Gender differences in the relationship between loneliness and health-related behavioral risk factors among the Hakka elderly in Fujian, China

IntroductionTo explore gender differences in the relationship between loneliness and health-related behavioral risk factors (BRFs) among the Hakka elderly.MethodsLoneliness was measured by the UCLA Loneliness Scale Short-form (ULS-8). Seven BRFs were examined. Mann–Whitney U, Kruskal-Wallis, and post hoc tests were conducted to compare the differences in ULS-8 scores among the Hakka elderly with different BRFs. Generalized linear regression models were employed to examine the associations of specific BRF and its number with the ULS-8 scores among the Hakka elderly in male, female, and total samples.ResultsPhysical inactivity (B = 1.96, p < 0.001), insufficient leisure activities participation (B = 1.44, p < 0.001), unhealthy dietary behavior (B = 1.02, p < 0.001), and irregular sleep (B = 2.45, p < 0.001) were positively correlated with the ULS-8 scores, whereas drinking (B = −0.71, p < 0.01) was negatively associated with the ULS-8 scores in the total sample. In males, insufficient leisure activities participation (B = 2.35, p < 0.001), unhealthy dietary behavior (B = 1.39, p < 0.001), and irregular sleep (B = 2.07, p < 0.001) were positively associated with the ULS-8 scores. In females, physical inactivity (B = 2.69, p < 0.001) and irregular sleep (B = 2.91, p < 0.001) was positively correlated with the scores of ULS-8, while drinking (B = −0.98, p < 0.05) was negatively associated with the ULS-8 scores. More BRFs were significantly related to greater loneliness (p < 0.001).ConclusionThere are gender differences in the relationship between loneliness and BRFs among the Hakka elderly, and individuals with more BRFs were more likely to feel loneliness. Therefore, the co-occurrence of multiple BRFs requires more attention, and integrated behavioral intervention strategies should be adopted to reduce the loneliness of the elderly

Selective crystallisation of carbamazepine polymorphs on surfaces with differing properties

Surface-induced nucleation of carbamazepine (CBZ) in ethanol was investigated with different surface materials: glass, polytetrafluoroethylene (PTFE) and tin. The introduction of foreign surfaces with different areas and surface chemistries into the solution has an impact on the crystal morphology and polymorphic form (Form II or III). With an increase in supersaturation, a higher possibility of crystallisation of CBZ metastable Form II was observed, as expected. Increasing the number of inserts resulted in a direct increase in the surface area available for heterogeneous nucleation. The increase in surface area resulted in the greater possibility of obtaining the metastable Form II of CBZ. The stable Form III preferred to nucleate on tin rather than on glass and PTFE. The results indicate that the two different polymorphs of CBZ can be selectively crystallised out from solution with the aid of a foreign surface. The kinetic mechanism of heterogeneous nucleation of the different polymorphs induced by foreign surfaces was discussed. The potential applications will be used to control and design the crystallisation process

miR-590-3p protects against ischaemia/reperfusion injury in an oxygen-glucose deprivation and reoxygenation cellular model by regulating HMGB1/TLR4/MyD88/NF-κB signalling

miR-590-3p has been reported to be reduced in myocardial ischaemia-reperfusion (I/R) injury, but its specific role in cerebral I/R injury is still uncertain. Thus, we explored the function and mechanism of miR590-3p in cerebral I/R injury using a cellular model. miR-590-3p, high mobility group Box 1 (HMGB1), and signalling-related factor levels were assessed using qPCR or a western blot analysis. Cell apoptosis was measured by flow cytometry. Inflammatory factors were detected by ELISA. The target of miR-590-3p was confirmed by dual-luciferase reporter assay and western blot analysis. We found that miR-590-3p was decreased and HMGB1 was increased in the OGD/R model. Upregulation of miR-590-3p reduced cell apoptosis and inflammation in the OGD/R model, and the TLR4/MyD88/NF-κB signalling pathway was suppressed. However, inhibition of miR-590-3p showed the opposite effects. Moreover, HMGB1 was verified as a target gene of miR-590-3p. HMGB1 reversed the decrease in apoptosis and inflammation caused by overexpression of miR590-3p, and the TLR4/MyD88/NF-κB signalling pathway was activated. Our results suggest that miR-590-3p regulates the TLR4/MyD88/NF-κB pathway by interacting with HMGB1 to protect against OGD/R-induced I/R injury. Thus, miR-590-3p may serve as a potential therapeutic target in cerebral I/R repair

