Prediction of Cognitive Progression Due to Alzheimer's Disease in Normal Subjects Based on Individual Default Mode Network Metabolic Connectivity Strength.

BACKGROUND: Predicting cognitive decline in those already Aß positive or Tau positive among the aging population poses clinical challenges. In Alzheimer's disease (AD) research, intra-default mode network (DMN) connections play a pivotal role in diagnosis. This paper proposes metabolic connectivity within the DMN as a supplementary biomarker to the AT(N) framework. METHODS: Extracting data from 1292 subjects in the Alzheimer's Disease Neuroimaging Initiative, we collected paired T1-weighted structural MRI and 18F-labeled-fluorodeoxyglucose positron emission computed tomography (PET) scans. Individual metabolic DMN networks were constructed, and metabolic connectivity (MC) strength in DMN was assessed. In the cognitively unimpaired (CU) group, the Cox model identified CU(MC+), high-risk subjects, with Kaplan-Meier survival analyses and hazard ratio (HR) revealing MC strength's predictive performance. Spearman correlation analyses explored relationships between MC strength, AT(N) biomarkers, and clinical scales. DMN standard uptake value ratio (SUVR) provided comparative insights in the analyses. RESULTS: Both MC strength and SUVR exhibit gradual declines with cognitive deterioration, displaying significant intergroup differences. Survival analyses indicate enhanced Aß and Tau prediction with both metrics, with MC strength outperforming SUVR. Combined MC strength and Aß yield optimal predictive performance (HR = 9.29), followed by MC strength and Tau (HR = 8.92). In CU(MC+), MC strength correlates significantly with CSF Aß42 and AV45 PET SUVR (r = 0.22, -0.19). Generally, MC strength's correlation with AT(N) biomarkers exceeded SUVR. CONCLUSIONS: Individuals with normal cognition and disrupted DMN metabolic connectivity face an elevated cognitive decline risk linked to Aß, preceding metabolic issues.

Novel non-invasive method for urine mapping: Deep-learning-enabled SERS spectroscopy for the rapid differential detection of kidney allograft injury.

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual decline in function, chronic fibrosis, and allograft loss. It is vital to routinely and precisely monitor the risk of injuries after renal transplantation, which is difficult to achieve because the traditional laboratory tests lack sensitivity and specificity, and graft biopsies are invasive with the risk of many complications and time-consuming. Herein, a novel method for the diagnosis of graft injury is demonstrated, using deep learning-assisted surface-enhanced Raman spectroscopy (SERS) of the urine analysis. Specifically, we developed a hybrid SERS substrate composed of gold and silver with high sensitivity to the urine composition under test, eliminating the need for labels, which makes measurements easy to perform and meanwhile results in extremely abundant and complex Raman vibrational bands. Deep learning algorithms were then developed to improve the interpretation of the SERS spectral fingerprints. The deep learning model was trained with SERS signals of urine samples of recipients with different injury types including delayed graft function (DGF), calcineurin-inhibitor toxicity (CNIT), T cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), and BK virus nephropathy (BKVN), which explored the features of these types and achieved the injury differentiation with an overall accuracy of 93.03%. The results highlight the potential of combining label-free SERS spectroscopy with deep learning as a method for liquid biopsy of kidney allograft injuries, which can provide great potential to diagnose and evaluate allograft injuries, and thus extend the life of kidney allografts.

Crystalline nanoxylan from hot water extracted wood xylan at multi-length scale: Molecular assembly from nanocluster hydrocolloids to submicron spheroids.

As a contribution to expand accessibility in the territory of bio-based nanomaterials, we demonstrate a novel material strategy to convert amorphous xylan preserved in wood biomass to hierarchical assemblies of crystalline nanoxylan on a multi-length scale. By reducing the end group in pressurized hot water extracted (PHWE) xylan to primary alcohol as a xylitol form with borohydride reduction, the endwise-peeling depolymerization is effectively impeded in the alkali-catalyzed hydrolytic cleavage of side substitutions in xylan. Nanoprecipitation by a gradual pH decrease resulted in a stable hydrocolloid dispersion in the form of worm-like nanoclusters assembled with primary crystallites, owing to the self-assembly of debranched xylan driven by strong intra- and inter-chain H-bonds. With evaporation-induced self-assembly, we can further construct the hydrocolloids as dry submicron spheroids of crystalline nanoxylan (CNX) with a high average elastic modulus of 47-83 GPa. Taking the advantage that the chain length and homogeneity of PHWE-xylan can be tailored, a structure-performance correlation was established between the structural order in CNX and the phosphorescent emission of this crystalline biopolymer. Rigid clusterization and high crystallinity that are constructed by strong intra- and inter-molecule interactions within the nanoxylan effectively restrict the molecular motion, thereby promoting the emission of ultralong organic phosphorescence.

