Artificial Intelligence in battling infectious diseases: A transformative role.

It is widely acknowledged that infectious diseases have wrought immense havoc on human society, being regarded as adversaries from which humanity cannot elude. In recent years, the advancement of Artificial Intelligence (AI) technology has ushered in a revolutionary era in the realm of infectious disease prevention and control. This evolution encompasses early warning of outbreaks, contact tracing, infection diagnosis, drug discovery, and the facilitation of drug design, alongside other facets of epidemic management. This article presents an overview of the utilization of AI systems in the field of infectious diseases, with a specific focus on their role during the COVID-19 pandemic. The article also highlights the contemporary challenges that AI confronts within this domain and posits strategies for their mitigation. There exists an imperative to further harness the potential applications of AI across multiple domains to augment its capacity in effectively addressing future disease outbreaks.

The effect of probiotics supplementation on cancer-treatment complications: a critical umbrella review of interventional meta-analyses.

Cancer-related complications pose significant challenges in the management and treatment of patients with malignancies. Several meta-analyses have indicated improving effects of probiotics on cancer complications, while some studies have reported contentious findings. The purpose of the present study was to evaluate the efficacy of probiotics in addressing cancer complications, including diarrhea, mucositis, and infections, following chemotherapy, radiotherapy, and surgery. Relevant studies were searched in the PubMed, Scopus, Embase and Web of Science databases and Google Scholar up to September 2023. All meta-analyses addressing the effects of probiotics on all cancer treatments-induced complications including infection, diarrhea and oral mucositis were included. The pooled results were calculated using a random-effects model. Analyses of subgroups, sensitivity and publication bias were also conducted. The results revealed that the probiotics supplementation was effective on reduction of total cancer complications (OR:0.53; 95% CI: 0.44, 0.62, p < 0.001; I2=79.0%, p < 0.001), total infection rate (OR:0.47; 95%CI: 0.41, 0.52, p < 0.001; I2= 48.8%, p < 0.001); diarrhea (OR:0.50; 95%CI: 0.44, 0.57, p < 0.001; I2=44.4%, p = 0.023) and severe diarrhea (OR: 0.4; 95%CI: 0.27, 0.56, p < 0.001; I2=31.3%, p = 0.178), oral mucositis (OR: 0.76; 95%CI: 0.58, 0.94, p < 0.001; I2=95.5%, p < 0.001) and severe oral mucositis (OR:0.65, 95%CI: 0.58, 0.72 p < 0.001; I2=22.1%, p = 0.274). Multi strain probiotic (OR:0.49; 95%CI: 0.32, 0.65, p < 0.001; I2=90.7%, p < 0.001) were more efficacious than single strain (OR:0.73; 95%CI: 0.66, 0.81, p < 0.001; I2=0.00%, p = 0.786). The findings of the current umbrella meta-analysis provide strong evidence that probiotic supplementation can reduce cancer complications.

Focal length switchable metalens based on vanadium dioxide.

A metalens is a flat lens that can control the phase of light so that dispersed light can be reconcentrated. This study devised a tunable metalens with a switchable focal length based on the phase transition properties of vanadium dioxide (V O 2). The unit structure comprises three layers from bottom to top: gold, polyimide, and two square resonant rings. The metalens can not only transform incident x-polarized waves into y-polarized waves but also achieve beam focusing simultaneously. The designed metalens achieves polarization conversion efficiency at an operating frequency of 0.8 THz. In the insulating state of V O 2, the beam focal point is at L=1914µm; in the metallic state, the wave converges at L=982µm, closely aligning with the predetermined focal length. By controlling external temperature, focal point switching can be achieved, making it highly versatile in practical applications.

Mortality Study of Patients with Omicron Infection Before and After the Implementation of the New Crown Standard.

