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Digital PCR (dPCR) holds immense potential for precisely detecting nucleic acid markers essential for personalized medicine. However, its broader application is hindered by high consumable costs, complex procedures, and restricted multiplexing capabilities. To address these challenges, an all-in-one dPCR system is introduced that eliminates the need for microfabricated chips, offering fully automated operations and enhanced multiplexing capabilities. Using this innovative oscillation-induced droplet generation technique, OsciDrop, this system supports a comprehensive dPCR workflow, including precise liquid handling, pipette-based droplet printing, in situ thermocycling, multicolor fluorescence imaging, and machine learning-driven analysis. The system's reliability is demonstrated by quantifying reference materials and evaluating HER2 copy number variation in breast cancer. Its multiplexing capability is showcased with a quadruplex dPCR assay that detects key EGFR mutations, including 19Del, L858R, and T790M in lung cancer. Moreover, the digital stepwise melting analysis (dSMA) technique is introduced, enabling high-multiplex profiling of seven major EGFR variants spanning 35 subtypes. This innovative dPCR system presents a cost-effective and versatile alternative, overcoming existing limitations and paving the way for transformative advances in precision diagnostics.

Abstract Objective This study aimed to identify risk factors contributing to the early onset of patellofemoral osteoarthritis (PFOA) within the first two years following anterior cruciate ligament reconstruction (ACLR) using a hamstring tendon autograft. Methods Participants aged 18 to 40 who had undergone ACLR within the past two years were included in this study, along with a control group of healthy volunteers. Magnetic resonance imaging (MRI) data were obtained preoperatively, at two years postoperatively, and from the control group. T-tests were used to assess differences in patellofemoral alignment (PA) and trochlear morphology (TM) between the pre- and post-ACLR patients and healthy controls. The incidence of PFOA was recorded, and associations between PA, TM, and clinical parameters were evaluated in patients with and without PFOA. Logistic regression analysis was conducted to identify potential risk factors for PFOA development. Results A total of 177 patients, with a mean follow-up period of 22.17 ± 5.09 months and a mean age of 26.4 ± 5.6 years, were included in the study. Following ACL injury, significant alterations in patellar tilt angle (PTA), tuberositas tibae-trochlear groove distance (TT-TG), Insall-Salvati ratio (ISR), and static anterior tibial translation (SATT) were observed compared to the control group. Postoperatively, deviations in PTA and SATT remained significant when compared to healthy controls. Of the 177 patients, 68 (38.42%) developed early-onset PFOA. Factors associated with the early onset of PFOA included age at the time of surgery, the interval between injury and surgery, PTA, bisect offset (BO), sulcus angle (SA), thigh circumference, SATT, and partial meniscectomy. Conclusion Significant differences in PTA, TT-TG, ISR, and SATT were identified between patients who underwent ACLR and healthy controls. Postoperatively, there was no correction in PTA or SATT, which remained significantly altered. Factors such as age at the time of surgery, PTA, BO, SA, ISR, SATT, thigh circumference, partial meniscectomy, and the time interval between injury and surgery were associated with the early onset of PFOA within two years post-ACLR. These findings may aid in the prevention of PFOA by identifying individuals at higher risk for early development.

Abstract Background High-density lipoprotein cholesterol (HDL-C) is widely recognized for its protective effects against cognitive decline. However, recent studies have presented conflicting results, with some suggesting no significant cognitive benefits or even an increased risk of dementia associated with high HDL-C levels. For those who suffer from depression, the cognitive benefits of HDL-C may be diminished or reversed. The purpose of this study is to investigate the associations between HDL-C, cognitive ability, and depressive symptoms in middle-aged and older Chinese adults. Methods The datasets utilized were sourced from the China Health and Retirement Longitudinal Study (CHARLS) for the years 2011 and 2015, comprising 4,302 participants. Cross-lagged models were employed to explore the temporal sequence between cognitive performance and HDL-C levels, and to examine the interplay among depression, cognition, and HDL-C. Confounding factors such as sociodemographic characteristics, sleep conditions, and history of chronic diseases were controlled for. Results The analysis revealed unidirectional effects of baseline impaired cognition and greater severity of depression on increased HDL-C levels at follow-up (β = − 0.036 and β = 0.028, respectively, P 0.05). Depressive symptoms and cognition were found to have a significant bidirectional association (β = − 0.026 and β = − 0.053, respectively, P

