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Malignant astrocytomas are the most aggressive primary brain tumors with a poor prognosis despite optimal treatment. Dysfunction of mismatch repair (MMR) system accelerates the accumulation of mutations throughout the genome causing uncontrolled cell growth. The aim of this study was to characterize the MMR system defects that could be involved in malignant astrocytoma pathogenesis. We analyzed protein expression and promoter methylation of MLH1, MSH2 and MSH6 as well as microsatellite instability (MSI) and MMR gene mutations in a set of 96 low- and high-grade astrocytomas. Forty-one astrocytomas failed to express at least one MMR protein. Loss of MSH2 expression was more frequent in low-grade astrocytomas. Loss of MLH1 expression was associated with MLH1 promoter hypermethylation and MLH1-93G>A promoter polymorphism. However, MSI was not related with MMR protein expression and only 5% of tumors were MSI-High. Furthermore, the incidence of tumors carrying germline mutations in MMR genes was low and only one glioblastoma was associated with Lynch syndrome. Interestingly, survival analysis identified that tumors lacking MSH6 expression presented longer overall survival in high-grade astrocytoma patients treated only with radiotherapy while MSH6 expression did not modify the prognosis of those patients treated with both radiotherapy and chemotherapy. Our findings suggest that MMR system alterations are a frequent event in malignant astrocytomas and might help to define a subgroup of patients with different outcome.

Background Patients with schizophrenia die decades earlier than the general population. Among the factors involved in this mortality gap, evidence suggests a telomere length shortening in this clinical population, which is associated with premature ageing. Recent studies support the use of strength-based training exercise programmes to maintain, or even elongate, telomere length in healthy elderly populations. However, studies aiming at modifying telomere length in severe mental illnesses, such as schizophrenia, are still very scarce. Aims To investigate the effect of a strength-based physical exercise programme on the telomere length of individuals with schizophrenia. Method We propose a pragmatic, randomised controlled trial including 40 patients aged ≥18 years, with a stable diagnosis of schizophrenia, attending the Complejo de Rehabilitación Psicosocial (CRPS, Psychosocial Rehabilitation Centre) in Salamanca, Spain. These patients will be randomly assigned (1:1) to either receive the usual treatment and rehabilitation programmes offered by CRPS (treatment-as-usual group) or these plus twice weekly sessions of an evidence-based, strength-based training exercise programme for 12 weeks (intervention group). The primary outcome will be effect on telomere length. Secondary outcomes will include impact on cognitive function, frailty and quality of life. Results We expect to show the importance of implementing strength-based physical exercise programmes for patients with schizophrenia. We could find that such programmes induce biological and genetic changes that may lengthen life expectancy and decrease physical fragility. Conclusions We anticipate that our trial findings could contribute to parity of esteem for mental health, reducing premature ageing in patients with severe mental illnesses, such as schizophrenia.

Introduction: Chronic non-communicable diseases, including diseases of mental origin such as Alzheimer’s, affect all age groups and countries. These diseases have a major impact on the patient and their family environment. It is interesting that different questionnaires are measured in the same direction, given that different health questionnaires are used to measure caregiver burden. Objectives: To identify which type of intervention is the most appropriate to improve the health of the primary caregiver in patients with dementia. To understand the role played by the nurse within multidisciplinary teams and to know whether the different questionnaires used in the studies measure caregiver health in the same direction. Methods: A systematic search of the published and gray literature was carried out without restriction of the language used in the studies. Caregiver burden of patients with dementia, receiving an intervention to improve caregiver burden, was assessed. Standardized mean difference was used as the effect size measure, and there were possible causes of heterogeneity in the effect size. Results: In total, 1512 records were found, and 39 articles with 4715 participants were included. We found individual information with an effect of 0.48 (CI95%: 0.18; 0.79; I2 = 0%); group therapy with an effect of 0.20 (CI95%: 0.08; 0.31; I2 = 6%); workshops with an effect of 0.21 (CI95%: 0.01; I2 = 48%) and 0.32 (CI95%: 0.01; 0.54; I2 = 0%) when a nurse intervenes; respite care with an effect of 0.22 (CI95%: 0.05; 0.40; I2 = 66%); individual therapy with an effect of 0.28 (CI95%: 0.15; 0.4; I2 = 68%); and support groups with an effect of 0.07 (CI95%: 0; 0.15; I2 = 78%). Conclusions: The magnitude of the effects of the interventions has been low–moderate. Different instruments are not associated with the magnitude of the effect. The presence of nurses improves the effect of the intervention on caregivers when it is carried out in the form of workshops.

