Source apportionment and emission projections of heavy metals from traffic sources in India: Insights from elemental and Pb isotopic compositions.

The study investigates the sources of metals in urban road dusts using elemental concentration and Pb isotopic ratios. The elemental concentrations are also utilized to determine the present heavy metal emissions as well as projected emissions till 2045. Bayesian mixing model for source apportionment highlights the significant contributions of both exhaust and non-exhaust sources to the metal-enriched urban road dusts, with each contributing approximately 40 %. Emission analysis reveals that India's projected electric vehicle (EV) penetration may not be sufficient to suppress the metal emissions from vehicular exhausts. Further challenge is posed by high metal concentrations in the non-exhaust sources, that dominates the emission of some metals compared to exhaust sources. If the metal concentrations remain unchanged, the emission analysis predicts alarming increases in total emissions from all the exhaust and non-exhaust sources by 174 %, 176 %, 163 % and 184 % for Ni, Cu, Zn and Pb, respectively, from 2022 to 2045. Thus, it is crucial to reduce the metal concentrations in traffic emission sources and also impose better regulatory measures to improve the urban metal pollution scenario.

W18O49 Nanofibers Functionalized with Graphene as a Selective Sensing of NO2 Gas at Room Temperature.

Recent trends in two-dimensional (2D) graphene have demonstrated significant potential for gas-sensing applications with significantly enhanced sensitivity even at room temperature. Herein, this study presents fabrication of distinctive gas sensor based on one-dimensional (1D) W18O49 nanofibers decorated 2D graphene, specifically coated on copper (Cu)-based interdigitated electrodes formed by DC sputtering, which can selectively detect NO2 gas at room temperature. The sensor device fabricated using W18O49/Gr1.5% (i.e., W18O49 nanofibers hybrid nanocomposite with 1.5 wt % graphene) displays excellent overall sensing performance at 27 °C (room temperature) with high response (∼150-160 times) to NO2 gas. The W18O49/Gr1.5%-based sensor device reflects the highly selective detection toward NO2 gas among various gases with quick response time of 3 s and speedy recovery in 6 s. The limit of detection of ∼0.3 ppm with excellent reproducibility and stability for 3 months in all weather conditions (tested in humidity conditions 20-97%) are superior features of the device under test. However, W18O49/Gr3% displayed higher selectivity for NO2 but resulted with comparatively reduced sensitivity than W18O49/Gr1.5% sensor. The enhanced sensing performance could be attributed to the graphene content to decorate the nanofibers on it, oxygen vacancies/defects, and the contacts between the sensing material and Cu. This favorable synthesis and properties of self-assembled hybrid composite materials provide a potential utilization for detecting NO2 gas in environmental safety inspection.

Surgical Technique for Compartmental Resection of T4b Gingivobuccal Cancer.

Management of advanced gingivo-buccal complex cancers involving the masticatory space (T4b) is often managed by compartment resection. The oncological safety of the procedure is now clearly established. Based on the origin and epicenter of the tumor there are two classes of compartmental resection. Those tumors arising from the tuberosity of the maxilla and/or upper gingival sulcus region; the resection involves the tumor, posterior maxilla, and the ipsilateral infratemporal fossa. These tumors can be resected by mandibulotomy approach, preserving the mandible. This constitutes class-1 infratemporal fossa resection. The class-2 infratemporal fossa resection is applied for those tumors arising from the retromolar trigone and/or lower gingivo-buccal sulcus region. In this class, the mandible and often the overlying cheek skin needs to be sacrificed, in addition to the contents of the infratemporal fossa and the posterior maxilla. Both the classes of resections are carried out in an orderly fashion following well-defined steps. These sequential steps maximize the exposure of inaccessible structures, enables protection of critical structures as well as minimizes blood loss. This manuscript describes the surgical steps for the two classes of compartmental resection of the infratemporal fossa for advanced gingivo-buccal complex cancers involving the masticatory space.

Selection signatures for high altitude adaptation in livestock: A review.

