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Background: Approximately two-thirds of diabetes patients develop multimorbidity, which is associated with increased mortality. We aimed to examine whether, and to what extent, the time interval between pre-existing diabetes and a second chronic disease may be associated with the risk of mortality. Methods: We carried out a territory-wide nested case-control study using incidence density sampling, utilizing electronic health records from Hong Kong’s public healthcare facilities. Among 158 732 patients first diagnosed with diabetes from January 1, 2010 to December 31, 2012 and subsequently developed multimorbidity as of December 31, 2019, we extracted those who died before December 31, 2019 as case participants. For each participant, we randomly matched with up to 4 people of the same sex, multimorbidity age, and second chronic condition who had not died after going through the same survival period of the case participant. Multimorbidity interval was included as a continuous variable. We used conditional logistic regression to estimate adjusted odds ratios (aOR) for mortality. Results: In total, 3508 case participants were matched with 14 032 control participants. Conditional logistic regression showed there were 19%-reduced odds of mortality following the extension of multimorbidity interval by 1 year. Similar associations were observed in men, women, people aged 64 years or younger, and older people aged 65 years or more. Conclusions: Delayed multimorbidity among patients living with diabetes may be related to a lower risk of mortality. This study suggests that we should focus on mitigating and lowering the risk of multimorbidity in clinical management of diabetes to reduce further complication and mortality.

Cuspidevia Jäch & Boukal, 1995 is a member of the tribe Macronychini which has the following features: antennae short, 6-10 segmented, aedeagus long and cylindrical, paramere very small, slender or lacking. This genus currently comprises only three species. All species are distributed in China.Cuspidevia pilosus sp. nov. is reported from Guangdong, Guangxi and Jiangxi Provinces in China. Habitus and diagnostic features of the new species are illustrated.

Abstract Autistic Children often struggle with social interaction and communication, studies have found that many of them prefer to interact with objects than people. However, there is a lack of research exploring the specific characteristics and factors involved in interactions within families with autistic children where objects are the center of the interaction. This paper describes the process and findings of a diary study exploring how young autistic children interact with their families through objects in natural scenarios. A one-week diary study was conducted with six families with young autistic children. Diary videos were recorded onsite and coded later according to a social interaction behavior scheme with corresponding diary entries. Qualitative data analysis was conducted to reveal possible patterns. Results revealed ongoing difficulties in establishing and maintaining family interaction and identified influential factors of object-centered family interaction. The most prevalent pattern observed was parents taking the lead in interactions, followed by the child's confirmation response. Remarkably, daily necessities emerged as potential physical mediums for enhancing family interactions, opening avenues for exploring tangible designs in human–computer interaction. These findings offer valuable implications for future research and the development of innovative designs that promote enriching interactions for autistic children and their families.

Objectives Older individuals with multimorbidity are at an elevated risk of infection and complications from COVID-19. Effectiveness of post-COVID-19 interventions or care models in reducing subsequent adverse outcomes in these individuals have rarely been examined. This study aims to examine the effectiveness of attending general outpatient within 30 days after discharge from COVID-19 on 1-year survival among older adults aged 85 years or above with multimorbidity.Design Retrospective cohort study emulating a randomised target trial using electronic health records.Setting We used data from the Hospital Authority and the Department of Health in Hong Kong, which provided comprehensive electronic health records, COVID-19 confirmed case data, population-based vaccination records and other individual characteristics for the study.Participants Adults aged 85 years or above with multimorbidity who were discharged after hospitalisation for COVID-19 between January 2020 and August 2022.Interventions Attending a general outpatient within 30 days of last COVID-19 discharge defined the exposure, compared to no outpatient visit.Main outcome measures Primary outcome was all-cause mortality within one year. Secondary outcomes included mortality from respiratory, cardiovascular and cancer causes.Results A total of 6183 eligible COVID-19 survivors were included in the analysis. The all-cause mortality rate following COVID-19 hospitalisation was lower in the general outpatient visit group (17.1 deaths per 100 person-year) compared with non-visit group (42.8 deaths per 100 person-year). After adjustment, primary care consultations within 30 days after discharge were associated with a significantly greater 1-year survival (difference in 1-year survival: 11.2%, 95% CI 8.1% to 14.4%). We also observed significantly better survival from respiratory diseases in the general outpatient visit group (difference in 1-year survival: 6.3%, 95% CI 3.5% to 8.9%). In a sensitivity analysis for different grace period lengths, we found that the earlier participants had a general outpatient visit after COVID-19 discharge, the better the survival.Conclusions Timely primary care consultations after COVID-19 hospitalisation may improve survival following COVID-19 hospitalisation among older adults aged 85 or above with multimorbidity. Expanding primary care services and implementing follow-up mechanisms are crucial to support this vulnerable population’s recovery and well-being.

