Vacancy Ordering in Ultrathin Copper Oxide Films on Cu(111).

Oxide thin films grown on metal surfaces have wide applications in catalysis and beyond owing to their unique surface structures compared to their bulk counterparts. Despite extensive studies, the atomic structures of copper surface oxides on Cu(111), commonly referred to as "44" and "29", have remained elusive. In this work, we demonstrated an approach for the structural determination of oxide surfaces using element-specific scanning tunneling microscopy (STM) imaging enhanced by functionalized tips. This approach enabled us to resolve the atomic structures of "44" and "29" surface oxides, which were further corroborated by noncontact atomic force microscopy (nc-AFM) measurements and Monte Carlo (MC) simulations. The stoichiometry of the "44" and "29" frameworks was identified as Cu23O16 and Cu16O11, respectively. Contrary to the conventional hypothesis, we observed ordered Cu vacancies within the "44" structure manifesting as peanut-shaped cavities in the hexagonal lattice. Similarly, a combination of Cu and O vacancies within the "29" structure leads to bean-shaped cavities within the pentagonal lattice. Our study has thus resolved the decades-long controversy on the atomic structures of "44" and "29" surface oxides, advancing our understanding of copper oxidation processes and introducing a robust framework for the analysis of complex oxide surfaces.

Non-line-of-sight optical wireless communication system enabled by wavefront shaping for multi-user indoor access.

In this Letter, we experimentally investigate a non-line-of-sight (NLOS) optical wireless communication (OWC) system that utilizes wavefront shaping techniques to realize simultaneous data transmission for multiple users. Wavefront shaping techniques are employed to address the issue of low intensity of diffusely reflected light at the receiver in NLOS scenarios for indoor high-speed access. To achieve communication path planning and tracing for two different users in free-space optical communication, the pixels of the spatial light modulator (SLM) are divided into two halves to separately manipulate the wavefront of two independent data carriers centered at different wavelengths. The maximum received optical power can be effectively improved by more than 15 dB with the wavefront shaping technique. To avoid power enhancement of non-target wavelength, the wavelength difference of two different users is experimentally studied. The difference in power enhancement ratio (DPER) is increased with the wavelength difference, and 14.95 dB DPER is obtained with a 10 nm wavelength difference. Under the aforementioned wavelength planning strategy, successful transmission and reception of 2 × 160 Gbit/s 16-QAM signals for two users with coherent detection is achieved using wavelengths of 1550 and 1560 nm in an indoor access scenario.

Transport Properties of Aqueous Methane Solutions and Blocking Behavior of Intelligent-Responsive Temporary Plugging Agent in a Switchable Nano-channel: A Dissipative Particle Dynamics Simulation Study.

Intelligent-responsive temporary plugging agents (TPAs) have great potential in the field of oil and gas resource extraction due to their self-adaptability to the environment. However, the transport mechanism of oil and gas molecules, such as aqueous methane solution in intelligent-responsive TPA-modified nano-channels and the blocking behavior of TPA, have not been verified yet. In this work, dissipative particle dynamics simulations (DPD) are conducted to investigate the velocity distribution and the force characteristics of aqueous methane solutions under different driving velocities, as well as the blocking effect of TPA to the flow of solution. Simulation results indicate that aqueous methane solution primarily concentrates in the uncovered area of the TPA and diffuses into the TPA-covered area when the nano-channel is closed. The velocity distribution of the flowing solution in the open nano-channel follows a subparabolic pattern. Methane molecules in the closed nano-channel show sharp oscillations in velocity and force profiles, which can be mitigated by increasing the methane concentration. The designed TPA effectively blocks fluid flow but its head and tail are vulnerable to the shear forces from the fluid. This study enhances the understanding of the nanoflows in the wellbores during the extraction of oil and natural gas resources.

Complex silica composite nanomaterials templated with DNA origami.

