Formulation and Characterization of Silibinin Entrapped Nano-Liquid Crystals for Activity against Aß1-42 Neurotoxicity in In-Vivo Model.

Silibinin (SIL) Encapsulated Nanoliquid Crystalline (SIL-NLCs) particles were prepared to study neuroprotective effect against amyloid beta (Aß1-42) neurotoxicity in Balb/c mice model. Theses NLCs were prepared through hot emulsification and probe sonication technique. The pharmacodynamics was investigatigated on Aß1-42 intracerebroventricular (ICV) injected Balb/c mice. The particle size, zeta potential and drug loading were optimized to be 153 ± 2.5 nm, -21 mV, and 8.2%, respectively. Small angle X-ray (SAXS) and electron microscopy revealed to crystalline shape of SIL-NLCs. Thioflavin T (ThT) fluroscence and circular dichroism (CD) technique were employed to understand monomer inhibition effect of SIL-NLCs on Aß1-4. In neurobehavioral studies, SIL-NLCs exhibited enhanced mitigation of memory impairment induced on by Aß1-42 in T-maze and new object recognition test (NORT). Whereas biochemical and histopathological estimation of brain samples showed reduction in level of Aß1-42 aggregate, acetylcholine esterase (ACHE) and reactive oxygen species (ROS). SIL-NLCs treated animal group showed higher protection against Aß1-42 toxicity compared to free SIL and Donopezil (DPZ). Therefore SIL-NLCs promises great prospect in neurodegenerative diseases such as Alzheimer's disease.

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India.

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4 µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3 µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.

Association of socio-demographic factors with clinical outcome among hospitalized patients in first and second waves of COVID-19 pandemic: Study from the developing world.

Background: Recent disease resurgence in China indicates that corona virus infectious disease is still a pertinent public health problem. We stand at a juncture where we are still unsure about the initial dilemmas regarding its birth, therapies, and the emerging novel strains. Medical literature has focused on the clinical, laboratory, radiological, and therapeutic aspects of disease management. There is paucity of literature on the association between socio-demographic variables on disease severity and clinical outcome. Materials and Methods: This retrospective observational study analyzing the socio-demographic variables was performed at a dedicated COVID care center in western Maharashtra, India. Electronic records of all individuals who were admitted to this hospital from July 29 2020, to June 14, 2021, and diagnosed COVID-19 positive by reverse transcriptase polymerase chain reaction (RT-PCR) were identified after due institutional ethical clearance. Patients admitted from July 29, 2020, to February 27, 2021, were categorized as patients presenting during the 'first wave of viral pandemic'. Those admitted from March 01, 2021, to June 14, 2021, have been included as patients admitted during 'second wave of viral pandemic'. The following outcome parameters were collected (presenting symptoms, duration of symptoms before the individual presented for diagnostic RT-PCR, total duration of symptoms, severity of disease at onset, duration of hospital stay, the final outcome (discharge/death) and Charlson's comorbidity index). The linear regression model was used to establish association between socio-demographic factors and disease severity at onset (mild/moderate/severe/critical). Results: A total of 37033 patients were screened, and the positivity rate with RT-PCR was 16.99% (n = 6275) during the study period. Out of which 45% (n = 2824) of the patients had mild disease requiring home isolation and the remaining 55% of patients required admission. 1590 patients from the first wave and 910 from the second wave of COVID-19 were hospitalized and included in the study after exclusion. The mean age of patients in first wave was 49 years and that in second wave was 54 years with 77.6% and 70.6% males in two waves, respectively. The burden of critical cases was higher in second wave as computed to first wave (10% vs 8%). The second wave had more outreach in the rural population as compared to second one (17.8% vs 12.2%). The mean duration from the onset of symptoms to hospitalization was 03 and 04 days, respectively, in two waves. Mortality associated in two waves was 11.9% and 24%, respectively (P < 0.05). Higher Charlson's comorbidity index was associated with higher mortality, and the cumulative survival from urban area was more as compared to the rural population (log rank - 9.148, P = 0.0002). Conclusion: The second COVID-19 wave had significantly higher case mortality. It affected elderly patients and those with rural background. The factors associated with higher mortality during COVID-19 pandemic were rural background, higher Charlson's comorbidity index and late presentation to the hospital. Ongoing vaccine campaigns, thus, should focus on rural areas and individuals with comorbidities especially in developing and least developed countries.

