Category: Nevin Manimala

J Biophotonics. 2021 May 27:e202100041. doi: 10.1002/jbio.202100041. Online ahead of print.

ABSTRACT

The histopathological diagnosis of cancer is the current gold standard to differentiate normal from cancerous tissues. We propose a portable platform prototype to characterize the tissue’s thermal and optical properties, and their inter-dependencies to potentially aid the pathologist in making an informed decision. The measurements were performed on samples from 10 samples from 5 subjects, where the cancerous and adjacent normal were extracted from the same patient. It was observed that thermal conductivity (k) and reduced-scattering-coefficient (μ’_s ) for both the cancerous and normal tissues reduced with the rise in tissue temperature. Comparing cancerous and adjacent normal tissue, the difference in k and μ’_s (at 940 nm) were statistically significant (p = 7.94e-3), while combining k and μ’_s achieved the highest statistical significance (6.74e-4). These preliminary results promise and support testing on a large number of samples for rapidly differentiating cancerous from adjacent normal tissues. This article is protected by copyright. All rights reserved.

PMID:34042303 | DOI:10.1002/jbio.202100041

Transbound Emerg Dis. 2021 May 27. doi: 10.1111/tbed.14171. Online ahead of print.

ABSTRACT

A classical swine fever (CSF) epidemic has been ongoing in Japan since September 2018. The outbreak started in Gifu Prefecture and involved 21 prefectures by the end of October 2020, posing a serious threat to pork industries. The present study was conducted to capture the spatiotemporal dynamics of CSF in Japan and assess the geographic range of the CSF vaccination on pig farms. First infection dates were collected for wild boars and on swine farms by prefecture. A simple statistical model was used to describe the spatiotemporal dynamics of CSF, describing the infection risk in wild boars and the subsequent transmission hazards to swine farms for 47 prefectures. Because the spatial transmission mechanisms and wild boar population dynamics involved substantial uncertainties, 16 models were applied to the empirical data. Estimated hazard parameters were used to predict the risk of infection on swine farms by 15 December 2020 to explicitly evaluate the governmental recommendation for vaccinations on pig farms by prefecture in light of the predicted infection risk in domestic pigs. The best-fit model for the wild boars indicated that transmission occurred via neighboring prefectures and involved seasonality. The estimated conditional hazard was 0.008 (95% confidence interval [CI]:0.001-0.014) per day for infections transmitted from wild boars to swine farms, and the median time from wild boar infection to swine farm infection was 129.4 days (95% CI: 69.5-935.0). Our prediction indicated that prefectures connected by land to those with wild boar infections had a higher risk of infection on swine farms. CSF transmission in Japan likely progressed diffusively via wild boar movement, and tracking wild boar infections may help determine the risk of infection on swine farms. Our risk map highlights the importance of deciding vaccination policies according to predicted risk. This article is protected by copyright. All rights reserved.

PMID:34042305 | DOI:10.1111/tbed.14171

Ying Yong Sheng Tai Xue Bao. 2021 May;32(5):1554-1562. doi: 10.13287/j.1001-9332.202105.017.

ABSTRACT

Based on the construction of ecological network in Tianjin in 2000, 2010 and 2020, we evaluated the structural evolution of Tianjin ecological network from the multi-dimensional perspective of source-corridor-node-whole, using complex network evaluation index and landscape pattern index integrated with the stability, uniformity and connectivity indices. The results showed that from 2000 to 2020, the ecological source areas in Tianjin significantly shrank and degraded, be uneven in spatial distribution. Ecological corridors became sparse. Landscape fragmentation and shape complexity first increased and then decreased. The average length of corridors in 2000 and 2010 was shorter, with the bioflow efficiency being relatively high. In 2000, 2010, and 2020, the number of nodes with high significance accounted for 35.7%, 29.4% and 21.4% of the statistical nodes respectively. In 2020, the network connectivity robustness and vulnerability robustness showed substantial fluctuation, and the network was the most unstable. In 2010, the ecological network was of high connectivity and complexity, while in 2000 and 2020, it was more general. In 2000, the network uniformity was the highest, followed by 2010, and lowest in 2020.

