Trichophyton verrucosum is a zoophilic dermatophyte that causes skin inflammation. The present study aimed to evaluate the redox status in the blood of sheep clinically infected with T. verrucosum. According to clinical and mycological investigations, 48 juvenile male Balady sheep were selected in their natural habitat and divided into four groups depending on the lesion size: mild (MID), moderate (MOD), severe (SEV) T. verrucosum infection, and healthy control groups. Compared to the controls, plasma superoxide anion increased (P < 0.05) in both MOD and SEV but total peroxides (TPx) gradually increased (P < 0.05) in MID followed by MOD and SEV. Superoxide dismutase and total antioxidant capacity (TAC) were higher (P < 0.05) in MID and lower (P < 0.05) in MOD and SEV than in controls, but SEV showed lower TAC than MOD. Malondialdehyde  increased (P < 0.05) in SEV than in controls, but protein carbonyl  was augmented (P < 0.05) as lesions progressed from mild to severe. The oxidative stress index (TPx/TAC ratio) progressively increased (P < 0.05) in MOD and SEV. The correlation of PC was positive with TPx and negative with TAC (P < 0.01). In conclusion, sheep infection with T. verrucosum is characterized by increased TPx and decreased TAC in plasma depending on the lesion area. The redox status is shifted towards the oxidizing state, particularly in MOD and SEV cases. This results in a condition of OS, which may contribute to the pathogenesis of the disease. T. verrucosum is a host-specific dermatophyte essentially adapted to cattle and less frequent in small ruminants , are enhanced to act as a host defense against the invading pathogen  was offered indoors without extra supplementation. Infected sheep had a history of dermatological lesions for 1.5–3 months before the examination. Both the infected and control sheep had no history of recent topical or systemic medications for at least 1 month. The body condition score was visually evaluated in all sheep according to Kenyon et al. . These animals were selected from sheep reared in the eastern part of Assiut governorate, Egypt. Clinical and mycological investigations proved that 36 sheep were infected by n et al. . The scon = 14, mild infection, MID). The second had larger lesions that covered about a quarter to a third of the head and ear . Animals with lesions that covered the majority of the head and ears were considered to have a severe infection . The remainder (n = 12) were healthy sheep and were used as a control group.The selected sheep were divided clinically into four groups according to the lesion size. Only one of the authors evaluated these lesions. The first group showed 1–2 lesions, each with an approximate diameter of 2–4 cm , clear non-hemolyzed plasma was separated and stored at − 80 °C until analysis within a week.Skin lesions were cleaned with 70% ethyl alcohol. The margins were scraped in a sterile Petri dish to collect hair and skin tissues. In healthy sheep, areas around the muzzle and eyes, in addition to the ears, were also sampled. The scraping material was divided into two portions. The first was digested with 10% KOH for 15 min and examined for the presence of spores and hyphae under a microscope. The rest of the specimen was inoculated into Sabouraud’s dextrose agar supplemented with chloramphenicol and cycloheximide . The medium was enriched with inositol and thiamin and incubated at 28 °C and 37 °C for 2–6 weeks. Incubation was checked 2–3 times a week. A lactophenol cotton blue preparation was made for morphological studies of the isolates (Rebell and Taplin 2¯ was measured according to the procedure of Podczasy and Wei (2¯ generated by xanthine/xanthine oxidase to a water-soluble product (reddish pink) and the optical density is read at 505 nm.As a major component of free radicals, O֗ and Wei , which i+2  to Fe+3 by the various types of peroxides in the presence of xylenol orange in an acidic medium, which binds with Fe+3 to form a colored complex whose optical density is read at 560 nm.Measurement of total peroxides or so-called reactive oxygen metabolites (ROM) is usually used as an indirect method to estimate the reactive oxygen species (ROS) concentration Erel . Plasma Total antioxidant capacity (TAC) was determined by using the colorimetric ABTS assay kit  according to the method described by Miller et al. . In thisThe activity of SOD was estimated according to the method described by Misra and Fridovich . In an aLipid peroxidation was determined as thiobarbituric acid reactive substances (TBARS) according to Placer et al. . The metProtein carbonyls were measured by using DNPH  according to the method of Levine et al. . In brieThe TAC unit, mmol Trolox equiv/L, was converted to µmol Trolox equivalent/L. The OSI value (as an indicator of the degree of oxidative stress) was determined as the percentage ratio of TPx to TAS as follows: OSI (Arbitrary unit) =  × 100  and Pearson’s correlation (r) were done on the paired data obtained by the individual cases.The packaged SPSS program for Windows version 10.0.1  was used for statistical analysis. The normal distribution of data for each parameter was checked using the Shapiro–Wilk test. The data were analyzed using a one-way analysis of variance (ANOVA) and expressed as mean ± standard error (SE). Differences between groups were determined using pair-wise multiple comparison procedures (when a significant F test was found) using Duncan’s new multiple range test. The significance level was set at P > 0.05), but the SEV (30.97 ± 0.57 kg) tended to be lower (P = 0.051) than the control group. There were no apparent differences in the body condition score between all groups. The average score values recorded in all animals ranged from 2.5 to 3.0 units.No systemic reactions were observed in the infected animals. Those with extensive lesions showed variable degrees of ill-thriftiness and a rough coat. Weight differences between the control (32.17 ± 0.44 kg), MID (32.08 ± 0.46 kg), and MOD (31.67 ± 0.48 kg) groups were not significant  in the MID group but they increased in both MOD (P = 0.03) and SEV (P < 0.001) in comparison to the control values. Compared with the MID group, O֗2¯ value was higher (P = 0.008) in the SEV group. The values of TPx differed significantly (P < 0.05) between the four groups. There was a gradual increase in TPx concentrations in MID (P = 0.03), followed by MOD (P = 0.001) and SEV (P < 0.001) in comparison to the control group  in MID and lower in MOD (P = 0.03) and SEV (P = 0.02) in comparison with the control group. There was a non-significant difference (P = 0.27) between MOD and SEV. The same was observed for the TAC concentrations, where the values were higher in MID (P = 0.01) and lower in MOD (P = 0.03) and SEV (P = 0.004) in comparison with the control group. The SEV showed lower concentrations (P = 0.03) than the MOD group  and MOD (P = 0.061) but increased (P = 0.003) in the SEV group. MDA values in MID and MOD did not differ (P = 0.097). The same was observed between SEV and MOD (P = 0.103), but SEV was higher (P = 0.01) than MID. On the other hand, there was a significant difference in PC concentrations between the four groups. PC augmented as lesions progressed from mild to severe. Its concentrations demonstrated a steady increase in MID (P = 0.014) followed by MOD (P < 0.001) and SEV (P < 0.001) compared to the controls , but it progressively increased in MOD (P < 0.001) and SEV (P < 0.001), where the SEV group showed the highest value  and Pearson’s correlation (r) of the paired data obtained by the individual cases  whereas it was positively correlated with PC . The same was observed for TAC, where it was not correlated with MDA (P = 0.107), but the correlation with PC was negative .Linear regression analysis (es Figs.  and 8 reT. verrucosum infection.The findings in this study provide reliable biochemical evidence for a circulatory redox imbalance in sheep infected with T. verrucosum. The redox status shifted towards an oxidizing state depending on the lesion size. This could be detected by the augmented TPx biomarkers and the accumulation of lipid and protein oxidative by-products coupled with inhibited TAC in MOD and SEV lesions. The present study is, to our knowledge, the first to describe the oxidative stress status in sheep with T. verrucosum is well adapted to cattle, outbreaks with severe inflammation have occurred in sheep (Scott Although ep Scott . Clinicaep Scott . Previouep Scott , which mT. verrucosum augment the activity of the non-professional coetaneous immune cells, epidermal keratinocytes, and dermal fibroblasts, and trigger the circulating neutrophils and monocytes (Lord and Vyas 2¯ and TPx was enhanced progressively in mild, moderate, and severe infections, suggesting a link between the intensity of ROS generation and the increase in the circumference of infection by T. verrucosum on the skin of sheep. Our results agree with those reported for chronic dermatitis in humans (Grange et al. Despite the superficial localization of dermatophytosis, the systemic host-fungus interaction is still complicated and poorly understood. Infections with trichophyton species are limited to the hair and keratinized tissue of the epidermis, which makes them unique because they fail to penetrate the underlying