Revealing the Roles of Guanidine Hydrochloride Ionic Liquid in Ion Inhibition and Defects Passivation for Efficient and Stable Perovskite Solar Cells.

As a result of full-scale ongoing global efforts, the power conversion efficiency (PCE) of the organic-inorganic metal halide perovskite has skyrocketed. Unfortunately, the long-term operational stability for commercialization standards is still lagging owing to intrinsic defects such as ion migration-induced degradation, undercoordinated Pb2+, and shallow defects initiated by disordered crystal growth. Herein, we employed multifunctional, non-volatile tetra-methyl guanidine hydrochloride [TMGHCL] ionic liquid (IL) as an additive to elucidate defects' passivation effects on organic-inorganic metal halide perovskite. More specifically, the formation of hydrogen bonds between H+ in GA+ and I- and coordinate bonding between Cl- and undercoordinated Pb2+ could significantly passivate these defects. The hypothesis was confirmed by both experimental and DFT simulations displaying that the optimized ratio of IL integration restrains ion migration, improving grains' size, and significantly elongating the carrier lifetime. Remarkably, the modified cell achieved a peak efficiency of 22.00 % with negligible hysteresis, compared to the control device's PCE of 20.12 %. In addition, the TMGHCL-based device retains its 93.29 % efficiency after 16 days of continuous exposure to air with a relative humidity of 35±5% and temperature of 25±5 °C. This efficient approach of adding IL to perovskites absorber can produce high PCE and has strong commercialization potential.

Sulfonic Acid Functionalized Ionic Liquids for Defect Passivation via Molecular Interactions for High-Quality Perovskite Films and Stable Solar Cells.

The high photoelectric conversion efficiency and low cost of perovskite solar cells (PSCs) have further inspired people's determination to push this technology toward industrialization. The high-quality perovskite films and high-efficiency and stable PSCs are the crucial factors. Ionic liquids have been proven to be an effective strategy for regulating high-quality perovskite films and high-performance PSCs. However, the regulation mechanism between ionic liquids and perovskites still needs further clarification. In this study, a novel sulfonic acid-functionalized ionic liquid, 1-butyl-3-methylimidazolium trifluoromethanesulfonate (BSO3HMImOTf), was used as an effective additive to regulate high-quality perovskite films and high-performance devices. Microscopic mechanism studies revealed strong interactions between BSO3HMImOTf and Pb2+ ions as well as halogens in the perovskite. The perovskite film is effectively passivated with the controlled crystal growth, suppressed ion migration, facilitating to the greatly improved photovoltaic performance, and superior long-term stability. This article reveals the regulatory mechanism of sulfonic acid type ionic liquids through testing characterization and mechanism analysis, providing a new approach for the preparation of high-quality perovskite devices.

Investigating Potential Cancer Therapeutics: Insight into Histone Deacetylases (HDACs) Inhibitions.

Histone deacetylases (HDACs) are enzymes that remove acetyl groups from ɛ-amino of histone, and their involvement in the development and progression of cancer disorders makes them an interesting therapeutic target. This study seeks to discover new inhibitors that selectively inhibit HDAC enzymes which are linked to deadly disorders like T-cell lymphoma, childhood neuroblastoma, and colon cancer. MOE was used to dock libraries of ZINC database molecules within the catalytic active pocket of target HDACs. The top three hits were submitted to MD simulations ranked on binding affinities and well-occupied interaction mechanisms determined from molecular docking studies. Inside the catalytic active site of HDACs, the two stable inhibitors LIG1 and LIG2 affect the protein flexibility, as evidenced by RMSD, RMSF, Rg, and PCA. MD simulations of HDACs complexes revealed an alteration from extended to bent motional changes within loop regions. The structural deviation following superimposition shows flexibility via a visual inspection of movable loops at different timeframes. According to PCA, the activity of HDACs inhibitors induces structural dynamics that might potentially be utilized to define the nature of protein inhibition. The findings suggest that this study offers solid proof to investigate LIG1 and LIG2 as potential HDAC inhibitors.

Acute pancreatitis associated with pembrolizumab-induced hypertriglyceridemia.

