Palynological Investigations of the Miocene sediments from Murree formation of Pakistan: Evidence for Palaeoenvironment and Palaeoclimate interpretations.

The present study was carried out to investigate the palynoflora of Murree formation using microscopic techniques to understand the climatic changes and vegetation's evolution. In this palynological study, 31 samples were collected, analyzed, and then identified as palynomorphs using different previous published literature. The results of this study will be described in terms of the evolutionary history of plants and the depositional environment of the reported taxa in the study area. The botanical affinities and systematic description of the taxa were examined using light and scanning electron microscopy. The floral record identified Asteraceae as the dominant family and Pinus as a genus. Most of angiosperms i.e Fabaceae and Poaceae, have a poor fossil record but have an abundant palynological record in the study area. The highest polar diameter (75.75 µm), colpus length (34.5 µm) and colpus width (31 µm) were examined for the Convolvulus. Most of the taxa explained here had a wide geographical occurrence in Southeast Asia and show the abundance of angiosperms in the Miocene epoch. The palynological record of Holocene samples is important to know about the vegetation's origin and environmental fluctuations in the study area.

Excellent antibacterial and anti-inflammatory efficacy of amoxicillin by AgNPs and their conjugates synthesized using Micromeria biflora crude flavonoid extracts.

Antibacterial resistance is considered to be one of the major causes for mortality in coming years. In recent years green nanotechnology played a key role in addressing this problem. Biocompatible metal nanoparticles have gained popularity owing to their excellent therapeutic effects and minimal side effects. Method: We report the synthesis of AgNPs and their amoxicillin conjugates (Ag-amoxi) using Micromeria biflora crude flavonoid extracts. The physicochemical properties of the synthesized NPs and Ag-amoxi conjugates were systematically evaluated using scanning electron microscopy (SEM), energy dispersive X-ray (EDX) and X-ray diffraction (XRD) analysis, Fourier transform infrared (FTIR), and UV-visible (UV-Vis) spectroscopic techniques. Results: The average sizes of AgNPs and Ag-amoxi conjugates were 45 and 62 nm, respectively. We have also explored the antibacterial, antioxidant, anti-inflammatory, and analgesic properties of the AgNPs and Ag-amoxi conjugates through in vivo and in vitro analysis. The Ag-amoxi conjugates showed better antibacterial potential against Streptococcus Pneumoniae (S.P), Staphylococcus aureus (S.A), Pseudomonas aeruginosa (P.A), and Methicillin resistance Staphylococcus aureus (MRSA) strain both the drug and AgNPs. Similarly, in vivo anti-inflammatory studies revealed that both Ag-amoxi (68 %) and AgNPs (64 %) had strong anti-inflammatory effects, with (***p < 0.001) significance at a dose of 10 mg kg-1 body weight as compared to standard, amoxicillin (45 %), and flavonoids extract (48 %) at a dose of 100 mg kg-1. The findings of the antinociceptive activities (writhing and hot plate tests) demonstrated that the Ag-amoxi conjugates produced fewer writhing (15 in 20 s) and a shorter latency time of 22 s as compared to vehicle-treated (tramadol) animals, amoxicillin, and P.E at much lower doses. In vitro antioxidant studies revealed that the Ag-amoxi conjugate has the potential to be used as an antioxidant with an IC50 value of 43.58, compared with AgNPs (46.34), amoxicillin (58.17), compared to the standard of ascorbic acid (34.14). Conclusion: These results reveals that these biologically inspired AgNPs and Ag-amoxi conjugate could be used to improve antibiotic efficiency and could play a critical role in addressing the multidrug resistance problem in coming years.

Aggregated Pattern Classification Method for improving neural disorder stage detection.