Leprosy Presenting as Distal Acquired Demyelinating Symmetric Variant of Chronic Inflammatory Demyelinating Polyneuropathy: An Atypical Manifestation of Hansan's Disease.

Leprosy, caused by the bacterium Mycobacterium leprae, is known to primarily affect the skin and peripheral nerves. We present a rare case of leprosy initially manifesting as demyelinating polyneuropathy. A 46-year-old female presented with progressive weakness, tingling, and numbness in her extremities. Nerve conduction studies revealed evidence of demyelination, prompting further investigations. Skin slit-skin smears confirmed the diagnosis of leprosy, with the presence of acid-fast bacilli. The patient was subsequently started on multidrug therapy, leading to significant clinical improvement. This case highlights the importance of considering leprosy as a differential diagnosis in patients presenting with demyelinating polyneuropathy, especially in endemic regions.

Phenotype to Treatable Traits-Based Management in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD), a heterogeneous respiratory disease driven by various genetic and environmental factors, presents significant challenges in diagnosis and management. Traditional approaches focused on phenotypic classification, but recent paradigms emphasize identifying and addressing treatable traits to personalize treatment strategies. Treatable traits facilitate personalized interventions, optimizing symptom control, and reducing exacerbation risk. Dyspnea and exacerbations, recognized as key traits, guide treatment decisions and follow-up management. Various interventions, including bronchodilators, corticosteroids, and lifestyle modifications, target specific traits like airway inflammation, mucus overproduction, and emphysema. Strategies for assessing and addressing treatable traits during initial encounters and follow-up visits enhance disease monitoring and treatment efficacy. Comprehensive trait assessment demands resources and specialized monitoring, posing barriers to widespread implementation. The lack of standardized protocols and evolving evidence further complicates decision-making and clinical practice. Despite these challenges, the shift toward treatable traits-based management signifies a pivotal advancement in COPD care, emphasizing holistic approaches tailored to individual patient needs. Recognizing and addressing treatable traits offers personalized interventions, enhancing symptom control and disease management. Embracing treatable traits-based approaches holds promise for improving clinical outcomes and enhancing the quality of life for individuals living with COPD.

Harnessing Therapeutic Potentials of Biochanin A in Neurological Disorders: Pharmacokinetic and Pharmacodynamic Overview.

Biochanin A, an isoflavone flavonoid with estrogenic activity, is naturally found in red clover and other legumes. It possesses a wide range of pharmacological properties, including antioxidant, anti-inflammatory, anti-apoptotic, neuroprotective, and anticancer effects. In recent years, a growing body of pre-clinical research has focused on exploring the therapeutic potential of biochanin A in various neurological disorders, such as Alzheimer's and Parkinson's disease, multiple sclerosis, epilepsy, ischemic brain injury, gliomas, and neurotoxicity. This comprehensive review aims to shed light on the underlying molecular mechanisms that contribute to the neuroprotective role of biochanin A based on previous pre-clinical studies. Furthermore, it provides a detailed overview of the protective effects of biochanin A in diverse neurological disorders. The review also addresses the limitations associated with biochanin A administration and discusses different approaches employed to overcome these challenges. Finally, it highlights the future opportunities for translating biochanin A from pre-clinical research to clinical studies while also considering its commercial viability as a dietary supplement or a potential treatment for various diseases.

Celastrol-loaded polymeric mixed micelles shows improved antitumor efficacy in 4 T1 bearing xenograft mouse model through spatial targeting.

