High Degree Of Connectivity Research Articles

Whole genome sequencing of Castanea mollissima and molecular mechanisms of sugar and starch synthesis

The chestnut tree exhibits self-incompatibility, where the selection of the male parent (pollen xenia) significantly affects seed starch metabolism, as well as fruit yield and quality. Despite its importance, the molecular mechanisms underlying pollen xenia remains largely unknown. In this study, we utilized the ‘Lan You’ variety of C. mollissima to construct a high-quality reference genome. As a result, a first Telomere-to-telomere (T2T) gap-free genome for this species was successfully assembled. A total of 560 transcription factors and 22 structural genes were identified as consistent across the TO-GCNs, indicating a consistent regulation pattern in the co-expression of genes involved in starch accumulation. These networks were further divided into three sub-networks: T1, T2, and T3. Among these, the T1 and T2 sub-networks exhibited a higher number of structural genes with consistent regulation patterns and were closely associated with sugar biosynthesis. The gene SBE (Camol08G0254600) was identified as the hub gene with the highest degree of connectivity, encoding a key rate-limiting enzyme in the amylopectin biosynthesis pathway. This study provides a foundation for further research on C. mollissima population genetics, genetic improvement, and strategies aimed at enhancing yield and quality.

Connections and Spatial Network Structure of the Tourism Economy in Beijing–Tianjin–Hebei: A Social Network Perspective

In the context of the coordinated development of Beijing–Tianjin–Hebei, examining the spatial connections and network structure characteristics of the tourism economy holds substantial theoretical and practical significance. This study constructs a tourism economic quality evaluation index system from four dimensions and optimizes the tourism economic gravity model by incorporating time distance and weight factors to dynamically simulate the intensity of tourism economic spatial connection (ITESC). Based on the new perspective of relational data, social network analysis is employed to investigate the spatial correlation network characteristics and group structure changes in the tourism economy within the Beijing–Tianjin–Hebei urban agglomeration (BTHUA). The results demonstrate a significant improvement in overall tourism economic quality from 2013 to 2022, with the average quality increasing from 0.128 in 2013 to 0.157 in 2022. Tourism economic spatial connections are prevalent among cities, exhibiting heterogeneous characteristics, characterized by density in the north and relatively sparse in the south. The network cohesion of ITESC strengthens, and the network structure evolves from a highly centralized to a multi-centralized configuration, with increasingly frequent cooperation and interaction in tourism between cities. Beijing, Tianjin, and Shijiazhuang occupy central positions in the network, exhibiting strong ITESC and a high degree of connectivity, generating a significant “trickle-down effect” on peripheral cities. Consequently, strengthening ITESC between peripheral cities and core areas, as well as enhancing the bidirectional spillover of tourism development between cities, is crucial for the future sustainable and coordinated development of tourism in the BTHUA.

Geography of research networks in the Big South of Russia

The geography of research and innovation activity is a traditional topic of research in human geography. Classical studies of the clustering and diffusion of innovation in the 1960s and 70s received a new impetus in the 21st century with the understanding of the openness of innovation and the importance of interregional collaborative networks. Digitalization has played an important role, providing access to new sources of large geocoded data on the movement of key elements of the knowledge economy, including publications as a formalized outcome of scientific activity. The purpose of the article is to identify the center-periphery research ties of one of the largest macroregions of Russia – the Big South of Russia. The aim was to assess the territorial patterns of interregional research networks with the identification of gravity poles and interconnections at the local and national levels. The study uses the method of spatial scientometrics. Geocoded data on publications from the Scopus bibliographic database were used. In the course of the study the hypotheses of “Moscow-centricity” and “St. Petersburg-centricity” of the knowledge domain of the macroregion are tested, the influence of the factor of geographical proximity and the role of the diversity of interregional ties are evaluated, and the “heights-lowlands” of the landscape are revealed. The results of the research have shown a high degree of connectivity between the regions of the Big South of Russia in the research area. The hypothesis about the presence of several centers of gravity of scientific activity in the macroregion was confirmed. First of all, the peaks of the “scientific ridge” of the Big South form Rostov oblast with the largest urban agglomeration in the south of the country, the Rostov urban agglomeration, as well as the Krasnodar krai and Volgograd oblast. The hypothesis of the existence of several centers of scientific activity in the macroregion was confirmed. The influence of the factor of territorial proximity in the formation of research ties is not high and is manifested mainly in the southern Russian regions with relatively low indicators of research output (primarily, it is typical for national republics). Interregional research cooperation between advanced regions is not limited to immediate geographical proximity but is due to a combination of non-territorial factors. The “Moscow-centricity” of the scientific agenda of the regions of the Big South of Russia is true for most of the southern regions of the Russian Federation, which is particularly pronounced in regions with low internal scientific potential and in new regions undergoing a period of transformation of their scientific systems.

