Retrospective Analysis of Postoperative Nonhepatic Outcomes Following Major Liver Resection.

Background Liver surgery is a major and challenging procedure for the surgeon, the anesthetist, and the patient. The objective of this study was to evaluate the postoperative nonhepatic complications of patients undergoing liver resection surgery with perioperative factors. Methods We retrospectively analyzed 79 patients who underwent liver resection surgeries at the Shaukat Khanum Memorial Cancer Hospital and Research Centre in Lahore, Pakistan, from July 2015 to December 2022. Results The mean age at the time of surgery was 53 years (range: 3-77 years), and the mean BMI was 26.43 (range: 15.72-38.0 kg/m2). Of the total patients, 44.3 % (n = 35) had no comorbidities, 26.6% (n=21) had one comorbidity, and 29.1% (n=23) had two or more comorbidities. Patients in whom the blood loss was more than 375 ml required postoperative oxygen inhalation with a significant relative risk of 2.6 (p=0.0392) and an odds ratio of 3.5 (p=0.0327). Similarly, patients who had a surgery time of more than five hours stayed in the hospital for more than seven days, with a statistically significant relative risk of 2.7 (p=0.0003) and odds ratio of 7.64 (p=0.0001). The duration of surgery was also linked with the possibility of requiring respiratory support, with a relative risk of 5.0 (p=0.0134) and odds ratio of 5.73 (p=0.1190). Conclusion Patients in our cohort who had a prolonged duration of surgery received an increased amount of fluids, and a large volume of blood loss was associated with prolonged stay in the ICU (>2 days), hospital admission (>7 days), ICU readmission, and increased incidence of cardiorespiratory, neurological, and renal disturbances postoperatively.

Indirect prediction of graphene nanoplatelets-reinforced cementitious composites compressive strength by using machine learning approaches.

Graphene nanoplatelets (GrNs) emerge as promising conductive fillers to significantly enhance the electrical conductivity and strength of cementitious composites, contributing to the development of highly efficient composites and the advancement of non-destructive structural health monitoring techniques. However, the complexities involved in these nanoscale cementitious composites are markedly intricate. Conventional regression models encounter limitations in fully understanding these intricate compositions. Thus, the current study employed four machine learning (ML) methods such as decision tree (DT), categorical boosting machine (CatBoost), adaptive neuro-fuzzy inference system (ANFIS), and light gradient boosting machine (LightGBM) to establish strong prediction models for compressive strength (CS) of graphene nanoplatelets-based materials. An extensive dataset containing 172 data points was gathered from published literature for model development. The majority portion (70%) of the database was utilized for training the model while 30% was used for validating the model efficacy on unseen data. Different metrics were employed to assess the performance of the established ML models. In addition, SHapley Additve explanation (SHAP) for model interpretability. The DT, CatBoost, LightGBM, and ANFIS models exhibited excellent prediction efficacy with R-values of 0.8708, 0.9999, 0.9043, and 0.8662, respectively. While all the suggested models demonstrated acceptable accuracy in predicting compressive strength, the CatBoost model exhibited exceptional prediction efficiency. Furthermore, the SHAP analysis provided that the thickness of GrN plays a pivotal role in GrNCC, significantly influencing CS and consequently exhibiting the highest SHAP value of + 9.39. The diameter of GrN, curing age, and w/c ratio are also prominent features in estimating the strength of graphene nanoplatelets-based cementitious materials. This research underscores the efficacy of ML methods in accurately forecasting the characteristics of concrete reinforced with graphene nanoplatelets, providing a swift and economical substitute for laborious experimental procedures. It is suggested that to improve the generalization of the study, more inputs with increased datasets should be considered in future studies.

Correction: Expert Opinions on the Management of Hemophilia A in India: The Role of Emicizumab.

[This corrects the article DOI: 10.7759/cureus.58941.].

Expert Opinions on the Management of Hemophilia A in India: The Role of Emicizumab.

