Predicting the incidence of rifampicin resistant tuberculosis in Yunnan, China: a seasonal time series analysis based on routine surveillance data.

BACKGROUND: Rifampicin resistant tuberculosis (RR-TB) poses a growing threat to individuals and communities. This study utilized a seasonal autoregressive integrated moving average (SARIMA) model to quantitatively predict the monthly incidence of RR-TB in Yunnan Province which could guide government health administration departments and the centers for disease control and prevention (CDC) in preventing and controlling the RR-TB epidemic. METHODS: The study utilized routine surveillance reporting data from the infectious Disease Network Surveillance and Reporting System. Monthly incidence rates of RR-TB were collected from January 2019 to December 2022. A time series SARIMA model was used to predict the number of monthly RR-TB cases in Yunnan Province in 2023, and the model was validated using time series plots, seasonal and non-seasonal differencing, autocorrelation and partial autocorrelation analysis, and white noise tests. RESULTS: From 2019 to 2022, the incidence of RR-TB decreases as the incidence of all TB decreases (P < 0.05). There was no significant change in the proportion of RR-TB among all TB cases, which remained within 2.5% (P>0.05). The time series decomposition shows that it presented obvious seasonality, periodicity and randomness after being decomposed. Time series analysis was performed on the original series after 1 non-seasonal difference and 1 seasonal difference, the ADF test showed P < 0.05. According to ACF and PACF, the SARIMA (1, 1, 1) (1, 1, 0)12 model was chosen and statistically significant model parameter estimates (P < 0.05). The predicted seasonal trend of RR-TB incidence in 2019 to 2023 was similar to the actual data. The percentage accuracy in the prediction excesses 80% in 2019 to 2022 and is all within 95% CI. However there was a certain gap between the actual incidence and the predicted value in 2023, and the acutual incidence had increased by 12.4% compared to 2022. The percentage of accuracy in the prediction was only 70% in 2023. CONCLUSIONS: We found the incidence of RR-TB was based on that of all TB in Yunnan. The SARIMA model successfully predicted the seasonal incidence trend of RR-TB in Yunnan Province in 2019 to 2023, but the prediction precision could be influenced by factors such as new infectious disease outbreaks or pandemics, social issues, environmental challenges or other unknown risks. Hence CDCs should pay special attention to the post epidemic effects of new infectious disease outbreaks or pandemics, carry out monitoring and early warning, and better optimize disease prediction models.

Individualized functional connectome abnormalities obtained using two normative model unveil neurophysiological subtypes of obsessive compulsive disorder.

The high heterogeneity observed among patients with obsessive-compulsive disorder (OCD) underscores the need to identify neurophysiological OCD subtypes to facilitate personalized diagnosis and treatment. In this study, our aim was to identify potential OCD subtypes based on individualized functional connectome abnormalities. We recruited a total of 99 patients with OCD and 104 healthy controls (HCs) matched for demographic characteristics. Individualized functional connectome abnormalities were obtained using normative models of functional connectivity strength (FCS) and used as features to unveil OCD subtypes. Sensitivity analyses were conducted to assess the reproducibility and robustness of the clustering outcomes. Patients exhibited significant intersubject heterogeneity in individualized functional connectome abnormalities. Two subtypes with distinct patterns of FCS abnormalities relative to HCs were identified. Subtype 1 patients primarily exhibited significantly decreased FCS in regions including the frontal gyrus, insula, hippocampus, and precentral/postcentral gyrus, whereas subtype 2 patients demonstrated increased FCS in widespread brain regions. When all patients were combined, no significant differences were observed. Additionally, the identified subtypes showed significant differences in age of onset. Furthermore, sensitivity analyses confirmed the reproducibility of our subtyping results. In conclusion, the identified OCD subtypes shed new light on the taxonomy and neurophysiological heterogeneity of OCD.

Ortho-digital dynamics: Exploration of advancing digital health technologies in musculoskeletal disease management.

