The ankle-brachial index, gastrocnemius mitochondrial respirometry, and walking performance in people with and without peripheral artery disease.

Background: Mitochondrial abnormalities exist in lower-extremity peripheral artery disease (PAD), yet the association of the ankle-brachial index (ABI) with mitochondrial respiration in gastrocnemius muscle is unknown. The association of gastrocnemius mitochondrial respiration with 6-minute walk distance in PAD is unknown. Objective: To describe associations of the ABI with mitochondrial respiratory function in gastrocnemius muscle biopsies and associations of gastrocnemius mitochondrial respirometry with 6-minute walk distance in people with and without PAD. Methods: People with (ABI ⩽ 0.90) and without (ABI 1.00-1.40) PAD were enrolled. ABI and 6-minute walk distance were measured. Mitochondrial function of permeabilized myofibers from gastrocnemius biopsies was measured with high-resolution respirometry. Results: A total of 30 people with PAD (71.7 years, mean ABI: 0.64) and 68 without PAD (71.8 years, ABI: 1.17) participated. In non-PAD participants, higher ABI values were associated significantly with better mitochondrial respiration (Pearson correlation for maximal oxidative phosphorylation PCI+II: +0.29, p = 0.016). In PAD, the ABI correlated negatively and not significantly with mitochondrial respiration (Pearson correlation for PCI+II: -0.17, p = 0.38). In people without PAD, better mitochondrial respiration was associated with better 6-minute walk distance (Pearson correlation: +0.51, p < 0.001), but this association was not present in PAD (Pearson correlation: +0.10, p = 0.59). Conclusions: Major differences exist between people with and without PAD in the association of gastrocnemius mitochondrial respiration with ABI and 6-minute walk distance. Among people without PAD, ABI and walking performance were positively associated with mitochondrial respiratory function. These associations were not observed in PAD.

Rhein and hesperidin nanoparticles remodel tumor immune microenvironment by reducing CAFs and CCL2 secreted by CAAs for efficient triple-negative breast cancer therapy.

In triple-negative breast cancer (TNBC), the tumor immune microenvironment (TIME) is a highly heterogeneous ecosystem that exerts indispensable roles in tumorigenesis and tumor progression. Cancer-associated fibroblasts (CAFs) and cancer-associated adipocytes (CAAs) are the main matrix components in the TIME of TNBC. CAFs mediate the edesmoplastic response, which is a major driver of the immunosuppressive microenvironment to promote tumor growth. In addition, CAAs, a type of tumor-educated adipocyte, participate in crosstalk with breast cancer and are capable of secreting various cytokines, adipokines and chemokines, especially C-C Motif Chemokine Ligand 2 (CCL2), resulting in changes of cancer cell phenotype and function. Therefore, how to treat tumors by regulating the CAFs and the secretion of CCL2 by CAAs in TIME is investigated here. Our research group previously found that rhein (Rhe) has been identified as effective against CAFs, while hesperidin (Hes) could effectively diminish CCL2 secretion by CAAs. Inspired by the above, we developed unique PLGA-based nanoparticles loaded with Rhe and Hes (RH-NP) using the emulsion solvent diffusion method. The RH-NP particles have an average size of 114.1 ± 0.98 nm. RH-NP effectively reduces CAFs and inhibits CCL2 secretion by CAAs, promoting increased infiltration of cytotoxic T cells and reducing immunosuppressive cell presence within tumors. This innovative, safe, low-toxic, and highly effective anti-tumor strategy could be prospective in TNBC treatment.

Assessing the impact of vaccination and medical resource allocation on infectious disease outbreak management: a case study of COVID-19 in Taiyuan City.

