Consistency-guided Differential Decoding for Enhancing Semi-supervised Medical Image Segmentation.

Semi-supervised learning (SSL) has been proven beneficial for mitigating the issue of limited labeled data, especially on volumetric medical image segmentation. Unlike previous SSL methods which focus on exploring highly confident pseudo-labels or developing consistency regularization schemes, our empirical findings suggest that differential decoder features emerge naturally when two decoders strive to generate consistent predictions. Based on the observation, we first analyze the treasure of discrepancy in learning towards consistency, under both pseudo-labeling and consistency regularization settings, and subsequently propose a novel SSL method called LeFeD, which learns the feature-level discrepancies obtained from two decoders, by feeding such information as feedback signals to the encoder. The core design of LeFeD is to enlarge the discrepancies by training differential decoders, and then learn from the differential features iteratively. We evaluate LeFeD against eight state-of-the-art (SOTA) methods on three public datasets. Experiments show LeFeD surpasses competitors without any bells and whistles, such as uncertainty estimation and strong constraints, as well as setting a new state of the art for semi-supervised medical image segmentation. Code has been released at https://github.com/maxwell0027/LeFeD.

Small-size temperature/high-pressure integrated sensor via flip-chip method.

Hydraulic technology with smaller sizes and higher reliability trends, including fault prediction and intelligent control, requires high-performance temperature and pressure-integrated sensors. Current designs rely on planar wafer- or chip-level integration, which is limited by pressure range, chip size, and low reliability. We propose a small-size temperature/high-pressure integrated sensor via the flip-chip technique. The pressure and temperature units are arranged vertically, and the sensing signals of the two units are integrated into one plane through silicon vias and gold-gold bonding, reducing the lateral size and improving the efficiency of signal transmission. The flip-chip technique ensures a reliable electrical connection. A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive effect. The temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation, which will improve the precision of the pressure unit. The integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated sensor. The integrated sensor is characterised, and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97 mV/MPa and -0.19% FS in the range of 0-20 MPa and -40 to 120 °C. The linearity, hysteresis, repeatability, accuracy, basic error, and zero-time drift are 0.16% FS, 0.04% FS, 0.06% FS, 0.18% FS, ±0.23% FS and 0.04% FS, respectively. The measurement error of the temperature sensor and temperature coefficient of resistance is less than ±1 °C and 3142.997 ppm/°C, respectively. The integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection, industrial equipment, and oil drilling platforms.

Reversible ON- and OFF-switch receptors Clec4G and Rab1A reveal the hormetic effects of a pectin polysaccharide in Aralia elata (Miq.) Seem.

BACKGROUND: Numerous studies indicate that natural polysaccharides have immune-enhancing effects as a host defense potentiator. Few reports are available on hormetic effects of natural polysaccharides, and the underlying mechanisms remain unclear. PURPOSE: AELP-B6 (arabinose- and galactose-rich pectin polysaccharide) from Aralia elata (Miq.) Seem was taken as a case study to clarify the potential mechanism of hormetic effects of natural polysaccharides. METHODS: The pharmacodynamic effect of AELP-B6 was verified by constructing the CTX-immunosuppressive mouse model. The hormetic effects were explored by TMT-labeled proteomics, energy metabolism analysis, flow cytometry and western blot. The core-affinity target of AELP-B6 was determined by pull down, nanoLC-nanoESI+-MS, CETSA, immunoblot and SPR assay. The RAW264.7Clec4G-RFP and RAW264.7Rab1A-RFP cell lines were simultaneously constructed to determine the affinity difference between AELP-B6 and targets by confocal laser scanning live-cell imaging. Antibody blocking assays were further used to verify the mechanism of hormetic effects. RESULTS: AELP-B6 at low and medium doses may maintain the structural integrity of thymus and spleen, increase the concentrations of TNF-α, IFN-γ, IL-3 and IL-8, and alleviate CTX-induced reduction of immune cell viability in vivo. Proteomics and energy metabolism analysis revealed that AELP-B6 regulate HIF-1α-mediated metabolic programming, causing Warburg effects in macrophages. AELP-B6 at low and medium doses promoted the release of intracellular immune factors, and driving M1-like polarization of macrophages. As a contrast, AELP-B6 at high dose enhanced the expression levels of apoptosis related proteins, indicating activation of the intrinsic apoptotic cascade. Two highly expressed transmembrane proteins in macrophages, Clec4G and Rab1A, were identified as the primary binding targets of AELP-B6 which co-localized with the cell membrane and directly impacted with immune cell activation and apoptosis. AELP-B6 exhibits affinity differences with Clec4G and Rab1A, which is the key to the hormetic effects. CONCLUSION: We observed hormesis of natural polysaccharide (AELP-B6) for the first time, and AELP-B6 mediates the hormetic effects through two dose-related targets. Low dose of AELP-B6 targets Clec4G, thereby driving the M1-like polarization via regulating NF-κB signaling pathway and HIF-1α-mediated metabolic programming, whereas high dose of AELP-B6 targets Rab1A, leading to mitochondria-dependent apoptosis.