Evil and allies: Opportunistic gulls as both spreaders and sentinels of antibiotic‐resistant bacteria in human‐transformed landscapes

Abstract Human‐transformed residuals, especially those derived from human waste (dumps), farmland, and livestock are involved in the emergence of antibiotic‐resistant bacteria (ARB) in the environment. Wildlife can act as vectors of ARB dispersal through different environments, but also as sentinels to detect the early spread and determine ARB sources. The development of integrated monitoring programmes focused on wildlife would help to anticipate the risks of ARB to humans and livestock. We used the yellow‐legged gull (Larus michahellis) as a model species to investigate and monitor the spatial patterns of ARB dispersal across an extensive farmland region located in northeastern Spain (Lleida). By integrating GPS tracking data and ARB clinical testing for 26 individuals within a network analysis framework, we modelled the risk of spatial pathogen spread through faeces during the bacteria‐transmission latency period (16 days after sample collection). Additionally, we created a connectivity network to determine the main sources of ARB in the area, focusing on three main habitats of special risk for infection: dumps, livestock facilities, and irrigation ponds. Seven individuals were infected by Escherichia coli, with one also co‐infected with Listeria monocytogenes and Salmonella spp. Potential pathogen dispersal distances ranged from 1.13 km to 23.13 km from the breeding colony. Our network analyses revealed 54 main nodes (i.e. high‐risk habitats recurrently visited by tracked gulls) and 1182 links among them. Our findings revealed a high degree of connectivity between the breeding area, located in a shallow lake, and nearby dumps, highlighting them as significant contributors to ARB dispersal. Synthesis and applications: The integration of GPS data, pathogen testing and network analyses can shed further light on pathogen dynamics by creating spatial risk maps and identifying ARB sources. In combination with complementary molecular epidemiology techniques within a One Health framework, our approach can emerge as an important tool for monitoring ARB dynamics within highly human‐transformed ecosystems. This may empower managers for the development of targeted ARB monitoring programmes and effective mitigation strategies, ultimately improving both animal and public health.

A Network Pharmacology Identified Metastasis Target for Oral Squamous Cell Carcinoma Originating from Breast Cancer with a Potential Inhibitor from F. sargassaceae

Abstract: This study aimed to identify specific therapeutic targets for oral squamous cell carcinoma (OSCC) that metastasize from breast cancer (BC) by using network pharmacology. The Gene Expression Omnibus for OSCC and BC served as the source of gene expression datasets and their analysis. Upregulated genes and the common intersecting genes of these cancers were determined along with that of the phytochemicals of F. sargassum to predict the pharmacological targets. Further, gene enrichment analysis revealed that their metastasis signature and metastasis targets were determined via a protein interaction network. Molecular docking and pharmacokinetic screening determined the potential therapeutic phytochemicals against the targets. The interaction network of 39 genes thus identified encoding proteins revealed HIF1A as a prominent metastasis target due to its high degree of connectivity and its involvement in cancer-related pathways. Molecular docking showed a strong binding affinity of isonahocol D2, a sargassum-derived compound with HIF1A, presenting a binding energy of −7.1 kcal/mol. Further, pharmacokinetic screening showed favorable ADME properties and molecular dynamics simulations showed stable interactions between isonahocol D2 and HIF1A, with significant stability over 100 ns. This study’s results emphasized that isonahocol D2 is a promising therapeutic candidate against HIF1A in OSCC metastasized from breast cancer in translational medicine.

