Seroprevalence of SARS-CoV-2 infection in the general population of Nepal during the first and second generalized waves of the COVID-19 pandemic-2020-2021.

Few seroprevalence studies have been conducted on coronavirus disease (COVID-19) in Nepal. Here, we aimed to estimate seroprevalence and assess risk factors for infection in the general population of Nepal by conducting two rounds of sampling. The first round was in October 2020, at the peak of the first generalized wave of COVID-19, and the second round in July-August 2021, following the peak of the wave caused by the delta variant of SARS-CoV-2. We used cross-sectional probability-to-size (PPS)-based multistage cluster sampling to estimate the seroprevalence in the general population of Nepal at the national and provincial levels. We tested for anti-SARS-CoV-2 total antibody using the WANTAI SARS-CoV-2 Ab ELISA kit. In Round 1, the overall national seroprevalence was 14.4%, with provincial estimates ranging from 5.3% in Sudurpaschim to 27.3% in Madhesh Province. In Round 2, the estimated national seroprevalence was 70.7%, with the highest in the Madhesh Province (84.8%) and the lowest in the Gandaki Province (62.9%). Seroprevalence was comparable between males and females (Round 1, 15.8% vs. 12.2% and Round 2, 72.3% vs. 68.7%). The seroprevalence in the ecozones-Terai, hills, and mountains-was 76.3%, 65.3%, and 60.5% in Round 2 and 17.7%, 11.7%, and 4.6% in Round 1, respectively. In Nepal, COVID-19 vaccination was introduced in January 2021. At the peak of the first generalized wave of COVID-19, most of the population of Nepal remained unexposed to SARS-CoV-2. Towards the end of the second generalized wave in April 2021, two thirds of the population was exposed.

Facilitators and barriers for implementation of a novel resuscitation quality improvement package in public referral hospitals of Nepal.

BACKGROUND: Improving the healthcare providers (HCP) basic resuscitation skills can reduce intrapartum related mortality in low- and middle-income countries. However, the resuscitation intervention's successful implementation is largely dependent on proper facilitation and context. This study aims to identify the facilitators and barriers for the implementation of a novel resuscitation package as part of the quality improvement project in Nepal. METHODS: The study used a qualitative descriptive design. The study sites included four purposively chosen public hospitals in Nepal, where the resuscitation package (Helping Babies Breathe [HBB] training, resuscitation equipment and NeoBeat) had been implemented as part of the quality improvement project. Twenty members of the HCP, who were trained and exposed to the package, were selected through convenience sampling to participate in the study interviews. Data were collected through semi-structured interviews conducted via telephone and video calls. Twenty interview data were analyzed with a deductive qualitative content analysis based on the core components of the i-PARiHS framework. RESULTS: The findings suggest that there was a move to more systematic resuscitation practices among the staff after the quality improvement project's implementation. This positive change was supported by a neonatal heart rate monitor (NeoBeat), which guided resuscitation and made it easier. In addition, seeing the positive outcomes of successful resuscitation motivated the HCPs to keep practicing and developing their resuscitation skills. Facilitation by the project staff enabled the change. At the same time, facilitators provided extra support to maintain the equipment, which can be a challenge in terms of sustainability, after the project. Furthermore, a lack of additional resources, an unclear leadership role, and a lack of coordination between nurses and medical doctors were barriers to the implementation of the resuscitation package. CONCLUSION: The introduction of the resuscitation package, as well as the continuous capacity building of local multidisciplinary healthcare staff, is important to continue the accelerated efforts of improving newborn care. To secure sustainable change, facilitation during implementation should focus on exploring local resources to implement the resuscitation package sustainably. TRIAL REGISTRATION: Not applicable.

Fabrication and Synthesis of Thiococlchicoside loaded Matrix type Transdermal Patch.