FGF4 protects the liver from immune-mediated injury by activating CaMKKß-PINK1 signal pathway to inhibit hepatocellular apoptosis.

Immune-mediated liver injury (ILI) is a condition where an aberrant immune response due to various triggers causes the destruction of hepatocytes. Fibroblast growth factor 4 (FGF4) was recently identified as a hepatoprotective cytokine; however, its role in ILI remains unclear. In patients with autoimmune hepatitis (type of ILI) and mouse models of concanavalin A (ConA)- or S-100-induced ILI, we observed a biphasic pattern in hepatic FGF4 expression, characterized by an initial increase followed by a return to basal levels. Hepatic FGF4 deficiency activated the mitochondria-associated intrinsic apoptotic pathway, aggravating hepatocellular apoptosis. This led to intrahepatic immune hyper-reactivity, inflammation accentuation, and subsequent liver injury in both ILI models. Conversely, administration of recombinant FGF4 reduced hepatocellular apoptosis and rectified immune imbalance, thereby mitigating liver damage. The beneficial effects of FGF4 were mediated by hepatocellular FGF receptor 4, which activated the Ca2+/calmodulin-dependent protein kinasekinase 2 (CaMKKß) and its downstream phosphatase and tensin homologue-induced putative kinase 1 (PINK1)-dependent B-cell lymphoma 2-like protein 1-isoform L (Bcl-XL) signalling axis in the mitochondria. Hence, FGF4 serves as an early response factor and plays a protective role against ILI, suggesting a therapeutic potential of FGF4 and its analogue for treating clinical immune disorder-related liver injuries.

Innovations in functional genomics and molecular breeding of pea: exploring advances and opportunities.

The garden pea (Pisum sativum L.) is a significant cool-season legume, serving as crucial food sources, animal feed, and industrial raw materials. The advancement of functional genomics over the past two decades has provided substantial theoretical foundations and progress to pea breeding. Notably, the release of the pea reference genome has enhanced our understanding of plant architecture, symbiotic nitrogen fixation (SNF), flowering time, floral organ development, seed development, and stress resistance. However, a considerable gap remains between pea functional genomics and molecular breeding. This review summarizes the current advancements in pea functional genomics and breeding while highlighting the future challenges in pea molecular breeding.

Study of spatiotemporal evolution of coupled airflow-gas-dust multi-field diffusion at low-gas tunnel.

The increasing level of mechanization in coal mining means more dust and gas are generated during excavation operations in tunnels. The high concentrations of dust and gas severely affect production efficiency and the physical and mental health of workers. Here, Ansys Fluent simulations were performed to derive the spatiotemporal evolution of coupled airflow-dust-gas diffusion in a low-gas excavation face. The aim was to optimize pollution control by determining the optimal duct distance, L, from the working face in the excavation tunnel. Our results showed that the airflow field affects the coupled diffusion and transport of dust and gas. According to a comparison of the effects of different duct distances from the working face, when L = 6 m, the average dust concentration in the tunnel is low (257.6 mg/m3), and the average gas concentration in the tunnel is 0.28 %, which does not exceed the safety limit. Accordingly, the optimal distance of the duct for pollution control is 6 m. The results of field measurements supported the validity of the simulation. Our findings can be used to improve the air quality in tunnels, thereby keeping miners safe and the working area clean.

Central precocious puberty secondary to postoperative craniopharyngioma: two case reports and a literature review.