Shaping the general resilience of green infrastructure through integrating structures, functions, and connections

Global climate change has necessitated the implementation of green infrastructure that is resilient in a manner of sustainable development. The current understanding of green infrastructure resilience is hindered by the divergence of generic properties and performance in adapting to uncertain disturbances. This study develops an operational methodology that integrates structural and functional properties of green infrastructure, and their connections to shape the general resilience. A further empirical study is conducted in the context of Shenzhen City, where the effectiveness of resilient connections is correlated with the distribution of waterlogging. We demonstrate that green infrastructure present different levels of resilience in terms of its structural composition and functional performance. The Shenzhen city shows a high capacity to maintain soil retention stability, but a feeble capacity regarding water yield and gross primary productivity. The resilient connections of green infrastructure are highly centralized, with a few pivotal nodes performing a high degree of connectivity. It shows that a total of 52.2% of resilient lines are identified as belonging to the fourth level but linking the majority of the nodes. Enhancing the general resilience of green infrastructure could facilitate its adaptation to specific disturbances such as waterlogging. When correlated the resilient connections of green infrastructure with the distribution of waterlogging, a distance of 1.6 km from the waterlogging points is significantly identified where the residuals of the entropy index display the lowest variance. As the distance increases, the composite entropy index initially decreases and then increases. We suggest that the alignment of generic properties and specified performance of green infrastructure is essential in the pursuit of sustainable development.

Inhibitory neurons marked by a connectivity molecule regulate memory precision.

The CA3 region is central to hippocampal function during learning and memory and has a unique connectivity. CA3 pyramidal neurons are the targets of huge, excitatory mossy fiber synapses from DG axons and have a high degree of excitatory recurrent connectivity. Thus, inhibition likely plays an outsized importance in constraining excitation and shaping CA3 ensembles during learning and memory. Here, we investigate the function of a never-before studied set of dendrite-targeting, GABAergic neurons defined by expression of the synaptic adhesion molecule, Kirrel3. We discovered that activating Kirrel3-expressing GABAergic neurons specifically impairs memory discrimination and inhibits CA3 pyramidal neurons in novel contexts. Kirrel3 is required for DG-to-GABA synapse formation and variants in Kirrel3 are strong risk factors for neurodevelopmental disorders. Thus, our work suggests that Kirrel3-GABA neurons are a critical source of feed-forward inhibition from DG to CA3 during the encoding and retrieval of contextual memories, a function which may be specifically disrupted in some brain disorders.

The Co-pathogenic Target Gene CNTN1 Involved in Coronary Artery Disease and Pulmonary Arterial Hypertension Has Potential for Diagnosis of Coronary Artery Disease.

We aimed to find a gene for coronary artery disease (CAD) early diagnosis by detecting co-pathogenic target gene involved in CAD and pulmonary arterial hypertension (PAH).
 
 Methods: Datasets were obtained from the Gene Expression Omnibus (GEO) database, including GSE113079, GSE113439, and GSE12288, to investigate gene expression patterns in cardiovascular diseases. Weighted Gene Co-expression Network Analysis (WGCNA) was performed to identify gene modules associated with clinical traits. Differential gene expression analysis and functional enrichment analysis were carried out. Protein-protein interaction (PPI) networks were constructed. JASPAR database and FIMO tool were utilized to predict transcription factor (TF) binding sites.
 
 Results: Fifteen key genes were identified in CAD and PAH, with CNTN1 being prioritized for further investigation due to its high connectivity degree. Upstream regulation analysis identified potential TFs (DRGX, HOXD3, and RAX) and 7 miRNAs targeting CNTN1. The expression profile of CNTN1 was significantly upregulated in CAD samples, and ROC analysis indicated potential diagnostic value for CAD. CMap database analysis predicted potential targeted drugs for CAD.
 