Hemophilia A (HA) is a genetic disorder of hemostasis associated with a deficiency or reduced activity of clotting factor VIII (FVIII). This disorder remains unacceptably underdiagnosed in India. Early diagnosis and appropriate management of HA can substantially prevent morbidity and mortality. Currently, HA is managed with regular replacement therapy using standard or extended half-life FVIII concentrates or non-factor drug products. The challenges associated with FVIII concentrates include plateauing of drug effect, issues with its administration and adherence to treatment, breakthrough bleeds, and the development of inhibiting antibodies against administered clotting factors. Emicizumab is a bispecific antibody, launched in India in April 2019, for managing patients with HA. To investigate the role of emicizumab in Indian patients with HA, opinions were sought from 13 eminent hematologists and experts from India on the effectiveness of emicizumab in preventing all bleeds, spontaneous bleeds, perioperative bleeds, and intracranial hemorrhage; resolving target joints; and reducing the rate of hospitalizations and fatality associated with HA in children and adults, with or without inhibitors. The benefits of emicizumab over traditional FVIII concentrates include the subcutaneous route of delivery, less frequent dosing, and a lack of inhibitor development, in addition to providing sustained hemostasis without in-depth monitoring. It is a safe and effective management option for all HA patients, especially for patients with certain archetypes, such as those with inhibitors, those with high annualized bleed rates, those living far away from hemophilia care centers, pediatric patients and infants with intravenous access challenges, and those with a history of life-threatening bleeding events.

Efficacy and Nuances of Precision Molecular Engineering for Hodgkin's Disease to a Gene Therapeutic Approach.

Gene therapy is a particularly useful treatment for nervous system genetic diseases, including those induced especially by infectious organisms and antigens, and is being utilized to treat Hodgkin's disease (HD). Due to the possible clonal relationship between both disorders, immunotherapy directed against CD20 positive cells may be a more effective treatment in patients with persistent HD and NHL. HL growth can be inhibited both in vitro and in vivo by AdsIL-13Ralpha2. High-dose treatment combined with stem cell transplantation has been effective in treating HIV-negative lymphoma that has progressed to high-risk or relapsed disease. For therapy, LMP2-specific CTL will be used. Furthermore, it is possible to view the cytotoxicity of genetically modified adenoviruses that express proteins such as p27Kip1, p21Waf1, and p16INK4A as a foundational element for (2,5)-derived ALCL genetic treatment for Hodgkin's disease.

Real-time navigation of mecanum wheel-based mobile robot in a dynamic environment.

Path planning and control of a mobile robot, in a dynamic environment, has been an important research topic for many years. In this paper an algorithm for autonomous motion of a mobile robot is proposed, with mecanum wheels, to reach a goal while avoiding obstacles through the shortest path in a dynamic environment. The proposed method uses a hybrid A⁎ and a velocity obstacle algorithms for path planning and obstacle avoidance. The A⁎ algorithm is implemented to explore the shortest path from starting position to the goal while avoiding all the static obstacles. However, in real time applications the dynamic obstacles need to be avoided, therefore, for such a case velocity obstacle algorithm is unified with the A⁎ algorithm. Initially, the proposed algorithm is verified through simulations. Then it is implemented using experimental setup in real time environment using single and multiple static obstacles as well as on a dynamic obstacle. It can be observed that the robot reaches the goal, effectively by avoiding static and dynamic obstacles. Moreover, the performance of the proposed work is evaluated through qualitative comparison between proposed method and recently published work, showing that the proposed algorithm is gives better features than existing work. In the end, the possible application of mobile robot having mecanum wheels with proposed path planning method is also given in the paper.

Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era.

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Hand gesture recognition with deep residual network using Semg signal.