CADS: A Self-supervised Learner via Cross-modal Alignment and Deep Self-distillation for CT Volume Segmentation.

Self-supervised learning (SSL) has long had great success in advancing the field of annotation-efficient learning. However, when applied to CT volume segmentation, most SSL methods suffer from two limitations, including rarely using the information acquired by different imaging modalities and providing supervision only to the bottleneck encoder layer. To address both limitations, we design a pretext task to align the information in each 3D CT volume and the corresponding 2D generated X-ray image and extend self-distillation to deep self-distillation. Thus, we propose a self-supervised learner based on Cross-modal Alignment and Deep Self-distillation (CADS) to improve the encoder's ability to characterize CT volumes. The cross-modal alignment is a more challenging pretext task that forces the encoder to learn better image representation ability. Deep self-distillation provides supervision to not only the bottleneck layer but also shallow layers, thus boosting the abilities of both. Comparative experiments show that, during pre-training, our CADS has lower computational complexity and GPU memory cost than competing SSL methods. Based on the pre-trained encoder, we construct PVT-UNet for 3D CT volume segmentation. Our results on seven downstream tasks indicate that PVT-UNet outperforms state-of-the-art SSL methods like MOCOv3 and DiRA, as well as prevalent medical image segmentation methods like nnUNet and CoTr. Code and pre-trained weight will be available at https://github.com/yeerwen/CADS.

Single cell analyses reveal the PD-1 blockade response-related immune features in hepatocellular carcinoma.

Background: Immunotherapy has demonstrated its potential to improve the prognosis of patients with hepatocellular carcinoma (HCC); however, patients' responses to immunotherapy vary a lot. A comparative analysis of the tumor microenvironment (TME) in responders and non-responders is expected to unveil the mechanisms responsible for the immunotherapy resistance and provide potential treatment targets. Methods: We performed sequencing analyses using 10x Genomics technology on six HCC patients who responded to anti-PD-1 therapy and one HCC patient who did not respond. Additionally, we obtained single cell data from untreated, responsive, and nonresponsive HCC patients from public databases, and used part of the datasets as a validation cohort. These data were integrated using algorithms such as Harmony. An independent validation cohort was established. Furthermore, we performed spatial transcriptomic sequencing on the tumor adjacent tissues of three HCC responsive patients using 10x Genomics spatial transcriptomic technology. Additionally, we analyzed data about three HCC patients obtained from public databases. Finally, we validated our conclusions using immunofluorescence, flow cytometry, and in vivo experiments. Results: Our findings confirmed the presence of "immune barrier" partially accounting for the limited efficacy of immunotherapy. Our analysis revealed a significant increase in TREM2+ Macrophages among non-responsive patients expressing multiple immunosuppressive signals. anti-Csf1r monoclonal antibodies effectively eliminated these macrophages and augmented the therapeutic effects of anti-PD-1 therapy. TCR+ Macrophages possessed direct tumor-killing capabilities. IL1B+ cDC2 was the primary functional subtype of cDC2 cells. Absence of THEMIShi CD8+ T subtypes might diminish immunotherapeutic effects. Furthermore, CD8+ T cells entered a state of stress after anti-PD-1 treatment, which might be associated with CD8+ T cell exhaustion and senescence. Conclusions: The profiles of immune TMEs showed differences in HCC patients responsive, non-responsive and untreated. These differences might explain the discounted efficacy of immunotherapy in some HCC patients. The cells and molecules, which we found to carry unique capabilities, may be targeted to enhance immunotherapeutic outcomes in patients with HCC.

Novel genetic alterations in liver cancer distinguish distinct clinical outcomes and combination immunotherapy responses.

