In situ immune response and mechanisms of cell damage in central nervous system of fatal cases microcephaly by Zika virus

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Predicting antimicrobial resistance in E. coli with discriminative position fused deep learning classifier

Escherichia coli (E. coli) has become a particular concern due to the increasing incidence of antimicrobial resistance (AMR) observed worldwide. Using machine learning (ML) to predict E. coli AMR is a more efficient method than traditional laboratory testing. However, further improvement in the predictive performance of existing models remains challenging. In this study, we collected 1937 high-quality whole genome sequencing (WGS) data from public databases with an antimicrobial resistance phenotype and modified the existing workflow by adding an attention mechanism to enable the modified workflow to focus more on core single nucleotide polymorphisms (SNPs) that may significantly lead to the development of AMR in E. coli. While comparing the model performance before and after adding the attention mechanism, we also performed a cross-comparison among the published models using random forest (RF), support vector machine (SVM), logistic regression (LR), and convolutional neural network (CNN). Our study demonstrates that the discriminative positional colors of Chaos Game Representation (CGR) images can selectively influence and highlight genome regions without prior knowledge, enhancing prediction accuracy. Furthermore, we developed an online tool (https://github.com/tjiaa/E.coli-ML/tree/main) for assisting clinicians in the rapid prediction of the AMR phenotype of E. coli and accelerating clinical decision-making.

Balancing functions of regulatory T cells in mosquito-borne viral infections

Mosquito-borne viral infections are on the rise worldwide and can lead to severe symptoms such as haemorrhage, encephalitis, arthritis or microcephaly. A protective immune response following mosquito-borne viral infections requires the generation of a controlled and balanced immune response leading to viral clearance without immunopathology. Here, regulatory T cells play a central role in restoring immune homeostasis. In current review, we aim to provide an overview and summary of the phenotypes of FOXP3+ Tregs in various mosquito-borne arboviral disease, their association with disease severity and their functional characteristics. Furthermore, we discuss the role of cytokines and Tregs in the immunopathogenesis of mosquito-borne infections. Lastly, we discuss possible novel lines of research which could provide additional insight into the role of Tregs in mosquito-borne viral infections in order to develop novel therapeutic approaches or vaccination strategies.

A novel cell source for therapy of knee osteoarthritis using atelocollagen microsphere-adhered adipose-derived stem cells: Impact of synovial fluid exposure on cell activity

Introduction

Administration of adipose-derived stem cells (ADSCs) into the joint cavity has been shown to alleviate the symptoms of knee osteoarthritis (OA) by releasing exosomes and anti-inflammatory cytokines. However, the therapeutic effect of these cells is limited by their rapid disappearance after administration. Thus, it is necessary to prolong cell survival in the joint cavity. This study aimed to investigate the potential application of ADSCs adhered to atelocollagen microspheres (AMSs) for cell therapy of knee OA.

Methods

ADSCs were cultured for 2, 4, and 7 days in AMS suspension or adherent culture dishes. The supernatants were analyzed for IL-10 and exosome secretion via enzyme-linked immunosorbent assay and Nanosight. The effect of AMS was compared with that of adherent-cultured ADSCs (2D-cultured ADSCs) using transcriptome analysis. Moreover, the solubility of AMS and viability of ADSCs were evaluated using synovial fluid (SF) from patients with knee OA.

Results

Compared with 2D-cultured ADSCs, AMS-cultured ADSCs exhibited a significant increase in secretion of exosomes and IL-10, and the expression of several genes involved in extracellular matrix and immune regulation were altered. Furthermore, when AMS-cultured ADSCs were cultured in SF from knee OA patients to mimic the intra-articular environment, the SF dissolved the AMSs and released viable ADSCs. In addition, AMS-cultured ADSCs showed significantly higher long-term cell viability than 2D-cultured ADSCs.

Conclusion

Increased survival of AMS-adhered ADSCs was observed in the intra-articular environment, and AMSs were found to gradually dissipate. These results suggest that AMS-adhered ADSCs are promising source for cell therapy of knee OA.

Computational pathology: A survey review and the way forward

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

Advanced approaches of the use of circRNAs as a replacement for cancer therapy

Cancer is a broad name for a group of diseases in which abnormal cells grow out of control and are characterized by their complexity and recurrence. Although there has been progress in cancer therapy with the entry of precision medicine and immunotherapy, cancer incidence rates have increased globally. Non-coding RNAs in the form of circular RNAs (circRNAs) play crucial roles in the pathogenesis, clinical diagnosis, and therapy of different diseases, including cancer. According to recent studies, circRNAs appear to serve as accurate indicators and therapeutic targets for cancer treatment. However, circRNAs are promising candidates for cutting-edge cancer therapy because of their distinctive circular structure, stability, and wide range of capabilities; many challenges persist that decrease the applications of circRNA-based cancer therapeutics. Here, we explore the roles of circRNAs as a replacement for cancer therapy, highlight the main challenges facing circRNA-based cancer therapies, and discuss the key strategies to overcome these challenges to improve advanced innovative therapies based on circRNAs with long-term health effects.

Overview of the current procedures in synthesis of heparin saccharides

Natural heparin, a glycosaminoglycan consisting of repeating hexuronic acid and glucosamine linked by 1 → 4 glycosidic bonds, is the most widely used anticoagulant. To subvert the dependence on animal sourced heparin, alternative methods to produce heparin saccharides, i.e., either heterogenous sugar chains similar to natural heparin, or structurally defined oligosaccharides, are becoming hot subjects. Although the success by chemical synthesis of the pentasaccharide, fondaparinux, encourages to proceed through a chemical approach generating homogenous product, synthesizing larger oligos is still cumbersome and beyond reach so far. Alternatively, the chemoenzymatic pathway exhibited exquisite stereoselectivity of glycosylation and regioselectivity of modification, with the advantage to skip the tedious protection steps unavoidable in chemical synthesis. However, to a scale of drug production needed today is still not in sight. In comparison, a procedure of de novo biosynthesis in an organism could be an ultimate goal. The main purpose of this review is to summarize the current available/developing strategies and techniques, which is expected to provide a comprehensive picture for production of heparin saccharides to replenish or eventually to replace the animal derived products. In chemical and chemoenzymatic approaches, the methodologies are discussed according to the synthesis procedures: building block preparation, chain elongation, and backbone modification.

