Bibliometric analysis of vitamin D and obesity research over the period 2000 to 2023.

Background: Globally, the incidence rates of obesity and its related diseases, such as cardiovascular diseases and type 2 diabetes, are continuously rising, posing a significant public health challenge. Studies have indicated a potential correlation between vitamin D deficiency and obesity. However, a quantitative analysis of the studies related vitamin D and obesity is lacking. This investigation aims to fill this gap by providing a comprehensive bibliometric analysis to uncover the collaborative networks, research hotspots, and evolutionary trends within the field of vitamin D and obesity research. Methods: This study retrieved literature related to vitamin D and obesity from the Web of Science database spanning from 2000 to 2023. Bibliometric analysis was conducted using tools such as HistCite, VOSviewer, and CiteSpace to excavate multi-dimensional information including countries, institutions, authors, journals, citations, and keywords. Results: A total of 6,144 records were retrieved, involving 123 countries, 6,726 institutions, and 28,156 authors, published in 1,551 journals. The number of published papers and citations showed a generally increasing trend. The United States led in terms of publication volume and influence, with journals such as Nutrients and Obesity Surgery having the highest publication counts. Nasser M. Al-Daghri was the most prolific and influential author. Keyword clustering revealed that research topics covered metabolic health, nutrition, immunity, and bariatric surgery. Citation burst analysis indicated a shift in research focus from the relationship between dietary calcium and obesity to the preventive effects of vitamin D supplementation on metabolic diseases. Conclusion: The application of bibliometric methods to analyze the research literature in the fields of obesity and vitamin D has provided a comprehensive understanding of the collaborative networks, key research focus, and evolutionary trends in this field, offering insights for guiding future research directions.

Optimization design of hydrocyclone with overflow slit structure based on experimental investigation and numerical simulation analysis.

This study aims to address the issue of high energy consumption in the hydrocyclone separation process. By introducing a novel slotted overflow pipe structure and utilizing experimental and response surface optimization methods, the optimal parameters were determined. The research results indicate that the number of slots, slot angles, and positioning dimensions significantly influence the performance of the hydrocyclone separator. The optimal combination was found to be three layers of slots, a positioning dimension of 5.3 mm, and a slot angle of 58°. In a Φ100mm hydrocyclone separator, validated through multiple experiments, the separation efficiency increased by 0.26% and the pressure drop reduced by 24.88% under a flow rate of 900 ml/s. CFD simulation verified the reduction in internal flow field velocity and pressure drop due to the slotted structure. Therefore, this study provides an effective reference for designing efficient and low-energy hydrocyclone separators.

GAB1 attenuates lipopolysaccharide­mediated endothelial dysfunction via regulation of SOCS3.

Endothelial dysfunction is a crucial pathogenetic mechanism for sepsis. GRB2-associated binder 1 (GAB1) alleviates sepsis-induced multi-organ damage; however, to the best of our knowledge, its function in endothelial dysfunction in sepsis remains unclear. HUVECs were induced by lipopolysaccharide (LPS) to simulate endothelial cell injury under sepsis. Cell transfection was conducted to achieve GAB1 overexpression or suppressor of cytokine signaling 3 (SOCS3) knockdown. The expression levels of GAB1 and SOCS3 were detected by reverse transcription-quantitative PCR and western blotting. Cell viability, apoptosis and migration were assessed using Cell Counting Kit-8, TUNEL and wound healing assays, respectively. The production of cytokines and nitric oxide (NO) was detected using commercial kits. The interaction between GAB1 and SOCS3 was confirmed using a co-immunoprecipitation assay. GAB1 was downregulated in LPS-induced HUVECs. However, GAB1 overexpression significantly mitigated LPS-induced cell viability decrease and apoptosis in HUVECs, accompanied by upregulation of Bcl2 expression, and downregulation of Bax and cleaved caspase-3 expression. GAB1 also inhibited the production of pro-inflammatory cytokines and increased NO level, increased the levels of endothelial NO synthase (eNOS) and phosphorylated (p)-eNOS, and promoted migration in LPS-induced HUVECs. However, SOCS3 knockdown partially weakened the effects of GAB1 overexpression on cell viability, apoptosis, inflammation, p-eNOS, eNOS expression and NO levels in LPS-induced HUVECs. In addition, GAB1 and SOCS3 regulated Janus kinase 2 (JAK2)/STAT3 signaling in LPS-induced HUVECs. In conclusion, GAB1 exerted a protective effect against LPS-induced endothelial cell apoptosis, inflammation and dysfunction by modulating the SOCS3/JAK2/STAT3 signaling pathway.