Objective: To investigate the mortality rate of patients with Omicron infection before and after the implementation of the new crown standard, and to evaluate the impact of new treatment protocols on the mortality rate of patients with Omicron infection. Methods: Clinical data of 1419 Omicron-infected patients treated in our hospital from April 10, 2022 to June 3, 2022 were collected(Patients diagnosed with Omicron infection who met the diagnostic criteria in the "Diagnosis and treatment protocol for novel coronavirus pneumonia (trial version 9)"15 and whose nasal/pharyngeal swab samples were typed as Omicron variants by laboratory viral genotyping). They were divided into the observation group (April 25 2022 - June 3 2022) and the control group (April 10 2022 - April 24 2022) before and after the implementation criteria. Clinical data of 1419 patients were collected and compared between the two groups on whether to use anticoagulant drugs, whether to use antiplatelet drugs, gender, whether to use new drugs of thymosin/thymus method, age, whether to use herbal medicine, whether to use Fuzheng prescription, blood routine, liver function, kidney function indicators, mortality of patients. Results: A total of 1419 patients were initially selected; 501 patients with incomplete information were excluded, and finally, 918 patients were included. According to the time period before and after the application criteria, they were divided into an observation group (586 cases) and a control group (332 cases). There were no statistically significant differences in gender, age, antiplatelet drug use, and herbal medicine use between the two groups (P < .05). However, there were significant differences in the use of anticoagulant drugs, thymidine/thymidine drugs, and Fu Zhengfang between the two groups. It was statistically significant that the mortality rate in the observation group (2.39)% was significantly lower than that in the control group (5.12)%. P < .05 White blood cell count, red blood cell ratio, lymphocyte count, hemoglobin, neutrophil count, and neutrophil ratio were not significantly different between the two groups (P < .05) .In comparison to the control group (4.92±8.00)10^9/L, the platelet count in the observation group (4.77±3.41)109/L was considerably lower. The difference was statistically significant (P < .05). The comparison of total bilirubin, total protein values and alkaline phosphatase values between the two groups was not significant (P < .05). In the observation group, albumin (38.71±6.39) g/L, glutamate transaminase (23.93±26.03) U/L, glutathione transaminase (26.12±25.53) U/L, gamma-glutamyltransferase (34.28±52.3) U/L, globulin values (28.13±5.55) g/L were significantly lower than those of the control group (36.66±7.08) g/L, (30.36±65.77) U/L, (33.29±49.72) U/L, (43.76±80.23) U/L, (29.85±5.67) g/L, the difference was statistically significant (P < .05). Between the two groups, there were no significant differences in the values of uric acid or creatinine (P > .05). Levels and uric acid readings did not differ significantly, P > .05. The difference between the urea values of the observation group (7.44±6.34 mmol/L) and the control group (8.75±7.51 mmol/L) was statistically significant (P < .05). Conclusion: After the implementation of the treatment protocol for COVID-19 (Trial Version 9), the number of death cases among patients with Omicron variant infection has significantly decreased. The treatment protocol is safe and feasible and can be widely applied in clinical settings..And it will further promote the development and administration of vaccines to prevent and control the spread of the novel coronavirus, reducing the occurrence of patients and death cases.

PKM2 is a Novel Osteoporosis-Associated Protein in Chinese.

Purpose:Osteoporosis is characterized by low bone mineral density (BMD) and high risk of osteoporotic fracture (OF). Peripheral blood monocytes (PBM) can differentiate into osteoclasts to resorb bone. This study was to identify PBM-expressed proteins significant for osteoporosis in Chinese Han elderly population (>65 years), and focused on two phenotypes of osteoporosis: low BMD and OF. METHODS: Label-free quantitative proteomics was employed to profile PBM proteome and to identify differentially expressed proteins (DEPs) between OF (N=27) vs. non-fractured (NF, N=24) subjects and between low BMD (N=12) vs. high BMD (N=12) subjects in women. Western blotting (WB) was conducted to validate differential expression, and ELISA to evaluate translational value for secretory protein of interest. RESULTS: We discovered 59 DEPs with fold change (FC)>1.3 (P<1×10-5), and validated the significant up-regulation of pyruvate kinase isozyme 2 (PKM2) with osteoporosis (P<0.001). PKM2 protein upregulation with OF was replicated with PBM in men (P=0.04). Plasma PKM2 protein level was significantly elevated with OF in an independent sample (N=100, FC=1.68, P=0.01). Pursuant functional assays showed that extracellular PKM2 protein supplement not only promoted monocyte trans-endothelial migration, growth, and osteoclast differentiation (marker gene expression), but also inhibited osteoblast growth, differentiation (ALP gene expression), and activity. CONCLUSION: The above findings suggest that PKM2 protein is a novel osteoporosis-associated functional protein in Chinese Han elderly population. It may serve as a risk biomarker and drug target for osteoporosis.