tissues (Roberson et al. T. verrucosum infection. Over time, the accumulation of ROS eventually exceeds the defense capacity of the antioxidant system (Bertino et al. Despite the pathway variations of the different antioxidants, TAC represents the cumulative action of all of them (Halliwell and Gutteridge T. verrucosum infection. This provides further evidence of enhancement of the pro-oxidants and the generation of toxic molecules, which might be key in understanding the mechanisms of T. verrucosum infection in sheep.The generation of ROS is considered a formidable weapon against invading pathogens and powerful fungicidal tools, but they are unspecific effectors and could severely damage the surrounding biological medium (Colitti et al. In the present study, plasma MDA increased in moderate and severe cases, but PC progressively increased in mild, moderate, and severe infections. In addition, PC was positively correlated with TPx and negatively correlated with TAC, but MDA did not show significant correlations with TPx or TAC. These results suggest that protein oxidative damage is continuously occurring and progressively amplified as the lesion area increases. Furthermore, the obtained results suggest that the increased PC concentrations are linked to the increased prooxidant power and the decreased antioxidant potential. Previous reports showed that mild conditions of oxidative stress are characterized by higher oxidized protein concentrations (Valacchi et al. Oxidative stress can result from increased TPx, decreased TAC, or even both, so the main players in redox homeostasis are TPx and TAC (Valacchi et al. T. verrucosum is characterized by increased TPx and decreased TAC in plasma depending on the lesion area. The redox status is shifted towards the oxidizing state, especially in MOD and SEV cases. This results in a condition of OS, which may contribute to the pathogenesis of the disease.Sheep infection with


Amid the COVID‐19 crisis, we put sizeable efforts to collect a high number of experimentally validated drug–virus association entries from literature by text mining and built a human drug–virus association database. To the best of our knowledge, it is the largest publicly available drug–virus database so far. Next, we develop a novel weight regularization matrix factorization approach, termed WRMF, for in silico drug repurposing by integrating three networks: the known drug–virus association network, the drug–drug chemical structure similarity network, and the virus–virus genomic sequencing similarity network. Specifically, WRMF adds a weight to each training sample for reducing the influence of negative samples (i.e. the drug–virus association is unassociated). A comparison on the curated drug–virus database shows that WRMF performs better than a few state‐of‐the‐art methods. In addition, we selected the other two different public datasets (i.e. Cdataset and HMDD V2.0) to assess WRMF's performance. The case study also demonstrated the accuracy and reliability of WRMF to infer potential drugs for the novel virus. In summary, we offer a useful tool including a novel drug–virus association database and a powerful method WRMF to repurpose potential drugs for new viruses. It transmits through the respiratory tract of mammals, and causes mild‐to‐severe respiratory infections. In the past two decades, two highly pathogenic coronaviruses, including Severe Acute Respiratory Syndrome coronavirus (SARS‐CoV) and Middle East Respiratory Syndrome coronavirus (MERS‐CoV) have caused global epidemics of excessive morbidity and mortality in human community.The development of a new drug for a disease (e.g. COVID‐19) is a long and expensive process. Therefore, drug repositioning is an effective drug discovery strategy, which can greatly reduce the time and cost compared with de novo drug discovery.The computational drug repositioning method provides new testable hypotheses for repositioning old drugs, which can predict potential drug–target interactions to direct the experimental verification and improve the drug discovery efficiency. In recent years, many computational association prediction methods have been developed. For example, Iorio et al. proposed a transcriptional‐network based approach, which applied the network theory and utilized similarity in gene expression profiles following drug treatment for drug repositioning.The above‐mentioned computational prediction approaches are mainly classified as network‐based approaches and machine learning‐based approaches. As the most typical machine learning‐based method, matrix factorization represents drugs and diseases in a shared latent space and reconstructs the drug–disease association using their latent vectors. Recently, a few variants of matrix factorization have also been widely and successfully used in bioinformatics researches,In this study, we developed a new weight regularization matrix factorization method (WRMF) for drug repositioning against COVID‐19 based on similarity constraints, which mainly includes the following four steps: (i) collect experimentally verified drug–virus associations from the literature, (ii) calculate the chemical structure similarity of drugs and the genome sequence similarity of viruses, (iii) build heterogeneous networks based on known drug–virus associations, drug–drug similarity and virus–virus similarity, and (iv) use the similarity constrained weight regularization matrix factorization method to predict drugs most likely to be effective on the virus. Via comprehensive evaluation on 5‐fold cross‐validation (CV), local leave‐one‐out‐cross‐validation (LOOCV), and two additional independent datasets, we found that WRMF achieved higher performance in comparison with several state‐of‐the‐art methods. To fully prove the reliability of WRMF, we further conducted a case study about MERS. The experimental results showed that six of the top ten WRMF‐predicted anti‐MERS drugs had been confirmed. We expect that WRMF‐predicted anti‐COVID‐19 drug candidates might have a therapeutic effect. In summary, WRMF provides a powerful model to predict new drug–virus associations for accelerating drug repurposing.2We give the main idea of WRMF in Figure 2.1Since the databases of drug–virus associations are urgently demanded in biomedical researches amid the COVID‐19 crisis, Mongia et al. curated a comprehensive Drug Virus Association database, called DVA, which includes 38 viral species and 119 drugs.di is observed to have a therapeutic effect on the virus vj, the entity Yi,jis equal to 1; otherwise, it is 0. The two variables nd and nv represent the number of drugs and viruses, respectively. In this study, we integrate the drug–virus association network, drug–drug similarity network, virus–virus similarity network into a heterogeneous network. For the drug–drug similarity network, we measure the similarity of drug pairs by calculating the chemical structure similarity. For the virus–virus similarity network, we evaluate the similarity of virus pairs by calculating the gene sequences similarity. Therefore, the adjacency matrix of the drug–virus heterogeneous network can be defined as:We define the adjacency matrix of the drug–virus association network as the variable Y, that is, if the drug Y represents the collected drug–virus association network, YT is the transposition of Y, Sd, and Sv, respectively, represent the adjacency matrix of drug–drug similarity network and virus–virus similarity network.The sub‐matrix 2.2There are many algorithms for calculating drug similarity, among which classic algorithms usually include molecular similarity.T is widely used in various drug development and relocation processes, and its value ranges from zero (no common bits) to one .2.3With the development of gene sequencing technology, our understanding of any virus often starts with its sequence. MAFFT is a multiple sequence alignment program for Unix‐like operating systems.2.4The drug repositioning against Human Coronavirus Like COVID‐19 problem can be modelled as a recommendation system that recommends novel indications by filling out the unknown entries in the drug–virus association matrix, which is known as matrix completion. Matrix completion algorithms have been widely and successfully used in bioinformatics research, such as uncovering lncRNA–disease associations,·F represents the Frobenius norm, λw and λh are regularization parameters.Generally, when the matrix is of low rank, the matrix factorization minimization problem can be expressed as:R to each training sample for reducing the influence of unknown samples. R represents the confidence of the drug's preference for the disease. In addition, the traditional matrix factorization does not take into account the similarity between viruses and the similarity between drugs. To solve the aforementioned problems, we propose a weight regularized matrix factorization model (WRMF), formalized as follows:In the drug–virus association database, there are many unobserved entries, and we do not know negative samples (i.e. the drug–virus pair is unassociated). We define a problem with only positive feedback as a type of one‐class problem because there are only positive samples.α controls the contribution of positive samples to model training.