PMID:34042349 | DOI:10.13287/j.1001-9332.202105.017

Am J Hum Biol. 2021 May 27:e23620. doi: 10.1002/ajhb.23620. Online ahead of print.

NO ABSTRACT

PMID:34042248 | DOI:10.1002/ajhb.23620

Clin Cardiol. 2021 May 27. doi: 10.1002/clc.23649. Online ahead of print.

ABSTRACT

BACKGROUND: The RE-DUAL PCI trial demonstrated that in patients with nonvalvular atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI), dual therapy with dabigatran and a P2Y₁₂ inhibitor, either clopidogrel or ticagrelor, reduced the risk of bleeding without an increased risk of thromboembolic events as compared to triple therapy with warfarin in addition to a P2Y₁₂ inhibitor and aspirin. What remains unclear is whether this effect is consistent between males and females undergoing PCI.

HYPOTHESIS: The reduction in risk of bleeding without increased risk of thromboembolic events with dual therapy with dabigatran and a P2Y₁₂ inhibitor in comparison to triple therapy with warfarin, a P2Y₁₂ inhibitor and aspirin is consistent in females and males.

METHODS: The primary safety endpoint was the first International Society on Thrombosis and Hemostasis (ISTH) major bleeding event (MBE) or clinically relevant non-major bleeding event (CRNMBE). The efficacy endpoint was the composite of death, thromboembolic event (stroke, myocardial infarction, and systemic embolism) or unplanned revascularization. Cox proportional hazard regression analyses were applied to calculate corresponding hazard ratios and interaction p values for each endpoint.

RESULTS: A total of 655 women and 2070 men were enrolled. The risk of major or CRNM bleeding was lower with both dabigatran 110 mg dual therapy and dabigatran 150 mg dual therapy compared with warfarin triple therapy in female and male patients (for 110 mg: females: HR 0.69, 95% CI 0.47-1.01, males: HR 0.46, 95% CI 0.37-0.59, interaction p value: 0.084 and for 150 mg: females HR 0.74, 95% CI 0.48-1.16, males HR 0.71, 95% CI 0.56-0.90, interaction p value: 0.83). There was also no detectable difference in the composite efficacy endpoint of death, thromboembolic events or unplanned revascularization between dabigatran dual therapy and warfarin triple therapy, with no statistically significant interaction between sex and treatment (interaction p values: 0.73 and 0.72, respectively).

CONCLUSIONS: Consistent with the overall study results, the risk of bleeding was lower with dabigatran 110 mg and 150 mg dual therapy compared with warfarin triple therapy, and risk of thromboembolic events was comparable with warfarin triple therapy independent of the patient’s sex.

PMID:34042199 | DOI:10.1002/clc.23649

Histopathology. 2021 May 27. doi: 10.1111/his.14421. Online ahead of print.

ABSTRACT

AIMS: There is widespread perception in clinic and pathology, that the histomorphological assessment of minor salivary gland tumours (MinSG) is more difficult and hampared by more misdiagnoses than that of major salivary glands. This is based on a vague, subjective clinical impression, while scientific proof of the difference and of potentional reasons that would explain this are lacking.

METHODS AND RESULTS: We identified fourteen putative clinical, pathological, and combined clinico-pathological reasons, which altogether could explain the phenomenon of perceived greater diagnostic difficulty of tumours of MinSG. We performed a comprehensive literature search and a statistical comparison of data from a large personal consultation series (biased for difficult cases) with cumulative data from straightforward, unselected (non-consultation) series from the literature. By that comparison we could prove with statistical significance a comprehensive series of reasons, as well as of consequences of greater diagnostic difficulty in MinSG.

