SARS-CoV-2 infection and H1N1 vaccination: does a relationship between the two factors really exist? A retrospective analysis of a territorial cohort in Ferrara, Italy.

OBJECTIVE: SARS-CoV-2 has been compared with other strains of coronaviruses, SARS-CoV and MERS-CoV, and with the flu viruses: all of them manifest themselves with respiratory symptoms and, although their genetic patterns are similar, the spread of SARS-CoV-2 infection has quickly reached global dimensions, demonstrating that SARS-CoV-2 is a virus with greater spreading capacity, albeit less lethal. Compared with influenza viruses, coronaviruses have a longer incubation period and the patients with coronaviruses' syndromes develop more severe diseases requiring frequent hospitalizations and intensive care admissions. The aim was to explore the relationships between seasonal influenza vaccination and coronavirus infection and to understand whether this hypothetic role by the flu vaccines modifies SARS-CoV-2 infection's outcomes. PATIENTS AND METHODS: In this retrospective, multicenter study, we enrolled 952 patients diagnosed with SARS-CoV-2 infection; 448 were admitted to our two main hospitals in Ferrara territory, while the remaining 504 were isolated at home. We compared the group of patients who had been vaccinated for influenza in the previous 12 months to that of unvaccinated patients. RESULTS: Significant differences were found for both the need for hospitalization and 30-day mortality between vaccinated and unvaccinated patients. We found age to be the only independent risk factor for a worse 30-day prognosis, while gender, influenza vaccinations and age itself were independent risk factors for undergoing hospitalization. CONCLUSIONS: In our groups of patients, we found a relationship between seasonal influenza vaccinations and SARS-CoV-2 infection. Age seems to be the main risk factor for short-term mortality in COVID-19 inpatients, while the influenza vaccination is, together with gender and age itself, a determining factor in predicting the need for hospitalization.

Human papillomavirus vaccine effectiveness within a cervical cancer screening programme: cohort study.

OBJECTIVE: To assess the effectiveness of an HPV vaccination programme in reducing the risk of cervical abnormalities identified at subsequent screening. DESIGN: Retrospective cohort study using administrative health data. SETTING: General population of Ferrara Province, Italy. POPULATION: Female residents born in 1986-1993 and participating in the organized cervical screening programme in 2011-2018, who were eligible for HPV vaccination in catch-up cohorts. METHODS: Logistic regression to evaluate the potential association between abnormal cervical cytology and one, two, three or at least one dose of HPV vaccine. MAIN OUTCOME MEASURES: Cervical abnormalities, as predicted by low-grade or high-grade cytology, by number of vaccine doses, stratified by age. RESULTS: The sample consisted of 7785 women (mean age 27.5 years, SD 2.3). Overall, 391 (5.0%) were vaccinated with ≥1 dose and 893 (11.5%) had abnormal cytology. Women receiving at least one vaccine dose were significantly less likely to have an abnormal cytology (adjusted odds ratio 0.52; 95% confidence interval 0.34-0.79). Similar results were observed for women receiving a single dose, for both bivalent and quadrivalent vaccines, and applying buffer periods (excluding cytological outcomes within 1 month, 6 months and 1 year of the first dose). CONCLUSIONS: In the context of an organised cervical screening programme in Italy, catch-up HPV vaccination almost halved the risk of cytological abnormalities. TWEETABLE ABSTRACT: Among Ferrara women, vaccination against human papillomavirus halved the risk of screening cervical abnormalities.

A meta-analysis of the accuracy of a neuroendocrine tumor mRNA genomic biomarker (NETest) in blood.