Cross-species analysis uncovers the mitochondrial stress response in the hippocampus as a shared mechanism in mouse early life stress and human depression

Depression, or major depressive disorder, poses a significant burden for both individuals and society, affecting approximately 10.8% of the general population. This psychiatric disorder leads to approximately 800,000 deaths per year. A combination of genetic and environmental factors such as early life stress (ELS) increase the risk for development of depression in humans, and a clear role for the hippocampus in the pathophysiology of depression has been shown. Nevertheless, the underlying mechanisms of depression remain poorly understood, resulting in a lack of effective treatments. To better understand the core mechanisms underlying the development of depression, we used a cross-species design to investigate shared hippocampal pathophysiological mechanisms in mouse ELS and human depression. Mice were subjected to ELS by a maternal separation paradigm, followed by RNA sequencing analysis of the adult hippocampal tissue. This identified persistent transcriptional changes linked to mitochondrial stress response pathways, with oxidative phosphorylation and protein folding emerging as the main mechanisms affected by maternal separation. Remarkably, there was a significant overlap between the pathways involved in mitochondrial stress response we observed and publicly available RNAseq data from hippocampal tissue of depressive patients. This cross-species conservation of changes in gene expression of mitochondria-related genes suggests that mitochondrial stress may play a pivotal role in the development of depression. Our findings highlight the potential significance of the hippocampal mitochondrial stress response as a core mechanism underlying the development of depression. Further experimental investigations are required to expand our understanding of these mechanisms.

Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

Salvia miltiorrhiza bunge extracts: a promising source for anti-atopic dermatitis activity

BACKGROUND

Atopic dermatitis (AD) is a chronic inflammatory condition characterized by the accumulation of reactive oxygen species and the expression of inflammatory factors. Regarding its anti-atopic activity, numerous traditional medicinal materials and secondary metabolic products play pivotal roles in modulating the associated mechanisms.

METHODS

This study aimed to utilize Salvia miltiorrhiza Bunge (SMB) as an anti-AD source. In-vitro activity assessments and qualitative and quantitative analyses using UPLC-TQ-MS/MS and HPLC-DAD were conducted in two cultivars ('Dasan' and 'Kosan'). Statistical analysis indicated that the profiles of their secondary metabolites contribute significantly to their pharmacological properties. Consequently, bio-guided fractionation was undertaken to figure out the distinct roles of the secondary metabolites present in SMB.

RESULTS

Comparative study of two cultivars indicated that 'Dasan', having higher salvianolic acid A and B, exhibited stronger antioxidant and anti-inflammatory activities. Meanwhile, 'Kosan', containing higher tanshinones, showed higher alleviating activities on anti-AD related genes in mRNA levels. Additionally, performed bio-guided fractionation re-confirmed that the hydrophilic compounds of SMB can prevent AD by inhibiting accumulation of ROS and suppressing inflammatory factors and the lipophilic components can directly inhibit AD.

CONCLUSIONS

SMB was revealed as a good source for anti-AD activity. Several bioactive compounds were identified from the UPLC-TQ-MS/MS and different compounds content was linked to biological activities. Characterization of these compounds may be helpful to understand differential role of secondary metabolites from SMB on alleviation of AD.

Zika virus infection suppresses CYP24A1 and CAMP expression in human monocytes

Monocytes are the primary targets of Zika virus (ZIKV) and are associated with ZIKV pathogenesis. Currently, there is no effective treatment for ZIKV infection. It is known that 1,25-dihydroxy vitamin D3 (VitD3) has strong antiviral activity in dengue virus-infected macrophages, but it is unknown whether VitD3 inhibits ZIKV infection in monocytes. We investigated the relationship between ZIKV infection and the expression of genes of the VitD3 pathway, as well as the inflammatory response of infected monocytes in vitro. ZIKV replication was evaluated using a plaque assay, and VitD3 pathway gene expression was analyzed by RT-qPCR. Pro-inflammatory cytokines/chemokines were quantified using ELISA. We found that VitD3 did not suppress ZIKV replication. The results showed a significant decrease in the expression of vitamin D3 receptor (VDR), cytochrome P450 family 24 subfamily A member 1 (CYP24A1), and cathelicidin antimicrobial peptide (CAMP) genes upon ZIKV infection. Treatment with VitD3 was unable to down-modulate production of pro-inflammatory cytokines, except TNF-α, and chemokines. This suggests that ZIKV infection inhibits the expression of VitD3 pathway genes, thereby preventing VitD3-dependent inhibition of viral replication and the inflammatory response. This is the first study to examine the effects of VitD3 in the context of ZIKV infection, and it has important implications for the role of VitD3 in the control of viral replication and inflammatory responses during monocyte infection.

Identification and analysis of oncogenic non-synonymous single nucleotide polymorphisms in the human NRAS gene: An exclusive in silico study

BACKGROUND

N-ras protein is encoded by the NRAS gene and operates as GDP-GTP-controlled on/off switching. N-ras interacts with cellular signaling networks that regulate various cellular activities including cell proliferation and survival. The nonsynonymous single nucleotide polymorphism (nsSNPs)-mediated alteration can substantially disrupt the structure and activity of the corresponding protein. N-ras has been reported to be associated with numerous diseases including cancers due to the nsSNPs. A comprehensive study on the NRAS gene to unveil the potentially damaging and oncogenic nsSNPs is yet to be accomplished. Hence, this extensive in silico study is intended to identify the disease-associated, specifically oncogenic nsSNPs of the NRAS gene.

RESULTS

Out of 140 missense variants, 7 nsSNPs (I55R, G60E, G60R, Y64D, L79F, D119G, and V152F) were identified to be damaging utilizing 10 computational tools that works based on different algorithms with high accuracy. Among those, G60E, G60R, and D119G variants were further filtered considering their location in the highly conserved region and later identified as oncogenic variants. Interestingly, G60E and G60R variants were revealed to be particularly associated with lung adenocarcinoma, rhabdomyosarcoma, and prostate adenocarcinoma. Therefore, D119G could be subjected to detailed investigation for identifying its association with specific cancer.

CONCLUSION

This in silico study identified the deleterious and oncogenic missense variants of the human NRAS gene that could be utilized for designing further experimental investigation. The outcomes of this study would be worthwhile in future research for developing personalized medicine.

Local anaesthetics and chemotherapeutic agents: a systematic review of preclinical evidence of interactions and cancer biology

Background

Local anaesthetics are widely used for their analgesic and anaesthetic properties in the perioperative setting, including surgical procedures to excise malignant tumours. Simultaneously, chemotherapeutic agents remain a cornerstone of cancer treatment, targeting rapidly dividing cancer cells to inhibit tumour growth. The potential interactions between these two drug classes have drawn increasing attention and there are oncological surgical contexts where their combined use could be considered. This review examines existing evidence regarding the interactions between local anaesthetics and chemotherapeutic agents, including biological mechanisms and clinical implications.

Methods

A systematic search of electronic databases was performed as per Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Selection criteria were designed to capture in vitro, in vivo, and clinical studies assessing interactions between local anaesthetics and a wide variety of chemotherapeutic agents. Screening and data extraction were performed independently by two reviewers. The data were synthesised using a narrative approach because of the anticipated heterogeneity of included studies.