In this study, we have proposed a novel approach that combines hyaluronic acid (HA), folic acid (FA), and celastrol (CLS) within a polymeric micelle system (CLS-HF/MLs), offering a dual-action strategy against breast cancer. Polymeric mixed micelles were prepared through the thin-film hydration method, and comprehensive quality control parameters were established, encompassing particle size, polydispersity index, zeta potential, surface morphology, encapsulation efficiency, drug content, in vitro drug release, and storage stability assessment. The average particle size of CLS-HF/MLs micelles was found to be 120 nm and their drug loading and encapsulation efficiencies were 15.9 % and 89.52 %, respectively. The in vitro release data showed that the CLS-HF/MLs targeted mixed micelles displayed a prolonged release profile compared to the free drug. Additionally, the stability of the developed polymeric mixed micelles was maintained for up to 8 weeks of storage in terms of particle size and drug content. Furthermore, both flow cytometry and confocal laser scanning microscopy studies indicated a significant enhancement in the cellular uptake efficiency and cytotoxicity of CLS-HF/MLs mixed micelles against MCF-7 cell line. In terms of pharmacokinetic analysis, the half-life and AUC values of CLS-HF/MLs mixed micelles were found to be approximately 4.71- and 7.36-folds higher than the values of free drug (CLS), respectively. The CLS-HF/MLs micelles exhibited remarkable antitumor efficacy (almost complete ablation of the 4 T1-cell bearing tumor xenografts mouse model) due to the dual receptor (CD44 and folate) targeting effects with minimal side effects. When considering the cumulative findings of our present research, it becomes evident that mixed micelles designed for chemotherapy offer a promising and potentially effective therapeutic avenue for the treatment of breast cancer.

Optimal fusion of genotype and drug embeddings in predicting cancer drug response.

Predicting cancer drug response using both genomics and drug features has shown some success compared to using genomics features alone. However, there has been limited research done on how best to combine or fuse the two types of features. Using a visible neural network with two deep learning branches for genes and drug features as the base architecture, we experimented with different fusion functions and fusion points. Our experiments show that injecting multiplicative relationships between gene and drug latent features into the original concatenation-based architecture DrugCell significantly improved the overall predictive performance and outperformed other baseline models. We also show that different fusion methods respond differently to different fusion points, indicating that the relationship between drug features and different hierarchical biological level of gene features is optimally captured using different methods. Considering both predictive performance and runtime speed, tensor product partial is the best-performing fusion function to combine late-stage representations of drug and gene features to predict cancer drug response.

Utilizing a Fe3O4 Magnetite Nanoparticle for Anode Modification in a Microbial Desalination Cell to Treat Saltwater.

The microbial desalination cell (MDC) is a bio-electrochemical system that exhibits the ability to oxidize organic compounds, produce energy, and decrease the saline concentrations within the desalination chamber. The selective removal of ions from the desalination chamber is significantly influenced by the anion and cation exchange membranes. In this study, a three-chamber microbial desalination cell was developed to treat seawater using a synthesize Fe3O4 magnetite nanoparticle (MNP)-modified anode. The impact of different performance parameters, such as temperature, pH, and concentrations of NPs, has been investigated in order to assess the performance of three-chamber MDCs in terms of energy recovery and salt removal. The evaluation criteria of the system included multiple factors such as chemical oxygen demand (COD), Coulombic efficiency (CE), desalination efficiency, as well as system aspects including voltage generation and power density. The highest COD% removal efficiency was 74% at 37 °C, pH = 7, and 30 g/L salt concentration with an optimized NPs concentration of 2.0 mg/cm2 impregnated on anode. The maximum Coulombic efficiency was 10.3% with the maximum power density of 4.3 W/m3. The effect of the nanoparticle concentration impregnated on the anode was clarified by the primary factor of analysis. This research has revealed consistent patterns in the enhancement of voltage generation, COD, and Coulombic efficiencies when incorporating higher concentrations of nanoparticles on the anode at a certain point.

Extracellular mitochondrial components as new biomarkers for lupus nephritis.

Major reason for mortality among systemic lupus erythematosus patients is renal failure due to the deposition of immune complexes in the glomeruli. Being a chronic disease with multiple relapses and remissions across the lifespan, it's important to know the degree of nephritis for diagnosis as well as the long-term clinical management of the patients. Currently, renal biopsy is being used as the gold standard to diagnose and define the stages of the disease. However, renal biopsy being invasive only provides a localized picture of nephritis, and has the risk of bleeding. Additionally, it is also cost-intensive. Hence, a reliable, non-invasive biomarker is required for lupus nephritis. This study has evaluated extracellular mitochondrial components, including cell-free mitochondria, and cell-free mitochondrial DNA as probable biomarkers of the degree of nephritis. Both showed a significant correlation with proteinuria and protein-creatinine ratio. Our study substantiates their usage as clinical biomarkers of nephritis upon their validation in a larger cohort of lupus nephritis patients and other forms of nephritis. Although the current data suggest using cell-free mitochondria as a biomarker of lupus nephritis is better than the cell-free mitochondrial DNA.

