Histopathology is the gold standard in cancer diagnosis. However, attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy has shown diagnostic potential in other settings. Therefore, this study aimed to investigate the sensitivity and specificity of the ATR-FTIR spectroscopy in evaluating breast lesions.

This study was conducted on formalin-fixed, paraffin-embedded biopsy blocks received at Ladoke Akintola University of Technology Teaching Hospital between 2022 and 2023. The blocks were categorized into 10 normal (from benign breast tissue), 15 benign, and 31 malignant samples. Tissue sections of 15 µm were obtained during block trimming and floated onto FTIR slides. An additional 4 µm tissue sections were stained with hematoxylin and eosin for tumor diagnosis and to identify suitable areas on the FTIR slide. Spectrometer readings were taken within the range of 4,000–600 cm−1, 32 scans, and 16 cm−1 resolution, using the average of 10 preprocessed spectra per slide. Biomarkers were calculated by ratioing peak intensities for A1632/A1543, A1632/A2922, A1632/A1080, A1080/A1543, A1237/A1080, and A1043/A1543, which represent protein, diagnostic marker, cytoplasm-nucleus ratio, carcinogenesis marker, phosphate, and glycogen, respectively. The receiver operating characteristic curve was used to determine sensitivity, specificity, and the area under the curve (AUC).

The AUC analysis showed that cytoplasm-nucleus ratio values of 0.99 and 0.95 effectively distinguished normal from malignant tissue, and benign from malignant tissue, respectively (p < 0.0001). Additionally, protein marker (AUC = 0.73), diagnostic marker (AUC = 0.85), and cytoplasm-nucleus ratio marker (AUC = 0.94) were able to discriminate normal from benign tissue. Overall, the receiver operating characteristic analysis showed 100% sensitivity and specificity ranging from 54% to 87%. Glycogen (AUC = 1.00) exhibited 100% sensitivity in discriminating fibroadenoma from fibrocystic changes.

ATR-FTIR spectroscopy demonstrates high diagnostic accuracy in differentiating normal, benign, and malignant breast tissues using specific spectral biomarkers. Among these, the cytoplasm-nucleus ratio marker showed strong potential as a reliable spectral indicator for distinguishing various types of breast tumors. The cytoplasm-nucleus ratio marker demonstrated strong potential as a reliable spectral indicator for distinguishing various types of breast tumors.

Shenqi Fuzheng (SQ) is a widely used Chinese medicine formula known for its immune-enhancing and Qi-supplementing properties. However, the blood-absorbed components of SQ and their pharmacokinetics remain underexplored. This study aimed to comprehensively analyze the chemical constituents of SQ and investigate their absorption and pharmacokinetic behavior in rat plasma.

Ultra-performance liquid chromatography-triple quadrupole time-of-flight mass spectrometry (hereinafter referred to as UPLC-Triple-TOF/MS) is employed to identify the chemical components in SQ extract and quantify the components absorbed into the blood after oral administration in rats. This method provides fragmentation patterns of compounds and key pharmacokinetic profiles of blood-absorbed compounds.

A total of 105 compounds are identified from the SQ extract, and 40 are detected in the blood following oral administration. Organic acids and amino acids are found at higher concentrations in the bloodstream. Compounds such as Astragalosides promptly enter the bloodstream within 5 m after administration, with levels declining after 15 m. Flavonoids are absorbed within 15–30 m, and the peak of alkaloids occurs approximately 1 h after administration.

This study provides new insights into the chemical composition and pharmacokinetics of SQ, highlighting the dynamic changes in the content of absorbed compounds in the blood. It further promotes the comprehensive characterization of traditional Chinese medicine formulations through UPLC-Triple-TOF/MS. Future research should focus on elucidating the pharmacological activities of the identified compounds and investigating their potential synergistic effects within the formulation.

Ectopic or heterotopic pancreases are normal pancreatic tissues located outside the pancreas. The ectopic pancreas has its own vascular and ductal systems and does not communicate with the normal pancreas. The prevalence of ectopic pancreas ranges from 0.6% to 15% among all autopsies. Many types of tumors, including intraductal papillary mucinous neoplasms (IPMNs), have been reported in the ectopic pancreas. However, little is known about the synchronous occurrence of IPMNs in both ectopic and orthotopic pancreas. In this study, we report, for the first time, two cases of concurrent IPMNs in an ectopic pancreas and an orthotopic pancreas. One patient had IPMNs both in the pancreas and in ectopic pancreatic tissue in the jejunum. Another patient had IPMNs in both the pancreas and ectopic pancreatic tissue in the duodenum. These cases may provide valuable insights into the etiological factors of IPMNs.

The incidence of early-onset pancreatic cancer (EOPC) is rising, yet optimal treatment strategies remain unclear. While adjuvant chemotherapy (ACT) has shown survival benefits in pancreatic ductal adenocarcinoma, its specific role in EOPC patients following neoadjuvant chemotherapy (NACT) and surgery remains underexplored. This study aimed to assess the clinical benefit of ACT in EOPC patients after NACT.

This retrospective cohort study analyzed pancreatic ductal adenocarcinoma patients from the SEER database (2006–2019) who received NACT followed by curative resection. Propensity score matching (1:1) was used to balance covariates such as tumor, lymph node, metastasis stage, chemotherapy, and radiotherapy. Overall survival (OS) and cancer-specific survival (CSS) were compared between patients with EOPC (<50 years) and average-onset pancreatic cancer (AOPC, ≥50 years). Multivariate Cox regression analysis was performed to identify prognostic factors.

After propensity score matching (124 EOPC vs. 124 AOPC), EOPC patients had significantly longer median OS (41.0 vs. 29.0 months, P = 0.042) and CSS (48.0 vs. 30.0 months, P = 0.016). ACT was an independent prognostic factor for EOPC (OS: hazard ratio = 0.495, 95% confidence interval 0.271–0.903, P = 0.022; CSS: hazard ratio = 0.419, 95% confidence interval 0.219–0.803, P = 0.009), but not for AOPC (P > 0.05). Subgroup analysis revealed that EOPC patients with tumor, lymph node, metastasis stage II disease or those receiving ACT derived the greatest survival benefit.

EOPC patients exhibit superior survival following NACT and surgical resection compared to AOPC, with ACT further enhancing outcomes in this subgroup. These findings support the use of tailored ACT for EOPC and underscore the need for prospective validation.

High-grade endometrial carcinoma (HGEC) is an aggressive tumor with increasing incidence and mortality. Traditional classifications, such as Bokhman’s dualistic model and the World Health Organization histopathological system, have limitations due to tumor heterogeneity and interobserver variability. This review provides a comprehensive understanding of how integrating histopathological and molecular data, particularly The Cancer Genome Atlas (TCGA) classification, advances risk stratification and personalized treatment in HGEC. It highlights current challenges and identifies future directions to improve diagnostic accuracy and patient outcomes through precision medicine.

A literature review was conducted focusing on the epidemiology, histopathology, and molecular profiling of HGEC, with an emphasis on TCGA and next-generation sequencing studies.

TCGA molecular classification stratifies HGEC into four subgroups with distinct prognoses which includes POLE-ultramutated (POLE), microsatellite instability hypermutated, copy number high and copy number low. The next-generation sequencing enhances diagnostic precision and guides personalized treatment. However, diagnostic challenges persist in clinical practice.

Integrating histopathology with TCGA-based molecular profiling refines HGEC classification, enabling improved risk stratification and targeted therapies. Continued efforts to improve diagnostic accuracy are essential to advance patient care.