BACKGROUND: Craniopharyngioma is a common intracranial tumour in children. Clinical manifestations are related to hypothalamic/pituitary deficiencies, visual impairment, and increased intracranial pressure. Defects in pituitary function cause shortages of growth hormone, gonadotropin, corticotropin, thyrotropin, and vasopressin, resulting in short stature, delayed puberty, feebleness, lethargy, polyuria, etc. However, manifestations involving precocious puberty (PP) are rare. CASE REPORT: In both patients, surgical resection was performed after the diagnosis of craniopharyngioma, and breast development occurred postoperatively at one month in one patient and at one year and three months in the other patient. Central precocious puberty (CPP) was diagnosed via relevant examinations. Leuprorelin was injected subcutaneously every 28 days, and changes in height, weight, bone age, gonadal ultrasound and sex hormones were recorded. During the follow-up of the two children, the sex hormone levels were significantly reduced, and significant acceleration in bone age was not observed. CONCLUSIONS: CPP was induced by craniopharyngioma surgery, and treatment with gonadotropin-releasing hormone analogues (GnRHa) inhibited sexual development and bone age progression. More attention should be given to monitoring for CPP during long-term follow-up of craniopharyngiomas in the clinic.

Chromosome balanced translocation in newborn fetus founded during prenatal diagnosis: Three cases reports.

RATIONALE: Because of the normal phenotype, carriers of specific chromosomal translocations are often diagnosed only after their development of associated malignancies, recurrent miscarriages, and reproductive difficulties. In this paper, we report primary balanced fetal chromosomal translocations by performing the necessary invasive prenatal diagnosis in couples with previous malformations coupled with prenatal testing suggesting a high risk for trisomy 21. PATIENT CONCERNS: Case 1 and Case 2 couples had malformed children, and Case 3 couples had a high risk of trisomy 21 on noninvasive preconception serological testing. DIAGNOSIS AND INTERVENTION: A balanced chromosomal translocation diagnosis was confirmed by karyotyping of fetal cells obtained by amniocentesis. OUTCOMES: All 3 couples decided to continue their pregnancies after learning about the consequences of the chromosomal abnormalities. Approximately a year after the children were born, the staff of the Prenatal Diagnostic Center followed up with a phone call and found that the children physical development and intelligence were normal. LESSON: This case report reports healthy chromosomal balanced translocation newborns born to couples with poor maternal history and couples with abnormalities suggested by preconception testing, and followed up with the newborns to provide some experience in prenatal diagnosis and genetic counseling for chromosomal balanced translocations.

Toxicity prediction and classification of Gunqile-7 with small sample based on transfer learning method.

Drug-induced diseases are the most important component of iatrogenic disease. It is the duty of doctors to provide a reasonable and safe dose of medication. Gunqile-7 is a Mongolian medicine with analgesic and anti-inflammatory effects. As a foreign substance in the body, even with reasonable medication, it may produce varying degrees of adverse reactions or toxic side effects. Since the cost of collecting Gunqile-7 for pharmacological animal trials is high and the data sample is small, this paper employs transfer learning and data augmentation methods to study the toxicity of Gunqile-7. More specifically, to reduce the necessary number of training samples, the data augmentation approach is employed to extend the data set. Then, the transfer learning method and one-dimensional convolutional neural network are utilized to train the network. In addition, we use the support vector machine-recursive feature elimination method for feature selection to reduce features that have adverse effects on model predictions. Furthermore, due to the important role of the pre-trained model of transfer learning, we select a quantitative toxicity prediction model as the pre-trained model, which is consistent with the purpose of this paper. Lastly, the experimental results demonstrate the efficiency of the proposed method. Our method can improve accuracy by up to 9 percentage points compared to the method without transfer learning on a small sample set.

Detection of individual brain tau deposition in Alzheimer's disease based on latent feature-enhanced generative adversarial network.

