El niño abusado se convierte en adulto: reflexiones sobre algunos casos tratados

Este artículo es la traducción del titulado “Il bambino abusato diventa adulto”, publicado en el número 91 de la revista Terapia Familiare (noviembre 2009, páginas 161-182). Traducción de Valentina Capecci, Gonzalo del Moral y Miguel Garrido.El autor analiza algunos casos clínicos para reflexionar sobre diferentes resultados que la experiencia del abuso sexual sufrido en la infancia puede tener en la influencia del desarrollo de un sujeto de sexo masculino. Se proponen tres distintas posibilidades que se pueden detectar en la población clínica. La clásica trasformación de víctima a agresor, la persistencia, por el contrario, en la posición de víctima y aquella del espectador relativa a los hermanos varones de víctimas de sexo femenino. Los recursos ofrecidos por el modelo de apego (ofrecido por el progenitor protector, y también por el mismo abusador) en relación a la dimensión del miedo suscitado por el evento traumático juegan un papel determinante en la dirección que puede tomar la evolución del niño abusado.The author analyzes some cases clinicians to reflect on different results than the experience of the sexual abuse suffered in childhood can have on the influence of development of a male subject. Proposed three different possibilities that are they can detect in the clinical population. The classical transformation of victim to aggressor, the persistence, on the contrary, in the position of victim and one the relative to the victims of female male brothers spectator. The resources offered by the attachment (offered by the parent) model (guard, and also by the same abuser) in relation to the dimension of the fear aroused by the traumatic event play a decisive role in the address that can take the evolution of the abused child

Analytical evaluation of QuantiFERON- Plus and QuantiFERON- Gold In-tube assays in subjects with or without tuberculosis

The QuantiFERON-TB Gold Plus (QFT-Plus) represents the new QuantiFERON-TB Gold In-tube (QFT-GIT) to identify latent tuberculosis infection (LTBI). The main differences is the addition of a new tube containing shorter peptides stimulating CD8 T-cells. Aim of this study is to evaluate the accuracy of QFT-Plus compared with QFT-GIT in a cross sectional study of individuals with or without tuberculosis (TB). We enrolled 179 participants: 19 healthy donors, 58 LTBI, 33 cured TB and 69 active TB. QFT-Plus and QFT-GIT were performed. The two tests showed a substantial agreement. Moreover we found a similar sensitivity in active TB and same specificity in healthy donors. A higher proportion of the LTBI subjects responded to both TB1 and TB2 compared to those with active TB (97% vs 81%). Moreover, a selective response to TB2 was associated with active TB (9%) and with a severe TB disease, suggesting that TB2 stimulation induces a CD8 T-cell response in absence of a CD4-response. In conclusion, QFT-Plus and QFT-GIT assays showed a substantial agreement and similar accuracy for active TB detection. Interestingly, a higher proportion of the LTBI subjects responded concomitantly to TB1 and TB2 compared to those with active TB, whereas a selective TB2 response associated with active TB

MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

Background: Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to implement and externally validate a magnetic resonance imaging (MRI)-based radiomics pipeline to predict response to treatment and to investigate the impact of manual and automatic segmentations on the radiomics models. Methods: Ninety-five patients with stage II/III LARC who underwent multiparametric MRI before chemoradiotherapy and surgical treatment were enrolled from three institutions. Patients were classified as responders if tumour regression grade was 1 or 2 and nonresponders otherwise. Sixty-seven patients composed the construction dataset, while 28 the external validation. Tumour volumes were manually and automatically segmented using a U-net algorithm. Three approaches for feature selection were tested and combined with four machine learning classifiers. Results: Using manual segmentation, the best result reached an accuracy of 68% on the validation set, with sensitivity 60%, specificity 77%, negative predictive value (NPV) 63%, and positive predictive value (PPV) 75%. The automatic segmentation achieved an accuracy of 75% on the validation set, with sensitivity 80%, specificity 69%, and both NPV and PPV 75%. Sensitivity and NPV on the validation set were significantly higher (p = 0.047) for the automatic versus manual segmentation. Conclusion: Our study showed that radiomics models can pave the way to help clinicians in the prediction of tumour response to chemoradiotherapy of LARC and to personalise per-patient treatment. The results from the external validation dataset are promising for further research into radiomics approaches using both manual and automatic segmentations

MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

BACKGROUND: Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to implement and externally validate a magnetic resonance imaging (MRI)-based radiomics pipeline to predict response to treatment and to investigate the impact of manual and automatic segmentations on the radiomics models. METHODS: Ninety-five patients with stage II/III LARC who underwent multiparametric MRI before chemoradiotherapy and surgical treatment were enrolled from three institutions. Patients were classified as responders if tumour regression grade was 1 or 2 and nonresponders otherwise. Sixty-seven patients composed the construction dataset, while 28 the external validation. Tumour volumes were manually and automatically segmented using a U-net algorithm. Three approaches for feature selection were tested and combined with four machine learning classifiers. RESULTS: Using manual segmentation, the best result reached an accuracy of 68% on the validation set, with sensitivity 60%, specificity 77%, negative predictive value (NPV) 63%, and positive predictive value (PPV) 75%. The automatic segmentation achieved an accuracy of 75% on the validation set, with sensitivity 80%, specificity 69%, and both NPV and PPV 75%. Sensitivity and NPV on the validation set were significantly higher (p = 0.047) for the automatic versus manual segmentation. CONCLUSION: Our study showed that radiomics models can pave the way to help clinicians in the prediction of tumour response to chemoradiotherapy of LARC and to personalise per-patient treatment. The results from the external validation dataset are promising for further research into radiomics approaches using both manual and automatic segmentations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41747-022-00272-2

Learning models for classifying Raman spectra of genomic DNA from tumor subtypes

An early and accurate detection of different subtypes of tumors is crucial for an effective guidance to personalized therapy and in predicting the ability of tumor to metastasize. Here we exploit the Surface Enhanced Raman Scattering (SERS) platform, based on disordered silver coated silicon nanowires (Ag/SiNWs), to efficiently discriminate genomic DNA of different subtypes of melanoma and colon tumors. The diagnostic information is obtained by performing label free Raman maps of the dried drops of DNA solutions onto the Ag/NWs mat and leveraging the classification ability of learning models to reveal the specific and distinct physico-chemical interaction of tumor DNA molecules with the Ag/NW, here supposed to be partly caused by a different DNA methylation degree

First characterization of the CD4 and CD8 T-cell responses to QuantiFERON-TB Plus

Summary Introduction QuantiFERON ® -TB Gold Plus (QFT-Plus) is the new generation of QuantiFERON-TB Gold In-Tube test to identify latent tuberculosis infection (LTBI). QFT-Plus includes TB1 and TB2 tubes which contain selected Mycobacterium tuberculosis (Mtb) peptides designed to stimulate both CD4 and CD8 T-cells. Aim of this study is the flow cytometric characterization of the specific CD4 and CD8 T-cell responses to Mtb antigens contained within QFT-Plus. Methods We enrolled 27 active tuberculosis (TB) patients and 30 LTBI individuals. Following stimulation with TB1 and TB2, antigen-specific T-cells were characterized by flow cytometry. Data were also correlated with the grade of TB severity. Results TB1 mainly elicited a CD4 T-cell response while TB2 induced both CD4 and CD8 responses. Moreover, the TB2-specific CD4 response was detected for both active TB and LTBI patients, whereas the TB2-specific CD8 response was primarily associated with active TB (p = 0.01). Conclusions To our knowledge, we report the first characterization of the CD4 and CD8 T-cell response to QFT-Plus. CD8 T-cell response is mainly due to TB2 stimulation which is largely associated to active TB. These results provide a better knowledge on the use of this assay