Introduction: Genomic profiling has revolutionized therapeutic interventions and the clinical management of liver cancer. However, pathogenetic mechanisms, molecular determinants of recurrence, and predictive biomarkers for first-line treatment (anti-PD-(L)1 plus bevacizumab) in liver cancer remain incompletely understood. Materials and methods: Targeted next-generation sequencing (tNGS) (a 603-cancer-gene panel) was applied for the genomic profiling of 232 hepatocellular carcinoma (HCC) and 22 intrahepatic cholangiocarcinoma (ICC) patients, among which 47 unresectable/metastatic HCC patients underwent anti-PD-1 plus bevacizumab therapy. Genomic alterations were estimated for their association with vascular invasion (VI), location of onset, recurrence, overall survival (OS), recurrence-free survival (RFS), and anti-PD-1 plus bevacizumab therapy response. Results: The genomic landscape exhibited that the most commonly altered genes in HCC were TP53, FAT3, PDE4DIP, KMT2C, FAT1, and MYO18A, while TP53, FAT1, FAT3, PDE4DIP, ROS1, and GALNT11 were frequently altered in ICC; notably, KRAS (18.18% vs. 1.29%) and BAP1 (13.64% vs. 1.29%) alterations were significantly more prevalent in ICC. Comparison analysis demonstrated the distinct clinicopathological/genomic characterizations between Chinese and Western HCC cohorts. Genomic profiling of HCC underlying VI showed that LDLR, MSH2, KDM5D, PDE3A, and FOXO1 were frequently altered in the VI group compared to patients without VIs. Compared to the right hepatic lobes of HCC patients, the left hepatic lobe of HCC patients had superior OS (median OS: 36.77 months vs. unreached, p < 0.05). By further comparison, Notch signaling pathway-related alterations were significantly prevalent among the right hepatic lobes of HCC patients. Of note, multivariate Cox regression analysis showed that altered RB1, NOTCH3, MGA, SYNE1, and ZFHX3, as independent prognostic factors, were significantly correlated with the OS of HCC patients. Furthermore, altered LATS1 was abundantly enriched in the HCC-recurrent group, and impressively, it was independent of clinicopathological features in predicting RFS (median RFS of altered type vs. wild-type: 5.57 months vs. 22.47 months, p < 0.01). Regarding those treated HCC patients, TMB value, altered PTPRZ1, and cell cycle-related alterations were identified to be positively associated with the objective response rate (ORR), but KMT2D alterations were negatively correlated with ORR. In addition, altered KMT2D and cell cycle signaling were significantly associated with reduced and increased time to progression-free survival (PFS), respectively. Conclusion: Comprehensive genomic profiling deciphered distinct molecular characterizations underlying VI, location of onset, recurrence, and survival time in liver cancer. The identification of novel genetic predictors of response to anti-PD-1 plus bevacizumab in HCC facilitated the development of an evidence-based approach to therapy.

Structural elucidation a complex galactosyl and glucosyl-rich pectin from the pericarp of immature fruits of Juglans mandshurica Maxim.

A glucosyl-rich pectin, JMMP-3 (Mw, 2.572 × 104 g/mol, O-methyl % = 3.62%), was isolated and purified from the pericarp of the immature fruit of Juglans mandshurica Maxim. (QingLongYi). The structure of JMMP-3 was studied systematically by infrared spectroscopy, monosaccharide compositions, methylation analysis, partial acid hydrolysis, and 1/2D-NMR. The backbone of JMMP-3 possessed a smooth region (→ 4GalA1 →) and a hairy region (→ 4GalA1 → 2Rha1 →) with a molar ratio of 2: 5. The substitution of four characteristic side chains (R1-R4) occurs at C-4 of → 2,4)-α-Rhap-(1→, where R1 is composed of → 5)-α-Araf-(1→, R2 is composed of → 4)-ß-Galp-(1 → and ß-Galp-(1→, R3 is composed of α-Glcp-(1→, →4)-α-Glcp-(1 → and → 4,6)-α-Glcp-(1→, and R4 is composed of → 5)-α-Araf-(1→, ß-Galp-(1→, → 4)-ß-Galp-(1→, → 3,4)-ß-Galp-(1→, → 4,6)-ß-Galp-(1 → and → 2,4)-ß-Galp-(1 → . In addition, the antitumor activity of JMMP-3 on HepG2 cells was preliminarily investigated.