 Conclusion: CNTN1 was detected as a co-pathogenetic gene for CAD and PAH. It is highly expressed in CAD patients and has potential value for CAD diagnosis. CNTN1 is potentially regulated by 3 TFs and 7 miRNAs.

Comparison of methods to calculate groundwater recharge for karst aquifers under a Mediterranean climate

Karst aquifers can be particularly vulnerable to human activities and climate change due to their relatively high degree of connection with the surface. This study utilized an ensemble of event-based recharge calculation methods to address the problem of structural uncertainty for the example of the Western Mountain Aquifer (WMA), a Mediterranean karst aquifer located in Israel and the West Bank. Spatially distributed recharge estimates derived from the Soil and Water Assessment Tool (SWAT) and the process-based infiltration model (PIM) were compared to site-specific, empirical regression models. The SWAT and PIM mean annual recharge estimates ranged from 32–34.6% of precipitation, almost equating to the results of empirical regression models (32–36%). Future recharge predictions under the influence of climate change were quantified by parameterizing the SWAT and PIM methods with a downscaled regional climate model of Israel. SWAT predicts a 23% decrease in recharge by 2051–2070 relative to 1981–2001. In contrast, PIM shows a 9% decrease, possibly due to the representation of infiltration through preferential flow pathways and exclusion of surface runoff processes. These divergent projections underline key methodological differences in the representation of hydrological processes. Nevertheless, both methods effectively provided good estimates of groundwater recharge. The recharge rates estimated from the various methods were integrated into MODFLOW to assess their relative impacts on groundwater storage dynamics. The ensemble of MODFLOW projected groundwater storage outputs can provide guidance for sustainable groundwater management in the region.

Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs.

Endometriosis is a gynecological disorder among reproductive-aged women. Recent epidemiological investigations suggest endometriosis increases the risk of endometrial cancer. However, the molecular entity leading to endometriosis-to-endometrial cancer is largely unknown. This study aimed to combine a variety of computational approaches to identify the key therapeutic target promoting endometriosis-to-endometrial cancer and screen potential inhibitors against target to prevent cancer development. Our systematic investigations, includes transcriptomic profiling, protein network, pharmacophore modeling, docking, binding free energy calculation, dynamics simulation, and quantum mechanics. The gene expression analysis on endometriosis and endometrial cancer was performed and showed 108 shared upregulated genes in both conditions. Further construction of interaction network with 108 genes showed intercellular adhesion molecule 1 (ICAM1) to be a crucial molecule with a high degree of connectivity that influences vital mechanisms related to cancer pathways. We then generated ligand-based pharmacophore models using established ICAM1 inhibitors. Among the models, the ADRRR_8 pharmacophore exhibited a robust area under curve (AUC = 0.83), was employed to screen 1739 anti-cancer drugs. On screening, 421 anti-cancer drugs displayed ICAM1-inhibiting pharmacophore features. Further, the docking of 421 drugs with ICAM1 showed lanreotide (-7.80 kcal/mol) with better affinity than the reference ICAM1 inhibitor (-3.59 kcal/mol). Further validation though binding free energy and dynamics simulation of the lanreotide-ICAM1 complex showed a high binding affinity of -55.90 kcal/mol and contributed stable confirmation. According to quantum chemical calculations, lanreotide's electronic properties favour ICAM1 binding with highest occupied molecular orbital was -6.91 eV and lowest unoccupied molecular orbital was -3.93 eV. Our study supports using lanreotide to treat endometriosis, which could delay or prevent endometrial cancer. These predictions need to be confirmed and examined to determine the use of lanreotide in endometriosis treatment.