Introduction: Amidst an emerging infectious disease outbreak, the rational allocation of vaccines and medical resources is crucial for controlling the epidemic's progression. Method: Analysing COVID-19 data in Taiyuan City from December 2022 to January 2023, this study constructed a S V 1 V 2 V 3 E I Q H R dynamics model to assess the impact of COVID-19 vaccination and resource allocation on epidemic trends. Results: Vaccination significantly reduces infection rates, hospitalisations, and severe cases, while also curtailing strain on medical resources by reducing congestion periods. An early and sufficient reserve of medical resources can delay the onset of medical congestion, and with increased maximum capacity of medical resources, the congestion's end can be accelerated. Stronger resource allocation capabilities lead to earlier congestion resolution within a fixed total resource pool. Discussion: Integrating vaccination and medical resource allocation can effectively reduce medical congestion duration and alleviate the epidemic's strain on medical resource capacity (CCMR).

Curcumin nanopreparations: recent advance in preparation and application.

Curcumin is a natural polyphenolic compound extracted from turmeric with antibacterial, antioxidant, antitumor, preventive and therapeutic neurological disorders and a variety of bioactivities, which is widely used in the field of food and medicine. However, the drawbacks of curcumin such as poor aqueous solubility and stability have limited the practical application of curcumin. To overcome these defects and enhance its functional properties, various nanoscale systems (liposomes, polymer nanoparticles, protein nanoparticles, solid lipid nanoparticles, metal nanoparticles, etc) have been extensively employed for curcumin encapsulation and delivery. Despite the rapid development of curcumin nanoformulations, there is a lack of comprehensive reviews on their preparation and properties. This review provides an overview of the construction of curcumin nano-delivery systems, mechanisms of action, nanocarrier preparation methods and the applications of curcumin nanocarriers in the food and pharmaceutical fields to provide a theoretical basis and technological support for the efficient bio-utilization, product development and early clinical application of curcumin.

Nano-mediated strategy: recent advance in the application of drug delivery systems in melanoma treatment and diagnosis.

Melanoma is a common malignant tumor, with a five-year mortality rate as high as 62% in cases of metastatic melanoma according to cancer statistics (2024). In recent years, the focus of melanoma research has predominantly centered on immunotherapy and targeted therapy, grappling with challenges such as resistance and immunogenicity. The discovery of nanoparticles (NPs) has brought nano-delivery systems to the forefront of melanoma diagnosis and treatment. Although certain NPs, like liposomes, have gained clinical approval, utilizing most nano-delivery systems for melanoma diagnosis and treatment remains largely exploratory. The inherent limitations of NPs present a major obstacle to their clinical translation. By selecting suitable nanocarriers and functionalizing NPs to optimize nano-delivery systems, and combining these systems with other therapies, it is possible to reduce the systemic toxicity and resistance associated with conventional therapies and the NPs themselves. This optimization could significantly improve the effectiveness of nano-delivery systems in the early detection and timely treatment of melanoma. However, there have been few reviews on the optimization of NPs and the combined application of other therapies in the treatment and diagnostic application of melanoma in the past three years. This review summarizes the latest applications of nano-delivery systems in the diagnosis and treatment of melanoma over the past three years, including innovations and achievements in both preclinical and clinical studies, offering new perspectives on their potential and future application prospects. It integrates clinical data and patent information, highlights trends in nano-delivery system development, and offers new insights into their clinical translation. Additionally, it discusses the challenges and opportunities of nano-delivery systems in melanoma treatment, providing a foundation for advancing their application in diagnosis, treatment, and clinical translation.

Temporal Variations in Fire Impacts on Characteristics and Composition of Soil-Derived Dissolved Organic Matter at Qipan Mountain, China.