Acaricide resistance status of deltamethrin and coumaphos in Hyalomma anatolicum ticks collected from different districts of Haryana.

To study the acaricide resistance status and possible mechanisms of action in conferring resistance to commonly used acaricides (deltamethrin and coumaphos), Hyalomma anatolicum ticks were collected from 6 dairy farms of Hisar and Charkhi Dadri districts of Haryana. By using standard larval packet test, H. anatolicum tick larvae of Charkhi Dadri isolates were found to be susceptible (100% mortality) to both the acaricides. Level-I resistance against coumaphos was recorded from four isolates, whereas, level-II was observed in only one isolate, collected from Hisar. One isolates (Kaimri) from Hisar also showed level-I resistance against deltamethrin. Biochemically, the ticks having higher values of resistance factor (RF) against coumaphos were found to possess increased enzymatic activity of α-esterase, ß-esterase, glutathione-S-transferase (GST) and mono-oxygenase enzymes, whereas, the monoamine oxidase did not show any constant trend. However, the RF showed a statistical significant correlation with GST only. Native PAGE analysis of H. anatolicum ticks revealed the presence of nine types of esterases (EST-1 h to EST-9 h) by using napthyl acetate as substrate. In the inhibitory assay, esterases were found to be inhibited by PMSF, indicating the presence of serine residue at catalytic triad. The partial cds of carboxylesterase and domain II of sodium channel genes were sequenced to determine any proposed mutations in resistant isolates of H. anatolicum ticks, however, no mutations were observed in either gene, indicating that increased expression of detoxification enzymes as a possible mechanism for resistance development, in the current study.

Harnessing the potential of nanoengineered siRNAs carriers for target responsive glioma therapy: Recent progress and future opportunities.

Past scientific testimonials in the field of glioma research, the deadliest tumor among all brain cancer types with the life span of 10-15 months after diagnosis is considered as glioblastoma multiforme (GBM). Even though the availability of treatment options such as chemotherapy, radiotherapy, and surgery, are unable to completely cure GBM due to tumor microenvironment complexity, intrinsic cellular signalling, and genetic mutations which are involved in chemoresistance. The blood-brain barrier is accountable for restricting drugs entry at the tumor location and related biological challenges like endocytic degradation, short systemic circulation, and insufficient cellular penetration lead to tumor aggression and progression. The above stated challenges can be better mitigated by small interfering RNAs (siRNA) by knockdown genes responsible for tumor progression and resistance. However, siRNA encounters with challenges like inefficient cellular transfection, short circulation time, endogenous degradation, and off-target effects. The novel functionalized nanocarrier approach in conjunction with biological and chemical modification offers an intriguing potential to address challenges associated with the naked siRNA and efficiently silence STAT3, coffilin-1, EGFR, VEGF, SMO, MGMT, HAO-1, GPX-4, TfR, LDLR and galectin-1 genes in GBM tumor. This review highlights the nanoengineered siRNA carriers, their recent advancements, future perspectives, and strategies to overcome the systemic siRNA delivery challenges for glioma treatment.

In silico strategies for identifying therapeutic candidates against Acinetobacter baumannii: spotlight on the UDP-N-acetylmuramoyl-L-alanine-D-glutamate:meso-diaminopimelate ligase (MurE).

The opportunistic bacterium Acinetobacter baumannii, which belongs to ESKAPE group of pathogenic bacteria, is leading cause of infections associated with gram-negative bacteria. Acinetobacter baumannii causes severe diseases, such as VAP (ventilator-associated pneumonia), meningitis, and UTI (urinary tract infections) among the nosocomial infections contracted in hospitals. The high infection rate and growing resistance to the vast array of antibiotics makes it paramount to look for new therapeutic strategies against this pathogen. The most promising therapeutic targets are the proteins involved in the synthesis of peptidoglycan which is chief component of bacterial cell wall, MurE is one of those enzymes and is responsible for the addition of one unit of meso-diaminopimelic acid (meso-A2pm) to the nucleotide precursor, UDPMurNAc-L-Ala-D-Glu, and aids in the formation of crosslinker pentapeptide chain. The three-dimensional structure of MurE was modelled using homology modelling technique and then vHTS was performed using this model against Approved Drug Library on DrugRep server using AutoDock Vina. Out of 500 drug molecules, two were selected based on estimated binding affinity, interaction pattern, interacting residues, etc. The selected drug molecules are DB12887 (Tazemetostat) and DB13879 (Glecaprevir). Then, MD simulations were performed on native MurE and its complexes with ligands to examine their dynamical behaviour, stability, integrity, compactness, and folding properties. The protein-ligand complexes were then subjected to binding free energy calculations using the MM/PBSA-based binding free energy analysis and the values are -109.788 ± 8.03 and -152.753 ± 11.98 kcal for MurE-DB12887 and MurE-DB13879 complex, respectively. All the analysis performed on MD trajectories for the complexes of these ligands with protein provided plenty of dependable evidences to consider these molecules for inhibition of MurE enzyme from A. baumannii. Communicated by Ramaswamy H. Sarma.