Results

Initial searches yielded 1225 relevant articles for screening, of which 43 met the inclusion criteria. The interactions between local anaesthetics and chemotherapeutic agents were diverse and multifaceted. In vitro studies frequently demonstrated altered cytotoxicity profiles when these agents were combined, with variations depending on the specific drug combination and cancer cell type. Mechanistically, some interactions were attributed to modifications in efflux pump activity, tumour suppressor gene expression, or alterations in cellular signalling pathways associated with tumour promotion. A large majority of in vitro studies report potentially beneficial effects of local anaesthetics in terms of enhancing the antineoplastic activity of chemotherapeutic agents. In animal models, the combined administration of local anaesthetics and chemotherapeutic agents showed largely beneficial effects on tumour growth, metastasis, and overall survival. Notably, no clinical study examining the possible interactions of local anaesthetics and chemotherapy on cancer outcomes has been reported.

Conclusions

Reported preclinical interactions between local anaesthetics and chemotherapeutic agents are complex and encompass a spectrum of effects which are largely, although not uniformly, additive or synergistic. The clinical implications of these interactions remain unclear because of the lack of prospective trials. Nonetheless, the modulation of chemotherapy effects by local anaesthetics warrants further clinical investigation in the context of cancer surgery where they could be used together.

Clinical trial registration

Open Science Framework (OSF, project link: https://osf.io/r2u4z).

Building blocks needed for mechanistic modeling of bioprocesses: A critical review based on protein production by CHO cells

This paper reviews the key building blocks needed to develop a mechanistic model for use as an operational production tool. The Chinese Hamster Ovary (CHO) cell, one of the most widely used hosts for antibody production in the pharmaceutical industry, is considered as a case study. CHO cell metabolism is characterized by two main phases, exponential growth followed by a stationary phase with strong protein production. This process presents an appropriate degree of complexity to outline the modeling strategy. The paper is organized into four main steps: (1) CHO systems and data collection; (2) metabolic analysis; (3) formulation of the mathematical model; and finally, (4) numerical solution, calibration, and validation. The overall approach can build a predictive model of target variables. According to the literature, one of the main current modeling challenges lies in understanding and predicting the spontaneous metabolic shift. Possible candidates for the trigger of the metabolic shift include the concentration of lactate and carbon dioxide. In our opinion, ammonium, which is also an inhibiting product, should be further investigated. Finally, the expected progress in the emerging field of hybrid modeling, which combines the best of mechanistic modeling and machine learning, is presented as a fascinating breakthrough. Note that the modeling strategy discussed here is a general framework that can be applied to any bioprocess.

Development and assessment of an immobilized bacterial alliance that efficiently degrades tylosin in wastewater

Microbial degradation of tylosin (TYL) is a safe and environmentally friendly technology for remediating environmental pollution. Kurthia gibsonii (TYL-A1) and Klebsiella pneumonia (TYL-B2) were isolated from wastewater; degradation efficiency of the two strains combined was significantly greater than either alone and resulted in degradation products that were less toxic than TYL. With Polyvinyl alcohol (PVA)-sodium alginate (SA)-activated carbon (AC) used to form a bacterial immobilization carrier, the immobilized bacterial alliance reached 95.9% degradation efficiency in 1 d and could be reused for four cycles, with > 93% degradation efficiency per cycle. In a wastewater application, the immobilized bacterial alliance degraded 67.0% TYL in 9 d. There were significant advantages for the immobilized bacterial alliance at pH 5 or 9, with 20 or 40 g/L NaCl, or with 10 or 50 mg/L doxycycline. In summary, in this study, a bacterial consortium with TYL degradation ability was constructed using PVA-SA-AC as an immobilized carrier, and the application effect was evaluated on farm wastewater with a view to providing application guidance in environmental remediation.

Voxel Design of Grayscale DLP 3D-Printed Soft Robots

Grayscale digital light processing (DLP) printing is a simple yet effective way to realize the variation of material properties by tuning the grayscale value. However, there is a lack of available design methods for grayscale DLP 3D-printed structures due to the complexities arising from the voxel-level grayscale distribution, nonlinear material properties, and intricate structures. Inspired by the dexterous motions of natural organisms, a design and fabrication framework for grayscale DLP-printed soft robots is developed by combining a grayscale-dependent hyperelastic constitutive model and a voxel-based finite-element model. The constitutive model establishes the relationship between the projected grayscale value and the nonlinear mechanical properties, while the voxel-based finite-element model enables fast and efficient calculation of the mechanical performances with arbitrarily distributed material properties. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion (DoC) variation in a single voxel. The design framework is used to design structures with reduced stress concentration and programmable multimodal motions. This work paves the way for integrated design and fabrication of functional structures using grayscale DLP 3D printing.

Evaluation of the protective effect of coenzyme Q10 against x-ray irradiation-induced ovarian injury

AIM

This study focused on the anti-oxidant and anti-apoptotic effects of CoQ10 in ovaries exposed to pelvic radiation.

METHODS

Thirty-two female rats were randomly assigned into four groups. Group I (control group), Group II: Only 2 Gy pelvic x-ray irradiation (IR) was administered as a single fractioned dose. Group III: 30 mg/kg CoQ10 was administered by oral gavage +2 Gy pelvic IR. Group IV: 150 mg/kg CoQ10 was administered by oral gavage +2 Gy pelvic IR. CoQ10 treatment was started 7 days before pelvic IR and completed 7 days later. The rats in Group III and IV were treated with CoQ10 for a total of 14 days.

RESULTS

Histopathological analysis showed severe damage to the ovarian tissue in the radiation group, while both doses of CoQ10 showed normal histological structure. Likewise, while there was a high level of staining in the IR group for necrosis and apoptosis, the CoQ10 treated ones were like the control group. Tissue Malondialdehyde (MDA) levels were like the control group in the low-dose CoQ10 group, while the MDA levels of the high dose CoQ10 group were similar to the radiation group.

CONCLUSION

Usage of low-dose CoQ10 has a radioprotective effect on radiation-induced ovarian damage. Although the use of high doses is morphologically radioprotective, no antioxidative effect was observed in the biochemical evaluation.

Marine litter along the shores of the Persian Gulf, Iran

Plastic wastes -including cigarette butts (CBs)- are dangerous for marine ecosystems not only because they contain hazardous chemicals but also because they can finally turn into micro- or even nano-particles that may be ingested by micro- and macro-fauna. Even large pieces of plastics can trap animals. In this research, the pollution status of macroplastics (abundance, size, type, and colour) and cigarette butts (CBs, number/m2) on the northern coasts of the Persian Gulf has been investigated. A total of 19 stations were explored in Bushehr province (Iran), which covers a length equivalent to 160 km of the Persian Gulf coastline. Among the collected plastic waste (2992 items), disposable mugs were the most frequent (18 %). Plastics with sizes 5-15 cm were the most abundant, and the most common type of plastic was PET (P-value <0.05). The origin of most macroplastics was domestic (2269 items). According to the Index of Clean Coasts (ICC), most surveyed beaches were extremely dirty. The average number and density of CBs in this study were 220 and 2.45 items/m2, respectively. Household litter was the most abundant type of waste in the studied beaches, and this problem can be better managed by training and improving the waste disposal culture. In general, it is suggested that an integrated and enhanced management for fishing, sewage and surface water disposal, and sandy recreational beaches be implemented in Bushehr to control plastic waste.