Abstract The assessment of psoriatic arthritis is complex and multidimensional. It is increasingly common to include the patient perspective using patient-reported outcomes. Although some research has explored sleep quality in patients with psoriatic arthritis, most studies have had small sample sizes, failed to assess sleep quality considering the inflammatory process together with the psychological well-being of patients, and have not described any use of sleep medication. Further, research to date has not provided data on the relationship of sleep quality with axial forms. In this context, the objective of this study was to assess sleep quality in patients with psoriatic arthritis and its relationship with clinical characteristics, disease activity, functioning, disease impact, fatigue and psychological status. A cross-sectional study was conducted including 247 consecutive patients with PsA recruited during 2021. Sleep quality was measured using the Pittsburgh Sleep Quality Index. We assessed correlations of Pittsburgh Sleep Quality Index score with peripheral disease activity (Disease Activity Index for PSoriatic Arthritis), axial disease activity (Ankylosing Spondylitis Disease Activity Score-C-reactive protein and Bath Ankylosing Spondylitis Disease Activity Index), functioning (Bath Ankylosing Spondylitis Functional Index and Health Assessment Questionnaire), impact (Psoriatic Arthritis Impact of Disease questionnaire), anxiety, depression (Hospital Anxiety and Depression Scale) and fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue) scores. A multiple linear regression model was constructed with PSQI as the dependent variable and as independent variables those that could influence sleep quality. Nearly two-thirds (63.15%) of patients had poor sleep quality. Poorer sleep quality was associated with being female, higher joint counts, greater peripheral and axial disease activity, fatigue, anxiety and depression, functioning and disease impact (p

BackgroundPhysical exercise is one of the main nonpharmacological treatments for most pathologies. In addition, physical exercise is beneficial in the prevention of various diseases. The impact of physical exercise has been widely studied; however, existing meta-analyses have included diverse and heterogeneous samples. Therefore, to our knowledge, this is the first meta-analysis to evaluate the impact of different physical exercise modalities on telomere length in healthy populations. ObjectiveIn this review, we aimed to determine the effect of physical exercise on telomere length in a healthy population through a meta-analysis of randomized controlled trials. MethodsA systematic review with meta-analysis and meta-regression of the published literature on the impact of physical exercise on telomere length in a healthy population was performed. PubMed, Cochrane Library, SCOPUS, Web of Science, and Embase databases were searched for eligible studies. Methodological quality was evaluated using the Risk Of Bias In Nonrandomized Studies of Interventions and the risk-of-bias tool for randomized trials. Finally, the certainty of our findings (closeness of the estimated effect to the true effect) was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). ResultsWe included 9 trials that met the inclusion criteria with fair methodological quality. Random-effects model analysis was used to quantify the difference in telomere length between the exercise and sham groups. Meta-analysis showed that exercise did not significantly increase telomere length compared with the control intervention (mean difference=0.0058, 95% CI −0.05 to 0.06; P=.83). Subgroup analysis suggested that high-intensity interventional exercise significantly increased telomere length compared with the control intervention in healthy individuals (mean difference=0.15, 95% CI 0.03-0.26; P=.01). Furthermore, 56% of the studies had a high risk of bias. Certainty was graded from low to very low for most of the outcomes. ConclusionsThe findings of this systematic review and meta-analysis suggest that high-intensity interval training seems to have a positive effect on telomere length compared with other types of exercise such as resistance training or aerobic exercise in a healthy population. Trial RegistrationPROSPERO CRD42022364518; http://tinyurl.com/4fwb85ff