CONCLUSIONS: Within the 14 criteria a high frequency of initial incisional biopsies and of low-grade category in malignant tumours emerged as the two most important reasons for enhanced diagnostic difficulty. Very rare entities, unusual locations, shortcomings in clinico-pathological communication, as well as pecularities of the special anatomic location of the hard palate, such as tumour necrosis, mucosal ulceration, pseudoinvasion, and the peculiar phenomenon of “tumoural-mucosal fusion”, contribute to further diagnostic difficulties. The awareness of these shortcomings and pitfalls enables a series of recommendations for clinic and pathology, which might help aid assessment and reduce the rate of misdiagnosis in tumours of MinSG.

PMID:34042205 | DOI:10.1111/his.14421

Inflamm Bowel Dis. 2021 May 27:izab117. doi: 10.1093/ibd/izab117. Online ahead of print.

ABSTRACT

BACKGROUND: Improving treatment outcomes with biological therapy is a demanding current need for patients with inflammatory bowel disease. Discovery of pretreatment prognostic indicators of response may facilitate patient selection and increase long-term remission rates. We aimed to identify baseline mucosal gene expression profiles with predictive value for subsequent response to or failure of treatment with the monoclonal antibody against integrin α4β7, vedolizumab, in patients with active ulcerative colitis (UC).

METHODS: Mucosal expression of 84 immunological and inflammatory genes was quantified in RNA extracted from colonic biopsies before vedolizumab commencement and compared between patients with or without response to treatment. Significantly differentiated genes were further validated in a larger patient cohort and within available public data sets, and their functional profiles were studied accordingly.

RESULTS: In the discovery cohort, we identified 21 genes with a statistically significant differential expression between 54-week responders and nonresponders to vedolizumab. Our validation study allowed us to recognize a “core” mucosal profile that was preserved in both discovery and validation cohorts and in the public database. The applied functional annotation and analysis revealed candidate dysregulated pathways in nonresponders to vedolizumab, including immune cell trafficking, TNF receptor superfamily members mediating noncanonical NF-kB pathway, in addition to interleukin signaling, MyD88 signaling, and toll-like receptors (TLRs) cascade.

CONCLUSIONS: Nonresponse to vedolizumab in UC is associated with specific pretreatment gene-expression mucosal signatures and dysregulation of particular immunological and inflammatory pathways. Baseline mucosal and/or systemic molecular profiling may help in the optimal stratification of patients to receive vedolizumab for active UC.

PMID:34042157 | DOI:10.1093/ibd/izab117

Histol Histopathol. 2021 May 27:18346. doi: 10.14670/HH-18-346. Online ahead of print.

ABSTRACT

AIM: To investigate whether USP18 can be used as a predictive marker for the diagnosis and development of colorectal cancer.

METHODS: The Gene Expression Omnibus (GEO) Dataset and the Cancer Genome Atlas (TCGA) database were used to select differential proteins for the ubiquitin-specific peptidases (USPs). The extensive target prediction and network analysis methods were used to assess the association with the USP18 interacting proteins, as well as the statistical correlation between USP18 and the clinical pathology parameters. The effects of USP18 on the proliferation of colorectal cancer were examined using CCK8. The effects of USP18 on the migration of colorectal cancer were examined using wound healing assays. Immunohistochemistry (IHC) was performed on the tissue microarray.

RESULTS: The results showed that the expression of USP18 was related to age (P=0.014). The positive rates of the USP18 protein in T1, T2, T3, and T4 were 0.00%, 22.92%, 78.38%, and 95.35%, respectively (P<0.00). The positive rates of the USP18 protein in I, II, III, and IV were 47.43%, 83.12%, 66.67%, and 100.00%, respectively (P<0.00). The Western blot assay showed that the expression of USP18 in colorectal cancer tissues was significantly higher than that in matched paracancerous tissues (P<0.05). The CCK8 experiments suggested that USP18 promoted the migration of CRC cells. Wound healing assays suggested that USP18 promoted the proliferation of CRC cells.