BACKGROUND: The goal of this work was to synthesize and fabricate matrix type transdermal patches based on a combination of polymers (Eudragit L100, HPMC and PVP K30), plasticizer and crosslinking agents (propylene glycol and triethyl citrate) and adhesives (Dura Tak 87-6908) to increase Thiocolchicoside (THC) absorption via topical route. This method allows avoidance of first-pass metabolism along with a consistent and extended duration of therapeutic activity. METHODS: Fabrication and casting of polymeric solutions containing THC was done either in petri plates or through lab coater to get transdermal patches. Finally, the formulated patches were studied for their physicochemical and biological evaluation using scanning electron microscopy, FTIR, DSC, XRD and ex-vivo permeation studies using pig ear skin. RESULTS: FTIR studies confirm that the THC characteristics peaks (carbonyl (Amide I) at 1525.5 cm-1, C=O stretching (tropane ring) at 1664.4 cm-1, Amide II band (N-H stretching) at 3325.9cm-1, thioether band at 2360.7cm-1, and OH group stretching band at 3400.2 cm-1) are still present in the polymer mixture even after formulation as a transdermal patch, indicating compatibility among all excipients. While on the other hand, DSC studies confirm endothermic peaks for all the polymers along with THC with the highest enthalpy of 65.979 J/g, which is an indicator of sharp endothermic peak at 198℃, leading to the melting of THC. The percentage drug content and percentage moisture uptake of all the formulation was found in the range of 96±2.04 to 98.56±1.34% and 4.13±1.16 to 8.23±0.90%, respectively. Drug release and release kinetics studies confirm that it is dependent on the composition of individual formulation. CONCLUSION: All these findings support the possibility of using suitable polymeric composition, as well as proper formulation and manufacturing circumstances, to create a one-of-a-kind technology platform for transdermal drug administration.

MYC drives platinum resistant SCLC that is overcome by the dual PI3K-HDAC inhibitor fimepinostat.

BACKGROUND: Small cell lung cancer (SCLC) is an aggressive neuroendocrine cancer with an appalling overall survival of less than 5% (Zimmerman et al. J Thor Oncol 14:768-83, 2019). Patients typically respond to front line platinum-based doublet chemotherapy, but almost universally relapse with drug resistant disease. Elevated MYC expression is common in SCLC and has been associated with platinum resistance. This study evaluates the capacity of MYC to drive platinum resistance and through screening identifies a drug capable of reducing MYC expression and overcoming resistance. METHODS: Elevated MYC expression following the acquisition of platinum resistance in vitro and in vivo was assessed. Moreover, the capacity of enforced MYC expression to drive platinum resistance was defined in SCLC cell lines and in a genetically engineered mouse model that expresses MYC specifically in lung tumors. High throughput drug screening was used to identify drugs able to kill MYC-expressing, platinum resistant cell lines. The capacity of this drug to treat SCLC was defined in vivo in both transplant models using cell lines and patient derived xenografts and in combination with platinum and etoposide chemotherapy in an autochthonous mouse model of platinum resistant SCLC. RESULTS: MYC expression is elevated following the acquisition of platinum resistance and constitutively high MYC expression drives platinum resistance in vitro and in vivo. We show that fimepinostat decreases MYC expression and that it is an effective single agent treatment for SCLC in vitro and in vivo. Indeed, fimepinostat is as effective as platinum-etoposide treatment in vivo. Importantly, when combined with platinum and etoposide, fimepinostat achieves a significant increase in survival. CONCLUSIONS: MYC is a potent driver of platinum resistance in SCLC that is effectively treated with fimepinostat.

Spatial Patterning Analysis of Cellular Ensembles (SPACE) enables statistically robust discovery of complex spatial organization at the cell and tissue level.

Spatial patterns of cells and other entities drive both physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple entities in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex tissue images generated using any collection modality. Unlike existing platforms, SPACE detects context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles - single entities, pairs, triplets, and so on - and ranks the strongest patterns of tissue organization. Using lymph node images for which ground truth has been defined, we validate SPACE and demonstrate its advantages. We then use SPACE to reanalyze a public dataset of human tuberculosis granulomas, verifying known patterns and discovering new patterns with possible insights into disease progression.

Audit of Clinical Care Received by COVID-19 Patients Treated at a Tertiary Care Hospital of Nepal in 2021.

Like the world over, Nepal was also hard hit by the second wave of COVID-19. We audited the clinical care provided to COVID-19 patients admitted from April to June 2021 in a tertiary care hospital of Nepal. This was a cohort study using routinely collected hospital data. There were 620 patients, and most (458, 74%) had severe illness. The majority (600, 97%) of the patients were eligible for admission as per national guidelines. Laboratory tests helping to predict the outcome of COVID-19, such as D-dimer and C-reactive protein, were missing in about 25% of patients. Nearly all (>95%) patients with severe disease received corticosteroids, anticoagulants and oxygen. The use of remdesivir was low (22%). About 70% of the patients received antibiotics. Hospital exit outcomes of most (>95%) patients with mild and moderate illness were favorable (alive and discharged). Among patients with severe illness, about 25% died and 4% were critically ill, needing further referral. This is the first study from Nepal to audit and document COVID-19 clinical care provision in a tertiary care hospital, thus filling the evidence gap in this area from resource-limited settings. Adherence to admission guidelines was excellent. Laboratory testing, access to essential drugs and data management needs to be improved.