Gut microbiota metabolite tyramine ameliorates high-fat diet-induced insulin resistance via increased Ca2+ signaling.

The gut microbiota and their metabolites are closely linked to obesity-related diseases, such as type 2 diabetes, but their causal relationship and underlying mechanisms remain largely elusive. Here, we found that dysbiosis-induced tyramine (TA) suppresses high-fat diet (HFD)-mediated insulin resistance in both Drosophila and mice. In Drosophila, HFD increases cytosolic Ca2+ signaling in enterocytes, which, in turn, suppresses intestinal lipid levels. 16 S rRNA sequencing and metabolomics revealed that HFD leads to increased prevalence of tyrosine decarboxylase (Tdc)-expressing bacteria and resulting tyramine production. Tyramine acts on the tyramine receptor, TyrR1, to promote cytosolic Ca2+ signaling and activation of the CRTC-CREB complex to transcriptionally suppress dietary lipid digestion and lipogenesis in enterocytes, while promoting mitochondrial biogenesis. Furthermore, the tyramine-induced cytosolic Ca2+ signaling is sufficient to suppress HFD-induced obesity and insulin resistance in Drosophila. In mice, tyramine intake also improves glucose tolerance and insulin sensitivity under HFD. These results indicate that dysbiosis-induced tyramine suppresses insulin resistance in both flies and mice under HFD, suggesting a potential therapeutic strategy for related metabolic disorders, such as diabetes.

Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest.

BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using electrocardiography (ECG) and photoplethysmography (PPG) during CPR. METHODS: Nine pigs were used in this study. ECG, PPG, invasive arterial blood pressure (ABP), and right atrial pressure (RAP) signals were simultaneously recorded. The CPPs were estimated using three datasets: (a) ECG, (b) PPG, and (c) ECG and PPG, and were compared with invasively measured CPPs. Four machine-learning algorithms, namely support vector regression, random forest (RF), K-nearest neighbor, and gradient-boosted regression tree, were used for estimation of CPP. RESULTS: The RF model with a combined ECG and PPG dataset achieved better estimation of CPP than the other algorithms. Specifically, the mean absolute error was 4.49 mmHg, the root mean square error was 6.15 mm Hg, and the adjusted R2 was 0.75. A strong correlation was found between the non-invasive estimation and invasive measurement of CPP (r = 0.88), which supported our hypothesis that machine-learning-based analysis of ECG and PPG parameters can provide a non-invasive estimation of CPP for CPR. CONCLUSIONS: This study proposes a novel estimation of CPP using ECG and PPG with machine-learning-based algorithms. Non-invasively estimated CPP showed a high correlation with invasively measured CPP and may serve as an easy-to-use physiological indicator for high-quality CPR treatment.

[Advances in the Effects of Microplastics on Soil N2O Emissions and Nitrogen Transformation].

Research on microplastics (MPs) is gaining more attention in the soil environment, but their impact on soil microbiota and related nitrogen processes remains poorly understood. Nitrous oxide (N2O) is one of the important greenhouse gases of the nitrogen cycle in agricultural soil, which mainly originates from microbial-mediated nitrogen (N) transformation processes. Microplastics can influence soil nitrogen transformation, as well as nitrogen-related functional enzymes and genes, and its enrichment may profoundly affect the N2O emissions in soil. However, because of the complexity of the properties of MPs, variations in experimental conditions, and spatial-temporal scales, the results on the effects of MPs on soil N2O emissions, nitrogen content, enzymes activities, and nitrogen functional genes remain inconsistent. Additionally, there is a lack of research conducted at broader experimental scales (e.g., pot scale), from diverse perspectives (e.g., denitrification or DNRA), and using advanced techniques (e.g., stable isotope approaches) to elucidate the underlying mechanisms. Therefore, to comprehend the environmental risk of MPs on soil from multiple perspectives, this review summarized the impact of MPs on soil N cycling from previous published research to provide a knowledge basis and gain holistic insights into the potential impact of soil microplastic enrichment on N2O emission patterns in agricultural soils under climate change conditions.