Background: Musculoskeletal (MSK) disorders, affecting billions of people worldwide, pose significant challenges to the healthcare system and require effective management models. The rapid development of digital healthcare technologies (DHTs) has revolutionized the healthcare industry. DHT-based interventions have shown promising clinical benefits in managing MSK disorders, alleviating pain, and improving functional impairment. There is, however, no bibliometric analysis of the overall trends on this topic. Methods: We extracted all relevant publications from the Web of Science Core Collection (WoSCC) database until April 30, 2023. We performed bibliometric analysis and visualization using CiteSpace, VOSviewer, and R software. Annual trends of publications, countries/regions distributions, funding agencies, institutions, co-cited journals, author contributions, references, core journals, and keywords and research hotspots were analyzed. Results: A total of 6810 papers were enrolled in this study. Publications have increased drastically from 16 in 1995 to 1198 in 2022, with 4067 articles published in the last five years. In all, 53 countries contributed with publications to this research area. The United States, the United Kingdom, and China were the most productive countries. Harvard University was the most contributing institution. Regarding keywords, research focuses include artificial intelligence, deep learning, machine learning, telemedicine, rehabilitation, and robotics. Conclusion: The COVID-19 pandemic has further accelerated the adoption of DHTs, highlighting the need for remote care options. The analysis reveals the positive impact of DHTs on improving physician productivity, enhancing patient care and quality of life, reducing healthcare expenditures, and predicting outcomes. DHTs are a hot topic of research not only in the clinical field but also in the multidisciplinary intersection of rehabilitation, nursing, education, social and economic fields. The analysis identifies four promising hotspots in the integration of DHTs in MSK pain management, biomechanics assessment, MSK diagnosis and prediction, and robotics and tele-rehabilitation in arthroplasty care.

Establishing a Classification System for Predicting Flow-Limiting Dissection After Balloon Angioplasty Using Explainable Machine-Learning Models: A Multicenter Retrospective Cohort Study.

OBJECTIVE: Percutaneous transluminal angioplasty (PTA) is the primary method for treatment in peripheral arterial disease. However, some patients experience flow-limiting dissection (FLD) after PTA. We utilized machine learning and SHapley Additive exPlanations to identify and optimize a classification system to predict FLD after PTA. METHODS: This was a multi-center, retrospective, cohort study. The cohort comprised 407 patients who underwent treatment of the femoropopliteal (FP) arteries in 3 institutions between January 2021 and June 2023. Preoperative computed tomography angiography images were evaluated to identify FP artery grading, chronic total occlusion (CTO), and vessel calcification (peripheral artery calcium scoring system [PACSS]). After PTA, FLD was identified by angiography. We trained and validated 6 machine-learning models to estimate FLD occurrence after PTA, and the best model was selected. Then, the sum of the Shapley values for each of CTO, FP, and PACSS was calculated for each patient to produce the CTO-FP-PACSS value. The CTO-FP-PACSS classification system was used to classify the patients into classes 1 to 4. Univariate and multivariate analyses were performed to validate the effectiveness of the CTO-FP-PACSS classification system for predicting FLD. RESULTS: Overall, 407 patients were analyzed, comprising 189 patients with FLD and 218 patients without FLD. Differences in sex (71% males vs 54% males, p<0.001), CTO (72% vs 43%, p<0.001), FP (3.26±0.94 vs 2.66±1.06, p<0.001), and PACSS (2.39±1.40 vs 1.74±1.35, p<0.001) were observed between patients with and without FLD, respectively. The random forest model demonstrated the best performance (validation set area under the curve: 0.82). SHapley Additive exPlanations revealed CTO, PACSS, and FP as the 3 most influential FLD predictors, and the univariate and multivariate analyses confirmed CTO-FP-PACSS classification as an independent FLD predictor (multivariate hazard ratio 4.13; p<0.001). CONCLUSION: The CTO-FP-PACSS classification system accurately predicted FLD after PTA. This user-friendly system may guide surgical decision-making, helping choose between PTA and additional devices to reduce FLD in FP artery treatment. CLINICAL IMPACT: We utilised machine-learning techniques in conjunction with SHapley Additive exPlanations to develop a clinical classification system that predicts the probability of flow-limiting dissection (FLD) after plain old balloon angioplasty. This classification system categorises lesions into Classes 1-4 based on three factors: chronic total occlusion, femoropopliteal grading, and peripheral artery calcium scoring. Each class demonstrated a different probability of developing FLD. This classification system may be valuable for surgeons in their clinical practice, as well as serving as a source of inspiration for other researchers.