Dissolved organic matter (DOM), the most reactive fraction of forest soil organic matter, is increasingly impacted by wildfires worldwide. However, few studies have quantified the temporal changes in soil DOM quantity and quality after fire. Here, soil samples were collected after the Qipan Mountain Fire (3-36 months) from pairs of burned and unburned sites. DOM contents and characteristics were analyzed using carbon quantification and various spectroscopic and spectrometric techniques. Compared with the unburned sites, burned sites showed higher contents of bulk DOM and most DOM components 3 months after the fire but lower contents of them 6-36 months after the fire. During the sharp drop of DOM from 3 to 6 months after the fire, carboxyl-rich alicyclic molecule-like and highly unsaturated compounds had greater losses than condensed aromatics. Notably, the burned sites had consistently higher abundances of oxygen-poor dissolved black nitrogen and fluorescent DOM 3-36 months after the fire, particularly the abundance of pyrogenic C2 (excitation/emission maxima of <250/∼400 nm) that increased by 150% before gradually declining. This study advances the understanding of temporal variations in the effects of fire on different soil DOM components, which is crucial for future postfire environmental management.

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vision impairment, cardiovascular disorders, and susceptibility to infections, leading to significant physical suffering and imposing substantial socio-economic burdens. This condition has evolved into an increasingly severe health crisis. There is an urgent need to develop new treatments with improved efficacy and fewer adverse effects to meet clinical demands. However, novel drug development is costly, time-consuming, and often associated with side effects and suboptimal efficacy, making it a major challenge. Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized drug development across its comprehensive lifecycle, spanning drug discovery, preclinical studies, clinical trials, and post-market surveillance. These technologies have significantly accelerated the identification of promising therapeutic candidates, optimized trial designs, and enhanced post-approval safety monitoring. Recent advances in AI, including data augmentation, interpretable AI, and integration of AI with traditional experimental methods, offer promising strategies for overcoming the challenges inherent in AI-based drug discovery. Despite these advancements, there exists a notable gap in comprehensive reviews detailing AI and ML applications throughout the entirety of developing medications for diabetes mellitus. This review aims to fill this gap by evaluating the impact and potential of AI and ML technologies at various stages of diabetes mellitus drug development. It does that by synthesizing current research findings and technological advances so as to effectively control diabetes mellitus and mitigate its far-reaching social and economic impacts. The integration of AI and ML promises to revolutionize diabetes mellitus treatment strategies, offering hope for improved patient outcomes and reduced healthcare burdens worldwide.

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson's disease.

BACKGROUND: Sleep fragmentation is a persistent problem throughout the course of Parkinson's disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear. METHOD: We recorded subthalamic nucleus (STN) local field potentials (LFPs) using deep brain stimulation (DBS) with real-time wireless recording capacity from 13 patients with PD undergoing a one-night polysomnography recording, 1 month after DBS surgery before initial programming and when the patients were off-medication. The STN LFP features that characterised different sleep stages, correlated with arousal and sleep fragmentation index, and preceded stage transitions during N2 and REM sleep were analysed. RESULTS: Both beta and low gamma oscillations in non-rapid eye movement (NREM) sleep increased with the severity of sleep disturbance (arousal index (ArI)-betaNREM: r=0.9, p=0.0001, sleep fragmentation index (SFI)-betaNREM: r=0.6, p=0.0301; SFI-gammaNREM: r=0.6, p=0.0324). We next examined the low-to-high power ratio (LHPR), which was the power ratio of theta oscillations to beta and low gamma oscillations, and found it to be an indicator of sleep fragmentation (ArI-LHPRNREM: r=-0.8, p=0.0053; ArI-LHPRREM: r=-0.6, p=0.0373; SFI-LHPRNREM: r=-0.7, p=0.0204; SFI-LHPRREM: r=-0.6, p=0.0428). In addition, long beta bursts (>0.25 s) during NREM stage 2 were found preceding the completion of transition to stages with more cortical activities (towards Wake/N1/REM compared with towards N3 (p<0.01)) and negatively correlated with STN spindles, which were detected in STN LFPs with peak frequency distinguishable from long beta bursts (STN spindle: 11.5 Hz, STN long beta bursts: 23.8 Hz), in occupation during NREM sleep (ß=-0.24, p<0.001). CONCLUSION: Features of STN LFPs help explain neurophysiological mechanisms underlying sleep fragmentations in PD, which can inform new intervention for sleep dysfunction. TRIAL REGISTRATION NUMBER: NCT02937727.