Evaluation of urban-rural difference in breast cancer mortality among Chinese women during 1987-2021: A hierarchical age-period-cohort analysis.

BACKGROUND: Breast cancer mortality varies in urban and rural areas in China. Studies have reported urban-rural difference across time period, however, the evaluation on urban-rural differences in age and birth cohort effects is limited. Our aim was to quantitatively assess urban-rural disparities in age, period and cohort effects in breast cancer mortality in China. METHODS: We collected age-specific breast cancer mortality rates for urban and rural females aged 20-84 years from 1987 to 2021. Hierarchical age-period-cohort (HAPC) models were used to evaluate the effect of area (urban, rural) on breast cancer mortality and investigate urban-rural differences in age, time period and birth cohort effects. RESULTS: We found a significant area (urban, rural) effect on breast cancer mortality in that rural females had a lower mortality risk than urban females [-0.25 (95 % confidence interval (CI): -0.32, -0.17)]. Age trajectories of mortality based on the HAPC model showed nonlinear trends with adjustment for area variable. The urban-rural difference in age effect appeared to be divergent with age, and urban women had higher mortality risk in the senior age group. The urban-rural difference in birth cohort effect indicated a reversal around the birth cohort group of 1962-1966, after which rural females had a higher mortality risk than urban females. CONCLUSION: The area (urban, rural) could affect breast cancer mortality among women, and the effect of urban-rural difference varies with age and birth cohort. To promote the health of urban and rural females, the gap between urban and rural areas should be shorten.

First-principles calculation of self-interstitial atom-impurity atom interactions in ferritic steel.

In this study, the interactions between self-interstitial atoms (SIA) and impurity atoms (Cu and P) in the body-centered cubic (bcc)-Fe matrix have been investigated using the first principles approach. The results show that Cu and P atoms are more prone to segregation on perpendicular and parallel surfaces containing dumbbell atoms, respectively. Next, by combining the charge density difference and considering the electronic structure and lattice distortion, the origin of the binding energy of complexes formed between SIA and impurity atoms was discussed. The results show that as the number of impurity atoms increases, the atomic bonds formed by the interactions between the impurity atoms decrease the binding energy between single impurity atoms and the matrix and reduce the strain field around them, resulting in an increase in the stability of the complexes. Comparison with previous experimental results revealed the reasons for the changes in atomic occupancy during the segregation of Cu and P atoms. The results provide insights into the behavior of impurity atoms in irradiated materials and provide a deeper understanding of the electron level of impurity atomization.

In silico development of a novel anti-mutation, multi-epitope mRNA vaccine against MPXV variants of emerging lineage and sub-lineages by using immunoinformatics approaches.

Over the past year, an unexpected surge in human monkeypox (hMPX) cases has been observed. This outbreak differs from previous ones, displaying distinct epidemiological characteristics and transmission patterns, believed to be influenced by a newly emerging monkeypox virus (MPXV) lineage. Notably, this emerging MPXV lineage has exhibited several non-synonymous mutations, some of which are linked to immunomodulatory activities and antigenic characteristics that aid in host detection. However, specific treatments or vaccines for human monkeypox are currently lacking. Hence, we aim to develop a multi-epitope mRNA vaccine by using immunoinformatics approaches against the MPXV, particularly its emerging variants. Six proteins (A29L, A35R, B6R, M1R, H3L, and E8L) were chosen for epitope and mutation site identification. Seventeen top-performing epitopes and eight epitopes containing mutation sites were selected and combined with adjuvants, the PADRE sequence, and linkers for vaccine development. The molecular and physical properties of the designed vaccine (WLmpx) were favorable. Immunological characteristics of WLmpx were assessed through molecular docking, molecular dynamics (MD) simulations, and immune simulations. Finally, the vaccine sequence was utilized to formulate an mRNA-based vaccine. The informatics-based predicted results indicated that the designed vaccine exhibits significant potential in eliciting high-level humoral and cellular immune responses, but further validation through in vivo and vitro studies is warranted.Communicated by Ramaswamy H. Sarma.

Machine learning surrogates for surface complexation model of uranium sorption to oxides.

The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change.

Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana's geographical distribution, including the driest month's precipitation, the coldest month's minimum temperature, the wettest month's precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

The response of sediment transport and morphological evolution to storms with different characteristics.