λw,λh, λ1,and λ2 are the regularization parameters.Among them, the hyperparameter Since the WRMF model is a fitting of matrix Y, directly using SGD optimization will face the problems of overfitting and training efficiency.W and H until the local minimum of the objective function. Finally, the predicted drug–virus association matrix is Y*=WTH. The ith column of Y*indicates the association score between virus vi and drugs. The larger the score, the more relevant it is.According to formula  and form2.5vi, we remove all the known associations of the virus vi and build prediction model using the remaining data. We then calculate the relevance score of each node in the test dataset, and rank these nodes according to their scores. The higher the grade of the positive sample, the better the performance is. If the score of the marked node is higher than a given threshold θ, it is regarded as a positive sample for successful identified. If the score of the unlabeled node is lower than θ, it is regarded as a negative sample correctly identified. By changing h, the true positive rate (TPR) and false positive rate (FPR) can be calculated to obtain the receiver operating characteristic (ROC) curve.To evaluate the performance of the algorithm, we used the 5‐fold CV and local LOOCV. In the 5‐fold CV experiment, all known drug–virus associations are randomly divided into five equal and disjoint parts. Then, leave a part as a test set in turn, and the remaining four parts are used as a training set to train the model. The process is repeated for five times until all samples are predicted once. In the local LOOCV experiment, for each virus TP and TN are the numbers indicating that the positive and negative samples are judged correct, respectively. FP and FN indicate the number of positive and negative samples that were judged wrong.33.1IMC ,CMF ,MBiRW ,BNNR ,NIMCGCN , To evaluate the performance of our proposed WRMF, we compared WRMF with five state‐of‐the‐art association prediction methods listed below.α, which controls the contribution of positive samples to model training, ranges from 1 to 10 and is set as 5. Meanwhile, there are four main parameters needed to be determined, including λw, λh, λ1, and λ2. Based on the drug–virus association dataset we constructed, we performed cross‐validation on the training dataset to tune the parameters, which are increasing from 0.1 to 1 with a step of 0.1, and the ones with the best AUC were selected. WRMF achieves the best performance when λw=λh=0.3 and λ1=λ2=0.1  in the same way. In BNNR algorithm, there are two parameters (i.e. α and β) needed to be determined, and we obtained the optimal parameters  by determined from {0.1, 1, 10, 100}. In MBiRW algorithm, α is chosen from 0.1,0.2,…,1 and the optimal value of α is 0.5. The parameters landr are set as 2. For the NIMCGCN algorithm, we chose the optimal parameters α=0.4 from 0.1,0.2,…,0.9, l=3, and t=2.In our proposed WRMF algorithm, the hyperparameter 3.2We applied WRMF, BNNR, CMF, IMC, MBiRW, and NIMCGCN into our constructed drug–virus association dataset, containing 451 unique associations between 34 viruses and 218 drugs. We plotted the receiver operating characteristic (ROC) curves and calculated the area under the ROC curve in the 5‐fold CV  on two different public datasets, which are the drug–disease association dataset (Cdatase)Cdataset is generated by combining DNdatasetsThe effective identification of disease‐related miRNAs plays an important role in the discovery of drug targets and the development of new drugs. In our study, we also tested the prediction performance of WRMF on the most commonly used miRNA‐disease database (HMDD V2.0), which has 10,381 experimentally verified miRNA–disease associations. For HMDD V2.0, as shown in Figure 3.5ClinicalTrials.gov and the Comparative Toxicogenomics Database (CTD)Clinicaltrials.gov and CTD. Nitazoxanide (ranked the fourth), a broad‐spectrum anti‐infective drug, can inhibit COVID‐19 at low micromolar concentrations (EC50 = 2.12 M).ClinicalTrials.gov and CTD. It indicates that WRMF offers a useful tool to prioritize potential repurposed drugs for COVID‐19.COVID‐19 is a brand‐new (i.e. there is no interaction between COVID‐19 and any drug) and zoonotic disease. To further validate the prediction performance of WRMF, we conducted a case study to predict novel anti‐COVID‐19 drugs from a computational perspective. Specifically, we put the other known drug–virus associations to as the input of WRMF, then ranked the predicted scores of the potential anti‐COVID‐19 drugs. Following previous studies,http://autodock.scripps.edu) was used for offline docking. The X‐ray crystal structures of protein were retrieved from the RCSB protein database (www.rscb.org). A macromolecule with PDB ID: 6LZG, which is a novel coronavirus spike receptor binding domain complexed with its receptor ACE2. All proteins and ligands were prepared using MGL Tools 1.5.6 and Autodock Tool (ADT). ADT is used to calculate the binding free energy and inhibition constant of the optimal docking complex of the aforementioned proteins. The negative value of the combined free energy further indicates the stability of the complex  and N4‐Hydroxycytidine (ranked the seventh) were conducted blind docking both in online and offline modes. The Autodock 4.2 package  and in vitro or in in vivo mechanistic studies for the WRMF‐predicted anti‐COVID‐19 candidates are required in the future.In summary, our findings suggest that in silico drug repurposing could benefit from constraints on drug and viral similarity, matrix factorization, and drug–virus heterogeneous network. WRMF could help offer novel efficacious therapies for multiple complex diseases if broadly applied.Junlin Xu: Conceptualization ; data curation ; methodology ; project administration ; writing – original draft . Yajie Meng: Conceptualization ; data curation ; visualization ; writing – review and editing . Lihong Peng: Conceptualization ; project administration . Lijun Cai: Conceptualization ; supervision . Xianfang Tang: Data curation . Yuebin Liang: Visualization . Geng Tian: Writing – review and editing . Jialiang Yang: Conceptualization ; supervision .The authors confirm that there are no conflicts of interest.Figures S1‐S2Click here for additional data file.Table S1Click here for additional data file.


No specific abnormalities were found in immunochemistry, urine, or fecal analyzes, except for elevated serum neuron‐specific enolase . Computed tomography showed what might be an enlarged frontal boundary of the right ventricle with calcified foci. On magnetic resonance imaging, this seemed to correspond to a T1 low intensity mass, measuring 2.5 × 2.0 × 2.1 cm, with a few darker strands and no enhancement .PDGFRA p.K385L (rate: 38.76%) and NSD2 p.L581H (rate: 2.02%) mutations.Targeted next‐generation sequencing analysis using a 599 gene panel revealed 4PDGFRA, typically a dinucleotide mutation at codon 385 of the PDGFRA oncogene replacing lysine with either leucine or isoleucine (p.K385L/I), which appear to be highly characteristic for this tumor [PIK3CA/PIK3R1 alterations or BRAF/FGFR1 mutations which are characteristic of the majority of RGNT and DNET, respectively. Copy number profile is generally balanced. MGNT has a distinct DNA methylation profile, which together with the mutational pattern may be critical in some cases in distinguishing it from other central nervous system tumors.Myxoid glioneuronal tumor (MGNT) is a newly defined glioneuronal tumor in the 2021 WHO Classification of Tumors of the central nervous system, usually found in the septal area (nucleus accumbens or cavum septum pellucidum) and sometimes in the surrounding white matter or corpus callosum. MGNT can occur across a wide age range (6–65 years) . In 2018PDGFRA p.K385L mutation. An additional gene mutation was observed in this case, namely, NSD2 p.L581H (NSD2:NM_133330:exon10:c.1742T>A:p.L581H), also referred to as the MMSET or WHSC1. NSD2 is located on chromosome pair 4 and encodes nuclear receptor‐binding SET domain protein 2. Specifically, NSD2 catalyzes the methylation of the lysine site on the histone protein, thereby promoting the occurrence and progression of tumors through interactions with other proteins or regulation of target genes. However, as NSD2 rarely been reported in CNS tumors, its significance in the occurrence and progression of MGNT is unclear.In our case, the diagnosis of MGNT was suspected based on its histological appearance and confirmed by the molecular analysis. Targeted next‐generation sequencing analysis revealed Jun Zhou and Kexuan Qu designed the study and drafted the manuscript; Yucheng Xie made the diagnosis; Yan Gao and Mengxing Lv reviewed the specimen; Ling Duan and Zhixiang A conducted the IHC and molecular analysis; Hong‐Fang Wu provided clinical data; Lin Zhang provided imaging data; all authors took part in writing the manuscript and approved the final, submitted version.This study was funded by Kunming Health Science and Technology Personnel Training Project and “Ten Hundred Thousand” Project (fund number: 2021‐SW (province)‐024).The authors declare that they have no conflicts of interest.Ethical approval was obtained from the ethical committee from the Kunming Children's Hospital, Kunming, China.Written informed consent was obtained from the patient's parents.


