Browse Articles
Discover research articles across all indexed journals
Impact of rhizobacterial inoculation in plant growth medium to mitigate lead stress in Tomato (Solanum lycopersicum L.)
Allocentric and egocentric spatial representations coexist in rodent medial entorhinal cortex
Parkinson’s disease screening using a fusion of gait point cloud and silhouette features
Parkinson’s Disease (PD) is a neurodegenerative disorder that is often accompanied by slowness of movement (bradykinesia) or gradual reduction in the frequency and amplitude of repetitive movement (hypokinesia). There is currently no cure for PD, but early detection and treatment can slow down its progression and lead to better treatment outcomes. Vision-based approaches have been proposed for the early detection of PD using gait. Gait can be captured using appearance-based or model-based approaches. Although appearance-based gait contains comprehensive features, it is easily affected by factors such as dressing. On the other hand, model-based gait is robust against changes in dressing and external contours, but it is often too sparse to contain sufficient information. Therefore, we propose a fusion of appearance-based and model-based gait features for PD prediction. First, we extracted keypoint coordinates from gait captured in videos and modeled these keypoints as a point cloud. The silhouette images are also segmented from the videos to obtain an overall appearance representation of the subject. We then perform a binary classification of gait as normal or Parkinsonian using a novel fusion of the gait point cloud and silhouette features, obtaining AUC up to 0.87 and F1-Scores up to 0.82 (precision: 0.85, recall: 0.80).
Tandospirone prevents anesthetic-induced respiratory depression through 5-HT1A receptor activation in rats
A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause
Exploring data literacy self-perception among Indonesian high school students
Data is becoming increasingly ubiquitous today, and data literacy has emerged an essential skill in the workplace. Therefore, it is necessary to equip high school students with data literacy skills in order to prepare them for further learning and future employment. In Indonesia, there is a growing shift towards integrating data literacy in the high school curriculum. As part of a pilot intervention project, academics from two leading Universities organised data literacy boot camps for high school students across various cities in Indonesia. The boot camps aimed at increasing participants’ awareness of the power of analytical and exploration skills, which in turn, would contribute to creating independent and data-literate students. This paper explores student participants’ self-perception of their data literacy as a result of the skills acquired from the boot camps. Qualitative and quantitative data were collected through student surveys and a focus group discussion, and were used to analyse student perception post-intervention. The findings indicate that students became more aware of the usefulness of data literacy and its application in future studies and work after participating in the boot camp. Of the materials delivered at the boot camps, students found the greatest benefit in learning basic statistical concepts and applying them through the use of Microsoft Excel as a tool for basic data analysis. These findings provide valuable policy recommendations that educators and policymakers can use as guidelines for effective data literacy teaching in high schools.
Addressing inter individual variability in CSF levels of brain derived proteins across neurodegenerative diseases
AbstractAccurate diagnosis and monitoring of neurodegenerative diseases require reliable biomarkers. Cerebrospinal fluid (CSF) proteins are promising candidates for reflecting brain pathology; however, their diagnostic utility may be compromised by natural variability between individuals, weakening their association with disease. Here, we measured the levels of 69 pre-selected proteins in cerebrospinal fluid using antibody-based suspension bead array technology in a multi-disease cohort of 499 individuals with neurodegenerative disorders including Alzheimer’s disease (AD), behavioral variant frontotemporal dementia, primary progressive aphasias, amyotrophic lateral sclerosis (ALS), corticobasal syndrome, primary supranuclear palsy, along with healthy controls. We identify significant inter-individual variability in overall CSF levels of brain-derived proteins, which could not be attributed to specific disease associations. Using linear modelling, we show that adjusting for median CSF levels of brain-derived proteins increases the diagnostic accuracy of proteins previously identified as altered in CSF in the context of neurodegenerative disorders. We further demonstrate a simplified approach for the adjustment using pairs of correlated proteins with opposite alteration in the diseases. With this approach, the proteins adjust for each other and further increase the biomarker performance through additive effect. When comparing the diseases, two proteins—neurofilament medium and myelin basic protein—showed increased levels in ALS compared to other diseases, and neurogranin showed a specific increase in AD. Several other proteins showed similar trends across the studied diseases, indicating that these proteins likely reflect shared processes related to neurodegeneration. Overall, our findings suggest that accounting for inter-individual variability is crucial in future studies to improve the identification and performance of relevant biomarkers. Importantly, we highlight the need for multi-disease studies to identify disease-specific biomarkers.