BACKGROUND: Neurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmental stage, severity, and nervous system effects has limitations. Leveraging artificial intelligence (AI) and machine learning (ML) for pattern recognition provides a potent solution to address these challenges. Therefore, this study focuses on proposing an innovative approach-the Aggregated Pattern Classification Method (APCM)-for precise identification of neural disorder stages. METHOD: The APCM was introduced to address prevalent issues in neural disorder detection, such as overfitting, robustness, and interoperability. This method utilizes aggregative patterns and classification learning functions to mitigate these challenges and enhance overall recognition accuracy, even in imbalanced data. The analysis involves neural images using observations from healthy individuals as a reference. Action response patterns from diverse inputs are mapped to identify similar features, establishing the disorder ratio. The stages are correlated based on available responses and associated neural data, with a preference for classification learning. This classification necessitates image and labeled data to prevent additional flaws in pattern recognition. Recognition and classification occur through multiple iterations, incorporating similar and diverse neural features. The learning process is finely tuned for minute classifications using labeled and unlabeled input data. RESULTS: The proposed APCM demonstrates notable achievements, with high pattern recognition (15.03%) and controlled classification errors (CEs) (10.61% less). The method effectively addresses overfitting, robustness, and interoperability issues, showcasing its potential as a powerful tool for detecting neural disorders at different stages. The ability to handle imbalanced data contributes to the overall success of the algorithm. CONCLUSION: The APCM emerges as a promising and effective approach for identifying precise neural disorder stages. By leveraging AI and ML, the method successfully resolves key challenges in pattern recognition. The high pattern recognition and reduced CEs underscore the method's potential for clinical applications. However, it is essential to acknowledge the reliance on high-quality neural image data, which may limit the generalizability of the approach. The proposed method allows future research to refine further and enhance its interpretability, providing valuable insights into neural disorder progression and underlying biological mechanisms.

Uncovering the stochastic dynamics of solitons of the Chaffee-Infante equation.

In this paper, we apply stochastic differential equations with the Wiener process to investigate the soliton solutions of the Chaffee-Infante (CI) equation. The CI equation, a fundamental model in mathematical physics, explains concepts such as wave propagation and diffusion processes. Exact soliton solutions are obtained through the application of the modified extended tanh (MET) method. The obtained wave figures in 3D, 2D, and contour are highly localized and determine an individual frequency shift under the behavior of sharp peak, periodic wave, and singular soliton. The MET method shows to be a valuable analytical tool for obtaining soliton solutions, essential for understanding the dynamics of nonlinear wave phenomena. Numerical simulations enable us to explore soliton solutions in two and three dimensions, shedding light on their properties over time. Our results have wide applications in various domains, including stochastic processes and nonlinear dynamics, impacting advancements in physics, engineering, finance, biology, and beyond.

Subtractive Proteomics and Reverse-Vaccinology Approaches for Novel Drug Target Identification and Chimeric Vaccine Development against Bartonella henselae Strain Houston-1.

Bartonella henselae is a Gram-negative bacterium causing a variety of clinical symptoms, ranging from cat-scratch disease to severe systemic infections, and it is primarily transmitted by infected fleas. Its status as an emerging zoonotic pathogen and its capacity to persist within host erythrocytes and endothelial cells emphasize its clinical significance. Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to the B. henselae strain Houston-1. Exploring these aspects is crucial for targeted therapeutic strategies against this versatile pathogen. Using reverse-vaccinology-based subtractive proteomics, this research aimed to identify the most antigenic proteins for formulating a multi-epitope vaccine against the B. henselae strain Houston-1. One crucial virulent and antigenic protein, the PAS domain-containing sensor histidine kinase protein, was identified. Subsequently, the identification of B-cell and T-cell epitopes for the specified protein was carried out and the evaluated epitopes were checked for their antigenicity, allergenicity, solubility, MHC binding capability, and toxicity. The filtered epitopes were merged using linkers and an adjuvant to create a multi-epitope vaccine construct. The structure was then refined, with 92.3% of amino acids falling within the allowed regions. Docking of the human receptor (TLR4) with the vaccine construct was performed and demonstrated a binding energy of -1047.2 Kcal/mol with more interactions. Molecular dynamic simulations confirmed the stability of this docked complex, emphasizing the conformation and interactions between the molecules. Further experimental validation is necessary to evaluate its effectiveness against B. henselae.

