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Xiao Jiang,1 Faheem Ahmed Khan,1 Min Qi Ow,2 Hermione Mei Niang Poh2 1Department of Intensive Care Medicine, Ng Teng Fong General Hospital, Singapore; 2Department of Medical Informatics, Ng Teng Fong General Hospital, SingaporeCorrespondence: Xiao Jiang, Department of intensive Care Medicine, Ng Teng Fong General Hospital, Tower B, Level4, ICM office, 1 Jurong East Street 21, 609606, Singapore, Email xiaoj2015@gmail.comBackground: Sepsis is a common indication for intensive care unit (ICU) admission and is associated with significant mortality and morbidity. The aim of our study was to first assess the incidence, severity, short-term and long-term mortality of sepsis in a combined medical and surgical high dependency/ ICU in Singapore, and to identify factors associated with increasing short-term and long-term mortality.Methods: All admissions from July 1 to December 31, 2017 were retrospectively screened and clinical data were collected. Patients were followed up until 3 years post ICU admission.Results: Of a total 1526 admissions, 281 had infection at ICU admission, and 254 (16.6%) fulfilled sepsis-3 criteria for sepsis. A total of 141 (9.2%) had septic shock. The 30-day, 1-year, 2-year and 3-year mortality of sepsis patients were 19.3%, 25.2%, 30.3% and 32.3%, respectively. Lung was the most common site of infection. Compared with 30-day sepsis survivors, non-survivors were older (median age 70 vs 63, P < 0.001), had higher percentage of lung infection (65.3% vs 36.1%, P < 0.05), higher admission Sequential Organ Failure Assessment (SOFA) score (median 9 vs 5, P < 0.001), and longer ICU stay (median days: 4 vs 3, P = 0.037). In stepwise Cox regression analysis, lung infection was an independent risk factor for both increasing 30-day and 3-year mortality. Immunocompromised host, increasing age and SOFA score were associated with higher 30-day mortality. Diabetes, admission quick Sequential Organ Failure Assessment (qSOFA) score > 1 and unplanned ICU re-admission were associated with increasing 3-year mortality in 30-day survivors.Conclusion: Our retrospective cohort single center study first reported sepsis admission incidence of 16.6% in a combined medical and surgical high dependency/ICU in Singapore, with significant short-term and long-term mortality. Lung infection was an independent risk factor for both 30-day and 3-year mortality.Keywords: sepsis, septic shock, incidence, severity, mortality, intensive care unit

Guangyu He,1 Amos Z Dai,2 Vamiq M Mustahsan,1 Christopher L Blum,2 Imin Kao,1 Fazel A Khan2 1Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY, USA; 2Department of Orthopedics, Stony Brook University Hospital, Stony Brook, NY, USACorrespondence: Fazel A Khan, Email fazel.khan@stonybrookmedicine.eduIntroduction: Computer navigation and customized 3D-printed jigs improve accuracy during bone tumor resection, but such technologies can be bulky, costly, and require intraoperative radiation, or long lead time to be ready in OR.Methods: We developed a method utilizing a compact, inexpensive, non-X-ray based 3D surface light scanner to provide a visual aid that helps surgeons accurately draw osteotomy lines on the surface of exposed bone to reproduce a well-defined preoperative bone resection plan. We tested the accuracy of the method on 18 sawbones using a distal femur hemimetaphyseal resection model and compared it with a traditional, freehand method.Results: The method significantly reduces the positional error from 2.53 (± 1.13) mm to 1.04 (± 0.43) mm (p< 0.001), and angular error of the front angle from 2.10° (± 0.83°) to 0.80° (± 0.66°) (p=0.001). The method also reduces the mean maximum deviation of the bone resection, with respect to the preoperative path, from 3.75mm to 2.69mm (p=0.003). However, no increased accuracy was observed at the back side of the bone surface where this method would not be expected to provide information.Discussion: In summary, we developed a novel 3D-LAD navigation technology. From the experimental study, we demonstrated that the method can improve the ability of surgeons to accurately draw the preoperative osteotomy lines and perform resection of a primary bone sarcoma, with comparison to traditional methods, using 18 sawbones.Keywords: computer-assist surgery, 3D light assisted drawing, osteotomy lines, structured-light scanning, surgical technique