BACKGROUND: The lack of an accurate blood biomarker in neuroendocrine tumor (NET) disease has hindered management. The advance of genomic medicine and the development of molecular biomarkers has provided a strategy-liquid biopsy-to facilitate real-time management. We reviewed the role of a blood mRNA-based NET biomarker, the NETest, as an in vitro diagnostic (IVD). PATIENTS AND METHODS: A systematic review of the literature using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was undertaken. The methodological quality was evaluated using the QUADAS-2 tool. We identified ten original scientific papers that met the inclusion criteria. These were assessed by qualitative analysis and thereafter meta-analysis. Data were pooled and a median [95% confidence interval (CI)] diagnostic odds ratio (DOR), positive likelihood ratio (+LR), and negative likelihood ratio (-LR) were calculated. For the meta-analysis, a generic inverse variance method was undertaken using the accuracy and area under the curve (AUC) data. RESULTS: The ten studies exhibited moderate to high methodological quality. They evaluated NETest usage both as a diagnostic and as a monitoring tool. The meta-analysis identified the diagnostic accuracy of the NETest to be 95%-96% with a mean DOR of 5 853, +LR of 195, and -LR of 0.06. The NETest was 84.5%-85.5% accurate in differentiating stable disease from progressive disease. As a marker of natural history, the accuracy was 91.5%-97.8%. As an interventional/response biomarker, the accuracy was 93.7%-97.4%. The pooled AUC for the NETest was 0.954 ± 0.005, with a z-statistic of 175.06 (P < 0.001). CONCLUSIONS: The NETest is an accurate biomarker suitable for clinical use in NET disease management. The meta-analysis supports the utility of the NETest as an IVD to establish a diagnosis and monitor therapeutic efficacy. The use of this as a biomarker provides information relevant to NET management consistent with observations regarding utility of liquid biopsies in other oncological disciplines.

Sodium-reduced lean sausages with fish oil optimized by a mixture design approach.

A partial NaCl replacement by KCl and sodium tripolyphosphate on low-fat meat sausages formulated with fish oil was studied using a mixture design. Thermal behavior by modulated differential scanning calorimetry, physicochemical, and textural properties were determined; afterwards they were mathematically modeled as a function of salts content. The thermo-rheological behavior of the different formulations was also studied in a control-stress rheometer. The optimal sodium reduction was found employing a desirability function approach. This formulation was experimentally validated and employed for microstructure analysis by environmental scanning microscopy. The results obtained in this work revealed that partial sodium replacement affected the matrix microstructure, but this change had no impact on sensory acceptability. In comparison with US and Argentinean commercial sausages, our product has 58% and 70% less Na(+) respectively.

Low-fat meat sausages with fish oil: optimization of milk proteins and carrageenan contents using response surface methodology.

Response surface methodology was used to analyze the effect of milk proteins and 2:1 κ:ι-carrageenans on cooking loss (CL), weight lost by centrifugation (WLC) and texture attributes of low-fat meat sausages with pre-emulsified fish oil. A central-composite design was used to develop models for the objective responses. Changes in carrageenans affected more the responses than milk proteins levels. Convenience functions were calculated for CL, WLC, hardness, and springiness of the product. Responses were optimized simultaneously minimizing CL and WLC; ranges for hardness and springiness corresponded to commercial products (20 g of pork fat/100 g). The optimum corresponded to 0.593 g of carrageenans/100 g and 0.320 g of milk proteins and its total lipid content was 6.3 g/100 g. This formulation was prepared and evaluated showing a good agreement between predicted and experimental responses. These additives could produce low-fat meat sausages with pre-emulsified fish oil with good nutritional quality and similar characteristics than traditional ones.

STK38 is a critical upstream regulator of MYC's oncogenic activity in human B-cell lymphoma.

The MYC protooncogene is associated with the pathogenesis of most human neoplasia. Conversely, its experimental inactivation elicits oncogene addiction. Besides constituting a formidable therapeutic target, MYC also has an essential function in normal physiology, thus creating the need for context-specific targeting strategies. The analysis of post-translational MYC activity modulation yields novel targets for MYC inactivation. Specifically, following regulatory network analysis in human B-cells, we identify a novel role of the STK38 kinase as a regulator of MYC activity and a candidate target for abrogating tumorigenesis in MYC-addicted lymphoma. We found that STK38 regulates MYC protein stability and turnover in a kinase activity-dependent manner. STK38 kinase inactivation abrogates apoptosis following B-cell receptor activation, whereas its silencing significantly decreases MYC levels and increases apoptosis. Moreover, STK38 knockdown suppresses growth of MYC-addicted tumors in vivo, thus providing a novel viable target for treating these malignancies.

Multivariate dependence and genetic networks inference.

A critical task in systems biology is the identification of genes that interact to control cellular processes by transcriptional activation of a set of target genes. Many methods have been developed that use statistical correlations in high-throughput data sets to infer such interactions. However, cellular pathways are highly cooperative, often requiring the joint effect of many molecules. Few methods have been proposed to explicitly identify such higher-order interactions, partially due to the fact that the notion of multivariate statistical dependence itself remains imprecisely defined. The authors define the concept of dependence among multiple variables using maximum entropy techniques and introduce computational tests for their identification. Synthetic network results reveal that this procedure uncovers dependencies even in undersampled regimes, when the joint probability distribution cannot be reliably estimated. Analysis of microarray data from human B cells reveals that third-order statistics, but not second-order ones, uncover relationships between genes that interact in a pathway to cooperatively regulate a common set of targets.