Skin Tolerability of Oleic Acid Based Nanovesicles Designed for the Improvement of Icariin and Naproxen Percutaneous Permeation.

Deformable nanovesicles have a crucial role in topical drug delivery through the skin, due to their capability to pass intact the stratum corneum and epidermis (SCE) and significantly increase the efficacy and accumulation of payloads in the deeper layers of the skin. Namely, lipid-based ultradeformable nanovesicles are versatile and load bioactive molecules with different physicochemical properties. For this reason, this study aims to make oleic acid based nanovesicles (oleosomes) for the codelivery of icariin and sodium naproxen and increase their permeation through the skin. Oleosomes have suitable physicochemical properties and long-term stability for a potential dermal or transdermal application. The inclusion of oleic acid in the lipid bilayer increases 3-fold the deformable properties of oleosomes compared to conventional liposomes and significantly improves the percutaneous permeation of icariin and sodium naproxen through the human SCE membranes compared to hydroalcoholic solutions of both drugs. The tolerability studies on human volunteers demonstrate that oleosomes are safer and speed up the recovery of transepidermal water loss (TEWL) baselines compared to saline solution. These results highlight promising properties of icariin/sodium naproxen coloaded oleosomes for the treatment of skin disorders and suggest the potential future applications of these nanovesicles for further in vivo experiments.

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.

Micrometer insights into Nepeta genus: Pollen micromorphology unveiled.

This study provides a comprehensive pollen micromorphology within the Nepeta genus, revealing intricate details about the pollen grains' structure and characteristics. The findings shed light on the evolutionary and taxonomical aspects of this plant genus, offering valuable insights for botanists and researchers studying Nepeta species. The pollen grains of 18 Nepeta species were studied using scanning electron microscopy (SEM) and light microscopy (LM) in Northern Pakistan. At the microscale, pollen quantitative measurements, qualitative traits, and diverse sculpturing patterns were reported and compared. Significant differences in pollen size, shape, ornamentation, and sculpturing patterns were discovered among the Nepeta species. Our data show that exine sculpturing is quite diverse, with most species exhibiting a reticulate perforate pollen pattern. Nepeta connata, Nepeta discolor, Nepeta elliptica, revealed a distinct bireticulate perforate exine stratification. Hexazonocolpate pollen is the most common. Furthermore, the surface membrane attributes of the colpus varied greatly, ranging from rough, scabrate, psilate, to sinuate patterns. Principal Component Analysis (PCA) was used to discover the key factors influencing pollen diversity. PCA results showed that polar and equatorial diameters, colpi size, and exine thickness were the most influential pollen features between Nepeta species. This study adds to our understanding of pollen morphology in the Nepeta genus, offering information on the vast range of characteristics found in this economically important group. The extensive characterization of pollen features provides useful insights for the categorization and differentiation of Nepeta species, adding to the Lamiaceae micromorphology.

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.

Assessment of heavy metals among auto workers in metropolitan city: a case study.