The Roles of Alpha, Beta, and Functional Diversity Indices in the Ecological Connectivity between Two Sub-Antarctic Macrobenthic Assemblages

The study of ecological connectivity is a global priority due to the important role it plays in the conservation of diversity. However, few studies in this context have focused on marine benthic ecosystems. To address this issue, the present work determines the ecological connectivity between two sub-Antarctic macrobenthic assemblages through assessment of the α-, β-, and functional diversity indices. Samples were collected using a van Veen grab at stations located in Bahia Inútil and Seno Almirantazgo. The ecological analysis was based on a total of 113 invertebrate taxa. The mean abundance values were lower in Bahia Inútil (888.9 ± 26.8 ind m−2) than in Seno Almirantazgo (1358.6 ± 43.4 ind m−2). While the mean α-diversity values showed significant differences between assemblages, β- and functional diversity indices presented no significant differences. These results indicate that, despite the distance (56 km) separating the two basins from each other, there is a high degree of connectivity at the functional level between the assemblages due to the high number of shared species and their functional traits. The species most responsible for this observation were the polychaetes Capitela capitata and Aricidia (Acmira) finitima, as well as the bivalves Nucula pisum and Yoldiella sp. 1. In terms of functional biodiversity, species characterized as omnivorous and with lecithotrophic larval development were mostly responsible for connectivity between assemblages. These results suggest the importance of including β- and functional diversity indices as criteria in the future planning of marine protected areas for the maintenance of marine ecosystem integrity.

Connectivity among the returns of sectoral indices of the Brazilian capital market

PurposeAs specific objectives, we intend to: (1) measure the connectivity between the spillovers of returns from the financial and nonfinancial sectors of the Brazilian stock market; (2) estimate the spillovers of individual returns for each sector to identify periods of higher and lower profits over a period of around eight years; (3) investigate the existence of relationships between these repercussions between pairs of sectoral indices, evaluating how much each specific sector transfers to each other and the market as a whole and (4) examine whether the connectivity of the Brazilian stock market itself and future interest rates in the USA and Brazil as well as the risk of the Brazilian economy, were explanatory variables of the dynamics of interdependence in the returns of these indices.Design/methodology/approachWith a daily series of closing prices of sectoral indices from March 3, 2015, until June 21, 2023, we researched eight of the most relevant sectoral indices on the São Paulo Stock Exchange (B3). With this data, we estimate the Diebold–Yilmaz spillover index and frequency decompositions of Barunik–Krehlik.FindingsThe conclusions indicate that there is an overall connection of 66% in the financial and nonfinancial sectoral indices, with a peak of 83%. The consumer, energy and public services sectors stand out as significant sources of primary spillovers. When we classified secondary effects into periods, we saw that the shocks dissipated as time passed and the returns of the commodity index remained resilient across all periods.Originality/valueOur conclusions highlight the influence of three main factors in sectors with a high degree of connectivity: periods of increased uncertainty; negative externalities in post-crisis periods and the impact of financial news on market sentiment. We think this study provides information that can be useful for policymakers, investors, investment portfolio managers, economists (financial, monetary and industrial), investment consultants and researchers who are interested in the complex interconnection among emerging market stock indices.

Potential Mechanism and Therapeutic Targets of Polymyositis.

To investigate the variability in the expression profile of genes associated with polymyositis (PM), explore the potential molecular mechanisms underlying PM, and predict novel targets for intervention. Descriptive study. Place and Duration of the Study: Department of Rheumatology, Taizhou Municipal Hospital, Taizhou, China, from August to November 2023. Three microarray datasets (GSE3112, GSE39454, and GSE128470) were extracted from the gene expression omnibus (GEO). The analysis of this research involved identifying the differentially expressed genes (DEGs) in PM compared to normal samples. Enrichment analysis, gene-microRNA, gene-transcription factor (TF), and protein-protein interaction (PPI) network studies were conducted to identify hub genes and relevant pathways. Additionally, the drug-gene interaction database (DGIdb) was used to predict therapeutic medications. Eighty-eight DEGs were identified. The enrichment analysis results highlighted the significant involvement of downregulated DEGs in antigen processing and presentation. Based on the PPI networks, seven hub genes with high connectivity degrees were selected including a cluster of differentiation 74 (CD74), human leukocyte antigen (HLA)-DPA1, HLA-B, guanylate-binding protein 1 (GBP1), recombinant 2', 5'-oligoadenylate synthetase 1 (OAS1), HLA-C, and HLA-E. This research screened-out core genes, projected prospective therapeutic medications, discovered DEGs between PM and normal samples, and offered fresh perspectives for additional research into the possible mechanism and therapeutic targets of PM. Polymyositis, DEGs, Hub genes, Bioinformatics, Potential therapeutic agents.