Genetically encoded protein scaffolds often serve as templates for the mineralization of biocomposite materials with complex yet highly controlled structural features that span from nanometres to the macroscopic scale1-4. Methods developed to mimic these fabrication capabilities can produce synthetic materials with well defined micro- and macro-sized features, but extending control to the nanoscale remains challenging5,6. DNA nanotechnology can deliver a wide range of customized nanoscale two- and three-dimensional assemblies with controlled sizes and shapes7-11. But although DNA has been used to modulate the morphology of inorganic materials12,13 and DNA nanostructures have served as moulds14,15 and templates16,17, it remains challenging to exploit the potential of DNA nanostructures fully because they require high-ionic-strength solutions to maintain their structure, and this in turn gives rise to surface charging that suppresses the material deposition. Here we report that the Stöber method, widely used for producing silica (silicon dioxide) nanostructures, can be adjusted to overcome this difficulty: when synthesis conditions are such that mineral precursor molecules do not deposit directly but first form clusters, DNA-silica hybrid materials that faithfully replicate the complex geometric information of a wide range of different DNA origami scaffolds are readily obtained. We illustrate this approach using frame-like, curved and porous DNA nanostructures, with one-, two- and three-dimensional complex hierarchical architectures that range in size from 10 to 1,000 nanometres. We also show that after coating with an amorphous silica layer, the thickness of which can be tuned by adjusting the growth time, hybrid structures can be up to ten times tougher than the DNA template while maintaining flexibility. These findings establish our approach as a general method for creating biomimetic silica nanostructures.

Profiling of the genetic features of Chinese patients with gastric cancer with HRD germline mutations in a large-scale retrospective study.

BACKGROUND: Approximately 10% of gastric cancers (GCs) are associated with strong familial clustering and can be attributed to genetic predisposition. Homologous recombination deficiency (HRD) leads to genomic instability and accumulation of genetic variations, playing an important role in the development and progression of cancer. We aimed to delineate the germline mutation characteristics of patients with HRD-mut GC in Chinese. METHODS: We retrospectively reviewed the genomic sequencing data of 1135 patients with Chinese GC. Patients harbouring at least one loss of function (LoF) germline mutations in BRCA1, BRCA2, ATM, PALB2, BRIP1, CHEK1, CHEK2, FANCA and FANCL were selected for analysis. RESULTS: 89 patients were identified with LoF germline mutations of HRD gene. Germline mutations occurred most commonly in ATM (30.33%), followed by BRIP1 (17.98%), BRCA2 (14.61%), BRCA1 (12.36%), FANCA (10.11%), PALB2 (10.11%), FANCL (6.74%), CHEK1 (3.37%) and CHEK2 (3.37%). 14 out of 89 patients with HRD-mut harboured double mutations in HRD and MMR genes, with the median age of 51.5 years. The decreasing median age would be attributed to five patients with HRD+MMR double-muts harbouring mutations in both HRD and MMR genes. The median age of onset of patients with HRD+MMR double-muts is 47, which is significantly earlier than that of Chinese patients with GC (p=0.0235). CONCLUSION: Our data suggest that carrying both HRD and MMR gene LoF germline mutations may cause early-onset GC. Germline mutations in the HRD gene should be of concern in the study of hereditary GC.

Disparity of serum uric acid threshold for CKD among hypertensive and non-hypertensive individuals.

INTRODUCTION: Hypertension and rising serum uric acid (sUA) played a pivotal role in the development of Chronic Kidney Disease (CKD). This study investigates the interactive effect of sUA and hypertension on CKD and identifies the optimal threshold of sUA among individuals with and without hypertension in the Chinese community population. MATERIALS AND METHODS: The study included 4180 individuals aged 45-85 years, derived from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2015. Additionally, a hospital-based study enrolled subjects in the Department of Nephrology at Zhongshan Hospital, China from January 1, 2019, to December 31, 2021. The interaction effect analysis were used to assess the impact of sUA and hypertension on CKD. We also compared the distribution of sUA and the CKD risk in community populations, distinguishing between those with and without hypertension. For the hospital-based population, kidney injury was marked by a KIM-1 positive area. RESULTS: Our results indicate a higher prevalence of CKD in the community population with hypertension (10.2% vs. 3.9%, p < .001). A significant additive synergistic effects of the sUA and hypertension on the CKD risk were found. When the sUA level was < 4.55 mg/dL in the hypertensive population and < 5.58 mg/dL in the non-hypertensive population, the risk of CKD was comparable (p = .809). In the propensity score matched (PSM) population, the result remained roughly constant. CONCLUSION: Therefore, even moderate levels of sUA was associated with a higher risk of CKD in middle-aged hypertensive patients, who warrant stricter sUA control.