N = 267; 40.4% mothers). Parents completed measures of their PA‐related beliefs, depressive symptomatology, and their responses to adolescents' PA at two‐time points, 5 months apart. Parental PA‐related beliefs showed low stability and depressive symptoms showed moderate stability across time. There were concurrent bivariate associations between parental PA‐related beliefs and their socialisation behaviours, though these relations did not hold in multivariate path analyses across time. Parental depressive symptoms at T1 inversely predicted family savouring at T2 and positively predicted dampening at T2. These findings provide the first line of evidence indicating that parental cognitions and their own mood contribute to their emotion‐related parenting behaviours in India.Emerging literature examines implications of parental socialisation of positive affect (PA) for children's socio‐emotional functioning, though little is known about predictors of parental PA socialisation behaviours in diverse families around the world. Based on the literature that suggests that parental cognitions  and their own mood state contribute to their parenting , we examined two parent‐related factors  as predictors of parental responses to their adolescents' PA in an urban middle‐class sample of mothers and fathers from India ( Positive emotions play an important role in adaptive outcomes including self‐esteem, enhancing creativity, and lowering the risk for depression  influence their parenting behaviours  from an urban city in India with a child in grade (standards) 9 through 12 . Of parents providing data, 96.4% were married. Parents endorsed family religion as 65.1% Hinduism, followed by 30.2% Christianity, 4.0% Islam and 0.7% Jainism. Number of total individuals in family homes ranged from 2 to 20 with three participants reporting between 12 and 20 individuals . The number of children ranged from 1 to 6 . A majority of participants had a monthly family income of 21,000–60,000 Rs. (51.5%) and parents' education ranged from less than standard 10 (2.1%), standard 10 complete (14.9%), standard 12 complete (19.5%), a few years of college (13.1%), a Bachelor's degree (32.6%), Master's degree (5.7%), to Doctoral/Professional degree (7.1%).Participants were 281 parents . Interested parents were instructed to read and sign the consent form, complete questionnaires, and return packets to their child's school in a sealed envelope. Study materials were available in both English and Kannada, a local language, although all parents chose to complete questionnaires in English. High school students in India spend a substantial amount of time preparing for state examinations with parents providing close monitoring. To be responsive to participants' needs to attend to academics, T2 data were collected before students began their exam preparations, 5 months after T1. A total of 89.32% of parents from T1 completed the questionnaires for T2. Participants received educational supplies worth INR 150 (US $2.29).Parents reported their gender, age, adolescent gender and age, number of individuals in the home, religion, and monthly income.Beliefs that PA is harmful were measured using the Parents' Beliefs about Children's Emotion Scale cost of positivity subscale which has been validated amongst North American samples  = 928.87, p < .01; CFI = 0.69; RMSEA (90%CI) = 0.08 ; SRMR = 0.11). Four items failed to load onto the dampening factor. Two of these items assessed parental encouragement of children to work harder after receiving a good grade, and two items assessed parental probing for NA when their child expressed PA. After removal of these items, fit was acceptable (χ2(268) = 455.32, p < .01; CFI = 0.87; RMSEA (90% CI) = 0.05; SRMR = 0.08). This factor structure was reasonably replicated at with Time 2 data (χ2 (268) = 517.78, p < 0.01; CFI = 0.84; RMSEA (90%CI) = 0.06; SRMR = 0.08). For analyses, mean item scores for dampening (8 items) and enhancing (17 items) at each time point, respectively, were used. Cronbach's alpha revealed adequate levels of reliability and ranged from 0.72 to 0.90  1310.70, p = .121) suggested that data were consistent with pattern of missing completely at random. Missing data were handled with multiple imputations for preliminary analyses  and full‐information maximum likelihood for primary aims.For primary variables, 13.20% of the data were missing. Variables with the most missingness included the RAHAS enhancement and dampening scales at T1 . Little's MCAR test  and mothers  reported more family savouring at T2 and parents with more education reported less dampening at T2 . As such, parent age, gender and education were included as covariates on relevant outcomes. No other demographic variables were associated with dependent variables in the model and thus were not considered further.A path analysis was conducted in Mplus v 7.4  = 17.44, p = .134; RMSEA(90%CI) = .04 ; CFI = .98; SRMR = .02; Hu & Bentler, Overall, the model fit the data well . In contrast, however, neither parental cost of positivity beliefs nor valuing PA beliefs significantly predicted changes in dampening responses.χ2(13) = 17.01, p = .199).Finally, we tested parent gender as a moderator. Because 16 parents did not indicate their gender identity, these moderation analyses were conducted on a subsample of 265 parents. To test moderation, a multigroup approach was used. Using a chi‐square difference test, model fit was compared for a model with all parameters freely estimated amongst mothers and fathers to a model in which parameters were constrained across gender. If the constrained model fit significantly worse, “omnibus” moderation would be indicated and followed by systematically testing each parameter across groups to identify specific paths that differed by parent gender. For this model, parent gender did not moderate any relations  serve as correlates of parents' responses in expected directions; if parents consider PA to be harmful, they prefer to reduce PA experiences for their adolescent and respond with dampening, whereas if parents consider PA to be valuable, they prefer to maximise PA experiences for their adolescent. These findings replicated the cross‐sectional finding from a US‐based study demonstrating that parental cost of positivity beliefs were uniquely associated with dampening responses . There were no significant bivariate associations between PA beliefs and depressive symptoms within or across time  suggesting that parents' depression did not contribute to low stability in their beliefs, and that parents' beliefs and mood are relatively independent of one another.Depressive symptoms showed moderate stability , type of PA experienced , and how adolescents respond to parental socialisation. Future research may examine how these additional factors impact parental PA socialisation processes over time across a longer duration. Future research may also use open‐ended qualitative methods to explore parents' PA socialisation behaviours, and use these data to modify existing measures or develop new measures.The current study extends previous cross‐sectional work conducted in the USA to demonstrate that parental cognitions and mood are important correlates of parent behaviours in communities around the world. Furthermore, this study is the first to demonstrate predictive value of parents' depressive symptoms for their PA socialisation over time using a longitudinal design. These findings contribute to expanding theoretical frameworks of PA socialisation in diverse families, and have implications for parenting interventions that may target parental beliefs and mood to change parent behaviours.


Recent reports indicate that the prevalence of food allergy is increasing, but accurate estimates remain a challenge due to cross‐reactivity and limited use of precise diagnostic methods. Molecular allergy diagnostics, in which sensitization to individual molecular allergens is measured, is emerging as a promising tool for evaluation of sensitization profiles. In this systematic review, we summarized estimates of prevalence of sensitization to molecular food allergens in the general population in Europe.Following a protocol prospectively registered with the International Prospective Register of Systematic Reviews , we searched seven databases with no restrictions on publication date or language. Two reviewers independently screened the literature, extracted data, and appraised the risk of bias in the included studies. The findings were synthesized narratively.From 4776 de‐duplicated records, five studies, with low to moderate overall risk of bias, were included. Forty‐six molecular allergens from 18 foods were investigated. Overall, the prevalence of sensitization was low, particularly for major allergens, and non‐existent for 10 molecular allergens (0% [95% CI 0–0.8]). The highest prevalence was seen for PR‐10 proteins, such as Cor a 1.04 (13.6% [95% CI 10.9–16.9]).Available data, primarily from North‐western Europe, indicate that sensitization to molecular food allergens is overall low. The highest estimates were found for cross‐reactive PR‐10 proteins. There were not enough studies to discern regional differences or perform meta‐analysis, highlighting the need for more population‐representative studies in order to elucidate patterns of sensitization to molecular food allergens in Europe. Conversely, case studies, case series, clinical trials, non‐systematic reviews, expert opinions, and animal studies were excluded. There was no restriction regarding publication status/date or language. Articles in languages other than English were translated using Google Translate.2.2.2Studies with population‐representative samples were eligible. A sample was considered population‐representative if the participants had comparable statistical likelihood of being recruited, either through the means of exhaustive sampling, or through random selection. Studies with participants residing in European countries, as defined by the United Nations ; 3) fetching articles in the “Epidemiology from Literature” table. Due to the overwhelming number of allergens in Allergome, steps 1)–3) were repeated only for the eight most common foods.Allergome was searched by: 1) searching for the first molecular allergen  of that food ; 2) browsing to the page for each molecular allergen of that food .EndNote 20  was used for de‐duplication. Screening of title/abstract, full‐text screening, and general management of full‐text PDFs was done in Rayyan  independently. After each stage, the decisions were unblinded and compared for differences, which were resolved through discussion. No arbitration through a third reviewer was required.2.6A Microsoft Excel  extraction form (available upon request), piloted a priori, was used to extract data. Two reviewers (DL and AI) extracted data independently, and differences were resolved through discussion. No arbitration through a third reviewer was required.2.7The following data items were extracted and summarized from each study: surname of first author; publication year; study design; number of individuals recruited/included; period of data collection; country of study; subject characteristics ; molecular