INTRODUCTION: Acute pancreatitis (AP) following drug-induced hypertriglyceridemia is a rare clinical phenomenon. Immune checkpoint inhibitors have revolutionized treatment for a variety of solid organ and hematological malignancies. Pembrolizumab is a programmed cell death receptor-1 (PD-1) inhibitor that has shown promising responses in many advanced cancers. However, a constellation of immune-related adverse events has also been described. There are reports of pembrolizumab-induced hypertriglyceridemia, but AP as a result of this side effect remains an exceedingly rare clinical sequela. CASE REPORT: We delineate a case of a patient with stage IVB non-small-cell lung cancer who developed progressive abdominal pain and nausea following administration of pembrolizumab for four months. Laboratory studies revealed increased serum lipase and triglyceride levels at 12,562 IU/L and 16,901 mg/dL, respectively. The diagnosis of AP was made based on the revised Atlanta classification criteria. After ruling out alternative causes, pembrolizumab-induced hypertriglyceridemia was considered the likely etiology of AP. MANAGEMENT AND OUTCOME: The patient was transferred to the medical intensive care unit for close monitoring. Treatment was initiated with intravenous fluids, pain medications, and an insulin infusion. However, her hypertriglyceridemia levels remained persistently elevated, necessitating therapeutic apheresis. She recovered well with no complications after triglyceride apheresis. DISCUSSION: AP following pembrolizumab-associated hypertriglyceridemia remains a rare clinicopathologic entity. Given the widespread clinical use of immune checkpoint inhibitors, knowledge of such rare adverse events is crucial. Evaluation of serum triglyceride levels before and after initiating pembrolizumab therapy may be mandated, especially in patients with metabolic comorbidities.

The Gastric Obstruction Due to Orbeez Beads Ingestion: A Case Report With Esophagogastroduodenoscopy Findings.

Ingestion of non-food entities poses a critical risk, particularly in children and young adults. Mostly foreign bodies can safely pass through the gastrointestinal tract if they traverse the pylorus; however, ingestion of Orbeez beads can present as a unique challenge. Orbeez beads have the potential to absorb water and can expand in the stomach and small intestine, and can result in complications including constipation, intestinal obstruction, perforation, and peritonitis. Timely diagnosis and management are crucial to improve patient outcomes. We present a case of a 19-year-old male who ingested Orbeez beads and presented with nausea, vomiting, and abdominal pain. A non-contrast CT scan of the abdomen confirmed the foreign bodies. Fifty to seventy beads were successfully removed via esophagogastroduodenoscopy (EGD) without any complications, and the patient is currently doing well.

Remote sensing based forest cover classification using machine learning.

Pakistan falls significantly below the recommended forest coverage level of 20 to 30 percent of total area, with less than 6 percent of its land under forest cover. This deficiency is primarily attributed to illicit deforestation for wood and charcoal, coupled with a failure to embrace advanced techniques for forest estimation, monitoring, and supervision. Remote sensing techniques leveraging Sentinel-2 satellite images were employed. Both single-layer stacked images and temporal layer stacked images from various dates were utilized for forest classification. The application of an artificial neural network (ANN) supervised classification algorithm yielded notable results. Using a single-layer stacked image from Sentinel-2, an impressive 91.37% training overall accuracy and 0.865 kappa coefficient were achieved, along with 93.77% testing overall accuracy and a 0.902 kappa coefficient. Furthermore, the temporal layer stacked image approach demonstrated even better results. This method yielded 98.07% overall training accuracy, 97.75% overall testing accuracy, and kappa coefficients of 0.970 and 0.965, respectively. The random forest (RF) algorithm, when applied, achieved 99.12% overall training accuracy, 92.90% testing accuracy, and kappa coefficients of 0.986 and 0.882. Notably, with the temporal layer stacked image of the Sentinel-2 satellite, the RF algorithm reached exceptional performance with 99.79% training accuracy, 96.98% validation accuracy, and kappa coefficients of 0.996 and 0.954. In terms of forest cover estimation, the ANN algorithm identified 31.07% total forest coverage in the District Abbottabad region. In comparison, the RF algorithm recorded a slightly higher 31.17% of the total forested area. This research highlights the potential of advanced remote sensing techniques and machine learning algorithms in improving forest cover assessment and monitoring strategies.

Computational analysis of target genes in monkeypox virus infection and potential therapeutic precursors.

BACKGROUND: Monkeypox is an orthopoxvirus that is responsible for zoonotic infections in humans. The virus has recently spread rapidly and the WHO has listed it as an international public health emergency of concern. RESEARCH DESIGN AND METHODS: Here, we used network analysis and gene enrichment protocols and analyzed datasets of MPXV infection that induced host cell gene expression list and subsequently mapped them against two herbal target gene lists which highlighted considerable coherence in pharmacological attributes with COVID-19. Molecular docking and simulation were performed for the screened compounds. RESULTS: Our results identified ß-carotene and kaempferol possessing tremendous ability against the MPXV PLD protein. Both compounds were subjected to each of 100 ns molecular dynamics simulation and were found native to the PLD pocket. MM-PB (GB) SA analyses indicated -25.4, -40.1 kcal/mol and -17.2, -26.4kcal/mol of ΔGbind to the active pocket of PLD. Our data suggest the adaptive nature of the MPXV PLD active pocket toward hydrophobic inhibitors. CONCLUSION: These results will be of high importance for the viral researchers to be tested in wet lab settings in designing potential inhibitors.