Abstract Background The spread of cervical squamous cell carcinoma to the inner surface of the uterus with replacement of the endometrium is rare. Continuity of the lesion must be demonstrated to confirm superficial spread and rule out concomitant endometrial cancer. Case presentation We present the case of a 66-year-old white woman with superficial spreading squamous cell carcinoma of the cervix that involved the endometrium. Her relevant past history included conization of the cervix to treat cervical intraepithelial neoplasia III with positive margins. She subsequently had three negative cervical vaginal cytology results, each with a positive high-risk human papillomavirus test. Transvaginal ultrasound showed occupation of the entire uterine cavity by dense material consistent with pyometra in addition to myometrial thinning due to tension and cervical dilation. The patient presented with greenish vaginal discharge of 3 months’ duration. The cervix was not visible during speculum examination. Access for endometrial sampling was not possible, raising suspicion of post-conization cervical stenosis. The patient was treated with laparoscopic hysterectomy with double adnexectomy. Histologic examination showed superficial squamous cell carcinoma invading the cervix to a depth of 2.8 mm; superficial spreading squamous cell carcinoma in situ was also observed in the lower uterine segment and endometrium. The patient was free of symptoms 12 months after surgery. Conclusions Squamous cell carcinoma of the cervix with superficial spread to the endometrium is not included in the 2020 (fifth edition) World Health Organization Classification of Female Genital Tract Tumors or the 2018 International Federation of Gynecology and Obstetrics cervical cancer staging system. More clinical cases are needed to identify other prognostic factors and inform clinical practice guidelines on the management of this disease.

Abstract Background Isolated fallopian tube torsion associated with hydrosalpinx is a rare condition in the pediatric population. We present this unusual clinical case study in a sexually inactive girl. Case presentation a12-year-old Caucasian girl presented symptoms of acute abdominal pain. Pelvic ultrasound revealed a normal looking uterus and ovaries and next to left ovary a imaging compatible with hydrosalpinx. She was discharged 48 hours later after clinical monitoring with oral analgesia and normal blood workup. At 3 weeks, she was readmitted for acute abdominal pain. Leukocytosis with left shift and raised C-reactive protein were observed. Her clinical condition worsened, and complication of the preexisting hydrosalpinx was suspected. Exploratory laparoscopy confirmed torsion of the fallopian tube. Left salpingectomy was performed. Histopathologic study confirmed a fallopian tube with hemorrhagic infarct. Conclusion Torsion of the fallopian tube must be considered in the event of acute abdominal pain. Early diagnosis and trying conservative management with a view to preserving fertility in this group of patients are essential.

Introduction: Health-related quality of life (HRQL), pain and sleep have been described as relevant traits in patients with human immunodeficiency virus (HIV). The aim of this study is to describe and evaluate HRQL, pain and sleep and their interdependence in HIV-positive patients. Methods: A cross-sectional study on HIV-infected patients was conducted. A set of five different questionnaires was used: two questionnaires addressing HRQL (Short Form 36 [SF-36] Health Survey and Medical Outcomes Study Short Form 30 [MOS-SF 30]), one on pain (McGill Pain Questionnaire) and one on sleep (Pittsburgh Sleep Quality Index [PSQI]). We also collected the sociodemographic and clinical characteristics of patients. Results: The sample included 109 patients (age: 46.08 ± 10.49 years; 68.8% male). The pain experience was independent of HRQL and sleep. Relationships among HRQL, pain and sleep associated to sociodemographic and clinical factors were not detected (p > 0.05). Patients with CDC category A showed moderate to high correlations among HRQL, pain and sleep. In CDC B-type patients, a moderate correlation was observed between pain and mental health. In CDC C patients, moderate correlations were observed between HRQL and sleep and pain and sleep, with no correlations between HRQL and pain. Conclusions: HRQL, pain and sleep are differently correlated in HIV patients depending on their clinical stage. Neither the nadir of CD4-T cells nor the current count of CD4-T cells was found to be related with HRQL, pain or sleep.

Purpose: To report a case of intestinal-type adenocarcinoma of the Bartholin gland treated successfully with surgery and to review the current literature. Methods: We report the case of a 45-year-old white woman with intestinal-type adenocarcinoma of the Bartholin gland treated with wide local excision followed by bilateral inguinal femoral lymph node dissection without adjuvant therapy. We also review the literature on the treatment and management of this rare tumor. We searched Pubmed / MEDLINE databases for previous case reports or series using the keywords “Bartholin gland”, “adenocarcinoma” and “intestinal type”. Results: We found 19 cases of intestinal-type adenocarcinoma of the Bartholin gland published up to November 2020. The treatments described varied from case to case. Conclusion: Intestinal-type adenocarcinoma of the Bartholin gland has been treated and managed in the same way as squamous carcinoma. Treatment of these cancers is understudied and involves local resection with curative intent. More case reports are needed to determine the best treatment strategies.

Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between traits with mixed phenotypes in order to improve prediction accuracy in the context of genomic selection (GS). For this reason, when breeders have mixed phenotypes, they usually analyze them using univariate models, and thus are not able to exploit the correlation between traits, which many times helps improve prediction accuracy. In this paper we propose applying deep learning for analyzing multiple traits with mixed phenotype data in terms of prediction accuracy. The prediction performance of multiple-trait deep learning with mixed phenotypes (MTDLMP) models was compared to the performance of univariate deep learning (UDL) models. Both models were evaluated using predictors with and without the genotype × environment (G×E) interaction term (I and WI, respectively). The metric used for evaluating prediction accuracy was Pearson’s correlation for continuous traits and the percentage of cases correctly classified (PCCC) for binary and ordinal traits. We found that a modest gain in prediction accuracy was obtained only in the continuous trait under the MTDLMP model compared to the UDL model, whereas for the other traits (1 binary and 2 ordinal) we did not find any difference between the two models. In both models we observed that the prediction performance was better for WI than for I. The MTDLMP model is a good alternative for performing simultaneous predictions of mixed phenotypes (binary, ordinal and continuous) in the context of GS.

Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this paper we explore the genomic based prediction performance of two popular machine learning methods: the Multi Layer Perceptron (MLP) and support vector machine (SVM) methods vs. the Bayesian threshold genomic best linear unbiased prediction (TGBLUP) model. We used the percentage of cases correctly classified (PCCC) as a metric to measure the prediction performance, and seven real data sets to evaluate the prediction accuracy, and found that the best predictions (in four out of the seven data sets) in terms of PCCC occurred under the TGLBUP model, while the worst occurred under the SVM method. Also, in general we found no statistical differences between using 1, 2 and 3 layers under the MLP models, which means that many times the conventional neuronal network model with only one layer is enough. However, although even that the TGBLUP model was better, we found that the predictions of MLP and SVM were very competitive with the advantage that the SVM was the most efficient in terms of the computational time required.

Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models that can exploit the correlation between traits to improve prediction accuracy in the context of genomic selection (GS). Multi-trait models are more complex than univariate models and usually require more computational resources, but they are preferred because they can exploit the correlation between traits, which many times helps improve prediction accuracy. For this reason, in this paper we explore the power of multi-trait deep learning (MTDL) models in terms of prediction accuracy. The prediction performance of MTDL models was compared to the performance of the Bayesian multi-trait and multi-environment (BMTME) model proposed by Montesinos-López et al. (2016), which is a multi-trait version of the genomic best linear unbiased prediction (GBLUP) univariate model. Both models were evaluated with predictors with and without the genotype×environment interaction term. The prediction performance of both models was evaluated in terms of Pearson’s correlation using cross-validation. We found that the best predictions in two of the three data sets were found under the BMTME model, but in general the predictions of both models, BTMTE and MTDL, were similar. Among models without the genotype×environment interaction, the MTDL model was the best, while among models with genotype×environment interaction, the BMTME model was superior. These results indicate that the MTDL model is very competitive for performing predictions in the context of GS, with the important practical advantage that it requires less computational resources than the BMTME model.

Background: Determining predictive biomarkers for immune checkpoint inhibitors (ICIs) is a current challenge in oncology. Previous studies on non-small cell lung cancer (NSCLC) have shown how TP53 gene mutations are correlated with different responses to ICIs. Strong and diffuse immuno-expression of p53 by immunohistochemistry (IHC) is interpreted as a likely indicator of a TP53 gene mutation. We aimed to assess the p53 protein expression via IHC in NSCLC as a predictive biomarker of the response to ICIs. Methods: This was a retrospective hospital-based study of patients with NSCLC treated with Nivolumab in the University Hospital of Salamanca. All diagnostic biopsies were studied via IHC (measuring p53 protein expression, peroxidase anti-peroxidase immunohistochemistry technique using Leica BOND Polymer development kits). Survival analysis was performed by subgroups of expression of p53 and other factors using the Kaplan-Meier estimator and Cox proportional-hazards model. Results: Seventy-three patients were included (59 men and 14 women). The median age was 68 (44–84) years. Thirty-six biopsies were adenocarcinoma, 34 were squamous, and three were undifferentiated. In 41 biopsies (56.2%), the cellular expression of p53 was

