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Tissue adhesives are promising alternatives to sutures and staples for joining tissues, sealing defects, and immobilizing devices. However, existing adhesives mostly take the forms of glues or hydrogels, which offer limited versatility. We report a direct-ink-write 3D printable tissue adhesive which can be used to fabricate bioadhesive patches and devices with programmable architectures, unlocking new potential for application-specific designs. The adhesive is conformable and stretchable, achieves robust adhesion with wet tissues within seconds, and exhibits favorable biocompatibility. In vivo rat trachea and colon defect models demonstrate the fluid-tight tissue sealing capability of the printed patches, which maintained adhesion over 4 weeks. Moreover, incorporation of a blood-repelling hydrophobic matrix enables the printed patches to seal actively bleeding tissues. Beyond wound closure, the 3D printable adhesive has broad applicability across various tissue-interfacing devices, highlighted through representative proof-of-concept designs. Together, this platform offers a promising strategy toward developing advanced tissue adhesive technologies. Tissue adhesives have received significant interest for their clinical utility but are typically incompatible with advanced manufacturing methods. Here, the authors introduce a 3D printable tissue adhesive for the fabrication of patches and devices for diverse biomedical applications.

Epoxidation of high-linolenic perilla oil was carried out in the presence of solid acidic ion-exchange resin at varying reaction temperatures for 8 h. A pseudo two-phase kinetic model that captures the differences in reactivity of double bonds at various positions in the fatty acid of a triglyceride molecule during both epoxy formation and cleavage was developed. The proposed model is based on the Langmuir-Hinshelwood-Hougen-Watson (L-H-H-W) postulates and considers the adsorption of formic acid on the catalyst as the rate-determining step. To estimate the kinetic rate constants of various reactions, genetic algorithm was used to fit experimentally obtained iodine and epoxy values of epoxidized perilla oil. A re-parametrized form of Arrhenius equation was used in the proposed model to facilitate the precise estimation of parameters with least computational effort. The obtainment of the least error between experimentally determined and theoretically predicted iodine and epoxy values indicates the robustness of the proposed model.

IntroductionRecurrent pulmonary exacerbations lead to progressive lung damage in cystic fibrosis (CF). Inhaled medications (mucoactive agents and antibiotics) help prevent exacerbations, but objectively measured adherence is low. We investigated whether a multi-component (complex) self-management intervention to support adherence would reduce exacerbation rates over 12 months.MethodsBetween October 2017 and May 2018, adults with CF (aged ≥16 years; 19 UK centres) were randomised to the intervention (data-logging nebulisers, a digital platform and behavioural change sessions with trained clinical interventionists) or usual care (data-logging nebulisers). Outcomes included pulmonary exacerbations (primary outcome), objectively measured adherence, body mass index (BMI), lung function (FEV1) and Cystic Fibrosis Questionnaire-Revised (CFQ-R). Analyses were by intent to treat over 12 months.ResultsAmong intervention (n=304) and usual care (n=303) participants (51% female, median age 31 years), 88% completed 12-month follow-up. Mean exacerbation rate was 1.63/year with intervention and 1.77/year with usual care (adjusted ratio 0.96; 95% CI 0.83 to 1.12; p=0.64). Adjusted mean differences (95% CI) were in favour of the intervention versus usual care for objectively measured adherence (9.5% (8.6% to 10.4%)) and BMI (0.3 (0.1 to 0.6) kg/m2), with no difference for %FEV1 (1.4 (−0.2 to 3.0)). Seven CFQ-R subscales showed no between-group difference, but treatment burden reduced for the intervention (3.9 (1.2 to 6.7) points). No intervention-related serious adverse events occurred.ConclusionsWhile pulmonary exacerbations and FEV1 did not show statistically significant differences, the intervention achieved higher objectively measured adherence versus usual care. The adherence difference might be inadequate to influence exacerbations, though higher BMI and lower perceived CF treatment burden were observed.