Development of V2O3 Nanostructures for Alkali Metal Ion Batteries: A Novel Approach through Mild Metal Vapor Reduction and Interface Engineering.

V2O3 has been extensively researched as a battery electrode material due to its ample reserves and high theoretical capacity. However, the synthesis of valence-sensitive V2O3 presents technical challenges as it requires a strict combination of high-temperature treatment and a narrow range of oxygen partial pressures. This study proposes a gentle Li vapor-assisted thermal reduction method to synthesize pure-phase V2O3 at a relatively low temperature of 480 °C without any hazardous gases. It has been discovered that reducing the temperature also improves the specific surface area of the nanoto-mesoscale hierarchical structures and enhances the reactive sites between their secondary grains. These advantages enable the V2O3 micronano particles to store higher levels of Li+, Na+, and K+, increase ionic transport, and tolerate volume expansion. It demonstrates a significant capacity of 767 mA h g-1 in lithium-ion batteries, 393 mA h g-1 in sodium-ion batteries, and 209 mA h g-1 in potassium-ion batteries. It has also been discovered that the crystal structure of V2O3 is easily adjustable by varying the synthesis temperature, which significantly affects the electrochemical storage mechanism. The V2O3 synthesized at 480 °C with low crystallinity exhibits a notable intercalation reaction, facilitating the electrochemical kinetics of reversible insertion/extraction of Li+, Na+, and K+. In contrast, the highly crystalline sample synthesized at 580 °C displays pseudocapacitance behavior instead of an intercalation reaction. The highly crystalline sample synthesized at 680 °C exhibits a thorough pseudocapacitance reaction possessing the capacitive functionality for the electrochemical storage of Na+ or K+ with larger ion radii. This study describes a new synthesis strategy and rational modification of vanadium-based electrodes for alkali metal ion batteries, leading to the development of reasonably priced rechargeable battery systems with applications extending beyond lithium-ion batteries.

Construction of intelligent response gene vector based on MOF/Fe3O4/AuNRs for tumor-targeted gene delivery.

Metal-organic frameworks (MOFs) have the potential to efficiently carry cargo due to their excellent porosity and high surface area. Nevertheless, conventional MOFs and their derivatives exhibit low efficiency in transporting nucleic acids and other small molecules, as well as having poor colloidal stability. In this study, a ZIF-90 loaded with iron oxide nanoparticles and Au nanorods was prepared, and then surface-functionalized with polyethyleneimine (PEI) to create a multifunctional nanocomposite (AFZP25k) with pH, photothermal, and magnetic responsiveness. AFZP25k can condense plasmid DNA to form AFZP25k/DNA complexes, with a maximum binding efficiency of 92.85 %. DNA release assay showed significant light and pH responsiveness, with over 80 % cumulative release after 6 h of incubation. When an external magnetic field is applied, the cellular uptake efficiency in HeLa cells reached 81.51 %, with low cytotoxicity and specific distribution. In vitro transfection experiments demonstrated a gene transfection efficiency of 44.77 % in HeLa cells. Following near-infrared irradiation, the uptake efficiency and transfection efficiency of AFZP25k in HeLa cells increased by 21.3 % and 13.59 % respectively. The findings indicate the potential of AFZP25k as an efficient and targeted gene delivery vector in cancer gene therapy.

NCAPH, ubiquitinated by TRIM21, promotes cell proliferation by inhibiting autophagy of cervical cancer through AKT/mTOR dependent signaling.