Background: Osteoporosis and obesity are major public health problems that are closely correlated, as they share various features, including a genetic predisposition. A genetic correlation between obesity and osteoporosis due to the biological common pathways of bone and fat metabolism, which implies pleiotropic genes regulating has been described. The objective of our study was to analyse whether polymorphisms in obesity-related genes modify the risk of osteoporotic bone fracture. Methods: We studied 575 subjects from the Hortega Study. The subjects were followed-up for 12–14 years. 202 subjects were overweight, 143 obese and 221 had bone fractures. The distribution of 39 genetic variants in 22 obesity-related genes were studied. Results: The results showed a relationship between polymorphisms in the FTO and NEGR1 genes and the susceptibility to osteoporotic fracture. The variant genotype of the rs2568958 NEGR1 polymorphism and the rs6499649, rs3751812, and rs8044769 genetic variants in FTO were associated with susceptibility to bone fracture. In the best of our knowledge, this is the first time that these variants in NEGR1 and FTO genes have been associated with the susceptibility to osteoporotic bone fracture, supporting the hypothesis that the NEGR1 and FTO genes might be candidates for osteoporosis and bone fracture. Conclusions: In conclusion, this study associates obesity-related polymorphisms in the NEGR1 and FTO genes with osteoporotic bone fracture, reinforcing the hypothesis that obesity and bone metabolism are closely correlated genetically.

Background: Physical exercise is an effective measure for preventing the onset of cognitive decline and has a direct influence on the aging process. The purpose of this study was to assess the effect of a 6-month physical exercise program on cognition and telomere length in adults over 65 years of age. Method: Seventy-four healthy women were separated into two groups: 41 were included in the intervention group (IG) (72.70 ± 4.127 years and 8.18 ± 1.551 years of education) and 33 in the control group (CG) (71.21 ± 4.127 years and 8.42 ± 2.562). The participants included within the IG carried out three sessions of physical exercise per week for six months. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), the Stroop test and the Trail Making Test (TMT). Saliva samples were taken and analyzed and relative telomere length was calculated. Those conducting the analysis were blind to the group to which the participants had been assigned. Results: An improvement was observed in global cognitive function, in both attentional and executive functions, in the group of adults doing physical exercise as compared to the control group. Six months after the physical exercise program had finished, relative telomere length was found to have increased in the participants in the intervention group. Conclusion: Physical exercise programs can lead to an improvement in both cognitive functions and telomere length.

The study of the heterogeneity of effect sizes is a key aspect of ecological meta-analyses. Here we propose a meta-analytic methodology to study the influence of moderators in effect sizes by splitting heterogeneity: meta-partition. To introduce this methodology, we performed a meta-partition of published data about the traits that influence species sensitivity to habitat loss, that have been previously analyzed through meta-regression. Thus, here we aim to introduce meta-partition and to make an initial comparison with meta-regression. Meta-partition algorithm consists of three steps. Step 1 is to study the heterogeneity of effect sizes under the assumption of fixed effect model. If heterogeneity is found, we perform step 2, that is, to partition the heterogeneity by the moderator that minimizes heterogeneity within a subset while maximizing heterogeneity between subsets. Then, if effect sizes of the subset are still heterogeneous, we repeat step 1 and 2 until we reach final subsets. Finally, step 3 is to integrate effect sizes of final subsets, with fixed effect model if there is homogeneity, and with random effects model if there is heterogeneity. Results show that meta-partition is valuable to assess the importance of moderators in explaining heterogeneity of effect sizes, as well as to assess the directions of these relations and to detect possible interactions between moderators. With meta-partition we have been able to evaluate the importance of moderators in a more objective way than with meta-regression, and to visualize the complex relations that may exist between them. As ecological issues are often influenced by several factors interacting in complex ways, ranking the importance of possible moderators and detecting possible interactions would make meta-partition a useful exploration tool for ecological meta-analyses.