Shiferaw D, Faruqi S. Ther Clin Risk Manag. 2019;15:1029-1040.Following a review of our paper post-publication, wefound an error had been introduced during the typesettingprocess.On page 1029, the first sentence of the introduction sectionreads as \"Cystic fibrosis (CF) is a life-threatening geneticdisease that affects approximately ct 380,000 peopleworldwide.1\" This should read as \"Cystic fibrosis (CF) is alife-threatening genetic disease that affects approximately80,000 people worldwide.1\"Read the original article

A geometrical model generator for biological products is presented, which uses X-ray computed tomography images of quasi-axisymmetric biological products as input. It was tested with a dataset of 73 scanned Braeburn apples. For each sample, the generator constructed different cross sections. From these sections, contours were extracted and selected. The contours were expressed as a series of shape descriptors. For this purpose, elliptical Fourier descriptors were used. The obtained frequency distributions were transformed to standard normal distributions. On these transformed distributions, the covariance decomposition algorithm was applied. This algorithm generated new sets of descriptors, which opened up a large range of possibilities for generation of representative shape contours. After reverse transformation of the (generated) descriptor distributions, new contours were obtained from the new descriptors. These new contours were converted to 3D geometrical models of biological products by interpolation and revolving. By comparing the volumes of the generated models with those of the scanned fruit, it was shown that the resulting geometrical models have the same variability as the biological variability in the original dataset. This generator is a fast method, which requires minimal user intervention, and creates 3D models including the biological variability as observed in the scanned fruit. Because these 3D geometrical models are directly available as CAD models, they are useful for numerical modelling of transport phenomena in and around biological products.

Suicidal mortality is high in rural areas, and suicidal ideation, an early psychology of suicidal behavior, is particularly important for the early prevention and intervention of suicide. This study aimed to establish a nomogram model to predict high-risk groups among rural adolescents who might develop suicidal ideation. This study conducted a cross-sectional survey of 1900 rural secondary school students in Xuzhou, China. The samples were randomly divided into a training set (1330) and a validation set (570), and a nomogram prediction model was constructed using the potential predictors of suicidal ideation screened from the training set using Lasso-Logistic regression. The model was validated using ROC, calibration, and clinical decision curves. The reported rate of suicidal ideation among rural adolescents is 18.9%. Lasso-Logistic regression found that emotional abuse, emotional neglect, hostility, subjective sleep quality, daytime dysfunction, withdrawal/escape, and depression were significant risk factors for suicidal ideation. A nomogram was built using the above 7 predictors. The area under the ROC curve (AUC) of our predictive model was 0.821 in the training set and 0.765 in the validation set, with corrected C-indices of 0.817 and 0.764, respectively. Furthermore, the calibration curves demonstrated good alignment with the ideal line ( > 0.05), and the decision curve analysis results indicated positive clinical utility. The nomogram model constructed in this study may be an effective tool for predicting suicidal ideation in rural middle school students. It helps identify high-risk groups with suicidal ideation and provides more reliable information for the early prevention and intervention of suicide.

Shiferaw Alemu D, Desalegn Gudeta A, Tsega Ferede A,Woretaw Alemu H. Clin Optom (Auckl). 2016;8:85-91.On page 85, the correct article title should read as follows:Prevalence and degrees of myopia and hyperopia atUniversity of Gondar Hospital Tertiary Eye Care andTraining Center, Northwest Ethiopia. The correct affiliationname should read as follows:Department of Optometry, College of Medicine and HealthSciences, University of Gondar, Gondar, Ethiopia. Thecorrect correspondence details should read as follows:Correspondence: Destaye Shiferaw AlemuDepartment of Optometry, College of Medicine andHealth Sciences, University of Gondar, PO Box 196,Gondar, EthiopaTel +251 918 0322Email destayest@gmail.comRead the original article