OBJECTIVE: The conventional methods for interpreting tau PET imaging in Alzheimer's disease (AD), including visual assessment and semi-quantitative analysis of fixed hallmark regions, are insensitive to detect individual small lesions because of the spatiotemporal neuropathology's heterogeneity. In this study, we proposed a latent feature-enhanced generative adversarial network model for the automatic extraction of individual brain tau deposition regions. METHODS: The latent feature-enhanced generative adversarial network we propose can learn the distribution characteristics of tau PET images of cognitively normal individuals and output the abnormal distribution regions of patients. This model was trained and validated using 1131 tau PET images from multiple centres (with distinct races, i.e., Caucasian and Mongoloid) with different tau PET ligands. The overall quality of synthetic imaging was evaluated using structural similarity (SSIM), peak signal to noise ratio (PSNR), and mean square error (MSE). The model was compared to the fixed templates method for diagnosing and predicting AD. RESULTS: The reconstructed images archived good quality, with SSIM = 0.967 ± 0.008, PSNR = 31.377 ± 3.633, and MSE = 0.0011 ± 0.0007 in the independent test set. The model showed higher classification accuracy (AUC = 0.843, 95 % CI = 0.796-0.890) and stronger correlation with clinical scales (r = 0.508, P < 0.0001). The model also achieved superior predictive performance in the survival analysis of cognitive decline, with a higher hazard ratio: 3.662, P < 0.001. INTERPRETATION: The LFGAN4Tau model presents a promising new approach for more accurate detection of individualized tau deposition. Its robustness across tracers and races makes it a potentially reliable diagnostic tool for AD in practice.

A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer's disease.

BACKGROUND: Functional connectivity (FC) biomarkers play a crucial role in the early diagnosis and mechanistic study of Alzheimer's disease (AD). However, the identification of effective FC biomarkers remains challenging. In this study, we introduce a novel approach, the spatiotemporal graph convolutional network (ST-GCN) combined with the gradient-based class activation mapping (Grad-CAM) model (STGC-GCAM), to effectively identify FC biomarkers for AD. METHODS: This multi-center cross-racial retrospective study involved 2,272 participants, including 1,105 cognitively normal (CN) subjects, 790 mild cognitive impairment (MCI) individuals, and 377 AD patients. All participants underwent functional magnetic resonance imaging (fMRI) and T1-weighted MRI scans. In this study, firstly, we optimized the STGC-GCAM model to enhance classification accuracy. Secondly, we identified novel AD-associated biomarkers using the optimized model. Thirdly, we validated the imaging biomarkers using Kaplan-Meier analysis. Lastly, we performed correlation analysis and causal mediation analysis to confirm the physiological significance of the identified biomarkers. RESULTS: The STGC-GCAM model demonstrated great classification performance (The average area under the curve (AUC) values for different categories were: CN vs MCI = 0.98, CN vs AD = 0.95, MCI vs AD = 0.96, stable MCI vs progressive MCI = 0.79). Notably, the model identified specific brain regions, including the sensorimotor network (SMN), visual network (VN), and default mode network (DMN), as key differentiators between patients and CN individuals. These brain regions exhibited significant associations with the severity of cognitive impairment (p < 0.05). Moreover, the topological features of important brain regions demonstrated excellent predictive capability for the conversion from MCI to AD (Hazard ratio = 3.885, p < 0.001). Additionally, our findings revealed that the topological features of these brain regions mediated the impact of amyloid beta (Aß) deposition (bootstrapped average causal mediation effect: ß = -0.01 [-0.025, 0.00], p < 0.001) and brain glucose metabolism (bootstrapped average causal mediation effect: ß = -0.02 [-0.04, -0.001], p < 0.001) on cognitive status. CONCLUSIONS: This study presents the STGC-GCAM framework, which identifies FC biomarkers using a large multi-site fMRI dataset.

Genome-Wide Analysis of the TCP Transcription Factor Gene Family in Pepper (Capsicum annuum L.).

TCP transcription factors play a key role in regulating various developmental processes, particularly in shoot branching, flower development, and leaf development, and these factors are exclusively found in plants. However, comprehensive studies investigating TCP transcription factors in pepper (Capsicum annuum L.) are lacking. In this study, we identified 27 CaTCP members in the pepper genome, which were classified into Class I and Class II through phylogenetic analysis. The motif analysis revealed that CaTCPs in the same class exhibit similar numbers and distributions of motifs. We predicted that 37 previously reported miRNAs target 19 CaTCPs. The expression levels of CaTCPs varied in various tissues and growth stages. Specifically, CaTCP16, a member of Class II (CIN), exhibited significantly high expression in flowers. Class I CaTCPs exhibited high expression levels in leaves, while Class II CaTCPs showed high expression in lateral branches, especially in the CYC/TB1 subclass. The expression profile suggests that CaTCPs play specific roles in the developmental processes of pepper. We provide a theoretical basis that will assist in further functional validation of the CaTCPs.