UniMiSS+: Universal Medical Self-Supervised Learning From Cross-Dimensional Unpaired Data.

Self-supervised learning (SSL) opens up huge opportunities for medical image analysis that is well known for its lack of annotations. However, aggregating massive (unlabeled) 3D medical images like computerized tomography (CT) remains challenging due to its high imaging cost and privacy restrictions. In our pilot study, we advocated bringing a wealth of 2D images like chest X-rays as compensation for the lack of 3D data, aiming to build a universal medical self-supervised representation learning framework, called UniMiSS. Especially, we designed a pyramid U- like medical Transformer (MiT) as the backbone to make UniMiSS possible to perform SSL with both 2D and 3D images. Consequently, the predecessor UniMiSS has two obvious merits compared to current 3D-specific SSL: (1) more effective - superior to learning strong representations, benefiting from more and diverse data; and (2) more versatile - suitable for various downstream tasks without the restriction on the dimensionality barrier. Unfortunately, UniMiSS did not dig deeply into the intrinsic anatomy correlation between 2D medical images and 3D volumes due to the lack of paired multi-modal/dimension patient data. In this extension paper, we propose the UniMiSS+, in which we introduce the digitally reconstructed radiographs (DRR) technology to simulate X-ray images from a CT volume to access paired CT and X-ray data. Benefiting from the paired group, we introduce an extra pair- wise constraint to boost the cross-modality correlation learning, which also can be adopted as a cross-dimension regularization to further improve the representations. We conduct expensive experiments on multiple 3D/2D medical image analysis tasks, including segmentation and classification. The results show that the proposed UniMiSS+ achieves promising performance on various downstream tasks, not only outperforming the ImageNet pre-training and other advanced SSL counterparts substantially but also improving the predecessor UniMiSS pre-training. Code is available at: https://github.com/YtongXie/UniMiSS-code.

Asymmetric Construction of Functionalized Cyclopenta[b]pyrrolines via Cascade Aza-Piancatelli/Hydroamination Reactions.

A chiral Brønsted acid/Pd that cooperatively catalyzed the asymmetric cascade aza-Piancatelli rearrangement/hydroamination of readily accessible alkynyl-functionalized tertiary furylcarbinols with anilines has been developed. This protocol provides expedient access to a variety of densely functionalized cyclopenta[b]pyrroline derivatives in high yields with excellent enantioselectivities.

A Reverse Thinking Based on Partially Methylated Aldononitrile Acetates to Analyze Glycoside Linkages of Polysaccharides Using Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry.

Glycoside linkage analyses of medicine and food homologous plant polysaccharides have always been a key point and a difficulty of structural characterization. The gas chromatography-mass spectrometry (GC-MS) method is one of the commonly used traditional techniques to determine glycoside linkages via partially methylated alditol acetates and aldononitrile acetates (PMAAs and PMANs). Due to the simplicity of derivatization and the highly structural asymmetry of PMANs, reverse thinking is proposed using liquid chromatography-electrospray ionization-multiple reaction monitoring mass spectrometry (LC-ESI-MRM-MS) for the first time to directly determine the neutral and acidic glycosyl linkages of polysaccharides. The complete characterization of glycoside linkages deduced from PMANs was achieved using a combination of tR values, characteristic MRM ion pairs, diagnostic ESI+-MS/MS fragmentation ions (DFIs), and optimal collision energy (OCE). The DFI and OCE parameters were confirmed to be effective for the auxiliary discrimination of some isomers of the PMANs. The practicality of LC-ESI+-MRM-MS was further verified by analyzing the glycoside linkages of polysaccharides in five medicine and food homologous plants. This method can serve as an alternative to GC-MS for the simultaneous determination of neutral and acidic glycosyl linkages in polysaccharides.

Fluorescent Materials Based on Spiropyran for Advanced Anti-Counterfeiting and Information Encryption.

In daily life, counterfeit and substandard products, particularly currency, medicine, food, and confidential documents, are capable of bringing about very serious consequences. The development of anti-counterfeiting and authentication technologies with multilevel securities is a powerful means to overcome this challenge. Among various anti-counterfeiting technologies, fluorescent anti-counterfeiting technology is well-known and commonly used to fight counterfeiters due to its wide material source, low cost, simple usage, good concealment, and simple response mechanism. Spiropyran is favored by scientists in the fields of anti-counterfeiting and information encryption due to its reversible photochromic property. Here, we summarize the current available spiropyran-based fluorescent materials from design to anti-counterfeiting applications. This review will be help scientists to design and develop fluorescent anti-counterfeiting materials with high security, high performance, quick response, and high anti-counterfeiting level.