Strong wave-current interaction under the impact of storm events can induce a series of complex sedimentary processes of sediment resuspension and transport and morphology changes, significantly changing the topography of coastal zones. However, coastal sedimentary processes during storm events have not been fully understood. In this study, we developed a wave-current-sediment coupled model to investigate the response of dynamical processes to extreme storm events. The model was first validated against the observed data for both storm conditions during the 2007 Typhoon Wipha and fair-weather conditions in 2016 in the Haizhou Bay (HZB) of the Yellow Sea. The simulated results indicated that the longshore sediment transport was dominated originally by tidal effects which were significantly enhanced by wind-induced waves during the passage of the Typhoon Wipha. Storms with different characteristics correspond to two typical sedimentary dynamic response modes based on a series of numerical experiments. The tidal pumping effect (T3 + T4 + T5) and gravitational circulation term (T6) controlled the total storm-induced sediment flux, and T6 played a crucial and special role, typically in the opposite direction of the dominant wind of the storm. The strong wind could lead to the stratification of the water column, causing the down-slope or up-slope cross-shore sediment transport, resulting in coastal seabed erosion/deposition. In addition, the onshore wind was found to have a stronger impact on the sedimentary process. The methodology and findings of this study provide a scientific basis for understanding the response mechanism of sediment transport during storm events in coastal areas.

Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma: a step towards virtual biopsy.

OBJECTIVES: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour grading and staging in upper urothelial tract carcinoma patients and to compare these predictions with histopathological diagnosis used as reference standards. METHODS: Protocol-based computed tomographic urogram data from 106 patients were obtained and visualised in 3D. Digital segmentation of the tumours was conducted by extracting textural radiomics features. They were further classified using 11 predictive models. The predicted grades and stages were compared to the histopathology of radical nephroureterectomy specimens. RESULTS: Classifier models worked well in mining the radiomics data and delivered satisfactory predictive machine learning models. The multilayer panel showed 84% sensitivity and 93% specificity while predicting UTUC grades. The Logistic Regression model showed a sensitivity of 83% and a specificity of 76% while staging. Similarly, other classifier algorithms [e.g. Support Vector classifier (SVC)] provided a highly accurate prediction while grading UTUC compared to clinical features alone or ureteroscopic biopsy histopathology. CONCLUSION: Data mining tools could handle medical imaging datasets from small (<2 cm) tumours for UTUC. The radiomics-based machine learning algorithms provide a potential tool to model tumour grading and staging with implications for clinical practice and the upgradation of current paradigms in cancer diagnostics. CLINICAL RELEVANCE: Machine learning based on radiomics features can predict upper tract urothelial cancer grading and staging with significant improvement over ureteroscopic histopathology. The study showcased the prowess of such emerging tools in the set objectives with implications towards virtual biopsy.

Hydrological response of drought impacts across catchments worldwide.

Drought will inevitably affect linkages between different water components, which have previously been investigated across different spatiotemporal scales. Elucidating drought-induced precipitation (P) partition effects remain uncertain because they involve drought propagation, even inducing streamflow (Q) non-stationarity. This study collected data on 1069 catchments worldwide to investigate Q and evapotranspiration (ET) impacts from P deficit-derived reductions in drought propagation. Results show that P deficits trigger soil moisture drought, subsequently inducing negative Q and ET anomalies that vary under different climate regimes. Generally, drought-induced hydrological legacies indicate that breaks in hydrological linkages cause a relatively rapid Q response (i.e., negative Q anomaly), amplified by drought strength and duration. Compared with the Q response, the ET response to drought stress involves a more complex, associative vegetation response and an associative evaporative state controlled by water and energy, which lags behind the Q response and can also intensify with increasing drought severity and duration. This is confirmed by the ET response under different climate regimes. Namely, in drier climates, a positive ET anomaly can be detected in its early stages, this is unusual in wetter climate. Additionally, Q and ET sensitivity to drought strength can be mechanistically explained by the water and energy status. This implies that ET is mainly controlled by water and energy, resulting in higher and lower drought sensitivity within water- and energy-limited regions, respectively. Understanding the impacts of drought on Q and ET response is essential for identifying key linkages in drought propagation across different climate regimes. Our findings will also be useful for developing early warning and adaptation systems that support both human and ecosystem requirements.

Robust Ultrafast Projection Pipeline for Structural and Angiography Imaging of Fourier-Domain Optical Coherence Tomography.