Application of PLS-NN model based on mid-infrared spectroscopy in the origin identification of Cornus officinalis

Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of Cornus officinalis samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, F1-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of Cornus officinalis with an accuracy of 91.9%.

Multi-color dual wavelength vat photopolymerization 3D printing via spatially controlled acidity

Dual wavelength vat photopolymerization (DW-VP) has emerged as a powerful approach to create multimaterial objects. However, only a limited range of properties have been showcased. In this work, we report the 3D printing (3DP) of multi-color objects from a single resin vat using DW-VP. This was accomplished by concurrently curing resin with visible light and modulating local resin color with 365-nm ultraviolet (UV) light. The key advance was to use a photoacid generator (PAG) in combination with pH responsive dyes in the 3DP resins. The specific color is dictated by the extent of reaction, or local acidity in our case, and controlled by the light dosage and pattern of UV light applied. Multi-color object formation was implemented in two-step processes involving first 3DP to set the object structure, followed by UV exposure, as well as single processes that leveraged DW-VP to create a broad range of vibrant colors and patterns.

Sensor-integrated brain-on-a-chip platforms: Improving the predictive validity in neurodegenerative research

Affecting millions of individuals worldwide, neurodegenerative diseases (NDDs) pose a significant and growing health concern in people over the age of 60 years. Contributing to this trend are the steady increase in the aging population coupled with a persistent lack of disease-altering treatment strategies targeting NDDs. The absence of efficient therapeutics can be attributed to high failure rates in clinical trials and the ineptness of animal models in preceding preclinical studies. To that end, in recent years, significant research effort has been dedicated to the development of human cell-based preclinical disease models characterized by a higher degree of predictive validity. However, a key requirement of any in vitro model constitutes the precise knowledge and replication of the target tissues' (patho-)physiological microenvironment. Herein, microphysiological systems have demonstrated superiority over conventional static 2D/3D in vitro cell culture systems, as they allow for the emulation and continuous monitoring of the onset, progression, and remission of disease-associated phenotypes. This review provides an overview of recent advances in the field of NDD research using organ-on-a-chip platforms. Specific focus is directed toward non-invasive sensing strategies encompassing electrical, electrochemical, and optical sensors. Additionally, promising on- and integrable off-chip sensing strategies targeting key analytes in NDDs will be presented and discussed in detail.

Evidence for the role of affective theory of mind in face-name associative memory

Poor face-name recall has been associated with age-related impairments in cognitive functioning, namely declines in episodic memory and executive control. However, the role of social cognitive function - the ability to remember, process, and store information about others - has been largely overlooked in this work. Extensive work has shown that social and nonsocial cognitive processes rely on unique, albeit overlapping, mechanisms. In the current study, we explored whether social cognitive functioning - specifically the ability to infer other people's mental states (i.e., theory of mind) - facilitates better face-name learning. To do this, a sample of 289 older and young adults completed a face-name learning paradigm along with standard assessments of episodic memory and executive control alongside two theory of mind measures, one static and one dynamic. In addition to expected age differences, several key effects emerged. Age-related differences in recognition were explained by episodic memory, not social cognition. However, age effects in recall were explained by both episodic memory and social cognition, specifically affective theory of mind in the dynamic task. Altogether, we contend that face-name recall can be supported by social cognitive functioning, namely understanding emotions. While acknowledging the influence of task characteristics (i.e., lures, target ages), we interpret these findings in light of existing accounts of age differences in face-name associative memory.

Targeting epidermal growth factor receptor and its downstream signaling pathways by natural products: A mechanistic insight

The epidermal growth factor receptor (EGFR) is a transmembrane receptor tyrosine kinase (RTK) that maintains normal tissues and cell signaling pathways. EGFR is overactivated and overexpressed in many malignancies, including breast, lung, pancreatic, and kidney. Further, the EGFR gene mutations and protein overexpression activate downstream signaling pathways in cancerous cells, stimulating the growth, survival, resistance to apoptosis, and progression of tumors. Anti-EGFR therapy is the potential approach for treating malignancies and has demonstrated clinical success in treating specific cancers. The recent report suggests most of the clinically used EGFR tyrosine kinase inhibitors developed resistance to the cancer cells. This perspective provides a brief overview of EGFR and its implications in cancer. We have summarized natural products-derived anticancer compounds with the mechanistic basis of tumor inhibition via the EGFR pathway. We propose that developing natural lead molecules into new anticancer agents has a bright future after clinical investigation.

Differentiating viral and bacterial infections: A machine learning model based on routine blood test values

The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Virus vs. Bacteria machine learning model was developed to distinguish between these infection types using 16 routine blood test results, C-reactive protein concentration (CRP), biological sex, and age. With a dataset of 44,120 cases from a single medical center, the model achieved an accuracy of 82.2 %, a sensitivity of 79.7 %, a specificity of 84.5 %, a Brier score of 0.129, and an area under the ROC curve (AUC) of 0.905, outperforming a CRP-based decision rule. Notably, the machine learning model enhanced accuracy within the CRP range of 10-40 mg/L, a range where CRP alone is less informative. These results highlight the advantage of integrating multiple blood parameters in diagnostics. The "Virus vs. Bacteria" model paves the way for advanced diagnostic tools, leveraging machine learning to optimize infection management.

In silico identification of drug targets and vaccine candidates against Bartonella quintana: a subtractive proteomics approach

BACKGROUND

The availability of genes and protein sequences for parasites has provided valuable information for drug target identification and vaccine development. One such parasite is Bartonella quintana, a Gram-negative, intracellular pathogen that causes bartonellosis in mammalian hosts.

OBJECTIVE

Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to B. quintana.

METHODS AND FINDINGS

To explore these aspects, we have adopted a subtractive proteomics approach to analyse the proteome of B. quintana. By subtractive proteins between the host and parasite proteome, a set of proteins that are likely unique to the parasite but absent in the host were identified. This analysis revealed that out of the 1197 protein sequences of the parasite, 660 proteins are non-homologous to the human host. Further analysis using the Database of Essential Genes predicted 159 essential proteins, with 28 of these being unique to the pathogen and predicted as potential putative targets. Subcellular localisation of the predicted targets revealed 13 cytoplasmic, eight membranes, one periplasmic, and multiple location proteins. The three-dimensional structure and B cell epitopes of the six membrane antigenic protein were predicted. Four B cell epitopes in KdtA and mraY proteins, three in lpxB and BQ09550, whereas the ftsl and yidC proteins were located with eleven and six B cell epitopes, respectively.