Effect of type of emulsifiers and antioxidants on oxidative stability, colour and fatty acid profile of low-fat beef burgers enriched with unsaturated fatty acids and phytosterols.

Low-fat beef burgers were formulated using fresh lean meat, 9.9% oleic sunflower oil and 0.1% deodorized fish oil to obtain a product enriched in unsaturated fatty acids. The effect of two emulsifiers (whey proteins or egg white) and natural antioxidants (tocopherols and/or oregano-rosemary), as well as the influence of frozen storage on the oxidative stability, colour, and fatty acid (FA) profile was determined on the cooked products. Whey proteins protected better against oxidation than egg white, and tocopherols demonstrated an adequate antioxidant effect in formulations with egg white. For all the formulations the unsaturated/saturated FA ratio was higher than 5.8, showing a good lipid balance in the products. The consumption of 100g of the cooked product would provide 6% of the recommended daily intake of phytosterols suggested to decrease cholesterol and the risk of heart disease. Formulated low-fat burgers with pre-emulsified oils and phytosterols could be considered to be potentially functional foodstuffs.

Innovations in the development of healthier chicken sausages formulated with different lipid sources.

Long-chain polyunsaturated n-3 fatty acids are critical nutrients for human health and the fortification of foods with these fatty acids is an important emerging area from the commercial and academic point of view. Development, characterization, and changes during refrigerated vacuum storage of low-fat chicken sausages formulated with preemulsified squid oil were examined and compared with those formulated with beef tallow. Physicochemical analysis and process yield after heat treatment were determined; the heat-treated sausages were evaluated by purge loss, color, texture, microstructure by SEM, microbial counts, fatty acid profile, lipid oxidation, and sensory analysis during refrigerated vacuum storage. Process yield of both formulations was higher than 97% and purge losses during storage were lower than 7%. Purge losses of oil-formulated sausages were lower than those with beef tallow. Sausages with squid oil resulted in higher lightness, lower redness and yellowness, and lower texture profile analysis parameters than the formulation prepared with beef tallow. Microstructure of both formulations was similar, except for the fat droplets that microscopic observations showed in the sausages made with beef tallow. Low lipid oxidation was detected in formulation with squid oil due to the the combination of ingredients and storage conditions. Microbial counts of both products were less than 5 log cfu/g at the end of 90 d of storage. The sausage formulated with squid oil presented more than 30 and 40 g/100 g of monounsaturated and polyunsaturated fatty acids, respectively. Docosahexaenoic acid was the predominant polyunsaturated fatty acid, followed by eicosapentaenoic acid and linoleic acid. Both products showed safe sanitary conditions, good sensory acceptability, and presented very good stability and quality attributes, but sausages formulated with squid oil showed a better fatty acid profile according to nutritional criteria.

Modeling heat transfer and inactivation of Escherichia coli O157:H7 in precooked meat products in Argentina using the finite element method.

The presence of Escherichia coli is linked with sanitary deficiencies and undercooking of meat products. Recent studies have detected E. coli O157:H7 in black blood sausages. Minimum time-temperature specifications to kill the bacteria were obtained by numerical simulations of the microscopic heat conduction equation using the finite element method, and calculating the temperature profile of the sausage and the population of E. coli at the coldest point during heating. The model was validated by heating sausages in a water-bath. The effects of heat transfer coefficients and water temperatures on the required time to achieve an inactivation value (IV) of 12(log) are reported. Macroscopic heat balances were simultaneously solved to consider the temperature drop in the water batch as a function of the ratio between the mass of thermally treated sausage and the heat capacity of the system.

Granulomatous lesions of the homolateral limb after previous mastectomy.

BACKGROUND: Granulomas may be classified as palisaded, sarcoidal, tuberculoid, suppurative and foreign body. In cancer patients they are defined as tumour-related sarcoid granulomas. Otherwise they are classified as granulomatous lesions of unknown significance. It is still unknown why neoplastic diseases are sometimes associated with granulomas. OBJECTIVES: To investigate granulomas found on the same side as a previous mastectomy. METHODS: We studied four women who had previously undergone mastectomy and presented with epithelioid cell granulomas of the same side as the previous mastectomy. CONCLUSIONS: The association between breast cancer and host granulomatous reaction is uncommon. The cases discussed may correspond to cutaneous tumour-related sarcoid granuloma reactions.