The current methods to generate projections for structural and angiography imaging of Fourier-Domain optical coherence tomography (FD-OCT) are significantly slow for prediagnosis improvement, prognosis, real-time surgery guidance, treatments, and lesion boundary definition. This study introduced a robust ultrafast projection pipeline (RUPP) and aimed to develop and evaluate the efficacy of RUPP. RUPP processes raw interference signals to generate structural projections without the need for Fourier Transform. Various angiography reconstruction algorithms were utilized for efficient projections. Traditional methods were compared to RUPP using PSNR, SSIM, and processing time as evaluation metrics. The study used 22 datasets (hand skin: 9; labial mucosa: 13) from 8 volunteers, acquired with a swept-source optical coherence tomography system. RUPP significantly outperformed traditional methods in processing time, requiring only 0.040 s for structural projections, which is 27 times faster than traditional summation projections. For angiography projections, the best RUPP variation took 0.15 s, making it 7518 times faster than the windowed eigen decomposition method. However, PSNR decreased by 41-45% and SSIM saw reductions of 25-74%. RUPP demonstrated remarkable speed improvements over traditional methods, indicating its potential for real-time structural and angiography projections in FD-OCT, thereby enhancing clinical prediagnosis, prognosis, surgery guidance, and treatment efficacy.

Olfactory Ensheathing Cell Ameliorate Neuroinflammation Following Spinal Cord Injury Through Upregulating REV-ERBα in Microglia.

Circadian dysregulation involved in the pathophysiology of spinal cord injury (SCI). Modulation of circadian rhythms hold promise for the SCI treatment. Here, we aim to investigated the mechanism of olfactory ensheathing cells (OEC) in alleviating neuroinflammation via modulating clock gene expression in microglia. In this study, SCI rats were randomly divided into OEC group and vehicle group. At 1 day after the surgery, OECs were intravenously transplanted into OEC group SCI rat, while the rats in vehicle group received culture medium. After 7 days post of OEC transplantation, tissues were collected from the brain (prefrontal cortex, hypothalamus, spinal cord) for PCR, western blotting and immunohistochemistry (IHC) assay at zeitgeber time (ZT) 6, ZT 12, ZT 18, and ZT 24. The roles of OEC in modulating REV-ERBα in microglia were studied by experimental inhibition of gene expression and the co-culture experiment. In the vehicle group, IHC showed a significant increase of Iba-1 expression in the cerebral white matter and spinal cord compared with control group (P < 0.0001 for all comparisons). The expression of Iba-1 was significantly decreased (P < 0.0001 for all comparisons). In the OEC group, the expression of PER 1, PER 2, CLOCK, and REV-ERBα was in a rhythmical manner in both spinal cord and brain regions. SCI disrupted their typical rhythms. And OECs transplantation could modulate those dysregulations by upregulating REV-ERBα. In vitro study showed that OECs couldn't reduce the activation of REV-ERBα inhibited microglia. The intravenous transplantation of OECs can mediate cerebral and spinal microglia activation through upregulation REV-ERBα after SCI.

Forest fire risk zoning based on fuzzy logic and analytical network process.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

Characteristics of Klebsiella pneumoniae pyogenic liver abscess from 2010-2021 in a tertiary teaching hospital of South China.

OBJECTIVES: Pyogenic liver abscess (PLA) is a severe and potentially fatal infectious disease. Klebsiella pneumoniae (K. pneumoniae) is the predominant pathogen responsible for PLA. This study aims to investigate the clinical characteristics and prognostic factors of K. pneumoniae-induced pyogenic liver abscess (KP-PLA), particularly those caused by carbapenem-resistant K. pneumoniae (CRKP). METHODS: Analyses were performed on PLA patients from January 2010 to December 2021, to investigate the differences of K. pneumoniae from other etiologically infected PLA patients. Univariate and multivariate logistic regression analyses were used to compare prognostic factors between patients with carbapenem-resistant K. pneumoniae PLA (CRKP-PLA) and patients with carbapenem-sensitive K. pneumoniae PLA. RESULTS: Univariate analysis demonstrated a significant association between KP-PLA and factors including diabetes mellitus (P < 0.001), cholecystitis and cholelithiasis (P = 0.032), single abscess (P = 0.016), and abscesses with a diameter over 50 mm (P = 0.004). The CRKP group exhibited a higher prevalence of therapeutic interventions before K. pneumoniae infection, including abdominal surgery, mechanical ventilation, sputum suction, tracheal cannula, routine drainage of the abdominal cavity, and peripherally inserted central venous catheters (P < 0.05). Multivariate logistic regression analysis revealed that admission to the intensive care unit was an independent risk factor associated with CRKP-PLA (odds ratio 36; 95% confidence interval 1.77-731.56; P = 0.020). CONCLUSION: The KP-PLA patients were significantly associated with diabetes and were more likely to have single abscesses larger than 50 mm. PLA patients with a history of admission to intensive care unit or invasive therapeutic procedures should be given special consideration if combined with CRKP infection.