ObjectiveThis study aims to determine whether the live birth rates were similar between GnRH antagonist original reference product Cetrotide® and generic Ferpront®, in gonadotropin-releasing hormone (GnRH) antagonist protocol for controlled ovarian stimulation (COS).MethodsThis retrospective cohort study investigates COS cycles utilizing GnRH antagonist protocols. The research was conducted at a specialized reproductive medicine center within a tertiary care hospital, spanning the period from October 2019 to October 2021. Within this timeframe, a total of 924 cycles were administered utilizing the GnRH antagonist originator, Cetrotide® (Group A), whereas 1984 cycles were undertaken using the generic, Ferpront® (Group B).ResultsOvarian reserve markers, including anti-Mullerian hormone, antral follicle number, and basal follicular stimulating hormone, were lower in Group A compared to Group B. Propensity score matching (PSM) was performed to balance these markers between the groups. After PSM, baseline clinical features were similar, except for a slightly longer infertile duration in Group A versus Group B (4.43 ± 2.92 years vs. 4.14 ± 2.84 years, P = 0.029). The duration of GnRH antagonist usage was slightly longer in Group B than in Group A (6.02 ± 1.41 vs. 5.71 ± 1.48 days, P < 0.001). Group B had a slightly lower number of retrieved oocytes compared to Group A (14.17 ± 7.30 vs. 14.96 ± 7.75, P = 0.024). However, comparable numbers of usable embryos on day 3 and good-quality embryos were found between the groups. Reproductive outcomes, including biochemical pregnancy loss, clinical pregnancy, miscarriage, and live birth rate, did not differ significantly between the groups. Multivariate logistic regression analyses suggested that the type of GnRH antagonist did not independently impact the number of oocytes retrieved, usable embryos, good-quality embryos, moderate to severe OHSS rate, clinical pregnancy, miscarriage, or live birth rate.ConclusionThe retrospective analysis revealed no clinically significant differences in reproductive outcomes between Cetrotide® and Ferpront® when used in women undergoing their first and second COS cycles utilizing the GnRH antagonist protocol.

Objectives Analyzing the lower limb coronal morphological parameters in populations without knee osteoarthritis (KOA) holds significant value in predicting, diagnosing, and formulating surgical strategies for KOA. This study aimed to comprehensively analyze the variability in these parameters among Chinese non‐KOA populations, employing a substantial sample size. Methods A cross‐sectional retrospective analysis was performed on the Chinese non‐KOA populations (n = 407; 49.9% females). The study employed an in‐house developed artificial intelligence software to meticulously assess the coronal morphological parameters of all 814 lower limbs. The parameters evaluated included the hip‐knee‐ankle angle (HKAA), weight‐bearing line ratio (WBLR), joint line convergence angle (JLCA), mechanical lateral‐proximal‐femoral angle (mLPFA), mechanical lateral‐distal‐femoral angle (mLDFA), mechanical medial‐proximal‐tibial angle (mMPTA), and mechanical lateral‐distal‐tibial angle (mLDTA). Differences in these parameters were compared between left and right limbs, different genders, and different age groups (with 50 years as the cut‐off point). Results HKAA and JLCA exhibited left–right differences (left vs. right: 178.2° ± 3.0° vs. 178.6° ± 2.9° for HKAA, p = 0.001; and 1.8° ± 1.5° vs. 1.4° ± 1.6° for JLCA, p