Gene expression profiling of B cell chronic lymphocytic leukemia reveals a homogeneous phenotype related to memory B cells.

B cell-derived chronic lymphocytic leukemia (B-CLL) represents a common malignancy whose cell derivation and pathogenesis are unknown. Recent studies have shown that >50% of CLLs display hypermutated immunoglobulin variable region (IgV) sequences and a more favorable prognosis, suggesting that they may represent a distinct subset of CLLs which have transited through germinal centers (GCs), the physiologic site of IgV hypermutation. To further investigate the phenotype of CLLs, their cellular derivation and their relationship to normal B cells, we have analyzed their gene expression profiles using oligonucleotide-based DNA chip microarrays representative of approximately 12,000 genes. The results show that CLLs display a common and characteristic gene expression profile that is largely independent of their IgV genotype. Nevertheless, a restricted number of genes (<30) have been identified whose differential expression can distinguish IgV mutated versus unmutated cases and identify them in independent panels of cases. Comparison of CLL profiles with those of purified normal B cell subpopulations indicates that the common CLL profile is more related to memory B cells than to those derived from naive B cells, CD5(+) B cells, and GC centroblasts and centrocytes. Finally, this analysis has identified a subset of genes specifically expressed by CLL cells of potential pathogenetic and clinical relevance.

Advances in sequence analysis.

In its early days, the entire field of computational biology revolved almost entirely around biological sequence analysis. Over the past few years, however, a number of new non-sequence-based areas of investigation have become mainstream, from the analysis of gene expression data from microarrays, to whole-genome association discovery, and to the reverse engineering of gene regulatory pathways. Nonetheless, with the completion of private and public efforts to map the human genome, as well as those of other organisms, sequence data continue to be a veritable mother lode of valuable biological information that can be mined in a variety of contexts. Furthermore, the integration of sequence data with a variety of alternative information is providing valuable and fundamentally new insight into biological processes, as well as an array of new computational methodologies for the analysis of biological data.

Systematic and fully automated identification of protein sequence patterns.

We present an efficient algorithm to systematically and automatically identify patterns in protein sequence families. The procedure is based on the Splash deterministic pattern discovery algorithm and on a framework to assess the statistical significance of patterns. We demonstrate its application to the fully automated discovery of patterns in 974 PROSITE families (the complete subset of PROSITE families which are defined by patterns and contain DR records). Splash generates patterns with better specificity and undiminished sensitivity, or vice versa, in 28% of the families; identical statistics were obtained in 48% of the families, worse statistics in 15%, and mixed behavior in the remaining 9%. In about 75% of the cases, Splash patterns identify sequence sites that overlap more than 50% with the corresponding PROSITE pattern. The procedure is sufficiently rapid to enable its use for daily curation of existing motif and profile databases. Third, our results show that the statistical significance of discovered patterns correlates well with their biological significance. The trypsin subfamily of serine proteases is used to illustrate this method's ability to exhaustively discover all motifs in a family that are statistically and biologically significant. Finally, we discuss applications of sequence patterns to multiple sequence alignment and the training of more sensitive score-based motif models, akin to the procedure used by PSI-BLAST. All results are available at httpl//www.research.ibm.com/spat/.

Analysis of gene expression microarrays for phenotype classification.

Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized by a given phenotype and for a set of control cells, an important problem is to identify "patterns" of gene expression that can be used to predict cell phenotype. The potential number of such patterns is exponential in the number of genes. In this paper, we propose a solution to this problem based on a supervised learning algorithm, which differs substantially from previous schemes. It couples a complex, non-linear similarity metric, which maximizes the probability of discovering discriminative gene expression patterns, and a pattern discovery algorithm called SPLASH. The latter discovers efficiently and deterministically all statistically significant gene expression patterns in the phenotype set. Statistical significance is evaluated based on the probability of a pattern to occur by chance in the control set. Finally, a greedy set covering algorithm is used to select an optimal subset of statistically significant patterns, which form the basis for a standard likelihood ratio classification scheme. We analyze data from 60 human cancer cell lines using this method, and compare our results with those of other supervised learning schemes. Different phenotypes are studied. These include cancer morphologies (such as melanoma), molecular targets (such as mutations in the p53 gene), and therapeutic targets related to the sensitivity to an anticancer compounds. We also analyze a synthetic data set that shows that this technique is especially well suited for the analysis of sub-phenotype mixtures. For complex phenotypes, such as p53, our method produces an encouragingly low rate of false positives and false negatives and seems to outperform the others. Similar low rates are reported when predicting the efficacy of experimental anticancer compounds. This counts among the first reported studies where drug efficacy has been successfully predicted from large-scale expression data analysis.