A new and highly efficient CuMOF-based nanoenzyme and its application to the aptamer SERS/FL/RRS/Abs quadruple-mode analysis of ultratrace malachite green.

Malachite green (MG) is highly toxic, persistent, and carcinogenic, and its widespread use is a danger to the ecosystem and a threat to public health and food safety, making it necessary to develop new sensitive multimode molecular spectroscopy methods. In this work, a new copper-based nanomaterial (CuNM) was prepared by a high-temperature roasting using a copper metal-organic framework (CuMOF) as precursor. The as-prepared CuNM was characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy, transmission electron microscopy (TEM), and BET surface area analysis. CuNM was found to catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 to produce the oxidation product TMBOX; however, subsequently, the MG aptamer (Apt) could be adsorbed on the CuNM surface by intermolecular interaction, which would inhibit the catalytic performance. After the addition of MG to be tested, the CuNM previously adsorbed by the Apt was transformed into its free state, thus restoring its catalytic activity. This new nanocatalytic indicator reaction could be monitored by surface-enhanced Raman scattering (SERS)/resonance Rayleigh scattering (RRS)/fluorescence (FL)/absorption (Abs) quadruple-mode methods. The SERS determination range was 0.004-0.4 nmol L-1 MG, with a limit of detection of 0.0032 nM. In this way, a rapid, stable, and sensitive method for the determination of MG residues in the environment was established.

Development and Validation of a Prediction Model for 30-Day Mortality and Functional Outcome in Patients with Primary Brainstem Hemorrhage.

INTRODUCTION: Primary brainstem hemorrhage (PBSH) is the most fatal subtype of intracerebral hemorrhage and is associated with poor prognosis. We aimed to develop a prediction model for predicting 30-day mortality and functional outcome in patients with PBSH. METHODS: We reviewed records of 642 consecutive patients with first-time PBSH from three hospitals between 2016 and 2021. Multivariate logistic regression was used to establish a nomogram in a training cohort. Cutoff points of the variables were determined by receiver operating characteristic curve analysis, and certain points were assigned to these predictors to produce the PBSH score. The nomogram and PBSH score were compared with other scoring systems for PBSH. RESULTS: Five independent predictors, comprised of temperature, pupillary light reflex, platelet-to-lymphocyte ratio, Glasgow Coma Scale (GCS) score on admission, and hematoma volume, were incorporated to construct the nomogram. The PBSH score consisted of 4 independent factors with individual points assigned as follows: temperature, ≥38°C (=1 point), <38°C (=0 points); pupillary light reflex, absence (=1 point), presence (=0 points); GCS score 3-4 (=2 points), 5-11 (=1 point), and 12-15 (=0 points); PBSH volume >10 mL (=2 points), 5-10 mL (=1 point), and <5 mL (=0 points). Results showed that the nomogram was discriminative in predicting both 30-day mortality (area under the ROC curve [AUC] of 0.924 in the training cohort, and 0.931 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The PBSH score was discriminative in predicting both 30-day mortality (AUC of 0.923 in the training cohort and 0.923 in the validation cohort) and 30-day functional outcome (AUC of 0.887). The prediction performances of the nomogram and the PBSH score were superior to the intracranial hemorrhage (ICH) score, primary pontine hemorrhage (PPH) score, and new PPH score. CONCLUSIONS: We developed and validated two prediction models for 30-day mortality and functional outcome in patients with PBSH. The nomogram and PBSH score could predict 30-day mortality and functional outcome in PBSH patients.

Rspo2 exacerbates rheumatoid arthritis by targeting aggressive phenotype of fibroblast-like synoviocytes and disrupting chondrocyte homeostasis via Wnt/ß-catenin pathway.