Left Coronary Artery to Pulmonary Trunk Fistula: Two Case Reports With Literature Review.

Coronary artery fistulas (CAFs) are abnormal communication between coronary arteries and the pulmonary trunk or with adjacent heart structures. Coronary pulmonary artery fistulas (CPAFs) can be congenital or acquired. Mostly, CAFs are found as incidental findings on angiographic evaluation. The management of CPAFs varies from case to case depending on size, anatomical location, patient's clinical presentation, and presence of coronary steal phenomenon. We present two cases of CPAFs; one of them had coronary steal phenomena at a young age with no past medical history of coronary artery disease, and the patient underwent transcatheter coil embolization to close the fistula. In other cases, a fistulous connection between the left anterior descending (LAD) and the pulmonary trunk was found incidentally on computed tomography (CT) of the heart and based on a small-sized fistula and symptomatic improvement, the patient was discharged with conservative management. CPAFs are rare cardiac anomalies but can give rise to severe hemodynamic complications, so this should be a part of the initial differential diagnosis if the patient does not have significant coronary artery disease. Percutaneous closure or surgical correction is indicated if the patients are symptomatic or have secondary complications.

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.

The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.

Myopericarditis Following the Third Dose of COVID-19 mRNA Vaccination: A Case Report.

Coronavirus disease 2019 (COVID-19) mRNA vaccine-related cases of pericarditis and myocarditis have been reported infrequently. Most of the patients usually present within a week of the vaccine, and on average, most of the cases were reported after the second dose of vaccine within two to four days. Chest pain was the most common presentation, and fever and shortness of breath were the other commonly reported symptoms. The patients can have positive cardiac markers and electrocardiogram (EKG) changes, and the cases can be mistaken for cardiac emergencies. We present a 17-year-old male patient with sudden onset substernal chest pain for two days who got the third dose of the Pfizer-BioNTech mRNA vaccine within 24 hours prior. EKG was remarkable for diffuse ST elevations, and troponins were elevated. Later, the cardiac magnetic resonance imaging confirmed the findings of myopericarditis. The patient was treated with colchicine and non-steroidal anti-inflammatory drugs (NSAIDs), completely recovered, and is doing fine to date. This case hights that post-vaccine myocarditis can be mistaken and early diagnosis and management can prevent unnecessary interventions.

3D-QSAR Studies, Molecular Docking, Molecular Dynamic Simulation, and ADMET Proprieties of Novel Pteridinone Derivatives as PLK1 Inhibitors for the Treatment of Prostate Cancer.

Overexpression of polo-like kinase 1 (PLK1) has been found in many different types of cancers. With its essential role in cell proliferation, PLK1 has been determined to be a broad-spectrum anti-cancer target. In this study, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations were applied on a series of novel pteridinone derivatives as PLK1 inhibitors to discover anti-cancer drug candidates. In this work, three models­CoMFA (Q² = 0.67, R² = 0.992), CoMSIA/SHE (Q² = 0.69, R² = 0.974), and CoMSIA/SEAH (Q² = 0.66, R² = 0.975)­of pteridinone derivatives were established. The three models that were established gave Rpred2 = 0.683, Rpred 2= 0.758, and Rpred 2= 0.767, respectively. Thus, the predictive abilities of the three proposed models were successfully evaluated. The relations between the different champs and activities were well-demonstrated by the contour chart of the CoMFA and CoMSIA/SEAH models. The results of molecular docking indicated that residues R136, R57, Y133, L69, L82, and Y139 were the active sites of the PLK1 protein (PDB code: 2RKU), in which the more active ligands can inhibit the enzyme of PLK1. The results of the molecular dynamic MD simulation diagram were obtained to reinforce the previous molecular docking results, which showed that both inhibitors remained stable in the active sites of the PLK1 protein (PDB code: 2RKU) for 50 ns. Finally, a check of the ADME-Tox properties of the two most active molecules showed that molecular N° 28 could represent a good drug candidate for the therapy of prostate cancer diseases.

Identification of natural marine compounds as potential inhibitors of CDK2 using molecular docking and molecular dynamics simulation approach.