Review on natural hydrogen wells safety
A new extended Chen distribution for modelling COVID-19 data
In this paper, we propose a new flexible statistical distribution, the Topp-Leone Exponentiated Chen distribution, to model real-world data effectively, with a particular focus on COVID-19 data. The motivation behind this study is the need for a more flexible distribution that can capture various hazard rate shapes (e.g., increasing, decreasing, bathtub) and provide better fitting performance compared to existing models such as the Chen and exponentiated Chen distributions. The principal results include the derivation of key statistical properties such as the probability density function, cumulative distribution function, moments, hazard rate function, and order statistics. Maximum likelihood estimation is employed to estimate the parameters of the TLEC distribution, and simulation studies demonstrate the efficiency of the maximum likelihood method. The innovation of this work is further validated by applying the TLEC distribution to real COVID-19 data, where it outperforms several related models. The study concludes with significant insights into how the TLEC distribution provides a more accurate and flexible approach to modeling real-world phenomena.
Accelerated aging modulates the toxicological properties of the diazo tattoo pigment PO13
Ionizable polymeric micelles (IPMs) for efficient siRNA delivery
Factors associated with adherence to antiretroviral therapy among HIV-positive adolescents and young adult patients attending HIV care and treatment clinic at Bombo Hospital in Tanga region-Tanzania
Background Adherence to HIV treatment regimens involves the consistent and correct intake of all prescribed medications. The implementation of antiretroviral therapy (ART) program has significantly reduced mortality among adolescents living with HIV. However, adherence to ART is lower among adolescents compared to other sub-populations and even lower in sub-Saharan Africa. The factors influencing ART adherence are context-specific and vary across countries and regions. In the Tanzanian context, there is a paucity of data regarding these factors. Methodology This cross-sectional study involved 385 adolescents and young adults living with HIV receiving treatment at Bombo Hospital Referral Hospital’s Care and Treatment Clinic, in Tanga, Tanzania. To assess adherence, a one-month self-recall medication adherence scale was used while a structured questionnaire was used to gather data on determinants of adherence. Data were collected using Google Forms and subsequently exported as a Microsoft Excel file. The data were then entered into Stata software version 15 for cleaning for descriptive and logistic regression analyses. Results More than a third (35.3%) of adolescents and young adults living with HIV in Tanga were not adherent to the effective and available ART. Adolescents and young adults living in households experiencing moderate food insecurity were 67% less likely to adhere to ART (95%CI 0.16–0.66) compared to those who were food secure. Those with secondary education were 2.3 times more likely to adhere to ART (95%CI 1.02–5.23), compared to those without formal education. While participants who consistently obtain their ART at the clinic were more 4.2 times more likely to adhere to medication (95%CI 1.29–13.72), those experiencing ART side effects were 39% less likely to adhere to ART (95%CI 0.38–0.98). Conclusion More than one-third of adolescents and young adults were not adherent to ART in Tanga, Tanzania. Addressing such unprecedented challenges calls for efforts targeting adolescents and young adults with limited education, from households with food insecurity, and ensuring counseling and management of ART side effects.
Discovery of potent anti-toxoplasmosis drugs from secondary metabolites in Citrus limon (lemon) leaves, supported in-silico study
Abstract Toxoplasmosis induced by Toxoplasma gondii is a well-known health threat, that prompts fatal encephalitis increased with immunocompromised patients, in addition, it can cause chorioretinitis, microcephaly, stillbirth in the fetus and even led to death. Standard therapy uses sulfadiazine and pyrimethamine drugs revealed beneficial results during the acute stage, however, it has severe side effects. UPLC-ESI-MS/MS used to explore C. limon MeOH ext. constituents, which revealed a list of 41 metabolites of different classes encompasses; unsaturated fatty acid, tricarboxylic acids, phenolic aldehyde, phenolic acids, phenolic glycosides, coumarins, sesquiterpene lactone, limonoid, steroid and flavonoids. C. limon MeOH ext. and the isolates reduced significantly the number of T. gondii tachyzoites. Consequently, histopathological examination, proved significant reduction in the number of mononuclear inflammatory cells in the kidney and liver sections, besides, lowering the number of shrunken and degenerative neurons in the brain sections of infected mice. Molecular docking study was performed targeted certain receptors, which are important for the life cycle fundamentals for the parasite mobility including invasion and egress, and further molecular dynamics simulation was conducted to get insights into the structural changes of the formed complexes, along with a pharmacophoric mapping approach, that confirmed the need for a free hydroxyl group and/or a phenolic substituted one, in order to form HB, Hyd/Aro and ML interactions, through which, cell cycle disruption via iron chelation, could be achieved. In addition, the ADMIT properties of all identified metabolites were predicted.