High altitude adapted livestock species (cattle, yak, goat, sheep, and horse) has critical role in the human socioeconomic sphere and acts as good source of animal source products including milk, meat, and leather, among other things. These species sustain production and reproduction even in harsh environments on account of adaptation resulting from continued evolution of beneficial traits. Selection pressure leads to various adaptive strategies in livestock whose footprints are evident at the different genomic sites as the "Selection Signature". Scrutiny of these signatures provides us crucial insight into the evolutionary process and domestication of livestock adapted to diverse climatic conditions. These signatures have the potential to change the sphere of animal breeding and further usher the selection programmes in right direction. Technological revolution and recent strides made in genomic studies has opened the routes for the identification of selection signatures. Numerous statistical approaches and bioinformatics tools have been developed to detect the selection signature. Consequently, studies across years have identified candidate genes under selection region found associated with numerous traits which have a say in adaptation to high-altitude environment. This makes it pertinent to have a better understanding about the selection signature, the ways to identify and how to utilize them for betterment of livestock populations as well as farmers. This review takes a closer look into the general concept, various methodologies, and bioinformatics tools commonly employed in selection signature studies and summarize the results of recent selection signature studies related to high-altitude adaptation in various livestock species. This review will serve as an informative and useful insight for researchers and students in the field of animal breeding and evolutionary biology.

Comparative transcriptome profile of embryos at different developmental stages derived from somatic cell nuclear transfer (SCNT) and in-vitro fertilization (IVF) in riverine buffalo (Bubalus bubalis).

Somatic cell nuclear transfer (SCNT) is a very important reproductive technology with many diverse applications, such as fast multiplication of elite animals, the production of transgenic animals and embryonic stem (ES) cells. However, low cloning efficiency, a low live birth rate and the abnormally high incidence of abnormalities in the offspring born are attributed to incomplete or aberrant nuclear reprogramming. In SCNT embryos, the aberrant expression pattern of the genes throughout embryonic development is responsible for the incomplete nuclear reprogramming. The present study was carried out to identify the differential gene expression (DEGs) profile and molecular pathways of the SCNT and IVF embryos at different developmental stages (2 cell, 8 cell and blastocyst stages). In the present study, 1164 (2 cell), 1004 (8 cell) and 530 (blastocyst stage) DEGs were identified in the SCNT embryos as compared to IVF embryos. In addition, several genes such as ZEB1, GDF1, HSF5, PDE3B, VIM, TNNC, HSD3B1, TAGLN, ITGA4 and AGMAT were affecting the development of SCNT embryos as compared to IVF embryos. Further, Gene Ontology (GO) and molecular pathways analysis suggested, SCNT embryos exhibit variations compared to their IVF counterparts and affected the development of embryos throughout the different developmental stages. Apart from this, q-PCR analysis of the GDF1, TMEM114, and IGSF22 genes were utilized to validate the RNA-seq data. These findings contribute valuable insights about the different genes and molecular pathways underlying SCNT embryo development and offer crucial information for improving SCNT efficiency.

A synchronized symphony: Intersecting roles of ubiquitin proteasome system and autophagy in cellular degradation.

Eukaryotic cells have evolved dynamic quality control pathways and recycling mechanisms for cellular homeostasis. We discuss here, the two major systems for quality control, the ubiquitin-proteasome system (UPS) and autophagy that regulate cellular protein and organelle turnover and ensure efficient nutrient management, cellular integrity and long-term wellbeing of the plant. Both the pathways rely on ubiquitination signal to identify the targets for proteasomal and autophagic degradation, yet they use distinct degradation machinery to process these cargoes. Nonetheless, both UPS and autophagy operate together as an interrelated quality control mechanism where they communicate with each other at multiple nodes to coordinate and/or compensate the recycling mechanism particularly under development and environmental cues. Here, we provide an update on the cellular machinery of autophagy and UPS, unravel the nodes of their crosstalk and particularly highlight the factors responsible for their differential deployment towards protein, macromolecular complexes and organelles.

Hypoxia related genes modulate in similar fashion in skin fibroblast cells of yak (Bos grunniens) adapted to high altitude and native cows (Bos indicus) adapted to tropical climate during hypoxia stress.