The multifunctional enzyme cyclin-dependent kinase 2 (CDK2) protein is essential for cell proliferation, transcription and modulation of the cell cycle. There is a dysfunction that is connected to various diseases, such as cancer, making it an important treatment target in oncology and beyond. The goal of this study is to identify novel CDK2 ATP binding site inhibitors using in silico drug designing. To find competitive inhibitors for the ATP site, molecular docking, molecular dynamics (MD) simulation and free-binding energy calculations were used. Natural compounds retrieved from marine sources (fungi and algae) were docked against protein, and the best-binding compounds were further evaluated using MD simulations. LIG1, LIG2 and LIG3 (ΔGPB = -19.98, -15.82 and -12.98 kcal/mol, respectively) were placed in the top positions based on their overall binding energy calculated using MMPBSA approach. Stability of the complexes was confirmed by carefully analyzing the rmsd and rmsf patterns retrieved from the MD trajectories. Several residues and areas (Leu124, Val123, Phe80, Leu83, Glu81, Arg 126, Asn132, Leu134, Gln131, Lys88 and Glu195) appear to be critical for inhibitor retention across the active pocket, according to RMSD and RMSF. The dynamics of the ligands inside the active pocket were mapped using principle component analysis. It has been observed that LIG1-3 appear to be the best possible inhibitors due to their high binding energies, interaction pattern and retention inside the active pocket.Communicated by Ramaswamy H. Sarma.

Theoretical analysis of unsteady squeezing nanofluid flow with physical properties.

Theoretical analysis of physical characteristics of unsteady, squeezing nanofluid flow is studied. The flow of nanofluid between two plates that placed parallel in a rotating system by keeping the variable physical properties: viscosity and thermal conductivity. It is analyzed by using Navier Stokes Equation, Energy Equation and Concentration equation. The prominent equations are transformed by virtue of suitable similarity transformation. Nanofluid model includes the important effects of Thermophoresis and Brownian motion. For analysis graphical results are drawn for verity parameters of our interest i.e., Injection parameter, Squeezing number, Prandtle number and Schmidt number are investigated for the Velocity field, Temperature variation and Concentration profile numerically. The findings underline that the parameter of skin friction increases when the Squeezing Reynolds number, Injection parameter and Prandtle number increases. However, it shows inverse relationship with Schmidt number and Rotation parameter. Furthermore, direct relationship of Nusselt number with injection parameter and Reynolds number is observed while its relation with Schmidt number, Rotation parameter, Brownian parameter and Thermophoretic parameter shows an opposite trend. The results are thus obtained through Parametric Continuation Method (PCM) which is further validated through BVP4c. Moreover, the results are tabulated and set forth for comparison of findings through PCM and BVP4c which shows that the obtained results correspond to each other.

In silico-prediction of chloroquine as a multi-targeted drug against CDKN2A signaling network associated with cutaneous malignant melanoma.

Melanoma is one of the most common skin infections, has triggered significant morbidity and mortality across the globe. Previous studies have reported that mutations in CDKN2A signalling network is associated with cutaneous malignant melanoma. In the present study, initially, the BioGrid database was utilized, and then hierarchical clustering was performed to identify the CDKN2A signature pathways. In addition, a GO Enrichment analysis was investigated using DAVID (n=187 genes) toolkit. Subsequently, the cBioPortal cancer genomic platform was exploited using alteration ranked frequency to determine the role of the CDKN2A signaling network in 363 samples of cutaneous malignant melanoma patients and we find that CDKN2A and its close interactors PTEN and HUWE1 show highest mutations. Further, we systematically employed molecular docking approach via MOE to target PTEN, CDKN2A and HUWE1 with chloroquine which is naturally occurring in medicinal plant Nigella sativa (NS) and observed virtuous interactions between all receptors and ligand molecules with a binding energy of -11.379, -10.324 and -9.06 Kcal/mol, respectively. The outcomes obtained stipulate a vigorous research resource for using chloroquine as a multitargeted anticancer drug. This novel evidence should help the development of effective therapeutic compounds for the treatment of cancer. Our results reveal that chloroquine is a relevant and novel potential therapeutic drug for the treatment of melanoma.

Therapeutic Effect of Sunflower Seeds and Flax Seeds on Diabetes.