BACKGROUND: The aggressive phenotype of fibroblast-like synoviocytes (FLS) has been identified as a contributing factor to the exacerbation of rheumatoid arthritis (RA) through the promotion of synovitis and cartilage damage. Regrettably, there is currently no effective therapeutic intervention available to address this issue. Recent research has shed light on the crucial regulatory role of R-spondin-2 (Rspo2) in cellular proliferation, cartilage degradation, and tumorigenesis. However, the specific impact of Rspo2 on RA remains poorly understood. We aim to investigate the function and mechanism of Rspo2 in regulating the aggressive phenotype of FLS and maintaining chondrocyte homeostasis in the context of RA. METHODS: The expression of Rspo2 in knee joint synovium and cartilage were detected in RA mice with antigen-induced arthritis (AIA) and RA patients. Recombinant mouse Rspo2 (rmRspo2), Rspo2 neutralizing antibody (Rspo2-NAb), and recombinant mouse DKK1 (rmDKK1, a potent inhibitor of Wnt signaling pathway) were used to explore the role and mechanism of Rspo2 in the progression of RA, specifically in relation to the aggressive phenotype of FLS and chondrocyte homeostasis, both in vivo and in vitro. RESULTS: We indicated that Rspo2 expression was upregulated both in synovium and articular cartilage as RA progressed in RA mice and RA patients. Increased Rspo2 upregulated the expression of leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5), as the ligand for Rspo2, and ß-catenin in FLS and chondrocytes. Subsequent investigations revealed that intra-articular administration of rmRspo2 caused striking progressive synovitis and articular cartilage destruction to exacerbate RA progress in mice. Conversely, neutralization of Rspo2 or inhibition of the Wnt/ß-catenin pathway effectively alleviated experimental RA development. Moreover, Rspo2 facilitated FLS aggressive phenotype and disrupted chondrocyte homeostasis primarily through activating Wnt/ß-catenin pathway, which were effectively alleviated by Rspo2-NAb or rmDKK1. CONCLUSIONS: Our data confirmed a critical role of Rspo2 in enhancing the aggressive phenotype of FLS and disrupting chondrocyte homeostasis through the Wnt/ß-catenin pathway in the context of RA. Furthermore, the results indicated that intra-articular administration of Rspo2 neutralizing antibody or recombinant DKK1 might represent a promising therapeutic strategy for the treatment of RA.

Electrical-mechanical dynamical coupling between electrocardiographic and photoplethysmographic signals during cardiopulmonary resuscitation.

BACKGROUND AND OBJECTIVE: Cardiac arrest (CA) remains a significant cause of death and disability. High-quality cardiopulmonary resuscitation (CPR) can improve the survival rate of CA. A challenging issue is to find physiological indicators for screening and evaluating the cardiovascular function associated with CPR. This study aimed to investigate the electrical-mechanical dynamic coupling between electrocardiographic (ECG) and photoplethysmographic (PPG) signals for indicating cardiovascular function in the progress of CPR. METHOD: The ECG and PPG signals were simultaneously collected from a porcine CA model (n = 10) induced by ventricular fibrillation, and were further divided into four periods: Baseline, CA, CPR, and recovery of spontaneous circulation (ROSC). Recurrence quantitative analysis (RQA) was applied to examine the nonlinear dynamics of the ECG and PPG signals individually, and cross recurrence quantitative analysis (CRQA) was used to examine the ECG-PPG dynamical coupling. RESULTS: The CA influenced the dynamic patterns of electrical and mechanical activities and the electrical-mechanical coupling, which can be observed from the reduced entropy (ENTR) (p < 0.01), reduced determinism (DET) (p < 0.01) and reduced trapping time (TT) (p < 0.01) at CA compared to Baseline. The recurrence rate (RR), ENTR, DET, and TT at CPR were significantly lower than the parameters at ROSC but higher than those at CA. CONCLUSIONS: The electrical-mechanical dynamical coupling was sensitive to CPR and able to reflect the changes in cardiac function in the process of CPR.

Metabolomics in aging research: aging markers from organs.

Metabolism plays an important role in regulating aging at several levels, and metabolic reprogramming is the main driving force of aging. Due to the different metabolic needs of different tissues, the change trend of metabolites during aging in different organs and the influence of different levels of metabolites on organ function are also different, which makes the relationship between the change of metabolite level and aging more complex. However, not all of these changes lead to aging. The development of metabonomics research has opened a door for people to understand the overall changes in the metabolic level in the aging process of organisms. The omics-based "aging clock" of organisms has been established at the level of gene, protein and epigenetic modifications, but there is still no systematic summary at the level of metabolism. Here, we reviewed the relevant research published in the last decade on aging and organ metabolomic changes, discussed several metabolites with high repetition rate, and explained their role in vivo, hoping to find a group of metabolites that can be used as metabolic markers of aging. This information should provide valuable information for future diagnosis or clinical intervention of aging and age-related diseases.