In recent decades, heavy metals (HMs) have emerged as a global health concern. Unfortunately, in Pakistan, there is a general lack of awareness regarding the potential health risks associated with HMs pollution among automobile workers. Herein, we investigated the concentration of heavy metals such as lead (Pb), cadmium (Cd), and chromium (Cr) among automobile workers who were occupationally exposed in Mingora City, Khyber Pakhtunkhwa, Pakistan. Three different automobile groups, i.e., battery recyclers, spray painters, and mechanics were studied in detail. A total of 40 blood samples were collected from automobile workers groups while 10 blood samples were collected as control individuals from different locations in the study area. We investigated heavy metals concentration with a standard method using an atomic absorption spectrometer AAS (PerkinElmer Analyst 700, United States). Based on our findings, the battery recycling group displayed the most elevated Pb levels (5.45 ± 2.11 µg/dL), exceeding those of both the spray painters' group (5.12 ± 1.98 µg/dL) and the mechanics' group (3.79 ± 2.21 µg/dL). This can be attributed to their higher exposure to Pb pollution resulting from the deterioration, dismantling, grinding, or crushing of old batteries. In the context of chromium (Cr) exposure, a similar trend was observed among the battery recycling group, as well as the spray painters and mechanics groups. However, in the case of cadmium (Cd), the mechanics' group exhibited the highest level of exposure (4.45 ± 0.65 µg/dL), surpassing the battery recycling group (1.17 ± 0.45 µg/dL) and the spray painters' group (1.35 ± 0.69 µg/dL), which was attributed to their greater exposure to welding fumes and other activities in their workplace. We believe that our findings will encourage regulatory measures to improve the health of automobile workers. However, further work is needed to determine various health-related issues associated with heavy metal exposure among automobile workers.

Enhancing the Super-Resolution of Medical Images: Introducing the Deep Residual Feature Distillation Channel Attention Network for Optimized Performance and Efficiency.

In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by introducing a channel attention block that is tailored for high-frequency features-crucial for the nuanced details in medical diagnostics-while streamlining the network structure for enhanced computational efficiency. DRFDCAN's architecture adopts a residual-within-residual design to facilitate faster inference and reduce memory demands without compromising the integrity of the image reconstruction. This design strategy, combined with an innovative feature extraction method that emphasizes the utility of the initial layer features, allows for improved image clarity and is particularly effective in optimizing the peak signal-to-noise ratio (PSNR). The proposed work redefines efficiency in SR models, outperforming established frameworks like RFDN by improving model compactness and accelerating inference. The meticulous crafting of a feature extractor that effectively captures edge and texture information exemplifies the model's capacity to render detailed images, necessary for accurate medical analysis. The implications of this study are two-fold: it presents a viable solution for deploying SR technology in real-time medical applications, and it sets a precedent for future models that address the delicate balance between computational efficiency and high-fidelity image reconstruction. This balance is paramount in medical applications where the clarity of images can significantly influence diagnostic outcomes. The DRFDCAN model thus stands as a transformative contribution to the field of medical image super-resolution.

Preventing overloaded dissemination in healthcare applications using NonDelay tolerant dissemination technique.

Wearable Sensors (WSs) are widely used in healthcare applications to monitor patient health. During the data transmission, dissemination requires additional time to transmit the details with minimum computation difficulties. The existing techniques consume high overloaded while transmitting data in healthcare applications. The research problem is overcome by applying the non-delay-tolerant dissemination technique (NDTDT) to prevent overloaded dissemination and augment immediate, swift message delivery. The dissemination techniques utilize the intelligent decision-making process to provide the accumulated details to the healthcare center. The proposed approach is reliable in mitigating the errors due to inconsistent and discrete sensing intervals between the WSs. The constraints due to delay and interrupted transmission losses are reduced by selecting appropriate slots for WS information handling. This technique aims at maximizing the delivery of accumulated WS information through non-submissive or underlay dissemination. The method is designed to reduce dissemination delay and maximize successful message delivery. Two variations, sensors and data flows, validate the proposed NDTDT system's performance. The model increases the delivery rate by 0.91% and 0.932%, the dissemination probability by 0.964% and 0.98%, and the final metrics involved are an average delay of 12.78 ms and 11.67 ms.

Green Synthesis of Zinc Oxide (ZnO) Nanoparticles from Green Algae and Their Assessment in Various Biological Applications.