Autophagy is closely related to the occurrence and development of human malignancies; however, the detailed mechanisms underlying autophagy in cervical cancer require further investigation. Previously, we found that the ectopic expression of NCAPH, a regulatory subunit of condensed protein complexes, significantly enhanced the proliferation of tumor cells; however, the underlying mechanisms were unclear. Here, we revealed that NCAPH is a novel autophagy-associated protein in cervical cancer that promotes cell proliferation by inhibiting autophagosome formation and reducing autophagy, with no effect on the cell cycle, apoptosis, or aging. Tripartite motif-containing protein 21 (TRIM21) is well known to be involved in inflammation, autoimmunity and cancer, mainly via its E3 ubiquitin ligase activity. Mass spectrometry and immunoprecipitation assays showed that TRIM21 interacted with NCAPH and decreased the protein stability of NCAPH via ubiquitination at the K11 lysine residue. Structural domain mutation analysis revealed that TRIM21 combined with NCAPH through its PRY/SPRY and CC domains and accelerated the degradation of NCAPH through the RING domain. Furthermore, TRIM21 promoted autophagosome formation and reduced cell proliferation by inhibiting NCAPH expression and the downstream AKT/mTOR pathway in cervical cancer cells. Immunohistochemical staining revealed that the protein expression of TRIM21 was negatively correlated with that of NCAPH and positively correlated with that of beclin-1 in cervical cancer tissues. Therefore, we provide evidence for the role of the TRIM21-NCAPH axis in cervical cancer autophagy and proliferation and the involvement of the AKT/mTOR signaling pathway in this process. These results deepen our understanding of the carcinogenesis of cervical cancer, broaden the understanding of the molecular mechanisms of TRIM21 and NCAPH, and provide guidance for individualized treatment of cervical cancer in the future.

Discovery of Novel Mcl-1 Inhibitors with a 3-Substituted-1H-indole-1-yl Moiety Binding to the P1-P3 Pockets to Induce Apoptosis in Acute Myeloid Leukemia Cells.

Mcl-1 is a main antiapoptotic protein in acute myeloid leukemia (AML) and is used as a target to develop inhibitors. Currently, potent Mcl-1 inhibitors primarily interact with the P2-P4 pockets of Mcl-1, but pharmacological modulation by targeting the P1 pocket is less explored. We designed a series of 1H-indole-2-carboxylic acid compounds as novel Mcl-1 inhibitors occupying the P1-P3 pockets and evaluated their Mcl-1 inhibition and apoptosis induction in AML cells. Two-dimensional 15N-HSQC spectroscopy indicated that 47 (Ki = 24 nM) bound to the BH3 binding groove, occupied the P1 pocket in Mcl-1, and formed interactions with Lys234 and Val249. 47 exhibited good microsomal stability and pharmacokinetic profiles, with low potential risk of cardiotoxicity. 47 inhibited tumor growth in HL-60 and THP-1 xenograft models with growth inhibition rate of 63.7% and 57.4%, respectively. Collectively, 47 represents a novel Mcl-1 inhibitor targeting the P1-P3 pockets with excellent antileukemia effects.

In-situ rapid cultivation of aerobic granular sludge in A/O bioreactor by using Ca(ClO)2 pretreating sludge.

The efficient utilization of residual sludge and the rapid cultivation of aerobic granular sludge in continuous-flow engineering applications present significant challenges. In this study, aerobic granular cultivation was fostered in a continuous-flow system using Ca(ClO)2-sludge carbon (Ca-SC). Ca-SC retained the original sludge properties, contributing to granular growth in an A/O bioreactor. By day 40, the granule diameters increased to 0.8 mm with the SVI30 decreased by 2.7 times. Moreover, Ca-SC facilitated protein secretion, reaching 98.06 mg/g VSS and enhanced the hydrophobicity to 68.4 %. The continuous-flow aerobic granular sludge exhibited a nutrient removal rate above 90 %. Furthermore, Tessaracoccus and Nitrospira were enriched to promote granular formation and nitrogen removal. The residual sludge was carbonized and reused in the traditional wastewater treatment process to culture granular sludge in situ, aiming to achieve "self-production and self-consumption" of sludge and promote the innovative model of "treating waste with waste" in urban sewage environmental restoration.

The Use of Multifamily Discharge Preparation Groups in the Discharge Process of Patients with Schizophrenia.