Construction of an Enzymatically Controlled DNA Nanomachine for One-Step Imaging of Telomerase in Living Cells.

Telomerase is a basic reverse transcriptase that maintains the telomere length in cells, and accurate and specific sensing of telomerase in living cells is critical for medical diagnostics and disease therapeutics. Herein, we demonstrate for the first time the construction of an enzymatically controlled DNA nanomachine with endogenous apurinic/apyrimidinic endonuclease 1 (APE1) as a driving force for one-step imaging of telomerase in living cells. The DNA nanomachine is designed by rational engineering of substrate probes and reporter probes embedded with an enzyme-activatable site (i.e., AP site) and their subsequent assembly on a gold nanoparticle (AuNP). Upon recognition and cleavage of the AP site in the substrate probe by APE1, the loop of the substrate probe unfolds, exposing telomeric primer (TP) with the 3'-OH end. Subsequently, the TP is elongated by telomerase at the 3'-OH end to generate a long telomeric product. The resultant telomeric product acts as a swing arm that can hybridize with a reporter probe to initiate the APE1-powered walking reaction, ultimately generating a significantly enhanced fluorescence signal. Notably, endogenous APE1 is used as the driving force of the DNA nanomachine, avoiding the introduction of exogenous auxiliary cofactors into the cellular microenvironment. Owing to the high kinetics and high amplification efficiency of the APE1-powered DNA nanomachine, this strategy enables one-step sensitive sensing of telomerase in vitro and in vivo. It can successfully discriminate telomerase activity between cancer cells and normal cells, screen telomerase inhibitors, and monitor the variations of telomerase activity in living cells, offering a prospective platform for molecular diagnostics and drug discovery.

Functional and structural gradients reveal atypical hierarchical organization of Parkinson's disease.

Parkinson's disease (PD) patients exhibit deficits in primary sensorimotor and higher-order executive functions. The gradient reflects the functional spectrum in sensorimotor-associated areas of the brain. We aimed to determine whether the gradient is disrupted in PD patients and how this disruption is associated with treatment outcome. Seventy-six patients (mean age, 59.2 ± 12.4 years [standard deviation], 44 women) and 34 controls participants (mean age, 58.1 ± 10.0 years [standard deviation], 19 women) were evaluated. We explored functional and structural gradients in PD patients and control participants. Patients were followed during 2 weeks of multidisciplinary intensive rehabilitation therapy (MIRT). The Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) was administered to patients before and after treatment. We investigated PD-related alterations in the principal functional and structural gradients. We further used a support vector machine (SVM) and correlation analysis to assess the classification ability and treatment outcomes related to PD gradient alterations, respectively. The gradients showed significant differences between patients and control participants, mainly in somatosensory and visual networks involved in primary function, and higher-level association networks (dorsal attentional network (DAN) and default mode network (DMN)) related to motor control and execution. On the basis of the combined functional and structural gradient features of these networks, the SVM achieved an accuracy of 91.2% in discriminating patients from control participants. Treatment reduced the gradient difference. The altered gradient exhibited a significant correlation with motor improvement and was mainly distributed across the visual network, DAN and DMN. This study revealed damage to gradients in the brain characterized by sensorimotor and executive control deficits in PD patients. The application of gradient features to neurological disorders could lead to the development of potential diagnostic and treatment markers for PD.

S0-driven partial denitrification coupled with anammox (S0PDA) enables highly efficient autotrophic nitrogen removal from wastewater.