Abstract Background Preclinical evidence suggests that certain antipsychotic medications may inhibit the development of lung cancer. This study aims to investigate the association between incident lung cancer and different cumulative exposure periods of flupentixol or any antipsychotics. Methods Using electronic health records from the Hospital Authority in Hong Kong, this nested case-control study included case participants aged 18 years or older with newly diagnosed lung cancer after initiating antipsychotics between January 1, 2003, and August 31, 2022. Each case was matched to up to ten controls of the same sex and age, who were also antipsychotic users. Multivariable conditional logistic regression models were conducted to quantify the association between lung cancer and different cumulative exposure times of flupentixol (0–365 days [ref]; 366–1825 days; 1826+ days) and any antipsychotics (1–365 days [ref]; 366–1825 days; 1826+ days), separately. Results Here we show that among 6435 cases and 64,348 matched controls, 64.06% are males, and 52.98% are aged 65–84 years. Compared to patients with less than 365 days of exposure, those with 366–1825 days of exposure to flupentixol (OR = 0.65 [95% CI, 0.47–0.91]) and any antipsychotics (0.42 [0.38–0.45]) have a lower risk of lung cancer. A decreased risk is observed in patients who have 1826+ days of cumulative use of any antipsychotics (0.54 [0.47–0.60]). Conclusions A reduced risk of lung cancer is observed in patients with more than one year of exposure to flupentixol or any antipsychotics. Further research on the association between lung cancer and other antipsychotic agents is warranted.

Abstract Ultrafast physical random bit (PRB) generators and integrated schemes have proven to be valuable in a broad range of scientific and technological applications. In this study, we experimentally demonstrated a PRB scheme with a chaotic microcomb using a chip-scale integrated resonator. A microcomb contained hundreds of chaotic channels, and each comb tooth functioned as an entropy source for the PRB. First, a 12 Gbits/s PRB signal was obtained for each tooth channel with proper post-processing and passed the NIST Special Publication 800-22 statistical tests. The chaotic microcomb covered a wavelength range from 1430 to 1675 nm with a free spectral range (FSR) of 100 GHz. Consequently, the combined random bit sequence could achieve an ultra-high rate of about 4 Tbits/s (12 Gbits/s × 294 = 3.528 Tbits/s), with 294 teeth in the experimental microcomb. Additionally, denser microcombs were experimentally realized using an integrated resonator with 33.6 GHz FSR. A total of 805 chaotic comb teeth were observed and covered the wavelength range from 1430 to 1670 nm. In each tooth channel, 12 Gbits/s random sequences was generated, which passed the NIST test. Consequently, the total rate of the PRB was approximately 10 Tbits/s (12 Gbits/s × 805 = 9.66 Tbits/s). These results could offer potential chip solutions of Pbits/s PRB with the features of low cost and a high degree of parallelism. Graphical Abstract

Photonic convolution processing units are the core components of photonic neural networks (PNNs). Traditionally, for an N × N photonic convolution processing unit, it typically requires O(N2) or O(Nlog2N) cascaded photonic devices, which leads to larger sizes and lower density. Therefore, nanophotonic neural networks (N-PNN) with high density are highly attractive. In this work, we propose an ultra-high density and nonvolatile N-PNN scheme, requiring only a compact photonic device to represent all weight values in the N × N convolution kernel, which results in a computational density of more than 5 petaflop operations per second per square millimeter (POPS/mm2) under ideal conditions. The footprints of the proposed 2 × 2 and 3 × 3 nanophotonic convolution processing units are only 4 × 4 μm2 and 6 × 6 μm2, respectively. Moreover, based on these two types of units, the N-PNN achieves image classification and recognition capabilities comparable to traditional computers. In addition, Owing to its lower insertion loss, our approach holds great significance for the scalability and on-chip integration of large-scale N-PNNs. This facilitated the integration of N-PNNs with existing electronic systems.

Abstract Network slicing and mobile edge computing are key technologies in 5G/6G networks. Stable allocation of slicing resources is a challenge while communication and computation offloading coexist. To meet the service requirements of communication and computation offloading, a radio access network model which consists of enhanced mobile broadband (eMBB) slicing users, ultra‐reliable low latency communication (URLLC) slicing users, base stations integrated with MEC servers, and fog nodes with computing power are proposed. By employing the Lyapunov optimisation technique, a slicing resource allocation algorithm is proposed to maintain the queue stability and minimise the energy consumption of the system. For eMBB and URLLC slices, long time interval and short time interval resource allocation algorithms are proposed respectively. Simulation results show that the proposed algorithm can guarantee the long‐term stability of the network system while ensuring the service requirements.

