Diagnosis of periprosthesis joint infection and selection of replantation timing: A novel nomogram diagnosis model.

Preoperative diagnosis of periprosthetic joint infection (PJI) is critical to guide treatment options and improve patient outcomes. In this letter, we discuss results from our experiences with a novel nomogram diagnosis model based on serum and synovial fluid indicators for the preoperative diagnosis of PJI. The results showed that the novel nomogram diagnosis model can distinguish PJI from aseptic loosening before the operation. And it is also a useful candidate for the selection of the timing of current secondary revision.

Impact of omega-3 fatty acids supplementation on lipid levels in pregnant women with previous pregnancy losses: a retrospective longitudinal study.

Objective: This research aims to investigate the impact of omega-3 fatty acids supplementation on the lipid levels of pregnant women who have experienced pregnancy losses. Methods: This retrospective study analyzed data from pregnant women with previous pregnancy losses from two medical centers. Their lipid profiles were measured at least twice during pregnancy. According to the use of omega-3 soft gel capsules, participants were divided into the omega-3 group and the control group. We assessed the relationship between omega-3 fatty acids supplementation and longitudinal lipid levels during pregnancy using generalized estimating equations (GEE). Subsequently, we conducted subgroup analyses to delineate the profile of beneficiaries who received omega-3 fatty acids based on body mass index (BMI), age, menstrual regularity, number of previous pregnancy losses, number of previous live births, and educational level. Results: The omega-3 group included 105 participants, while the control group comprised 274 participants. Women in the omega-3 group started supplementation between 3.43 and 17.14 weeks of gestation. According to GEE analysis, supplementing omega-3 fatty acids significantly reduced triglyceride (TG) levels during pregnancy (adjusted ß = -0.300, 95% CI -0.445 to -0.154, p < 0.001). No associations between omega-3 fatty acids supplementation and total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) levels were observed. Subgroup analyses revealed that omega-3 fatty acids supplementation was related to a reduction in TG levels among pregnant women with age of ≤35 years, a normal BMI (18.5-24.9 kg/m2), 1-2 previous pregnancy losses, no previous live births, or an educational level above high school. Conclusion: Supplementation with omega-3 fatty acids may significantly reduce TG levels, yet it does not seem to improve TC, LDL-C, or HDL-C levels in pregnant women with previous pregnancy losses.

Diagnosis and treatment of anterior cruciate ligament injuries: Consensus of Chinese experts part II: Graft selection and clinical outcome evaluation.

Background: In the recent decade, there has been substantial progress in the technologies and philosophies associated with diagnosing and treating anterior cruciate ligament (ACL) injuries in China. The therapeutic efficacy of ACL reconstruction in re-establishing the stability of the knee joint has garnered widespread acknowledgment. However, the path toward standardizing diagnostic and treatment protocols remains to be further developed and refined. Objective: In this context, the Chinese Association of Orthopaedic Surgeons (CAOS) and the Chinese Society of Sports Medicine (CSSM) collaboratively developed an expert consensus on diagnosing and treating ACL injury, aiming to enhance medical quality through refining professional standards. Methods: The consensus drafting team invited experts across the Greater China region, including the mainland, Hong Kong, Macau, and Taiwan, to formulate and review the consensus using a modified Delphi method as a standardization approach. As members of the CSSM Lower Limb Study Group and the CAOS Arthroscopy and Sports Medicine Study Group, invited experts concentrated on two pivotal issues: "Graft Selection" and "Clinical Outcome Evaluation" during the second part of the consensus development. Results: This focused discussion ultimately led to a strong consensus on nine specific consensus terms. Conclusion: The consensus clearly states that ACL reconstruction has no definitive "gold standard" graft choice. Autografts have advantages in healing capability but are limited in availability and have potential donor site morbidities; allografts reduce surgical trauma but incur additional costs, and there are concerns about slow healing, quality control issues, and a higher failure rate in young athletes; synthetic ligaments allow for early rehabilitation and fast return to sport, but the surgery is technically demanding and incurs additional costs. When choosing a graft, one should comprehensively consider the graft's characteristics, the doctor's technical ability, and the patient's needs. When evaluating clinical outcomes, it is essential to ensure an adequate sample size and follow-up rate, and the research should include patient subjective scoring, joint function and stability, complications, surgical failure, and the return to sport results. Medium and long-term follow-ups should not overlook the assessment of knee osteoarthritis.