MAINS CONCLUSIONS

This insight prioritises such proteins as novel putative targets for further investigations on their potential as drug and vaccine candidates.

Serum autotaxin is a prognostic indicator of liver-related events in patients with non-alcoholic fatty liver disease

BACKGROUND

Circulating autotaxin (ATX) levels have been reported to correlate with liver inflammation activity and liver fibrosis severity in patients with non-alcoholic fatty liver disease (NAFLD). The objective of this study is to investigate whether serum ATX could predict liver-related events (LRE) in NAFLD patients.

METHODS

This retrospective investigation includes 309 biopsy-proven NAFLD patients registered at Shinshu University Hospital. All patients are followed for at least 1 year, during which time the prevalence of LRE, including newly developing hepatocellular carcinoma, hepatic encephalopathy, ascites, and esophagogastric varices, is investigated in relation to ATX levels at the time of liver biopsy.

RESULTS

During the median follow-up period of 7.0 years, LRE are observed in 20 patients (6.5%). The area under the receiver operating characteristic curve and cut-off value of serum ATX for predicting LRE are 0.81 and 1.227 mg/l, respectively. Multivariate Cox proportional hazards models for LRE determine ATX and advanced fibrosis as independently associated factors. Furthermore, in a competing risk analysis that considered non-liver-related death as a competing event, ATX (HR 2.29, 95% CI 1.22-4.30, p = 0.010) is identified as an independent factor associated with LRE, along with advanced fibrosis (HR 8.01, 95% CI 2.10-30.60, p = 0.002). The predictive utility of ATX for LRE is validated in an independent cohort.

CONCLUSIONS

Serum ATX may serve as a predictive marker for LRE in patients with NAFLD.

Tertiary structure and conformational dynamics of the anti-amyloidogenic chaperone DNAJB6b at atomistic resolution

DNAJB6b is a molecular chaperone of the heat shock protein network, shown to play a crucial role in preventing aggregation of several disease-related intrinsically disordered proteins. Using homology modeling and microsecond-long all-atom molecular dynamics (MD) simulations, we show that monomeric DNAJB6b is a transiently interconverting protein cycling between three states: a closed state, an open state (both abundant), and a less abundant extended state. Interestingly, the reported regulatory autoinhibitory anchor between helix V in the G/F1 region and helices II/III of the J-domain, which obstructs the access of Hsp70 to the J-domain remains present in all three states. This possibly suggests a mechanistically intriguing regulation in which DNAJB6b only becomes exposed when loaded with substrates that require Hsp70 processing. Our MD results of DNAJB6b carrying mutations in the G/F1 region that are linked to limb-girdle muscular dystrophy type D1 (LGMDD1) show that this G/F1 region becomes highly dynamic, pointing towards a spontaneous release of the autoinhibitory helix V from helices II/III. This would increase the probability of non-functional Hsp70 interactions to DNAJB6b without substrates. Our cellular data indeed confirm that non-substrate loaded LGMDD1 mutants have aberrant interactions with Hsp70.

The role of the correlated motion(s) of the chromophore in photoswitching of green and red forms of the photoconvertible fluorescent protein mSAASoti

Wild-type SAASoti and its monomeric variant mSAASoti can undergo phototransformations, including reversible photoswitching of the green form to a nonfluorescent state and irreversible green-to-red photoconversion. In this study, we extend the photochemistry of mSAASoti variants to enable reversible photoswitching of the red form. This result is achieved by rational and site-saturated mutagenesis of the M163 and F177 residues. In the case of mSAASoti it is M163T substitution that leads to the fastest switching and the most photostable variant, and reversible photoswitching can be observed for both green and red forms when expressed in eukaryotic cells. We obtained a 13-fold increase in the switching efficiency with the maximum switching contrast of the green form and the appearance of comparable switching of the red form for the C21N/M163T mSAASoti variant. The crystal structure of the C21N mSAASoti in its green on-state was obtained for the first time at 3.0 Å resolution, and it is in good agreement with previously calculated 3D-model. Dynamic network analysis reveals that efficient photoswitching occurs if motions of the 66H residue and phenyl fragment of chromophore are correlated and these moieties belong to the same community.

Effects of removing in-feed antibiotics and zinc oxide on the taxonomy and functionality of the microbiota in post weaning pigs

BACKGROUND

Post weaning diarrhoea (PWD) causes piglet morbidity and mortality at weaning and is a major driver for antimicrobial use worldwide. New regulations in the EU limit the use of in-feed antibiotics (Ab) and therapeutic zinc oxide (ZnO) to prevent PWD. New approaches to control PWD are needed, and understanding the role of the microbiota in this context is key. In this study, shotgun metagenome sequencing was used to describe the taxonomic and functional evolution of the faecal microbiota of the piglet during the first two weeks post weaning within three experimental groups, Ab, ZnO and no medication, on commercial farms using antimicrobials regularly in the post weaning period.

RESULTS

Diversity was affected by day post weaning (dpw), treatment used and diarrhoea but not by the farm. Microbiota composition evolved towards the dominance of groups of species such as Prevotella spp. at day 14dpw. ZnO inhibited E. coli overgrowth, promoted higher abundance of the family Bacteroidaceae and decreased Megasphaera spp. Animals treated with Ab exhibited inconsistent taxonomic changes across time points, with an overall increase of Limosilactobacillus reuteri and Megasphaera elsdenii. Samples from non-medicated pigs showed virulence-related functions at 7dpw, and specific ETEC-related virulence factors were detected in all samples presenting diarrhoea. Differential microbiota functions of pigs treated with ZnO were related to sulphur and DNA metabolism, as well as mechanisms of antimicrobial and heavy metal resistance, whereas Ab treated animals exhibited functions related to antimicrobial resistance and virulence.

CONCLUSION

Ab and particularly ZnO maintained a stable microbiota composition and functionality during the two weeks post weaning, by limiting E. coli overgrowth, and ultimately preventing microbiota dysbiosis. Future approaches to support piglet health should be able to reproduce this stable gut microbiota transition during the post weaning period, in order to maintain optimal gut physiological and productive conditions.

Synthesis and study of antibiofilm and antivirulence properties of flavonol analogues generated by palladium catalyzed ligand free Suzuki-Miyaura coupling against Pseudomonas aeruginosa PAO1

The Suzuki-Miyaura coupling is one of the ubiquitous method for the carbon-carbon bond-forming reactions in organic chemistry. Its popularity is due to its ability to undergo extensive coupling reactions to generate a broad range of biaryl motifs in a straightforward manner displaying a high level of functional group tolerance. A convenient and efficient synthetic route to arylate different substituted flavonols through the Suzuki-Miyaura cross-coupling reaction has been explained in this study. The arylated products were acquired by the coupling of a variety of aryl boronic acids with flavonols under Pd(OAc)2 catalyzed reaction conditions in a ligand-free reaction strategy. Subsequently, the antibiofilm and antivirulence properties of the arylated flavonols against Pseudomonas aeruginosa PAO1 were studied thoroughly. The best ligands for quorum sensing proteins LasR, RhlR, and PqsR were identified using molecular docking study. These best fitting ligands were then studied for their impact on gene expression level of P. aeruginosa by RT-PCR towards quorum sensing genes lasB, rhlA, and pqsE. The downregulation in the gene expression with the effect of synthesized flavonols endorse the antibiofilm efficiency of the compounds.