This study proposed a novel strategy that integrates S0 particles (diameter: 2-3 mm) and granular sludge to establish S0-driven partial denitrification coupled with anammox (S0PDA) process for autotrophic nitrogen removal from NH4+- and NO3--containing wastewaters. This process was evaluated using an up-flow anoxic sludge bed bioreactor, operating continuously for 240 days. The influent concentrations of NH4+ and NO3- were 29.9 ± 2.7 and 50.2 ± 2.7 mg-N/L, respectively. Throughout the operation, the hydraulic retention time was shortened from 4.0 h to 2.0 h, while the effluent concentrations of NH4+ and NO3- were maintained at a desirable level of 1.45-1.51 mg-N/L and 4.46-6.52 mg-N/L, respectively. Despite an autotrophic process, the nitrogen removal efficiency and rate reached up to 88.5 ± 2.0 % and 1.75 ± 0.07 kg-N/(m3·d), respectively, indicating the remarkable robustness of the S0PDA process. Autotrophic anammox and sulfur-oxidizing bacteria (Candidatus Brocadia and Thiobacillus) were the predominant bacterial genera involved in the S0PDA process. Candidatus Brocadia was primarily enriched in the granular sludge, with a relative abundance of 6.70 %. Thiobacillus occupied a unique niche on the S0 particles, with a relative abundance as high as 57.6 %, of which Thiobacillus thioparus with partial denitrification function (reducing NO3- to NO2- without further reduction to N2) accounted for 78.0 %. These findings challenge the stereotype of low efficiency in autotrophic nitrogen removal from wastewater, shedding fresh light on the applications of autotrophic processes.

A Polymer-Based Antigen Carrier Activates Two Innate Immune Pathways for Adjuvant-Free Subunit Vaccines.

The activation of multiple Pattern Recognition Receptors (PRRs) has been demonstrated to trigger inflammatory responses and coordinate the host's adaptive immunity during pathogen infections. The use of PRR agonists as vaccine adjuvants has been reported to synergistically induce specific humoral and cellular immune responses. However, incorporating multiple PRR agonists as adjuvants increases the complexity of vaccine design and manufacturing. In this study, we discovered a polymer that can activate both the Toll-like receptor (TLR) pathway and cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. The polymer was then conjugated to protein antigens, creating an antigen delivery system for subunit vaccines. Without additional adjuvants, the antigen-polymer conjugates elicited strong antigen-specific humoral and cellular immune responses. Furthermore, the antigen-polymer conjugates, containing the Receptor Binding Domain (RBD) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Spike Protein or the Monkeypox Antigen M1R as the antigens, were found to induce potent antigen-specific antibodies, neutralizing antibodies, and cytotoxic T cells. Immunization with M1R-polymer also resulted in effective protection in a lethal challenge model. In conclusion, this vaccine delivery platform offers an effective, safe, and simple strategy for inducing antigen-specific immunity against infectious diseases.

Unique quinoline orientations shape the modified aptamer to sclerostin for enhanced binding affinity and bone anabolic potential.

Osteogenesis imperfecta (OI) is a rare genetic disease characterized by bone fragility and bone formation. Sclerostin could negatively regulate bone formation by antagonizing the Wnt signal pathway, whereas it imposes severe cardiac ischemic events in clinic. Our team has screened an aptamer that could promote bone anabolic potential without cardiovascular risk. However, the affinity of the aptamer is lower and needs to be improved. In the study, hydrophobic quinoline molecule with unique orientations (seven subtypes) were incorporated into key sites of a bone anabolic aptamer against sclerostin to form a modified aptamer library. Among all the quinoline modifications, 5-quinoline modification could shape the molecular recognition of modified aptamers to sclerostin to facilitate enhancing its binding to sclerostin toward the highest affinity by interacting with newly participated binding sites in sclerostin. Further, 5-quinoline modification could facilitate the modified aptamer attenuating the suppressed effect of the transfected sclerostin on both Wnt signaling and bone formation marker expression levels in vitro, promoting bone anabolism in OI mice (Col1a2+/G610C). The proposed quinoline-oriented modification strategy could shape the molecular recognition of modified aptamers to proteins to facilitate enhancing its binding affinity and therapeutic potency.

Source-specific light absorption and radiative effects decreases and indications due to the lockdown.