Recent Application of Artificial Intelligence in Non-Gynecological Cancer Cytopathology: A Systematic Review.

State-of-the-art artificial intelligence (AI) has recently gained considerable interest in the healthcare sector and has provided solutions to problems through automated diagnosis. Cytological examination is a crucial step in the initial diagnosis of cancer, although it shows limited diagnostic efficacy. Recently, AI applications in the processing of cytopathological images have shown promising results despite the elementary level of the technology. Here, we performed a systematic review with a quantitative analysis of recent AI applications in non-gynecological (non-GYN) cancer cytology to understand the current technical status. We searched the major online databases, including MEDLINE, Cochrane Library, and EMBASE, for relevant English articles published from January 2010 to January 2021. The searched query terms were: "artificial intelligence", "image processing", "deep learning", "cytopathology", and "fine-needle aspiration cytology." Out of 17,000 studies, only 26 studies (26 models) were included in the full-text review, whereas 13 studies were included for quantitative analysis. There were eight classes of AI models treated of according to target organs: thyroid (n = 11, 39%), urinary bladder (n = 6, 21%), lung (n = 4, 14%), breast (n = 2, 7%), pleural effusion (n = 2, 7%), ovary (n = 1, 4%), pancreas (n = 1, 4%), and prostate (n = 1, 4). Most of the studies focused on classification and segmentation tasks. Although most of the studies showed impressive results, the sizes of the training and validation datasets were limited. Overall, AI is also promising for non-GYN cancer cytopathology analysis, such as pathology or gynecological cytology. However, the lack of well-annotated, large-scale datasets with Z-stacking and external cross-validation was the major limitation found across all studies. Future studies with larger datasets with high-quality annotations and external validation are required.

Operational Gaps in Implementing the COVID-19 Case Investigation and Contact Tracing in Madhesh Province of Nepal, May-July 2021.

In Nepal, case investigation and contact tracing (CICT) was adopted as an important public health measure to reduce COVID-19 transmission. In this study, we assessed the performance of CICT in Madhesh Province of Nepal against national benchmarks, using routine programmatic data reported by district CICT teams. Between May and July 2021, 17,943 COVID-19 cases were declared in the province, among which case investigation was performed for 30% (95% CI: 29.6-31.0%) within 24 h (against 80% benchmark). As a result of case investigations, 6067 contacts were identified (3 contacts per 10 cases), of which 40% were traced and tested for SARS-CoV-2 infection (against 100% benchmark). About 60% of the contacts tested positive. At most 14% (95% CI: 13.1% to 14.9%) of traced contacts underwent a 14-day follow-up assessment (against 100% benchmark). We found the performance of the CICT program in Madhesh Province to be sub-optimal and call for corrective measures to strengthen CICT in the province and the country at large. Similar studies with wider geographical scope and longer time frames are needed to identify and address deficiencies in data recording and reporting systems for COVID-19, in low- and middle-income countries like Nepal and others.

COVID-19 Amongst Travelers at Points of Entry in Nepal: Screening, Testing, Diagnosis and Isolation Practices.

WHO recommends surveillance for COVID-19 among travelers at Points of Entry (POE) to countries. At 13 selected POE at the Nepal-India border, between March 2021 and July 2021, we describe the screening, testing, diagnosis and isolation practices of COVID-19 amongst travelers. Those who stayed in India or elsewhere for > one day and those who did not have a negative RT-PCR result within the last 72 h of travel were tested for COVID-19 with rapid antigen diagnostic tests. Daily surveillance reports maintained at POE were used for analysis. Of 337,338 travelers screened, 69,886 (21%) were tested and 3907 (6%) were diagnosed with COVID-19. The proportions tested averaged 15% during April-May when screened numbers were high and increased to 35% in July when screened numbers had decreased. The proportions diagnosed positive peaked at 10% in April-May, but decreased to below 1% in June and July. Testing coverage varied from 0−99% in the different POE. Most COVID-19 cases were Nepalese, male, <60 years of age, migrant workers and presented with fever. Of COVID-19 cases, 32% had home-based isolation, 64% underwent community-based isolation and the remainder either went to hospital or returned to India. In conclusion, about one fifth of travelers overall were tested, with coverage varying considerably over time and among different POE. Strengthening surveillance processes at POE is needed.