Alterations in Synaptic Connectivity and Synaptic Transmission in Alzheimer's Disease with High Physical Activity.

Background: Alzheimer's disease (AD) is a progressive neurodegeneration disease. Physical activity is one of the most promising modifiable lifestyles that can be effective in slowing down the progression of AD at an early stage. Objective: Explore the molecular processes impaired in AD that were conversely preserved and enhanced by physical activity. Methods: Integrated transcriptomic analyses were performed in datasets that contain AD patients and elders with different degrees of physical activity. The changes of the hub genes were validated through analyzing another two datasets. The expression of the hub genes was further detected in the hippocampus and cortexes of APP/PS1 transgenic mice with or without physical activity by Quantitative polymerase chain reaction (qPCR). Results: Cross-comparison highlighted 195 DEGs displaying opposed regulation patterns between AD and high physical activity (HPA). The common DEGs were predominantly involved in synaptic vesicle recycling and synaptic transmission, largely downregulated in AD patients but upregulated in the elders with HPA. Two key modules and four hub genes that were related to synaptic vesicle turnover were obtained from the PPI network. The expression of these hub genes (SYT1, SYT4, SH3GL2, and AP2M1) was significantly decreased in AD transgenic mice and was reversed by HPA training. Conclusions: HPA may reverse AD pathology by upregulating a range of synaptic vesicle transport related proteins which might improve the efficiency of synaptic vesicle turnover and facilitate inter-neuronal information transfer. The study provides novel insights into the mechanisms underlining the protective effects of HPA on AD.

Protective effect and mechanism of Qingfei Paidu decoction on myocardial damage mediated by influenza viruses.

Introduction: Significant attention has been paid to myocardial damage mediated by the single-stranded RNA virus. Qingfei Paidu decoction (QFPDD) has been proved to protect the damage caused by the influenza virus A/PR/8/1934 (PR8), but its specific mechanism is unclear. Methods: Molecular biological methods, together with network pharmacology, were used to analyze the effects and underlying mechanism of QFPDD treatment on PR8-induced myocardial damage to obtain insights into the treatment of COVID-19-mediated myocardial damage. Results: Increased apoptosis and subcellular damage were observed in myocardial cells of mice infected by PR8. QFPDD treatment significantly inhibited the apoptosis and subcellular damage induced by the PR8 virus. The inflammatory factors IFN-ß, TNF-α, and IL-18 were statistically increased in the myocardia of the mice infected by PR8, and the increase in inflammatory factors was prevented by QFPDD treatment. Furthermore, the expression levels or phosphorylation of necroptosis-related proteins RIPK1, RIPK3, and MLKL were abnormally elevated in the group of infected mice, while QFPDD restored the levels or phosphorylation of these proteins. Our study demonstrated that HIF-1α is a key target of QFPDD in the treatment of influenza virus-mediated injury. The HIF-α level was significantly increased by PR8 infection. Both the knockdown of HIF-1α and treatment of the myocardial cell with QFPDD significantly reversed the increased inflammatory factors during infection. Overexpression of HIF-1α reversed the inhibition effects of QFPDD on cytokine expression. Meanwhile, seven compounds from QFPDD may target HIF-1α. Conclusion: QFPDD can ameliorate influenza virus-mediated myocardial damage by reducing the degree of cell necroptosis and apoptosis, inhibiting inflammatory response and the expression of HIF-1α. Thus, our results provide new insights into the treatment of respiratory virus-mediated myocardial damage.

Rhein potentiates doxorubicin in treating triple negative breast cancer by inhibiting cancer-associated fibroblasts.