OBJECTIVES: To design and develop a classifier, named Sewing Driving Training based Optimization-Deep Residual Network (SDTO_DRN) for hand gesture recognition. METHODS: The electrical activity of forearm muscles generates the signals that can be captured with Surface Electromyography (sEMG) sensors and includes meaningful data for decoding both muscle actions and hand movement. This research develops an efficacious scheme for hand gesture recognition using SDTO_DRN. Here, signal pre-processing is done through Gaussian filtering. Thereafter, desired and appropriate features are extracted. Following that, effective features are chosen using SDTO. At last, hand gesture identification is accomplished based on DRN and this network is effectively fine-tuned by SDTO, which is a combination of Sewing Training Based Optimization (STBO) and Driving Training Based Optimization (DTBO). The datasets employed for the implementation of this work are MyoUP Dataset and putEMG: sEMG Gesture and Force Recognition Dataset. RESULTS: The designed SDTO_DRN model has gained superior performance with magnificent results by delivering a maximum accuracy of 0.943, True Positive Rate (TPR) of 0.929, True Negative Rate (TNR) of 0.919, Positive Predictive Value (PPV) of 0.924, and Negative Predictive Value (NPV) of 0.924. CONCLUSIONS: The hand gesture recognition using the proposed model is accurate and improves the effectiveness of the recognition.

Clinical outcomes and safety of immune checkpoint inhibitors in patients with solid tumors and paraneoplastic syndromes.

BACKGROUND: Patients with paraneoplastic syndromes (PNS) are excluded from clinical trials involving immune checkpoint inhibitors (ICIs) due to safety concerns. Moreover, real-world data on efficacy and safety is scarce. METHODS: In this retrospective study, data were collected on patients with PNS and solid tumors receiving ICI between 2015 and 2022 at nine institutions. Patients were classified into: Cohort 1 (pre-existing PNS before ICI initiation), cohort 2 (PNS during ICI treatment), and cohort 3 (PNS after ICI discontinuation). Patients with metastatic non-small cell lung cancer (NSCLC) (mNSCLC) from cohort 1 were matched to patients who were PNS-free at each institution up to a 1:3 ratio for age, sex, type of ICI, use of concurrent chemotherapy, and number of lines of systemic therapy prior to ICI initiation. Kaplan-Meier method was used to assess overall survival (OS) and time-to-next treatment (TTNT). RESULTS: Among 109 patients with PNS treated with ICIs, median age at ICI initiation was 67 years (IQR: 58-74). The most represented cancer type was NSCLC (n=39, 36%). In cohort 1 (n=55), PNS exacerbations occurred in 16 (29%) patients with median time to exacerbation after ICI of 1.1 months (IQR: 0.7-3.3). Exacerbation or de novo PNS prompted temporary/permanent interruption of ICIs in 14 (13%) patients. For cohort 2 (n=16), median time between ICI initiation and de novo PNS was 1.2 months (IQR: 0.4-3.5). Treatment-related adverse events (trAEs) occurred in 43 (39%) patients. Grade ≥3 trAEs occurred in 18 (17%) patients. PNS-directed immunosuppressive therapy was required in 55 (50%) patients. We matched 18 patients with mNSCLC and PNS (cohort 1) to 40 without PNS, treated with ICIs. There was no significant difference in OS or TTNT between patients with mNSCLC with and without PNS, although a trend was seen towards worse outcomes in patients with PNS. TrAEs occurred in 6/18 (33%) and 14/40 (35%), respectively. Grade ≥3 trAEs occurred in 4 (22%) patients with PNS and 7 (18%) patients without PNS. CONCLUSIONS: Exacerbations of pre-existing PNS occurred in 29% of patients treated with ICIs and both exacerbations and de novo PNS occur early in the ICI course. TrAE from ICIs were similar between patients with and without PNS. Our data suggest that pre-existing PNS should not preclude consideration of ICI therapy although patients may not derive the same clinical benefit compared with patients without PNS.

Multiscale tribology analysis of MHD hybrid nanofluid flow over a curved stretching surface.