CD4+ T Cell Defects in a Mulibrey Patient With Specific TRIM37 Mutations

Mulibrey (muscle-liver-brain-eye) syndrome (MUL) is an autosomal recessive disorder caused by mutations in the TRIpartite motif (TRIM)37 gene, encoding for TRIM37 a member of the TRIM E3 ubiquitin ligase protein family. MUL patients are characterized by growth retardation, dysmorphic features, and a wide range of abnormalities affecting different organs. However, T-cell abnormalities have not been observed in MUL subjects, to date. Here we described the immunological features of a MUL child carrying recently identified TRIM37 mutations, a 17q22 deletion of maternal origin combined with a TRIM37 variant of paternal origin. Here we found quantitative and functional defects in CD4+ T cells fromthisMUL case. Low levels of TRIM37 protein were specifically detected in CD4+ T cells ofMUL patient and associated with their altered proliferation and cytokine production. Of note, both CD4+ and CD8+ T lymphocytes of MUL child displayed an effector memory phenotype compared with healthy children. This clinical case research highlighted the possible role of TRIM37 in the control of immune cell number and function, especially in CD4+ T cells. Finally, this study may contribute to the novel mechanistic studies aim of identifying, in depth, the role of the TRIM37 protein in the immune system

Learning models for classifying Raman spectra of genomic DNA from tumor subtypes

An early detection of different tumor subtypes is crucial for an effective guidance to personalized therapy. While much efforts focus on decoding the sequence of DNA basis to detect the genetic mutations related to cancer, it is becoming clear that physical properties, including structural conformation, stiffness, and shape, as well as biological processes, such as methylation, can be pivotal to recognize DNA modifications. Here we exploit the Surface Enhanced Raman Scattering (SERS) platform, based on disordered silver coated--silicon nanowires, to investigate genomic DNA from subtypes of melanoma and colon cancers and to efficiently discriminate tumor and healthy cells, as well as the different tumor subtypes. The diagnostic information is obtained by performing label--free Raman maps of the dried drops of DNA solutions onto the Ag/NWs mat, and leveraging the classification ability of learning models to reveal the specific and distinct interaction of healthy and tumor DNA molecules with nanowires

Large cryptic genomic rearrangements with apparently normal karyotypes detected by array-CGH.

Background: Conventional karyotyping (550 bands resolution) is able to identify chromosomal aberrations >5-10 Mb, which represent a known cause of intellectual disability/developmental delay (ID/DD) and/or multiple congenital anomalies (MCA). Array-Comparative Genomic Hybridization (array-CGH) has increased the diagnostic yield of 15-20%. Results: In a cohort of 700 ID/DD cases with or without MCA, including 15 prenatal diagnoses, we identified a subgroup of seven patients with a normal karyotype and a large complex rearrangement detected by array-CGH (at least 6, and up to 18 Mb). FISH analysis could be performed on six cases and showed that rearrangements were translocation derivatives, indistinguishable from a normal karyotype as they involved a similar band pattern and size. Five were inherited from a parent with a balanced translocation, whereas two were apparently de novo. Genes spanning the rearrangements could be associated with some phenotypic features in three cases (case 3: DOCK8; case 4: GATA3, AKR1C4; case 6: AS/PWS deletion, CHRNA7), and in two, likely disease genes were present (case 5: NR2F2, TP63, IGF1R; case 7: CDON). Three of our cases were prenatal diagnoses with an apparently normal karyotype. Conclusions: Large complex rearrangements of up to 18 Mb, involving chromosomal regions with similar size and band appearance may be overlooked by conventional karyotyping. Array-CGH allows a precise chromosomal diagnosis and recurrence risk definition, further confirming this analysis as a first tier approach to clarify molecular bases of ID/DD and/or MCA. In prenatal tests, array-CGH is confirmed as an important tool to avoid false negative results due to karyotype intrinsic limit of detection