Fluoxetine as a Potential Therapeutic Agent for Inhibiting Melanoma Brain and Lung Metastasis: Induction of Apoptosis, G0/G1 Cell Cycle Arrest, and Disruption of Autophagy Flux.

Brain metastases and lung metastases are major causes of treatment failure and related mortality in melanoma. Fluoxetine hydrochloride (FXT), a widely-used antidepressant, has emerged as a potential anticancer agent in preclinical studies. Previous research has shown its potential to inhibit melanoma. However, its efficacy and the underlying mechanisms in melanoma metastasis, especially concerning brain metastases and lung metastases, remain underexplored. This study investigates FXT's inhibitory effects on melanoma growth and metastasis to the lung and brain. Employing a combination of in vitro assays, we demonstrate FXT's potent suppression of melanoma growth through induction of intrinsic apoptosis, disruption of autophagic flux, and cell cycle arrest at the G0/G1 phase. In in vivo mouse models, we found that FXT exhibits strong inhibitory activity against melanoma brain metastases and lung metastases. Our findings provide a foundation for future clinical exploration of FXT as a novel treatment strategy for melanoma, underscoring its ability to target both primary and metastatic lesions.

Exploratory Training for Universal Lesion Detection: Enhancing Lesion Mining Quality Through Temporal Verification.

Universal lesion detection (ULD) has great value in clinical practice as it can detect various lesions across multiple organs. Deep learning-based detectors have great potential but require high-quality annotated training data. In practice, due to cost, expertise requirements, and the diverse nature of lesions, incomplete annotations are often encountered. Directly training ULD detectors under this condition can yield suboptimal results. Leading pseudo-label methods rely on a dynamic lesion-mining mechanism operating at the mini-batch level to address the issue of incomplete annotations. However, the quality of mined lesions in this approach is inconsistent across different iterations, potentially limiting performance enhancement. Inspired by the observation that deep models learn concepts with increasing complexity, we propose an innovative exploratory-training-based ULD (ET-ULD) method to assess the reliability of mined lesions over time. Specifically, we employ a teacher-student detection model, the teacher model is used to mine suspicious lesions, which are combined with incomplete annotations to train the student model. On top of that, we design a bounding-box bank to record the mining timestamps. Each image is trained in several rounds, allowing us to get a sequence of timestamps for the mined lesions. If a mined lesion consistently appears in the timestamp sequence, it is likely to be a true lesion, otherwise, it may just be a noise. This serves as a crucial criterion for selecting reliable mined lesions for subsequent retraining. Our experimental results confirm the effectiveness of ET-ULD, showcasing its ability to surpass existing state-of-the-art methods on two distinct lesion image datasets. Notably, on the DeepLesion dataset, ET-ULD achieved a significant enhancement, outperforming the previous leading method by 5.4% in Average Precision (AP), thus demonstrating its superior performance.

TriLA: Triple-Level Alignment based Unsupervised Domain Adaptation for Joint Segmentation of Optic Disc and Optic Cup.

Cross-domain joint segmentation of optic disc and optic cup on fundus images is essential, yet challenging, for effective glaucoma screening. Although many unsupervised domain adaptation (UDA) methods have been proposed, these methods can hardly achieve complete domain alignment, leading to suboptimal performance. In this paper, we propose a triple-level alignment (TriLA) model to address this issue by aligning the source and target domains at the input level, feature level, and output level simultaneously. At the input level, a learnable Fourier domain adaptation (LFDA) module is developed to learn the cut-off frequency adaptively for frequency-domain translation. At the feature level, we disentangle the style and content features and align them in the corresponding feature spaces using consistency constraints. At the output level, we design a segmentation consistency constraint to emphasize the segmentation consistency across domains. The proposed model is trained on the RIGA+ dataset and widely evaluated on six different UDA scenarios. Our comprehensive results not only demonstrate that the proposed TriLA substantially outperforms other state-of-the-art UDA methods in joint segmentation of optic disc and optic cup, but also suggest the effectiveness of the triple-level alignment strategy.

Differentiation and immunosuppressive function of CD19+CD24hiCD27+ regulatory B cells are regulated through the miR-29a-3p/NFAT5 pathway.