Scalable Drug-Mimicking Nanoplasmonic Therapy for Bradyarrhythmia in Cardiomyocytes.

Bradyarrhythmia poses a serious threat to human health, with chronic progression causing heart failure and acute onset leading to sudden death. In this study, we develop a scalable drug-mimicking nanoplasmonic therapeutic strategy by introducing gold nanorod (Au NR) mediated near-infrared (NIR) photothermal effects. An integrated sensing and regulation platform is established for in situ synchronized NIR laser regulation and electrophysiological property recording. The Au NR plasmonic regulation enables the restoration of normal cardiomyocyte rhythm from the bradyarrhythmia. By regulating the aspect ratio and concentration of Au NRs, as well as the intensity and time of NIR irradiation, we precisely optimized the plasmonic photothermal effect to explore effective therapeutic strategies. Furthermore, mRNA sequencing revealed a significant increase in the number of differentially expressed genes (DEGs) involved in the electrophysiological activities of cardiomyocytes following photothermal therapy. Au NR-mediated plasmonic photothermal therapy, as an efficient and noninvasive approach to bradyarrhythmia, holds profound implications for cardiology research.

Mechanisms and Factors Influencing the Production of Uniform-Sized Giant Unilamellar Vesicles by Discrete Lipid Film Arrays.

In this paper, we innovatively proposed a highly uniform vesicle preparation scheme based on the intervesicle mechanical self-constraint effect of vesicle crowding. By adjusting the spacing of discrete microwell structures, we observed that during the self-assembly of phospholipid molecules in microwells to form giant unilamellar vesicles (GUVs), the scale swelling of the vesicles during the continuous growth process would lead to the crowding of vesicles in adjacent microwells, thus inducing the formation of intervesicle mechanical self-constraint effect. The results of the experiment showed that this paper obtained the optimized discretized microwell structure (micropillar side: 30 µm; pitch: 0 µm), and the corresponding lipid mass was measured and determined, yielding homogeneous giant GUVs of 37.9 ± 2.0 µm. In this paper, homogenized GUVs (∼40 µm) with different cholesterol concentrations (10, 20, and 30%) were obtained by this method, and the above vesicles were subjected to controlled electroporation experiment under external electric fields of 23, 31, and 41 kV/cm, respectively. It showed that the mechanical self-constraint effect of vesicle crowding induced by patterned microstructures during the self-assembly of phospholipid molecules significantly enhances the size homogeneity of GUVs, which would be helpful for the wide applications of GUVs in other areas such as cell-like models and controlled release of drugs.

If CE affects infertile women's outcomes after surgery?

OBJECTIVE: To investigate the prevalence of chronic endometritis (CE) in infertile patients and whether it affects spontaneous pregnancy after reproductive surgery in infertile patients. MATERIALS AND METHODS: In this study, we collected clinical information on infertility patients who underwent reproductive surgery at the Reproductive Medicine Centre of the Second Hospital of Lanzhou University from 2021.1 to 2022.8. All patients underwent laparoscopic and hysteroscopic surgery. Tubal lubrication was performed concurrently with endometrial sample collection and pathological examination. The specimens were immunohistochemically stained with CD38 and CD138, and those who tested positive at the same time were diagnosed with chronic endometritis. As of 2023.9, the patients were followed up by telephone to determine whether chronic endometritis impacted postoperative pregnancy. OUTCOME: A total of 81 patients were finally included in the study. Of these, 25 were in the chronic endometritis group, and 56 were in the non-chronic endometritis group. There were no appreciable differences between the two groups' demographic statistics. Furthermore, neither the bilateral appendages nor the uterus's intraoperative conditions showed a statistically significant difference. Patients in the chronic endometritis group had a longer time to conception from the time of surgery (7 (6.00-11.75) vs. 10 (6.50-16.00), p = 0.467) and a lower rate of spontaneous pregnancies (8/25 = 32.00 % vs. 28/55 = 50.00 %, p = 0.132) than patients with non-chronic endometritis. Among the patients who had successful spontaneous pregnancies after surgery, approximately 77.14 % had live births and 22.86 % had miscarriages, and the live birth rate between the two groups was not significantly different. (21/28 = 75.00 % vs 7/8 = 87.50 %, p = 0.651) CONCLUSION: Chronic endometritis affects approximately 31.82% of infertile patients, and following reproductive surgery, it has no discernible impact on spontaneous pregnancy.