The on-chip nano-integration of large-scale optical phased arrays (OPAs) is a development trend. However, the current scale of integrated OPAs is not large because of the limitations imposed by the lateral dimensions of beam-splitting structures. Here, we propose an ultra-compact and broadband OPA beam-splitting scheme with a nano-inverse design. We employed a staged design to obtain a T-branch with a wavelength bandwidth of 500 nm (1300–1800 nm) and an insertion loss of −0.2 dB. Owing to the high scalability and width-preserving characteristics, the cascaded T-branch configuration can significantly reduce the lateral dimensions of an OPA, offering a potential solution for the on-chip integration of a large-scale OPA. Based on three-dimensional finite-difference time-domain (3D FDTD) simulations, we demonstrated a 1 × 16 OPA beam-splitter structure composed entirely of inverse-designed elements with a lateral dimension of only 27.3 μm. Additionally, based on the constructed grating couplers, we simulated the range of the diffraction angle θ for the OPA, which varied by 0.6°–41.6° within the wavelength range of 1370–1600 nm.

BackgroundBenign uretero-ileal anastomotic stricture (UIAS) is a major complication following radical cystectomy (RC) and ileal orthotopic bladder substitution, and it can occur in combination with other complications. But risk factors for patients with UIAS have not been well described.Material and methodsWe retrospectively reviewed 198 patients treated with RC for bladder cancer from 2014 to 2019 at the Zhejiang Provincial People’s Hospital. Patient demographic and clinical variables were examined to determine the risk factors associated with UIAS by univariate and multivariate logistic regression analysis.ResultsA total of 180 patients into the group standards and in all 360 uretero-ileal anastomoses. Among the above cases, 22 patients developed UIAS, including 10 cases of left UIAS, nine cases of right UIAS, and three cases of bilateral UIAS. There was no difference in demographic, operative, or perioperative variables between patients with and without UIAS. In a multivariate analysis, after adjusting for gender, age, surgical methods, and underlying diseases, intraoperative or postoperative blood transfusion (HR = 0.144, P

With the rapid development of China’s new energy vehicle industry, the supply security of lithium resources is crucial. To ensure the healthy development of the new energy vehicle industry and the security of supply of key mineral resources, it is necessary to accurately determine the supply and demand pressure of lithium resources and their sources. This study analyzes the lithium stock and flow at the end of the new energy vehicle chain by constructing a material flow analysis framework for the new energy vehicle industry and compiling a lithium resource flow table for the new energy vehicle industry, and the results show that 1) the supply and demand pressure on lithium resources in China is increasing year by year, and the external dependence of lithium resources has reached 75% in 2019; 2) China’s domestic lithium battery production and consumption accounted for nearly 70% of the lithium consumption in various industries, of which 60% of the lithium batteries were assembled on new energy vehicles, and the net outflow of lithium exceeded more than the lithium consumption of new energy vehicles in 2019. The lithium consumption of new energy vehicles was more than five times that of the previous year. Insufficient supply of domestic lithium ore, lithium inventory, and import and export are the key reasons for the pressure on lithium supply and demand in the new energy vehicle industry; 3) By the end of 2019, the cumulative scrap lithium batteries in new energy vehicles contain about 10,000 tons. The lithium accumulated in new energy vehicles has 26,500 tons. These results provide a theoretical basis for policy recommendations to ensure the healthy development of the new energy vehicle industry and to promote international cooperation in the development, utilization, and recycling of lithium resources.

Photonic logic gates have important applications in fast data processing and optical communication. This study aims to design a series of ultra-compact non-volatile and reprogrammable photonic logic gates based on the Sb2Se3 phase-change material. A direct binary search algorithm was adopted for the design, and four types of photonic logic gates (OR, NOT, AND, and XOR) are created using silicon-on-insulator technology. The proposed structures had very small sizes of 2.4 μm × 2.4 μm. Three-dimensional finite-difference time-domain simulation results show that, in the C-band near 1550 nm, the OR, NOT, AND, and XOR gates exhibit good logical contrast of 7.64, 6.1, 3.3, and 18.92 dB, respectively. This series of photonic logic gates can be applied in optoelectronic fusion chip solutions and 6G communication systems.