allergen(s) investigated; diagnostic method and cut‐off value(s); results .2.8Assessment of risk of bias in the included studies was done using forms based on the Critical Appraisal Skills Programme (CASP) tool. CASP checklists for systematic reviews, cohort studies , and case‐control studies, respectively, were adapted. Specific questions differed somewhat between the forms for respective study design, but assessed the same four sections: study design, participant selection, exposure assessment, and outcome assessment. Each of these sections were rated as “high”, “moderate”, or “low” risk of bias, or “not applicable”/“not available”, depending on available information. Each study was also given an overall rating, based on the section ratings and a collected assessment. This process was performed by two reviewers (DL and AI) independently. Differences were resolved through discussion. No arbitration through a third reviewer was required.2.9A descriptive table was produced to summarize essential characteristics of the included studies. The results were narratively synthesized. For consistency, data in the synthesis were limited to measurements with the conventional2.10p=nsensitized/ntotal. The 95% CI was estimated using Wilson's score interval without continuity correction,plower=2r+z2−zz2+4rq2n+z2 and pupper=2r+z2+zz2+4rq2n+z2, where r = nsensitized, q = 1 – p, and z = 1.96 .Prevalence was defined as 2.11post hoc.After having conducted the initial searches, the authors identified Allergome as a relevant source, housing articles not identified with previous methods. A search of Allergome was thus performed 33.1Our searches yielded 5425 records. After de‐duplication, 4776 records were screened. Of these, five studies3.2Two studies3.33.3.1Alpha‐gal was investigated by Gonzalez‐Quintela et al.,3.3.2Molecular peanut allergens were evaluated in two studies.In a sample of 501 school‐age children in Austria, Stemeseder et al.3.3.3n = 246) of children from a British birth cohort followed up at 10 years (n = 827) consented to an allergy screening blood test using a panel of aeroallergens and food allergens, respectively. In the 15% (n = 37) who showed sIgE sensitization to whole wheat extract, molecular allergy diagnostics was performed. Prevalence of sensitization to Tri a 14 and wheat gliadin , respectively, was 2.7% (95% CI 0.5–13.8), and 8.1% (95% CI 2.8–21.3) to Tri a 19 in the wheat‐sensitized children. The authors found that significantly more subjects (p < 0.05) had a history of any allergen sensitization among those who took the allergy screening test than those who did not take the test, and thus regard that the prevalence estimates are reflective of a higher risk population. Stemeseder et al.,Molecular wheat allergens were evaluated in two studies.3.3.4In the study by Stemeseder et al.,3.4In a birth cohort of 104 children from five German cities, Huang et al.3.5Huang et al.44.1st century.This is the first systematic review to summarize the sensitization prevalence to molecular food allergens in the general population in Europe. Overall, sensitization was low to most of the 46 investigated molecular allergens. In non‐allergic individuals, labile, cross‐reactive molecular allergens were the most common, while individuals with food allergy were more commonly sensitized to storage proteins. Sensitization to 20 molecular allergens was non‐existent or barely detected. In the general population, the highest sensitization was found for PR‐10 proteins. There were too few studies to draw conclusions regarding which foods had the highest/lowest sensitization rates, and whether the “big eight” foods are the most common at the molecular allergen level. Some indications of regional differences were noted, such as lower sensitization to alpha‐gal in Denmark than in Spain, but the data were insufficient to draw any conclusions, neither on country level nor on urban/rural level. It is also noteworthy, that while the included studies were published 2010–2018, the data were collected 2000–2014; thus, a significant proportion of the data describes sensitization prevalence from the early 214.2We have conducted a comprehensive search of seven databases with no restrictions on language or publication date. Despite this, the number of relevant studies with population‐based samples was low. Given the vast nomenclature in molecular allergology, the search queries may not have encompassed all appropriate keywords, and thus not have identified all relevant literature. The included studies were heterogenous, which limited the possibility to identify patterns from the findings or perform meta‐analysis. Such differences were apparent in the molecular allergy diagnostic assays employed across studies. In addition, four out of the five studies only presented data on children/adolescents, and four studies only presented data from North‐western Europe, further narrowing the representativeness of the data. It is also worth noting, that two of the studies employed ISAC, which, due to lower sensitivity, increases the risk of underestimating the point prevalence compared to ImmunoCAP.4.3To the best of our knowledge, no systematic review has previously assessed the prevalence of sensitization to molecular allergens of multiple foods on a Europe‐wide general population basis. Existing reviews have primarily focused on single foods in a non‐systematic manner,Aligning with existing literature,4.4Although molecular allergy diagnostics has increasingly been implemented over the last decade, this review found important research gaps in the field. In particular, only five studies published so far are population‐based, while most studies are case reports or case series, recruiting participants from hospitals or specialized inpatient/outpatient allergy clinics. These studies do not allow accurate estimation of population prevalence. Going forward, there is a need for more population‐based studies to accurately assess the prevalence of sensitization to molecular food allergens. Finally, given the current use of varying assays to measure IgE sensitization to molecular food allergens , standardizing molecular allergy diagnostic assays will facilitate comparison between different tests.5This review, with data primarily from North‐western Europe, indicates that sensitization to molecular food allergens is overall low, particularly for molecular allergens representing primary sensitizers from the food, such as peanut storage proteins. The highest sensitization rates were seen for cross‐reactive PR‐10 proteins, for which birch pollen are acknowledged to be the primary sensitizer. More population‐representative studies are needed to gain a clearer appreciation of sensitization patterns to molecular food allergens in Europe.Bright I. Nwaru and Graham Roberts conceived the research question and developed the search strategy with assistance from Daniil Lisik. The data extraction form was developed by Daniil Lisik, with assistance from Bright I. Nwaru. Screening, data extraction, narrative synthesis, and writing of the manuscript was done by Daniil Lisik, Athina Ioannidou, and Bright I. Nwaru. Ekaterina Khaleva, Carina Venter, Ronald van Ree, Margitta Worm, Berber Vlieg‐Boerstra, Aziz Sheikh, Antonella Muraro, and Graham Roberts were consulted concerning methodology and synthesis of the findings. All authors critically commented on drafts of the manuscript.Carina Venter reports: grants  and personal fees . Ronald van Ree reports: consultancies , speaker's fees , and stock options (Angany Inc.). Margitta Worm reports: grants and personal fees  outside of the submitted work and being past WAO co‐chair of the anaphylaxis committee and past chair of the food allergy interest group of EAACI. Berber Vlieg‐Boerstra reports: personal fees  and grants (Nutricia). Antonella Muraro reports: grants and speaker's fees (Aimmune), speaker's fees , and being member of the Executive Committee of GA2LEN and past president of EAACI. Graham Roberts reports grants . Bright Nwaru reports unrestricted grants and personal fees from DBV Technologies and AstraZeneca, respectively. The other authors report no conflicting interests related to this work. The funder played no role in the content and decision to submit this manuscript.Supporting Information S1Click here for additional data file.Supporting Information S2Click here for additional data file.Supporting Information S3Click here for additional data file.Supporting Information S4Click here for additional data file.


Given the low incidence of urachal carcinoma of the bladder (UCB), there is limited published data from contemporary population‐based cohorts. This study aimed to describe demographic, clinicopathological features, and survival outcomes of patients diagnosed with UCB.The National Cancer Database (2004–2016) was queried for UCB patients. Descriptive analyses characterized demographics and clinicopathologic features. We assessed 5‐year overall survival (OS) rates of the entire cohort and subgroups of localized/locally advanced and metastatic disease. We utilized Cox proportional hazards models to assess the association between covariates of interest and all‐cause mortality and to examine the impact of surgical technique and chemotherapy.p < 0.001). Overall, median OS was 59 months, and 5‐year OS was 49%. In patients with localized/locally advanced disease, we found no association between partial and radical cystectomy  as well as receipt of perioperative chemotherapy  and outcomes. Lastly, receipt of systemic therapy was not associated with survival benefit  in metastatic disease cohort.We identified 841 patients with UCB. The most common histologic subtype was non‐mucinous adenocarcinoma (39.6%). Approximately 50% had ≥cT2 disease, and 14.3% were metastatic at diagnosis. Altogether, partial cystectomy (60%) was most performed, and lymph node dissection was performed in 377 patients (44.8%), with specific temporal increase in utilization over the study period  provides insight into the surgical management and systemic therapy, without clear evidence on the association of chemotherapy and survival in the peri‐operative and metastatic setting. Prospective, multi‐intuitional studies are needed to identify multi‐modal approaches to improve outcomes for patients with UCB. Though a persistent urachal remnant remains mainly benign, it can give rise to more sinister pathologies later in life, such as urachal cancer.Due to the substantially low incidence of urachal cancer, the current diagnostic and treatment evidence is primarily derived from single‐institution series, and there is limited published data from contemporary population‐based cohorts.We sought to utilize population‐based data to inform contemporary patient and disease‐ related features of UCB, and patterns of treatment using the National Cancer Database (NCDB). We focused on two patient subgroups  to describe clinicopathologic features and analyzed the association between survival outcomes and histologic types, varying treatment strategies. This included surgical treatments (PC or RC and the role of lymph node dissection [LND]) in localized/locally advanced disease, and the role of systemic chemotherapy in metastatic