Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in automatically detecting keratitis through a slit lamp camera, remote and underserved areas often lack this professional equipment. Smartphones, a widely available device, have recently been found to have potential in keratitis screening. However, given the limited data available from smartphones, employing traditional deep learning algorithms to construct a robust intelligent system presents a significant challenge. This study aimed to propose a meta-learning framework, cosine nearest centroid-based metric learning (CNCML), for developing a smartphone-based keratitis screening model in the case of insufficient smartphone data by leveraging the prior knowledge acquired from slit-lamp photographs. METHODS: We developed and assessed CNCML based on 13,009 slit-lamp photographs and 4,075 smartphone photographs that were obtained from 3 independent clinical centers. To mimic real-world scenarios with various degrees of sample scarcity, we used training sets of different sizes (0 to 20 photographs per class) from the HUAWEI smartphone to train CNCML. We evaluated the performance of CNCML not only on an internal test dataset but also on two external datasets that were collected by two different brands of smartphones (VIVO and XIAOMI) in another clinical center. Furthermore, we compared the performance of CNCML with that of traditional deep learning models on these smartphone datasets. The accuracy and macro-average area under the curve (macro-AUC) were utilized to evaluate the performance of models. RESULTS: With merely 15 smartphone photographs per class used for training, CNCML reached accuracies of 84.59%, 83.15%, and 89.99% on three smartphone datasets, with corresponding macro-AUCs of 0.96, 0.95, and 0.98, respectively. The accuracies of CNCML on these datasets were 0.56% to 9.65% higher than those of the most competitive traditional deep learning models. CONCLUSIONS: CNCML exhibited fast learning capabilities, attaining remarkable performance with a small number of training samples. This approach presents a potential solution for transitioning intelligent keratitis detection from professional devices (e.g., slit-lamp cameras) to more ubiquitous devices (e.g., smartphones), making keratitis screening more convenient and effective.

DeepMonitoring: a deep learning-based monitoring system for assessing the quality of cornea images captured by smartphones.

Smartphone-based artificial intelligence (AI) diagnostic systems could assist high-risk patients to self-screen for corneal diseases (e.g., keratitis) instead of detecting them in traditional face-to-face medical practices, enabling the patients to proactively identify their own corneal diseases at an early stage. However, AI diagnostic systems have significantly diminished performance in low-quality images which are unavoidable in real-world environments (especially common in patient-recorded images) due to various factors, hindering the implementation of these systems in clinical practice. Here, we construct a deep learning-based image quality monitoring system (DeepMonitoring) not only to discern low-quality cornea images created by smartphones but also to identify the underlying factors contributing to the generation of such low-quality images, which can guide operators to acquire high-quality images in a timely manner. This system performs well across validation, internal, and external testing sets, with AUCs ranging from 0.984 to 0.999. DeepMonitoring holds the potential to filter out low-quality cornea images produced by smartphones, facilitating the application of smartphone-based AI diagnostic systems in real-world clinical settings, especially in the context of self-screening for corneal diseases.

SGLT-2 inhibitors and high-dose acarbose as potential high-risk combinations for ketosis and ketoacidosis in Asian patients with T2DM: A case series.

Key Clinical Message: High-dose acarbose may increase the risk of diabetic ketosis/diabetic ketoacidosis in Asian patients on sodium-glucose cotransporter-2 inhibitors. Healthcare providers and patients should be cautious to avoid this combination. Abstract: Low-calorie diets should be avoided in patients receiving sodium-glucose cotransporter-2 (SGLT-2) inhibitors to decrease the risk of diabetic ketoacidosis (DKA). High-dose acarbose can decelerate carbohydrate absorption. We detail three cases of diabetic ketosis (DK) following concurrent SGLT-2 inhibitor and high-dose acarbose therapy (acarbose 300 mg/day and dapagliflozin 10 mg/day). Patients, aged 38-63 years with 3-10 years of type 2 diabetes mellitus (T2DM), developed DK, indicated by moderate urinary ketones and high glucose (urine ketone 2+ to 3+ and glucose 3+ to 4+) without acidosis, within 4 days to 1 month post-therapy initiation. Serum glucose was 172.8-253.8 mg/dL; HbA1c was 9.97%-10.80%. The combination therapy was halted, and DK was managed with low-dose intravenous insulin and fluids, followed by intensive insulin therapy. High-dose acarbose with SGLT-2 inhibitors may increase the risk of DK/DKA in Asian patients.