Thermokarst lake formation accelerates permafrost degradation due to climate warming, thereby releasing significant amounts of carbon into the atmosphere, complicating hydrological cycles, and causing environmental damage. However, the energy transfer mechanism from the surface to the sediment of thermokarst lakes remains largely unexplored, thereby limiting our understanding of the magnitude and duration of biogeochemical processes and hydrological cycles. Therefore, herein, a typical thermokarst lake situated in the center of the Qinghai–Tibet Plateau (QTP) was selected for observation and energy budget modeling. Our results showed that the net radiation of the thermokarst lake surface was 95.1, 156.9, and 32.3 W m−2 for the annual, ice-free, and ice-covered periods, respectively, and was approximately 76% of the net radiation consumed by latent heat flux. Alternations in heat storage in the thermokarst lake initially increased from January to April, then decreased from April to December, with a maximum change of 48.1 W m−2 in April. The annual average heat fluxes from lake water to sediments were 1.4 W m−2; higher heat fluxes occurred during the ice-free season at a range of 4.9–12.0 W m−2. The imbalance between heat absorption and release in the millennium scale caused the underlying permafrost of the thermokarst lake to completely thaw. At present, the ground temperature beneath the lake bottom at a depth of 15 m has reached 2.0 °C. The temperatures and vapor-pressure conditions of air and lake surfaces control the energy budget of the thermokarst lake. Our findings indicate that changes in the hydrologic regime shifts and biogeochemical processes are more frequent under climate warming and permafrost degradation.

Abstract BCL-2 inhibitors such as venetoclax offer therapeutic promise in acute myeloid leukemia (AML) and other cancers, but drug resistance poses a significant challenge. It is crucial to understand the mechanisms that regulate venetoclax response. While correlative studies have identified numerous genes linked to venetoclax sensitivity, their direct impact on the drug response remains unclear. In this study, we targeted around 1400 genes upregulated in venetoclax-sensitive primary AML samples and carried out a CRISPR knockout screen to evaluate their direct effects on venetoclax response. Our screen identified the transcription factor ZNF740 as a critical regulator, with its expression consistently predicting venetoclax sensitivity across subtypes of the FAB classification. ZNF740 depletion leads to increased resistance to ventoclax, while its overexpression enhances sensitivity to the drug. Mechanistically, our integrative transcriptomic and genomic analysis identifies NOXA as a direct target of ZNF740, which negatively regulates MCL-1 protein stability. Loss of ZNF740 downregulates NOXA and increases the steady state protein levels of MCL-1 in AML cells. Restoring NOXA expression in ZNF740-depleted cells re-sensitizes AML cells to venetoclax treatment. Furthermore, we demonstrated that dual targeting of MCL-1 and BCL-2 effectively treats ZNF740-deficient AML in vivo. Together, our work systematically elucidates the causal relationship between venetoclax response signature genes and establishes ZNF740 as a novel transcription factor regulating venetoclax sensitivity.

Abstract Background The heightened risk of cardiovascular and cerebrovascular events is associated with the increased instability of atherosclerotic plaques. However, the lack of effective diagnostic biomarkers has impeded the assessment of plaque instability currently. This study was aimed to investigate and identify hub genes associated with unstable plaques through the integration of various bioinformatics tools, providing novel insights into the detection and treatment of this condition. Methods Weighted Gene Co-expression Network Analysis (WGCNA) combined with two machine learning methods were used to identify hub genes strongly associated with plaque instability. The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method was utilized to assess immune cell infiltration patterns in atherosclerosis patients. Additionally, Gene Set Variation Analysis (GSVA) was conducted to investigate the potential biological functions, pathways, and mechanisms of hub genes associated with unstable plaques. To further validate the diagnostic efficiency and expression of the hub genes, immunohistochemistry (IHC), quantitative real-time polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA) were performed on collected human carotid plaque and blood samples. Immunofluorescence co-staining was also utilized to confirm the association between hub genes and immune cells, as well as their colocalization with mitochondria. Results The CIBERSORT analysis demonstrated a significant decrease in the infiltration of CD8 T cells and an obvious increase in the infiltration of M0 macrophages in patients with atherosclerosis. Subsequently, two highly relevant modules (blue and green) strongly associated with atherosclerotic plaque instability were identified. Through intersection with mitochondria-related genes, 50 crucial genes were identified. Further analysis employing least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms revealed six hub genes significantly associated with plaque instability. Among them, NT5DC3, ACADL, SLC25A4, ALDH1B1, and MAOB exhibited positive correlations with CD8 T cells and negative correlations with M0 macrophages, while kynurenine 3-monooxygenas (KMO) demonstrated a positive correlation with M0 macrophages and a negative correlation with CD8 T cells. IHC and RT-qPCR analyses of human carotid plaque samples, as well as ELISA analyses of blood samples, revealed significant upregulation of KMO and MAOB expression, along with decreased ALDH1B1 expression, in both stable and unstable samples compared to the control samples. However, among the three key genes mentioned above, only KMO showed a significant increase in expression in unstable plaque samples compared to stable plaque samples. Furthermore, the expression patterns of KMO in human carotid unstable plaque tissues and cultured mouse macrophage cell lines were assessed using immunofluorescence co-staining techniques. Finally, lentivirus-mediated KMO silencing was successfully transduced into the aortas of high-fat-fed ApoE-/- mice, with results indicating that KMO silencing attenuated plaque formation and promoted plaque stability in ApoE-/- mice. Conclusions The results suggest that KMO, a mitochondria-targeted gene associated with macrophage cells, holds promise as a valuable diagnostic biomarker for assessing the instability of atherosclerotic plaques.