How Does University-Industry Collaboration Drives the Green Innovation?

Breaking through the company’s own green knowledge barriers through school-enterprise cooperation has become an important means for companies to expand market competitive advantages and environmental governance. This article uses China’s non-financial listed company data from 2010 to 2021 to study the causal effect of school-enterprise cooperation on corporate green innovation. The results passed a series of robustness tests and confirmed that school enterprise cooperation can improve the level of green innovation of enterprises. This paper also uses the instrumental variable method to mitigate the causal relationship between the two. The results show that school-enterprise cooperation can still significantly improve corporate green innovation. The results of the mechanism test confirm that school-enterprise cooperation will promote corporate green innovation by reducing corporate green innovation risks and easing corporate financing constraints. At the same time, the heterogeneity analysis results show that school-enterprise cooperation has a better effect on improving green innovation for enterprises in heavily polluting industries, enterprises in years with low economic policy uncertainty, and enterprises with a high degree of government-enterprise connection. The findings of this article help to understand the intrinsic mechanism between school-enterprise cooperation and corporate green innovation, and confirm that school-enterprise cooperation can improve the climate and environmental innovation system, which has important practical significance for the construction of the industry-university-research system.

Integrative study of transcriptome and microbiome to reveal the response of Rhododendron decorum to cadmium stress

The anomalies of cadmium (Cd) in karst region pose a severe threat to plant growth and development. In this study, the responses of Rhododendron decorum to Cd stress were investigated at physiological, molecular, and endophytic microbial levels, and the potential correlation among these responses was assessed. The Cd stress impeded R. decorum growth and led to an increase in malondialdehyde (MDA) and hydrogen peroxide (H2O2) levels, as well as enhanced superoxide dismutase (SOD) and catalase (CAT) activities. Meanwhile, Cd stress increased the Cd (up to 80 times compared to the control), sodium (Na), aluminum (Al), and zinc (Zn) contents, while decreased the magnesium (Mg) and manganese (Mn) contents in R. decorum leaves. Transcriptome suggested that Cd significantly regulated the pathways including “protein repair”, “hormone-mediated signaling pathway”, and “ATP-binding cassette (ABC) transporters”. Additionally, q-PCR analysis showed that Cd stress significantly up-regulated the expressions of ABCB19-like and pleiotropic drug resistance, while down-regulated the expressions of indole-3-acetic acid-amido synthetase and cytokinin dehydrogenase. The Cd stress influenced the composition of endophytic microbial communities in R. decorum leaves and enhanced the interspecific bacterial associations. Furthermore, the bacterial genera Achromobacter, Aureimonas and fungal genus Vishniacozyma exhibited a high degree of connectivity with other nodes in networks constructed by the metal element contents, differentially expressed genes (DEGs), and microbial communities, respectively. These findings provide a comprehensive insight into the response of R. decorum to Cd-induced stress, which might facilitate the breeding of the Cd-tolerant R. decorum.

Metastable cellular structures govern localized corrosion damage development in additive manufactured stainless steel

The rapid solidification associated with additive manufacturing (AM) leads to complex microstructures with peculiar features amongst which cellular solidification structures are the most remarkable. These metastable structures possess a clear segregation pattern dictated by the solidification pathway of the alloy and are bounded by dislocation walls. While they confer exceptional strength and ductility to AM 316L stainless steel, their effect on localized corrosion in chloride environments remains to be established. Here, we employ correlative electron microscopy to reveal coupled chemical, electrochemical, and crystallographic effects on localized corrosion attack and its development. We show that the Cr and Mo-depleted interior of the cellular solidification structures dissolves selectively, giving rise to an intricate damage morphology, that is directly related to the underlying crystallographic orientation. Whereas surface observations only reveal apparently shallow micrometer-size cavities, 3D tomography via focused ion beam serial-sectioning shows a high degree of connectivity between these features underneath the surface. We reveal this intricate morphology, propose a formation mechanism, and discuss alloy design guidelines to mitigate this phenomenon.