Time-restricted eating with or without a low-carbohydrate diet improved myocardial status and thyroid function in individuals with metabolic syndrome: secondary analysis of a randomized clinical trial.

BACKGROUND: Obesity and metabolic syndrome (MetS) have become urgent worldwide health problems, predisposing patients to unfavorable myocardial status and thyroid dysfunction. Low-carbohydrate diet (LCD) and time-restricted eating (TRE) have been confirmed to be effective methods for weight management and improving MetS, but their effects on the myocardium and thyroid are unclear. METHODS: We conducted a secondary analysis in a randomized clinical diet-induced weight-loss trial. Participants (N = 169) diagnosed with MetS were randomized to the LCD group, the 8 h TRE group, or the combination of the LCD and TRE group for 3 months. Myocardial enzymes and thyroid function were tested before and after the intervention. Pearson's or Spearman's correlation was assessed between functions of the myocardium and thyroid and cardiometabolic parameters at baseline. RESULTS: A total of 162 participants who began the trial were included in the intention-to-treat (ITT) analysis, and 57 participants who adhered to their assigned protocol were involved in the per-protocol (PP) analysis. Relative to baseline, lactate dehydrogenase, creatine kinase MB, hydroxybutyrate dehydrogenase, and free triiodothyronine (FT3) declined, and free thyroxine (FT4) increased after all 3 interventions (both analyses). Creatine kinase (CK) decreased only in the TRE (- 18 [44] U/L, P < 0.001) and combination (- 22 [64] U/L, P = 0.003) groups (PP analysis). Thyrotropin (- 0.24 [0.83] µIU/mL, P = 0.011) and T3 (- 0.10 ± 0.04 ng/mL, P = 0.011) decreased in the combination group (ITT analysis). T4 (0.82 ± 0.39 µg/dL, P = 0.046), thyroglobulin antibodies (TgAb, 2 [1] %, P = 0.021), and thyroid microsomal antibodies (TMAb, 2 [2] %, P < 0.001) increased, while the T3/T4 ratio (- 0.01 ± 0.01, P = 0.020) decreased only in the TRE group (PP analysis). However, no significant difference between groups was observed in either analysis. At baseline, CK was positively correlated with the visceral fat area. FT3 was positively associated with triglycerides and total cholesterol. FT4 was negatively related to insulin and C-peptide levels. TgAb and TMAb were negatively correlated with the waist-to-hip ratio. CONCLUSIONS: TRE with or without LCD confers remarkable metabolic benefits on myocardial status and thyroid function in subjects with MetS. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04475822.

Effects of time-restricted eating and low-carbohydrate diet on psychosocial health and appetite in individuals with metabolic syndrome: A secondary analysis of a randomized controlled trial.

BACKGROUND & AIMS: Time-restricted eating (TRE) and low-carbohydrate diet (LCD) can improve multiple cardiometabolic parameters in patients with metabolic syndrome (MetS), but their effects on psychosocial health and satiety are unclear. In this study, we aimed to evaluate the effects of TRE, LCD, and their combination (TRE + LCD) on quality of life (QoL), sleep, mood, appetite, and metabolic hormones in patients with MetS. METHODS: This is a secondary analysis of a single-center, 3-month, open-label, randomized clinical trial investigating the effects of TRE, LCD, and TRE + LCD on weight and cardiometabolic parameters in individuals with MetS. This secondary analysis examined QoL, sleep, mood, and appetite using the Rand 36-Item Short Form (SF-36); Pittsburgh Sleep Quality Index (PSQI); Depression, Anxiety, and Stress Scale; and Eating Behavior Rating Scale, respectively, as well as measured levels of metabolic hormones including leptin, amylin, glucose-dependent insulinotropic polypeptide, glucagon-like peptide-1 (GLP-1), pancreatic polypeptide (PP), and peptide YY. Between-group comparisons were conducted via one-way ANOVAs and post hoc LSD tests for normally distributed variables or Kruskal‒Wallis H tests and the Nemenyi test for abnormally distributed variables. P < 0.017 was considered significant in multiple comparisons following Bonferroni adjustment. RESULTS: A total of 162 participants (mean [SD] age, 41.2 [9.9] years; mean [SD] body mass index, 29.3 [3.4] kg/m2; 102 [63%] men) who started the intervention were analyzed. After 3 months, only the TRE group decreased GLP-1 levels (-0.9 [IQR, -1.9 to -0.3] pg/mL; P = 0.002), increased PP levels (8.9 [IQR, -7.6 to 71.8] pg/mL; P = 0.011), physical functioning in the SF-36 (5.2 [95% CI, 1.9 to 8.5]; P = 0.001), social functioning in the SF-36 (9.1 [95% CI, 2.5 to 15.6]; P = 0.005), role-physical in the SF-36 (24.1 [95% CI, 11.8 to 36.4]; P < 0.001), role-emotional in the SF-36 (22.4 [95% CI, 12.6 to 32.2]; P < 0.001), and sleep efficiency in the PSQI (0.29 [95% CI, 0.03 to 0.55]; P = 0.021). Compared with changes in LCD, TRE further increased general health in the SF-36 (9.7 [95% CI, 3.3 to 16.0]; P = 0.006). Relative to the changes of TRE + LCD, TRE significantly increased role-emotional in the SF-36 (19.9 [95% CI 4.9 to 34.8]; P = 0.006). Changes in sleep quality, mood status, appetite, and metabolic hormones did not differ among three groups. Greater weight loss was associated with decreased leptin levels (r = 0.538), decreased amylin levels (r = 0.294), reduced total appetite scores (r = 0.220), and improved general health (r = -0.253) (all P ≤ 0.01). CONCLUSIONS: TRE, LCD, and TRE + LCD all could improve psychosocial health and reduce appetite. Notably, TRE yielded greater benefits in QoL compared with LCD or TRE + LCD in individuals with MetS. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04475822.