The biosynthesis of algal-based zinc oxide (ZnO) nanoparticles has shown several advantages over traditional physico-chemical methods, such as lower cost, less toxicity, and greater sustainability. In the current study, bioactive molecules present in Spirogyra hyalina extract were exploited for the biofabrication and capping of ZnO NPs, using zinc acetate dihydrate and zinc nitrate hexahydrate as precursors. The newly biosynthesized ZnO NPs were characterized for structural and optical changes through UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDX). A color change in the reaction mixture from light yellow to white indicated the successful biofabrication of ZnO NPs. The UV-Vis absorption spectrum peaks at 358 nm (from zinc acetate) and 363 nm (from zinc nitrate) of ZnO NPs confirmed that optical changes were caused by a blue shift near the band edges. The extremely crystalline and hexagonal Wurtzite structure of ZnO NPs was confirmed by XRD. The involvement of bioactive metabolites from algae in the bioreduction and capping of NPs was demonstrated by FTIR investigation. The SEM results revealed spherical-shaped ZnO NPs. In addition to this, the antibacterial and antioxidant activity of the ZnO NPs was investigated. ZnO NPs showed remarkable antibacterial efficacy against both Gram-positive and Gram-negative bacteria. The DPPH test revealed the strong antioxidant activity of ZnO NPs.

Toxoplasmosis-Awareness and Knowledge of Pregnant Women in Rural Areas of Malakand Region, Pakistan.

Background: The current study was carried out between October 2017 and October 2018 to explore knowledge, attitudes, practices, and information sources regarding toxoplasmosis among pregnant women in Malakand region, the northwestern part of Pakistan. The current study was carried out between October 2017 and October 2018. Methods: A structured questionnaire was used to interview the women after taking verbal informed consent. Graphpad version 5 was used to indicate the differences. Significant was considered as a P-value of less than 0.05. This study revealed poor knowledge regarding toxoplasmosis. Results: Overall, 31.2% of the respondents showed good knowledge, and 39.2% showed moderate knowledge. On the other hand, 29.5% of the participants showed poor knowledge about toxoplasmosis. The average knowledge score of pregnant women was 79 ± 12.2, which is considered to be within the scale of good knowledge. Number of children within the pregnant multipara women was significantly associated with knowledge about toxoplasmosis. Pregnant women who measured in number of childbirths within a women showed the highest mean score of 42.3 ± 13.3 with 57 (44.8%) displaying a good knowledge level. Pregnant women with more than one child had significantly higher (<0.0001) knowledge scores compared to women with one child or none child. The majority of pregnant women with one child used the social media, followed by mass media as sources of information about toxoplasmosis. Scientific sources of information were used more commonly by pregnant women with none of the child birth. Conclusion: Pregnant women knowledge regarding toxoplasmosis was poor as compared to attitudes and practices. Health workers and newspapers/magazines were the main sources of information.

Malaria prevalence in Pakistan: A systematic review and meta-analysis (2006-2021).

Malaria is one of the major public health issues globally. Malaria infection spreads through mosquito bites from infected female Anopheles mosquitoes. This study aims to conduct a systematic review and meta-analysis on malaria prevalence in Pakistan from 2006 to 2021. We searched PubMed, Science Direct, EMBASE, EMCare, and Google Scholar to acquire data on the prevalence of malaria infections. We performed a meta-analysis with a random-effects model to obtain the pooled prevalence of malaria, Plasmodium vivax, and Plasmodium falciparum. Meta-analysis was computed using R 4.1.2 Version statistical software. I2 and time series analysis were performed to identify a possible source of heterogeneity across studies. A funnel plot and the Freeman-Tukey Double Arcsine Transformed Proportion were used to evaluate the presence of publication bias. Out of the 315 studies collected, only 45 full-text articles were screened and included in the final measurable meta-analysis. Pooled malaria prevalence in Pakistan was 23.3%, with Plasmodium vivax, Plasmodium falciparum, and mixed infection rates of 79.13%, 16.29%, and 3.98%, respectively. Similarly, the analysis revealed that the maximum malaria prevalence was 99.79% in Karachi and the minimum was 1.68% in the Larkana district. Amazingly, this systematic review and meta-analysis detected a wide variation in malaria prevalence in Pakistan. Pakistan's public health department and other competent authorities should pay close attention to the large decrease in mosquito populations to curb the infection rate.