disease.22.1The NCDB is a joint project between the Commission on Cancer (CoC) of the American Cancer Society and American College of Surgeons. It is a contemporary, hospital‐based database that captures approximately 70% of new cancer diagnoses in the US annually, based on data collected from more than 1500 participating CoC accredited hospitals.2.2The NCDB was queried to identify patients with International Classification of Disease for Oncology, Third Edition, (ICD‐O‐3) topographical code for urachal carcinoma (C67.7) who were aged 18 to 90 years old and diagnosed between 2004 and 2016. The staging information for patients was coded using the American Joint Committee on Cancer (AJCC) staging system for bladder cancer. For analytic purposes, patients with in‐situ and stage 1 disease were grouped together as stage 1. Patients with 1cT1–cT4, cN0–1, and cM0 were included in our entire cohort.2.3Demographic and clinical data included age, sex, race, Charlson comorbidity index (CCI), residence , and insurance status. Facility‐level variables included location  and the degree of practice specialization. Disease‐related characteristics included tumor histology, clinical T‐stage, grade, presence of distant metastasis, regional lymph node positivity, tumor size, surgical approach, surgical margin status, and treatment modality. Site‐specific surgery codes were used to identify surgical procedures, as local tumor excision , PC (30), and RC . Excision of metastatic lesions was assessed according to the Facility Oncology Registry Standards.2.4The primary outcome was overall survival (OS) from the initial diagnosis to the date of death or last follow‐up.2.5Demographic, clinicopathologic, and treatment data of patients with diagnosis of urachal carcinoma are presented as median [interquartile range (IQR)] for continuous variables and number (percentage) for categorical variables. OS was estimated using the Kaplan–Meier analyses for staging subgroups, and the Log‐rank testing was used to determine significant OS differences.Cox proportional hazards models were utilized to determine the association between survival and patient‐, facility‐, and disease factors. The global test, based on Schoenfeld residuals, showed that the proportional hazard assumption was violated for several variables, including histology, clinical staging, receipt of PC or RC, tumor size, and receipt of systemic therapy (neoadjuvant or adjuvant). Therefore, a multivariable Cox model was built, with an interaction term with time for violated variables along with other covariates. Hazard ratios were derived for 1, 3, and 5‐year time periods for interpretability.p < 0.05 for all tests. All analyses were performed with STATA version 16 (Stata Corp.).Patients were subdivided into two cohorts for subgroup analysis. The first consisted of localized and locally advanced urachal carcinoma  to evaluate the association of varying surgical management (PC or RC), nodal dissection, and perioperative chemotherapy and survival. Patients with ≤cT1 were excluded from this subgroup survival analysis because patients harboring this stage of disease do not typically undergo systemic therapy. A second cohort, consisting of patients with metastatic disease (Stage 4), was created to evaluate the association between chemotherapy and survival. The proportional hazard assumptions were met in both subgroups. Statistical significance was defined as two‐tailed 33.1Baseline demographic, clinicopathologic, tumor characteristics are summarized in Table Clinical T‐stage was ≤T1 in 21%, T2 in 15.2%, and ≥T3 in 9.4% at the time of diagnosis. The most common, known clinical nodal stage was cN0 in 525 patients (65.3%), followed by unknown or not examined nodal status in 233 (29.0%). Only 46 patients (5.7%) had clinically suspected nodal disease at diagnosis. Most patients were diagnosed with non‐metastatic disease (85.5%), and 14.3% of patients presented with suspected metastatic disease.The majority of the tumors were histologically noted to be either moderately (31.3%) or poorly (29.4%) differentiated. Overall, urachal tumors predominantly harbored glandular histologic features (85.3%), with the most common histologic subtypes being non‐mucinous adenocarcinoma (39.6%) and mucinous adenocarcinoma (39.1%). When comparing all histological subtypes of UCB, signet ring cell (66.7%), urothelial (51.2%), and squamous cell carcinomas (46.2%) presented with worse histologic grade with poorly differentiated or undifferentiated Table 3.2n = 256). Among patients who were treated with chemotherapy, those with locally advanced or metastatic disease were the most prevalent population (61.4%), as expected. The combination of surgical management with radiation was less common , but when given, most cases were adjuvant radiation . In the subgroup of patients with localized or locally advanced disease, the majority underwent PC . Those undergoing PC were more likely to harbor glandular histology (p = 0.012) and undergo concurrent LND (p = 0.004) as compared to RC , of which PC was found to be the most common surgical procedure (60.4%), followed by local tumor excision (18%) and RC (8.4%) Table . SystemiRC Table .p < 0.001); however, despite the increased utilization of LND at the time of RC from 50% in 2004 to 100% in 2016, the increased trend was not found to be statistically significant (Cochran‐Armitage test for trend p = 0.42), likely owing to the small number of patients undergoing RC.At the time surgery, approximately 45% of patients underwent regional LND. When we examined the rate of LND between patients who underwent PC or RC by the year of surgery, we identified an increase over the study period for PC . Median OS for the entire cohort was 59 months, and the estimated 5‐year OS was 49% (95% CI 44.8–53) Figure . Using Kp = 0.003), stage (p < 0.001), tumor size (p = 0.02), and either PC or RC  were associated with OS. Most notably, signet ring cell carcinoma, a non‐adenocarcinoma histology, was associated with an increased risk of all‐cause mortality . Receipt of multi‐agent chemotherapy was also associated with higher risk of all‐cause mortality  compared to no chemotherapy. However, tumor grade and CCI were not independently associated with worse survival than well‐ or moderately differentiated tumor and CCI of 0.Multivariable Cox proportional hazards model demonstrated several predictors of OS Table . We mode3.4p = 0.04), as compared to clinical T‐stage 2. Receipt of neoadjuvant  or adjuvant  chemotherapy was not associated with OS in this cohort. We found no association between receipt of any chemotherapy and survival . Surgical technique (PC vs. RC) was not associated with OS . A positive surgical margin was not associated with an increased risk of all‐cause mortality .In the subgroup of patients diagnosed with localized or locally advanced disease and those who underwent either PC or RC Table , higher p = 0.52, Table Lastly, in the subgroup of patients diagnosed with metastatic disease, in whom the preferred treatment is systemic therapy, we observed no association between the receipt of chemotherapy and OS .The current literature on urachal tumors histology (adenocarcinoma) is that the prognosis of either glandular or non‐glandular subtypes are both equally poor.p = 0.004), while those undergoing RC were more likely to harbor non‐glandular pathology which was shown to portend a poor outcome. The decision to undergo surgery is multifactorial, and requires assessment of patient preferences, bladder functionality , and tumor factors, including resectability and location. Ultimately, this may inevitably lead to selection bias for treatment approach.The current recommended treatment for localized disease includes excision of the urachus and bilateral medial umbilical ligaments with PC or RC.p < 0.001) had an increased risk in all‐cause mortality, which likely represents selection bias, as those patients harboring worse disease likely preferentially received LND.The role of LND is pivotal in defining cancer staging (pT), as evident in Sheldon, Mayo, and TNM staging guidelines.Chemotherapy is typically considered for patients with adenocarcinoma of the urachus per NCCN guidelines in the metastatic and adjuvant setting in those with high‐risk pathology, including locally advanced or regionally positive nodal disease.There are several limitations to this study. First, our findings should be interpreted within the retrospective framework of the study. There is a possibility of selection bias, either due to physician practice patterns or patient preferences. Second, data regarding surgical technique, anatomic dissection limits are not reported in NCDB. The mainstay of the treatment, en‐bloc resection of the median umbilical ligament with the umbilicus during the PC, was not recorded by NCDB. Third, the NCDB does not capture several important chemotherapy characteristics, including the type of regimen, the number of cycles, and data regarding response to treatment, making specific practice recommendations impossible. Fourth, our findings can only be generalized to facilities participating in the NCDB. While this includes roughly 70% of all new cancer cases, it may represent a biased sample of facilities with a high volume of oncology referrals and patients. We also found that approximately ~40% patients had an overall unknown AJCC stage, which may reflect a lack of a standardized staging system for urachal carcinoma. The most two common staging systems used are Sheldon and Mayo staging;5We present the largest cohort ever assembled of patients with this rare disease. Our results implicate that either PC or RC for the management of UCB in localized and locally advanced disease is reasonable, and the decision should be made based on patient preference, comorbidities, and bladder function status. Unlike prior studies, we found no association in OS and positive margin status. Our findings demonstrate that LND has been increasingly performed over the last few years for patients undergoing PC. Systemic chemotherapy was not associated with OS in the management of localized or advanced disease, however. Thus, further studies are warranted to develop novel treatment strategies to improve patient outcomes.Furkan Dursun: Conceptualization, investigation, methodology; writing – original draft; writing – review & editing. Kelvin Lim: Writing – review & editing. Robert S. Svatek: Writing – review & editing. Jiaqiong Xu: Formal analysis, software, writing – review & editing. Ziad M. El‐Zaatari: Writing – review & editing. Evan P. Wenker: Writing – review & editing. Zachary W. Klaassen: Writing – review & editing. Ahmed M. Mansour: Writing – review & editing. Taliah Muhammad: Writing – review & editing. Eleni Efstathiou: Writing – review & editing. Guru P. Sonpavde: Writing – review & editing. Christopher J.D. Wallis: Methodology; writing – review & editing. Raj Satkunasivam: Conceptualization, investigation, methodology; supervision; data curation; writing – original draft; writing – review & editing.There are no relevant conflict of interest for all authors.This study was exempt from required ethics board approval at our institutions.Table S1.Click here for additional data file.