In this study, we investigate the interactions of a hybrid nanofluid on a curved surface that is being stretched. The magnetic field is perpendicular to the flow and interacts with a mixture of molybdenum disulfide and argentum nanoparticles suspended in pure water, forming a hybrid nanomaterial. Our investigation considers heat transport analysis under different conditions, such as magnetohydrodynamic, Darcy-Forchheimer porous medium flow, Joule heating, and a convective boundary condition. We employ numerical and statistical methods to study the problem's intricacies comprehensively. Our findings indicate that Darcy-Forchheimer flow includes viscous and inertial forces, which results in higher flow rates and reduced skin friction. Additionally, the convective boundary condition leads to uniform temperature distribution within the hybrid material due to rapid internal heat transfer relative to surface resistance, significantly increasing the heat transfer rate.

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifically HDAC6 is required for the NLRP3 inflammasome to assemble and activate. Thus, NLRP3 serves as an attractive target for the development of novel therapeutic approaches. Several companies are now attempting to develop specific modulators of the NLRP3 inflammasome, but only a handful of small molecules of NLRP3 inflammasome inhibitors, such as MCC950 and Tranilast, are currently available for clinical use. However, their use is limited due to severe side effects and short half-lives. Thus, the repurposing of FDA-approved drugs with NLRP3 inhibitory activity is needed. The present study was aimed at repurposing preexisting drugs that might act as safe and effective NLRP3 inhibitors. A library of 2,697 FDA-approved drugs was screened for binding with NLRP3 (PDB: 7ALV) using Glide (Schrödinger). The top seven FDA-approved drugs with potential binding affinities were selected based on docking scores and subjected to ADMET profiling using pkCSM and SwissADME. The binding of the ADMET-favorable FDA-approved drugs to NLRP3 was validated using MMGBSA (Prime) and Molecular Dynamics (Desmond) in the Schrödinger suite. ADMET profiling revealed that of the seven best docking drugs, empagliflozin and citicoline had good drug-likeness properties. Moreover, MMGBSA analysis and molecular dynamics demonstrated that empagliflozin and citicoline exhibited stable ligand-NLRP3 interactions in the presence of solvents. This study sheds light on the ability of various FDA-approved drugs to act as NLRP3 inhibitors.Communicated by Ramaswamy H. Sarma.

Oncolytic Virotherapy: An Advanced Microbial Approach for the Management of Cancer.

Destruction of the tumor (cancerous) cells may be caused by live viruses, which have replicative ability and replicate selectively in tumor cells, known as oncolytic virotherapy. In comparison of conservative cancer therapy, tumor-selective replicating viruses have more advantages. These viruses have introduced new methodologies for the human cancer treatment. Numerous strategies are used in development of virotherapeutics. Virotherapy is not unusual concept, but modern advances in technology of genetic modification of oncolytic viruses have improved the ability of targeting tumor cells more specifically, it triggered the development of novel ammunition to fight cancer. An effective virotherapeutic approach with oncolytic viruses exhibits the feasibility and safety under clinical approach. New strategies are being explored to overcome basic obstacles and challenges in virotherapy. Administration of oncolytic viruses, logically, will successfully augment new treatments against many kinds of tumors. Some encouraging antitumor responses shown by combination therapy are provoking strong immunity against established cancer. Chief developments in oncolytic virotherapy have seen in past several years. Significant understandings have been provided by findings on the interface among immune comebacks and viruses, whereas potential results have shown in clinical trials.

Arboviruses: Transmission and Host Resistance.

In this review, there is a complete description of the classes of arboviruses, their evolutionary process, virus characterization, disease transmission methods; it also describes about the vectors involved in transmission and their mood of transmission, both biologically as well as non-biologically and, about host, the resistance mechanism in host, and artificial methods of preventing those viral transmissions. Arboviruses transmitted to hosts by some vectors such as mosquitoes, ticks, etc. The virus replicates in the host can be prevented by some host resistance mechanisms like RNA interference (RNAi), which degrade virus RNA by its antiviral activity, insect repellents, IGRs, and PI technology.

Advances in the Management of Neuroblastoma.