SPLASH: structural pattern localization analysis by sequential histograms.

MOTIVATION: The discovery of sparse amino acid patterns that match repeatedly in a set of protein sequences is an important problem in computational biology. Statistically significant patterns, that is patterns that occur more frequently than expected, may identify regions that have been preserved by evolution and which may therefore play a key functional or structural role. Sparseness can be important because a handful of non-contiguous residues may play a key role, while others, in between, may be changed without significant loss of function or structure. Similar arguments may be applied to conserved DNA patterns. Available sparse pattern discovery algorithms are either inefficient or impose limitations on the type of patterns that can be discovered. RESULTS: This paper introduces a deterministic pattern discovery algorithm, called Splash, which can find sparse amino or nucleic acid patterns matching identically or similarly in a set of protein or DNA sequences. Sparse patterns of any length, up to the size of the input sequence, can be discovered without significant loss in performances. Splash is extremely efficient and embarrassingly parallel by nature. Large databases, such as a complete genome or the non-redundant SWISS-PROT database can be processed in a few hours on a typical workstation. Alternatively, a protein family or superfamily, with low overall homology, can be analyzed to discover common functional or structural signatures. Some examples of biologically interesting motifs discovered by Splash are reported for the histone I and for the G-Protein Coupled Receptor families. Due to its efficiency, Splash can be used to systematically and exhaustively identify conserved regions in protein family sets. These can then be used to build accurate and sensitive PSSM or HMM models for sequence analysis. AVAILABILITY: Splash is available to non-commercial research centers upon request, conditional on the signing of a test field agreement. CONTACT: acal@us.ibm.com, Splash main page http://www.research.ibm.com/splash

Clinical trial of the efficacy and safety of oral etretinate with calcipotriol cream compared with etretinate alone in moderate-severe psoriasis.

BACKGROUND: The aim of this clinical trial was to assess the efficacy and safety of calcipotriol cream associated with oral etretinate compared with etretinate alone in the treatment of moderate-severe psoriasis. METHODS: This controlled multicenter trial, within patients (hemiparts), enrolled 86 in- or out-patients (62 males, 24 females), mean (+/-SD) age 57.1 +/- 14.2 years, with psoriasis vulgaris on both sides of the body, and mean (+/-SE) baseline PASI score (Psoriasis Area and Severity Index) 30.7 +/- 0.9. All patients took oral etretinate 50 mg/day and applied calcipotriol cream (50 microg/g) on one half of their body twice a day. Treatment was continued for 9 weeks, and patients were seen every 3 weeks. RESULTS: At the end of the first 3 weeks the PASI score indicated a significant clinical difference between the two sides of the body (P < 0.001, ANOVA), with a reduction of 50.7% in the score for the calcipotriol-treated half, compared with a 39% reduction for the untreated half. By the 9th week of treatment the PASI score was 81.4% lower on the treated half, and 70.3% on the untreated side (P < 0.001, ANOVA). CONCLUSIONS: These findings suggest that patients with moderate-severe psoriasis might benefit from treatment with etretinate plus calcipotriol, with the aim of achieving a faster response and an overall smaller total dose of etretinate.

Diaper dermatitis in an adult. A case of erythema papuloerosive of Sevestre and Jacquet.

BACKGROUND: Irritants, friction and occlusion favor dermatitis or inflammatory reactions in the diaper area. Diaper dermatitis is not found exclusively in children but also in adults wearing a diaper for urinary incontinence. CASE: We report a case of eroded papules on the labia majora in a woman with urinary incontinence. CONCLUSION: Erythema papuloerosive of Sevestre and Jacquet is an unusual dermatitis due to irritant agents in the diaper area that may also affect adults. As this dermatitis may resemble neoplasia and venereal disease, it can be easily misdiagnosed, especially in adults.