The present study was conducted to understand transcriptional response of skin fibroblast of yak (Bos grunniens) and cows of Bos indicus origin to hypoxia stress. Six primary fibroblast cell lines derived from three individuals each of Ladakhi yak (Bos grunniens) and Sahiwal cows (Bos indicus) were exposed to low oxygen concentration for a period of 24 h, 48 h and 72 h. The expression of 10 important genes known to regulate hypoxia response such as HIF1A, VEGFA, EPAS1, ATP1A1, GLUT1, HMOX1, ECE1, TNF-A, GPx and SOD were evaluated in fibroblast cells of Ladakhi yak (LAY-Fb) and Sahiwal cows (SAC-Fb) during pre- and post-hypoxia stress. A panel of 10 reference genes (GAPDH, RPL4, EEF1A1, RPS9, HPRT1, UXT, RPS23, B2M, RPS15, ACTB) were also evaluated for their expression stability to perform accurate normalization. The expression of HIF1A was significantly (p < 0.05) induced in both LAY-Fb (2.29-fold) and SAC-Fb (2.07-fold) after 24 h of hypoxia stress. The angiogenic (VEGFA), metabolic (GLUT1) and antioxidant genes (SOD and GPx) were also induced after 24 h of hypoxia stress. However, EPAS1 and ATP1A1 induced significantly (p < 0.05) after 48 h whereas, ECE1 expression induced significantly (p < 0.05) at 72 h after exposure to hypoxia. The TNF-alpha which is a pro-inflammatory gene induced significantly (p < 0.05) at 24 h in SAC-Fb and at 72 h in LAY-Fb. The induction of hypoxia associated genes indicated the utility of skin derived fibroblast as cellular model to evaluate transcriptome signatures post hypoxia stress in populations adapted to diverse altitudes.

Inhibition Conversion of Aspirin into Salicylic Acid in Presence of Glycine.

Aspirin (AS) is a common drug having anti-pyretic and anti-inflammatory properties which is widely used in diverse medical conditions. The intake of AS may cause adverse effects such as gastrointestinal ulcer, tinnitus and Reye's syndrome. The adverse effects of AS arise due to conversion of AS into salicylic acid (SAL). Glycine (Gly) is a simplest non essential amino acid having anti-oxidative and anti-inflammatory effects. It also reduces the risk of obesity, hypertension, and diabetes mellitus. AS with Gly is well accepted form of the drug for the treatment of rheumatic conditions in comparisons to the bare AS. In the present work using UV-Visible absorption, fluorescence and DFT/ TD-DFT techniques confirmed that in presence of Gly inhibited the conversion of AS into SAL effectively.

Nonwoven fiber meshes for oxygen sensing.

Accurate oxygen sensing and cost-effective fabrication are crucial for the adoption of wearable devices inside and outside the clinical setting. Here we introduce a simple strategy to create nonwoven polymeric fibrous mats for a notable contribution towards addressing this need. Although morphological manipulation of polymers for cell culture proliferation is commonplace, especially in the field of regenerative medicine, non-woven structures have not been used for oxygen sensing. We used an airbrush spraying, i.e. solution blowing, to obtain nonwoven fiber meshes embedded with a phosphorescent dye. The fibers serve as a polymer host for the phosphorescent dye and are shown to be non-cytotoxic. Different composite fibrous meshes were prepared and favorable mechanical and oxygen-sensing properties were demonstrated. A Young's modulus of 9.8 MPa was achieved and the maximum oxygen sensitivity improved by a factor of ∼2.9 compared to simple drop cast film. The fibers were also coated with silicone rubbers to produce mechanically robust sensing films. This reduced the sensing performance but improved flexibility and mechanical properties. Lastly, we are able to capture oxygen concentration maps via colorimetry using a smartphone camera, which should offer unique advantages in wider usage. Overall, the introduced composite fiber meshes show a potential to significantly improve cell cultures and healthcare monitoring via absolute oxygen sensing.

CARDPSoML: Comparative approach to analyze and predict cardiovascular disease based on medical report data and feature fusion approach.