Neuroblastoma is a malignant tumor of neuroblasts, immature nerve cells found in several areas of the body. It usually affects children under age of 5. As usual, the tumor has ability to grow rapidly and to expand vastly which ultimately leads to death. Mostly, management decisions can be drawn by the prediction of the stage of the disease as well as age at the time of its diagnosis. There are four main stages of neuroblastoma, and treatment is according to the low and high risk of the disease. Several cytotoxic agents along with other therapies (antibody therapy, gene therapy, and even immunological therapies, antiangiogenic therapy, etc.) are used. Immunotherapy also has an important treatment option used nowadays for neuroblastoma. The discovery of major neuroblastoma-predisposition gene anaplastic lymphoma kinase cause somatic transformation or gene strengthening in diagnosed neuroblastoma. Promising new antiangiogenic strategies have also been introduced for the treatment of neuroblastoma with multiple mylomas. To manage numerous myelomas and cancers, including neuroblastoma, bone marrow transplantation and peripheral blood stem cell transplantation may be used.

Determinants of Diarrhea Among Children Aged 1 to 6 Years in Flood-Affected Areas of Pakistan: A Cross-Sectional Study.

Frequent floods can contribute to the spread of various diseases and complications, some of which may result in diarrhea, especially among children. The current study aimed to find the determinants of diarrhea among children aged 1-6 years in flood-affected areas in Khyber Pakhtunkhwa, Pakistan. A cross-sectional study was conducted in flood-affected districts. Data regarding sociodemographic information related to diarrhea and anthropometric data were collected through a validated questionnaire. Logistic regression was used to find the determinants of diarrhea. In the presence of diarrhea, the prevalences found of stunting, wasting, and being underweight were 75.2%, 76.5%, and 74.1%, respectively, which is higher than those in children without diarrhea (stunting, 24.8%; wasting, 23.5%; and being underweight, 25.9%). In bivariate regression, children aged 2-4 years (odds ratio [OR] = 1.65, P < 0.05), large family size (OR = 7.46, P < 0.01), low income (OR = 2.55, < 0.001), bathing in ponds (OR = 3.05, P < 0.05), drinking of untreated water (OR = 3, P < 0.05), flooding (OR = 1.8, P < 0.05), children living in mud houses (OR = 1.5, P < 0.05), and usage of utensils without lids (OR = 1.96, P < 0.001) were significantly associated with occurrence of diarrhea. In multivariate regression, the identified risk factors (P < 0.05) for diarrhea in flood-affected areas included illiterate mothers, flooding, large family size, households without livestock, poor water quality, untreated water, and lack of toilet facilities. In conclusion, addressing the determinants of diarrhea identified in this study is crucial for mitigating the impact of frequent floods on children in flood-affected areas. Moreover, the higher prevalence of malnutrition underscores the urgent need for comprehensive strategies and proper water, sanitation, and hygiene programs to reduce the occurrence and determinants of diarrhea.

Anesthetic Management of Emergency Insulinoma Resection: Case Report and Review of Literature.

Insulinoma, a neuroendocrine tumor originating from pancreatic islets, presents unique challenges in diagnosis and management. We present a case of a 73-year-old female with recurrent hypoglycemia leading to syncope, who underwent emergency pancreatectomy for a secreting insulinoma with multiple comorbidities. This case report aims to shed light on the complexities of insulinoma management and the importance of tailored perioperative strategies. The patient, presenting with severe hypoglycemia, was admitted for optimization. Preoperative assessment labeled her as ASA IVE and indicated a high risk of perioperative morbidity. General anesthesia, invasive monitoring, and epidural anesthesia were planned. Intraoperative glucose control was crucial, achieved with continuous blood glucose monitoring, octreotide administration, and insulin titration. The patient was extubated post-surgery, and pain was managed with epidural infusion. She was discharged on the 4th postoperative day with follow-up care. Insulinoma diagnosis relies on clinical, biochemical, and imaging tests, with 72-hour fasting as the gold standard. Localizing the tumor within the pancreas is essential for surgical success, often requiring invasive techniques. Surgical resection remains the definitive treatment, while medical management may be necessary in select cases. Anesthetic management should prioritize agents that minimize the cerebral metabolic rate for oxygen. Careful intraoperative glucose control and vigilant postoperative monitoring are essential. This case report highlights the intricate management of insulinoma, emphasizing tailored perioperative strategies that balance glucose regulation, anesthesia techniques, and postoperative care. However, the limited existing literature underscores the need for further research to refine anesthesia protocols, glucose control methods, and postoperative care, ultimately improving outcomes for patients with insulinoma.