Laser Direct Writing of Flexible Thermal Flow Sensors.

Thin film-based thermal flow sensors afford applications in healthcare and industries owing to their merits in preserving initial flow distributions. However, traditional thermal flow sensors are primarily applied to track flow intensities based on hot-wire or hot-film sensing mechanisms due to their relatively facile device configurations and fabrication strategies. Herein, a calorimetric thermal flow sensor is proposed based on laser direct writing to form laser-induced graphene as heaters and temperature sensors, resulting in monitoring both flow intensities and orientations. Via homogeneously surrounding spiral heaters with multiple temperature sensors, the device exhibits high sensitivity (∼162 K·s/m) at small flows with an extended flow detection range (∼25 m/s). Integrating the device with a data-acquisition board and a dual-mode graphical user interface enables wirelessly and dynamically monitoring respiration and the motion of robotic arms. This versatile flow sensor with facile manufacturing affords potentials in health inspection, remote monitoring, and studying hydrodynamics.

TREM2+ macrophages suppress CD8+ T-cell infiltration after transarterial chemoembolisation in hepatocellular carcinoma.

BACKGROUND & AIMS: The immune landscape of hepatocellular carcinoma (HCC) following transarterial chemoembolisation (TACE) remains to be clarified. This study aimed to characterise the immune landscape following TACE and the underlying mechanism of HCC progression. METHODS: Tumour samples from five patients with treatment-naive HCC and five patients who received TACE therapy were collected and subjected to single-cell RNA sequencing. Another 22 paired samples were validated using immunofluorescence staining and flow cytometry. To clarify the underlying mechanisms, in vitro co-culture experiments and two types of TREM2-KO/WT mouse models, namely, an HCC cell orthotopic injection model and a spontaneous HCC model, were used. RESULTS: A reduced number of CD8+ T cells and an increased number of tumour-associated macrophages (TAMs) were observed in the post-TACE microenvironment. TACE therapy reduced the cluster CD8_C4, which was highly enriched with tumour-specific CD8+ T cells of pre-exhausted phenotype. TREM2 was found to be highly expressed in TAMs following TACE, which was associated with a poor prognosis. TREM2+ TAMs secreted less CXCL9 but more galectin-1 than did TREM2- TAMs. Galectin-1 promoted PD-L1 overexpression in vessel endothelial cells, impeding CD8+ T cell recruitment. TREM2 deficiency also increased CD8+ T cell infiltration, which inhibited tumour growth in both in vivo HCC models. More importantly, TREM2 deficiency enhanced the therapeutic effect of anti-PD-L1 blockade. CONCLUSIONS: This study shows that TREM2+ TAMs play an important role in suppressing CD8+ T cells. TREM2 deficiency increased the therapeutic effect of anti-PD-L1 blockade by enhancing antitumour activity of CD8+ T cells. These findings explain the reasons for recurrence and progression after TACE and provide a new target for HCC immunotherapy after TACE. IMPACT AND IMPLICATIONS: Studying the immune landscape in post-TACE HCC is important to uncover the mechanisms of HCC progression. By using scRNA sequencing and functional assays, we discovered that both the number and function of CD8+ T cells are compromised, whereas the number of TREM2+ TAMs is increased in post-TACE HCC, correlating with worse prognosis. Moreover, TREM2 deficiency dramatically increases CD8+ T cell infiltration and augments the therapeutic efficacy of anti-PD-L1 blockade. Mechanistically, TREM2+ TAMs display lower CXCL9 and increased Gal-1 secretion than do TREM2- TAMs, with Gal-1 mediating the overexpression of PD-L1 in vessel endothelial cells. These results suggest that TREM2 could be a novel immunotherapeutic target for patients treated with TACE in HCC. This provides an opportunity to break the plateau of limited therapeutic effect. This study has the value of understanding the tumour microenvironment of post-TACE HCC and thinking a new strategy of immunotherapy in the field of HCC. It is therefore of key impact for physicians, scientists and drug developers in the field of liver cancer and gastrointestinal oncology.