[Pollution Characteristics of PM2.5 Chemical Composition in Zhejiang Province].

To investigate the seasonal and regional pollution characteristics of PM2.5 chemical composition in Zhejiang province, this study was based on manual sampling monitoring data from 11 sampling sites of four regions in Zhejiang province from October 1, 2019 to September 30, 2020. The results showed that during the observation period, the average ρ(PM2.5) of the four regions ranged from 34.3 µg·m-3 to 46.4 µg·m-3. The PM2.5 mass concentrations in the hinterland areas of western Zhejiang and northern Zhejiang were relatively high, 15.1% and 13.2% higher than the mean value, respectively. The PM2.5 mass concentrations in the coastal areas of eastern Zhejiang and southern Zhejiang were relatively low, 8.4% and 14.9% lower than the average, respectively. The seasonal characteristics showed a higher concentration in autumn and winter and lowest concentration in summer. The seasonal variation in PM2.5 mass concentration from autumn to spring was not obvious in southern Zhejiang, whereas in western Zhejiang, the PM2.5 mass concentration followed a descending sequence of autumn>winter>spring>summer. In northern Zhejiang and eastern Zhejiang, the trend was winter>autumn>spring>summer. During the observation period in the inland area, the ρ(PM2.5) of the scenic area, administrative area, residential area, and mixed area of commercial traffic and residents were (40.2±10.2), (46.3±9.6), (50.1±10.6), and (46.7±10.2) µg·m-3, respectively. The highest value of ρ(PM2.5) was in the residential area. During the sampling period in coastal areas, the ρ(PM2.5) of the cultural and entertainment area and mixed area of commercial traffic and residents were (27.4±5.8) µg·m-3and (37.2±5.6) µg·m-3, respectively. The contribution rates of organic matter (OM), NO3-, SO42-, NH4+, trace elements, and crustal matter in PM2.5were 26.4%, 15.4%, 12.4%, 9.0%, 7.1%, and 5.7%, respectively. The SNA, including SO42-, NO3-, and NH4+, contributed 36.8% in PM2.5. In terms of seasons, the contribution of OM to PM2.5 in autumn, spring, and summer was higher than that of other compositions, which accounted for 28.3%, 27.7%, and 26.3%, respectively. The contribution rate of NO3- in PM2.5 was the largest in winter, reaching 24.3%. In terms of spatial distribution, SNA contributed the most to PM2.5 in all regions, ranging from 32.8% to 39.7%, with the highest in northern Zhejiang and the lowest in southern Zhejiang. The SNA of all regions presented NO3->SO42->NH4+. Based on the backward trajectory clustering analysis, the main air sources of northern Zhejiang were the Yellow Sea-southern Jiangsu (autumn), northern Anhui (winter), East China Sea (spring), and western Jiangsu (summer) areas, with contribution rates of 38.11%, 35.28%, 37.46%, and 27.87%, respectively. The main air sources of western Zhejiang were the Yellow Sea-southern Jiangsu (autumn), southern Anhui (winter), eastern Zhejiang (spring), and northern Zhejiang (summer), with contribution rates of 38.11%, 37.50%, 46.55%, and 32.58%, respectively. The air of autumn, winter, spring, and summer in eastern Zhejiang were influenced by air masses from northern Hebei (36.07%), eastern Shandong (38.06%), East China Sea (30.17%), and southern Guangdong (34.43%), respectively. In autumn, winter, spring, and summer, southern Zhejiang was affected by air masses from the Yellow Sea (35.66%), northeast Anhui (34.44%), East China Sea (26.72%), and southern Fujian coast (35.00%), respectively. The regions in Zhejiang province showed large seasonal differences. The difference value between the maximum value of ρ(PM2.5) in the northwest and the lowest value in the southeast was 21.0 µg·m-3 and 20.5 µg·m-3 in autumn and winter, respectively; the difference values in spring and summer were 10.4 µg·m-3 and 6.1 µg·m-3. Thus, the northern air mass had a certain exogenous contribution to PM2.5 in autumn and winter in Zhejiang province. However, with the weakening of the northern air mass trajectory in spring and summer and the increasing contribution of the southern and east China Sea air mass to the air flow in Zhejiang province, PM2.5 pollution showed a trend of improvement.