The 'extreme' emission abatement during the lockdown (from the end of 2019 to the early 2020) provided an experimental period to investigate the corresponding source-specific effects of aerosol. In this study, the variations of source-specific light absorption (babs) and direct radiative effect (DRE) were obtained during and after the lockdown period by using the artificial neural network (ANN) and source apportionment environmental receptor model. The results showed that the babs decreased for all sources during the two periods. The most reductions were observed with ∼90% for traffic-related emissions (during the lockdown) and ∼85% for coal combustion (after the lockdown), respectively. Heightened babs (370 nm) values were obtained for coal and biomass burning during the lockdown, which was attributed to the enhanced atmospheric oxidization capacity. Nevertheless, the variations of babs (880 nm) after the lockdown was mainly due to the weakening of oxidation and reduced emissions of secondary precursors. The present study indicated that the large-scale emission reduction can promote both reductions of babs (370 nm) and DRE (34-68%) during the lockdown. The primary emissions decrease (e.g., Traffic emission) may enhance atmosphere oxidation, increase the ultraviolet wavelength light absorption and DRE efficiencies. The source-specific emission reduction may be contributed to various radiation effects, which is beneficial for the adopting of control strategies.

Unveiling the microbiota of sauce-flavor Daqu and its relationships with flavors and color during maturation.

This study investigated the microbial community in three-color sauce-flavor Daqu (black, yellow, and white) throughout their maturation processes, together with their physicochemical factors, culturable microbes, flavor components, and fermenting vitalities. Results from high-throughput sequencing revealed distinct microbial diversity, with more pronounced variations in bacterial community than in fungal community. Firmicutes and Ascomycota emerged as the most dominant bacterial and fungal phyla, respectively, during maturation. Genus-level analysis identified Kroppenstedia, Virgibacillus, and Bacillus as dominant bacteria in black Daqu, yellow Daqu, and white Daqu, severally, while Thermoascus was shared as the core dominant fungi for these Daqu. Physicochemical factors, particularly acidity, were found to exert a significant impact on microbial community. Kroppenstedtia was the key bacteria influencing the color formation of these Daqu. Furthermore, correlations between dominant microbes and flavor compounds highlighted their role in Daqu quality. Molds (Aspergillus, Rhizomucor, and Rhizopus), excepting Bacillus, played a crucial role in the formation of pyrazine compounds. Consequently, this study offers innovative insights into the microbial perspectives on color and pyrazine formation, establishing a groundwork for future mechanized Daqu production and quality control of sauce-flavor baijiu.

Partial denitrifying phosphorus removal coupling with anammox (PDPRA) enables synergistic removal of C, N, and P nutrients from municipal wastewater: A year-round pilot-scale evaluation.

Applying anaerobic ammonium oxidation (anammox) in municipal wastewater treatment plants (MWWTPs) can unlock significant energy and resource savings. However, its practical implementation encounters significant challenges, particularly due to its limited compatibility with carbon and phosphorus removal processes. This study established a pilot-scale plant featuring a modified anaerobic-anoxic-oxic (A2O) process and operated continuously for 385 days, treating municipal wastewater of 50 m3/d. For the first time, we propose a novel concept of partial denitrifying phosphorus removal coupling with anammox (PDPRA), leveraging denitrifying phosphorus-accumulating organisms (DPAOs) as NO2- suppliers for anammox. 15N stable isotope tracing revealed that the PDPRA enabled an anammox reaction rate of 6.14 ± 0.18 µmol-N/(L·h), contributing 57.4 % to total inorganic nitrogen (TIN) removal. Metagenomic sequencing and 16S rRNA amplicon sequencing unveiled the co-existence and co-prosperity of anammox bacteria and DPAOs, with Candidatus Brocadia being highly enriched in the anoxic biofilms at a relative abundance of 2.46 ± 0.52 %. Finally, the PDPRA facilitated the synergistic conversion and removal of carbon, nitrogen, and phosphorus nutrients, achieving remarkable removal efficiencies of chemical oxygen demand (COD, 83.5 ± 5.3 %), NH4+ (99.8 ± 0.7 %), TIN (77.1 ± 3.6 %), and PO43- (99.3 ± 1.6 %), even under challenging operational conditions such as low temperature of 11.7 °C. The PDPRA offers a promising solution for reconciling the mainstream anammox and the carbon and phosphorus removal, shedding fresh light on the paradigm shift of MWWTPs in the near future.