BACKGROUND: Regulatory B cells (Bregs) is an indispensable element in inducing immune tolerance after liver transplantation. As one of the microRNAs (miRNAs), miR-29a-3p also inhibits translation by degrading the target mRNA, and yet the relationship between Bregs and miR-29a-3p has not yet been fully explored. This study aimed to investigate the impact of miR-29a-3p on the regulation of differentiation and immunosuppressive functions of memory Bregs (mBregs) and ultimately provide potentially effective therapies in inducing immune tolerance after liver transplantation. METHODS: Flow cytometry was employed to determine the levels of Bregs in peripheral blood mononuclear cells. TaqMan low-density array miRNA assays were used to identify the expression of different miRNAs, electroporation transfection was used to induce miR-29a-3p overexpression and knockdown, and dual luciferase reporter assay was used to verify the target gene of miR-29a-3p. RESULTS: In patients experiencing acute rejection after liver transplantation, the proportions and immunosuppressive function of mBregs in the circulating blood were significantly impaired. miR-29a-3p was found to be a regulator of mBregs differentiation. Inhibition of miR-29a-3p, which targeted nuclear factor of activated T cells 5 (NFAT5), resulted in a conspicuous boost in the differentiation and immunosuppressive function of mBregs. The inhibition of miR-29a-3p in CD19+ B cells was capable of raising the expression levels of NFAT5, thereby promoting B cells to differentiate into mBregs. In addition, the observed enhancement of differentiation and immunosuppressive function of mBregs upon miR-29a-3p inhibition was abolished by the knockdown of NFAT5 in B cells. CONCLUSIONS: miR-29a-3p was found to be a crucial regulator for mBregs differentiation and immunosuppressive function. Silencing miR-29a-3p could be a potentially effective therapeutic strategy for inducing immune tolerance after liver transplantation.

Neutrophil-to-lymphocyte ratio in colorectal tissue affects prognosis in patients with colorectal cancer.

The objective of this investigation was to analyse the correlation between the neutrophil-to-lymphocyte ratio (NLR) status in the immune microenvironment (IME) and the prognostic outcomes of patients who have undergone radical surgery for colorectal cancer (CRC). In light of the continued prevalence of CRC in China, this study utilised Kaplan-Meier and Cox regression analyses to assess the prognostic relevance of NLR status in IME among patients with CRC. Furthermore, cellular experiments, such as cell scratching, were conducted to elucidate the underlying mechanisms of NLR's impact on CRC. The NLR status in IME has been found to have a significant impact on the prognosis of patients with CRC. Patients who exhibit elevated intratumoural and extratumoural NLR are associated with a poor prognosis. Experimental evidence indicates that tumour-associated neutrophil (TAN) augments the migratory, invasive, and proliferative potential of HT-29, HCT-116 and LOVO colorectal cancer cells, while concurrently reducing their sensitivity to oxaliplatin. Conversely, lymphocytes have demonstrated cytotoxic effects on HT-29 cells. The NLR status in IME may serve as a prognostic biomarker for resectable CRC.

Impact of Preoperative Neutrophil to Prealbumin Ratio Index (NPRI) on Short-Term Complications and Long-Term Prognosis in Patients Undergoing Laparoscopic Radical Surgery for Colorectal Cancer.

Objective: This study aims to evaluate the impact and predictive value of the preoperative NPRI on short-term complications and long-term prognosis in patients undergoing laparoscopic radical surgery for colorectal cCancer (CRC). Methods: A total of 302 eligible CRC patients were included, assessing five inflammation-and nutrition-related markers and various clinical features for their predictive impact on postoperative outcomes. Emphasis was on the novel indicator NPRI to elucidate its prognostic and predictive value for perioperative risks. Results: Multivariate logistic regression analysis identified a history of abdominal surgery, prolonged surgical duration, CEA levels ≥5 ng/mL, and NPRI ≥ 3.94 × 10-2 as independent risk factors for postoperative complications in CRC patients. The Clavien--Dindo complication grading system highlighted the close association between preoperative NPRI and both common and severe complications. Multivariate analysis also identified a history of abdominal surgery, tumor diameter ≥5 cm, poorly differentiated or undifferentiated tumors, and NPRI ≥ 2.87 × 10-2 as independent risk factors for shortened overall survival (OS). Additionally, a history of abdominal surgery, tumor maximum diameter ≥5 cm, tumor differentiation as poor/undifferentiated, NPRI ≥ 2.87 × 10-2, and TNM Stage III were determined as independent risk factors for shortened disease-free survival (DFS). Survival curve results showed significantly higher 5-year OS and DFS in the low NPRI group compared to the high NPRI group. The incorporation of NPRI into nomograms for OS and DFS, validated through calibration and decision curve analyses, attested to the excellent accuracy and practicality of these models. Conclusion: Preoperative NPRI independently predicts short-term complications and long-term prognosis in patients undergoing laparoscopic colorectal cancer surgery, enhancing predictive accuracy when incorporated into nomograms for patient survival.