CONCLUSION: This study showed that USP18 can promote the proliferation of colorectal cancer cells and might be a potential biomarker for the diagnosis of CRC.

PMID:34042164 | DOI:10.14670/HH-18-346

Pathologica. 2021 Apr;113(2):102-114. doi: 10.32074/1591-951X-217.

ABSTRACT

BACKGROUND: Forkhead box (FOX) A1 is a potential therapeutic biomarker that has been investigated in various human cancers. Limited data exist about FOXA1 biologic role in epithelial ovarian cancer (EOC).

AIM: This study assessed FOXA1 immunohistochemical (IHC) expression and evaluated its association with clinico-pathological parameters in EOC including overall and disease-free survivals (OS, DFS) and patient’s outcome.

METHODS: Patient’s socio-epidemiologic, clinical, radiological, laboratory, surgical, and follow-up data were collected. After histopathologic typing, grading and staging, FOXA1 IHC expression was scored in 98 EOC specimens. Clinico-pathological associations were investigated in high-and low-FOXA1 expression groups using appropriate statistical methods. Kaplan-Meier method was used for survival analysis.

RESULTS: FOXA1 tumor cell nuclear staining was detected in 63.3% of EOC with weak, moderate and strong scores (28.6%, 12.2% and 22.5% respectively). Comparing high- and low-expression groups (34.7% and 65.3% respectively), high FOXA1 was associated with larger tumors, low mean serum CA-125, tumor histopathology (mucinous and low-grade serous), type I EOC, limited tumor’s anatomical extent, absence of nodal or distant metastases and omental nodules, earlier FIGO stages, non-recurrent tumors and survival advantage with longer and OS and DFS (all p ≤ 0.05). Independent predictors of high FOXA1 expression included: omental nodules, tumor’s anatomical extent and tumor’s size (p ≤ 0.001, = 0.046 and = 0.023 respectively).

CONCLUSION: FOXA1 is frequently expressed in EOC notably mucinous and low-grade serous carcinomas in association with favorable prognostic clinico-pathological parameters and longer OS and DFS. It likely has a suppressor function in EOC and could be recommended as a prognostic and therapeutic biomarker.

PMID:34042091 | DOI:10.32074/1591-951X-217

JMIRx Med. 2021 May 5;2(2):e20617. doi: 10.2196/20617. eCollection 2021 Apr-Jun.

ABSTRACT

With over 117 million COVID-19-positive cases declared and the death count approaching 3 million, we would expect that the highly digitalized health systems of high-income countries would have collected, processed, and analyzed large quantities of clinical data from patients with COVID-19. Those data should have served to answer important clinical questions such as: what are the risk factors for becoming infected? What are good clinical variables to predict prognosis? What kinds of patients are more likely to survive mechanical ventilation? Are there clinical subphenotypes of the disease? All these, and many more, are crucial questions to improve our clinical strategies against the epidemic and save as many lives as possible. One might assume that in the era of big data and machine learning, there would be an army of scientists crunching petabytes of clinical data to answer these questions. However, nothing could be further from the truth. Our health systems have proven to be completely unprepared to generate, in a timely manner, a flow of clinical data that could feed these analyses. Despite gigabytes of data being generated every day, the vast quantity is locked in secure hospital data servers and is not being made available for analysis. Routinely collected clinical data are, by and large, regarded as a tool to inform decisions about individual patients, and not as a key resource to answer clinical questions through statistical analysis. The initiatives to extract COVID-19 clinical data are often promoted by private groups of individuals and not by health systems, and are uncoordinated and inefficient. The consequence is that we have more clinical data on COVID-19 than on any other epidemic in history, but we have failed to analyze this information quickly enough to make a difference. In this viewpoint, we expose this situation and suggest concrete ideas that health systems could implement to dynamically analyze their routine clinical data, becoming learning health systems and reversing the current situation.

PMID:34042100 | PMC:PMC8104306 | DOI:10.2196/20617