SNR-enhanced signal delivery scheme with delta-sigma modulation in a four-mode fiber system.

This Letter proposes a scheme for optimizing the signal-to-noise ratio (SNR) of signal to improve the system performance by a 1 bit delta-sigma modulation (DSM) in a four-mode MDM system for mobile fronthaul. A 1 bit digitalized signal with an SNR of 60 dB from transmitter digital signal processing (Tx DSP) can be achieved. Based on this system, an experimental demonstration of the ultrahigh-order 1048576-QAM signal transmission over a 50 km strong-coupling few-mode fiber (FMF) is successfully realized. With DSP, the bit error rate (BER) of the received 1048576-QAM signals over four modes transmission is below the 20% soft-decision forward error correction (20% SD-FEC) threshold of 2.4 × 10-2. To the best of our knowledge, this is the first time that the combination of DSM technology and strong-coupling MDM system is achieved and that the highest-modulation order with DSM reported in MDM system is reached. This experimental demonstration of the proposed novel scheme in MDM system can provide an effective solution for ultra-large-capacity mobile fronthaul in the future.

Identifying optimal candidates for post-TIPS patients with HCC undergoing TACE: a multicenter observational study.

OBJECTIVE: To develop a prognostic model for post-transjugular intrahepatic portosystemic shunt (TIPS) patients with hepatocellular carcinoma (HCC) beyond the Milan criteria treated by transarterial chemoembolization (TACE). DESIGN: Between January 2013 and January 2020, 512 patients with HCC beyond the Milan criteria who underwent TACE after TIPS were retrospectively recruited from 15 tertiary centers. Patients were randomly sorted into a training set (n = 382) and a validation set (n = 130). Medical data and overall survival were assessed. A prediction model was developed using multivariate Cox regression analyses. Predictive performance and discrimination were evaluated and compared with other prognostic models. RESULTS: Vascular invasion, log10(AFP), 1/creatinine, extrahepatic spread, and log10(ALT) were the most significant prognostic factors of survival. These five parameters were included in a new VACEA score. This score was able to stratify patients in the training set into four distinct risk grades whose median overall survival were 25.2, 15.1, 8.9, and 6.2 months, respectively. The 6-month, 1-year, 2-year, and 3-year AUROC values and C-index of the VACEA model were 0.819, 0.806, 0.779, 0.825, and 0.735, respectively, and higher than those of other seven currently available models in both the training and validation sets, as well as in different subgroups. CONCLUSION: The VACEA score could stratify post-TIPS patients with HCC beyond the Milan criteria treated by TACE and help to identify candidates who benefit from this treatment. KEY POINTS: • Vascular invasion, AFP, creatinine, extrahepatic spread, and ALT were independent significant prognostic factors of survival for HCC patients who underwent TACE after TIPS. • Our new model, named VACEA score, can accurately predict prognosis at the individual level and stratify patients into four distinct risk grades. • The VACEA model showed better prognostic discrimination and calibration than other current TACE-/TIPS-specific models Graphical abstract.

Reaction-induced iodine adsorption on Cu surfaces facilitates electrocatalytic CO2 reduction.

The electrolyte effect has been key to the electrochemical CO2 reduction reaction (CO2RR) and has received extensive attention in recent years. Here we combined atomic force microscopy, quasi-in situ X-ray photoelectron spectroscopy, and in situ attenuated total reflection surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) to study the effect of iodine anions on Cu-catalyzed CO2RR in the absence or presence of KI in the KHCO3 solution. Our results suggested that iodine adsorption caused coarsening of the Cu surface and altered its intrinsic activity for CO2RR. As the potential of the Cu catalyst became more negative, there was an increase in surface iodine anion concentration ([I-]), which could be connected to the reaction-enhanced adsorption of I- ions accompanying the increase in CO2RR activity. A linear relationship was observed between [I-] and current density. SEIRAS results further suggested that the presence of KI in the electrolyte strengthened the Cu-CO bond and facilitated the hydrogenation process, enhancing the production of CH4. Our results have thus provided insight into the role of halogen anions and aided in the design of an efficient CO2RR process.