Brett E Youngerman, Farhan A Khan, Guy M McKhannDepartment of Neurological Surgery, Columbia University Medical Center, New York, NY, USAAbstract: For patients with drug-resistant epilepsy, surgical intervention may be an effective treatment option if the epileptogenic zone (EZ) can be well localized. Subdural strip and grid electrode (SDE) implantations have long been used as the mainstay of intracranial seizure localization in the United States. Stereoelectroencephalography (SEEG) is an alternative approach in which depth electrodes are placed through percutaneous drill holes to stereotactically defined coordinates in the brain. Long used in certain centers in Europe, SEEG is gaining wider popularity in North America, bolstered by the advent of stereotactic robotic assistance and mounting evidence of safety, without the need for catheter-based angiography. Rates of clinically significant hemorrhage, infection, and other complications appear lower with SEEG than with SDE implants. SEEG also avoids unnecessary craniotomies when seizures are localized to unresectable eloquent cortex, found to be multifocal or nonfocal, or ultimately treated with stereotactic procedures such as laser interstitial thermal therapy (LITT), radiofrequency thermocoagulation (RF-TC), responsive neurostimulation (RNS), or deep brain stimulation (DBS). While SDE allows for excellent localization and functional mapping on the cortical surface, SEEG offers a less invasive option for sampling disparate brain areas, bilateral investigations, and deep or medial targets. SEEG has shown efficacy for seizure localization in the temporal lobe, the insula, lesional and nonlesional extra-temporal epilepsy, hypothalamic hamartomas, periventricular nodular heterotopias, and patients who have had prior craniotomies for resections or grids. SEEG offers a valuable opportunity for cognitive neurophysiology research and may have an important role in the study of dysfunctional networks in psychiatric disease and understanding the effects of neuromodulation.Keywords: stereoelectroencephalography, SEEG, epilepsy surgery, cognitive neurophysiology, psychiatric neurosurgery

Firdos Alam Khan, Dana Almohazey, Munthar Alomari, Sarah Ameen Almofty Department of Stem Cell Biology, Institute for Research and Medical Consultations, Imam Abdulrahman Bin Faisal University, Dammam, Kingdom of Saudi Arabia Abstract: Nanoparticles have enormous applications in textiles, cosmetics, electronics, and pharmaceuticals. But due to their exceptional physical and chemical properties, particularly antimicrobial, anticancer, antibacterial, anti-inflammatory properties, nanoparticles have many potential applications in diagnosis as well as in the treatment of various diseases. Over the past few years, nanoparticles have been extensively used to investigate their response on the neuronal cells. These nanoparticles cause stem cells to differentiate into neuronal cells and promote neuronal cell survivability and neuronal cell growth and expansion. The nanoparticles have been tested both in in vitro and in vivo models. The nanoparticles with various shapes, sizes, and chemical compositions mostly produced stimulatory effects on neuronal cells, but there are few that can cause inhibitory effects on the neuronal cells. In this review, we discuss stimulatory and inhibitory effects of various nanoparticles on the neuronal cells. The aim of this review was to summarize different effects of nanoparticles on the neuronal cells and try to understand the differential response of various nanoparticles. This review provides a bird’s eye view approach on the effects of various nanoparticles on neuronal differentiation, neuronal survivability, neuronal growth, neuronal cell adhesion, and functional and behavioral recovery. Finally, this review helps the researchers to understand the different roles of nanoparticles (stimulatory and inhibitory) in neuronal cells to develop effective therapeutic and diagnostic strategies for neurodegenerative diseases. Keywords: nanoparticles, neuron biology, neuroprotection, neurotoxicity

Using the concept of - -proximal mapping, we study the existence and sensitivity analysis of solution of a parametric general variational-like inequality problem in uniformly smooth Banach space. The approach used may be treated as an extension and unification of approaches for studying sensitivity analysis for various important classes of variational inequalities given by many authors in this direction.