Background and Aims: Diabetes patients are at high risk for cardiovascular disease (CVD), which makes early identification and prompt management essential. To diagnose CVD in diabetic patients, this work attempts to provide a feature-fusion strategy employing supervised learning classifiers. Methods: Preprocessing patient data is part of the method, and it includes important characteristics connected to diabetes including insulin resistance and blood glucose levels. Principal component analysis and wavelet transformations are two examples of feature extraction techniques that are used to extract pertinent characteristics. The supervised learning classifiers, such as neural networks, decision trees, and support vector machines, are then trained and assessed using these characteristics. Results: Based on the area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy, these classifiers' performance is closely evaluated. The assessment findings show that the classifiers have a good accuracy and area under the receiver operating characteristic curve value, suggesting that the suggested strategy may be useful in diagnosing CVD in patients with diabetes. Conclusion: The recommended method shows potential as a useful tool for developing clinical decision support systems and for the early detection of CVD in diabetes patients. To further improve diagnostic skills, future research projects may examine the use of bigger and more varied datasets as well as different machine learning approaches. Using an organized strategy is a crucial first step in tackling the serious problem of CVD in people with diabetes.

A sensorised surgical glove to improve training and detection of obstetric anal sphincter injury: A preclinical study on a pig model.

OBJECTIVE: To create a sensorised surgical glove that can accurately identify obstetric anal sphincter injury to facilitate timely repair, reduce complications and aid training. DESIGN: Proof-of-concept. SETTING: Laboratory. SAMPLE: Pig models. METHODS: Flexible triboelectric pressure/force sensors were mounted onto the fingertips of a routine surgical glove. The sensors produce a current when rubbed on materials of different characteristics which can be analysed. A per rectum examination was performed on the intact sphincter of pig cadavers, analogous to routine examination for obstetric anal sphincter injuries postpartum. An anal sphincter defect was created by cutting through the vaginal mucosa and into the external anal sphincter using a scalpel. The sphincter was then re-examined. Data and signals were interpreted. MAIN OUTCOME MEASURES: Sensitivity and specificity of the glove in detecting anal sphincter injury. RESULTS: In all, 200 examinations were performed. The sensors detected anal sphincter injuries in a pig model with sensitivities between 98% and 100% and a specificity of 100%. The current produced when examining an intact sphincter and sphincter with a defect was significantly different (p < 0.001). CONCLUSION: In this preliminary study, the sensorised glove accurately detected anal sphincter injury in a pig model. Future plans include its clinical translation, starting with an in-human study on postpartum women, to determine whether it can accurately detect different types of obstetric anal sphincter injury in vivo.

Protocol for preparation of highly durable superhydrophobic bulks with hierarchical porous structures.

Superhydrophobic surfaces face challenges in comprehensive durability when used in extreme outdoor environments. Here, we present a protocol for preparing nanocomposite bulks with hierarchical structures using the template technique. We describe steps for using hybrid nanoparticles of polytetrafluoroethylene and multi-walled carbon nanotube to fill inside and dip on the polyurethane (PU) foam. We then detail procedures for its removal by sintering treatment. The extra accretion layer on the PU foam surface was highlighted to construct hierarchical porous structures. For complete details on the use and execution of this protocol, please refer to Wu et al.1.

The Effect of Enzymatic Treatment with Mutanase, Beta-Glucanase, and DNase on a Saliva-Derived Biofilm Model.

INTRODUCTION: The dental biofilm matrix is an important determinant of virulence for caries development and comprises a variety of extracellular polymeric substances that contribute to biofilm stability. Enzymes that break down matrix components may be a promising approach to caries control, and in light of the compositional complexity of the dental biofilm matrix, treatment with multiple enzymes may enhance the reduction of biofilm formation compared to single enzyme therapy. The present study investigated the effect of the three matrix-degrading enzymes mutanase, beta-glucanase, and DNase, applied separately or in combinations, on biofilm prevention and removal in a saliva-derived in vitro-grown model. METHODS: Biofilms were treated during growth to assess biofilm prevention or after 24 h of growth to assess biofilm removal by the enzymes. Biofilms were quantified by crystal violet staining and impedance-based real-time cell analysis, and the biofilm structure was visualized by confocal microscopy and staining of extracellular DNA (eDNA) and polysaccharides. RESULTS: The in vitro model was dominated by Streptococcus spp., as determined by 16S rRNA gene amplicon sequencing. All tested enzymes and combinations had a significant effect on biofilm prevention, with reductions of >90% for mutanase and all combinations including mutanase. Combined application of DNase and beta-glucanase resulted in an additive effect (81.0% ± 1.3% SD vs. 36.9% ± 21.9% SD and 48.2% ± 14.9% SD). For biofilm removal, significant reductions of up to 73.2% ± 5.5% SD were achieved for combinations including mutanase, whereas treatment with DNase had no effect. Glucans, but not eDNA decreased in abundance upon treatment with all three enzymes. CONCLUSION: Multi-enzyme treatment is a promising approach to dental biofilm control that needs to be validated in more diverse biofilms.