Background: After acute treatment, patients with schizophrenia return to their original living environment for further rehabilitation, which not only determines the quality of life of the patients and their families but also has an important impact on society. However, patients often find it difficult to adapt to changes in the environment when they are discharged from the hospital. This may be related to the incompleteness of China's mental health service system, as many services for schizophrenia patients are only in the treatment stage. In China, schizophrenia is traditionally associated with poor moral quality, and patients find it difficult to obtain support. Many patients have trouble reintegrating into the community after treatment. Schizophrenic multifamily teams gather families affected by the same illness and pain together to promote healing together in an environment that allows mutual sharing, understanding and transparency, maximizes the use of family resources for support, improves discharge readiness, and better deals with post-discharge recovery. Methods: The multifamily group intervention method was used to improve the motivation of the patients' family motivation as well as the discharge readiness and self-efficacy of the patient. Results: After the intervention, the motivation of the family and discharge readiness of the patient were improved compared with that of the baseline period; however, the improvement was not significant. The self-efficacy of the patients was significantly improved (P=0.042). Conclusions: In the discharge preparation of schizophrenia patients, multifamily teams can be used to help patients and their families share resources, enhance support and prepare for discharge. Patients will have better support following discharge for recovery in the community. Additional consideration should be given to the impact of the environment on patient services, and the evaluation of the service process is key to continuously improving the service effect.

Fatal multiple acyl-CoA dehydrogenase deficiency caused by ETFDH gene mutation: A case report.

BACKGROUND: Multiple acyl-CoA dehydrogenase deficiency (MADD) is a disease of rare autosomal recessive disorder. There are three types of MADD. Type I is a neonatal-onset form with congenital anomalies. Type II is a neonatal-onset form without congenital anomalies. Type III is considered to a milder form and usually responds to riboflavin. However, late-onset form could also be fatal and not responsive to treatments. CASE SUMMARY: We report a severe case of a young man with onset type III MADD induced by drugs and strenuous exercise characterized by rhabdomyolysis and liver dysfunction. Urine analysis indicated 12 out of 70 kinds of organic acids like glutaric acid-2 were detected. Serum analysis in genetic metabolic diseases revealed 24 out of 43 tested items were abnormal, revealing the elevation of several acylcarnitines and the reduction of carnitine in the patient. By next generation sequencing technology for gene sequencing related to fatty acid oxidation and carnitine cycle defects, a rare ETFDH gene variant was identified: NM_004453:4:C.1448C>T(p.Pro483 Leu). The patient was diagnosed with late-onset GAII. He was not responsive to riboflavin and progressively worsened into multiple organ failure that finally led to death. CONCLUSION: Type III MADD can also be fatal and not responsive to treatments.

Coagulation risk predicting in anticoagulant-free CRRT.

INTRODUCTION: Continuous Renal Replacement Therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bleeding and with contraindications to sodium citrate, anticoagulant-free dialysis therapy is necessary. However, this approach increases the risk of CRRT circuit coagulation, leading to treatment interruption and increased resource consumption. In this study, we utilized artificial intelligence machine learning methods to predict the risk of CRRT circuit coagulation based on pre-CRRT treatment metrics. METHODS: We retrospectively analyzed 212 patients who underwent anticoagulant-free CRRT from October 2022 to October 2023. Patients were categorized into high-risk and low-risk groups based on CRRT circuit coagulation within 24 hours. We employed eight machine learning methods to predict the risk of circuit coagulation. The performance of the model was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC). 5-fold cross-validation was used to validate the machine learning models. Feature importance and SHAP plots were used to interpret the model's performance and key drivers. RESULTS: We identified 88 patients (41.51%) at high risk of circuit coagulation within 24 hours of CRRT. Our machine learning models showed excellent predictive performance, with ensemble learning (EL) achieving an AUC of 0.863 (95% CI 0.860 - 0.868), outperforming individual algorithms. Random forest (RF) was the best single-algorithm model, with an AUC of 0.819(95% CI 0.814 - 0.823). The top three features identified as most important by the SHAP summary plot and feature importance graph are platelet, FF, and triglycerides. CONCLUSION: We created a model using machine learning to predict the risk of circuit coagulation during anticoagulant-free CRRT therapy. Our model performs well (AUC 0.863) and identifies key factors like platelets, filtration fraction, and triglycerides. This facilitates the development of personalized treatment strategies by clinicians, aimed at reducing circuit coagulation risk, thereby enhancing patient outcomes and reducing healthcare expenses.