Assessment of heavy metals and associated oxidative stress in occupationally exposed workers from Bannu and Karak Districts in Pakistan.

Heavy metals (HMs) are extensively found in occupationally exposed miners and industrial workers, which may cause serious health-related problems to the large workforce. In order to evaluate the impact of these toxic pollutants, we have investigated the effect of cadmium (Cd), chromium (Cr), copper (Cu), and lead (Pb) concentration on exposed workers of mining, and woolen textile mill and compared the findings with unexposed individuals. From each category like exposed workers (mining, and woolen mill textile site) and unexposed individuals, 50 blood samples were taken. The occurrence of HMs in a sample was investigated through atomic absorption spectrometry while the oxidative stress marker malondialdehyde (MDA) and antioxidant enzyme statuses such as superoxide dismutase (SOD) and catalase (CAT) were analyzed in exposed and control samples. The results showed significant (p < 0.05) variation in Cd, Cr, Cu, and Pb levels in exposed and control samples. The concentration of Cd in the blood of WMWs, KMWs, and control group was 5.75, 3.89, and 0.42 µg/dL, respectively. On the other hand, the concentration of Pb in the blood of WMWs, MWs, and control was 32.34, 24.39, and 0.39 µg/dL while the concentrations of Cr and Cu in the blood of WMWs, MWs, and control group were 11.61 and 104.14 µg/dL, 4.21 and 113.21 µg/dL, 0.32 and 65.53 µg/dL, respectively. An increase in MDA was recorded in the exposed workers' group as compared to control subjects, whereas SOD and CAT activities decreased. Meanwhile, MDA was significantly and positively (p < 0.01) correlated with HMs, while negative significant correlations were found among HMs with SOD and CAT.

One Pot Synthesis, Biological Efficacy of AuNPs and Au-Amoxicillin Conjugates Functionalized with Crude Flavonoids Extract of Micromeria biflora.

Amoxicillin is the most widely used antibiotic in human medicine for treating bacterial infections. However, in the present research, Micromeria biflora's flavonoids extract mediated gold nanoparticles (AuNPs) were conjugated with amoxicillin (Au-amoxi) to study their efficacy against the inflammation and pain caused by bacterial infections. The formation of AuNPs and Au-amoxi conjugates were confirmed by UV-visible surface plasmon peaks at 535 nm and 545 nm, respectively. The scanning electron microscopy (SEM), zeta potential (ZP), and X-ray diffraction (XRD) studies reveal that the size of AuNPs and Au-amoxi are found to be 42 nm and 45 nm, respectively. Fourier-transform infrared spectroscopy (FT-IR) absorption bands at 3200 cm-1, 1000 cm-1, 1500 cm-1, and 1650 cm-1 reveal the possible involvement of different moieties for the formation of AuNPs and Au-amoxi. The pH studies show that AuNPs and Au-amoxi conjugates are stable at lower pH. The carrageenan-induced paw edema test, writhing test, and hot plate test were used to conduct in vivo anti-inflammatory and antinociceptive studies, respectively. According to in vivo anti-inflammatory activity, Au-amoxi compounds have higher efficiency (70%) after 3 h at a dose of 10 mg/kg body weight as compared to standard diclofenac (60%) at 20 mg/kg, amoxicillin (30%) at 100 mg/kg, and flavonoids extract (35%) at 100 mg/kg. Similarly, for antinociceptive activities, writhing test results show that Au-amoxi conjugates produced the same number of writhes (15) but at a lower dose (10 mg/kg) compared to standard diclofenac (20 mg/kg). The hot plate test results demonstrate that the Au-amoxi has a better latency time of 25 s at 10 mg/kg dose when compared to standard Tramadol of 22 s at 30 mg/ kg, amoxicillin of 14 s at 100 mg/kg, and extract of 14 s at 100 mg/kg after placing the mice on the hot plate for 30, 60, and 90 min with a significance of (p ≤ 0.001). These findings show that the conjugation of AuNPs with amoxicillin to form Au-amoxi can boost its anti-inflammatory and antinociceptive potential caused by bacterial infections.