Breast cancer (BC) continues to be a primary worldwide health concern despite the tremendous efforts made to deploy novel chemotherapeutic techniques for the treatment of BC. It is, therefore, essential to elucidate better plant-based compounds targeting deregulated signaling components in various cancer cell types. Our objective was to elucidate a potent targeted therapeutic approach by exploiting the anticancerous potential of carvacrol in MDA-MB-231 cells via employing silicon and in vitro approaches. In silico analysis was executed to identify the anticancer potential of carvacrol against BC via targeting crucial signaling component of the NOTCH pathway, namely Jagged-1 and its downstream target cyclin D1. In vitro, assays were also employed to display the antiproliferative potential of carvacrol at the mRNA level in MDA-MB-231 cells via targeting Jagged-1 and cyclin D1 genes. Docking studies using CB DOCK displayed better binding energy of carvacrol (Jagged-1: −5.0 and cyclin D1: −5.8) in comparison to the standard drug, 5-fluorouracil (Jagged-1: −4.5; cyclin D1: −4.6) against these crucial targets. Carvacrol potentially downregulated the expression of these crucial genes along with caspase-mediated apoptosis induction. However, more in vitro assays must be employed to validate its candidature for drug development against BC. This study provided a novel insight into the targeted therapeutic approach using natural products and deregulated signaling components for managing breast carcinoma.

Herein, capsaicin nanoparticles (NPs) were prepared by two different methods, namely, evaporative precipitation of nanosuspension (EPN) and anti-solvent precipitation with a syringe pump (APSP). The nanoparticles of the necessary sizes were obtained after optimizing experimental parameters such as the solvent-to-anti-solvent ratio and stirring speed. They had spherical shapes and an average diameter of 171.29 ± 1.94 and 78.91 ± 0.54 nm when prepared using the EPN and APSP methods, respectively. Differential scanning calorimetry and an X-ray diffractometer showed that the capsaicin crystallinity decreased. FTIR results showed that the NPs were produced with their original configuration and did not result in the synthesis of any additional structures. The NP formulation had a desirable drug content. They surpassed the unprocessed drug in solubility and displayed the desired stability. Capsaicin NP cream showed many folds of enhanced analgesic, anti-inflammatory, and antimicrobial effects compared to unprocessed capsaicin.

Steganography, an intricate technique that discreetly conceals information within innocuous carrier files, has become indispensable for safeguarding confidential communication. Hence, a comprehensive exploration of its multifaceted aspects and constituent elements is imperative to grasp Steganography’s nuanced layers of security. This discourse endeavors to illuminate the profound essence of security within Steganography, encompassing pivotal facets such as confidentiality, integrity, and resilience against emerging threats. Developing an innovative and secure reversible Steganography algorithm rooted in the Least Significant Bit (LSB) methodology assumes paramount significance in attaining these lofty security objectives. This imperative arises from the escalating demand for secure communication across public networks, necessitating techniques to ensure the confidentiality and integrity of transmitted data. Reversible steganographic approaches, characterized by their ability to extract the original image and embedded data without loss, hold particular relevance in domains where the intrinsic value of the original image is irreplaceable, as exemplified in medical imaging and satellite applications. Preserving the embedded data’s security is critical to forestall unauthorized access or tampering. Thus, the employment of secure reversible image Steganography techniques within the spatial domain emerges as a vital strategy in fortifying the protection of sensitive information while upholding the sanctity and confidentiality of the original image. In this vein, the scrutiny of Kerckhoff’s principle, which accentuates the reliance of system security on the secrecy of the key rather than the algorithm, assumes significance in ensuring robust security protocols. Our research underscores the indispensable nature of adhering to Kerckhoff’s principle and mandating the obliviousness of bit embedding locations within the cover image for the enduring prevalence of secure Steganography, particularly in the face of well-known cover attacks.