In recent years, the occurrence of rice pests has been increasing, which has greatly affected the yield of rice in many parts of the world. The prevention and cure of rice pests is urgent. Aiming at the problems of the small appearance difference and large size change of various pests, a deep neural network named YOLO-GBS is proposed in this paper for detecting and classifying pests from digital images. Based on YOLOv5s, one more detection head is added to expand the detection scale range, the global context (GC) attention mechanism is integrated to find targets in complex backgrounds, PANet is replaced by BiFPN network to improve the feature fusion effect, and Swin Transformer is introduced to take full advantage of the self-attention mechanism of global contextual information. Results from experiments on our insect dataset containing Crambidae, Noctuidae, Ephydridae, and Delphacidae showed that the average mAP of the proposed model is up to 79.8%, which is 5.4% higher than that of YOLOv5s, and the detection effect of various complex scenes is significantly improved. In addition, the paper analyzes and discusses the generalization ability of YOLO-GBS model on a larger-scale pest data set. This research provides a more accurate and efficient intelligent detection method for rice pests and others crop pests.

The present study explores the perceptions of elementary and intermediate learners toward English as a code-switching medium in Chinese as a Foreign Language (CFL) classrooms. The data were collected by means of a survey of international elementary and intermediate-level students studying Chinese at the College of Chinese Language and Culture (CCLC) of Jinan University in Guangzhou, China. The data collection method included a five-point Likert scale questionnaire survey (18 closed-ended questions and one open-ended question). The analysis of quantitative and qualitative data collected from the questionnaire showed that CFL learners at both proficiency levels tended to favor code-switching in classrooms. However, the results of the Mann–Whitney U test showed that intermediate learners favored code-switching to a lesser extent than elementary learners. Moreover, their perceptions were found to differ significantly in terms of the varying functions of code-switching. These findings suggest that code-switching functions as an effective teaching strategy in the CFL classrooms, although teachers should regulate its deployment when teaching learners with different proficiency levels.

High-intensity ultrasound was introduced for the casting of 2195 aluminum–lithium alloy ingots. The shape of the ingots was a cylinder with a length of 650 mm and a radius of 30 mm. In this study, the effects of different ultrasonic powers were applied in the melt. The grain shape, α-Al grain size, the size of the precipitated phase, and the mechanical properties of the ingots were compared. The results showed that when the power of the ultrasonic system was maintained at 1,600 W, an ingot with a more uniformly dispersed precipitation phase and grain refinement structure was formed. It can be concluded that the coarse eutectic structure in the ingot is effectively reduced when the power is around 1,600 W, and the mechanical properties of the ingot reach the best value.

Considering the complementarity between the deep learning,spectrum and time frequency analysis methods,a multi-stream framework was designed by combining the convolutional network,Fourier transform and wavelet package decomposition methods,with the aim to analyze the non-stationary signal.Accordingly,a none-stationary signal combined analysis based fault diagnosis method was proposed to extract features in difference aspects.The fault diagnosis experiments demonstrate that the combined analysis method can efficiently and stably depict the fault and significantly improve the performance of fault diagnosis.

Citrus Huanglongbing (HLB), also named citrus greening disease, occurs worldwide and is known as a citrus cancer without an effective treatment. The symptoms of HLB are similar to those of nutritional deficiency or other disease. The methods based on single-source information, such as RGB images or hyperspectral data, are not able to achieve great detection performance. In this study, a multi-modal feature fusion network, combining a RGB image network and hyperspectral band extraction network, was proposed to recognize HLB from four categories (HLB, suspected HLB, Zn-deficient, and healthy). Three contributions including a dimension-reduction scheme for hyperspectral data based on a soft attention mechanism, a feature fusion proposal based on a bilinear fusion method, and auxiliary classifiers to extract more useful information are introduced in this manuscript. The multi-modal feature fusion network can effectively classify the above four types of citrus leaves and is better than single-modal classifiers. In experiments, the highest accuracy of multi-modal network recognition was 97.89% when the amount of data was not very abundant (1,325 images of the four aforementioned types and 1,325 pieces of hyperspectral data), while the single-modal network with RGB images only achieved 87.98% recognition and the single-modal network using hyperspectral information only 89%. Results show that the proposed multi-modal network implementing the concept of multi-source information fusion provides a better way to detect citrus HLB and citrus deficiency.