Tumor Budding as a Marker for Poor Prognosis and Epithelial-Mesenchymal Transition in Lung Cancer: A Systematic Review and Meta-Analysis.

Introduction: Currently, tumor budding (TB) is considered to predict the prognosis of patients. The prognostic significance of TB has also been explored in patients with lung cancer, but has not been fully clarified. In the present meta-analysis, we evaluated the prognostic significance, clinicopathological value, and relationship with epithelial-mesenchymal transition (EMT) of TB in lung cancer. Methods: The MEDLINE, EMBASE, and Cochrane databases were searched up to July 7, 2021, for the relevant articles that showed the relationship between TB and prognosis in patients with lung cancer. For statistical analysis, we used pooled hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) to assess the correlation between high-grade TB expression and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), clinicopathological factors, and EMT markers. Results: A total of 3,784 patients from 10 independent studies were included in the statistical analysis. Our results indicated that high-grade TB was significantly associated with poor OS [HR 1.64 (95% CI, 1.43-1.87)] and DFS [HR 1.65 (95% CI, 1.22-2.25)]. In terms of clinicopathological characteristics, high-grade TB was associated with larger tumor size, higher T and N stage, pleural invasion, vascular invasion, lymphatic invasion, and severe nuclear atypia. Interestingly, smoking showed significant association with high-grade TB, despite the fact that previous studies could not show a significant relationship between them. Furthermore, through our systematic analysis, high-grade TB showed a significant relationship with EMT markers. Conclusion: Our findings indicate that high-grade TB is associated with a worse prognosis in patients with lung cancer. TB evaluation should be implemented in routine pathological diagnosis, which may guide the patient's treatment.

Recent Applications of Artificial Intelligence from Histopathologic Image-Based Prediction of Microsatellite Instability in Solid Cancers: A Systematic Review.

Cancers with high microsatellite instability (MSI-H) have a better prognosis and respond well to immunotherapy. However, MSI is not tested in all cancers because of the additional costs and time of diagnosis. Therefore, artificial intelligence (AI)-based models have been recently developed to evaluate MSI from whole slide images (WSIs). Here, we aimed to assess the current state of AI application to predict MSI based on WSIs analysis in MSI-related cancers and suggest a better study design for future studies. Studies were searched in online databases and screened by reference type, and only the full texts of eligible studies were reviewed. The included 14 studies were published between 2018 and 2021, and most of the publications were from developed countries. The commonly used dataset is The Cancer Genome Atlas dataset. Colorectal cancer (CRC) was the most common type of cancer studied, followed by endometrial, gastric, and ovarian cancers. The AI models have shown the potential to predict MSI with the highest AUC of 0.93 in the case of CRC. The relatively limited scale of datasets and lack of external validation were the limitations of most studies. Future studies with larger datasets are required to implicate AI models in routine diagnostic practice for MSI prediction.

Current Trend of Artificial Intelligence Patents in Digital Pathology: A Systematic Evaluation of the Patent Landscape.

The integration of digital pathology (DP) with artificial intelligence (AI) enables faster, more accurate, and thorough diagnoses, leading to more precise personalized treatment. As technology is advancing rapidly, it is critical to understand the current state of AI applications in DP. Therefore, a patent analysis of AI in DP is required to assess the application and publication trends, major assignees, and leaders in the field. We searched five major patent databases, namely, those of the USPTO, EPO, KIPO, JPO, and CNIPA, from 1974 to 2021, using keywords such as DP, AI, machine learning, and deep learning. We discovered 6284 patents, 523 of which were used for trend analyses on time series, international distribution, top assignees; word cloud analysis; and subject category analyses. Patent filing and publication have increased exponentially over the past five years. The United States has published the most patents, followed by China and South Korea (248, 117, and 48, respectively). The top assignees were Paige.AI, Inc. (New York City, NY, USA) and Siemens, Inc. (Munich, Germany) The primary areas were whole-slide imaging, segmentation, classification, and detection. Based on these findings, we expect a surge in DP and AI patent applications focusing on the digitalization of pathological images and AI technologies that support the vital role of pathologists.

Tumor Budding in Gynecologic Cancer as a Marker for Poor Survival: A Systematic Review and Meta-Analysis of the Perspectives of Epithelial-Mesenchymal Transition.

