expensive compensations. Another type of MDoF accelerometers is based on monolithic integration and is proving to be effective in solving the footprint and calibration problems. There are mainly two classes of such monolithic MDoF accelerometers, depending on the number of proof masses used. The first class uses multiple proof masses with the main advantage being zero calibration issues. The second class uses a single proof mass, which results in compact device with a reduced noise floor. The latter class, however, suffers from high cross-axis sensitivity. It also requires very innovative layout designs, owing to the complicated mechanical structures and electrical contact placement. The performance complications due to nonlinearity, post fabrication process, and readout electronics affects both classes of accelerometers. In order to effectively compare them, we have used metrics such as sensitivity per unit area and noise-area product. This paper is devoted to an in-depth review of monolithic multi-axis capacitive MEMS accelerometers, including a detailed analysis of recent advancements aimed at solving their problems such as size, noise floor, cross-axis sensitivity, and process aware modeling.
Journal Article
Small LEA proteins mitigate air-water interface damage to fragile cryo-EM samples during plunge freezing
Air-water interface (AWI) interactions during cryo-electron microscopy (cryo-EM) sample preparation cause significant sample loss, hindering structural biology research. Organisms like nematodes and tardigrades produce Late Embryogenesis Abundant (LEA) proteins to withstand desiccation stress. Here we show that these LEA proteins, when used as additives during plunge freezing, effectively mitigate AWI damage to fragile multi-subunit molecular samples. The resulting high-resolution cryo-EM maps are comparable to or better than those obtained using existing AWI damage mitigation methods. Cryogenic electron tomography reveals that particles are localized at specific interfaces, suggesting LEA proteins form a barrier at the AWI. This interaction may explain the observed sample-dependent preferred orientation of particles. LEA proteins offer a simple, cost-effective, and adaptable approach for cryo-EM structural biologists to overcome AWI-related sample damage, potentially revitalizing challenging projects and advancing the field of structural biology.
Cryo-EM faces a problem of sample damage at the air-water interface. In this work, the authors show that stress-response proteins from dehydration-tolerant organisms can be used as a simple sample additive to mitigate the sample damage problem.
Journal Article
Comparative study of physico-chemical properties of some molecules from Khaya Grandifoliola plant
The three molecular compounds: A (17-epi-methyl-6-hydroxylangolensate), B (7-deacetoxy-7-oxogedunin) and C (7-deacetoxy-7R-hydroxygedunin) isolated from
Khaya Grandifoliola
, a plant of the Meliaceae family, able to protect the normal human hepatocyte cell line against paracetamol-induced hepatotoxicity were studied using HF and DFT methods. It appears from this study that compound A has the greatest capacity of donating charges while compound B, which is the most reactive compound according to the HOMO-LUMO energy gap, has a greater capacity to accept charges. From the calculation of certain donor-acceptor parameters, it comes out that compound C is the most easily oxidizable substance and therefore the most effective free radical scavenger. Of the three molecular compounds, A is the best antioxidant while B is the best antireductant. From the values obtained for compounds A, B and C, we concluded that these compounds are better antioxidants than β-carotene and better antireductants than vitamins A, C and E. Compounds A, B, and C are less efficient electron acceptors than fluorine and more efficient electron donors than Na. The calculation of certain thermodynamic parameters shows that, the molecular compounds studied can easily bind to a biomolecular complex. UV-vis spectrum analysis shows that the maximum peaks are located in the UV region between 230 and 356 nm. The nonlinear optical parameters along with vibrational frequencies of these compounds were calculated and compared.