Dehydrogenation of the 2195 Al–Li alloy was accomplished using argon degassing, ultrasonic degassing, and vacuum degassing. The concentration of hydrogen, its microstructure, and its mechanical characteristics were all investigated. The hydrogen content in the 2195 Al–Li alloy is high. The degassing process significantly improved the mechanical properties of the cast alloy, owing the removal of hydrogen. Among the three degassing techniques, ultrasonic argon treatment was an efficient dehydrogenation approach and an effective procedure for enhancing the microstructure while minimizing lithium loss in the Al–Li alloy. On the one hand, ultrasonic waves can dissolve purged argon bubbles, allowing them to degas more efficiently. On the other hand, ultrasonic waves may cause a large number of cavitation bubbles to form in the melt, which should be the cause of the microstructure refinement. The dynamics of rising argon bubbles and ultrasonic effects are involved in ultrasonic argon treatments such as cavitation and flow.

The microstructural refinement of 2195 aluminum alloy ingots is particularly important for improving their industrial applications and mechanical properties. Combined with vacuum casting and inert gas protection, scalable high-strength ultrasonic melt processing (USMT) technology was used to manufacture 2195 aluminum alloy cylindrical ingots. Then, the influence of USMT on the main microstructural components (primary α-Al grains, secondary phase network, and precipitated particles) was studied. Our experiments show that the main microstructure of the ingot was improved after the introduction of ultrasound. Compared to the ingot formed without USMT, the size and morphology of the primary α-Al phase were optimized. The agglomeration of coarsening secondary phases can be alleviated, and the large layered secondary phase network becomes discontinuous throughout the ingot under USMT. At the same time, the mechanical properties of the solidified aluminum alloy ingots were also tested, and comparisons were made between samples formed with and without USMT. The results show that the stress concentration caused by the large area of coarse secondary phase in the ingot leads to the decrease of mechanical properties.

ABSTRACT Intestinal bacterial dysbiosis has been increasingly linked to ankylosing spondylitis (AS), which is a prototypic and best studied subtype of spondyloarthritis (SpA). Fungi and bacteria coexist in the human gut and interact with each other. Although they have been shown to contribute actively to health or disease, no studies have investigated whether the fungal microbiota in AS patients is perturbed. In this study, fecal samples from 22 AS patients, with clinical and radiographic assessments, and 16 healthy controls (HCs) were collected to systematically characterize the gut microbiota and mycobiota in AS patients by 16S rRNA gene- and ITS2-based DNA sequencing. Our results showed that the microbiota of AS patients was characterized by increased abundance of Proteobacteria and decreased Bacteroidetes, which was contributed by enrichment of Escherichia-Shigella, Veillonella, Lachnospiraceae NK4A136 group, and reduction of Prevotella strain 9, Megamona, and Fusobacterium. The gut mycobiota of AS patients was characterized by higher levels of Ascomycota, especially the class of Dothideomycetes, and decreased abundance of Basidiomycota, which was mainly contributed by the decease of Agaricales. Compared to HCs, decreased ITS2/16S biodiversity ratios and altered bacterial-fungal interkingdom networks were observed in AS patients. Compared with nonsteroidal anti-inflammatory drugs (NSAIDs), treating AS patients with biological agents induced obvious changes in the gut mycobiota, and this result was highly associated with disease activity indexes, including AS disease activity index (ASDAS) C-reactive protein (asCRP), erythrocyte sedimentation rate (ESR), and Bath AS disease activity index (BASDAI). In addition, altered mycobiota in AS patients was also found associated with the degree of radiographic damage. IMPORTANCE The human gut is colonized by diverse fungi (mycobiota), and fungi have long been suspected in the pathogenesis of SpA. Our study unraveled a disease-specific interkingdom network alteration in AS, suggesting that fungi, or the interkingdom interactions between bacteria and fungi, may play an essential role in AS development. However, our study is limited by sample size, and in-depth mechanism studies and additional large-scale investigations characterizing the gut mycobiome in AS patients are needed to form a foundation for research into the relationship between mycobiota dysbiosis and AS development.