Development of Multiplex Molecular Assays for Simultaneous Detection of Dengue Serotypes and Chikungunya Virus for Arbovirus Surveillance.

The major arboviruses mainly belong to the Bunyaviridae, Togaviridae, and Flaviviridae families, among which the chikungunya virus and dengue virus have emerged as global public health problems. The main objective of this study was to develop specific, sensitive, and cost-effective molecular multiplex RT-PCR and RT-qPCR assays for the rapid and simultaneous detection of CHIKV and the four serotypes of DENV for arbovirus surveillance. Specific primers for all viruses were designed, and one-step multiplex RT-PCR (mRT-PCR) and RT-qPCR (mRT-qPCR) were developed using reference strains of the CHIKV and DENV serotypes. The specificity of the test for all the viruses was confirmed through sequencing. The standard curves showed a high correlation coefficient, R2 = 0.99, for DENV-2 and DENV-3; R2 = 0.98, for DENV-4; and CHIKV; R2 = 0.93, for DENV-1. The limits of detection were calculated to be 4.1 × 10-1 copies/reaction for DENV-1, DENV-3, and CHIKV and 4.1 × 101 for DENV-2 and DENV-4. The specificity and sensitivity of the newly developed mRT-PCR and mRT-qPCR were validated using positive serum samples collected from India and Burkina Faso. The sensitivity of mRT-PCR and mRT-qPCR are 91%, and 100%, respectively. The specificity of both assays was 100%. mRT-PCR and mRT-qPCR assays are low-cost, and a combination of both will be a useful tool for arbovirus surveillance.

Comprehensive antifungal investigation of green synthesized silver nanoformulation against four agriculturally significant fungi and its cytotoxic applications.

The present study reports the green synthesis of silver nanoparticles (AgNPs) in powder form using the leaf extract of Azadirachta indica. The synthesis of AgNPs was confirmed by UV-vis spectroscopy, FTIR, XRD, FESEM, and EDX. The synthesized AgNPs were in a powdered state and dispersed completely in 5% polyethylene glycol (PEG) and demonstrated prolonged shelf life and enhanced bioavailability over a year without any aggregation. The resulting silver nanoformulation demonstrated complete inhibition against Sclerotinia sclerotiorum and Colletotrichum falcatum and 68% to 80% inhibition against Colletotrichum gloeosporioides and Rhizoctonia solani respectively, at 2000 ppm. The EC50 values determined through a statistical analysis were 66.42, 157.7, 19.06, and 33.30 ppm for S. sclerotiorum, C. falcatum, C. gloeosporioides, and R. solani respectively. The silver nanoformulation also established significant cytotoxicity, with a 74.96% inhibition rate against the human glioblastoma cell line U87MG at 250 ppm. The IC50 value for the cancerous cell lines was determined to be 56.87 ppm through statistical analysis. The proposed silver nanoformulation may be used as a next-generation fungicide in crop improvement and may also find application in anticancer investigations. To the best of our knowledge, this is also the first report of silver nanoformulation demonstrating complete inhibition against the economically significant phytopathogen C. falcatum.

Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization.