Transcriptomic profiling identifies a nucleotide metabolism-related signature with prognostic power in gliomas.

OBJECTIVE: Nucleotide metabolic reprogramming as a hallmark of cancer is closely related to the occurrence and progression of cancer. We aimed to comprehensively analyze the nucleotide metabolism-related gene set and clinical significance in gliomas. METHODS: The RNA sequencing data of 702 gliomas from the Cancer Genome Atlas (TCGA) dataset were included as the training set, and the RNA sequencing data from the other three datasets (CGGA, GSE16011, and Rembrandt) were used as independent validation sets. Survival curve, Cox regression analysis, time-dependent ROC curve and nomogram model were performed to evaluate prognostic power of signature. R language was the main tool for bioinformatic analysis and graphical work. RESULTS: Based on the expression profiles of nucleotide metabolism-related genes, consensus clustering identified two robust clusters with different prognosis. We then developed a nucleotide metabolism-related signature that was closely related to clinical, pathological, and genomic characteristics of gliomas. And ROC curve showed that our signature was a potential biomarker for mesenchymal subtype. Survival curve and Cox regression analysis revealed signature as an independent prognostic factor for gliomas. In addition, we constructed a nomogram model to predict individual survival. Finally, functional analysis showed that nucleotide metabolism not only affected cell division and cell cycle, but also was associated with immune response in gliomas. CONCLUSION: We developed a nucleotide metabolism-related signature to predict prognosis and provided new insights into the role of nucleotide metabolism in gliomas.

Tryptophan supplements in high-carbohydrate diets by improving insulin response and glucose transport through PI3K-AKT-GLUT2 pathways in blunt snout bream (Megalobrama amblycephala).

The aim of this experiment was to elucidate the metabolic ramifications of tryptophan supplementation in the context of high-carbohydrate diet-feeding, which is important for improving feeding strategies in aquaculture in order to improve fish carbohydrate metabolism. Juvenile blunt snout bream with an initial mean body mass of 55.0±0.5 g were allocated to consume one of three experimental diets: CN, a normal diet with carbohydrate content of 30% (w/w); HC, a diet with high carbohydrate content of 43% (w/w); and HL, a high-carbohydrate diet to which 0.8% L-tryptophan (L-trp) had been added. These diets were fed for 8 weeks, and the effects of the carbohydrate and tryptophan contents of the diets were assessed. Histological analysis using Hematoxylin and Eosin (H&E) and Oil Red O staining revealed that high-carbohydrate intake was associated with abnormal hepatocyte morphology and excessive liver lipid accumulation, which were notably ameliorated by tryptophan supplementation. A significant increase in plasma glucose, glucagon, AGEs (advanced glycation end products), triglycerides, total cholesterol, and a significant decrease in insulin and hepatic glycogen after a high-carbohydrate diet in terms of plasma indices, compared to the control group. Almost all of them were restored to the normal level in the HL group. The present study might preliminarily suggest that tryptophan supplementation ameliorates the imbalance in glucose metabolism of this species induced by a high-carbohydrate diet. Transcriptomics showed that glucose metabolism under high carbohydrate was mainly regulated by the PI3K-AKT signaling pathway. The mRNA expression and protein levels of GLUT2 also varied with this pathway, which would suggest that sustained activation of this pathway with the addition of tryptophan accelerates glucose transport and insulin secretion under high-carbohydrate diet. Subsequent GTT and ITT experiments have also demonstrated that tryptophan improves glucose tolerance and insulin tolerance in blunt snout bream on a high-carbohydrate diet. In conclusion, these findings elucidate the positive regulatory effect of tryptophan on the PI3K-AKT-GLUT2 pathway under a high carbohydrate diet and provide a theoretical basis for the subsequent rational application of high carbohydrate diets in the future.