The current study aimed to assess the neuroprotective effect of Zn and Fe oxide nanoparticles biofabricated by Taverniera glabra in alloxan-induced diabetic rats. The experimental animals (160–200 g) were divided into nine groups (n = 9). The blood glucose, body weight, glucose-6-phosphate dehydrogenase (G6PD), superoxide dismutase (SOD), catalase test (CAT), lipid peroxidation (TBARS), glutathione (GSH), and acetylcholinesterase (AChE) activities were determined. Oral administration of nanoparticles and T. glabra methanol extract (TGME; 10 and 15 mg/kg b.w) significantly decreased the glucose level, increased the body weight, controlled the quantitative level of G6PD, and significantly decreased the levels of ALT, ALP, cholesterol, and creatinine. Moreover, TGME and their Zn and Fe oxide nanoparticles significantly restored the antioxidant enzymes (SOD, CAT, GPx, and GSH) that decreased during induced diabetes. In the diabetic group, a significant increase in TBARS was noted and recovered in diabetic animals (p < 0.05) as compared to glibenclamide. The AChE activity was significantly recovered by nanoparticles and TGME both in the blood and brain of the diabetic group (p < 0.05). Taken together, it can be suggested that TGME and Zn and Fe oxide nanoparticles significantly improved memory and could be considered as an effective biogenic nanomaterial for diabetes, Alzheimer’s disease, and oxidative stress.

Plant-derived bioactive compounds displayed major therapeutic and chemo-preventive roles in the pathogenesis of numerous chronic malignancies such as cancer and enhanced oxidative stress and inflammation. Antioxidants found in food, such as genkwanin, may reduce oxidative stress and the release of cytokines or pathways that promote inflammation. The goal of this work is to summarize the potential for anticancer effects of genkwanin, a methoxyflavone that is present in a variety of plant species. This review examined and analyzed numerous research studies on identifying, isolating, measuring, and analyzing anticancer properties of genkwanin. The mechanisms involved cellular and molecular activities at various levels, including apoptosis induction and cancer cell growth and proliferation inhibition. Preclinical studies have demonstrated genkwanin’s effects and mechanism of action; however, further research is required to investigate its therapeutic potential thoroughly. Additional research is needed to further our understanding of the pharmacodynamic effects of genkwanin. Additional toxicological study is necessary to evaluate the clinical efficacy and safety of genkwanin, which would help scientists to elucidate a potent drug candidate for cancer management.

Lung cancer is a substantial health issue globally, and it is one of the main causes of mortality. Malignant mesothelioma (MM) is a common kind of lung cancer. The majority of patients with MM have no symptoms. In the diagnosis of any disease, etiology is crucial. MM risk factor detection procedures include positron emission tomography, magnetic resonance imaging, biopsies, X-rays, and blood tests, which are all necessary but costly and intrusive. Researchers primarily concentrated on the investigation of MM risk variables in the study. Mesothelioma symptoms were detected with the help of data from mesothelioma patients. The dataset, however, included both healthy and mesothelioma patients. Classification algorithms for MM illness diagnosis were carried out using computationally efficient data mining techniques. The support vector machine outperformed the multilayer perceptron ensembles (MLPE) neural network (NN) technique, yielding promising findings. With 99.87% classification accuracy achieved using 10-fold cross-validation over 5 runs, SVM is the best classification when contrasted to the MLPE NN, which achieves 99.56% classification accuracy. In addition, SPSS analysis is carried out for this study to collect pertinent and experimental data.

Due to urban sprawl, the demand for land has increased for the purpose of construction. It is unlikely that soil available at different construction sites will be suitable for designed structures. For improving the load-bearing capacity of the soil, different soil binders are used, which are present in distinct states. In this review, the authors have collected details about various binders, which are generally used in the soil stabilization, and their effect as a binding agent on the soil. In this article, the authors tried to review different traditional binders. After studying various research articles, the authors found that lime, ground-granulated blast slag (GGBS) polypropylene, polyurethane grouting, and asphalt mix are frequently used binders. However, the authors also gathered information about the negative environmental impact of these traditional soil binders, which led to the need for alternatives to these commonly used soil binders. To diminish this issue, different alternate hydraulic and non-hydraulic binders are discussed. The authors found alternatives to cement and lime with the alkali-activated material consisting of Na2O and silica modulus and belite-calcium sulfoaluminate ferrite, which is also known as “Aether™.” According to the research, both alternatives emit 20–30% less CO2 into the environment and also improve the compressive strength of the soil. The various studies promotes bitumen modification. Incorporating 20-mesh crumb rubber and bio-oil into the bitumen reduces its viscosity and improves its fatigue value. When waste oil is mixed with asphalt, it revitalizes the bitumen, improves fatigue resistance, and increases compressive strength. The soil particles treated by Eko soil are held together by enzymes, which give them the same strength as cement. Apart from that, low-carbon binders such as basic oxygen furnace slag, bamboo fiber, enzyme-based soil treatment, zebu manure for stabilization, and lignin-contained biofuels and coproducts are discussed. Replacing these traditional binders helps with energy savings. All waste products are recycled, and energy is saved by not manufacturing traditional binders. Additionally, energy is saved, which is required to avoid the detrimental effects of these conventional binders, making them energy-efficient alternate binders. The authors also summarize the methods used, impacts, and changes that occur in soil properties after using substitutes in place of traditional binders. From the review, the authors determined that different binders have various properties in terms of chemical and physical compositions, and they show different variations in terms of strength when added to soil with low bearing capacity or poor stability.