Synergistic rheumatoid arthritis therapy by interrupting the detrimental feedback loop to orchestrate hypoxia M1 macrophage polarization using an enzyme-catalyzed nanoplatform.

A detrimental feedback loop between hypoxia and oxidative stress consistently drives macrophage polarization toward a pro-inflammatory M1 phenotype, thus persistently aggravating rheumatoid arthritis (RA) progression. Herein, an enzyme-catalyzed nanoplatform with synergistic hypoxia-relieving and reactive oxygen species (ROS)-scavenging properties was developed using bovine serum albumin-bilirubin-platinum nanoparticles (BSA-BR-Pt NPs). Bilirubin was employed to eliminate ROS, while platinum exhibited a synergistic effect in scavenging ROS and simultaneously generated oxygen. In mice RA model, BSA-BR-Pt NPs treatment exhibited superior effects, resulting in significant improvements in joint inflammation, cartilage damage, and bone erosion, compared to methotrexate, the most widely used antirheumatic drug. Mechanistically, RNA-sequencing data and experimental results elucidated that BSA-BR-Pt NPs induced a re-polarization of hypoxic M1 macrophages to M2 macrophages via switching glycolysis to oxidative phosphorylation through the inhibition of HIF-1α pathway. Collectively, this research for the first time elaborated the underlying mechanism of enzyme-catalyzed nanoplatform in orchestrating macrophage polarization, and identified a novel therapeutic strategy for RA and other inflammatory disorders.

Unraveling the Pathogenesis of Post-Stroke Depression in a Hemorrhagic Mouse Model through Frontal Lobe Circuitry and JAK-STAT Signaling.

Post-stroke depression is a common complication that imposes significant burdens and challenges on patients. The occurrence of depression is often associated with frontal lobe hemorrhage, however, current understanding of the underlying mechanisms remains limited. Here, the pathogenic mechanisms associated with the circuitry connectivity, electrophysiological alterations, and molecular characteristics are investigated related to the frontal lobe in adult male mice following unilateral injection of blood in the medial prefrontal cortex (mPFC). It is demonstrated that depression is a specific neurological complication in the unilateral hematoma model of the mPFC, and the ventral tegmental area (VTA) shows a higher percentage of connectivity disruption compared to the lateral habenula (LHb) and striatum (STR). Additionally, long-range projections originating from the frontal lobe demonstrate higher damage percentages within the connections between each region and the mPFC. mPFC neurons reveal reduced neuronal excitability and altered synaptic communication. Furthermore, transcriptomic analysis identifies the involvement of the Janus Kinase-Signal Transducer and Activator of Transcription (JAK-STAT) signaling pathway, and targeting the JAK-STAT pathway significantly alleviates the severity of depressive symptoms. These findings improve the understanding of post-hemorrhagic depression and may guide the development of efficient treatments.

A thematic content analysis of the structure and effects of good doctor abilities in China.

BACKGROUND: The efforts to explore and build the structure of good doctor abilities are important because they help improve the quality of education for medical students and better standardize the working performance of doctors. However, at present, no worldwide standards for such a structure have been established. In this study, we endeavoured to map the structure of good doctor abilities and identify their effects. METHODS: With a focus on China, a thematic content analysis was adopted in this study to analyse the personal profiles of 50 widely recognized good doctors. NVivo11 software was used. RESULTS: The Structure and Effects of Good Doctor Abilities in China model was proposed, and interpretations were made based on AMO theory. Good doctor abilities fall within six categories: rigorous clinical thinking, skilled in diagnosis and therapy, clinical empathy, continuous learning and innovation, enhancing and sharing experiences, and communication and coordination. These abilities have positive impacts on doctors' work performances and social benefits by encouraging good behaviours, ultimately promoting the sustainable development of the hospitals where they serve. CONCLUSIONS: In this study, we established a model of the structure and effects of good-doctor abilities in China and interpreted its mechanism, innovation and theory diversification in "good-doctor" research. Moreover, this study has practical significance because it provides systematic and well-targeted criteria for improving the professionalism of doctors, promoting more good doctor behaviours, providing guidance for regulating doctors' conduct and providing a reference for medical education and working performance reviews worldwide.