A Fast-scanning Protocol of Optical Coherence Tomography Angiography Based on Structure-Aware Attention.

Oral diseases have imposed a heavy social and financial burden on many countries and regions. If left untreated, severe cases can lead to malignant tumours. Common devices can no longer meet the high-resolution and non-invasive requirement, while Optical Coherence Tomography Angiography (OCTA) provides an ideal perspective for detecting vascular microcirculation. However, acquiring high-quality OCTA images takes time and can result in unpredictable motion artefacts. Therefore, we propose a systematic workflow for rapid OCTA data acquisition. Initially, we implement a fourfold reduction in sampling points to enhance the scanning speed. Then, we apply a deep neural network for rapid image reconstruction, elevating the resolution to the level achieved through full scanning. Specifically, it is a hybrid attention model with a structure-aware loss to extract local and global information on angiography, which improves the visualisation performance and quantitative metrics of numerous classical and recent-presented models by 3.536%-9.943% in SSIM and 0.930%-2.946% in MS-SSIM. Through this approach, the time of constructing one OCTA volume can be reduced from nearly 30 s to about 3 s. The rapid-scanning protocol of high-quality imaging also presents feasibility for future real-time detection applications.

pH-Responsive polymer boosts cytosolic siRNA release for retinal neovascularization therapy.

Small interfering RNA (siRNA) has a promising future in the treatment of ocular diseases due to its high efficiency, specificity, and low toxicity in inhibiting the expression of target genes and proteins. However, due to the unique anatomical structure of the eye and various barriers, delivering nucleic acids to the retina remains a significant challenge. In this study, we rationally design PACD, an A-B-C type non-viral vector copolymer composed of a hydrophilic PEG block (A), a siRNA binding block (B) and a pH-responsive block (C). PACDs can self-assemble into nanosized polymeric micelles that compact siRNAs into polyplexes through simple mixing. By evaluating its pH-responsive activity, gene silencing efficiency in retinal cells, intraocular distribution, and anti-angiogenesis therapy in a mouse model of hypoxia-induced angiogenesis, we demonstrate the efficiency and safety of PACD in delivering siRNA in the retina. We are surprised to discover that, the PACD/siRNA polyplexes exhibit remarkable intracellular endosomal escape efficiency, excellent gene silencing, and inhibit retinal angiogenesis. Our study provides design guidance for developing efficient nonviral ocular nucleic acid delivery systems.

A signature based on circadian rhythm-associated genes for the evaluation of prognosis and the tumour microenvironment in HNSCC.

The morbidity and mortality rates of head and neck squamous cell carcinoma (HNSCC) remain high worldwide. Therefore, there is an urgent need to identify a new prognostic biomarker to guide the personalized treatment of HNSCC patients. Increasing evidence suggests that circadian rhythm genes play an important role in the development and progression of cancer. We aimed to explore the value of circadian rhythm genes in predicting prognosis and guiding the treatment of HNSCC. We first obtained a list of circadian rhythm genes from previous research. The sequencing data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Finally, univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox proportional hazard analysis were performed to develop a prognostic signature (Circadian Rhythm-Related Gene Prognostic Index, CRRGPI) consisting of nine circadian rhythm genes. The signature exhibited good performance in predicting overall survival. Patients with low CRRGPI scores had lower metabolic activities and an active antitumour immunity ability. Additionally, a clinical cohort was used to further evaluate the ability of the CRRGPI to predict the efficacy of immune checkpoint inhibitors. In conclusion, the novel circadian rhythm-related gene signature can provide a precise prognostic evaluation with the potential capacity to guide individualized treatment regimens for HNSCC patients.