Urinary N-Acetyl-Beta-D-Glucosaminidase levels predict immunoglobulin a nephropathy remission status.

BACKGROUND: Tubulointerstitial lesions play a pivotal role in the progression of IgA nephropathy (IgAN). Elevated N-acetyl-beta-D-glucosaminidase (NAG) in urine is released from damaged proximal tubular epithelial cells (PTEC) and may serve as a biomarker of renal progression in diseases with tubulointerstitial involvement. METHODS: We evaluated the predictive value of urinary NAG (uNAG) for disease progression in 213 biopsy-proven primary IgAN patients from January 2018 to December 2019 at Zhongshan Hospital, Fudan University. We compared the results with those of serum cystatin C (sCysC). RESULTS: Increased uNAG and sCysC levels were associated with worse clinical and histological manifestations. Only uNAG level was independently associated with remission status after adjustment. Patients with high uNAG levels (> 22.32 U/g Cr) had a 4.32-fold greater risk of disease progression. The combination of baseline uNAG and clinical data may achieve satisfactory risk prediction in IgAN patients with relatively preserved renal function (eGFR ≥ 60 ml/min/1.73 m2, area under the curve [AUC] 0.760). CONCLUSION: Our results suggest that uNAG is a promising biomarker for predicting IgAN remission status.

Risk factor mining and prediction of urine protein progression in chronic kidney disease: a machine learning- based study.

BACKGROUND: Chronic kidney disease (CKD) is a global public health concern. Therefore, to provide timely intervention for non-hospitalized high-risk patients and rationally allocate limited clinical resources is important to mine the key factors when designing a CKD prediction model. METHODS: This study included data from 1,358 patients with CKD pathologically confirmed during the period from December 2017 to September 2020 at Zhongshan Hospital. A CKD prediction interpretation framework based on machine learning was proposed. From among 100 variables, 17 were selected for the model construction through a recursive feature elimination with logistic regression feature screening. Several machine learning classifiers, including extreme gradient boosting, gaussian-based naive bayes, a neural network, ridge regression, and linear model logistic regression (LR), were trained, and an ensemble model was developed to predict 24-hour urine protein. The detailed relationship between the risk of CKD progression and these predictors was determined using a global interpretation. A patient-specific analysis was conducted using a local interpretation. RESULTS: The results showed that LR achieved the best performance, with an area under the curve (AUC) of 0.850 in a single machine learning model. The ensemble model constructed using the voting integration method further improved the AUC to 0.856. The major predictors of moderate-to-severe severity included lower levels of 25-OH-vitamin, albumin, transferrin in males, and higher levels of cystatin C. CONCLUSIONS: Compared with the clinical single kidney function evaluation indicators (eGFR, Scr), the machine learning model proposed in this study improved the prediction accuracy of CKD progression by 17.6% and 24.6%, respectively, and the AUC was improved by 0.250 and 0.236, respectively. Our framework can achieve a good predictive interpretation and provide effective clinical decision support.

Inorganic-Organic Hybrid Phototransistor Array with Enhanced Photogating Effect for Dynamic Near-Infrared Light Sensing and Image Preprocessing.

Narrow-band-gap organic semiconductors have emerged as appealing near-infrared (NIR) sensing materials by virtue of their unique optoelectronic properties. However, their limited carrier mobility impedes the implementation of large-area, dynamic NIR sensor arrays. In this work, high-performance inorganic-organic hybrid phototransistor arrays are achieved for NIR sensing, by taking advantage of the high electron mobility of In2O3 and the strong NIR absorption of a BTPV-4F:PTB7-Th bulk heterojunction (BHJ) with an enhanced photogating effect. As a result, the hybrid phototransistors reach a high responsivity of 1393.0 A W-1, a high specific detectivity of 4.8 × 1012 jones, and a fast response of 0.72 ms to NIR light (900 nm). Meanwhile, an integrated 16 × 16 phototransistor array with a one-transistor-one-phototransistor (1T1PT) architecture is achieved. On the basis of the enhanced photogating effect, the phototransistor array can not only achieve real-time, dynamic NIR light mapping but also implement image preprocessing, which is promising for advanced NIR image sensors.