ABSTRACT The milk glycobiome has a significant impact on the gut microbiota of infants, which plays a pivotal role in health and development. Fucosylated human milk oligosaccharides (HMOs) and N-glycans on milk proteins are beneficial for the development of healthy gut microbiota, and the fucosylation levels of these glycans can be affected by the maternal fucosyltransferase 2 gene (FUT2). Here, we present results of longitudinal research on paired milk and stool samples from 56 Chinese mothers (CMs) and their breast-fed children. Changes of HMOs and fucosylated N-glycans in milk of CMs at different lactation stages were detected, which allowed characterization of the major differences in milk glycans and consequential effects on the gut microbiome of infants according to maternal FUT2 status. Significant differences in the abundance of total and fucosylated HMOs between secretor and nonsecretor CMs were noted, especially during early lactation. Despite a tendency toward decreasing milk protein concentrations, the fucosylation levels of milk N-glycans increased during late lactation. The changes in the levels of fucosylated HMOs and milk N-glycans were highly correlated with the growth of Bifidobacterium spp. and Lactobacillus spp. in the gut of infants during early and later lactation, respectively. Enriched expression of genes encoding glycoside hydrolases, glycosyl transferases, ATP-binding cassette (ABC) transporters, and permeases in infants fed by secretor CMs contributed to the promotion of these bacteria in infants. Our data highlight the important role of fucosylated milk glycans in shaping the gut microbiome of infants and provide a solid foundation for development of “personalized” nutrition for Chinese infants. IMPORTANCE Human milk glycans provide a broad range of carbon sources for gut microbes in infants. Levels of protein glycosylation in human milk vary during lactation and may also be affected by the stages of gestation and lactation and by the secretor status of the mother. This was the first study to evaluate systematically dynamic changes in human milk oligosaccharides and fucosylated N-glycans in the milk of Chinese mothers with different secretor statuses during 6 months of lactation. Given the unique single nucleotide polymorphism site (rs1047781, A385T) on the fucosyltransferase 2 gene among Chinese populations, our report provides a specific insight into the milk glycobiome of Chinese mothers, which may exert effects on the gut microbiota of infants that differ from findings from other study cohorts.

Objectives Older individuals with multimorbidity are at an elevated risk of infection and complications from COVID-19. Effectiveness of post-COVID-19 interventions or care models in reducing subsequent adverse outcomes in these individuals have rarely been examined. This study aims to examine the effectiveness of attending general outpatient within 30 days after discharge from COVID-19 on 1-year survival among older adults aged 85 years or above with multimorbidity. Design Retrospective cohort study emulating a randomised target trial using electronic health records. Setting We used data from the Hospital Authority and the Department of Health in Hong Kong, which provided comprehensive electronic health records, COVID-19 confirmed case data, population-based vaccination records and other individual characteristics for the study. Participants Adults aged 85 years or above with multimorbidity who were discharged after hospitalisation for COVID-19 between January 2020 and August 2022. Interventions Attending a general outpatient within 30 days of last COVID-19 discharge defined the exposure, compared to no outpatient visit. Main outcome measures Primary outcome was allcause mortality within one year. Secondary outcomes included mortality from respiratory, cardiovascular and cancer causes. Results A total of 6183 eligible COVID-19 survivors were included in the analysis. The all-cause mortality rate following COVID-19 hospitalisation was lower in the general outpatient visit group (17.1 deaths per 100 person-year) compared with non-visit group (42.8 deaths per 100 person-year). After adjustment, primary care consultations within 30 days after discharge were associated with a significantly greater 1-year survival (difference in 1-year survival: 11.2%, 95%CI 8.1% to 14.4%). We also observed significantly better survival from respiratory diseases in the general outpatient visit group (difference in 1-year survival: 6.3%, 95%CI 3.5% to 8.9%). In a sensitivity analysis for different grace period lengths, we found that the earlier participants had a general outpatient visit after COVID-19 discharge, the better the survival. Conclusions Timely primary care consultations after COVID-19 hospitalisation may improve survival following COVID-19 hospitalisation among older adults aged 85 or above with multimorbidity. Expanding primary care services and implementing follow-up mechanisms are crucial to support this vulnerable population’s recovery and well-being. [ABSTRACT FROM AUTHOR]

The constructs of lipid molecules follow self-assembly, driven by intermolecular interactions, forming stacking of lipid bilayer films. Achieving designed geometry at nano- to micro-levels with packing deviating from the near-equilibrium structure is difficult to achieve due to the strong tendency of lipid molecules to self-assemble. Using ultrasmall (sn-glycero-3-phosphocholine (POPC). Taking advantage of the high spatial precision and the minute size of the delivery probe in our combined atomic force microscopy and microfluidic delivery, the transient shape of each liquid droplet is regulated. In doing so, the final geometry of the POPC assemblies has been regulated to the designed geometry with nanometer precision. The results extend the concept of controlled assembly of molecules to amphiphilic systems. The outcomes exhibit high potential in lipid-based biomaterial science and biodevice engineering.