All‐cause mortality risk prediction models for patients with type 2 diabetes mellitus (T2DM) in mainland China have not been established. This study aimed to fill this gap.Based on the Shanghai Link Healthcare Database, patients diagnosed with T2DM and aged 40‐99 years were identified between January 1, 2013 and December 31, 2016 and followed until December 31, 2021. All the patients were randomly allocated into training and validation sets at a 2:1 ratio. Cox proportional hazards models were used to develop the all‐cause mortality risk prediction model. The model performance was evaluated by discrimination (Harrell C‐index) and calibration .A total of 399 784 patients with T2DM were eventually enrolled, with 68 318 deaths over a median follow‐up of 6.93 years. The final prediction model included age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, glycosylated hemoglobin, and high‐density lipoprotein cholesterol. The model showed good discrimination and calibration in the validation sets: the mean C‐index value was 0.8113 (range 0.8110–0.8115) and the predicted risks closely matched the observed risks in the calibration plots.This study constructed the first 5‐year all‐cause mortality risk prediction model for patients with T2DM in south China, with good predictive performance. HighlightsThis study constructed the first 5‐year all‐cause mortality risk prediction model for patients with type 2 diabetes mellitus in south China.This well‐performing model, using highly accessible predictors collected in routine clinical settings, provides a powerful tool for clinicians to identify high‐risk diabetic patients. More than 6.7 million adults were estimated to have died from diabetes or its complications in 2021, accounting for 12.2% of all‐cause deaths worldwide.In the past decade or so, many prediction models have been well developed in Western populations, such as the Estimation of Mortality Risk in Type 2 Diabetic Patients (ENFORCE) model,22.1This study was conducted using the Shanghai Link Healthcare Database (SLHD), a representative clinical database covering ＞99% of the residents, developed and operated by the Shanghai Hospital Development Center . In China, government‐run hospitals are classified as primary (grade I), secondary (grade II), and tertiary (grade III) hospitals according to their capabilities in medical care, medical education, and medical research, with tertiary hospitals being the best. The Shanghai Hospital Development Center is responsible for monitoring 35 tertiary hospitals, all of which are required by administrative regulations to upload general medical practice data  to the SLHD. The SLHD has released data for academic research since 2013, which requires review and approval to access. Mortality data were obtained from the Shanghai Big Data Center.International Classification of Diseases, 10th Revision and relevant diagnosis . Follow‐up started from the date of the first diagnosis of T2DM until death or December 31, 2021, whichever came first. After excluding patients with <1 year of follow‐up (n = 18 946), a total of 399 784 patients with T2DM were finally enrolled in the study , total cholesterol, high‐density lipoprotein cholesterol (HDL‐C), low‐density lipoprotein cholesterol (LDL‐C), and triglyceride. Comorbidities and medications were assessed between the earliest date of recording and the end date of the 1‐year lag period after cohort entry. Biochemical indicators were defined as the closest recorded values within 2 years before and after enrollment.Multiple imputation was performed to handle missing values of biochemical indicators. The imputation model included candidate predictors and event indicators. A total of 10 datasets were imputed, and the data distribution of biochemical indicators in the original and imputed datasets indicated good imputation Table . Subsequ2.4t test for continuous variables and the chi‐square test for categorical variables. Standardized mean differences (SMDs) were also calculated to assess the comparability of baseline characteristics between the training and validation sets, with values less than 10% indicating relative balance.All the patients were randomly allocated into training and validation sets at a 2:1 ratio. Baseline characteristics between the training and validation sets were compared using the Student's Cox proportional hazards models were used to develop the all‐cause mortality prediction model. To account for the nonlinearity of the continuous variables , we transformed them using restricted cubic splines with four knots placed at the respective 5th, 35th, 65th, and 95th sample percentiles.The developed model was applied to the 10 imputed validation datasets to evaluate model performance. Discrimination was assessed by estimating Harrell C‐index, with higher values indicating better performance. Calibration was assessed by plotting the predicted event probabilities against the observed event probabilities. The risk prediction model was internally validated using 100 bootstrap samples. In addition, to examine the effect of missing data, we repeated the validation using complete case analysis. All statistical analyses were performed using R language software, version 4.1.2 .3n = 266 523) and validation set (n = 133 261). The SMD values for all baseline characteristics between the training and validation sets were much lower than 10%, implying that the two were well balanced.A total of 399 784 patients with T2DM were enrolled in this study. During a median follow‐up of 6.93 years (IQR 5.64–8.31 years), 68 318 patients died, with an all‐cause mortality of 2.54 per 100 person‐years. The median age was 63 years (IQR 56–72 years), and 51.11% were male. Table u+=u,ifu>0,0,ifu≤0.Variable selection was performed in each of the 10 imputed training datasets. Predictors included in the final model were age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, HbA1c, and HDL‐C. Table Example: 65 years old; male; history of heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, and cancer; use of insulin; HbA1c level = 12.00%, HDL‐C level = 1.00 mmol/L.5‐year all‐cause mortality risk ≈ 86.94%Table 4This study constructed the first 5‐year all‐cause mortality risk prediction model for patients with T2DM in south China. The model achieved good discrimination and calibration by using highly accessible predictors collected in routine clinical settings, including age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, HbA1c, and HDL‐C.Over the past decade or so, many all‐cause mortality risk prediction models have been constructed for patients with T2DM. However, due to differences in ethnicity, genetics, socioeconomic factors, and disease management approaches, prediction models developed based on specific populations are usually not directly applicable to other populations. Several models have been established to predict the risk of all‐cause mortality in Western populations with T2DM.Notably, the data sources used to develop the models can also affect predictive validity. Whether models developed based on non‐real‐world data can be well applied to the real world remains a question. It has been found that prediction models perform much less well in the clinical trial setting than in the real world.The SLHD is the largest medical database in mainland China, which provided a good basis for the design and implementation of this study. We identified a number of candidate predictors based on data availability and clinical relevance. The final prediction model included age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, HbA1c, and HDL‐C, which balanced the predictive validity and parsimony of the model well.Glycemic control is definitely crucial for patients with T2DM. Clinically, the main indicator used to evaluate glycemic control status is HbA1c, which reflects the average plasma glucose level over the past 2–3 months. Insulin, as the most effective class of antidiabetic drugs, is commonly used in patients whose plasma glucose levels cannot be well controlled by oral antidiabetic drugs. In general, patients with higher HbA1c levels or those using insulin have a longer duration and more severe disease. Therefore, HbA1c and insulin play a crucial role in predicting the risk of all‐cause mortality among patients with T2DM.This study has some limitations. The first is the data limitation. Although the SLHD is the largest medical database in mainland China, there is a relatively high proportion of missing data for some variables, such as biochemical indicators, duration of diabetes, body mass index, smoking, and alcohol consumption. It is worth noting that such missing data were usually not random and may indicate patient characteristics, health awareness level, and health status. Directly removing observations with missing values would introduce severe bias. Therefore, we performed multiple imputation to handle missing data (widely considered the best approach) and conducted complete case analysis to examine the effect of missing data. Second, due to resource constraints, the prediction model was only internally validated, and further external validation in other populations is advisable. Third, only a 5‐year all‐cause mortality risk prediction model was constructed in this study, and future studies with longer follow‐up periods are needed to update the model to predict the mortality risk at 10, 15, and more years.In conclusion, this study constructed the first 5‐year all‐cause mortality risk prediction model for patients with T2DM in south China, which achieved good discrimination and calibration by using highly accessible predictors collected in routine clinical settings. The model provides a powerful tool for clinicians to identify high‐risk diabetic patients, which can enhance clinical management and facilitate timely intervention, ultimately improving survival quality and extending life expectancy.The authors declare that there is no conflict of interest.Figure S1. Flowchart showing the selection process of the study populationClick here for additional data file.Figure S2. Calibration curve of the 5‐year all‐cause mortality risk prediction model in the complete datasetClick here for additional data file.Table S1. ICD‐10 codes for diseasesTable S2. Data distribution of biochemical indicators in the original and imputed datasetsClick here for additional data file.