Cancer-associated fibroblasts (CAFs), one of the most abundant stromal cells in the tumor microenvironment, mediate desmoplastic responses. CAFs are major drivers for the failure of triple-negative breast cancer (TNBC) chemotherapy. It is well-documented that many traditional Chinese medicines (TCMs) exhibit potent anti-fibrotic effects based on their capacity to suppress the production of ECM proteins. Therefore, the combination of TCMs exhausting CAFs with chemotherapy is a potential regimen for treating TNBC. Here, TGF-ß was used to induce the transformation of NIH/3T3 cells into CAFs for screening TCMs to inhibit tumor fibrosis. After screening 11 candidate TCMs for inhibiting CAFs using the TMS method, rhein (Rhe) was found to strongly inhibit the proliferation of CAFs. Therefore, Rhe was chosen as a representative TCM to inhibit CAFs in TNBC. A 4T1Fluc/CAFs tumor sphere resembling the TME in vivo was constructed to explore the feasibility of inhibiting CAFs to sensitize DOX in treating TNBC. It was found that CAFs apparently hindered the penetration of DOX into 4T1Fluc/CAFs tumor spheres and decreased the the sensitivity of 4T1Fluc cells to DOX, while Rhe significantly restored the sensitivity of 4T1Fluc cells to DOX by inhibiting the proliferation of CAFs. Consistent with in vitro results, Rhe reversed the abnormal activation of CAFs and diminished the accumulation of collagen in 4T1Fluc mouse xenograft models. This removal of stromal barrier facilitated the antitumor efficacy of DOX. Altogether, this study demonstrated for the first time that Rhe could inhibit tumor tissue fibrosis and synergize DOX to treat TNBC.

Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China.

BACKGROUND: In 2022, Omicron outbreaks occurred at multiple sites in China. It is of great importance to track the incidence trends and transmission dynamics of coronavirus disease 2019 (COVID-19) to guide further interventions. METHODS: Given the population size, economic level and transport level similarities, two groups of outbreaks (Shanghai vs. Chengdu and Sanya vs. Beihai) were selected for analysis. We developed the SEAIQRD, ARIMA, and LSTM models to seek optimal modeling techniques for waves associated with the Omicron variant regarding data predictive performance and mechanism transmission dynamics, respectively. In addition, we quantitatively modeled the impacts of different combinations of more stringent interventions on the course of the epidemic through scenario analyses. RESULTS: The best-performing LSTM model showed better prediction accuracy than the best-performing SEAIQRD and ARIMA models in most cases studied. The SEAIQRD model had an absolute advantage in exploring the transmission dynamics of the outbreaks. Regardless of the time to inflection point or the time to Rt curve below 1.0, Shanghai was later than Chengdu (day 46 vs. day 12/day 54 vs. day 14), and Sanya was later than Beihai (day 16 vs. day 12/day 20 vs. day 16). Regardless of the number of peak cases or the cumulative number of infections, Shanghai was higher than Chengdu (34,350 vs. 188/623,870 vs. 2,181), and Sanya was higher than Beihai (1,105 vs. 203/16,289 vs. 3,184). Scenario analyses suggested that upgrading control level in advance, while increasing the index decline rate and quarantine rate, were of great significance for shortening the time to peak and Rt below 1.0, as well as reducing the number of peak cases and final affected population. CONCLUSIONS: The LSTM model has great potential for predicting the prevalence of Omicron outbreaks, whereas the SEAIQRD model is highly effective in revealing their internal transmission mechanisms. We recommended the use of joint interventions to contain the spread of the virus.

Temperature Thresholds of Pyrogenic Dissolved Organic Matter in Heating Experiments Simulating Forest Fires.