Near-infrared-triggered plasmonic regulation and cardiomyocyte-based biosensing system for in vitro bradyarrhythmia treatment.

Bradyarrhythmia, a life-threatening cardiovascular disease, is an increasing burden for the healthcare system. Currently, surgery, implanted device, and drug are introduced to treat the bradyarrhythmia in clinical practice. However, these conventional therapeutic strategies suffer from the invasive surgery, power supply, or drug side effect, respectively, hence developing the alternative therapeutic strategy is necessarily imperative. Here, a convenient and effective strategy to treat the bradyarrhythmia is proposed using near-infrared-triggered Au nanorod (NR) based plasmonic photothermal effect (PPE). Moreover, electrophysiology of cardiomyocytes is dynamically monitored by the integrated biosensing-regulating system during and after the treatment. Cardiomyocyte-based bradyarrhythmia recover rhythmic for a long time by regulating plasmonic photothermal effect. Furthermore, the regulatory mechanism is qualitatively investigated to verify the significant thermal stimulation in the recovery process. This study establishes a reliable platform for long-term recording and evaluation of mild photothermal therapy for bradyarrhythmia in vitro, offering an efficient and non-invasive strategy for the potential clinical applications.

Corrigendum: A new prognostic model for recurrent pregnancy loss: assessment of thyroid and thromboelastograph parameters.

[This corrects the article DOI: 10.3389/fendo.2024.1415786.].

A dual-mode, image-enhanced, miniaturized microscopy system for incubator-compatible monitoring of live cells.

Imaging live cells under stable culture conditions is essential to investigate cell physiological activities and proliferation. To achieve this goal, typically, a specialized incubation chamber that creates desired culture conditions needs to be incorporated into a microscopy system to perform cell monitoring. However, such imaging systems are generally large and costly, hampering their wide applications. Recent advances in the field of miniaturized microscopy systems have enabled incubator cell monitoring, providing a hospitable environment for live cells. Although these systems are more cost-effective, they are usually limited in imaging modalities and spatial temporal resolution. Here, we present a dual-mode, image-enhanced, miniaturized microscopy system (termed MiniCube) for direct monitoring of live cells inside incubators. MiniCube enables both bright field imaging and fluorescence imaging with single-cell spatial resolution and sub-second temporal resolution. Moreover, this system can also perform cell monitoring inside the incubator with tunable time scales ranging from a few seconds to days. Meanwhile, automatic cell segmentation and image enhancement are realized by the proposed data analysis pipeline of this system, and the signal-to-noise ratio (SNR) of acquired data is significantly improved using a deep learning based image denoising algorithm. Image data can be acquired with 5 times lower light exposure while maintaining comparable SNR. The versatility of this miniaturized microscopy system lends itself to various applications in biology studies, providing a practical platform and method for studying live cell dynamics within the incubator.

Two-Dimensional Deep Learning Frameworks for Drug-Induced Cardiotoxicity Detection.

The identification of drug-induced cardiotoxicity remains a pressing challenge with far-reaching clinical and economic ramifications, often leading to patient harm and resource-intensive drug recalls. Current methodologies, including in vivo and in vitro models, have severe limitations in accurate identification of cardiotoxic substances. Pioneering a paradigm shift from these conventional techniques, our study presents two deep learning-based frameworks, STFT-CNN and SST-CNN, to assess cardiotoxicity with markedly improved accuracy and reliability. Leveraging the power of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) as a more human-relevant cell model, we record mechanical beating signals through impedance measurements. These temporal signals were converted into enriched two-dimensional representations through advanced transformation techniques, specifically short-time Fourier transform (STFT) and synchro-squeezing transform (SST). These transformed data are fed into the proposed frameworks for comprehensive analysis, including drug type classification, concentration classification, cardiotoxicity classification, and new drug identification. Compared to traditional models like recurrent neural network (RNN) and 1-dimensional convolutional neural network (1D-CNN), SST-CNN delivered an impressive test accuracy of 98.55% in drug type classification and 99% in distinguishing cardiotoxic and noncardiotoxic drugs. Its feasibility is further highlighted with a stellar 98.5% average accuracy for classification of various concentrations, and the superiority of our proposed frameworks underscores their promise in revolutionizing drug safety assessments. With a potential for scalability, they represent a major leap in drug safety assessments, offering a pathway to more robust, efficient, and human-relevant cardiotoxicity evaluations.