Toward the efficient direct regeneration of spent cathode materials through the effect of residual sodium ions analysis.

Recycling spent lithium-ion batteries is an important means for promoting sustainability within the energy industry. In this study, the effects of residual sodium on the regeneration process and the performance of spent LiNi0.5Co0.2Mn0.3O2 were explored. An appropriate amount of residual sodium was found to improve the properties of the regenerated material, with the best cycle performance and rate performance at a residual sodium of 3 mol %. The first-cycle and 100-cycle discharge capacities were 136.4 mA h g-1 and 120 mA h g-1, respectively, with a capacity retention rate of 87.98% after 100 cycles at a rate of 1 C. The electrochemical performance of the regenerated cathode materials was improved because sodium occupied the lithium sites in the crystal structure, providing a channel for lithium deintercalation. These results indicate that the residual sodium ions should be monitored in appropriate quantities to improve the efficiency of recycling spent lithium-ion batteries.

Highly Linear and Symmetric Synaptic Memtransistors Based on Polarization Switching in Two-Dimensional Ferroelectric Semiconductors.

Brain-inspired neuromorphic computing hardware based on artificial synapses offers efficient solutions to perform computational tasks. However, the nonlinearity and asymmetry of synaptic weight updates in reported artificial synapses have impeded achieving high accuracy in neural networks. Here, this work develops a synaptic memtransistor based on polarization switching in a two-dimensional (2D) ferroelectric semiconductor (FES) of α-In2 Se3 for neuromorphic computing. The α-In2 Se3 memtransistor exhibits outstanding synaptic characteristics, including near-ideal linearity and symmetry and a large number of programmable conductance states, by taking the advantages of both memtransistor configuration and electrically configurable polarization states in the FES channel. As a result, the α-In2 Se3 memtransistor-type synapse reaches high accuracy of 97.76% for digit patterns recognition task in simulated artificial neural networks. This work opens new opportunities for using multiterminal FES memtransistors in advanced neuromorphic electronics.

Bio-Inspired In-Sensor Compression and Computing Based on Phototransistors.

The biological nervous system possesses a powerful information processing capability, and only needs a partial signal stimulation to perceive the entire signal. Likewise, the hardware implementation of an information processing system with similar capabilities is of great significance, for reducing the dimensions of data from sensors and improving the processing efficiency. Here, it is reported that indium-gallium-zinc-oxide thin film phototransistors exhibit the optoelectronic switching and light-tunable synaptic characteristics for in-sensor compression and computing. Phototransistor arrays can compress the signal while sensing, to realize in-sensor compression. Additionally, a reservoir computing network can also be implemented via phototransistors for in-sensor computing. By integrating these two systems, a neuromorphic system for high-efficiency in-sensor compression and computing is demonstrated. The results reveal that even for cases where the signal is compressed by 50%, the recognition accuracy of reconstructed signal still reaches ≈96%. The work paves the way for efficient information processing of human-computer interactions and the Internet of Things.

Wireless transmission of a 200-m PS-64QAM THz-wave signal using a likelihood-based selection radius-directed equalizer.

Based on a photonics-aided scheme, we achieve an experimental demonstration of a, to the best of our knowledge, record-breaking 200-m terahertz (THz)-wave wireless delivery at 335 GHz with the aid of a pair of high-gain polytetrafluoroethylene (PTFE) lenses. By using a 10-GBaud probabilistically shaped 64-ary quadrature amplitude modulation (PS-64QAM) signal and advanced digital signal processing (DSP) including a likelihood-based selection radius-directed equalizer (LBS-RDE), the single-carrier net bit rate of the wireless delivery reaches 44 Gbit/s. High-speed THz-wave communication with up to 200-m wireless distance is successfully realized based on a photonics-aided scheme for the first time.