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Here, we show that odorant mixtures of increasing complexity evoke progressively denser OSN activity, yet cortical feedback activity is of similar sparsity for all stimuli. Also, representations of complex mixtures are similar in OSNs but are decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibit a sigmoidal relationship, cortical axonal responses are complex and nonmonotonic, which can be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

Role of oxygen functional groups and attachment of Au nanoparticles on graphene oxide sheets for improved photodetection performance

Integrating low-dimensional graphene oxide (GO) with conventional Si technology offers innovative strategies for developing ultrafast wideband photodetectors. In this study, we synthesized GO and explored its potential application in broadband photodetection alongside silicon heterostructures. The as-synthesized GO contains various oxygen functional groups, as evidenced by X-ray photoelectron and Fourier transform infrared spectroscopy. These functional groups contribute to increased photo absorption, enhancing photodetection performance. The systematic reduction of these functional groups from the GO surface via thermal annealing decreases photo absorption and consequently lowers the photocurrent. This reduction diminishes photo absorption and amplifies the dark current by approximately 25 times, from 20 nA to 496 nA. This dark current increase is attributed to the electron mobility following the reduction of functional groups. However, attaching plasmonic gold nanoparticles (Au NPs) to the GO surface enhances UV-Vis absorption in the visible region, enabling broadband detection. The even distribution of attached Au NPs on the GO surface is confirmed through field emission transmission electron microscopy. While thermal annealing of GO diminishes the responsivity from 4.6 A W-1 to 3.0 A W-1, the attachment of Au NPs augments the responsivity by more than two-fold, reaching 10.0 A W-1. Thus, it highlights the importance of rich oxygen functional groups in GO and the attachment of Au NPs to achieve more efficient photo-sensing properties.

Optimization of CoFe2O4 nanoparticles and graphite fillers to endow thermoplastic polyurethane nanocomposites with superior electromagnetic interference shielding performance

The rapid growth, integration, and miniaturization of electronics have raised significant concerns about how to handle issues with electromagnetic interference (EMI), which has increased demand for the creation of EMI shielding materials. In order to effectively shield against electromagnetic interference (EMI), this study developed a variety of thermoplastic polyurethane (TPU)-based nanocomposites in conjunction with CoFe2O4 nanoparticles and graphite. The filler percentage and nanocomposite thickness were tuned and optimized. The designed GF15-TPU nanocomposite, which has a 5 mm thickness, 15 weight percent cobalt ferrite nanoparticles, and 35 weight percent graphite, showed the highest total EMI shielding effectiveness value of 41.5 dB in the 8.2-12.4 GHz frequency range, or 99.993% shielding efficiency, out of all the prepared polymer nanocomposites. According to experimental findings, the nanocomposite's dipole polarization, interfacial polarization, conduction loss, eddy current loss, natural resonance, exchange resonance, multiple scattering, and high attenuation significantly contribute to improving its electromagnetic interference shielding properties. The created TPU-based nanocomposites containing graphite and CoFe2O4 nanoparticles have the potential to be used in communication systems, defense, spacecraft, and aircraft as EMI shielding materials.

A supervised learning-assisted multi-scale study for thermal and mechanical behavior of porous Silica

This paper presents a comprehensive investigation of mesoporous Silica utilizing a multi-scale modeling approach under periodic boundary conditions integrated with machine learning algorithms. The study begins with Molecular Dynamics (MD) simulations to extract Silica's elastic properties and thermal conductivity at the nano-scale, employing the Tersoff potential. Subsequently, the derived material characteristics are applied to a series of generated porous Representative Volume Elements (RVEs) at the microscale. This phase involves the exploration of porosity and void shape effects on Silica's thermal and mechanical properties, considering inhomogeneities' distributions along the X-axis and random dispersion of pore cells within a three-dimensional space. Furthermore, the influence of pore shape is examined by defining open and closed-cell models, encompassing spherical and ellipsoidal voids with aspect ratios of 2 and 4. To predict the properties of porous Silica, a shallow Artificial Neural Network (ANN) is deployed, utilizing geometric parameters of the RVEs and porosity. Subsequently, it is revealed that Silica's thermal and mechanical behavior is linked to pore geometry, distribution, and porosity model. Finally, to classify the behavior of porous Silica into three categories, quasi-isotropic, orthotropic, and transversely-isotropic, three methodologies of decision tree approach, K-Nearest Neighbors (KNN) algorithm, and Support Vector Machines (SVMs) are employed. Among these, SVMs employing a quadratic kernel function demonstrate robust performance in categorizing the thermal and mechanical behavior of porous Silica.

Integrated transcriptome sequencing and weighted gene co-expression network analysis reveals key genes of papillary thyroid carcinomas

Objective

Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancers and has a high recurrence rate. We aimed to screen key genes involved in PTC to provide novel insights into the mechanisms of PTC.

Methods

Seven microarray datasets of PTC were downloaded from gene expression omnibus database. Differentially expressed genes (DEGs) between PTC and normal samples were screened in the merged dataset. Then, protein-protein interaction (PPIs) functional modules analysis and weighted gene co-expression network analysis (WGCNA) were utilized to identify PTC-associated key genes. The identified key genes were then characterized from various aspects, including gene set enrichment analysis (GSEA) and the associations with immune infiltration, methylation levels and prognosis.

Results

A large numbers of DEGs were identified, and these DEGs are involved in several cancer pathways. Nine key genes (including down-regulated genes GNA14, AVPR1A, and WFS1, and up-regulated genes LAMB3, PLAU, MET, MFGE8, PRSS23, and SERPINA1) were identified. Patients in the AVPR1A and GNA14 high expression groups had better disease-free survival (DFS) than those in the low expression group. Key genes were mainly involved in P53 pathway, estrogen response, apoptosis, glycolysis, NOTCH signaling, epithelial mesenchymal transition, WNT_beta catenin signaling, and inflammatory response. The expression of key genes was associated with immune cell infiltration and corresponding methylation levels. The verification results of key gene proteins and mRNA expression levels using external validation datasets were consistent with our expectations, implying the involvements of key genes in PTC.

Conclusion

The key genes may serve as potential therapeutic targets for PTC. This study provides novel insights into the mechanisms underlying PTC development.