Heating temperature (HT) during forest fires is a critical factor in regulating the quantity and quality of pyrogenic dissolved organic matter (DOM). However, the temperature thresholds at which maximum amounts of DOM are produced (TTmax) and at which the DOC gain turns into net DOC loss (TT0) remain unidentified on a component-specific basis. Here, based on solid-state 13C nuclear magnetic resonance, absorbance and fluorescence spectroscopies, and Fourier transform ion cyclotron resonance mass spectrometry, we analyzed variations in DOM composition in detritus and soil with HT (150-500 °C) and identified temperature thresholds for components on structural, fluorophoric, and molecular formula levels. TTmax was similar for detritus and soil and ranged between 225 and 250 °C for bulk dissolved organic carbon (DOC) and most DOM components. TT0 was consistently lower in detritus than in soil. Moreover, temperature thresholds differed across the DOM components. As the HT increased, net loss was observed initially in molecular formulas tentatively associated with carbohydrates and aliphatics, then proteins, peptides, and polyphenolics, and ultimately condensed aromatics. Notably, at temperatures lower than TT0, particularly at TTmax, burning increased the DOC quantity and thus might increase labile substrates to fuel soil microbial community. These composition-specific variations of DOM with temperature imply nonlinear and multiple temperature-dependent wildfire impacts on soil organic matter properties.

Integrated animal experiments and network pharmacology for investigating therapeutic effect of celastrol-loaded liposomes on NAFLD.

BACKGROUND: The prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) is closely related to the increase of the incidence rate of obesity. AIMS: To find out the targets of celastrol on NAFLD with the treatment of celastrol-loaded liposomes (Cel-Lips). METHODS: Gene Expression Omnibus (GEO) data were used to compare the expression of differential genes in NAFLD patients with normal individuals. Celastrol was loaded into liposomes to improve its solubility, as well as, achieving a passive targeting effect on the liver to improve the availability, which also could delay the release rate of celastrol to prolong the action time and thus reduce the frequency of administration. Due to rarely reported molecular mechanisms of celastrol, with the help of network pharmacological analysis, the targets of celastrol acting on NAFLD were predictively analyzed. RESULTS: An association between NAFLD and lipid metabolism was detected in GEO data. Cel-Lips significantly alleviated NAFLD in vivo. Through network pharmacology, it was found that most of the action pathways of celastrol were related to lipid metabolism. CONCLUSION: Celastrol has the potential to treat NAFLD, and its possible targets have been identified through network pharmacological screening, which provides a certain basis for the follow-up researches.

Exploring the Mechanism of Single-Crystal MnO2 as Cathodes for Zinc Ion Batteries.

MnO2 has the advantages of low cost and abundant resources, so it is considered to be an important electrode material in zinc ion batteries. However, its practical application is still challenged by easy collapse and capacity loss. In this paper, a stable single crystal ß-MnO2 nanorod cathode material was prepared. When used as ZIBs cathode material, single crystal ß-MnO2 has high ionic diffusion kinetics and calculability. In this paper, we prepared single-crystal MnO2 through hydrothermal nanotechnology. By leveraging the benefits of the single-crystal structure, we optimized the structural stability, ion conductivity, surface reactions, and phase control of the cathode material, resulting in improved battery performance and cycle life. In the fabricated single-crystal MnO2 aqueous zinc-ion battery, the elimination of internal crystal faces in MnO2 leads to ordered lattice arrangement, enabling a more direct and unobstructed diffusion path for H+ ions within the lattice. This significantly enhances the ion conductivity of the cathode material, promoting the rate and efficiency of the battery's charge and discharge processes. Therefore, single-crystal MnO2 exhibits excellent cycling performance for zinc-ion storage in ZIBs, achieving a high specific capacity of 224.7 mA h g-1 after 250 cycles under a current density of 0.3 A g-1 , while maintaining a Coulombic efficiency of 99.58 %.

Altered gut microbiota-host bile acid metabolism in IBS-D patients with liver depression and spleen deficiency pattern.