The CMS Submission Infrastructure (SI) is the main computing resource provisioning system for CMS workloads. A number of HTCondor pools are employed to manage this infrastructure, which aggregates geographically distributed resources from the WLCG and other providers. Historically, the model of authentication among the diverse components of this infrastructure has relied on the Grid Security Infrastructure (GSI), based on identities and X509 certificates. In contrast, commonly used modern authentication standards are based on capabilities and tokens. The WLCG has identified this trend and aims at a transparent replacement of GSI for all its workload management, data transfer and storage access operations, to be completed during the current LHC Run 3. As part of this effort, and within the context of CMS computing, the Submission Infrastructure group is in the process of phasing out the GSI part of its authentication layers, in favor of IDTokens and Scitokens. The use of tokens is already well integrated into the HTCondor Software Suite, which has allowed us to fully migrate the authentication between internal components of SI. Additionally, recent versions of the HTCondor-CE support tokens as well, enabling CMS resource requests to Grid sites employing this CE technology to be granted by means of token exchange. After a rollout campaign to sites, successfully completed by the third quarter of 2022, the totality of HTCondor CEs in use by CMS are already receiving Scitoken-based pilot jobs. On the ARC CE side, a parallel campaign was launched to foster the adoption of the REST interface at CMS sites (required to enable token-based job submission via HTCondor-G), which is nearing completion as well. In this contribution, the newly adopted authentication model will be described. We will then report on the migration status and final steps towards complete GSI phase out in the CMS SI.

The former CMS Run 2 High Level Trigger (HLT) farm is one of the largest contributors to CMS compute resources, providing about 25k job slots for offline computing. This CPU farm was initially employed as an opportunistic resource, exploited during inter-fill periods, in the LHC Run 2. Since then, it has become a nearly transparent extension of the CMS capacity at CERN, being located on-site at the LHC interaction point 5 (P5), where the CMS detector is installed. This resource has been configured to support the execution of critical CMS tasks, such as prompt detector data reconstruction. It can therefore be used in combination with the dedicated Tier 0 capacity at CERN, in order to process and absorb peaks in the stream of data coming from the CMS detector. The initial configuration for this resource, based on statically configured VMs, provided the required level of functionality. However, regular operations of this cluster revealed certain limitations compared to the resource provisioning and use model employed in the case of WLCG sites. A new configuration, based on a vacuum-like model, has been implemented for this resource in order to solve the detected shortcomings. This paper reports about this redeployment work on the permanent cloud for an enhanced support to CMS offline computing, comparing the former and new models’ respective functionalities, along with the commissioning effort for the new setup.

While the computing landscape supporting LHC experiments is currently dominated by x86 processors at WLCG sites, this configuration will evolve in the coming years. LHC collaborations will be increasingly employing HPC and Cloud facilities to process the vast amounts of data expected during the LHC Run 3 and the future HL-LHC phase. These facilities often feature diverse compute resources, including alternative CPU architectures like ARM and IBM Power, as well as a variety of GPU specifications. Using these heterogeneous resources efficiently is thus essential for the LHC collaborations reaching their future scientific goals. The Submission Infrastructure (SI) is a central element in CMS Computing, enabling resource acquisition and exploitation by CMS data processing, simulation and analysis tasks. The SI must therefore be adapted to ensure access and optimal utilization of this heterogeneous compute capacity. Some steps in this evolution have been already taken, as CMS is currently using opportunistically a small pool of GPU slots provided mainly at the CMS WLCG sites. Additionally, Power9 processors have been validated for CMS production at the Marconi-100 cluster at CINECA. This note will describe the updated capabilities of the SI to continue ensuring the efficient allocation and use of computing resources by CMS, despite their increasing diversity. The next steps towards a full integration and support of heterogeneous resources according to CMS needs will also be reported.