Journal Article
Microplastics pollution in the river Karnaphuli: a preliminary study on a tidal confluence river in the southeast coast of Bangladesh
Bangladesh is a deltaic country in Asia, and its riverine systems ultimately drain into the Bay of Bengal. Plastic is a severe environmental issue for coastal-marine ecosystems due to the indiscriminate usage and discarding of plastic items in the upstream river that eventually find their route into the Bay of Bengal. Microplastics (MPs) are widespread pollutants in almost all environmental compartments, including aquatic environments. This study aimed to quantify and understand the distribution of microplastics in surface water and sediments of the river Karnaphuli, a tidal confluence river adjacent to the Chattogram seaport city of Bangladesh, a highly inhabited and industrial area on the southeast coast of the Bay of Bengal. A manta trawl net (300-µm mesh size) was used to collect surface water samples, while an Ekman dredge was used to collect sediment samples. The concentrations of microplastics in the surface water of the river Karnaphuli during late monsoon, winter, and early summer were recorded to be 120,111.11, 152,222.22, and 164,444.44 items/km
2
, respectively, while in sediments, those were recorded to be 103.83, 137.50, and 103.67 items/kg, respectively. A higher abundance of microplastics was observed in downstream surface water (228,888.88 items/km
2
) and sediments (164.17 items/kg). Smaller sizes (0.3 to 0.5 mm) of microplastics were predominant, fibers or threads were the frequent types, and black was the most common color in the river Karnaphuli. The Fourier transform infrared analysis revealed that polyethylene terephthalate (surface water: 22%, sediments: 19%), polyamide (surface water: 15%, sediments: 13%), polyethylene (surface water: 12%, sediments: 18%), polystyrene (surface water: 13%, sediments: 11%), and alkyd resin (surface water: 13%, sediments: 10%) were the most prevalent polymers in the river Karnaphuli. Moreover, there was a moderate positive correlation between MPs abundance in surface water and sediments. Therefore, improved long-term research (in different seasons with horizontal and vertical monitoring) is necessary in order to accurately determine the flux of microplastics from the river Karnaphuli to the Bay of Bengal.
Journal Article
In-ear EEG wearables for brain activity assessment and cognitive rehabilitation: the emerging role of multimodal embedded intelligence
This literature review critically examines the design, validation, and application of non-invasive in-ear electroencephalography (ear-EEG) systems as emerging wearable platforms for long-term neurophysiological monitoring and intervention. Following PRISMA guidelines, studies published between 2010 and 2025 were systematically selected from four major databases and organized into four thematic domains: in-ear wearable system design and validation, multimodal sensing and stimulation, embedded intelligence, and brain-state monitoring and rehabilitation. The review focuses exclusively on wearable, ear-centered EEG technologies, explicitly excluding cochlear implants and other invasive or behind-the-ear systems. We analyze key engineering challenges unique to ear-EEG, including electrode placement constraints, mechanical–electrical coupling, motion robustness, power efficiency, and long-term wearability. The review highlights a growing transition toward compact, wireless ear-EEG systems with on-device signal processing and embedded machine learning, enabling real-time brain-state estimation under ambulatory conditions. Multimodal integration, combining ear-EEG with complementary sensors such as EOG, inertial units, and cardiovascular signals is shown to improve artifact awareness, contextual interpretation, and closed-loop capability. Beyond summarizing existing technologies, this review identifies critical gaps limiting clinical translation, including the lack of standardized validation protocols, limited embedded autonomy, and underexplored closed-loop neurofeedback and neuromodulation architectures. By synthesizing advances across hardware design, signal processing, and intelligent system integration, this work provides a systems-level roadmap for the future development of wearable, intelligent, and clinically robust ear-EEG platforms for mental health, neurorehabilitation, and continuous brain monitoring.
Journal Article
Diverse Localization Patterns of an R-Type Lectin in Marine Annelids
Lectins facilitate cell–cell contact and are critical in many cellular processes. Studying lectins may help us understand the mechanisms underlying tissue regeneration. We investigated the localization of an R-type lectin in a marine annelid (Perinereis sp.) with remarkable tissue regeneration abilities. Perinereis nuntia lectin (PnL), a galactose-binding lectin with repeating Gln-X-Trp motifs, is derived from the ricin B-chain. An antiserum was raised against PnL to specifically detect a 32-kDa lectin in the crude extracts from homogenized lugworms. The antiserum detected PnL in the epidermis, setae, oblique muscle, acicula, nerve cord, and nephridium of the annelid. Some of these tissues and organs also produced Galactose (Gal) or N-acetylgalactosamine (GalNAc), which was detected by fluorescent-labeled plant lectin. These results indicated that the PnL was produced in the tissues originating from the endoderm, mesoderm, and ectoderm. Besides, the localizing pattern of PnL partially merged with the binding pattern of a fluorescent-labeled mushroom lectin that binds to Gal and GalNAc. It suggested that PnL co-localized with galactose-containing glycans in Annelid tissue; this might be the reason PnL needed to be extracted with haptenic sugar, such as d-galactose, in the buffer. Furthermore, we found that a fluorescein isothiocyanate-labeled Gal/GalNAc-binding mushroom lectin binding pattern in the annelid tissue overlapped with the localizing pattern of PnL. These findings suggest that lectin functions by interacting with Gal-containing glycoconjugates in the tissues.
Journal Article