Financial and social efficiency of microcredit programs of partner organizations of Pakistan Poverty Alleviation Fund.

This paper examines the financial and social efficiency of the microcredit programs offered by the Pakistan Poverty Alleviation Fund partner organizations. Panel data concerning variables of interest are collected from Pakistan Microfinance Network, covering a minimum of 14 partner organizations (in 2005) to a maximum of 35 partner organizations (in 2014). The data is analyzed using the Data Envelopment Analysis, assuming both constant and variable returns to scale scenarios and the operational scale of the partner organizations. Trends in average efficiency scores have been analyzed to assess the mission drift of the partner organizations. Results reveal that managerial inefficiency is more pronounced than the sub-optimal production scale in all three scenarios under consideration. Moreover, trends in the efficiency scores indicated a slight mission drift of the microfinance providers. About 77.5% of the partner organizations were financially sustainable over the entire study period. The study recommends providing objective-oriented training, workshops, and seminars for managing microfinance providers.

L-proline transporter inhibitor (LQFM215) promotes neuroprotection in ischemic stroke.

BACKGROUND: L-proline transporter (PROT/SLC6A7) is closely associated with glutamatergic neurotransmission, where L-proline modulates the NMDA receptor (NMDAR) function. NMDAR-mediated excitotoxicity is a primary cause of neuronal death following stroke, which is triggered by the uncontrolled release of glutamate during the ischemic process. After ischemic stroke, L-proline levels show a reduction in the plasma, but high circulating levels of this molecule indicate good functional recovery. This work aimed to produce new PROT inhibitors and explore their effects on ischemic stroke. METHODS: Initially, we built a three-dimensional model of the PROT protein and run a molecular docking with the newly designed compounds (LQFM215, LQFM216, and LQFM217). Then, we synthesized new PROT inhibitors by molecular hybridization, and proline uptake was measured in ex vivo and in vivo models. The behavioral characterization of the treated mice was performed by the open-field test, elevated plus-maze, Y-maze, and forced swimming test. We used the permanent middle cerebral artery occlusion (MCAO) model to study the ischemic stroke damage and analyzed the motor impairment with limb clasping or cylinder tests. RESULTS: LQFM215 inhibited proline uptake in hippocampal synaptosomes, and the LQFM215 treatment reduced proline levels in the mouse hippocampus. LQFM215 reduced the locomotor and exploratory activity in mice and did not show any anxiety-related or working memory impairments. In the MCAO model, LQFM215 pre-treatment and treatment reduced the infarcted area and reduced motor impairments in the cylinder test and limb clasping. CONCLUSIONS: This dataset suggests that the new compounds inhibit cerebral L-proline uptake and that LQFM215 promotes neuroprotection and neuro-repair in the acute ischemic stroke model.

Role of Non-contrast Computed Tomography of Nose and Paranasal Sinus in Preoperative Evaluation of Patients with Symptomatic Deviated Nasal Septum.

Symptomatic deviated nasal septum is a commonly encountered clinical condition by otorhinolaryngologist. Non-contrast Computed tomography (NCCT) of nose and Paranasal sinuses is a good tool in the preoperative evaluation of symptomatic deviated nasal septum so as to find hidden sinonasal pathologies in addition to deviated nasal septum. The aim of this article is to find the role and scope of preoperative Computed tomography in the management of symptomatic deviated nasal septum. This cross-sectional observational study was conducted on 120 patients with symptomatic deviated nasal septum, out of which 27 had concomitant hypertrophy of inferior turbinate. All were planned for septoplasty with or without turbinoplasty. Non contrast computed tomography (NCCT) scan was done in all cases. Different findings on NCCT were noted. After NCCT was done, 33 (27.5%) out of 120 patients underwent additional surgical procedures. In conclusion, NCCT of Nose and Paranasal sinus surgery should be given due consideration in the evaluation of symptomatic deviated nasal septum so as to avoid second surgery.