Evidence on survival and major prognosticators after salvage surgery in recurrent sinonasal cancers (SNC) is limited.A retrospective, single‐center study of recurrent SNC treated with salvage surgery between 1997 and 2019 was conducted. Univariate and multivariable analyses were performed to define a prognostic score for overall survival (OS).One hundred and eighteen patients were included. Recurrent SNC originated mostly in the naso‐ethmoidal box (67.8%) and were mainly epithelial (76.2%), high‐grade (49.2%), and locally advanced  malignancies. Negative margins were achieved in 56.6% of cases. Two‐ and 5‐year OS were 71.7% and 56%, respectively. The prognostic model included treatment modality for primary tumor, histology, rpT class, margin status, perineural invasion, and adjuvant radiotherapy and stratified patients into three prognostic groups .Treatment of recurrent SNC can result in good long‐term survival estimates with limited morbidity. Our score can provide excellent prognostic stratification. Survival is usually dismal, ranging between 50% and 70% at 5 years,Local recurrences of SNC pose prominent challenges. In view of the low rate of distant spread (approximately in 10%–15% of cases),In this setting, the trade‐off threshold between aggressive and palliative treatments remains undetermined owing to the scarcity of published evidence. To date, only one study has specifically investigated prognostic indicators for salvage surgery in recurrent SNC.The present study is a retrospective analysis of a cohort of patients with recurrent SNC who underwent salvage surgery with or without adjuvant treatments at a single tertiary, academic, referral center. The aim is to define prognosticators for these patients and propose a prognostic score to predict survival.22.1A retrospective analysis of consecutive patients affected by recurrent SNC treated from October 1997 to February 2019 was conducted at the Unit of Otorhinolaryngology – Head and Neck Surgery, ASST Spedali Civili, University of Brescia, Italy. Inclusion criteria were (a) first local recurrence of primary SNC  after treatment with curative intent; (b) recurrence treated with curative intent through a surgery‐including protocol; (c) availability of survival outcomes with minimum follow‐up of 6 months for event‐free observations. Exclusion criteria included (a) persistent disease, defined as disease‐free interval (DFI) between primary and recurrent SNC <6 months, and (b) distant metastasis at recurrence.The study was conducted in accordance with the Declaration of Helsinki and approved by the local ethics committee (NP3616).2.2Patients were selected from a prospectively accrued database and clinical‐pathological data  were retrieved by chart review. All tumors were reclassified according to the AJCC‐UICC TNM Staging System 8th Edition.Uninvolved surgical margins (R0) were defined as described in a previous publication from our group.2.3The primary objective was the definition of recurrent SNC major prognosticators, and their combination in a prognostic score, having as main outcomes of interest overall (OS) and relapse‐free (RFS) survivals.Secondary objectives were (a) definition of survival estimates for locoregional recurrence‐free survival (LRRFS) and distant recurrence‐free survival (DRFS) and (b) evaluation of safety of treatments.2.4Characteristics of patients were expressed in terms of percentages, median, interquartile range (IQR), and range of values, as appropriate. Continuous variables were categorized according to their median value.Univariate analyses were conducted using the Cox proportional hazard model and log‐rank test. Results were expressed in terms of hazard ratio (HR) and 5‐year OS estimates, respectively, with the relative 95% confidence intervals (CI), and graphically depicted by Kaplan–Meier curves.A multivariable Cox proportional‐hazards model was conducted considering prognostically relevant clinical factors that may guide treatment in a recurrent setting. Variance inflation factor (vif) was estimated to exclude multicollinearity; vif <5 was considered as satisfactory. A prognostic formula, equivalent to the sum of the coefficients of risk for each independent prognosticator, was developed. The prognostic formula was applied in our cohort and a score was calculated for each patient.p and the maximum χ2 values. The X‐tile software generated randomized “training” and “validation” cohorts, which were normalized so that their base survival curves were similar. The “training” to “validation” cohort size ratio was 1:1. The minimum percentage of the total patient cohort for each subpopulation was set at 10%. Once the ideal cut‐off was automatically set in the “training” cohort, the software then internally validated it through its application in the “validation” cohort.To distinguish patients with poor, intermediate, and favorable prognosis, specific cut‐offs in the prognostic score were found by X‐tile software , according to the minimum The so‐defined cutoffs were applied to the entire cohort. Survival curves with relative 95% CI and number of patients at risk by time according to the prognostic classification were plotted using the Kaplan–Meier method and compared with the log‐rank test. HR were retrieved with the Cox proportional hazard regression model.p‐values <0.05 were considered statistically significant.Uni‐ and multivariate analyses for RFS were conducted using the same methodology. Statistical analysis was performed using R  and 33.1During the study period, 543 patients with SNC were treated with curative intent at our institution; 118 (21.7%) met inclusion criteria. Eighty‐two (69.5%) patients were males and median age at recurrence was 66 years .Tumor features are detailed in Table Recurrences were mostly classified as high‐grade (49.2%) and locally advanced  lesions. The anterior skull base, dura, and brain were involved in 35.9%, 14.8%, and 4.3% of cases, respectively, while the nasopharynx, pterygopalatine (PPF), and infratemporal (ITF) fossae in 12.8%, 12.2%, and 12.0% of patients, respectively. Orbital involvement beyond the periorbita was recorded in 20 (16.9%) patients.Details on treatments are summarized in Table 3.2Oncological outcomes and survival estimates are detailed in Table Median follow‐up was 36 months . At the last follow‐up, 57 (48.3%) patients were alive, and 47 (39.8%) were disease‐free. Sixty‐one (51.7%) were dead, mostly due to disease progression , showing a median survival time of 23 months . Further disease relapse (any site) was diagnosed in 61 (55.4%) patients, with a median DFI of 10 months . Locoregional recurrence was the most frequent site of tumor relapse . Five‐year OS was 56.0%, while 5‐year RFS, LRRFS, and DRFS were 42.5%, 48.1%, and 79.3%, respectively.p = 0.203). The use of adjuvant RT .The median hospitalization ratio among dead patients was 1.1%. At univariate analysis Tables . OlfactoT Figure  was asso3.3Multivariable analysis of the most relevant clinicopathological and treatment‐related features confirmed (C)RT for primary tumor, histology, rpT4b class, positive margins, PNI, and adjuvant RT after salvage surgery as independent prognosticators of OS Table .The risk coefficients of the abovementioned independent variables were used to develop our prognostic score, as follows:SCORE = A*0.79 + B*2.09 + C*1.43 + D*3.03 + E*2.51 + F*1.03 + G*1.30 + H*1.13 + I*1.03.A: Exclusive (C)RT for primary tumor .B: Recurrent SCC .C: Recurrent ITAC .D: Recurrent MM .E: Recurrent SNEC .F: rpT4b .G: Positive surgical margins .H: Presence of perineural invasion .I: No adjuvant RT after salvage surgery .p < 0.001) and Group C .According to the cut‐offs found with X‐tile analysis, patients were categorized into three groups: Group A (score <3.15) with favorable prognosis; Group B (score between 3.15 and 4.85) with intermediate prognosis; Group C (score >4.85) with poor prognosis Figure . Median 3.4p = 0.088), while SCC, MM, SNEC, and SNUC showed the worst estimates. The multivariable model (Table p = 0.033), MM , rpT4b class , and positivity of surgical margins  on tumor control. Adjuvant RT as part of salvage treatment showed a close‐to‐significant independent protective role .RFS largely paralleled OS. At univariate analysis Table , severalel Table  outlined4The present study demonstrates that aggressive treatment of recurrent SNCs through surgery‐including protocols can convey good survival estimates even in the long term. However, patient selection plays a pivotal role in optimizing outcomes, improving allocation of resources, and avoiding futile treatment‐related morbidity. Our score, based on the type of primary treatment, histology, rpT class, margin status, PNI, and adjuvant RT allows excellent discrimination of patients with recurrent SNC according to prognosis.In the recurrent setting, achievement of local control is essential to provide the best chance of cure. In our series, the pattern of disease failure is dominated by further local relapses, representing the main cause of cancer‐related death. Survival estimates  are in line with the literatureA major open issue is the possibility to discriminate among patients who can benefit from intensified re‐treatments, and those who are likely to experience early failure and poor survival regardless of an aggressive therapeutic strategy. Kaplan et al. revised their series of 42 recurrent SNCs and proposed a therapeutic algorithm which included histology, site of recurrence, and tumor extension as key parameters.The score presented herein includes a wider set of prognosticators and provides a quantitative estimate of survival probability for the individual patient. Group A included subjects with excellent survival estimates, which was maintained even in the long term. Group B included patients with intermediate prognosis: the treatment strategy may still be curative, but the risk of failure in the long term is greater. Finally, in Group C survival estimates were comparable to those of metastatic head and neck cancers. In these cases, morbidity of treatment should be cautiously weighed against the limited chance of survival. Evaluation of patient age, performance status, and his/her compliance/motivation should play a pivotal role within a thorough multidisciplinary discussion involving, as much as possible, the patient and his/her caregiver(s).As for primary SNCs, even in the recurrent setting histology and tumor biology are critical and largely drive the prognosis despite any intensified treatment. In fact, in our series, aggressive histology  and PNI were major negative prognosticators irrespective of T classification, margin status, and adjuvant treatments.Surprisingly, DFI showed only a marginal influence on survival. Even in other smaller series, it did not reach statistical significance.Delivering adjuvant treatments was protective for further recurrence and improved survival. In addition to selecting radioresistant and dedifferentiated clones, primary CRT may also have a negative prognostic impact by limiting the use of adjuvant treatments in the recurrent setting, even when indicated. In fact, in our series, the use of adjuvant (C)RT after salvage surgery was relatively low (30%) compared to the high rate of negative major prognosticators , and re‐irradiation was proposed to only eight patients. These findings should prompt clinicians to carefully evaluate the overall therapeutic margin before treating recurrent SNCs, and possibly consider re‐RT more favorably in highly selected cases. In a recent series, re‐RT with stereotactic technique or protons showed promising results with acceptable toxicity and definitively warrants further investigation.Differently than expected, in our series the safety profile was deemed acceptable, with limited treatment‐related mortality, low complication rates, and short duration of hospitalization. Even in dead patients, hospitalization time was negligible (1.1%). Our findings are in line with those of Kaplan et al. which support a relatively low threshold to propose salvage surgery even in patients with comorbidities.Lastly, some limitations of the study should be outlined. First, the retrospective design implies all the classical bias related to data retrieval and lack of control on treatment decisions, although this is minimized by the monocentric nature of the series. Second, there is a risk of overfitting of the model, and external validation with possible refinements in the variables considered or their relative weight is mandatory. Third, we could not include parameters related to the performance and nutritional status of patients , as well as preoperative blood markers, because they could be retrieved only for a small proportion of the series. Finally, the score includes parameters that are available only at pathological report , which prevents its use in the therapeutic decision‐making process. However, pT classification can be allegedly predicted through adequate preoperative imaging; PNI may sometimes be inferred from the pathologic evaluation at first diagnosis, and the probability to achieve free margins may be anticipated based on tumor extension and the surgeon's evaluation.5Intensified treatment of recurrent SNCs can lead to prolonged survival, with OS estimates that are close to those of primary SNCs. Patient selection plays a crucial role, and herein we propose a prognostic score that is able to stratify those with excellent, intermediate, or extremely poor prognosis. The overall safety profile is satisfactory. Retreatment protocols are recommended in recurrent SNCs and should be thoroughly discussed in a multidisciplinary setting.The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.Appendix S1 Supporting Information.Click here for additional data file.