Nickel-Catalyzed, Enantioselective Hydrofluoromethylation of Olefins: Access to Chiral α-Fluoromethylated Amides and Esters.

We herein report the nickel-catalyzed enantioselective hydrofluoromethylation of enamides and enol esters with CH2FI as the fluoromethyl source to enable the diversity-oriented synthesis (DOS) of chiral α-fluoromethylated amides as well as esters with features of wide functional group compatibility as well as excellent enantioselectivity. The synthetic value of this protocol was demonstrated by transformations of the resulted α-fluoromethylated amides to different scaffolds including amine, oxazoline, thiazoline, and α-fluoromethylated tetrahydroquinoline.

Streptococcus dysgalactiae subsp. dysgalactiae presents with progressive weakness in limbs: a case report and literature review.

BACKGROUND: Streptococcus dysgalactiae subsp. dysgalactiae has been identified as an animal pathogen that is thought to occur only in animal populations. Between 2009 and 2022, humans infected with SDSD were reported rarely. There is a lack of details on the natural history, clinical features, and management of disease caused by this pathogen. This case outlines a human SDSD with muscle aches and progressive loss of muscle strength leading to immobility and multi-organ dysfunction syndrome. CASE PRESENTATION: She presented with muscle pain and weakness, and later developed a sore throat, headache and fever with a maximum temperature of 40.5 °C. The muscle strength of the extremities gradually decreased to grade 1 and the patient was unable to move on his own. Next-generation blood sequencing and multi-culture confirmed the presence of Streptococcus dysgalactiae and Streptococcus dysgalactiae subsp. Dysgalactiae, respectively. A Sequential Organ Failure Assessment score of 6 indicated septicemia, and therapeutic antibiotics were prescribed empirically. After 19 days of inpatient treatment, the patient's condition greatly improved and completely recovered within a month. CONCLUSION: Symptoms of Streptococcus dysgalactiae subsp. dysgalactiae presenting with progressive limb weakness resemble polymyositis, so a precise differential diagnosis is essential. Multidisciplinary consultation is helpful when polymyositis cannot be ruled out and facilitates the choice of an optimal treatment protocol. In the context of this case, penicillin is an effective antibiotic for Streptococcus dysgalactiae subsp. dysgalactiae infection.

Leptospira infection complicated by demyelinating disease: A case report.

Leptospirosis is a zoonotic disease, found worldwide, that is caused by bacteria of the genus Leptospira. People can be infected with Leptospira if they come in direct contact with the urine of an infected animal. Leptospirosis may be associated with demyelinating lesions of the central nervous system. This case report describes a 66-year-old female patient who presented with fever and generalized aches and progressed to unconsciousness within a few hours of admission. Laboratory tests showed Leptospira infection, and brain magnetic resonance imaging revealed acute demyelinating lesions. The patient responded well to penicillin and intravenous methylprednisolone therapy. Leptospirosis presenting with acute disseminated encephalomyelitis is rare. In this patient, an interdisciplinary collaboration involving the neurologist, radiologist, and pathologist was crucial for diagnosis and management. Further studies are warranted to investigate whether there is a correlation between demyelinating lesions and leptospiral infection.

Modular Approach for Diversity-Oriented Synthesis of ß-Fluoroalkylated Arenes via Pd/Norbornene Cooperative Catalysis.

A novel approach towards the efficient assembly of ß-fluoroalkylated arenes is presented here based on Pd/norbornene cooperative catalysis, which features an excellent functional group tolerance, as well as a broad ipso termination scope. The mild reaction conditions enabled the diversity-oriented synthesis (DOS) of the 13 and 14-membered fluorinated macrolactones which is extremely challenging otherwise. This new abstract could be used instead of our old version.

Effects of pH alterations on stress- and aging-induced protein phase separation.

