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Objective: To investigate the risk factors for the development of mild cognitive dysfunction in hypertensive patients in the community and to develop a risk prediction model. Method: The data used in this study were obtained from two sources: the China Health and Retirement Longitudinal Study (CHARLS) and the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 1121 participants from CHARLS were randomly allocated into a training set and a validation set, following a 70:30 ratio. Meanwhile, an additional 4016 participants from CLHLS were employed for external validation of the model. The patients in this study were divided into two groups: those with mild cognitive impairment and those without. General information, employment status, pension, health insurance, and presence of depressive symptoms were compared between the two groups. LASSO regression analysis was employed to identify the most predictive variables for the model, utilizing 14-fold cross-validation. The risk prediction model for cognitive impairment in hypertensive populations was developed using generalized linear models. The model's discriminatory power was evaluated through the area under the receiver operating characteristic (ROC) curve and calibration curves. Results: In the modeling group, eight variables such as gender, age, residence, education, alcohol use, depression, employment status, and health insurance were ultimately selected from an initial pool of 21 potential predictors to construct the risk prediction model. The area under the curve (AUC) values for the training, internal, and external validation sets were 0.777, 0.785, and 0.782, respectively. All exceeded the threshold of 0.7, suggesting that the model effectively predicts the incidence of mild cognitive dysfunction in community-based hypertensive patients. A risk prediction model was developed using a generalized linear model in conjunction with Lasso regression. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve. Hosmer-Lemeshow test values yielded p = .346 and p = .626, both of which exceeded the 0.05 threshold. Calibration curves demonstrated a significant agreement between the nomogram model and observed outcomes, serving as an effective tool for evaluating the model's predictive performance. Discussion: The predictive model developed in this study serves as a promising and efficient tool for evaluating cognitive impairment in hypertensive patients, aiding community healthcare workers in identifying at-risk populations.
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Magnetic impurities in superconductors are of increasing interest due to emergent Yu-Shiba-Rusinov (YSR) states and Majorana zero modes for fault-tolerant quantum computation. However, a direct relationship between the YSR multiple states and magnetic anisotropy splitting of quantum impurity spins remains poorly characterized. By using scanning tunneling microscopy, we systematically resolve individual transition-metal (Fe, Cr, and Ni) impurities induced YSR multiplets as well as their Zeeman effects in the K3C60 superconductor. The YSR multiplets show identical d orbital-like wave functions that are symmetry-mismatched to the threefold K3C60(1 1 1) host surface, breaking point-group symmetries of the spatial distribution of YSR bound states in real space. Remarkably, we identify an unprecedented fermion-parity-preserving quantum phase transition between ground states with opposite signs of the uniaxial magnetic anisotropy that can be manipulated by an external magnetic field. These findings can be readily understood in terms of anisotropy splitting of quantum impurity spins, and thus elucidate the intricate interplay between the magnetic anisotropy and YSR multiplets.
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The current strategies for building 2D organic-inorganic heterojunctions involve mostly wet-chemistry processes or exfoliation and transfer, leading to interface contaminations, poor crystallizing, or limited size. Here we show a bottom-up procedure to fabricate 2D large-scale heterostructure with clean interface and highly-crystalline sheets. As a prototypical example, a well-ordered hydrogen-bonded organic framework is self-assembled on the highly-oriented-pyrolytic-graphite substrate. The organic framework adopts a honeycomb lattice with faulted/unfaulted halves in a unit cell, resemble to molecular "graphene". Interestingly, the topmost layer of substrate is self-lifted by organic framework via strong interlayer coupling, to form effectively a floating organic framework/graphene heterostructure. The individual layer of heterostructure inherits its intrinsic property, exhibiting distinct Dirac bands of graphene and narrow bands of organic framework. Our results demonstrate a promising approach to fabricate 2D organic-inorganic heterostructure with large-scale uniformity and highly-crystalline via the self-lifting effect, which is generally applicable to most of van der Waals materials.
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Two-dimensional topological insulators hosting the quantum spin Hall effect have application potential in dissipationless electronics. To observe the quantum spin Hall effect at elevated temperatures, a wide band gap is indispensable to efficiently suppress bulk conduction. Yet, most candidate materials exhibit narrow or even negative band gaps. Here, via elegant control of van der Waals epitaxy, we have successfully grown monolayer ZrTe5 on a bilayer graphene/SiC substrate. The epitaxial ZrTe5 monolayer crystalizes in two allotrope isomers with different intralayer alignments of ZrTe3 prisms. Our scanning tunneling microscopy/spectroscopy characterization unveils an intrinsic full band gap as large as 254 meV and one-dimensional edge states localized along the periphery of the ZrTe5 monolayer. First-principles calculations further confirm that the large band gap originates from strong spin-orbit coupling, and the edge states are topologically nontrivial. These findings thus provide a highly desirable material platform for the exploration of the high-temperature quantum spin Hall effect.
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OBJECTIVE: To systematically evaluate obesity on the outcome of rotator cuff repair. METHODS: Literatures on the relationship between obesity and outcomes after rotator cuff repair were searched from PubMed, Embase, Cochrane Library, Web of Science, China biology medicine(CBM), CNKI, Wanfang and VIP databases from building database to August 1, 2022, and were screened independently by two authors according to inclusion and exclusion criteria. Endnote X9 and Excel 2019 were used for literature extraction, management and data entry, and Newcastle-Ottawa Scale (NOS) was used to evaluate quality of the included literatures. STATA 16.0 and RevMan 5.4 softwares were used to evaluate postoperative retear rate, reoperation rate, complication rate, American Shoulder and Elbow Surgeons (ASES) score, visual analogue scale (VAS), operative time and external rotation angle of shoulder joint pain were analyzed. RESULTS: Totally 13 literatures were included, including 6 retrospective studies, 5 case-control studies, 1 prospective cohort study, and 1 abstract of a study for which the full text was not available, with 85 503 patients (31 973 in obese group and 53 530 in non-obese group). Meta-analysis showed there were statistical differences between two groups in retear rate [OR=2.58, 95%CI(1.23, 5.41), P=0.01], reoperation rate[OR=1.31, 95%CI(1.21, 1.42), P<0.00], complication rate [OR=1.57, 95%CI(1.31, 1.87), P=0.00], ASES score[MD=-3.59, 95%CI(-5.45, -1.74), P=0.00], and VAS[MD=0.24, 95%CI(0.00, 0.49), P=0.05]. While there were no differences between two groups in operative time[MD=6.03, 95%CI(-7.63, 19.69), P=0.39], external rotation angle of shoulder joint[MD=-1.79, 95%CI(-5.30, 1.71), P=0.32]. CONCLUSION: Obesity is associated with higher rates of retear, resurgery, complications, poorer shoulder function and pain after rotator cuff repair.