Emergence of ferroelectricity in Sn-based perovskite semiconductor films by iminazole molecular reconfiguration
AbstractFerroelectric semiconductors have the advantages of switchable polarization ferroelectric field regulation and semiconductor transport characteristics, which are highly promising in ferroelectric transistors and nonvolatile memory. However, it is difficult to prepare a Sn-based perovskite film with both robust ferroelectric and semiconductor properties. Here, by doping with 2-methylbenzimidazole, Sn-based perovskite [93.3 mol% (FA0.86Cs0.14)SnI3 and 6.7 mol% PEA2SnI4] semiconductor films are transformed into ferroelectric semiconductor films, owing to molecular reconfiguration. The reconfigured ferroelectric semiconductors exhibit a high remanent polarization (Pr) of 23.2 μC/cm2. The emergence of ferroelectricity can be ascribed to the hydrogen bond enhancement after imidazole molecular doping, and then the spatial symmetry breaks causing the positive and negative charge centers to become non-coincident. Remarkably, the transistors based on perovskite ferroelectric semiconductors have a low subthreshold swing of 67 mv/dec, which further substantiates the superiority of introducing ferroelectricity. This work has developed a method to realize Sn-based ferroelectric semiconductor films for electronic device applications.
Correction: Genetic differentiation at extreme latitudes in the socially plastic sweat bee Halictus rubicundus
Exploring the spatiotemporal effects of urban scale and urban vitality on S&D balance in the Yangtze River Delta, China from 2015 to 2025
Deeper response predicts better outcomes in high-risk-smoldering-myeloma: results of the I-PRISM phase II clinical trial
AbstractEarly therapeutic intervention in high-risk smoldering multiple myeloma (HR-SMM) has shown benefits, however, no studies have assessed whether biochemical progression or response depth predicts long-term outcomes. The single-arm I-PRISM phase II trial (NCT02916771) evaluated ixazomib, lenalidomide, and dexamethasone in 55 patients with HR-SMM. The primary endpoint, median progression-free survival (PFS), was not reached (NR) (95% CI: 57.7–NR, median follow-up 50 months). The secondary endpoint, biochemical PFS, was 48.6 months (95% CI: 39.9–NR) and coincided with or preceded SLiM-CRAB in eight patients. For additional secondary objectives, the overall response rate was 93% with 31% achieving complete response (CR) and 45% very good partial response (VGPR) or better. CR correlated strongly with the absence of SLiM-CRAB and biochemical progression. MRD-negativity (10-5 sensitivity) predicted a 5-year biochemical PFS of 100% versus 40% in MRD-positive patients (p = 0.051), demonstrating that deep responses significantly improve time to progression. Exploratory single-cell RNA sequencing linked tumor MHC class I expression to proteasome inhibitor response, and a lower proportion of GZMB+ T cells within clonally expanded CD8+ T cells associated with suboptimal outcomes.
The involvement of Elf5 in regulating keratinocyte proliferation and differentiation processes in skin
Skin and hair development is regulated by multitude of programs of activation and silencing of gene expression to maintain normal skin and hair follicle (HF) development, homeostasis, and cycling. Here, we have identified E74-like factor 5 (Elf5) transcription factor, as a novel regulator of keratinocyte proliferation and differentiation processes in skin. Expression analysis has revealed that Elf5 expression was localised and elevated in stem/progenitor cell populations of both the epidermis (basal and suprabasal) and in HF bulge and hair germ stem cell (SCs) compartments during skin and hair development and cycling. Expressional and functional analysis using RT-qPCR, western blot and colony forming assays, revealed that Elf5 plays an important role in regulating keratinocyte proliferation and differentiation processes as well as potentially determining cell fate by regulating the stem/progenitor cell populations in skin and HFs. These data will provide a platform for pharmacological manipulation of Elf5 in skin, leading to advancements in many areas of research, including stem cell, regenerative medicine, and ageing.