Low genetic variability and high isolation of a post-harvest South American pinniped population as revealed by genome-wide single nucleotide polymorphisms

Abstract Otaria flavescens has been one of the most heavily exploited pinnipeds during the last 200 years, with depletion of ~90% in some colonies. After the prohibition on sealing in South America, populations stabilized except for the Uruguayan population, which showed a constant decrease. The underlying causes of its decline are unknown. This study used genome-wide single nucleotide polymorphisms to assess the variability and connectivity of some of the most overexploited sea lion colonies in the Atlantic Ocean. Our results revealed low allelic richness, nucleotide diversity, and heterozygosity in the Uruguayan population and evidence of complete isolation from the Argentinean populations under study. In contrast, the Patagonian populations showed a high degree of connectivity, which could explain their recovery and high levels of diversity at present. Our study highlights the critical situation of the Uruguayan sea lion population, emphasizing the need for maintaining continuous conservation efforts in the region.

Monolithically Defined Wireless Fully Implantable Nervous System Interfaces.

Evolution of implantable neural interfaces is critical in addressing the challenges in understanding the fundamental working principles and therapeutic applications for central and peripheral nervous systems. Traditional approaches utilizing hermetically sealed, rigid electronics and detached electrodes face challenges in power supply, encapsulation, channel count, dispersed application location, and modality. Employing thin-film, wirelessly powered devices is promising to expand capabilities. Devices that forego bulky power supplies, favoring a configuration where electronics are integrated directly onto thin films, reduce displacement volumes for seamless, fully implantable interfaces with high energy availability and soft mechanics to conform to the neuronal target. We discuss 3 device architectures: (1) Highly miniaturized devices that merge electronics and neural interfaces into a single, injectable format; (2) Interfaces that consolidate power, computation, and neural connectivity on a thin sheet applied directly to the target area; (3) A spatially dislocated approach where power and computation are situated subdermally, connected via a thin interconnect to the neural interface.Each has advantages and constraints in terms of implantation invasiveness, power capturing efficiency, and directional sensitivity of power delivery. In powering these devices, near-field power delivery emerges as the most implemented technique. Key parameters are size and volume of primary and secondary antennas, which determine coupling efficiency and power delivery. Based on application requirements, ranging from small to large animal models, subjects require system level designs. Material strategies play a crucial role; monolithic designs, with materials like polyimide substrates, enable scalability with high performance. This contrasts with established hermetic encapsulation approaches that use a stainless steel or titanium box with passthroughs that result in large tissue displacements and prohibit intimate integration with target organ systems. Encapsulation, particularly with parylene, enables longevity and effectiveness; more research is needed to enable human lifetime operation. Implant-to-ambient device communication, focusing on strategies compatible with well-established standards and off-the-shelf electronics, is discussed with the goal of enabling seamless system integration, reliability, and scalability. The interface with the central nervous system is explored through various wireless, battery-free devices capable of both stimulation (electrical and optogenetic) and recording (photometric and electrochemical). These devices show advanced capabilities for chronic studies and insights into neural dynamics. In the peripheral nervous system, stimulation devices for applications, such as spinal and muscle stimulation, are discussed. The challenges lie in the mechanical and electrochemical durability. Examples that successfully navigate these challenges offer solutions for chronic studies in this domain. The potential of wireless, fully implantable nervous system interfaces using near field resonant power transfer is characterized by monolithically defined device architecture, providing a significant leap toward seamless access to the central and peripheral nervous systems. New avenues for research and therapeutic applications supporting a multimodal and multisite approach to neuromodulation with a high degree of connectivity and a holistic approach toward deciphering and supplementing the nervous system may enable recovery and treatment of injury and chronic disease.

From desert flora to cancer therapy: systematic exploration of multi-pathway mechanisms using network pharmacology and molecular modeling approaches.