Trace elements in pancreatic cancer.

BACKGROUND: Pancreatic cancer (PCA) is an extremely aggressive malignant cancer with an increasing incidence and a low five-year survival rate. The main reason for this high mortality is that most patients are diagnosed with PCA at an advanced stage, missing early treatment options and opportunities. As important nutrients of the human body, trace elements play an important role in maintaining normal physiological functions. Moreover, trace elements are closely related to many diseases, including PCA. REVIEW: This review systematically summarizes the latest research progress on selenium, copper, arsenic, and manganese in PCA, elucidates their application in PCA, and provides a new reference for the prevention, diagnosis and treatment of PCA. CONCLUSION: Trace elements such as selenium, copper, arsenic and manganese are playing an important role in the risk, pathogenesis, diagnosis and treatment of PCA. Meanwhile, they have a certain inhibitory effect on PCA, the mechanism mainly includes: promoting ferroptosis, inducing apoptosis, inhibiting metastasis, and inhibiting excessive proliferation.

Deep learning for multi-type infectious keratitis diagnosis: A nationwide, cross-sectional, multicenter study.

The main cause of corneal blindness worldwide is keratitis, especially the infectious form caused by bacteria, fungi, viruses, and Acanthamoeba. The key to effective management of infectious keratitis hinges on prompt and precise diagnosis. Nevertheless, the current gold standard, such as cultures of corneal scrapings, remains time-consuming and frequently yields false-negative results. Here, using 23,055 slit-lamp images collected from 12 clinical centers nationwide, this study constructed a clinically feasible deep learning system, DeepIK, that could emulate the diagnostic process of a human expert to identify and differentiate bacterial, fungal, viral, amebic, and noninfectious keratitis. DeepIK exhibited remarkable performance in internal, external, and prospective datasets (all areas under the receiver operating characteristic curves > 0.96) and outperformed three other state-of-the-art algorithms (DenseNet121, InceptionResNetV2, and Swin-Transformer). Our study indicates that DeepIK possesses the capability to assist ophthalmologists in accurately and swiftly identifying various infectious keratitis types from slit-lamp images, thereby facilitating timely and targeted treatment.

Gut microbes on the risk of advanced adenomas.

BACKGROUND: More than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC. OBJECTIVE: To analyze the characteristic microbes in AA. METHODS: Fecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and ß diversity. α diversity included box diagram, and ß diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed. RESULTS: The abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively. CONCLUSION: Prevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.

Modulation of Lipid Dynamics in the ß-Amyloid Aggregates Induced Membrane Fragmentation.

Nonspecific membrane disruption is considered a plausible mechanism for the cytotoxicity induced by ß-amyloid (Aß) aggregates. In scenarios of high local Aß concentrations, a two-step membrane fragmentation model has been proposed. Initially, membrane-embedded Aß oligomeric aggregates form, followed by membrane fragmentation. However, the key molecular-level interactions between Aß oligomeric aggregates and lipids that drive the second-stage membrane fragmentation remain unclear. This study monitors the time-dependent changes in lipid dynamics and water accessibility of model liposomes during Aß-induced membrane fragmentation. Our results indicate that lipid dynamics on the nanosecond to microsecond time scale undergo rapid acceleration upon initial incubation with membrane-incorporated Aß oligomeric aggregates, followed by a slow deceleration process. Concurrently, lipid headgroups become less accessible to water. Both observations suggest a carpet-like mechanism of membrane disruption for the Aß-induced membrane fragmentation process.

Storage-D: A user-friendly platform that enables practical and personalized DNA data storage.