BACKGROUND: Dysregulation of gut microbiota-host bile acid (BA) co-metabolism is a critical pathogenic factor of diarrhea-predominant irritable bowel syndrome (IBS-D). Traditional Chinese Medicine (TCM), instructed by pattern differentiation, is effective in treating IBS-D, in which liver depression and spleen deficiency (LDSD) is the most prevalent pattern. Still, it is unclear the linkage between the LDSD pattern and the BA metabolic phenotype. PURPOSE: This study aimed to uncover the biological basis of the LDSD pattern from the BA metabolic perspective. METHODS: Patients with IBS-D completed questionnaires regarding the irritable bowel severity scoring system (IBS-SSS), stool frequency, Stool Bristol scale, and Self-Rating Scales of mental health. Fasting blood and morning feces were collected to analyze the gut metagenome and BA-related indices/metabolites. RESULTS: IBS-D patients with LDSD had a higher incidence of BA overexcretion (41% vs. 23% non-LDSD) with significant elevations in fecal total BAs and serum BA precursor 7α-hydroxy-4-cholesten-3-one levels. Compared to controls or non-LDSD patients, LDSD patients had a featured fecal BA profile, with higher proportions of deoxycholic acid (DCA), 7-ketodeoxycholic acid, and lithocholic acid. It is consistent with the BA-metabolizing genomic changes in the LDSD gut microbiota characterized by overabundances of 7-dehydroxylating bacteria and BA-inducible genes (baiCD/E/H). The score of bowel symptoms (stool frequency and abdominal pain) showing greater severity in the LDSD pattern were positively correlated with bai-expressing bacterial abundances and fecal DCA levels separately. CONCLUSION: We clarified a differed BA metabolic phenotype in IBS patients with LDSD, which closely correlates with the severity of bowel symptoms. It demonstrates that gut microbiota and host co-metabolism of BAs would provide crucial insight into the biology of the LDSD pattern and its internal relationship with IBS progression.

Epidemiological characteristics and transmission dynamics of the COVID-19 outbreak in Hohhot, China: a time-varying SQEIAHR model analysis.

Background: On September 28, 2022, the first case of Omicron subvariant BF.7 was discovered among coronavirus disease 2019 (COVID-19) infections in Hohhot, China, and then the epidemic broke out on a large scale during the National Day holiday. It is imminently necessary to construct a mathematical model to investigate the transmission dynamics of COVID-19 in Hohhot. Methods: In this study, we first investigated the epidemiological characteristics of COVID-19 cases in Hohhot, including the spatiotemporal distribution and sociodemographic distribution. Then, we proposed a time-varying Susceptible-Quarantined Susceptible-Exposed-Quarantined Exposed-Infected-Asymptomatic-Hospitalized-Removed (SQEIAHR) model to derive the epidemic curves. The next-generation matrix method was used to calculate the effective reproduction number (Re). Finally, we explored the effects of higher stringency measures on the development of the epidemic through scenario analysis. Results: Of the 4,889 positive infected cases, the vast majority were asymptomatic and mild, mainly concentrated in central areas such as Xincheng District. People in the 30-59 age group primarily were affected by the current outbreak, accounting for 53.74%, but females and males were almost equally affected (1.03:1). Community screening (35.70%) and centralized isolation screening (26.28%) were the main ways to identify positive infected cases. Our model predicted the peak of the epidemic on October 6, 2022, the dynamic zero-COVID date on October 15, 2022, a number of peak cases of 629, and a cumulative number of infections of 4,963 (95% confidential interval (95%CI): 4,692 ~ 5,267), all four of which were highly consistent with the actual situation in Hohhot. Early in the outbreak, the basic reproduction number (R0) was approximately 7.01 (95%CI: 6.93 ~ 7.09), and then Re declined sharply to below 1.0 on October 6, 2022. Scenario analysis of higher stringency measures showed the importance of decreasing the transmission rate and increasing the quarantine rate to shorten the time to peak, dynamic zero-COVID and an Re below 1.0, as well as to reduce the number of peak cases and final affected population. Conclusion: Our model was effective in predicting the epidemic trends of COVID-19, and the implementation of a more stringent combination of measures was indispensable in containing the spread of the virus.

Relaxin-encapsulated polymeric metformin nanoparticles remodel tumor immune microenvironment by reducing CAFs for efficient triple-negative breast cancer immunotherapy.