This study aimed to assess the prognostic significance, assessment methods, and molecular features of tumor budding (TB). A literature search of Medline, EMBASE, Cochrane Library, and eleven cohort studies (seven cervical and four endometrial cancers) was conducted. Three assessment methods for TB involving 2009 patients were collected and constituted in the analysis. Our meta-analysis showed that TB was a marker of poor survival, regardless of the cancer origin site or assessment method (overall survival: hazard ratio [HR], 2.40; 95% confidence interval [CI], 1.82-3.17; disease-free survival: HR, 3.32; 95% CI, 2.46-4.48). In endometrial cancers, TB is associated with the epithelial-mesenchymal transition, microvessel density, and decreased hormone receptor expression. Thus, we suggest TB as a poor prognostic marker for all gynecologic cancers.

IBEX: an iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues.

High-content imaging is needed to catalog the variety of cellular phenotypes and multicellular ecosystems present in metazoan tissues. We recently developed iterative bleaching extends multiplexity (IBEX), an iterative immunolabeling and chemical bleaching method that enables multiplexed imaging (>65 parameters) in diverse tissues, including human organs relevant for international consortia efforts. IBEX is compatible with >250 commercially available antibodies and 16 unique fluorophores, and can be easily adopted to different imaging platforms using slides and nonproprietary imaging chambers. The overall protocol consists of iterative cycles of antibody labeling, imaging and chemical bleaching that can be completed at relatively low cost in 2-5 d by biologists with basic laboratory skills. To support widespread adoption, we provide extensive details on tissue processing, curated lists of validated antibodies and tissue-specific panels for multiplex imaging. Furthermore, instructions are included on how to automate the method using competitively priced instruments and reagents. Finally, we present a software solution for image alignment that can be executed by individuals without programming experience using open-source software and freeware. In summary, IBEX is a noncommercial method that can be readily implemented by academic laboratories and scaled to achieve high-content mapping of diverse tissues in support of a Human Reference Atlas or other such applications.

Understanding immunity in a tissue-centric context: Combining novel imaging methods and mathematics to extract new insights into function and dysfunction.

A central question in immunology is what features allow the immune system to respond in a timely manner to a variety of pathogens encountered at unanticipated times and diverse body sites. Two decades of advanced and static dynamic imaging methods have now revealed several major principles facilitating host defense. Suborgan spatial prepositioning of distinct cells promotes time-efficient interactions upon pathogen sensing. Such pre-organization also provides an effective barrier to movement of pathogens from parenchymal tissues into the blood circulation. Various molecular mechanisms maintain effective intercellular communication among otherwise rapidly moving cells. These and related discoveries have benefited from recent increases in the number of parameters that can be measured simultaneously in a single tissue section and the extension of such multiplex analyses to 3D tissue volumes. The application of new computational methods to such imaging data has provided a quantitative, in vivo context for cell trafficking and signaling pathways traditionally explored in vitro or with dissociated cell preparations. Here, we summarize our efforts to devise and employ diverse imaging tools to probe immune system organization and function, concluding with a commentary on future developments, which we believe will reveal even more about how the immune system operates in health and disease.

Prehypertension and its predictors among older adolescents: A cross-sectional study from eastern Nepal.

Prehypertension is a state of transition between normal blood pressure and hypertension. Adolescent prehypertension is a strong predictor of hypertension in adults and is now considered for cardiovascular intervention or risk reduction. This study was conducted among adolescents to assess the burden of pre-hypertension and its predictors. A cross-sectional study was conducted among grade 11 and 12 students in three districts in eastern Nepal namely Jhapa, Morang and Sunsari. Sampling was done using a multistage stratified proportionate random method. A semi-structured questionnaire adapted from the WHO STEPwise approach to the non-communicable disease risk factor surveillance (STEPS) instrument was used as a study tool after modification and pre-testing in addition to the anthropometric and blood pressure measurements by the investigators. The prevalence of prehypertension was assessed along with the identification of its predictors through multivariable binary logistic regression modelling. A total of 806 participants aged 15 to 19 years, with 57.1% female, participated in the study. Prehypertension was found in 20.8% (24.6% in males and 18.0% in females) of the participants, while 7.1% of them were hypertensive (9.2% males and 5.4% females). Obesity and central obesity were seen among 6.3% and 17.7% of the respondents respectively. Age, sex, ethnicity and obesity were found to be significantly associated with prehypertension. A significant proportion of prehypertension was seen among the adolescent population along with a notable presence of risk factors such as smoking, alcohol consumption, obesity, and eating out. This warrants careful consideration and identification of relevant strategies to reduce the burden of prehypertension via school-based interventions to reduce the modifiable risk factors.

Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Automatic pattern recognition using deep learning techniques has become increasingly important. Unfortunately, due to limited system memory, general preprocessing methods for high-resolution images in the spatial domain can lose important data information such as high-frequency information and the region of interest. To overcome these limitations, we propose an image segmentation approach in the compressed domain based on principal component analysis (PCA) and discrete wavelet transform (DWT). After inference for each tile using neural networks, a whole prediction image was reconstructed by wavelet weighted ensemble (WWE) based on inverse discrete wavelet transform (IDWT). The training and validation were performed using 351 colorectal biopsy specimens, which were pathologically confirmed by two pathologists. For 39 test datasets, the average Dice score, the pixel accuracy, and the Jaccard score were 0.804 ± 0.125, 0.957 ± 0.025, and 0.690 ± 0.174, respectively. We can train the networks for the high-resolution image with the large region of interest compared to the result in the low-resolution and the small region of interest in the spatial domain. The average Dice score, pixel accuracy, and Jaccard score are significantly increased by 2.7%, 0.9%, and 2.7%, respectively. We believe that our approach has great potential for accurate diagnosis.

High Poly(ADP-Ribose) Polymerase Expression Does Relate to Poor Survival in Solid Cancers: A Systematic Review and Meta-Analysis.

Poly (ADP-ribose) polymerase (PARP) is a DNA damage repair protein, and its inhibitors have shown promising results in clinical trials. The prognostic significance of PARP is inconsistent in studies of various cancers. In the present study, we conducted a systematic review and meta-analysis to reveal the prognostic and clinicopathological significance of PARP expression in multiple solid cancers. We searched the MEDLINE, EMBASE, and Cochrane databases for relevant research articles published from 2005 to 2021. The pooled hazard ratio (HR) with confidence interval (CI) was calculated to investigate the relationship between PARP expression and survival in multiple solid cancers. In total, 10,667 patients from 31 studies were included. A significant association was found between higher PARP expression and overall survival (OS) (HR = 1.54, 95% CI = 1.34-1.76, p < 0.001), disease-free survival (DFS) (HR = 1.15, 95% CI = 1.10-1.21, p < 0.001), and progression-free survival (PFS) (HR = 1.05, 95% CI = 1.03-1.08, p < 0.001). Subgroup analyses showed that PARP overexpression was significantly related to poor OS in patients with breast cancers (HR = 1.38, 95% CI = 1.28-1.49, p < 0.001), ovary cancers (HR = 1.21, 95% CI = 1.10-1.33, p = 0.001), lung cancers (HR = 2.11, 95% CI = 1.29-3.45, p = 0.003), and liver cancers (HR = 3.29, 95% CI = 1.94-5.58, p < 0.001). Regarding ethnicity, Asian people have almost twice their worst survival rate compared to Caucasians. The pooled odds ratio analysis showed a significant relationship between higher PARP expression and larger tumour size, poor tumour differentiation, lymph node metastasis, distant metastasis, higher TNM stage and lymphovascular invasion, and positive immunoreactivity for Ki-67, BRCA1, and BRCA2. In addition, nuclear expression assessed by the QS system using Abcam and Santa Cruz Biotechnology seems to be the most commonly used and reproducible IHC method for assessing PARP expression. This meta-analysis revealed that higher PARP expression was associated with a worse OS, DFS, and PFS in patients with solid cancers. Moreover, inhibition of this pathway through its specific inhibitors may extend the survival of patients with higher PARP expression.

A Comprehensive Overview on the Production of Vaccines in Plant-Based Expression Systems and the Scope of Plant Biotechnology to Combat against SARS-CoV-2 Virus Pandemics.

Many pathogenic viral pandemics have caused threats to global health; the COVID-19 pandemic is the latest. Its transmission is growing exponentially all around the globe, putting constraints on the health system worldwide. A novel coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), causes this pandemic. Many candidate vaccines are available at this time for COVID-19, and there is a massive international race underway to procure as many vaccines as possible for each country. However, due to heavy global demand, there are strains in global vaccine production. The use of a plant biotechnology-based expression system for vaccine production also represents one part of this international effort, which is to develop plant-based heterologous expression systems, virus-like particles (VLPs)-vaccines, antiviral drugs, and a rapid supply of antigen-antibodies for detecting kits and plant origin bioactive compounds that boost the immunity and provide tolerance to fight against the virus infection. This review will look at the plant biotechnology platform that can provide the best fight against this global pandemic.