Potential therapeutic effects of green tea (Camellia sinensis) in eye diseases, a review

This review aims to evaluate the therapeutic potential of green tea (GT), scientifically named Camellia sinensis, in treating eye diseases. We provide an overview of the ingredients and traditional use of Camellia sinensis, followed by a detailed discussion of its therapeutic uses in various eye diseases, including ocular surface diseases (allergic diseases, dry eye, pterygium, and infections), cataract, glaucoma, uveitis, retinal diseases, and optic nerve diseases. The pharmacologic activities related to ocular diseases, such as anti-vascular endothelial growth factor, aldose reductase inhibitor activity, anti-bacterial, anti-inflammatory, and antioxidant effects are also explored in this review. The dose and route of administration of GT in various studies are discussed. Safety issues related to the use of GT, such as the side effects associated with high doses and long-term use, are also addressed. The review highlights the potential of GT as a natural therapeutic agent for a variety of ocular diseases. Its various pharmacologic activities make it a promising treatment option. However, more well-designed studies are needed to determine the optimal dose and route of administration and to assess its long-term safety and efficacy. Overall, GT appears to be a promising adjunct therapy for various ocular diseases.

Fluorimetric detection of DNA methylation by cerium oxide nanoparticles for early cancer diagnosis

In this study, a very sensitive fluorescence nano-biosensor was developed using CeO2 nanoparticles for the rapid detection of DNA methylation. The characteristics of CeO2 nanoparticles were determined by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) spectroscopy, UV-visible spectroscopy, and fluorescence spectroscopy. The CeO2 nanoparticles were reacted with a single-stranded DNA (ssDNA) probe, and then methylated and unmethylated target DNAs hybridized with an ssDNA probe, and the fluorescence emission was measured. Upon adding the target unmethylated and methylated ssDNA, the fluorescence intensity increased in the linear range of concentration from 2 × 10-13 - 10-18 M. The limit of detection (LOD) was 1.597 × 10-6 M for methylated DNA and 1.043 × 10-6 M for unmethylated DNA. The fluorescence emission intensity of methylated sequences was higher than of that unmethylated sequences. The fabricated DNA nanobiosensor showed a fluorescence emission at 420 nm with an excitation wavelength of 280 nm. The impact of CeO2 binding on methylated and unmethylated DNA was further demonstrated by agarose gel electrophoresis. Finally, the actual sample analysis suggested that the nanobiosensor could have practical applications for detecting methylation in the human plasma samples.

Porous α-Fe2O3 nanocarriers: Biosynthesis and in vitro gene delivery applications

Non-viral gene delivery is a new therapeutic in the treating genetic disorders. The most important challenge in nonviral gene transformation is the immunogenicity of carriers. Nowadays, The immunogenicity of nanocarriers as a deliverer of nucleic acid molecules has received significant attention. In this research, hematite green nanocarriers were prepared in one step with rosemary extract. Synthetic nanocarriers were investigated by using XRD (X-ray diffraction analysis), FESEM-EDX (field emission scanning electron microscopy with energy dispersive X-Ray spectroscopy), HR-TEM (high-resolution transmission electron microscopy), VSM (value stream mapping), TGA- DTG (thermal gravimetric analysis-differential thermal analysis), FT-IR (fourier-transform infrared spectroscopy), BET (brunauer-emmett-teller) and BJH (barrett-joyner-halenda) analyses. The cytotoxicity of synthetic nanocarriers was evaluated on HEK-293Tcell lines at concentration of 1-500 μg/ml using MTT method. Finally, targeted transfection of GFP plasmid using green porous particles was performed using an external magnetic field. Biogenic hematite nanoparticles with hexagonal crystal structures have a 3D pile flower-like morphology. The existence of rosemary phytochemicals in the construction of nanoparticles has caused minimal toxicity and high biocompatibility of nanocarriers. Also, TGA studies confirmed the stability of bionic nanoparticles. Superparamagnetic green nanocarriers at concentrations above 500 μg/ml is not toxic to HEK293T cells. The delivery efficiency of the plasmid was optimal at an N/P ratio of 3. Therefore, the porous α-Fe2O3 green nanocarriers are non-viral and safe carriers with potential applications in gene therapy.

Evaluation of curcumin-based ophthalmic nano-emulsion on atropine-induced dry eye in mice

Background

One of the most efficient treatments for dry eye syndrome (DES) is to use nanocarriers as a potential delivery system. We aim to evaluate curcumin in a nano emulsion formulation.

Methods

A new formulation containing 5.5% curcuminoid was used. DLS, Zeta potential, TEM, and HPLC tests were performed to determine the size and morphology. First, 30 mice were selected as atropine-induced dry eye models. Next, 25 mice in 5 groups were treated with the nano emulsion at different doses, and corneal tissues were separated for evaluation.

Results

The DLS test results were indicative of the particles' stability. Nano curcumin appeared to be thoroughly effective in all groups, with the highest dose showing the most similarity to the healthy control group.

Conclusions

Curcumin-based nano emulsion eye drop is a promising candidate for DES management. However, further investigation is required to evaluate the possible risks in humans.

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex

Background

Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets.

Results

A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements.

Conclusions

Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

Hydrophobic surface induced pro-metastatic cancer cells for in vitro extravasation models

In vitro vascularized cancer models utilizing microfluidics have emerged as a promising tool for mechanism study and drug screening. However, the lack of consideration and preparation methods for cancer cellular sources that are capable of adequately replicating the metastatic features of circulating tumor cells contributed to low relevancy with in vivo experimental results. Here, we show that the properties of cancer cellular sources have a considerable impact on the validity of the in vitro metastasis model. Notably, with a hydrophobic surface, we can create highly metastatic spheroids equipped with aggressive invasion, endothelium adhesion capabilities, and activated metabolic features. Combining these metastatic spheroids with the well-constructed microfluidic-based extravasation model, we validate that these metastatic spheroids exhibited a distinct extravasation response to epidermal growth factor (EGF) and normal human lung fibroblasts compared to the 2D cultured cancer cells, which is consistent with the previously reported results of in vivo experiments. Furthermore, the applicability of the developed model as a therapeutic screening platform for cancer extravasation is validated through profiling and inhibition of cytokines. We believe this model incorporating hydrophobic surface-cultured 3D cancer cells provides reliable experimental data in a clear and concise manner, bridging the gap between the conventional in vitro models and in vivo experiments.

North Central Asia isotopic database for archaeological samples

The North Central Asia Isotopic Database (NCAID) is an open-access dataset of stable isotope measurements from archaeological remains, spanning from the Early Neolithic until present-day in North Central Asia. With 3,143 individual entries corresponding to data accumulated over more than 20 years of research, this comprehensive dataset encompasses measurements of stable carbon and nitrogen isotopes in organic fractions from archaeological humans, animals, and plants. NCAID incorporates diverse supporting information, providing geographical information, archaeological context descriptions, and chronology. This resource facilitates research into past human lifeways, paleo-environments/climates, and animal management practices throughout North Central Asia and will be continually updated as more novel data is released.