Cystic fibrosis (CF) is a life-limiting autosomal recessive disease caused by dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR) ion channel. Management of CF has traditionally relied upon managing complications of CFTR protein dysfunction and this has led to a steady improvement in survival of CF patients. However, the landscape of CF care has changed substantially over the last decade with the discovery of CFTR modulators that aim to increase or potentially restore the function of the disease-causing CFTR protein. This narrative review summarizes the development of CFTR therapies so far with emphasis on tezacaftor/ivacaftor combination therapy. We have also summarized the Phase II results of triple combination therapy which promises an effective CFTR modulator therapy for more than 90% of CF patients.

Previous findings indicate that stress has a profound influence on suicide behavior, but the potential mediating and moderating mechanisms are unknown between uncertainty stress and suicide behavior. The present study, therefore, examined the relationship between uncertainty stress and suicide behavior, the mediating effect of depressive symptoms, and the moderating effect of family relationship in a sample of university students in China. 1828 university students were assessed anonymously by using the Uncertainty Stress Scale, Center for Epidemiologic Studies Depression Scale, Brief Suicidal Scale, and Family Relationship Scale between May to June in 2021. SPSS 26.0 was used for descriptive statistics and Spearman correlation analysis. PROCESS 3.5 was used to calculate the significance of the mediating and moderating effects of the variables. Moderated mediation model analyses showed that: (a) depressive symptoms partially mediated the link between uncertainty stress and suicide behavior (indirect effect = 0.14, 95%bootstrap CI = 0.10, 0.19). The indirect effect of the depressive symptoms accounted for 67.12% of the total variance in suicide behavior. (b) The indirect association between uncertainty stress and suicide behavior was moderated by family relationship. Specifically, the paths from uncertainty stress to depressive symptoms (interact effect = -0.06, <0.001) and depressive symptoms to suicide behavior (interact effect = -0.08, <0.01) were weakened in the context of higher family relationship. Depressive symptoms play a crucial role in bridging uncertainty stress and suicide behavior, while the family relationship can buffer the mediation impact of depressive symptoms. These findings significantly contribute to the prevention and intervention of suicide in Chinese university students.

The pandemic of coronavirus disease spreading is impacting mental health globally. Even though the pandemic is challenging for patients, the community, policymakers, as well as health organizations, and teams, the data on COVID-19 and its association with anxiety and coping mechanisms towards infection among community members are currently limited. Thus, the study is intended to assess COVID-19-related levels of anxiety and coping strategies among community members of Bale and East Bale Zones, Southeast Ethiopia. A community-based survey was carried out among 634 study participants of Bale and East Bale Zones from June 1 to 20, 2020. The level of anxiety was determined by using the 5-item Coronavirus Scale and the coping strategies were determined by using the 15-item Coping and Adaptation Processing Scale. Interviewer-administered questionnaires were used to collect the data. Bi-variable analysis and multiple logistic regression analysis were used to estimate the relationship among the variables. COVID-19-related dysfunctional level of anxiety was found 95 (16.58%). About 290 (50.6%) respondents were copied from anxiety that occurred as a result of COVID-19. Factors significantly associated with the dysfunctional level of anxiety related to COVID-19 were being an urban resident (AOR = 0.44, 95% CI: 0.23, 0.86), those who had no information from TV/radio (AOR=1.76, 95% CI: 1.09, 2.84), and walking a long distance more than 1 hour from the health institution (AOR=0.58, 95% CI: 0.34, 0.97). COVID-19-related dysfunctional levels of anxiety were 16.58% in the study community. Half of the community was coped with COVID-19-related anxiety. Being an urban resident and walking along distances more than 1 hour from the health facility were the factors that decreased the odds of having a dysfunctional anxiety, whereas respondents who had no information from TV/radio increased the odds of having a dysfunctional anxiety. Accordingly, focusing on these identified factors could improve a dysfunctional level of anxiety in the study community.