Non-invasive vagus nerve stimulation (VNS) represents a transformative approach for managing a broad spectrum of inflammatory and autoimmune conditions, including rheumatoid arthritis and inflammatory bowel disease. This comprehensive review delineates the mechanisms underlying VNS, emphasizing the cholinergic anti-inflammatory pathway, and explores interactions within the neuro-immune and vagus-gut axes based on both clinical outcomes and pre-clinical models. Clinical applications have confirmed the efficacy of VNS in managing specific autoimmune diseases, such as rheumatoid arthritis, and chronic inflammatory conditions like inflammatory bowel disease, showcasing the variability in stimulation parameters and patient responses. Concurrently, pre-clinical studies have provided insights into the potential of VNS in modulating cardiovascular and broader inflammatory responses, paving the way for its translational application in clinical settings. Innovations in non-invasive VNS technology and precision neuromodulation are enhancing its therapeutic potential, making it a viable option for patients who are unresponsive to conventional treatments. Nonetheless, the widespread adoption of this promising therapy is impeded by regulatory challenges, patient compliance issues, and the need for extensive studies on long-term efficacy and safety. Future research directions will focus on refining VNS technology, optimizing treatment parameters, and exploring synergistic effects with other therapeutic modalities, which could revolutionize the management of chronic inflammatory and autoimmune disorders.

Abstract In order to investigate the failure modes and instability mechanism of fractured rock. Uniaxial compression tests were conducted on sandstone specimens with different dip angles. Based on rock energy dissipation theory and fractal theory, the energy evolution characteristics and fragmentation fractal characteristics in the process of deformation and failure of specimens were analyzed. The results show that the peak strength and elastic modulus of fractured rock mass are lower than those of intact samples, and both show an exponential increase with the increase of fracture dip angle. The energy evolution laws of different fracture specimens are roughly similar and can be classified into four stages based on the stress–strain curve: pressure-tight, elastic, plastic, and post-destructive. The total strain energy, elastic strain energy, and dissipated strain energy of the specimen at the peak stress point increased exponentially with crack inclination, and the dissipated strain energy and compressive strength conformed to a power function growth relationship. The distribution of the fragments after the failure of the fracture sample has fractal characteristics, and the fractal dimension increases with the increase of the fracture dip angle. In addition, the higher the compressive strength of the specimen, the greater the energy dissipation, the more serious the degree of fragmentation, and the greater the fractal dimension. The data fitting further shows that there is a power function relationship between the dissipated strain energy and the fractal dimension. The research results can provide a theoretical basis for the stability of rock mass engineering and structural deformation control.

Abstract This study aimed to evaluate the safety of Moringa by comparing the effects of different gavage doses of Moringa. The general behavior, body weight, food intake, blood indexes, serum biochemical indexes, and histopathology of rats were used to determine the safety threshold and to provide a reference for the further development and use of Moringa as animal feed. 40 Sprague Dawley rats were selected and given transoral gavage for 28 consecutive days. The T1, T2 and T3 groups were observed for general behavior, body weight, and food intake. Blood and serum biochemical indices were quantified, and histopathology was performed to evaluate the effect and safety of Moringa. The results of the toxicological test showed that (1) Only T1 groups experienced diarrhea. (2) The body weight and food intake of rats in each group were normal compared with the control group. (3) The hematological and serum biochemical indices of rats in the T1 group were significantly different from those of CK but were in the normal range; (4) The results of microscopic examination of the heart, liver, spleen, lung, and kidney of rats in each group were normal, but inflammation occurred in stomach and jejunum of rats in the T1 group, but not in the ileum. The gastrointestinal tract of rats in the T2 and T3 groups were normal. (5) No abnormal death occurred in any of the treatment groups.The results of this study revealed that gavage of Moringa homogenate at a dose of 6 g/kg BW can cause diarrhea in rats. Although there is no pathological effect on weight, food intake, blood and serum biochemical indicators in rats, there are pathological textures in the gastrointestinal tissue caused by diarrhea. Therefore, the safety threshold of Moringa homogenate should be ≤ 3 g/kg BW.

Electric submersible pump (ESP) oil production technology is widely used in non-flowing high-yield wells and high water-cut wells, but equipment faults are prone to occur during operation, and subsequent maintenance may trigger long-term downtime, which may cause incalculable economic losses. At present, ESP fault diagnosis mainly depends on the experience of field technicians, and automatic diagnosis and analysis cannot be done quickly and timely. Therefore, this paper proposes an ESP fault diagnosis model based on Laplacian eigenmaps and weighted extreme learning machine. In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. The results show that the classification average accuracy, maximum accuracy, and G-mean of the algorithm proposed in this paper are improved by more than 10% on average compared with those of the support vector machine, decision tree, backpropagation (BP) algorithm, extreme learning machine, and weighted extreme learning machine, thus confirming the effectiveness of the proposed method.