Comprehensive Screening and Characterization of α-glucosidase Inhibitory Components in the Edible Medicinal Plant Pholidota cantonensis Rolfe Using UPLC-Q-TOF-MS/MS Analysis and Molecular Docking.

Pholidota cantonensis Rolfe is an edible medicinal plant in the genus Pholidota of the family Orchidaceae. This plant is used to prepare medicated food in China and has been reported to possess anti-α-glucosidase activity. To date, little is known about the active substances responsible for the observed anti-α-glucosidase activity. In the present study, we aimed to screen and characterize the α-glucosidase inhibitory fraction of P. cantonensis using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) analysis and molecular docking. As a result, the 50% ethanol fraction obtained from D101 macroporous adsorption resin column chromatography (D50 fraction) had the highest total phenol content (353.83 ± 6.06 mg GAE/g) and the most prominent α-glucosidase inhibitory activity (IC50 = 30.01 ± 7.30 µg/mL). Forty-five compounds were identified from the D50 fraction by using UPLC-Q-TOF-MS/MS analysis. Molecular docking results showed that six main constituents, namely, crepidatin, 2,7-dihydroxy-4-methoxyl-9,10-dihydrophenylene, 4,4',5,6-tetrahydroxystilbene, 4,7-dihydroxy-2-methoxyl-9,10-dihydrophenylene, (-)-lariciresinol, and thunalbene, in the D50 fraction occupied the catalytic sites of α-glucosidase through strong hydrophobic interactions, hydrogen bonding, and other patterns. The binding energies were between - 29.95 and - 11.41 kJ/mol, indicating good binding between the tested compounds and α-glucosidase. The active ingredients responsible for the α-glucosidase inhibitory activity may include phenanthrenes, stilbenes, dibenzyls, and lignans. The D50 fraction has potential value for developing innovative drugs for the prevention and treatment of diabetes mellitus (DM) and is worthy of in-depth research.

α7-nAChR/P300/NLRP3-regulated pyroptosis mediated poor articular cartilage quality induced by prenatal nicotine exposure in female offspring rats.

Nicotine is developmentally toxic. Prenatal nicotine exposure (PNE) affects the development of multiple fetal organs and causes susceptibility to a variety of diseases in offspring. In this study, we aimed to investigate the effect of PNE on cartilage development and osteoarthritis susceptibility in female offspring rats. Wistar rats were orally gavaged with nicotine on days 9-20 of pregnancy. The articular cartilage was obtained at gestational day (GD) 20 and postnatal week (PW) 24, respectively. Further, the effect of nicotine on chondrogenic differentiation was explored by the chondrogenic differentiation model in human Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs). The PNE group showed significantly shallower Safranin O staining and lower Collagen 2a1 content of articular cartilage in female offspring rats. Further, we found that PNE activated pyroptosis in the articular cartilage at GD20 and PW24. In vitro experiments revealed that nicotine inhibited chondrogenic differentiation and activated pyroptosis. After interfering with nod-like receptors3 (NLRP3) expression by SiRNA, it was found that pyroptosis mediated the chondrogenic differentiation inhibition of WJ-MSCs induced by nicotine. In addition, we found that α7-nAChR antagonist α-BTX reversed nicotine-induced NLRP3 and P300 high expression. And, P300 SiRNA reversed the increase of NLRP3 mRNA expression and histone acetylation level in its promoter region induced by nicotine. In conclusion, PNE caused chondrodysplasia and poor articular cartilage quality in female offspring rats. PNE increased the histone acetylation level of NLRP3 promoter region by α7-nAChR/P300, which resulting in the high expression of NLRP3. Further, NLRP3 mediated the inhibition of chondrogenic differentiation by activating pyroptosis.

First report on liquid crystal monomers in tree barks surrounding a display manufacturer: Insights for atmospheric transport and establishment of priority list.