Alcohol consumption and its association with chronic kidney disease: Evidence from a 12-year China health and Nutrition Survey.

BACKGROUND AND AIMS: Alcohol consumption is a major threat to global health. The aim of the present study was to explore the association between alcohol consumption and chronic kidney disease (CKD) in a Chinese population. METHODS AND RESULTS: A total of 4664 participants, aged ≥18 years, who participated in a baseline alcohol survey in 1997 and were followed up in 2009 of the China Health and Nutrition Survey (CHNS), were recruited in the current study. Data on alcohol consumption was obtained using standardized questionnaires, with CKD (defined as eGFR <60 mL/min/1.73 m2) as the outcome. The results showed that 37.3% of the participants had consumed alcohol at the baseline. Current drinkers were mainly men, with at least senior high school education, and a history of smoking. In the 2009 survey, 14.5% of the participants had CKD. Association analyses revealed that alcohol drinkers had a lower likelihood of CKD than non-drinkers (11.0% vs. 16.6%, aOR: 0.76, 95%CI: 0.58-1.00), after adjusting potential covariates. Restricted cubic splines revealed that the relationship between alcohol consumption and CKD prevalence was U-shaped. The probability of CKD significantly increased when alcohol consumption exceeded 18 standard drinks per week (aOR: 1.66, 95%CI: 1.00-2.76). Approximately one-fourth of participants changed their drinking patterns during the 12-year follow-up, and male drinkers with persistent drinking patterns had the lowest prevalence of CKD (aOR: 0.48, 95% CI: 0.31-0.73). CONCLUSION: Alcohol consumption showed a U-shaped association with CKD. Moderate drinkers exhibited a lower disease prevalence compared with non-drinkers and heavy drinkers. Further studies should be conducted to explore the mechanisms underlying this protective effect. However, non-drinkers should not start drinking alcohol even with this protective effect.

Long-term drinking behavior change patterns and its association with hyperuricemia in chinese adults: evidence from China Health and Nutrition Survey.

BACKGROUND: We aimed to explore the association between long-term drinking behavior change patterns with hyperuricemia (HUA) in Chinese community adults. METHODS: This study was designed as a community-based unbalanced cohort study involving 4127 adults aged between 18 ~ 75 years, derived from the China Health and Nutrition Survey (CHNS) in 1997 and 2009. Drinking behavior change patterns were categorized into: never drinking, change to drinking, quitting drinking, and continued drinking. The alcoholism, type, and frequency of drinking were further categorized. We applied logistic regression models to explore the associations between drinking behavior change patterns and HUA. RESULTS: The average age of the participants was 54.6 (± 11.3) years and 47.8% were male. The overall prevalence of HUA was 15.5%. Drinking behavior change patterns of quitting (aOR 1.8; 95% CI 1.1 ~ 2.8) and continued drinking (aOR 2.0; 95% CI 1.3 ~ 3.0) were positively associated with high risks of HUA in the male participants. Early drinking behaviors such as liquor intake (aOR 1.8; 95% CI 1.4 ~ 2.5) and high consumption or frequency showed a positive correlation with HUA. Of note, heavy alcoholism (aOR 2.0; 95% CI 1.4 ~ 2.8) and daily drinking (aOR 2.5; 95% CI 1.7 ~ 3.6) had the highest risks of HUA. Furthermore, in the male participants, the association between early total alcohol intake and HUA was more pronounced at 18 standard drinks intake, with a stable increasing trend. In contrast, no statistical correlation was observed between the drinking behaviors and HUA in the female participants. CONCLUSIONS: Drinking behavior change patterns of quitting and continued drinking are strongly associated with increased risks of HUA in males. The risks emanated from early drinking behaviors such as liquor drinking, high drinking frequency, and alcohol consumption. Although quitting drinking was associated with lower HUA risks compared to continued drinking, it still presented an undeniable risk for HUA.