Ovarian cancer, often labeled a "silent killer," remains one of the most compelling and challenging areas of cancer research. In 2019 alone, a staggering 222,240 new cases of ovarian cancer were reported, with nearly 14,170 lives tragically lost to this relentless disease. The absence of effective diagnostic methods, increased resistance to chemotherapy, and the heterogeneous nature of ovarian cancer collectively contribute to the unfavorable prognosis observed in the majority of cases. Thus, there is a pressing need to explore therapeutic interventions that offer superior efficacy and safety, thereby enhancing the survival prospects for ovarian cancer patients. Recognizing this potential, our research synergizes bioinformatics with a network pharmacology approach to investigate the underlying molecular interactions of Saudi Arabian flora (Onopordum heteracanthum, Acacia ehrenbergiana, Osteospermum vaillantii, Cyperus rotundus, Carissa carandas, Carissa spinarum, and Camellia sinensis) in ovarian cancer treatment. At first, phytoconstituents of indigenous flora and their associated gene targets, particularly those pertinent to ovarian cancer, were obtained from open-access databases. Later, the shared targets of plants and diseases were compared to identify common targets. A protein-protein interaction (PPI) network of predicted targets was then constructed for the identification of key genes having the highest degree of connectivity among networks. Following that, a compound-target protein-pathway network was constructed, which uncovered that, namely, hispidulin, stigmasterol, ascorbic acid, octopamine, cyperene, kaempferol, pungenin, citric acid, d-tartaric acid, beta-sitosterol, (-)-epicatechin gallate, and (+)-catechin demonstrably influence cell proliferation and growth by impacting the AKT1 and VEGFA proteins. Molecular docking, complemented by a 20-ns molecular dynamic (MD) simulation, was used, and the binding affinity of the compound was further validated. Molecular docking, complemented by a 20-ns MD simulation, confirmed the binding affinity of these compounds. Specifically, for AKT1, ascorbic acid showed a docking score of -11.1227kcal/mol, interacting with residues Ser A:240, Leu A:239, Arg A:243, Arg C:2, and Glu A:341. For VEGFA, hispidulin exhibited a docking score of -17.3714kcal/mol, interacting with Asn A:158, Val A:190, Gln B:160, Ser A:179, and Ser B:176. To sum up, both a theoretical and empirical framework were established by this study, directing more comprehensive research and laying out a roadmap for the potential utilization of active compounds in the formulation of anti-cancer treatments.

Analysis of Genetic Diversity in Greengram (Vigna radiata L. Wilczek)

The current study titled “Analysis of genetic diversity in green gram [Vigna radiata (L.) Wilczek]” was carried out at Center for Crop Research (C.R.C.), Sardar Vallabhbhai Patel University of Agriculture & Technology, Meerut. A set of twenty five mungbean genotypes were examined to investigate the essence and extend of divergence of genes using Mahalanobis’s D2 Statistics on twelve critical quantitative attributes. The study material was assessed using Randomized Block Design (RBD) with three replication plots of two rows of 4 meter length. Out of every replication, five plants were selected at random, marked, and observations were recorded for twelve quantitative attributes. Analysis of variance showed that there was significant variation among all characters examined. The twenty-five genotypes of mungbean have been split into seven distinct clusters. With seven genotypes apiece, Cluster I and Cluster IV were determined to be the largest. The intra cluster distance was maximum for Cluster IV. The maximum inter cluster distance between cluster V and cluster II suggests that the genotypes in these clusters doesn't correlate with one another and the minimal inter-cluster distance between cluster V and cluster IV demonstrates a high degree of connection between the genotypes in these clusters. Based on high inter cluster distances, hybridization programme could be taken up between the varieties of cluster II (Pusa Vaishali, IPM-02-19, IPM 02-19, OMG-1045, VBG-04-008) and cluster V (Pusa-0871, Pusa-0891, SMM-15-72, PDM-262).Hence, these nine genotypes are recognized as promising progenitors and can be employed in further breeding programme. Plant height, number of branches/plants, number of pods/plant, number of pods/clusters, pod length, biological yield, harvest index and seed yield per plant are vital for genetic diversity and were recognized as significant contributors to genetic divergence.