The computing resource needs of LHC experiments are expected to continue growing significantly during the Run 3 and into the HL-LHC era. The landscape of available resources will also evolve, as High Performance Computing (HPC) and Cloud resources will provide a comparable, or even dominant, fraction of the total compute capacity. The future years present a challenge for the experiments’ resource provisioning models, both in terms of scalability and increasing complexity. The CMS Submission Infrastructure (SI) provisions computing resources for CMS workflows. This infrastructure is built on a set of federated HTCondor pools, currently aggregating 400k CPU cores distributed worldwide and supporting the simultaneous execution of over 200k computing tasks. Incorporating HPC resources into CMS computing represents firstly an integration challenge, as HPC centers are much more diverse compared to Grid sites. Secondly, evolving the present SI, dimensioned to harness the current CMS computing capacity, to reach the resource scales required for the HLLHC phase, while maintaining global flexibility and efficiency, will represent an additional challenge for the SI. To preventively address future potential scalability limits, the SI team regularly runs tests to explore the maximum reach of our infrastructure. In this note, the integration of HPC resources into CMS offline computing is summarized, the potential concerns for the SI derived from the increased scale of operations are described, and the most recent results of scalability test on the CMS SI are reported.

Scattered data interpolation plays an important role in computer graphics and scientific visualization. This method can be used to interpolate any regular or irregular data sets. For instance, rainfall distribution is an example of an irregular data that usually appear in statistics. In this study, cubic Bézier-Like triangular patches defined on triangular domain is used to interpolate rainfall data sets. From graphical results, we obtain a very smooth surface. Therefore, the proposed scheme can be used to interpolate and provide a good visualization to the given irregular data sets.

These days vaccines are considered the best economical and effective technique for preventing and handling bacterial infections, like human papillomavirus (HPV) or meningitis, allergies, autoimmune Relevant Disorders, Microbial Infections, and many more viral diseases. Annually millions of lives are saved from death-causing infections and other relevant disorders with the help of proper immunization with the help of vaccines. But still, many diseases are not yet preventable by vaccines and there is a chance of the improvement of current vaccines with help of many approaches. One of these is a compound known as a virosome, which is produced when pure haemagglutinin and neuraminidase projections of the influenza virus surface are removed from viral envelope and deposited on the exterior of unilamellar liposomes.Studies have shown that in order to attain the desired therapeutic effect, a physical attachment between the target antigen and the virosomal carrier is necessary. A virosome can bind to and “infect” host cells and deliver the antigen directly into the processing pathway which is an Alternatively, the virosome may be phagocytosed by an APC. So Our review gives a novel idea of the vector technology for vaccine delivery, its properties, method of preparation, and importance as well as some applications of different virosomal vaccine discoveries.

Spam is any form of annoying and unsought digital communication sent in bulk and may contain offensive content feasting viruses and cyber-attacks. The voluminous increase in spam has necessitated developing more reliable and vigorous artificial intelligence-based anti-spam filters. Besides text, an email sometimes contains multimedia content such as audio, video, and images. However, text-centric email spam filtering employing text classification techniques remains today's preferred choice. In this paper, we show that text pre-processing techniques nullify the detection of malicious contents in an obscure communication framework. We use Spamassassin corpus with and without text pre-processing and examined it using machine learning (ML) and deep learning (DL) algorithms to classify these as ham or spam emails. The proposed DL-based approach consistently outperforms ML models. In the first stage, using pre-processing techniques, the long-short-term memory (LSTM) model achieves the highest results of 93.46% precision, 96.81% recall, and 95% F1-score. In the second stage, without using pre-processing techniques, LSTM achieves the best results of 95.26% precision, 97.18% recall, and 96% F1-score. Results show the supremacy of DL algorithms over the standard ones in filtering spam. However, the effects are unsatisfactory for detecting encrypted communication for both forms of ML algorithms.