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

The ratios of branching fractions $\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu})$ and $\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu})$ are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb${ }^{-1}$ of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode $\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}$. The measured values are $\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024$ and $\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066$, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is $\rho=-0.43$. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

Estimating foliar anthocyanin content of purple corn via hyperspectral model

To date, the foliar anthocyanin content was either determined via the pH differential or HPLC methods, both of which are slow and destructive. Here, a hyperspectral model was established to estimate the foliar anthocyanin content of purple corn (Zea mays L. var. Jingzi No. 1). The reflectivity (P) of the foliar hyperspectral was inverted to 1/P, lg P, 1/lg P, urn:x-wiley:20487177:media:fsn3588:fsn3588-math-0001, urn:x-wiley:20487177:media:fsn3588:fsn3588-math-0002, urn:x-wiley:20487177:media:fsn3588:fsn3588-math-0003, and urn:x-wiley:20487177:media:fsn3588:fsn3588-math-0004. The correlation coefficient between these inversions and the foliar anthocyanin content was plotted against the hyperspectral wavelength. The wavelength of inversions around 650 nm was sensitive to the foliar anthocyanin content. The hyperspectral model was fitted via linear, polynomial, power, exponential, and logarithmic functions with the sensitive band as independent variable and the anthocyanin content as function. The hyperspectral model (y = 3,000,000,000 × W6854.5896) fitted via inversion of urn:x-wiley:20487177:media:fsn3588:fsn3588-math-0005 showed the highest determination coefficients (0.768) among all models. The hyperspectral model was well validated with a determination coefficient of 0.932 and an RMSE of 0.0065. Moreover, the accuracy and stability of the hyperspectral model were further enhanced with a determination coefficient of 0.954 and RMSE of 0.0047 when the anthocyanin content of the sample was below 20 mg/g. Hence, the hyperspectral model estimated the foliar anthocyanin content of purple corn quickly and nondestructively

Short-term prognostic models for severe acute kidney injury patients receiving prolonged intermittent renal replacement therapy based on machine learning

Abstract Background As an effective measurement for severe acute kidney injury (AKI), the prolonged intermittent renal replacement therapy (PIRRT) received attention. Also, machine learning has advanced and been applied to medicine. This study aimed to establish short-term prognosis prediction models for severe AKI patients who received PIRRT by machine learning. Methods The hospitalized AKI patients who received PIRRT were assigned to this retrospective case-control study. They were grouped based on survival situation and renal recovery status. To screen the correlation, Pearson’s correlation coefficient, partial ETA square, and chi-square test were applied, eight machine learning models were used for training. Results Among 493 subjects, the mortality rate was 51.93% and the kidney recovery rate was 30.43% at 30 days post-discharge, respectively. The indices related to survival were Sodium, Total protein, Lactate dehydrogenase (LDH), Phosphorus, Thrombin time, Liver cirrhosis, chronic kidney disease stage, number of vital organ injuries, and AKI stage, while Sodium, Total protein, LDH, Phosphorus, Thrombin time, Diabetes, peripherally inserted central catheter and AKI stage were selected to predict the 30-day renal recovery. Naive Bayes has a good performance in the prediction model for survival, Random Forest has a good performance in 30-day renal recovery prediction model, while for 90-day renal recovery prediction model, it’s K-Nearest Neighbor. Conclusions Machine learning can not only screen out indicators influencing prognosis of AKI patients receiving PIRRT, but also establish prediction models to optimize the risk assessment of these people. Moreover, attention should be paid to serum electrolytes to improve prognosis