Deoxyribonucleic acid (DNA) has been suggested as a very promising medium for data storage in recent years. Although numerous studies have advocated for DNA data storage, its practical application remains obscure and there is a lack of a user-oriented platform. Here, we developed a DNA data storage platform, named Storage-D, which allows users to convert their data into DNA sequences of any length and vice versa by selecting algorithms, error-correction, random-access, and codec pin strategies in terms of their own choice. It incorporates a newly designed "Wukong" algorithm, which provides over 20 trillion codec pins for data privacy use. This algorithm can also control GC content to the selected standard, as well as adjust the homopolymer run length to a defined level, while maintaining a high coding potential of ~1.98 bis/nt, allowing it to outperform previous algorithms. By connecting to a commercial DNA synthesis and sequencing platform with "Storage-D," we successfully stored "Diagnosis and treatment protocol for COVID-19 patients" into 200 nt oligo pools in vitro, and 500 bp genes in vivo which replicated in both normal and extreme bacteria. Together, this platform allows for practical and personalized DNA data storage, potentially with a wide range of applications.

All-fiber multifunction differential absorption CO2 lidar integrating single-photon and coherent detection.

This study demonstrates a differential absorption lidar (DIAL) for CO2 that integrates both single-photon direct detection and coherent detection. Based on all-fiber 1572 nm wavelength devices, this compact lidar achieves detection of CO2 concentration, wind field, and single photon aerosol backscattering signal. First, by comparing DIAL with VAISALA-GMP343, the concentration deviation between the two devices is less than 5 ppm, proving the accuracy of the DIAL. Second, through the scanning detection experiment in Chaohu Lake, Hefei, not only the CO2 concentration between single-photon detection and coherent detection but also the wind field was obtained, proving the multifunctionality and stability of the DIAL. Benefiting from the advantages of combined the two detection methods, single photon detection offers 3-km CO2 and aerosol backscattering signals; coherent detection offers a 360-m shorter blind zone and wind field. This DIAL can achieve monitoring of CO2 flux and sudden emissions, which can effectively compensate for the shortages of in-situ sensors and spaceborne systems.

Plant-derived extracellular vesicles as a promising anti-tumor approach: A comprehensive assessment of effectiveness, safety, and mechanisms.

BACKGROUND: Plant-derived extracellular vesicles (PDEs) are expected to be a compelling alternative for cancer treatment due to their low cytotoxicity, low immunogenicity, high yield, and potential anti-tumor efficacy. Despite the significant advantages of PDEs, the reliable evidence for PDEs as promising anti-tumor approach remains unsystematic and insufficient. Some challenges remain for the clinical application and large-scale industrial production of PDEs. PURPOSE: Through systematic evaluation and meta-analysis, the objective was to provide scientific, systematic and reliable preclinical evidence to support the clinical use of PDEs in cancer therapy. METHODS: The search for relevant literature, conducted up to March 2024, encompassed various databases including Web of Science, the Cochrane Library, Embase, PubMed, CNKI, Wanfang Data, and the China Science and Technology Journal Database. The SYRCLE´s risk of bias tool was used to assess the methodological quality of the animal studies. For overall effect analysis and subgroup analysis, RevMan 5.4 and Stata 12.0 were utilized. RESULTS: The analysis incorporated a total of 38 articles, comprising 29 in vivo studies and 9 in vitro studies. Meta-analysis indicated that PDEs significantly reduced cancer cell activity and induced apoptosis, reduced tumor volume and tumor weight when used as therapeutic agents, as well as exhibited synergistic anti-cancer via combination therapy. Additionally, PDEs-drugs exerted stronger inhibition of tumor volume compared to the free drug or commercial liposome-drugs. Their therapeutic effects were closely related to regulating tumor cell biological behavior and remodeling the tumor microenvironment. The safety was associated with administration route of PDEs, oral administration was currently preferred until more in-depth studies on the safety of other methods are conducted. CONCLUSIONS: The meta-analysis revealed that PDEs have systematic and reliable preclinical evidence in preclinical studies of cancer therapy, and their efficacy and certain safety could support the clinical application of PDEs in cancer therapy. Of course, further researches are required for large-scale industrial production to meet the needs of clinical applications.

Neutron spin echo shows pHLIP is capable of retarding membrane thickness fluctuations.

Cell membranes are responsible for a range of biological processes that require interactions between lipids and proteins. While the effects of lipids on proteins are becoming better understood, our knowledge of how protein conformational changes influence membrane dynamics remains rudimentary. Here, we performed experiments and computer simulations to study the dynamic response of a lipid membrane to changes in the conformational state of pH-low insertion peptide (pHLIP), which transitions from a surface-associated (SA) state at neutral or basic pH to a transmembrane (TM) α-helix under acidic conditions. Our results show that TM-pHLIP significantly slows down membrane thickness fluctuations due to an increase in effective membrane viscosity. Our findings suggest a possible membrane regulatory mechanism, where the TM helix affects lipid chain conformations, and subsequently alters membrane fluctuations and viscosity.