Antibiofilm and anti-quorum sensing activity of Psidium guajava L. leaf extract: In vitro and in silico approach.

The quorum sensing mechanism relies on the detection and response to chemical signals, termed autoinducers, which regulate the synthesis of virulence factors including toxins, enzymes, and biofilms. Emerging therapeutic strategies for infection control encompass approaches that attenuate quorum-sensing systems. In this study, we evaluated the antibacterial, anti-quorum sensing, and anti-biofilm activities of Psidium guajava L. methanolic leaf extracts (PGME). Minimum Inhibitory Concentrations (MICs) of PGME were determined as 500 µg/ml for C. violaceum and 1000 µg/ml for P. aeruginosa PAO1. Significantly, even at sub-MIC concentrations, PGME exhibited noteworthy anti-quorum sensing properties, as evidenced by concentration-dependent inhibition of pigment production in C. violaceum 12742. Furthermore, PGME effectively suppressed quorum-sensing controlled virulence factors in P. aeruginosa PAO1, including biofilm formation, pyoverdin, pyocyanin, and rhamnolipid production, with concentration-dependent inhibitory effects. Phytochemical analysis utilizing GC-MS revealed the presence of compounds such as alpha-copaene, caryophyllene, and nerolidol. In-silico docking studies indicated a plausible mechanism for the observed anti-quorum sensing activity, involving favorable binding and interactions with QS-receptors, including RhlR, CviR', LasI, and LasR proteins. These interactions were found to potentially disrupt QS pathways through suppression of AHL production and receptor protein blockade. Collectively, our findings propose PGME as a promising candidate for the treatment of bacterial infections. Its attributes that mitigate biofilm development and impede quorum-sensing mechanisms highlight its potential therapeutic value.

Unlocking gut microbiota potential of dairy cows in varied environmental conditions using shotgun metagenomic approach.

Food security and environmental pollution are major concerns for the expanding world population, where farm animals are the largest source of dietary proteins and are responsible for producing anthropogenic gases, including methane, especially by cows. We sampled the fecal microbiomes of cows from varying environmental regions of Pakistan to determine the better-performing microbiomes for higher yields and lower methane emissions by applying the shotgun metagenomic approach. We selected managed dairy farms in the Chakwal, Salt Range, and Patoki regions of Pakistan, and also incorporated animals from local farmers. Milk yield and milk fat, and protein contents were measured and correlated with microbiome diversity and function. The average milk protein content from the Salt Range farms was 2.68%, with an average peak milk yield of 45 litters/head/day, compared to 3.68% in Patoki farms with an average peak milk yield of 18 litters/head/day. Salt-range dairy cows prefer S-adenosyl-L-methionine (SAMe) to S-adenosyl-L-homocysteine (SAH) conversion reactions and are responsible for low milk protein content. It is linked to Bacteroides fragilles which account for 10% of the total Bacteroides, compared to 3% in the Patoki region. The solid Non-Fat in the salt range was 8.29%, whereas that in patoki was 6.34%. Moreover, Lactobacillus plantarum high abundance in Salt Range provided propionate as alternate sink to [H], and overcoming a Methanobrevibacter ruminantium high methane emissions in the Salt Range. Furthermore, our results identified ruminant fecal microbiomes that can be used as fecal microbiota transplants (FMT) to high-methane emitters and low-performing herds to increase farm output and reduce the environmental damage caused by anthropogenic gases emitted by dairy cows.