Micronano Synergetic Three-Dimensional Bioelectronics: A Revolutionary Breakthrough Platform for Cardiac Electrophysiology.

Cardiovascular diseases (CVDs) are the leading cause of mortality and therefore pose a significant threat to human health. Cardiac electrophysiology plays a crucial role in the investigation and treatment of CVDs, including arrhythmia. The long-term and accurate detection of electrophysiological activity in cardiomyocytes is essential for advancing cardiology and pharmacology. Regarding the electrophysiological study of cardiac cells, many micronano bioelectric devices and systems have been developed. Such bioelectronic devices possess unique geometric structures of electrodes that enhance quality of electrophysiological signal recording. Though planar multielectrode/multitransistors are widely used for simultaneous multichannel measurement of cell electrophysiological signals, their use for extracellular electrophysiological recording exhibits low signal strength and quality. However, the integration of three-dimensional (3D) multielectrode/multitransistor arrays that use advanced penetration strategies can achieve high-quality intracellular signal recording. This review provides an overview of the manufacturing, geometric structure, and penetration paradigms of 3D micronano devices, as well as their applications for precise drug screening and biomimetic disease modeling. Furthermore, this review also summarizes the current challenges and outlines future directions for the preparation and application of micronano bioelectronic devices, with an aim to promote the development of intracellular electrophysiological platforms and thereby meet the demands of emerging clinical applications.

Laser patterned graphene pressure sensor with adjustable sensitivity in an ultrawide response range.

Flexible pressure sensors have attracted wide attention because of their applications in wearable electronic, human-computer interface, and healthcare. However, it is still a challenge to design a pressure sensor with adjustable sensitivity in an ultrawide response range to satisfy the requirements of different application scenarios. Here, a laser patterned graphene pressure sensor (LPGPS) is proposed with adjustable sensitivity in an ultrawide response range based on the pre-stretched kirigami structure. Due to the out-of-plane deformation of the pre-stretched kirigami structure, the sensitivity can be easily tuned by simply modifying the pre-stretched level. As a result, it exhibits a maximum sensitivity of 0.243 kPa-1, an ultrawide range up to 1600 kPa, a low detection limit (6 Pa), a short response time (42 ms), and excellent stability with high pressure of 1200 kPa over 500 cycles. Benefiting from its high sensitivity and ultrawide response range, the proposed sensor can be applied to detect physiological and kinematic signals under different pressure intensities. Additionally, taking advantage of laser programmable patterning, it can be easily configured into an array to determine the pressure distribution. Therefore, LPGPS with adjustable sensitivity in an ultrawide response range has potential application in wearable electronic devices.

A new prognostic model for recurrent pregnancy loss: assessment of thyroid and thromboelastograph parameters.

Objective: This study aimed to identify predictors associated with thyroid function and thromboelastograph (TEG) examination parameters and establish a nomogram for predicting the risk of subsequent pregnancy loss in recurrent pregnancy loss (RPL). Methods: In this retrospective study, we analyzed the medical records of 575 RPL patients treated at Lanzhou University Second Hospital, China, between September 2020 and December 2022, as a training cohort. We also included 272 RPL patients from Ruian People's Hospital between January 2020 and July 2022 as external validation cohort. Predictors included pre-pregnancy thyroid function and TEG examination parameters. The study outcome was pregnancy loss before 24 weeks of gestation. Variable selection was performed using least absolute shrinkage and selection operator regression and stepwise regression analyses, and the prediction model was developed using multivariable logistic regression. The study evaluated the model's performance using the area under the curve (AUC), calibration curve, and decision curve analysis. Additionally, dynamic and static nomograms were constructed to provide a visual representation of the models. Results: The predictors used to develop the model were body mass index, previous pregnancy losses, triiodothyronine, free thyroxine, thyroid stimulating hormone, lysis at 30 minutes, and estimated percent lysis which were determined by the multivariable logistic regression with the minimum Akaike information criterion of 605.1. The model demonstrated good discrimination with an AUC of 0.767 (95%CI 0.725-0.808), and the Hosmer-Lemeshow test indicated good fitness of the predicting variables with a P value of 0.491. Identically, external validation confirmed that the model exhibited good performance with an AUC of 0.738. Moreover, the clinical decision curve showed a positive net benefit in the prediction model. Meanwhile, the web version we created was easy to use. The risk stratification indicated that high-risk patients with a risk score >147.9 had a higher chance of pregnancy loss (OR=6.05, 95%CI 4.09-8.97). Conclusions: This nomogram well-predicted the risk of future pregnancy loss in RPL and can be used by clinicians to identify high-risk patients and provide a reference for pregnancy management of RPL.