Molecular characterization of chronic cutaneous wounds reveals subregion- and wound type-specific differential gene expression

A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri-wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA-Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine-like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.

Neuroinflammation, blood-brain barrier dysfunction, hippocampal atrophy and delayed neurodevelopment: Contributions for a rat model of congenital Zika syndrome

The congenital Zika syndrome (CZS) has been characterized as a set of several brain changes, such as reduced brain volume and subcortical calcifications, in addition to cognitive deficits. Microcephaly is one of the possible complications found in newborns exposed to Zika virus (ZIKV) during pregnancy, although it is an impacting clinical sign. This study aimed to investigate the consequences of a model of congenital ZIKV infection by evaluating the histopathology, blood-brain barrier, and neuroinflammation in pup rats 24 h after birth, and neurodevelopment of the offspring. Pregnant rats were inoculated subcutaneously with ZIKV-BR at the dose 1 × 107 plaque-forming unit (PFU mL-1) of ZIKV isolated in Brazil (ZIKV-BR) on gestational day 18 (G18). A set of pups, 24 h after birth, was euthanized. The brain was collected and later evaluated for the histopathology of brain structures through histological analysis. Additionally, analyses of the blood-brain barrier were conducted using western blotting, and neuroinflammation was assessed using ELISA. Another set of animals was evaluated on postnatal days 3, 6, 9, and 12 for neurodevelopment by observing the developmental milestones. Our results revealed hippocampal atrophy in ZIKV animals, in addition to changes in the blood-brain barrier structure and pro-inflammatory cytokines expression increase. Regarding neurodevelopment, a delay in important reflexes during the neonatal period in ZIKV animals was observed. These findings advance the understanding of the pathophysiology of CZS and contribute to enhancing the rat model of CZS.

The Cardioprotective and Anticancer Effects of SGLT2 Inhibitors: JACC: CardioOncology State-of-the-Art Review

Sodium-glucose cotransporter-2 (SGLT2) inhibitors, originally approved for type 2 diabetes mellitus, have demonstrated efficacy in reducing cardiovascular events, particularly heart failure, in patients with and without diabetes. An intriguing research area involves exploring the potential application of SGLT2 inhibitors in cardio-oncology, aiming to mitigate the cardiovascular adverse events associated with anticancer treatments. These inhibitors present a unique dual nature, offering both cardioprotective effects and anticancer properties, conferring a double benefit for cardio-oncology patients. In this review, the authors first examine the established cardioprotective effects of SGLT2 inhibitors in heart failure and subsequently explore the existing body of evidence, including both preclinical and clinical studies, that supports the use of SGLT2 inhibitors in the context of cardio-oncology. The authors further discuss the mechanisms through which SGLT2 inhibitors protect against cardiovascular toxicity secondary to cancer treatment. Finally, they explore the potential anticancer effects of SGLT2 inhibitors along with their proposed mechanisms.

The recent possible strategies for breeding ultraviolet-B-resistant crops

The sensitivity of crops to ultraviolet B (UVB, 280-315 nm) radiation varies significantly. Plants' sensitivity to UVB is heavily influenced by the activity of the enzyme cyclobutane pyrimidine dimer (CPD) photolyase, which fixes UVB-induced CPDs. Crops grown in tropical areas with high level of UVB radiation, like O. glaberrima from Africa and O. sativa ssp. indica rice from Bengal, are more sensitive to UVB radiation and could suffer more as a result of rising UVB levels on the earth's surface. Therefore, creating crops that can withstand high UVB is crucial in tropical regions. There is, however, little information on current techniques for breeding UVB-resistant plants. The most recent techniques for producing UVB-resistant crops are presented in this review. The use of DNA methylation, boosting the antioxidant system, regulating the expression of micro-RNA396, and overexpressing CPD photolyase in transgenic plants are some of the methods that are discussed. CPD photolyase overexpression in transgenic plants is the most popular technique for producing UVB-resistant rice. The study also offers several strategies for creating UVB-resistant plants using gene editing techniques. To feed the world's rapidly expanding population, researchers can use the information from this study to improve food production.

Endophytic Aspergillii and Penicillii from medicinal plants: a focus on antimicrobial and multidrug resistant pathogens inhibitory activity

The rise of multidrug resistance among microorganisms, where they develop resistance against formerly efficacious drugs, has led to increased disease prevalence and mortality rates, posing a growing challenge. Globally, antibiotic resistance has made a significant impact, causing millions of fatalities each year. Endophytic fungi have gained considerable attention in research due to their potential to produce a wide variety of secondary metabolites, including natural substances with antimicrobial capabilities. The genera Aspergillus and Penicillium stand out as the most prevalent species of endophytic fungi. Filamentous fungi, such as these are responsible for the production of 45% of known microbial metabolites. This review focuses on exploring the bioactive substances produced by endophytic fungi from these two genera, particularly in conjunction with medicinal plants. Emphasis is placed on their antimicrobial activity and their ability to inhibit multidrug-resistant pathogens. As the need for alternative treatments to combat drug-resistant infections continues to grow, endophytic fungi have the potential to provide a valuable source of bioactive molecules for medical applications.

Graphic analysis of various sulfur applications on safflower fatty acids profile

In this study, we examined the effects of seven different sulfur treatments on safflower seeds. The treatments included: no sulfur application (S0), 25 kg/ha of pure bulk sulfur (S25), 50 kg/ha of pure bulk sulfur (S50), 25 kg/ha of sulfur phosphate (Sp25), 50 kg/ha of sulfur phosphate (Sp50), 25 kg/ha of zinc sulfate (Zs25), and 50 kg/ha of zinc sulfate (Zs50). Our evaluation covered various seed quality attributes, including ash percentage (ASH), oil percentage (OIL), and protein percentage (PRO). Additionally, we analyzed the fatty acid composition, including palmitic acid 16 : 0 (PAL), stearic acid 18 : 0 (STE), oleic acid 18 : 1 (OLE), linoleic acid 18 : 2 (LINL), arachidic acid 20 : 0 (ARA), and linolenic acid 18 : 3 (LINN). The vector-view of the biplot illustrated positive associations among the fatty acids STE, PAL, and OLE, whereas ASH exhibited negative associations with OIL, LINL, and LINN. The polygon-view graph was divided into four sectors, with the genotype S50 emerging as the top performer for attributes such as OIL, PRO, LINL, ARA, and LINN. Treatment Zs50 occupied the vertex of another sector and displayed the highest values for palmitic acid PAL, STE, and OLE, while treatment S0 was positioned at the vertex of the next sector, characterized by its high ASH content. By utilizing the ideal tester tool of treatment by trait biplot, we identified OIL as the desirable trait that most effectively represented the data. The qualitative properties of safflower oil were notably influenced by sulfur application, with treatment S50 proving to be the most effective in enhancing these properties.

Light-Sheet Imaging to Reveal Cardiac Structure in Rodent Hearts

Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.