Compound heterozygous with Hb G-Taipei and Hb Lepore-Boston-Washington: An unexpected finding triggered by HbA1c measurement.

Background: Hemoglobin A1c has been widely used to diagnose and monitor diabetes. However, the accuracy of HbA1c analysis can be significantly affected by hemoglobin variants, leading to falsely low or elevated levels and misdiagnosis or inappropriate diabetes management. Case report: In this study, we present the case of a 23-year-old man with undetectable HbA1c levels during his annual checkup by high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE). To investigate the reason for HbA1c absence, Sanger sequencing, multiplex ligation-dependent probe amplification assay (MLPA), long-read single molecule real-time sequencing (SMRT) and MALDI-TOF mass spectrometry (MS) were performed, and the proband was identified as compound heterozygous of ß-thalassemia with Hb G-Taipei (HBB:c.68A > G) and Hb Lepore-Boston-Washington (NG_000007.3:g.63632_71046del). Conclusion: The combination of these molecular technologies including MLPA, long-read SMRT sequencing and MALDI-TOF MS is beneficial for identifying rare hemoglobin variants. This case also provides essential evidence for uncovering the effect of compound heterozygosity for Hb Lepore-Boston-Washington and Hb G-Taipei on hematological phenotypes and HbA1c analysis.

The Influence of Exercise on Cancer Risk, the Tumor Microenvironment and the Treatment of Cancer.

There are several modifiable factors that can be targeted to prevent and manage the occurrence and progression of cancer, and maintaining adequate exercise is a crucial one. Regular physical exercise has been shown to be a beneficial strategy in preventing cancer, potentially amplifying the effectiveness of established cancer therapies, alleviating certain cancer-related symptoms, and possibly mitigating side effects resulting from treatment. Nevertheless, the exact mechanisms by which exercise affects tumors, especially its impact on the tumor microenvironment (TME), remain uncertain. This review aims to present an overview of the beneficial effects of exercise in the context of cancer management, followed by a summary of the exercise parameters, especially exercise intensity, that need to be considered when prescribing exercise for cancer patients. Finally, we discuss the influence of exercise on the TME, including its effects on crucial immune cells (e.g., T cells, macrophages, neutrophils, natural killer cells, myeloid-derived suppressor cells, B cells), intratumor angiogenesis, and cancer metabolism. This comprehensive review provides up-to-date scientific evidence on the effects of exercise training on cancer and offers guidance to clinicians for the development of safe and feasible exercise training programs for cancer patients in clinical practice.

A case report of a patient with Turner syndrome who develops catatonia secondary to psychotic symptoms.

RATIONALE: Turner syndrome (TS) is a genetic disorder associated with partial or complete monosomy X abnormalities; some patients may have a higher risk of psychiatric symptoms. Catatonia is associated with a wide range of life-threatening complications with complex pathogenesis; However, It very rare for patients with TS to develop psychotic symptoms and eventually progress to catatonia. This case report describes the diagnostic and therapeutic course of catatonia-associated TS. PATIENT CONCERNS: In this study, we report the case of a patient with TS who initially developed sudden hallucinations, delusions, and emotional instability, followed by catatonia. DIAGNOSES: The patient was diagnosed with: unspecified catatonia; TS. INTERVENTIONS: Treatment included administering a combination of esazolam injections and olanzapine tablets, placing a gastric tube and urinary catheter, and providing nutritional support. OUTCOMES: After treatment, the patient's hallucinations, delusions, and catatonia disappeared, with no residual sequelae, and social functioning returned to normal. LESSONS: For patients with TS who present with psychotic symptoms and catatonia, a comprehensive evaluation is necessary, and treatment with antipsychotics and benzodiazepines is effective.