Cancer-associated fibroblasts (CAFs) are one of the most abundant stromal cells in the tumor microenvironment which mediate desmoplastic response and are the primary driver for an immunosuppressive microenvironment, leading to the failure of triple-negative breast cancer (TNBC) immunotherapy. Therefore, depleting CAFs may enhance the effect of immunotherapy (such as PD-L1 antibody). Relaxin (RLN) has been demonstrated to significantly improve transforming growth factor-ß (TGF-ß) induced CAFs activation and tumor immunosuppressive microenvironment. However, the short half-life and systemic vasodilation of RLN limit its in vivo efficacy. Here, plasmid encoding relaxin (pRLN) to locally express RLN was delivered with a new positively charged polymer named polymeric metformin (PolyMet), which could increase gene transfer efficiency significantly and have low toxicity that have been certified by our lab before. In order to improve the stability of pRLN in vivo, this complex was further formed lipid poly-γ-glutamic acid (PGA)/PolyMet-pRLN nanoparticle (LPPR). The particle size of LPPR was 205.5 ± 2.9 nm, and the zeta potential was +55.4 ± 1.6 mV. LPPR displayed excellent tumor penetrating efficacy and weaken proliferation of CAFs in 4T1luc/CAFs tumor spheres in vitro. In vivo, it could reverse aberrantly activated CAFs by decreasing the expression of profibrogenic cytokine and remove the physical barrier to reshape the tumor stromal microenvironment, which enabled a 2.2-fold increase in cytotoxic T cell infiltration within the tumor and a decrease in immunosuppressive cells infiltration. Thus, LPPR was observed retarded tumor growth by itself in the 4T1 tumor bearing-mouse, and the reshaped immune microenvironment further led to facilitate antitumor effect when it combined with PD-L1 antibody (aPD-L1). Altogether, this study presented a novel therapeutic approach against tumor stroma using LPPR to achieve a combination regimen with immune checkpoint blockade therapy against the desmoplastic TNBC model.

Epidemiological characteristics, spatial clusters and monthly incidence prediction of hand, foot and mouth disease from 2017 to 2022 in Shanxi Province, China.

Hand, foot and mouth disease (HFMD) is a common infection in the world, and its epidemics result in heavy disease burdens. Over the past decade, HFMD has been widespread among children in China, with Shanxi Province being a severely affected northern province. Located in the temperate monsoon climate, Shanxi has a GDP of over 2.5 trillion yuan. It is important to have a comprehensive understanding of the basic features of HFMD in those areas that have similar meteorological and economic backgrounds to northern China. We aimed to investigate epidemiological characteristics, identify spatial clusters and predict monthly incidence of HFMD. All reported HFMD cases were obtained from the Shanxi Center for Disease Control and Prevention. Overall HFMD incidence showed a significant downward trend from 2017 to 2020, increasing again in 2021. Children aged < 5 years were primarily affected, with a high incidence of HFMD in male patients (relative risk: 1.316). The distribution showed a seasonal trend, with major peaks in June and July and secondary peaks in October and November with the exception of 2020. Other enteroviruses were the predominant causative agents of HFMD in most years. Areas with large numbers of HFMD cases were primarily in central Shanxi, and spatial clusters in 2017 and 2018 showed a positive global spatial correlation. Local spatial autocorrelation analysis showed that hot spots and secondary hot spots were concentrated in Jinzhong and Yangquan in 2018. Based on monthly incidence from September 2021 to August 2022, the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) of the long short-term memory (LSTM) and seasonal autoregressive integrated moving average (SARIMA) models were 386.58 vs. 838.25, 2.25 vs. 3.08, and 461.96 vs. 963.13, respectively, indicating that the predictive accuracy of LSTM was better than that of SARIMA. The LSTM model may be useful in predicting monthly incidences of HFMD, which may provide early warnings of HFMD epidemics.