Tree bark has been proven as an effective passive air sampler, particularly where access to active sampling methods is limited. In this study, 60 target liquid crystal monomers (LCMs; comprising 10 cyanobiphenyl and analogs (CBAs), 13 biphenyl and analogs (BAs), and 37 fluorinated biphenyl and analogs (FBAs)) were analyzed in 34 tree barks collected from the vicinity of a liquid crystal display (LCD) manufacturer situated in the Pearl River Delta, South China. The concentrations of LCMs in tree barks ranged from 1400 to 16000 ng/g lipid weight, with an average of 5900 ng/g lipid weight. Generally, bark levels of BAs exponentially decreased within 5 km of the LCD manufacturer. The profiles of LCMs in tree barks are similar to previously reported patterns in gaseous phase, suggesting bark's efficacy as a sampler for gaseous LCMs. The inclusion of different congeners in existing studies on the environmental occurrence of LCMs has hindered the horizontal comparisons. Therefore, this study established a list of priority LCMs based on environmental monitoring data and the publicly accessible production data. This list comprised 146 LCMs, including 63 REACH registered LCMs that haven't been analyzed in any study and 56 belonging to 4 types of mainstream LCMs.

SFC active reconfiguration based on user mobility and resource demand prediction in dynamic IoT-MEC networks.

To achieve secure, reliable, and scalable traffic delivery, request streams in mobile Internet of Things (IoT) networks supporting Multi-access Edge Computing (MEC) typically need to pass through a service function chain (SFC) consisting of an ordered series of Virtual Network Functions (VNFs), and then arrive at the target application in the MEC for processing. The high mobility of users and the real-time variability of network traffic in IoT-MEC networks lead to constant changes in the network state, which results in a mismatch between the performance requirements of the currently deployed SFCs and the allocated resources. Meanwhile, there are usually multiple instances of the same VNF in the network, and proactively reconfiguring the deployed SFCs based on the network state changes to ensure high quality of service in the network is a great challenge. In this paper, we study the SFC Reconfiguration Strategy (SFC-RS) based on user mobility and resource demand prediction in IoT MEC networks, aiming to minimize the end-to-end delay and reconfiguration cost of SFCs. First, we model SFC-RS as Integer Linear Programming (ILP). Then, a user trajectory prediction model based on codec movement with attention mechanism and a VNF resource demand prediction model based on the Long Short-Term Memory (LSTM) network are designed to accurately predict user trajectories and node computational and storage resources, respectively. Based on the prediction results, a Prediction-based SFV Active Reconfiguration (PSAR) algorithm is proposed to achieve seamless SFC migration and routing update before the user experience quality degrades, ensuring network consistency and high quality service. Simulation results show that PSAR provides 51.28%, 28.60%, 21.75%, and 16.80% performance improvement over the existing TSRFCM, DDQ, OSA, and DPSM algorithms in terms of end-to-end delay reduction, and 33.32%, 18.94%, 67.42%, and 60.61% performance optimization in terms of reconfiguration cost reduction.

A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics.

3'UTR-APAs have been extensively studied, but intronic polyadenylations (IPAs) remain largely unexplored. We characterized the profiles of 22 260 IPAs in 9679 patient samples across 32 cancer types from the Cancer Genome Atlas cohort. By comparing tumor and paired normal tissues, we identified 180 ~ 4645 dysregulated IPAs in 132 ~ 2249 genes in each of 690 patient tumors from 22 cancer types that showed consistent patterns within individual cancer types. We selected 2741 genes that showed consistently patterns across cancer types, including 1834 pan-cancer tumor-enriched and 907 tumor-depleted IPA genes; the former were amply represented in the functional pathways such as deoxyribonucleic acid damage repair. Expression of IPA isoforms was associated with tumor mutation burden and patient characteristics (e.g. sex, race, cancer stages, and subtypes) in cancer-specific and feature-specific manners, and could be a more accurate prognostic marker than gene expression (summary of all isoforms). In summary, our study reveals the roles and the clinical relevance of tumor-associated IPAs.