An autonomous, power-assisted Turtlebot is presented in this paper in order to enhance human mobility. The turtlebot moves from its initial position to its final position at a predetermined speed and acceleration. We propose an intelligent navigation system that relies solely on individual instructions. When there is no individual present, the Turtlebot remains stationary. Turtlebot utilizes a rotating Kinect sensor in order to perceive its path. Various angles were examined in order to demonstrate the effectiveness of the system in experiments conducted on a U-shaped experimental pathway. The Turtlebot was used as an experimental device during these trials. Based on the U-shaped path, deviations from different angles were measured to evaluate its performance. SLAM (Simultaneous Localization and Mapping) experiments were also explored. We divided the SLAM problem into components and implemented the Kalman filter on the experimental path to address it. The Kalman filter focused on localization and mapping challenges, utilizing mathematical processes considering both the system's knowledge and the measurement tool. This approach allowed us to achieve the most accurate system state estimation possible. The significance of this work extends beyond the immediate application, as it lays the groundwork for advancements in wheelchair navigation research by Dynamic Control. The experiments conducted on a U-shaped pathway not only validate the efficacy of our algorithm but also provide valuable insights into the intricacies of navigating in both forward and reverse directions. These insights are pivotal for refining the navigation algorithm, ultimately contributing to the development of more robust and user-friendly systems for individuals with mobility challenges. The data used for this purpose included actuator input, vehicle location, robot movement sensors, and sensor readings representing the world state. The study provides a strong foundation for future wheelchair navigation research by Dynamic Control. Consequently, we found that navigating the Turtlebot in the reverse direction resulted in a 5%-6% increase in diversion compared to forward navigation, providing valuable insight into further improvement of the navigation algorithm.

Understanding the Landscape of Bronchoscopy in Lung Cancer: Insights From Lesion Location, Gender, and Diagnostic Efficacy.

INTRODUCTION: Lung cancer constitutes a critical global health concern. According to the International Agency for Research on Cancer's (IARC) GLOBOCAN 2020 estimates, lung cancer is the leading cause of death in cancer patients. In areas where tuberculosis is prevalent, misdiagnosis and mistreatment frequently result from overlap, creating significant difficulties that delay diagnosis and treatment. Amid this complication, bronchoscopic techniques emerge as critical diagnostic tools, though their efficacy varies between studies. METHOD: Our retrospective study, conducted from July 2021 to December 2022 at the Department of Respiratory Medicine, Ganesh Shankar Vidyarthi Memorial Medical College, Kanpur, examined 156 participants with malignancies. Our focus encompassed diverse lesions within the bronchial landscape, revealing intriguing findings. RESULTS: Bronchoscopic examinations unravelled prevalent abnormalities: 52 (33.3%) manifested as intraluminal growth, 48 (31.6%) as mucosal irregularities, and a less frequent (16, 10.3%) as an intraluminal bulge. Transbronchial needle aspiration stood out with a 10/11 (91%) positivity rate, biopsy came in second at 38/46 (83%), and bronchoalveolar lavage showed a 44/152 (29%) positivity rate. It was interesting to see how the lesions were spread out among the different types of histology. For example, squamous cell carcinoma showed 17/37 (46%) intraluminal growth, while adenocarcinoma showed 22/60 (36.7%) intraluminal growth and 4/60 (6.7%) intraluminal bulge. Moreover, a significant absence of abnormalities was observed in various lesions, underlining the intricacies of characterising bronchial lesions. CONCLUSION: Our study shows that direct tissue sampling is better and that new bronchoscopic technologies are important for diagnosing lesions that were hard to get to in the past. However, limitations in patient selection biases and the single-centre focus caution against generalised interpretations. Our research illuminates the pivotal role of bronchoscopic methods in diagnosing lung lesions, emphasising the necessity for continued advancements to enhance diagnostic accuracy and treatment efficacy in lung cancer subtypes.

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.

Exploring nanocarriers as innovative materials for advanced drug delivery strategies in onco-immunotherapies.

In recent years, Onco-immunotherapies (OIMTs) have been shown to be a potential therapy option for cancer. Several immunotherapies have received regulatory approval, while many others are now undergoing clinical testing or are in the early stages of development. Despite this progress, a large number of challenges to the broad use of immunotherapies to treat cancer persists. To make immunotherapy more useful as a treatment while reducing its potentially harmful side effects, we need to know more about how to improve response rates to different types of immunotherapies. Nanocarriers (NCs) have the potential to harness immunotherapies efficiently, enhance the efficiency of these treatments, and reduce the severe adverse reactions that are associated with them. This article discusses the necessity to incorporate nanomedicines in OIMTs and the challenges we confront with current anti-OIMT approaches. In addition, it examines the most important considerations for building nanomedicines for OIMT, which may improve upon current immunotherapy methods. Finally, it highlights the applications and future scenarios of using nanotechnology.