Heat stress adaptation in cows - Physiological responses and underlying molecular mechanisms.

Heat stress is a key abiotic stressor for dairy production in the tropics which is further compounded by the ongoing climate change. Heat stress not only adversely impacts the production and welfare of dairy cows but severely impacts the economics of dairying due to production losses and increased cost of rearing. Over the years, selection has ensured development of high producing breeds, however, the thermotolerance ability of animals has been largely overlooked. In the past decade, the ill effects of climate change have made it pertinent to rethink the selection strategies to opt for climate resilient breeds, to ensure optimum production and reproduction. This has led to renewed interest in evaluation of the impacts of heat stress on cows and the underlying mechanisms that results in their acclimatization and adaptation to varied thermal ambience. The understanding of heat stress and associated responses at various level of animal is crucial to device amelioration strategies to secure optimum production and welfare of cows. With this review, an effort has been made to provide an overview on temperature humidity index as an important indicator of heat stress, general effect of heat stress in dairy cows, and impact of heat stress and subsequent response at physiological, haematological, molecular and genetic level of dairy cows.

A Deep Learning Approach to Classify Surgical Skill in Microsurgery Using Force Data from a Novel Sensorised Surgical Glove.

Microsurgery serves as the foundation for numerous operative procedures. Given its highly technical nature, the assessment of surgical skill becomes an essential component of clinical practice and microsurgery education. The interaction forces between surgical tools and tissues play a pivotal role in surgical success, making them a valuable indicator of surgical skill. In this study, we employ six distinct deep learning architectures (LSTM, GRU, Bi-LSTM, CLDNN, TCN, Transformer) specifically designed for the classification of surgical skill levels. We use force data obtained from a novel sensorized surgical glove utilized during a microsurgical task. To enhance the performance of our models, we propose six data augmentation techniques. The proposed frameworks are accompanied by a comprehensive analysis, both quantitative and qualitative, including experiments conducted with two cross-validation schemes and interpretable visualizations of the network's decision-making process. Our experimental results show that CLDNN and TCN are the top-performing models, achieving impressive accuracy rates of 96.16% and 97.45%, respectively. This not only underscores the effectiveness of our proposed architectures, but also serves as compelling evidence that the force data obtained through the sensorized surgical glove contains valuable information regarding surgical skill.

Advancements in lanthanide-based perovskite oxide semiconductors for gas sensing applications: a focus on doping effects and development.

Lanthanide-based perovskite oxide semiconductors have garnered significant attention due to their exceptional electrical and sensing properties, making them promising candidates for gas sensing applications. This review paper focuses on developments and the impact of doping in lanthanide-based perovskite oxide semiconductors for gas sensing purposes. The review explores the factors influencing gas sensing performance, such as operating temperature, dopant selection, and target gas species. The role of dopants in enhancing gas sensing selectivity, sensitivity, response/recovery times, and stability is discussed in detail. Comparisons are drawn between doped perovskite oxide semiconductors, undoped counterparts, and other gas-sensing materials. Practical applications of lanthanide-based perovskite oxide semiconductor gas sensors are outlined, including environmental monitoring, industrial process control, and healthcare. The review also identifies current challenges and future perspectives in the field, such as the exploration of novel doping strategies and integration with emerging technologies like the Internet of Things (IoT). The findings emphasize the potential of these materials in advancing gas sensing technology and the importance of continued research in this field.