Upon stress challenges, proteins/RNAs undergo liquid-liquid phase separation (LLPS) to fine-tune cell physiology and metabolism to help cells adapt to adverse environments. The formation of LLPS has been recently linked with intracellular pH, and maintaining proper intracellular pH homeostasis is known to be essential for the survival of organisms. However, organisms are constantly exposed to diverse stresses, which are accompanied by alterations in the intracellular pH. Aging processes and human diseases are also intimately linked with intracellular pH alterations. In this review, we summarize stress-, aging-, and cancer-associated pH changes together with the mechanisms by which cells regulate cytosolic pH homeostasis. How critical cell components undergo LLPS in response to pH alterations is also discussed, along with the functional roles of intracellular pH fluctuation in the regulation of LLPS. Further studies investigating the interplay of pH with other stressors in LLPS regulation and identifying protein responses to different pH levels will provide an in-depth understanding of the mechanisms underlying pH-driven LLPS in cell adaptation. Moreover, deciphering aging and disease-associated pH changes that influence LLPS condensate formation could lead to a deeper understanding of the functional roles of biomolecular condensates in aging and aging-related diseases.

Diversity-Oriented Synthesis of Fluoromethylated Arenes via Palladium-Catalyzed C-H Fluoromethylation of Aryl Iodides.

Herein we report the first versatile and expeditious method for the site-selective C-H fluoromethylation of aryl iodides via Pd/norbornene cooperative catalysis, which could work as a robust toolbox for the diversity-oriented synthesis (DOS) of fluoromethylated arenes. This methodology features the use of the low-cost industrial raw material CH2IF as the fluoromethyl source, an excellent functional group tolerance, and a broad ipso termination scope and can be expanded to the late-stage modification of biorelevant molecules.

A cholesterol benzoate RRS probe for the determination of trace ammonium ions.

The measurement of NH4+ has attracted considerable attention with the increase of NH4+ emissions in sewage caused by human activities. So far, a variety of photometric and fluorescence methods for the detection of NH4+ have been researched and summarized, but there is no report about the use of liquid crystals (LCs) cholesteryl benzoate (CB) as a resonance Rayleigh scattering (RRS) probe to determine ammonium ions. In the NaAc-HAc buffer solution with pH = 4.80, the yellow compounds 3,5 diacetyl-1,4 dihydrolutidine (DDL) generated by the reaction of NH4+ with acetylacetone (AT) and formaldehyde (HCHO) act as the energy receiver and CB as the donor. Because the RRS spectrum of CB overlaps with the DDL absorption spectrum, resonance Rayleigh scattering energy transfer (RRS-ET) occurs. When the NH4+ concentration increased, the generated DDL increased, and the RRS-ET also increased, so the RRS intensity of the system at 395 nm decreased. For this reason, a fast and sensitive CB RRS-ET method was established to apply to the detection of NH4+ in water. The detection range was 1.00 × 10-3 - 4.66 µg/mL, and the detection limit was 6.62 × 10-3 µg/mL. Using this method to analyze and detect NH4+ in environmental water samples, the precision and recovery rate were between 1.30-9.30% and 95.5-109.9%, respectively. Therefore, this method has the advantages of sensitivity and simplicity.

Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles.

Virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in rapid materials discovery. By necessity, efficient DFT-based workflows are carried out with a single density functional approximation (DFA). Nevertheless, properties evaluated with different DFAs can be expected to disagree for cases with challenging electronic structure (e.g., open-shell transition-metal complexes, TMCs) for which rapid screening is most needed and accurate benchmarks are often unavailable. To quantify the effect of DFA bias, we introduce an approach to rapidly obtain property predictions from 23 representative DFAs spanning multiple families, "rungs" (e.g., semi-local to double hybrid) and basis sets on over 2000 TMCs. Although computed property values (e.g., spin state splitting and frontier orbital gap) differ by DFA, high linear correlations persist across all DFAs. We train independent ML models for each DFA and observe convergent trends in feature importance, providing DFA-invariant, universal design rules. We devise a strategy to train artificial neural network (ANN) models informed by all 23 DFAs and use them to predict properties (e.g., spin-splitting energy) of over 187k TMCs. By requiring consensus of the ANN-predicted DFA properties, we improve correspondence of computational lead compounds with literature-mined, experimental compounds over the typically employed single-DFA approach.