Effect of Membrane Thickness on Ion Transport in pH-Regulated Zero-Depth Interfacial Nanopores.

Zero-depth interfacial nanopores, which are formed by two crossed nanoscale channels at their intersection interface, have been proposed to increase the spatial resolution of solid-state nanopores. However, research on zero-depth interfacial nanopores is still in its early stages. Although it has been shown that the current passing through an interfacial nanopore is largely independent of the membrane thickness, existing studies have not fully considered the impact of membrane thickness on other ion transport characteristics within these nanopores. In this paper, we investigate the electrokinetic ion transport phenomenon in the zero-depth interfacial nanopores, especially focusing on the influence of membrane thickness on the ion transport phenomenon. Our model incorporates the Poisson-Nernst-Planck equations and the Navier-Stokes equations, featuring a pH-regulated surface charge density. We find that when the thickness of the nanochannels is close to the interface size of the formed interfacial nanopore, the phenomenon of ion transport in the interfacial nanopore is similar to that in a conventional cylindrical nanopore. However, when the thickness of the nanochannels is much greater than the interface size of the formed interfacial nanopore, several distinct phenomena occur. The surface charge density on the inner walls of the interfacial nanopores has a small peak at the interface of the two crossing nanochannels, and the anion concentration changes greatly between the two nanochannels; that is, a much greater anion concentration forms in the nanochannel near the anode side than in the nanochannel near the cathode side. When the surface charge is nonzero, the electric field within the interfacial nanopore creates three extreme points, and the directions of the local electric fields are opposite at the ends of the membrane.

Machine Learning Assisted Electronic/Ionic Skin Recognition of Thermal Stimuli and Mechanical Deformation for Soft Robots.

Soft robots have the advantage of adaptability and flexibility in various scenarios and tasks due to their inherent flexibility and mouldability, which makes them highly promising for real-world applications. The development of electronic skin (E-skin) perception systems is crucial for the advancement of soft robots. However, achieving both exteroceptive and proprioceptive capabilities in E-skins, particularly in terms of decoupling and classifying sensing signals, remains a challenge. This study presents an E-skin with mixed electronic and ionic conductivity that can simultaneously achieve exteroceptive and proprioceptive, based on the resistance response of conductive hydrogels. It is integrated with soft robots to enable state perception, with the sensed signals further decoded using the machine learning model of decision trees and random forest algorithms. The results demonstrate that the newly developed hydrogel sensing system can accurately predict attitude changes in soft robots when subjected to varying degrees of pressing, hot pressing, bending, twisting, and stretching. These findings that multifunctional hydrogels combine with machine learning to decode signals may serve as a basis for improving the sensing capabilities of intelligent soft robots in future advancements.

A smart tablet-phone-based high-performance pancreatic cancer cell biosensing system for drug screening.

Exploring more efficient pancreatic cancer drug screening platforms is of significant importance for accelerating the drug development process. In this study, we developed a high-sensitivity bioluminescence system based on smartphones and smart tablets, and constructed a pancreatic cancer drug screening platform (PCDSP) by combining the pancreatic cancer cell sensing model (PCCSM) on the multiwell plates (MTP). A smart tablet was used as the light source and a smartphone as the colorimetric sensing device. The smartphone dynamically controls the color and brightness displayed on the smart tablet to achieve lower LOD and wider detection ranges. We constructed PCCSM for 24 h, 48 h, and 72 h , and performed colorimetric experiments using both PCDSP and a commercial plate reader (CPR). The results showed that the PCDSP had a lower LOD than that of CPR. Moreover, PCDSP even exhibited a lower LOD for 24 h PCCSM testing compared to CPR for 48 h PCCSM testing, effectively shortening the drug evaluation process. Additionally, the PCDSP offers higher portability and efficiency compared with CPR, making it a promising platform for efficient pancreatic cancer drug screening.