Diabetes mellitus (DM) is a metabolic syndrome that is spreading like an epidemic throughout the world without any differentiation of races and ethnic groups and has become the cause of death worldwide. It is characterized by high levels of glucose in the blood and has different types classified on the basis of varying pathophysiology. Type 1 diabetes or insulin-dependent diabetes is characterized by insulin insufficiency due to autoimmune dysfunction. Type 2 diabetes or non-insulin-dependent diabetes results from the combination of resistance to insulin action or/and inadequate insulin secretion. Gestational diabetes (GDM) is defined as hyperglycemia due to insulin resistance during pregnancy. Other types include the monogenic type of DM such as neonatal diabetes mellitus (NDM), maturity-onset diabetes of young (MODY), and diabetes in metabolic syndrome. Diabetes is diagnosed by criteria given by American Diabetes Association (ADA) for different tests like fasting plasma glucose test and hemoglobin A1c test. It is characterized by polydipsia, polyphagia, hyperglycemia, and glucosuria. Diabetes mellitus is managed through medications but many studies have proven that consumption of particular foods leads to decreased glucose levels in diabetic patients. Seeds like sunflower and flax seeds have a role in the reduction of glucose levels and can be used to treat type 2 diabetes. The bioactive components in these seeds like chlorogenic acid in sunflower seeds and secoisolariciresinol diglucosoid are involved in the treatment of insulin resistance or insulin production. In different studies, different amounts of these seed extracts were consumed by rats and humans and it resulted in better glycemic control, which provides information that these seeds have anti-diabetic properties.

Impact of outpatient clinic ultrasound imaging in the diagnosis and treatment for shoulder impingement: a randomized prospective study.

The use of musculoskeletal ultrasonography (MSUS) in guiding subdeltoid injection has been shown to improve outcome up to 6 weeks in a few small studies. A recent meta-analysis identified the need for further studies with longer-term outcome and larger sample size. This randomized prospective study assessed whether clinic-based MSUS can significantly improve diagnostic accuracy in shoulder pain and whether MSUS-guided shoulder injection results in improved long-term outcomes. One hundred consecutive patients with 125 painful shoulders were recruited. Patients were randomized to receive either sonographic assessment with consequent palpation-guided injection (Group 1, n = 66) or sonographic assessment with a MSUS-guided injection of 40 mg of methylprednisolone acetate (Group 2, n = 59). A blinded rheumatologist (ADF) performed clinical assessments at baseline, 6 and 12 weeks including shoulder function tests (SFTs) (Hawkins-Kennedy test, supraspinatus tendon tenderness), physician global assessment (PGA) and patient visual analogue scores (VAS) for pain (0-10). Eighty patients with 90 symptomatic shoulders completed 12-week follow-up. Twenty patients, 11 (20 shoulders) from the palpation-guided group and 9 (15 shoulders) from the MSUS-guided group, were excluded at 6 weeks either due to requirement for repeat injection or due to surgical referral. Mean age for patients was 57.7 years, and 65 % patients were female; mean shoulder pain duration was 18 weeks (range 14-22 weeks). SFTs, patient VAS and PGA scores for pain improved significantly from baseline in both groups with significantly greater improvements in the MSUS-guided group (44 shoulders) compared to the palpation-guided group (46 shoulders) in all parameters at 6 (p < 0.01) and 12 weeks (p < 0.05). The use of MSUS in guiding subdeltoid injection has been shown to improve outcome up to 6 weeks in a few small studies. A recent meta-analysis identified the need for further studies with longer-term outcome and larger sample size.

Ankylosing spondylitis in Ireland: patient access and response to TNF-α blockers.

To investigate a group of Irish ankylosing spondylitis patients: current prescription practice for TNF blockers and patient response. All patients presenting with ankylosing spondylitis (AS) and treated with TNF-alpha between January 2006 and 2008 in the midwestern region of Ireland were studied. Response was evaluated using Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), and CRP results at 6 months. A total of 47 AS patients (32 men: 15 women, mean age 37.7 years, median disease duration 20 years, 80% HLA B27 positive) were identified; 66% were on disease-modifying anti-rheumatic drugs (DMARDs) concomitantly. All patients satisfied BSR/ASAS disease severity criteria for TNF-alpha at baseline, and mean BASDAI was 6.2, BASFI 6.9, and CRP 27.5 mg/L. At 6 months, these had reduced to a mean BASDAI of 3.8, BASFI 4.6, and CRP of 8.9 mg/L. Patients with advanced AS (disease duration >10 years, mean BASFI 7.5) responded at least as well. No allergies or serious side effects were encountered, and one patient successfully switched TNF agent due to secondary failure. Initial good responses at 6 months were seen to be maintained in sub-group analysis at 12 months. Disease severity in patients gaining access to treatment for active AS with TNF blockers in Ireland is very high. Patients mainly satisfy international guidelines for the use of biologics (BSR, EULAR) with some minor exceptions. High disease activity and long disease duration may predict better treatment response. Response rates were good and treatment was well tolerated, and no differences in response were noted between the 3 agents employed.