Decoupled response of microbial taxa and functions to nutrients: The role of stoichiometry in plantations.

The resource quantity and elemental stoichiometry play pivotal roles in shaping belowground biodiversity. However, a significant knowledge gap remains regarding the influence of different plant communities established through monoculture plantations on soil fungi and bacteria's taxonomic and functional dynamics. This study aimed to elucidate the mechanisms underlying the regulation and adaptation of microbial communities at the taxonomic and functional levels in response to communities formed over 34 years through monoculture plantations of coniferous species (Japanese larch, Armand pine, and Chinese pine), deciduous forest species (Katsura), and natural shrubland species (Asian hazel and Liaotung oak) in the temperate climate. The taxonomic and functional classifications of fungi and bacteria were examined for the mineral topsoil (0-10 cm) using MiSeq-sequencing and annotation tools of microorganisms (FAPROTAX and Funguild). Soil bacterial (6.52 ± 0.15) and fungal (4.46 ± 0.12) OTUs' diversity and richness (5.83*103±100 and 1.12*103±46.4, respectively) were higher in the Katsura plantation compared to Armand pine and Chinese pine. This difference was attributed to low soil DOC/OP (24) and DON/OP (11) ratios in the Katsura, indicating that phosphorus availability increased microbial community diversity. The Chinese pine plantation exhibited low functional diversity (3.34 ± 0.04) and richness (45.2 ± 0.41) in bacterial and fungal communities (diversity 3.16 ± 0.15 and richness 56.8 ± 3.13), which could be attributed to the high C/N ratio (25) of litter. These findings suggested that ecological stoichiometry, such as of enzyme, litter C/N, soil DOC/DOP, and DON/DOP ratios, was a sign of the decoupling of soil microorganisms at the genetic and functional levels to land restoration by plantations. It was found that the stoichiometric ratios of plant biomass served as indicators of microbial functions, whereas the stoichiometric ratios of available nutrients in soil regulated microbial genetic diversity. Therefore, nutrient stoichiometry could serve as a strong predictor of microbial diversity and composition during forest restoration.

"Cell Disk" DNA Storage System Capable of Random Reading and Rewriting.

DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 105 "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.

Palladium-Catalyzed Carbonylation Reaction of Indole/Pyrrole Involving HCFO-1233zd (E).

3-Indole-3-one is a key intermediate in the synthesis of many drugs and plays an important role in synthetic chemistry and biochemistry. A new method for synthesizing trifluoromethylated 3-indoleketones by Pd(0)-catalyzed carbonylation was introduced. In the absence of additives, 1-chloro-3,3,3-trifluoropropyl (an inexpensive and environmentally friendly synthetic block of trifluoromethyl) reacts with indole and carbon monoxide to generate trifluoromethylindole ketones with good yields, regioselectivity, and chemical selectivity; furthermore, the products exhibit strong resistance to basic functional groups, such as alkynes, aldehydes, and esters. In addition to the conversion of indole compounds into corresponding products, pyrrole and heteroindole may be suitable for corresponding chemical transformations. This study provides a synthetic method for the further construction of trifluoromethylated 3-indole ketones.

NH2-MIL-125-Derived N-Doped TiO2@C Visible Light Catalyst for Wastewater Treatment.

The utilization of titanium dioxide (TiO2) as a photocatalyst for the treatment of wastewater has attracted significant attention in the environmental field. Herein, we prepared an NH2-MIL-125-derived N-doped TiO2@C Visible Light Catalyst through an in situ calcination method. The nitrogen element in the organic connector was released through calcination, simultaneously doping into the sample, thereby enhancing its spectral response to cover the visible region. The as-prepared N-doped TiO2@C catalyst exhibited a preserved cage structure even after calcination, thereby alleviating the optical shielding effect and further augmenting its photocatalytic performance by increasing the reaction sites between the catalyst and pollutants. The calcination time of the N-doped TiO2@C-450 °C catalyst was optimized to achieve a balance between the TiO2 content and nitrogen doping level, ensuring efficient degradation rates for basic fuchsin (99.7%), Rhodamine B (89.9%) and tetracycline hydrochloride (93%) within 90 min. Thus, this study presents a feasible strategy for the efficient degradation of pollutants under visible light.